pandasai.log

2024-10-08 17:40:33 [INFO] Question: how many rows are there in the table?
2024-10-08 17:40:33 [INFO] Running PandasAI with local LLM...
2024-10-08 17:40:33 [INFO] Prompt ID: c12b7bcb-1bda-445a-b868-ac6cd86c026f
2024-10-08 17:40:33 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 17:40:33 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 17:40:33 [INFO] Executing Step 1: CacheLookup
2024-10-08 17:40:33 [INFO] Executing Step 2: PromptGeneration
2024-10-08 17:40:33 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,male,65.0,8,5,211.5,S,First,woman,False,C,Cherbourg,no,False
0,2,female,59.0,5,2,15.2458,,Third,child,True,,Queenstown,no,True
1,1,male,,1,1,14.0,Q,Second,man,True,B,,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are there in the table?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 17:40:33 [INFO] Executing Step 3: CodeGenerator
2024-10-08 17:41:44 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:41:44 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,male,65.0,8,5,211.5,S,First,woman,False,C,Cherbourg,no,False
0,2,female,59.0,5,2,15.2458,,Third,child,True,,Queenstown,no,True
1,1,male,,1,1,14.0,Q,Second,man,True,B,,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are there in the table?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 17:41:44 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Import 'matplotlib' for plotting if requested.
import matplotlib.pyplot as plt

# Initialize result variable with empty dictionary.
result = {"type": "", "value": ""}

# Iterate over each DataFrame in the list.
for df in dfs:
    # Print number of rows in the current DataFrame.
    num_rows = len(df)
    print(f"There are {num_rows} rows in this table.")

    # Update result variable for first (and only) DataFrame.
    if not result["type"]:
        result = {"type": "number", "value": num_rows}

# Print result.
print(result)
            ```
            
2024-10-08 17:41:44 [INFO] Executing Step 4: CachePopulation
2024-10-08 17:41:44 [INFO] Executing Step 5: CodeCleaning
2024-10-08 17:41:44 [INFO] 
Code running:
```
result = {'type': '', 'value': ''}
for df in dfs:
    num_rows = len(df)
    print(f'There are {num_rows} rows in this table.')
    if not result['type']:
        result = {'type': 'number', 'value': num_rows}
print(result)
        ```
2024-10-08 17:41:44 [INFO] Executing Step 6: CodeExecution
2024-10-08 17:41:44 [INFO] Executing Step 7: ResultValidation
2024-10-08 17:41:44 [INFO] Answer: {'type': 'number', 'value': 891}
2024-10-08 17:41:44 [INFO] Executing Step 8: ResultParsing
2024-10-08 17:43:53 [INFO] Question: how many males are above 25 years old?
2024-10-08 17:43:53 [INFO] Running PandasAI with local LLM...
2024-10-08 17:43:53 [INFO] Prompt ID: 090588e5-c9c0-4efc-a17c-afc3d87bc7ee
2024-10-08 17:43:53 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 17:43:53 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 17:43:53 [INFO] Executing Step 1: CacheLookup
2024-10-08 17:43:53 [INFO] Executing Step 2: PromptGeneration
2024-10-08 17:43:53 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males are above 25 years old?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 17:43:53 [INFO] Executing Step 3: CodeGenerator
2024-10-08 17:44:58 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:44:58 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males are above 25 years old?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 17:44:58 [INFO] Code generated:
            ```
            # Import the required dependencies
import pandas as pd

# Initialize an empty list to store DataFrames
dfs = []

# Initialize the result variable
result = {}

# Write code here
for i in range(len(dfs)):
    # Summarize your logic
    males_above_25 = dfs[i].loc[dfs[i]['sex'] == 'male', 'age'].gt(25).sum()
    
    result["type"] = "number"
    result["value"] = males_above_25

print(result)
            ```
            
2024-10-08 17:44:58 [INFO] Executing Step 4: CachePopulation
2024-10-08 17:44:58 [INFO] Executing Step 5: CodeCleaning
2024-10-08 17:44:58 [INFO] 
Code running:
```
result = {}
for i in range(len(dfs)):
    males_above_25 = dfs[i].loc[dfs[i]['sex'] == 'male', 'age'].gt(25).sum()
    result['type'] = 'number'
    result['value'] = males_above_25
print(result)
        ```
2024-10-08 17:44:58 [INFO] Executing Step 6: CodeExecution
2024-10-08 17:44:58 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 3, in <module>
AttributeError: 'NoneType' object has no attribute 'loc'

2024-10-08 17:44:58 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-08 17:44:58 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:44:58 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:44:58 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
for i in range(len(dfs)):
    males_above_25 = dfs[i].loc[dfs[i]['sex'] == 'male', 'age'].gt(25).sum()
    result['type'] = 'number'
    result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 3, in <module>
AttributeError: 'NoneType' object has no attribute 'loc'


Fix the python code above and return the new python code:
2024-10-08 17:44:58 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:45:40 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:45:40 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
for i in range(len(dfs)):
    males_above_25 = dfs[i].loc[dfs[i]['sex'] == 'male', 'age'].gt(25).sum()
    result['type'] = 'number'
    result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 3, in <module>
AttributeError: 'NoneType' object has no attribute 'loc'


Fix the python code above and return the new python code:
            
2024-10-08 17:45:40 [INFO] Code generated:
            ```
            result = {}
males_above_25 = dfs.loc[dfs['sex'] == 'male', 'age'].gt(25).sum()
result['type'] = 'number'
result['value'] = males_above_25
print(result)
            ```
            
2024-10-08 17:45:40 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:45:40 [INFO] 
Code running:
```
result = {}
males_above_25 = dfs.loc[dfs['sex'] == 'male', 'age'].gt(25).sum()
result['type'] = 'number'
result['value'] = males_above_25
print(result)
        ```
2024-10-08 17:45:40 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'

2024-10-08 17:45:40 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-10-08 17:45:40 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:45:40 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:45:40 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
males_above_25 = dfs.loc[dfs['sex'] == 'male', 'age'].gt(25).sum()
result['type'] = 'number'
result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
2024-10-08 17:45:40 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:46:22 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:46:22 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
males_above_25 = dfs.loc[dfs['sex'] == 'male', 'age'].gt(25).sum()
result['type'] = 'number'
result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
            
2024-10-08 17:46:22 [INFO] Code generated:
            ```
            result = {}
males_above_25 = len(dfs.loc[(dfs['sex'] == 'male') & (dfs['age'].astype(int) > 25)])
result['type'] = 'number'
result['value'] = males_above_25
print(result)
            ```
            
2024-10-08 17:46:22 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:46:22 [INFO] 
Code running:
```
result = {}
males_above_25 = len(dfs.loc[(dfs['sex'] == 'male') & (dfs['age'].astype(int) > 25)])
result['type'] = 'number'
result['value'] = males_above_25
print(result)
        ```
2024-10-08 17:46:22 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'

2024-10-08 17:46:22 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-10-08 17:46:22 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:46:22 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:46:22 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
males_above_25 = len(dfs.loc[(dfs['sex'] == 'male') & (dfs['age'].astype(int) > 25)])
result['type'] = 'number'
result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
2024-10-08 17:46:22 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:47:15 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:47:15 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,9.0,0,2,13.4167,,First,woman,False,,Cherbourg,no,True
1,1,male,,5,5,24.0,Q,Second,child,False,C,Southampton,no,False
1,3,female,0.75,8,4,25.4667,C,Third,man,True,G,,yes,True
</dataframe>


The user asked the following question:
### QUERY
 how many males are above 25 years old?

You generated this python code:
result = {}
males_above_25 = len(dfs.loc[(dfs['sex'] == 'male') & (dfs['age'].astype(int) > 25)])
result['type'] = 'number'
result['value'] = males_above_25
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
            
2024-10-08 17:47:15 [INFO] Code generated:
            ```
            males_above_25 = 0
for df in dfs:
    males_above_25 += len(df.loc[(df['sex'] == 'male') & (df['age'].astype(int) > 25)])
result = {}
result['type'] = 'number'
result['value'] = males_above_25
print(result)
            ```
            
2024-10-08 17:47:15 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:47:15 [INFO] 
Code running:
```
males_above_25 = 0
for df in dfs:
    males_above_25 += len(df.loc[(df['sex'] == 'male') & (df['age'].astype(int) > 25)])
result = {}
result['type'] = 'number'
result['value'] = males_above_25
print(result)
        ```
2024-10-08 17:47:15 [ERROR] Unable to extract filters for passed code
2024-10-08 17:47:15 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 3, in <module>
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\generic.py", line 6240, in astype
    new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\internals\managers.py", line 448, in astype
    return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\internals\managers.py", line 352, in apply
    applied = getattr(b, f)(**kwargs)
              ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\internals\blocks.py", line 526, in astype
    new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\dtypes\astype.py", line 299, in astype_array_safe
    new_values = astype_array(values, dtype, copy=copy)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\dtypes\astype.py", line 230, in astype_array
    values = astype_nansafe(values, dtype, copy=copy)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\dtypes\astype.py", line 140, in astype_nansafe
    return _astype_float_to_int_nansafe(arr, dtype, copy)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandas\core\dtypes\astype.py", line 182, in _astype_float_to_int_nansafe
    raise IntCastingNaNError(
pandas.errors.IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer

2024-10-08 17:47:15 [ERROR] Pipeline failed on step 6: Cannot convert non-finite values (NA or inf) to integer
2024-10-08 17:47:51 [INFO] Question: how many males present in data?
2024-10-08 17:47:51 [INFO] Running PandasAI with local LLM...
2024-10-08 17:47:51 [INFO] Prompt ID: 270ff0e3-2217-4360-a8e1-31ad3c811540
2024-10-08 17:47:51 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 17:47:51 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 17:47:51 [INFO] Executing Step 1: CacheLookup
2024-10-08 17:47:51 [INFO] Executing Step 2: PromptGeneration
2024-10-08 17:47:51 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,female,25.0,2,4,14.5,Q,Third,man,False,D,,yes,False
1,3,male,80.0,1,1,4.0125,,First,child,False,,Queenstown,no,True
0,2,male,,3,2,9.0,C,Second,woman,True,C,Cherbourg,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males present in data?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 17:47:51 [INFO] Executing Step 3: CodeGenerator
2024-10-08 17:49:34 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:49:34 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,female,25.0,2,4,14.5,Q,Third,man,False,D,,yes,False
1,3,male,80.0,1,1,4.0125,,First,child,False,,Queenstown,no,True
0,2,male,,3,2,9.0,C,Second,woman,True,C,Cherbourg,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males present in data?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 17:49:34 [INFO] Code generated:
            ```
            import pandas as pd
from matplotlib import pyplot as plt


# Query: How many males present in data?

dfs = []  # Variable `dfs: list[pd.DataFrame]` is already declared.

# Load your data frame into dfs variable.
dfs.append(pd.DataFrame({
    'survived': [1, 1, 0],
    'pclass': ['1', '3', '2'],
    'sex': ['female', 'male', 'male'],
    'age': [25.0, 80.0, ""],
    'sibsp': [2, 1, 3],
    'parch': [4, 1, 2],
    'fare': [14.5, 4.0125, 9.0],
    'embarked': ['Q', "", "C"],
    'class': ['Third', 'First', 'Second'],
    'who': ['man', 'child', 'woman'],
    'adult_male': [False, True, True],
    'deck': ['', '', ''],
    'embark_town': ['Queenstown', '', 'Cherbourg'],
    'alive': [False, False, 1],
    'alone': [True, True, True]
}))


male_count = dfs[0]['sex'][dfs[0]['sex'] == 'male'].count()

result = {"type": "number", "value": male_count}

print(result)
            ```
            
2024-10-08 17:49:34 [INFO] Executing Step 4: CachePopulation
2024-10-08 17:49:34 [INFO] Executing Step 5: CodeCleaning
2024-10-08 17:49:34 [INFO] 
Code running:
```
dfs.append(pd.DataFrame({'survived': [1, 1, 0], 'pclass': ['1', '3', '2'], 'sex': ['female', 'male', 'male'], 'age': [25.0, 80.0, ''], 'sibsp': [2, 1, 3], 'parch': [4, 1, 2], 'fare': [14.5, 4.0125, 9.0], 'embarked': ['Q', '', 'C'], 'class': ['Third', 'First', 'Second'], 'who': ['man', 'child', 'woman'], 'adult_male': [False, True, True], 'deck': ['', '', ''], 'embark_town': ['Queenstown', '', 'Cherbourg'], 'alive': [False, False, 1], 'alone': [True, True, True]}))
male_count = dfs[0]['sex'][dfs[0]['sex'] == 'male'].count()
result = {'type': 'number', 'value': male_count}
print(result)
        ```
2024-10-08 17:49:34 [INFO] Executing Step 6: CodeExecution
2024-10-08 17:49:34 [INFO] Executing Step 7: ResultValidation
2024-10-08 17:49:34 [INFO] Answer: {'type': 'number', 'value': 577}
2024-10-08 17:49:34 [INFO] Executing Step 8: ResultParsing
2024-10-08 17:50:33 [INFO] Question: how many males present in data which are in first class?
2024-10-08 17:50:33 [INFO] Running PandasAI with local LLM...
2024-10-08 17:50:33 [INFO] Prompt ID: 85126d11-7a2d-4220-a88c-abde0f67bc48
2024-10-08 17:50:33 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 17:50:33 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 17:50:33 [INFO] Executing Step 1: CacheLookup
2024-10-08 17:50:33 [INFO] Executing Step 2: PromptGeneration
2024-10-08 17:50:33 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,,3,3,14.4583,,Third,woman,True,G,Cherbourg,no,False
1,1,male,14.5,8,1,26.2833,C,First,man,False,A,,yes,False
0,3,female,60.0,2,2,57.9792,Q,Second,child,True,,Southampton,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males present in data which are in first class?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 17:50:33 [INFO] Executing Step 3: CodeGenerator
2024-10-08 17:51:30 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:51:30 [ERROR] Pipeline failed on step 3: No code found in the response
2024-10-08 17:54:27 [INFO] Question: In the data how many sex - males are present who have class - First ?
2024-10-08 17:54:27 [INFO] Running PandasAI with local LLM...
2024-10-08 17:54:27 [INFO] Prompt ID: 2b549880-7d0f-4c25-bb99-c838790074ba
2024-10-08 17:54:27 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 17:54:27 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 17:54:27 [INFO] Executing Step 1: CacheLookup
2024-10-08 17:54:27 [INFO] Executing Step 2: PromptGeneration
2024-10-08 17:54:27 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 In the data how many sex - males are present who have class - First ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 17:54:27 [INFO] Executing Step 3: CodeGenerator
2024-10-08 17:55:43 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:55:43 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 In the data how many sex - males are present who have class - First ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 17:55:43 [INFO] Code generated:
            ```
            Python
# TODO: import the required dependencies
import pandas as pd

# Initialize dfs variable
dfs = ...

dfs[0].head()  # Assuming your data is in the first dataframe

# Filter males who belong to 'First' class
first_class_males = dfs[0][dfs[0]['sex'] == 'male'][dfs[0]['class'] == 'First']

# Count the number of males who belong to 'First' class
result_count = len(first_class_males)

# Declare result variable as a dictionary
result = {"type": "number", "value": result_count}

print(result)
            ```
            
2024-10-08 17:55:43 [INFO] Executing Step 4: CachePopulation
2024-10-08 17:55:43 [INFO] Executing Step 5: CodeCleaning
2024-10-08 17:55:43 [INFO] 
Code running:
```
Python
dfs[0].head()
first_class_males = dfs[0][dfs[0]['sex'] == 'male'][dfs[0]['class'] == 'First']
result_count = len(first_class_males)
result = {'type': 'number', 'value': result_count}
print(result)
        ```
2024-10-08 17:55:43 [INFO] Executing Step 6: CodeExecution
2024-10-08 17:55:43 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-10-08 17:55:43 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-08 17:55:43 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:55:43 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:55:43 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
Python
dfs[0].head()
first_class_males = dfs[0][dfs[0]['sex'] == 'male'][dfs[0]['class'] == 'First']
result_count = len(first_class_males)
result = {'type': 'number', 'value': result_count}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-10-08 17:55:43 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:56:35 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:56:35 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
Python
dfs[0].head()
first_class_males = dfs[0][dfs[0]['sex'] == 'male'][dfs[0]['class'] == 'First']
result_count = len(first_class_males)
result = {'type': 'number', 'value': result_count}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-10-08 17:56:35 [INFO] Code generated:
            ```
            first_class_males = dfs[dfs['sex'] == 'male'][dfs['class'] == 'First']
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
            ```
            
2024-10-08 17:56:35 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:56:35 [INFO] 
Code running:
```
first_class_males = dfs[dfs['sex'] == 'male'][dfs['class'] == 'First']
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
        ```
2024-10-08 17:56:35 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str

2024-10-08 17:56:35 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-10-08 17:56:35 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:56:35 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:56:35 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
first_class_males = dfs[dfs['sex'] == 'male'][dfs['class'] == 'First']
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
2024-10-08 17:56:35 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:57:31 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:57:31 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
first_class_males = dfs[dfs['sex'] == 'male'][dfs['class'] == 'First']
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
            
2024-10-08 17:57:31 [INFO] Code generated:
            ```
            first_class_males = dfs[(dfs['sex'] == 'male') & (dfs['class'] == 'First')]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
            ```
            
2024-10-08 17:57:31 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:57:31 [INFO] 
Code running:
```
first_class_males = dfs[(dfs['sex'] == 'male') & (dfs['class'] == 'First')]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
        ```
2024-10-08 17:57:31 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str

2024-10-08 17:57:31 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-10-08 17:57:31 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-08 17:57:31 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-08 17:57:31 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
first_class_males = dfs[(dfs['sex'] == 'male') & (dfs['class'] == 'First')]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
2024-10-08 17:57:31 [INFO] Executing Step 1: CodeGenerator
2024-10-08 17:58:10 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 17:58:10 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,male,22.0,8,4,21.075,S,Third,woman,False,,Cherbourg,yes,False
0,1,female,59.0,3,2,13.0,C,Second,man,True,G,Queenstown,no,True
1,2,female,,4,6,15.2458,,First,child,False,B,,no,False
</dataframe>


The user asked the following question:
### QUERY
 In the data how many sex - males are present who have class - First ?

You generated this python code:
first_class_males = dfs[(dfs['sex'] == 'male') & (dfs['class'] == 'First')]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
            
2024-10-08 17:58:10 [INFO] Code generated:
            ```
            Python
first_class_males = dfs[(dfs['sex'] == 'male') & (dfs['class'].str.contains('First'))]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
            ```
            
2024-10-08 17:58:10 [INFO] Executing Step 2: CodeCleaning
2024-10-08 17:58:10 [INFO] 
Code running:
```
Python
first_class_males = dfs[(dfs['sex'] == 'male') & dfs['class'].str.contains('First')]
result_count = len(first_class_males)
print(f'There are {result_count} sex - males present who have class - First.')
        ```
2024-10-08 17:58:10 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\anaconda3\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-10-08 17:58:10 [ERROR] Pipeline failed on step 6: name 'Python' is not defined
2024-10-08 18:01:41 [INFO] Question: How many rows and columns are present in current dataset?
2024-10-08 18:01:41 [INFO] Running PandasAI with local LLM...
2024-10-08 18:01:41 [INFO] Prompt ID: 00468f05-5189-4bac-bafd-10849875165c
2024-10-08 18:01:41 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 18:01:41 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 18:01:41 [INFO] Executing Step 1: CacheLookup
2024-10-08 18:01:41 [INFO] Executing Step 2: PromptGeneration
2024-10-08 18:01:41 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,1,male,60.0,8,6,14.1083,,Second,child,False,C,,no,True
1,3,male,14.0,4,5,80.0,Q,First,woman,False,G,Cherbourg,no,False
0,2,female,,3,1,14.4,S,Third,man,True,,Southampton,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many rows and columns are present in current dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 18:01:41 [INFO] Executing Step 3: CodeGenerator
2024-10-08 18:02:52 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 18:02:52 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,1,male,60.0,8,6,14.1083,,Second,child,False,C,,no,True
1,3,male,14.0,4,5,80.0,Q,First,woman,False,G,Cherbourg,no,False
0,2,female,,3,1,14.4,S,Third,man,True,,Southampton,yes,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many rows and columns are present in current dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 18:02:52 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Load data into a list of DataFrames
dfs = ...

# Find number of rows and columns in the dataset
num_rows = dfs[0].shape[0]
num_cols = dfs[0].shape[1]

# Declare result variable with type "string" and value
result = {"type": "string", "value": f"{num_rows} rows and {num_cols} columns"}

print(result)
            ```
            
2024-10-08 18:02:52 [INFO] Executing Step 4: CachePopulation
2024-10-08 18:02:52 [INFO] Executing Step 5: CodeCleaning
2024-10-08 18:02:52 [INFO] 
Code running:
```
num_rows = dfs[0].shape[0]
num_cols = dfs[0].shape[1]
result = {'type': 'string', 'value': f'{num_rows} rows and {num_cols} columns'}
print(result)
        ```
2024-10-08 18:02:52 [INFO] Executing Step 6: CodeExecution
2024-10-08 18:02:52 [INFO] Executing Step 7: ResultValidation
2024-10-08 18:02:52 [INFO] Answer: {'type': 'string', 'value': '891 rows and 15 columns'}
2024-10-08 18:02:52 [INFO] Executing Step 8: ResultParsing
2024-10-08 18:03:37 [INFO] Question: What is the average age in dataset?
2024-10-08 18:03:37 [INFO] Running PandasAI with local LLM...
2024-10-08 18:03:37 [INFO] Prompt ID: 3c0464c9-c610-4294-ad79-b676364f515a
2024-10-08 18:03:37 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 18:03:37 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 18:03:37 [INFO] Executing Step 1: CacheLookup
2024-10-08 18:03:37 [INFO] Executing Step 2: PromptGeneration
2024-10-08 18:03:37 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,female,53.0,3,3,30.0708,C,Second,man,False,C,Cherbourg,no,False
1,1,male,5.0,4,5,49.5042,,First,child,True,G,Southampton,yes,True
0,3,female,,8,0,14.4542,Q,Third,woman,True,,,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is the average age in dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 18:03:37 [INFO] Executing Step 3: CodeGenerator
2024-10-08 18:04:39 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 18:04:39 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,female,53.0,3,3,30.0708,C,Second,man,False,C,Cherbourg,no,False
1,1,male,5.0,4,5,49.5042,,First,child,True,G,Southampton,yes,True
0,3,female,,8,0,14.4542,Q,Third,woman,True,,,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is the average age in dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-08 18:04:39 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Write code here
dfs = ...

result = {}

for df in dfs:
    if len(df) > 0:
        age_avg = df['age'].mean()
        result = {"type": "number", "value": age_avg}

print(result)
            ```
            
2024-10-08 18:04:39 [INFO] Executing Step 4: CachePopulation
2024-10-08 18:04:39 [INFO] Executing Step 5: CodeCleaning
2024-10-08 18:04:39 [INFO] 
Code running:
```
result = {}
for df in dfs:
    if len(df) > 0:
        age_avg = df['age'].mean()
        result = {'type': 'number', 'value': age_avg}
print(result)
        ```
2024-10-08 18:04:39 [INFO] Executing Step 6: CodeExecution
2024-10-08 18:04:39 [INFO] Executing Step 7: ResultValidation
2024-10-08 18:04:39 [INFO] Answer: {'type': 'number', 'value': 29.69911764705882}
2024-10-08 18:04:39 [INFO] Executing Step 8: ResultParsing
2024-10-08 18:09:22 [INFO] Question: how many people have more than 3 siblings?
2024-10-08 18:09:22 [INFO] Running PandasAI with local LLM...
2024-10-08 18:09:22 [INFO] Prompt ID: 7a89dfbc-37ae-4d21-8e7b-d51eae3a9a4e
2024-10-08 18:09:22 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-08 18:09:22 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-08 18:09:22 [INFO] Executing Step 1: CacheLookup
2024-10-08 18:09:22 [INFO] Executing Step 2: PromptGeneration
2024-10-08 18:09:22 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,2,male,20.5,5,0,89.1042,C,First,child,True,A,Cherbourg,no,True
1,3,female,,1,6,26.0,,Second,man,False,,Queenstown,yes,False
0,1,male,48.0,8,1,262.375,Q,Third,woman,False,E,,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people have more than 3 siblings?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-08 18:09:22 [INFO] Executing Step 3: CodeGenerator
2024-10-08 18:10:10 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-08 18:10:10 [ERROR] Pipeline failed on step 3: No code found in the response
2024-10-15 18:57:17 [INFO] Question: how many rows are there in the dataset?

2024-10-15 18:57:17 [INFO] Running PandasAI with local LLM...
2024-10-15 18:57:17 [INFO] Prompt ID: 6e9fb658-e1b7-4a87-919c-f9736c3db126
2024-10-15 18:57:17 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 18:57:17 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 18:57:17 [INFO] Executing Step 1: CacheLookup
2024-10-15 18:57:17 [INFO] Executing Step 2: PromptGeneration
2024-10-15 18:57:17 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,HR,Life Sciences,STAFF-33,1578,Female,Research Director,Single,No,Y,3,45,0,1431,5,Bachelor's Degree,1,3,58,1,1,3,2373,20938,4,17,4,3,80,1,22,3,37,12,7,5
Yes,Non-Travel,45 - 54,Current Employees,R&D,Human Resources,STAFF-1543,298,Female,Healthcare Representative,Divorced,Yes,Y,5,20,1,1410,17,Associates Degree,1,2,73,2,2,4,4621,7018,5,24,3,4,80,0,37,4,1,3,0,14
No,Travel_Frequently,35 - 44,Current Employees,Sales,Marketing,STAFF-1915,568,Male,Sales Executive,Married,No,Y,6,38,1,383,2,Master's Degree,1,1,49,3,4,2,2285,23965,9,11,4,1,80,2,2,1,8,4,12,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are there in the dataset?


Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 18:57:17 [INFO] Executing Step 3: CodeGenerator
2024-10-15 18:59:53 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 18:59:54 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,HR,Life Sciences,STAFF-33,1578,Female,Research Director,Single,No,Y,3,45,0,1431,5,Bachelor's Degree,1,3,58,1,1,3,2373,20938,4,17,4,3,80,1,22,3,37,12,7,5
Yes,Non-Travel,45 - 54,Current Employees,R&D,Human Resources,STAFF-1543,298,Female,Healthcare Representative,Divorced,Yes,Y,5,20,1,1410,17,Associates Degree,1,2,73,2,2,4,4621,7018,5,24,3,4,80,0,37,4,1,3,0,14
No,Travel_Frequently,35 - 44,Current Employees,Sales,Marketing,STAFF-1915,568,Male,Sales Executive,Married,No,Y,6,38,1,383,2,Master's Degree,1,1,49,3,4,2,2285,23965,9,11,4,1,80,2,2,1,8,4,12,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are there in the dataset?


Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 18:59:54 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
            ```
            
2024-10-15 18:59:54 [INFO] Executing Step 4: CachePopulation
2024-10-15 18:59:54 [INFO] Executing Step 5: CodeCleaning
2024-10-15 18:59:54 [INFO] 
Code running:
```

        ```
2024-10-15 18:59:54 [INFO] Executing Step 6: CodeExecution
2024-10-15 18:59:54 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-10-15 18:59:54 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 18:59:54 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 18:59:54 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 18:59:54 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,HR,Life Sciences,STAFF-33,1578,Female,Research Director,Single,No,Y,3,45,0,1431,5,Bachelor's Degree,1,3,58,1,1,3,2373,20938,4,17,4,3,80,1,22,3,37,12,7,5
Yes,Non-Travel,45 - 54,Current Employees,R&D,Human Resources,STAFF-1543,298,Female,Healthcare Representative,Divorced,Yes,Y,5,20,1,1410,17,Associates Degree,1,2,73,2,2,4,4621,7018,5,24,3,4,80,0,37,4,1,3,0,14
No,Travel_Frequently,35 - 44,Current Employees,Sales,Marketing,STAFF-1915,568,Male,Sales Executive,Married,No,Y,6,38,1,383,2,Master's Degree,1,1,49,3,4,2,2285,23965,9,11,4,1,80,2,2,1,8,4,12,13
</dataframe>


The user asked the following question:
### QUERY
 how many rows are there in the dataset?


You generated this python code:


It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
2024-10-15 18:59:54 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:05:19 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:05:19 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,HR,Life Sciences,STAFF-33,1578,Female,Research Director,Single,No,Y,3,45,0,1431,5,Bachelor's Degree,1,3,58,1,1,3,2373,20938,4,17,4,3,80,1,22,3,37,12,7,5
Yes,Non-Travel,45 - 54,Current Employees,R&D,Human Resources,STAFF-1543,298,Female,Healthcare Representative,Divorced,Yes,Y,5,20,1,1410,17,Associates Degree,1,2,73,2,2,4,4621,7018,5,24,3,4,80,0,37,4,1,3,0,14
No,Travel_Frequently,35 - 44,Current Employees,Sales,Marketing,STAFF-1915,568,Male,Sales Executive,Married,No,Y,6,38,1,383,2,Master's Degree,1,1,49,3,4,2,2285,23965,9,11,4,1,80,2,2,1,8,4,12,13
</dataframe>


The user asked the following question:
### QUERY
 how many rows are there in the dataset?


You generated this python code:


It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
            
2024-10-15 19:05:19 [INFO] Code generated:
            ```
            import pandas as pd

# Parse the XML dataset
data = """
<dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,HR,Life Sciences,STAFF-33,1578,Female,Research Director,Single,No,Y,3,45,0,1431,5,Bachelor's Degree,1,3,58,1,1,3,2373,20938,4,17,4,3,80,1,22,3,37,12,7,5
Yes,Non-Travel,45 - 54,Current Employees,R&D,Human Resources,STAFF-1543,298,Female,Healthcare Representative,Divorced,Yes,Y,5,20,1,1410,17,Associates Degree,1,2,73,2,2,4,4621,7018,5,24,3,4,80,0,37,4,1,3,0,14
No,Travel_Frequently,35 - 44,Current Employees,Sales,Marketing,STAFF-1915,568,Male,Sales Executive,Married,No,Y,6,38,1,383,2,Master's Degree,1,1,49,3,4,2,2285,23965,9,11,4,1,80,2,2,1,8,4,12,13
</dataframe>
"""

# Split the XML into header and data
xml_header = ''
xml_data = ''

found_start_of_data = False

for line in data.split('\n'):
    if 'dfs[0]:' in line:
        found_start_of_data = True
    elif found_start_of_data:
        xml_data += line + '\n'
    else:
        xml_header += line + '\n'

# Parse the XML into a Pandas DataFrame
df = pd.read_csv(StringIO(xml_header), sep=',', header=None, skiprows=1)
xml_df = pd.io.parsers.StringIO()
df.to_csv(xml_df, index=False)

# Count the number of rows in the dataset
num_rows = df.shape[0]

print(f"There are {num_rows} rows in the dataset.")
            ```
            
2024-10-15 19:05:19 [INFO] Executing Step 2: CodeCleaning
2024-10-15 19:05:19 [ERROR] Pipeline failed on step 2: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-10-15 19:05:19 [ERROR] Pipeline failed on step 6: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-10-15 19:09:56 [INFO] Question: how many rows are present in the dataset?
2024-10-15 19:09:56 [INFO] Running PandasAI with local LLM...
2024-10-15 19:09:56 [INFO] Prompt ID: f0a6def9-3493-4f30-9fb1-f176abf46eee
2024-10-15 19:09:56 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:09:56 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:09:56 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:09:57 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:09:57 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-1876,1784,Male,Sales Executive,Married,No,Y,4,19,1,542,27,High School,1,2,72,4,5,4,3597,13586,5,12,3,4,80,1,21,4,23,9,6,2
No,Travel_Rarely,35 - 44,Current Employees,HR,Human Resources,STAFF-1529,606,Male,Human Resources,Divorced,No,Y,3,33,0,572,3,Master's Degree,1,4,32,1,3,1,6230,22952,1,21,4,1,80,2,1,3,7,2,0,4
Yes,Travel_Frequently,Under 25,Ex-Employees,R&D,Marketing,STAFF-1916,421,Female,Manager,Single,Yes,Y,6,34,0,736,25,Doctoral Degree,1,1,83,3,1,3,3748,4156,8,14,4,3,80,3,33,1,15,1,3,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:09:57 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:11:19 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:11:19 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-1876,1784,Male,Sales Executive,Married,No,Y,4,19,1,542,27,High School,1,2,72,4,5,4,3597,13586,5,12,3,4,80,1,21,4,23,9,6,2
No,Travel_Rarely,35 - 44,Current Employees,HR,Human Resources,STAFF-1529,606,Male,Human Resources,Divorced,No,Y,3,33,0,572,3,Master's Degree,1,4,32,1,3,1,6230,22952,1,21,4,1,80,2,1,3,7,2,0,4
Yes,Travel_Frequently,Under 25,Ex-Employees,R&D,Marketing,STAFF-1916,421,Female,Manager,Single,Yes,Y,6,34,0,736,25,Doctoral Degree,1,1,83,3,1,3,3748,4156,8,14,4,3,80,3,33,1,15,1,3,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many rows are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:11:19 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

dfs = ["<dataframe>"]

# Calculate the total number of rows in the dataframes
total_rows = sum(len(df) for df in dfs)

# Declare result var: 
result = { "type": "string", "value": f"The dataset contains {total_rows} rows." }

print(result["value"])
            ```
            
2024-10-15 19:11:19 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:11:19 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:11:19 [INFO] 
Code running:
```
total_rows = sum(len(df) for df in dfs)
result = {'type': 'string', 'value': f'The dataset contains {total_rows} rows.'}
print(result['value'])
        ```
2024-10-15 19:11:19 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:11:19 [INFO] Executing Step 7: ResultValidation
2024-10-15 19:11:19 [INFO] Answer: {'type': 'string', 'value': 'The dataset contains 1470 rows.'}
2024-10-15 19:11:19 [INFO] Executing Step 8: ResultParsing
2024-10-15 19:13:16 [INFO] Question: how many female gender are present in the dataset?
2024-10-15 19:13:16 [INFO] Running PandasAI with local LLM...
2024-10-15 19:13:16 [INFO] Prompt ID: c25f7416-5a64-4590-9042-81c5ea8bc484
2024-10-15 19:13:16 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:13:16 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:13:16 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:13:16 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:13:16 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many female gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:13:16 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:13:19 [INFO] Question: how many female gender are present in the dataset?
2024-10-15 19:13:19 [INFO] Running PandasAI with local LLM...
2024-10-15 19:13:19 [INFO] Prompt ID: 000b6c8d-8777-4983-937a-7c2687c99948
2024-10-15 19:13:19 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:13:19 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:13:19 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:13:19 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:13:19 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Technical Degree,STAFF-1937,1045,Male,Human Resources,Single,No,Y,5,46,1,1171,18,Master's Degree,1,3,78,1,2,4,2341,15669,0,23,4,2,80,2,24,3,10,15,1,0
No,Non-Travel,45 - 54,Ex-Employees,Sales,Other,STAFF-2019,1103,Female,Research Director,Married,No,Y,6,60,0,1200,12,Associates Degree,1,4,74,3,4,2,3629,21445,9,13,4,3,80,3,15,1,24,5,13,15
No,Travel_Frequently,Under 25,Current Employees,R&D,Marketing,STAFF-302,905,Male,Sales Executive,Divorced,Yes,Y,0,49,0,1382,29,Doctoral Degree,1,2,59,2,5,3,10400,18384,8,20,3,1,80,0,31,2,25,4,10,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many female gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:13:19 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:13:19 [INFO] Question: how many female gender are present in the dataset?
2024-10-15 19:13:19 [INFO] Running PandasAI with local LLM...
2024-10-15 19:13:19 [INFO] Prompt ID: 1ec76096-502a-47df-97ce-0fbe53703f32
2024-10-15 19:13:19 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:13:19 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:13:19 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:13:19 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:13:19 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Medical,STAFF-12,293,Female,Sales Representative,Married,Yes,Y,5,29,0,636,5,Doctoral Degree,1,4,50,1,2,4,18665,19989,6,12,3,2,80,2,19,1,22,0,15,1
Yes,Non-Travel,Over 55,Current Employees,HR,Technical Degree,STAFF-804,1446,Male,Manager,Divorced,Yes,Y,2,51,1,583,3,Master's Degree,1,3,100,3,4,2,2856,11309,7,24,3,3,80,3,17,4,23,5,8,2
No,Travel_Rarely,Under 25,Current Employees,R&D,Marketing,STAFF-1136,1954,Male,Laboratory Technician,Single,No,Y,6,24,0,1060,1,Bachelor's Degree,1,1,99,2,5,1,3815,16439,8,21,4,1,80,0,34,3,19,13,12,15
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many female gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:13:19 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:14:29 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:14:29 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many female gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:14:29 [INFO] Code generated:
            ```
            Python
# TODO: import the required dependencies
import pandas as pd

# Iterate over each DataFrame in the list
for df in dfs:
    # Get the count of female gender in current DataFrame
    n_female = len(df[df['Gender'] == 'Female'])
    
    # Declare result var: 
    result = { "type": "string", "value": f"There are {n_female} females present in the dataset." }

print(result)
            ```
            
2024-10-15 19:14:29 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:14:29 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:14:29 [INFO] 
Code running:
```
Python
for df in dfs:
    n_female = len(df[df['Gender'] == 'Female'])
    result = {'type': 'string', 'value': f'There are {n_female} females present in the dataset.'}
print(result)
        ```
2024-10-15 19:14:29 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:14:29 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-10-15 19:14:29 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 19:14:29 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 19:14:29 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 19:14:29 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
Python
for df in dfs:
    n_female = len(df[df['Gender'] == 'Female'])
    result = {'type': 'string', 'value': f'There are {n_female} females present in the dataset.'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-10-15 19:14:29 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:16:12 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:16:12 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Medical,STAFF-12,293,Female,Sales Representative,Married,Yes,Y,5,29,0,636,5,Doctoral Degree,1,4,50,1,2,4,18665,19989,6,12,3,2,80,2,19,1,22,0,15,1
Yes,Non-Travel,Over 55,Current Employees,HR,Technical Degree,STAFF-804,1446,Male,Manager,Divorced,Yes,Y,2,51,1,583,3,Master's Degree,1,3,100,3,4,2,2856,11309,7,24,3,3,80,3,17,4,23,5,8,2
No,Travel_Rarely,Under 25,Current Employees,R&D,Marketing,STAFF-1136,1954,Male,Laboratory Technician,Single,No,Y,6,24,0,1060,1,Bachelor's Degree,1,1,99,2,5,1,3815,16439,8,21,4,1,80,0,34,3,19,13,12,15
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many female gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:16:12 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

dfs = [...]  # this variable is already provided
result = {}

for df in dfs:
    female_count = len(df[df['Gender'] == 'Female'])
    result = {"type": "string", "value": f"There are {female_count} females present in the dataset."}

print(result)
            ```
            
2024-10-15 19:16:12 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:16:12 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:16:12 [INFO] 
Code running:
```
result = {}
for df in dfs:
    female_count = len(df[df['Gender'] == 'Female'])
    result = {'type': 'string', 'value': f'There are {female_count} females present in the dataset.'}
print(result)
        ```
2024-10-15 19:16:12 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:16:12 [INFO] Executing Step 7: ResultValidation
2024-10-15 19:16:12 [INFO] Answer: {'type': 'string', 'value': 'There are 588 females present in the dataset.'}
2024-10-15 19:16:12 [INFO] Executing Step 8: ResultParsing
2024-10-15 19:19:44 [INFO] Question: how many male gender are present in the dataset?
2024-10-15 19:19:44 [INFO] Running PandasAI with local LLM...
2024-10-15 19:19:44 [INFO] Prompt ID: 8863ece4-2100-4093-8bce-6b618467140a
2024-10-15 19:19:44 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:19:44 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:19:44 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:19:44 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:19:44 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-19,1226,Male,Sales Representative,Single,No,Y,5,37,1,611,13,Doctoral Degree,1,4,90,3,2,3,1223,14460,3,16,3,1,80,0,3,4,14,18,3,8
No,Non-Travel,Under 25,Current Employees,R&D,Marketing,STAFF-1797,1650,Female,Manufacturing Director,Divorced,No,Y,1,59,0,345,7,Master's Degree,1,3,76,2,3,1,5605,24852,1,25,4,2,80,1,34,2,21,1,14,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Life Sciences,STAFF-2024,741,Female,Research Director,Married,Yes,Y,3,57,1,1064,12,High School,1,1,35,4,5,2,5743,22162,5,12,3,3,80,3,10,3,11,0,0,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:19:44 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:20:23 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:20:23 [ERROR] Pipeline failed on step 3: No code found in the response
2024-10-15 19:21:45 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:21:45 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
Python
for df in dfs:
    n_female = len(df[df['Gender'] == 'Female'])
    result = {'type': 'string', 'value': f'There are {n_female} females present in the dataset.'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-10-15 19:21:45 [INFO] Code generated:
            ```
            result = f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."
print(result)
            ```
            
2024-10-15 19:21:45 [INFO] Executing Step 2: CodeCleaning
2024-10-15 19:21:45 [INFO] 
Code running:
```
result = f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."
print(result)
        ```
2024-10-15 19:21:45 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 96, in execute
    if not OutputValidator.validate_result(result):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\helpers\output_validator.py", line 73, in validate_result
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Result must be in the format of dictionary of type and value

2024-10-15 19:21:45 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-10-15 19:21:45 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 19:21:45 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 19:21:45 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
result = f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 96, in execute
    if not OutputValidator.validate_result(result):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\helpers\output_validator.py", line 73, in validate_result
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Result must be in the format of dictionary of type and value


Fix the python code above and return the new python code:
2024-10-15 19:21:45 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:22:58 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:22:58 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-19,1226,Male,Sales Representative,Single,No,Y,5,37,1,611,13,Doctoral Degree,1,4,90,3,2,3,1223,14460,3,16,3,1,80,0,3,4,14,18,3,8
No,Non-Travel,Under 25,Current Employees,R&D,Marketing,STAFF-1797,1650,Female,Manufacturing Director,Divorced,No,Y,1,59,0,345,7,Master's Degree,1,3,76,2,3,1,5605,24852,1,25,4,2,80,1,34,2,21,1,14,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Life Sciences,STAFF-2024,741,Female,Research Director,Married,Yes,Y,3,57,1,1064,12,High School,1,1,35,4,5,2,5743,22162,5,12,3,3,80,3,10,3,11,0,0,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:22:58 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

dfs = [...]  # Your dataframes
dfs[0]

# Find males in the dataset
male_count = dfs[0]['Gender'].eq('Male').sum()

# Declare result var:
result = {"type": "number", "value": male_count}
            ```
            
2024-10-15 19:22:58 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:22:58 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:22:58 [INFO] 
Code running:
```
dfs[0]
male_count = dfs[0]['Gender'].eq('Male').sum()
result = {'type': 'number', 'value': male_count}
        ```
2024-10-15 19:22:58 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:22:58 [INFO] Executing Step 7: ResultValidation
2024-10-15 19:22:58 [INFO] Answer: {'type': 'number', 'value': 882}
2024-10-15 19:22:58 [INFO] Executing Step 8: ResultParsing
2024-10-15 19:24:09 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:24:09 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
result = f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 96, in execute
    if not OutputValidator.validate_result(result):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\helpers\output_validator.py", line 73, in validate_result
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Result must be in the format of dictionary of type and value


Fix the python code above and return the new python code:
            
2024-10-15 19:24:09 [INFO] Code generated:
            ```
            result = {"type": "answer", "value": f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)
            ```
            
2024-10-15 19:24:09 [INFO] Executing Step 2: CodeCleaning
2024-10-15 19:24:09 [INFO] 
Code running:
```
result = {'type': 'answer', 'value': f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)
        ```
2024-10-15 19:24:09 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type answer

2024-10-15 19:24:09 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-10-15 19:24:09 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 19:24:09 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 19:24:09 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
result = {'type': 'answer', 'value': f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type answer


Fix the python code above and return the new python code:
2024-10-15 19:24:09 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:24:11 [INFO] Question: how many male gender are present in the dataset which have even Employee Number?
2024-10-15 19:24:11 [INFO] Running PandasAI with local LLM...
2024-10-15 19:24:11 [INFO] Prompt ID: e48d3b36-7018-4e97-b306-c9d2696b555c
2024-10-15 19:24:11 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:24:11 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:24:11 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:24:11 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:24:11 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Under 25,Current Employees,HR,Human Resources,STAFF-2032,977,Male,Manager,Divorced,No,Y,4,59,1,179,21,Bachelor's Degree,1,3,92,2,5,2,3468,5543,0,13,4,1,80,3,6,2,29,4,13,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Technical Degree,STAFF-1481,270,Female,Research Director,Single,No,Y,2,48,1,1192,13,High School,1,2,38,1,1,4,9950,10410,1,12,3,4,80,2,13,4,12,18,11,10
Yes,Non-Travel,45 - 54,Current Employees,R&D,Life Sciences,STAFF-384,1912,Female,Sales Representative,Married,Yes,Y,5,36,0,1439,4,Associates Degree,1,4,98,3,3,3,6687,14947,9,22,4,2,80,1,26,3,21,17,10,0
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:24:11 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:24:49 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:24:49 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Technical Degree,STAFF-632,517,Female,Sales Representative,Married,No,Y,6,42,0,199,18,Bachelor's Degree,1,2,64,2,3,4,4240,19805,9,18,4,2,80,1,7,1,20,10,6,4
No,Travel_Rarely,25 - 34,Current Employees,Sales,Marketing,STAFF-944,650,Male,Laboratory Technician,Single,No,Y,4,43,1,1297,7,Associates Degree,1,3,44,1,5,2,2400,13137,6,20,3,1,80,2,30,3,27,15,8,5
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Human Resources,STAFF-421,410,Male,Sales Executive,Divorced,Yes,Y,1,36,1,988,4,Doctoral Degree,1,4,40,4,1,1,3920,22952,4,15,4,4,80,0,0,4,0,4,5,2
</dataframe>


The user asked the following question:
### QUERY
 how many female gender are present in the dataset?

You generated this python code:
result = {'type': 'answer', 'value': f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type answer


Fix the python code above and return the new python code:
            
2024-10-15 19:24:49 [INFO] Code generated:
            ```
            result = {'value': f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)
            ```
            
2024-10-15 19:24:49 [INFO] Executing Step 2: CodeCleaning
2024-10-15 19:24:49 [INFO] 
Code running:
```
result = {'value': f"There are {len([x for x in dfs[0]['Gender'] if x == 'Female'])} females present in the dataset."}
print(result)
        ```
2024-10-15 19:24:49 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 96, in execute
    if not OutputValidator.validate_result(result):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\helpers\output_validator.py", line 73, in validate_result
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Result must be in the format of dictionary of type and value

2024-10-15 19:24:49 [ERROR] Pipeline failed on step 6: Result must be in the format of dictionary of type and value
2024-10-15 19:25:52 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:25:52 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Under 25,Current Employees,HR,Human Resources,STAFF-2032,977,Male,Manager,Divorced,No,Y,4,59,1,179,21,Bachelor's Degree,1,3,92,2,5,2,3468,5543,0,13,4,1,80,3,6,2,29,4,13,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Technical Degree,STAFF-1481,270,Female,Research Director,Single,No,Y,2,48,1,1192,13,High School,1,2,38,1,1,4,9950,10410,1,12,3,4,80,2,13,4,12,18,11,10
Yes,Non-Travel,45 - 54,Current Employees,R&D,Life Sciences,STAFF-384,1912,Female,Sales Representative,Married,Yes,Y,5,36,0,1439,4,Associates Degree,1,4,98,3,3,3,6687,14947,9,22,4,2,80,1,26,3,21,17,10,0
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:25:52 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Initialize an empty dictionary to hold the result
result = {}

# Count the number of male gender having even Employee Number
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male' & (dfs[0]['Employee Number'] % 2 == 0)].shape[0]

# Store the count in the result dictionary
result.update({"type": "number", "value": count_even_male})

print(result)
            ```
            
2024-10-15 19:25:52 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:25:52 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:25:52 [INFO] 
Code running:
```
result = {}
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male' & (dfs[0]['Employee Number'] % 2 == 0)].shape[0]
result.update({'type': 'number', 'value': count_even_male})
print(result)
        ```
2024-10-15 19:25:52 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:25:52 [ERROR] Unable to extract filters for passed code
2024-10-15 19:25:52 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 305, in na_logical_op
    result = op(x, y)
             ^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\roperator.py", line 54, in rand_
    return operator.and_(right, left)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: ufunc 'bitwise_and' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 319, in na_logical_op
    result = libops.scalar_binop(x, y, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\ops.pyx", line 180, in pandas._libs.ops.scalar_binop
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'bool'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\common.py", line 72, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arraylike.py", line 76, in __rand__
    return self._logical_method(other, roperator.rand_)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 6254, in _logical_method
    res_values = ops.logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 395, in logical_op
    res_values = na_logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 328, in na_logical_op
    raise TypeError(
TypeError: Cannot perform 'rand_' with a dtyped [bool] array and scalar of type [bool]

2024-10-15 19:25:52 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 19:25:52 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 19:25:52 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 19:25:52 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Under 25,Current Employees,HR,Human Resources,STAFF-2032,977,Male,Manager,Divorced,No,Y,4,59,1,179,21,Bachelor's Degree,1,3,92,2,5,2,3468,5543,0,13,4,1,80,3,6,2,29,4,13,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Technical Degree,STAFF-1481,270,Female,Research Director,Single,No,Y,2,48,1,1192,13,High School,1,2,38,1,1,4,9950,10410,1,12,3,4,80,2,13,4,12,18,11,10
Yes,Non-Travel,45 - 54,Current Employees,R&D,Life Sciences,STAFF-384,1912,Female,Sales Representative,Married,Yes,Y,5,36,0,1439,4,Associates Degree,1,4,98,3,3,3,6687,14947,9,22,4,2,80,1,26,3,21,17,10,0
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number?

You generated this python code:
result = {}
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male' & (dfs[0]['Employee Number'] % 2 == 0)].shape[0]
result.update({'type': 'number', 'value': count_even_male})
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 305, in na_logical_op
    result = op(x, y)
             ^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\roperator.py", line 54, in rand_
    return operator.and_(right, left)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: ufunc 'bitwise_and' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 319, in na_logical_op
    result = libops.scalar_binop(x, y, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\ops.pyx", line 180, in pandas._libs.ops.scalar_binop
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'bool'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\common.py", line 72, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arraylike.py", line 76, in __rand__
    return self._logical_method(other, roperator.rand_)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 6254, in _logical_method
    res_values = ops.logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 395, in logical_op
    res_values = na_logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 328, in na_logical_op
    raise TypeError(
TypeError: Cannot perform 'rand_' with a dtyped [bool] array and scalar of type [bool]


Fix the python code above and return the new python code:
2024-10-15 19:25:52 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:27:27 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:27:27 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Under 25,Current Employees,HR,Human Resources,STAFF-2032,977,Male,Manager,Divorced,No,Y,4,59,1,179,21,Bachelor's Degree,1,3,92,2,5,2,3468,5543,0,13,4,1,80,3,6,2,29,4,13,1
No,Travel_Rarely,Over 55,Ex-Employees,Sales,Technical Degree,STAFF-1481,270,Female,Research Director,Single,No,Y,2,48,1,1192,13,High School,1,2,38,1,1,4,9950,10410,1,12,3,4,80,2,13,4,12,18,11,10
Yes,Non-Travel,45 - 54,Current Employees,R&D,Life Sciences,STAFF-384,1912,Female,Sales Representative,Married,Yes,Y,5,36,0,1439,4,Associates Degree,1,4,98,3,3,3,6687,14947,9,22,4,2,80,1,26,3,21,17,10,0
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number?

You generated this python code:
result = {}
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male' & (dfs[0]['Employee Number'] % 2 == 0)].shape[0]
result.update({'type': 'number', 'value': count_even_male})
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 305, in na_logical_op
    result = op(x, y)
             ^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\roperator.py", line 54, in rand_
    return operator.and_(right, left)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: ufunc 'bitwise_and' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 319, in na_logical_op
    result = libops.scalar_binop(x, y, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\ops.pyx", line 180, in pandas._libs.ops.scalar_binop
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'bool'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\common.py", line 72, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arraylike.py", line 76, in __rand__
    return self._logical_method(other, roperator.rand_)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 6254, in _logical_method
    res_values = ops.logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 395, in logical_op
    res_values = na_logical_op(lvalues, rvalues, op)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\ops\array_ops.py", line 328, in na_logical_op
    raise TypeError(
TypeError: Cannot perform 'rand_' with a dtyped [bool] array and scalar of type [bool]


Fix the python code above and return the new python code:
            
2024-10-15 19:27:27 [INFO] Code generated:
            ```
            result = {}
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male'][df['Employee Number'].astype(int) % 2 == 0].shape[0]
result.update({'type': 'number', 'value': count_even_male})
print(result)
            ```
            
2024-10-15 19:27:27 [INFO] Executing Step 2: CodeCleaning
2024-10-15 19:27:27 [INFO] 
Code running:
```
result = {}
count_even_male = dfs[0][dfs[0]['Gender'] == 'Male'][df['Employee Number'].astype(int) % 2 == 0].shape[0]
result.update({'type': 'number', 'value': count_even_male})
print(result)
        ```
2024-10-15 19:27:27 [ERROR] Unable to extract filters for passed code
2024-10-15 19:27:27 [INFO] Executing Step 7: ResultValidation
2024-10-15 19:27:27 [INFO] Answer: {'type': 'number', 'value': 463}
2024-10-15 19:27:27 [INFO] Executing Step 8: ResultParsing
2024-10-15 19:28:56 [INFO] Question: how many male gender are present in the dataset which have even Employee Number and Education as Medical ?
2024-10-15 19:28:56 [INFO] Running PandasAI with local LLM...
2024-10-15 19:28:56 [INFO] Prompt ID: ecfbe932-d39c-4bc1-be49-3da7fd48f4e7
2024-10-15 19:28:56 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:28:56 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:28:56 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:28:56 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:28:56 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,R&D,Human Resources,STAFF-1766,585,Female,Sales Representative,Divorced,Yes,Y,1,60,0,819,10,Doctoral Degree,1,3,46,2,5,1,17856,15815,5,17,3,3,80,1,22,4,5,0,13,2
No,Travel_Rarely,Under 25,Current Employees,HR,Life Sciences,STAFF-450,1915,Male,Manufacturing Director,Married,No,Y,0,33,0,857,1,Associates Degree,1,2,74,4,2,3,2625,23070,3,25,4,2,80,0,40,2,29,2,8,4
Yes,Travel_Frequently,Over 55,Ex-Employees,Sales,Marketing,STAFF-527,2065,Female,Human Resources,Single,No,Y,6,36,1,489,21,High School,1,4,37,3,4,2,2679,13983,8,19,4,1,80,3,35,3,27,15,3,1
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number and Education as Medical ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:28:56 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:30:56 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:30:56 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,R&D,Human Resources,STAFF-1766,585,Female,Sales Representative,Divorced,Yes,Y,1,60,0,819,10,Doctoral Degree,1,3,46,2,5,1,17856,15815,5,17,3,3,80,1,22,4,5,0,13,2
No,Travel_Rarely,Under 25,Current Employees,HR,Life Sciences,STAFF-450,1915,Male,Manufacturing Director,Married,No,Y,0,33,0,857,1,Associates Degree,1,2,74,4,2,3,2625,23070,3,25,4,2,80,0,40,2,29,2,8,4
Yes,Travel_Frequently,Over 55,Ex-Employees,Sales,Marketing,STAFF-527,2065,Female,Human Resources,Single,No,Y,6,36,1,489,21,High School,1,4,37,3,4,2,2679,13983,8,19,4,1,80,3,35,3,27,15,3,1
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number and Education as Medical ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:30:56 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Load the first dataframe from the list of dataframes
dfs = [...]  # load the dataframes here if its a list
df = dfs[0]  # assuming it's a list and you want the first one

# Filter the dataframe to include only male gender, even employee numbers, and Medical education
filtered_df = df.loc[(df['Gender'] == 'Male') & (df['Employee Number'].map(lambda x: int(x)) % 2 == 0) & (df['Education'] == 'Medical')]

# Count the number of rows in the filtered dataframe
count_male_even_medical_education = len(filtered_df)

# Declare result var:
result = {"type": "string", "value": f"There are {count_male_even_medical_education} males with even employee numbers and Medical education."}

print(result)
            ```
            
2024-10-15 19:30:56 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:30:56 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:30:56 [INFO] 
Code running:
```
df = dfs[0]
filtered_df = df.loc[(df['Gender'] == 'Male') & (df['Employee Number'].map(lambda x: int(x)) % 2 == 0) & (df['Education'] == 'Medical')]
count_male_even_medical_education = len(filtered_df)
result = {'type': 'string', 'value': f'There are {count_male_even_medical_education} males with even employee numbers and Medical education.'}
print(result)
        ```
2024-10-15 19:30:56 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:30:56 [INFO] Executing Step 7: ResultValidation
2024-10-15 19:30:56 [INFO] Answer: {'type': 'string', 'value': 'There are 0 males with even employee numbers and Medical education.'}
2024-10-15 19:30:56 [INFO] Executing Step 8: ResultParsing
2024-10-15 19:32:10 [INFO] Question: how many male gender are present in the dataset which have even Employee Number and Education as Life Science ?
2024-10-15 19:32:10 [INFO] Running PandasAI with local LLM...
2024-10-15 19:32:10 [INFO] Prompt ID: 85bdb175-9e47-4bf3-928b-ed1d151e4d55
2024-10-15 19:32:10 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:32:10 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:32:10 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:32:10 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:32:10 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Under 25,Current Employees,Sales,Life Sciences,STAFF-1537,600,Male,Research Scientist,Married,Yes,Y,6,27,1,279,2,Associates Degree,1,4,73,1,3,2,8463,16873,7,20,4,2,80,2,18,2,4,5,0,1
Yes,Non-Travel,45 - 54,Ex-Employees,R&D,Technical Degree,STAFF-1487,1544,Female,Laboratory Technician,Divorced,No,Y,5,21,1,138,14,Master's Degree,1,3,41,3,5,1,6032,10077,1,16,3,1,80,0,30,1,13,12,15,15
No,Travel_Rarely,25 - 34,Ex-Employees,HR,Human Resources,STAFF-1607,18,Male,Manufacturing Director,Single,No,Y,2,36,0,310,18,Doctoral Degree,1,1,72,4,4,4,9985,3909,5,13,3,4,80,1,4,3,33,16,6,17
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number and Education as Life Science ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:32:10 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:33:13 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:33:13 [ERROR] Pipeline failed on step 3: No code found in the response
2024-10-15 19:34:01 [INFO] Question: how many male gender are present in the dataset which have even Employee Number and Department as Sales ?
2024-10-15 19:34:01 [INFO] Running PandasAI with local LLM...
2024-10-15 19:34:01 [INFO] Prompt ID: a66c38c6-98b0-47da-820f-d30a60e88e34
2024-10-15 19:34:01 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 19:34:01 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 19:34:01 [INFO] Executing Step 1: CacheLookup
2024-10-15 19:34:01 [INFO] Executing Step 2: PromptGeneration
2024-10-15 19:34:01 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,HR,Life Sciences,STAFF-461,918,Female,Research Scientist,Divorced,Yes,Y,1,37,1,374,17,Doctoral Degree,1,1,80,2,3,1,5295,19764,4,18,4,1,80,1,7,4,31,16,15,2
No,Travel_Rarely,Under 25,Current Employees,Sales,Other,STAFF-712,244,Female,Human Resources,Married,Yes,Y,0,59,1,1376,25,Bachelor's Degree,1,2,96,1,2,2,4187,19255,2,11,4,2,80,2,38,1,18,0,14,7
Yes,Travel_Frequently,45 - 54,Current Employees,R&D,Technical Degree,STAFF-258,1126,Male,Sales Executive,Single,No,Y,3,33,0,441,2,High School,1,3,73,4,1,4,5940,26959,7,23,3,3,80,0,26,2,7,8,7,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 19:34:01 [INFO] Executing Step 3: CodeGenerator
2024-10-15 19:35:25 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:35:25 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,HR,Life Sciences,STAFF-461,918,Female,Research Scientist,Divorced,Yes,Y,1,37,1,374,17,Doctoral Degree,1,1,80,2,3,1,5295,19764,4,18,4,1,80,1,7,4,31,16,15,2
No,Travel_Rarely,Under 25,Current Employees,Sales,Other,STAFF-712,244,Female,Human Resources,Married,Yes,Y,0,59,1,1376,25,Bachelor's Degree,1,2,96,1,2,2,4187,19255,2,11,4,2,80,2,38,1,18,0,14,7
Yes,Travel_Frequently,45 - 54,Current Employees,R&D,Technical Degree,STAFF-258,1126,Male,Sales Executive,Single,No,Y,3,33,0,441,2,High School,1,3,73,4,1,4,5940,26959,7,23,3,3,80,0,26,2,7,8,7,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 19:35:25 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Filter male gender with even employee number and department as Sales
result = {"type": "string", "value": f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if (df['Gender'] == 'Male') and ((int(df.iloc[0]['Employee Number']) % 2 == 0) and (df['Department'].values[0] == 'Sales'))})}."}
            ```
            
2024-10-15 19:35:25 [INFO] Executing Step 4: CachePopulation
2024-10-15 19:35:25 [INFO] Executing Step 5: CodeCleaning
2024-10-15 19:35:25 [INFO] 
Code running:
```
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if df['Gender'] == 'Male' and (int(df.iloc[0]['Employee Number']) % 2 == 0 and df['Department'].values[0] == 'Sales')})}."}
        ```
2024-10-15 19:35:25 [INFO] Executing Step 6: CodeExecution
2024-10-15 19:35:25 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
  File "<string>", line 1, in <setcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

2024-10-15 19:35:25 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 19:35:25 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 19:35:25 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 19:35:25 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,HR,Life Sciences,STAFF-461,918,Female,Research Scientist,Divorced,Yes,Y,1,37,1,374,17,Doctoral Degree,1,1,80,2,3,1,5295,19764,4,18,4,1,80,1,7,4,31,16,15,2
No,Travel_Rarely,Under 25,Current Employees,Sales,Other,STAFF-712,244,Female,Human Resources,Married,Yes,Y,0,59,1,1376,25,Bachelor's Degree,1,2,96,1,2,2,4187,19255,2,11,4,2,80,2,38,1,18,0,14,7
Yes,Travel_Frequently,45 - 54,Current Employees,R&D,Technical Degree,STAFF-258,1126,Male,Sales Executive,Single,No,Y,3,33,0,441,2,High School,1,3,73,4,1,4,5940,26959,7,23,3,3,80,0,26,2,7,8,7,5
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

You generated this python code:
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if df['Gender'] == 'Male' and (int(df.iloc[0]['Employee Number']) % 2 == 0 and df['Department'].values[0] == 'Sales')})}."}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
  File "<string>", line 1, in <setcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


Fix the python code above and return the new python code:
2024-10-15 19:35:25 [INFO] Executing Step 1: CodeGenerator
2024-10-15 19:37:05 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 19:37:05 [ERROR] Pipeline failed on step 1: No code found in the response
2024-10-15 19:37:05 [ERROR] Pipeline failed on step 6: No code found in the response
2024-10-15 22:21:24 [INFO] Question: how many male gender are present in the dataset which have even Employee Number and Department as Sales ?
2024-10-15 22:21:24 [INFO] Running PandasAI with local LLM...
2024-10-15 22:21:24 [INFO] Prompt ID: 20f25102-9191-423f-9669-42af572931a4
2024-10-15 22:21:24 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 22:21:24 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 22:21:24 [INFO] Executing Step 1: CacheLookup
2024-10-15 22:21:24 [INFO] Using cached response
2024-10-15 22:21:24 [INFO] Executing Step 2: PromptGeneration
2024-10-15 22:21:24 [INFO] Executing Step 2: Skipping...
2024-10-15 22:21:24 [INFO] Executing Step 3: CodeGenerator
2024-10-15 22:21:24 [INFO] Executing Step 3: Skipping...
2024-10-15 22:21:24 [INFO] Executing Step 4: CachePopulation
2024-10-15 22:21:24 [INFO] Executing Step 4: Skipping...
2024-10-15 22:21:24 [INFO] Executing Step 5: CodeCleaning
2024-10-15 22:21:25 [INFO] 
Code running:
```
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if df['Gender'] == 'Male' and (int(df.iloc[0]['Employee Number']) % 2 == 0 and df['Department'].values[0] == 'Sales')})}."}
        ```
2024-10-15 22:21:25 [INFO] Executing Step 6: CodeExecution
2024-10-15 22:21:25 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
  File "<string>", line 1, in <setcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

2024-10-15 22:21:25 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 22:21:25 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 22:21:25 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 22:21:25 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Over 55,Current Employees,HR,Other,STAFF-1900,419,Female,Healthcare Representative,Single,No,Y,1,19,1,1311,26,Associates Degree,1,3,87,2,4,2,6870,15813,4,19,4,3,80,3,2,4,17,17,5,2
Yes,Non-Travel,35 - 44,Ex-Employees,R&D,Marketing,STAFF-2,325,Male,Research Scientist,Married,Yes,Y,4,46,1,1445,12,Bachelor's Degree,1,1,64,1,1,1,4284,25713,5,22,3,4,80,1,31,3,11,14,13,11
No,Travel_Frequently,45 - 54,Ex-Employees,Sales,Human Resources,STAFF-1507,1659,Male,Manager,Divorced,No,Y,0,59,0,1336,22,Doctoral Degree,1,2,50,3,5,4,3464,8277,6,23,3,1,80,2,32,2,7,3,2,9
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

You generated this python code:
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if df['Gender'] == 'Male' and (int(df.iloc[0]['Employee Number']) % 2 == 0 and df['Department'].values[0] == 'Sales')})}."}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
  File "<string>", line 1, in <setcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


Fix the python code above and return the new python code:
2024-10-15 22:21:25 [INFO] Executing Step 1: CodeGenerator
2024-10-15 22:23:32 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:23:32 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Over 55,Current Employees,HR,Other,STAFF-1900,419,Female,Healthcare Representative,Single,No,Y,1,19,1,1311,26,Associates Degree,1,3,87,2,4,2,6870,15813,4,19,4,3,80,3,2,4,17,17,5,2
Yes,Non-Travel,35 - 44,Ex-Employees,R&D,Marketing,STAFF-2,325,Male,Research Scientist,Married,Yes,Y,4,46,1,1445,12,Bachelor's Degree,1,1,64,1,1,1,4284,25713,5,22,3,4,80,1,31,3,11,14,13,11
No,Travel_Frequently,45 - 54,Ex-Employees,Sales,Human Resources,STAFF-1507,1659,Male,Manager,Divorced,No,Y,0,59,0,1336,22,Doctoral Degree,1,2,50,3,5,4,3464,8277,6,23,3,1,80,2,32,2,7,3,2,9
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

You generated this python code:
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len({df for df in dfs if df['Gender'] == 'Male' and (int(df.iloc[0]['Employee Number']) % 2 == 0 and df['Department'].values[0] == 'Sales')})}."}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
  File "<string>", line 1, in <setcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


Fix the python code above and return the new python code:
            
2024-10-15 22:23:32 [INFO] Code generated:
            ```
            Python
result = {'type': 'string', 'value': f"Number of males with even employee numbers in the Sales department is {len(sales_males)}."}

sales_males = sum(1 for df in dfs if (df['Department'].values[0] == 'Sales') & 
                  (int(df['Employee Number']) % 2 == 0) & 
                  (df['Gender'] == 'Male'))
            ```
            
2024-10-15 22:23:32 [INFO] Executing Step 2: CodeCleaning
2024-10-15 22:23:32 [INFO] 
Code running:
```
Python
result = {'type': 'string', 'value': f'Number of males with even employee numbers in the Sales department is {len(sales_males)}.'}
sales_males = sum(1 for df in dfs if (df['Department'].values[0] == 'Sales') & (int(df['Employee Number']) % 2 == 0) & (df['Gender'] == 'Male'))
        ```
2024-10-15 22:23:32 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-10-15 22:23:32 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-10-15 22:23:32 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 22:23:32 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 22:23:32 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Over 55,Current Employees,HR,Other,STAFF-1900,419,Female,Healthcare Representative,Single,No,Y,1,19,1,1311,26,Associates Degree,1,3,87,2,4,2,6870,15813,4,19,4,3,80,3,2,4,17,17,5,2
Yes,Non-Travel,35 - 44,Ex-Employees,R&D,Marketing,STAFF-2,325,Male,Research Scientist,Married,Yes,Y,4,46,1,1445,12,Bachelor's Degree,1,1,64,1,1,1,4284,25713,5,22,3,4,80,1,31,3,11,14,13,11
No,Travel_Frequently,45 - 54,Ex-Employees,Sales,Human Resources,STAFF-1507,1659,Male,Manager,Divorced,No,Y,0,59,0,1336,22,Doctoral Degree,1,2,50,3,5,4,3464,8277,6,23,3,1,80,2,32,2,7,3,2,9
</dataframe>


The user asked the following question:
### QUERY
 how many male gender are present in the dataset which have even Employee Number and Department as Sales ?

You generated this python code:
Python
result = {'type': 'string', 'value': f'Number of males with even employee numbers in the Sales department is {len(sales_males)}.'}
sales_males = sum(1 for df in dfs if (df['Department'].values[0] == 'Sales') & (int(df['Employee Number']) % 2 == 0) & (df['Gender'] == 'Male'))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-10-15 22:23:32 [INFO] Executing Step 1: CodeGenerator
2024-10-15 22:24:56 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:24:56 [ERROR] Pipeline failed on step 1: No code found in the response
2024-10-15 22:24:56 [ERROR] Pipeline failed on step 6: No code found in the response
2024-10-15 22:25:37 [INFO] Question: What is Average Age in the dataset?
2024-10-15 22:25:37 [INFO] Running PandasAI with local LLM...
2024-10-15 22:25:37 [INFO] Prompt ID: 06942c04-fcdd-452c-844f-1c6e3e22be75
2024-10-15 22:25:37 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 22:25:37 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 22:25:37 [INFO] Executing Step 1: CacheLookup
2024-10-15 22:25:37 [INFO] Executing Step 2: PromptGeneration
2024-10-15 22:25:37 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Non-Travel,Under 25,Current Employees,Sales,Human Resources,STAFF-138,284,Female,Human Resources,Married,No,Y,3,60,0,337,20,Master's Degree,1,1,74,1,3,3,4033,23177,4,14,3,4,80,2,15,4,18,2,15,15
No,Travel_Frequently,35 - 44,Current Employees,HR,Technical Degree,STAFF-1241,445,Female,Manufacturing Director,Divorced,Yes,Y,1,43,0,1268,14,High School,1,4,65,4,4,2,8793,4652,7,23,4,1,80,1,26,3,19,9,14,10
Yes,Travel_Rarely,25 - 34,Ex-Employees,R&D,Life Sciences,STAFF-725,1133,Male,Healthcare Representative,Single,No,Y,5,24,1,1436,26,Doctoral Degree,1,3,55,3,2,4,10976,22102,3,11,4,2,80,0,24,1,21,15,11,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Age in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 22:25:37 [INFO] Executing Step 3: CodeGenerator
2024-10-15 22:27:11 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:27:11 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Non-Travel,Under 25,Current Employees,Sales,Human Resources,STAFF-138,284,Female,Human Resources,Married,No,Y,3,60,0,337,20,Master's Degree,1,1,74,1,3,3,4033,23177,4,14,3,4,80,2,15,4,18,2,15,15
No,Travel_Frequently,35 - 44,Current Employees,HR,Technical Degree,STAFF-1241,445,Female,Manufacturing Director,Divorced,Yes,Y,1,43,0,1268,14,High School,1,4,65,4,4,2,8793,4652,7,23,4,1,80,1,26,3,19,9,14,10
Yes,Travel_Rarely,25 - 34,Ex-Employees,R&D,Life Sciences,STAFF-725,1133,Male,Healthcare Representative,Single,No,Y,5,24,1,1436,26,Doctoral Degree,1,3,55,3,2,4,10976,22102,3,11,4,2,80,0,24,1,21,15,11,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Age in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 22:27:11 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Load the dataframes from the list into a single dataframe
df = pd.concat(dfs)

# Calculate the average age
average_age = df['Age'].mean()

# Declare result var:
result = {"type": "number", "value": average_age}

print(result)
            ```
            
2024-10-15 22:27:11 [INFO] Executing Step 4: CachePopulation
2024-10-15 22:27:11 [INFO] Executing Step 5: CodeCleaning
2024-10-15 22:27:11 [INFO] 
Code running:
```
df = pd.concat(dfs)
average_age = df['Age'].mean()
result = {'type': 'number', 'value': average_age}
print(result)
        ```
2024-10-15 22:27:11 [INFO] Executing Step 6: CodeExecution
2024-10-15 22:27:11 [INFO] Executing Step 7: ResultValidation
2024-10-15 22:27:11 [INFO] Answer: {'type': 'number', 'value': 36.923809523809524}
2024-10-15 22:27:11 [INFO] Executing Step 8: ResultParsing
2024-10-15 22:28:27 [INFO] Question: What is Average Monthly Income of Male Gender in the dataset?
2024-10-15 22:28:27 [INFO] Running PandasAI with local LLM...
2024-10-15 22:28:27 [INFO] Prompt ID: 20bb4800-035b-47ed-8b88-c059620973ee
2024-10-15 22:28:27 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 22:28:27 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 22:28:27 [INFO] Executing Step 1: CacheLookup
2024-10-15 22:28:27 [INFO] Executing Step 2: PromptGeneration
2024-10-15 22:28:27 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,45 - 54,Current Employees,R&D,Human Resources,STAFF-1764,72,Male,Research Scientist,Married,No,Y,6,53,1,1169,2,Doctoral Degree,1,4,53,2,1,4,4448,9314,6,23,4,3,80,2,13,3,9,0,2,16
Yes,Travel_Frequently,Under 25,Ex-Employees,Sales,Medical,STAFF-382,75,Male,Healthcare Representative,Divorced,Yes,Y,5,30,0,155,18,Master's Degree,1,3,44,1,3,1,4723,15963,3,16,3,2,80,3,24,4,12,8,4,10
No,Non-Travel,35 - 44,Ex-Employees,HR,Life Sciences,STAFF-1863,155,Female,Sales Executive,Single,Yes,Y,0,29,0,244,10,Bachelor's Degree,1,1,39,3,2,2,19665,22984,8,13,3,1,80,0,40,1,26,1,0,6
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Male Gender in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 22:28:27 [INFO] Executing Step 3: CodeGenerator
2024-10-15 22:30:06 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:30:06 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,45 - 54,Current Employees,R&D,Human Resources,STAFF-1764,72,Male,Research Scientist,Married,No,Y,6,53,1,1169,2,Doctoral Degree,1,4,53,2,1,4,4448,9314,6,23,4,3,80,2,13,3,9,0,2,16
Yes,Travel_Frequently,Under 25,Ex-Employees,Sales,Medical,STAFF-382,75,Male,Healthcare Representative,Divorced,Yes,Y,5,30,0,155,18,Master's Degree,1,3,44,1,3,1,4723,15963,3,16,3,2,80,3,24,4,12,8,4,10
No,Non-Travel,35 - 44,Ex-Employees,HR,Life Sciences,STAFF-1863,155,Female,Sales Executive,Single,Yes,Y,0,29,0,244,10,Bachelor's Degree,1,1,39,3,2,2,19665,22984,8,13,3,1,80,0,40,1,26,1,0,6
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Male Gender in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 22:30:06 [INFO] Code generated:
            ```
            import pandas as pd
import numpy as np

# Assume dfs is already declared as a list of DataFrames
result = {}

for df in dfs:
    # Filter out non-male records
    male_df = df[df['Gender'] == 'Male']
    
    # Calculate Average Monthly Income for males
    avg_monthly_income = np.mean(male_df['Monthly Income'].astype(float))
    
    result = {'type': 'number', 'value': avg_monthly_income}
    break  # Only calculate once, since all DataFrames have the same structure

print(result)
            ```
            
2024-10-15 22:30:06 [INFO] Executing Step 4: CachePopulation
2024-10-15 22:30:06 [INFO] Executing Step 5: CodeCleaning
2024-10-15 22:30:06 [INFO] 
Code running:
```
result = {}
for df in dfs:
    male_df = df[df['Gender'] == 'Male']
    avg_monthly_income = np.mean(male_df['Monthly Income'].astype(float))
    result = {'type': 'number', 'value': avg_monthly_income}
    break
print(result)
        ```
2024-10-15 22:30:06 [INFO] Executing Step 6: CodeExecution
2024-10-15 22:30:06 [INFO] Executing Step 7: ResultValidation
2024-10-15 22:30:06 [INFO] Answer: {'type': 'number', 'value': 6380.507936507936}
2024-10-15 22:30:06 [INFO] Executing Step 8: ResultParsing
2024-10-15 22:50:08 [INFO] Question: What is Average Monthly Income of Female Gender in the dataset?
2024-10-15 22:50:08 [INFO] Running PandasAI with local LLM...
2024-10-15 22:50:08 [INFO] Prompt ID: 628ff9f7-5f27-4574-b6ed-bb8042b80a18
2024-10-15 22:50:08 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 22:50:08 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 22:50:08 [INFO] Executing Step 1: CacheLookup
2024-10-15 22:50:08 [INFO] Executing Step 2: PromptGeneration
2024-10-15 22:50:08 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Current Employees,R&D,Life Sciences,STAFF-1014,1520,Male,Healthcare Representative,Married,No,Y,4,49,1,461,24,Associates Degree,1,1,32,4,5,1,2394,15471,1,18,4,1,80,2,36,1,12,11,1,8
No,Travel_Rarely,35 - 44,Ex-Employees,HR,Marketing,STAFF-1898,1035,Female,Sales Executive,Divorced,Yes,Y,6,35,0,1050,6,High School,1,3,49,2,3,4,4941,10092,3,13,3,4,80,3,25,3,17,4,0,10
No,Non-Travel,Under 25,Current Employees,Sales,Other,STAFF-862,53,Male,Manufacturing Director,Single,No,Y,2,39,1,1029,14,Bachelor's Degree,1,4,72,3,1,3,7969,4992,8,17,4,2,80,0,37,2,29,18,13,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Female Gender in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 22:50:08 [INFO] Executing Step 3: CodeGenerator
2024-10-15 22:51:36 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:51:36 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Current Employees,R&D,Life Sciences,STAFF-1014,1520,Male,Healthcare Representative,Married,No,Y,4,49,1,461,24,Associates Degree,1,1,32,4,5,1,2394,15471,1,18,4,1,80,2,36,1,12,11,1,8
No,Travel_Rarely,35 - 44,Ex-Employees,HR,Marketing,STAFF-1898,1035,Female,Sales Executive,Divorced,Yes,Y,6,35,0,1050,6,High School,1,3,49,2,3,4,4941,10092,3,13,3,4,80,3,25,3,17,4,0,10
No,Non-Travel,Under 25,Current Employees,Sales,Other,STAFF-862,53,Male,Manufacturing Director,Single,No,Y,2,39,1,1029,14,Bachelor's Degree,1,4,72,3,1,3,7969,4992,8,17,4,2,80,0,37,2,29,18,13,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Female Gender in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 22:51:36 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

dfs = []  # list to store dataframes
# Rest of your code...

result = {}
average_female_income = dfs[0]['Monthly Income'][dfs[0]['Gender'] == 'Female'].mean()
result = {"type": "number", "value": average_female_income}

print(result)
            ```
            
2024-10-15 22:51:36 [INFO] Executing Step 4: CachePopulation
2024-10-15 22:51:36 [INFO] Executing Step 5: CodeCleaning
2024-10-15 22:51:36 [INFO] 
Code running:
```
result = {}
average_female_income = dfs[0]['Monthly Income'][dfs[0]['Gender'] == 'Female'].mean()
result = {'type': 'number', 'value': average_female_income}
print(result)
        ```
2024-10-15 22:51:36 [INFO] Executing Step 6: CodeExecution
2024-10-15 22:51:37 [INFO] Executing Step 7: ResultValidation
2024-10-15 22:51:37 [INFO] Answer: {'type': 'number', 'value': 6686.566326530612}
2024-10-15 22:51:37 [INFO] Executing Step 8: ResultParsing
2024-10-15 22:52:26 [INFO] Question: What is Average Monthly Income of Female Gender from Sales Department in the dataset?
2024-10-15 22:52:26 [INFO] Running PandasAI with local LLM...
2024-10-15 22:52:26 [INFO] Prompt ID: 36fa18cf-34c1-42c4-a4b9-9d8d9d6d27bd
2024-10-15 22:52:26 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-15 22:52:26 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-15 22:52:26 [INFO] Executing Step 1: CacheLookup
2024-10-15 22:52:26 [INFO] Executing Step 2: PromptGeneration
2024-10-15 22:52:26 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-15 22:52:26 [INFO] Executing Step 3: CodeGenerator
2024-10-15 22:54:12 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:54:12 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-15 22:54:12 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import numpy as np

# Initialize result variable
result = {}

# Extract all dataframes from list
dfs = [df for df in dfs]

# Filter Female Gender and Sales Department
female_sales = [df for df in dfs if (df['Gender'] == 'Female') & (df['Department'] == 'Sales')]

# Calculate Average Monthly Income
average_monthly_income = np.mean([int(x) for x in female_sales['Monthly Income'].tolist()])

# Combine result as dictionary of type and value
result = {"type": "number", "value": average_monthly_income}

print(result)
            ```
            
2024-10-15 22:54:12 [INFO] Executing Step 4: CachePopulation
2024-10-15 22:54:12 [INFO] Executing Step 5: CodeCleaning
2024-10-15 22:54:12 [INFO] 
Code running:
```
result = {}
female_sales = [df for df in dfs if (df['Gender'] == 'Female') & (df['Department'] == 'Sales')]
average_monthly_income = np.mean([int(x) for x in female_sales['Monthly Income'].tolist()])
result = {'type': 'number', 'value': average_monthly_income}
print(result)
        ```
2024-10-15 22:54:12 [INFO] Executing Step 6: CodeExecution
2024-10-15 22:54:12 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "<string>", line 2, in <listcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

2024-10-15 22:54:12 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-10-15 22:54:12 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 22:54:12 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 22:54:12 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
result = {}
female_sales = [df for df in dfs if (df['Gender'] == 'Female') & (df['Department'] == 'Sales')]
average_monthly_income = np.mean([int(x) for x in female_sales['Monthly Income'].tolist()])
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "<string>", line 2, in <listcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


Fix the python code above and return the new python code:
2024-10-15 22:54:12 [INFO] Executing Step 1: CodeGenerator
2024-10-15 22:55:15 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:55:15 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
result = {}
female_sales = [df for df in dfs if (df['Gender'] == 'Female') & (df['Department'] == 'Sales')]
average_monthly_income = np.mean([int(x) for x in female_sales['Monthly Income'].tolist()])
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "<string>", line 2, in <listcomp>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 1527, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().


Fix the python code above and return the new python code:
            
2024-10-15 22:55:15 [INFO] Code generated:
            ```
            import numpy as np

female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)
            ```
            
2024-10-15 22:55:15 [INFO] Executing Step 2: CodeCleaning
2024-10-15 22:55:15 [INFO] 
Code running:
```
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)
        ```
2024-10-15 22:55:15 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'

2024-10-15 22:55:15 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-10-15 22:55:15 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 22:55:15 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 22:55:15 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
2024-10-15 22:55:15 [INFO] Executing Step 1: CodeGenerator
2024-10-15 22:56:02 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:56:02 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
            
2024-10-15 22:56:02 [INFO] Code generated:
            ```
            import numpy as np
import pandas as pd

female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)
            ```
            
2024-10-15 22:56:02 [INFO] Executing Step 2: CodeCleaning
2024-10-15 22:56:02 [INFO] 
Code running:
```
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)
        ```
2024-10-15 22:56:02 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'

2024-10-15 22:56:02 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-10-15 22:56:02 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-10-15 22:56:02 [INFO] Executing Step 0: ErrorPromptGeneration
2024-10-15 22:56:02 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
2024-10-15 22:56:02 [INFO] Executing Step 1: CodeGenerator
2024-10-15 22:57:05 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-15 22:57:05 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,Under 25,Current Employees,HR,Other,STAFF-1712,1617,Male,Human Resources,Single,Yes,Y,0,26,1,177,4,Master's Degree,1,2,72,4,3,3,2684,16154,7,18,4,1,80,2,29,3,19,4,12,0
Yes,Travel_Rarely,45 - 54,Current Employees,R&D,Technical Degree,STAFF-1,96,Female,Research Scientist,Married,No,Y,2,58,0,304,18,Bachelor's Degree,1,3,54,1,2,4,2809,4060,0,20,3,2,80,3,20,1,6,17,5,17
No,Travel_Frequently,25 - 34,Ex-Employees,Sales,Human Resources,STAFF-757,2023,Male,Laboratory Technician,Divorced,Yes,Y,3,27,1,1470,28,Doctoral Degree,1,4,37,2,5,1,10976,13243,5,23,4,4,80,1,17,2,33,12,10,12
</dataframe>


The user asked the following question:
### QUERY
 What is Average Monthly Income of Female Gender from Sales Department in the dataset?

You generated this python code:
female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(female_sales.values.tolist())
result = {'type': 'number', 'value': average_monthly_income}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
AttributeError: 'list' object has no attribute 'loc'


Fix the python code above and return the new python code:
            
2024-10-15 22:57:05 [INFO] Code generated:
            ```
            import numpy as np
from io import StringIO

# assuming dfs is your dataframe and its content is in the format of your provided data frame

dfs = pd.read_csv(StringIO("""your dataframe content"""))  # replace with your actual file name or content

female_sales = dfs.loc[(dfs['Gender'] == 'Female') & (dfs['Department'] == 'Sales'), ['Monthly Income']]
average_monthly_income = np.mean(list(map(int, female_sales.iloc[:, 0].tolist())))
result = {'type': 'number', 'value': average_monthly_income}
print(result)
            ```
            
2024-10-15 22:57:05 [INFO] Executing Step 2: CodeCleaning
2024-10-15 22:57:05 [ERROR] Pipeline failed on step 2: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-10-15 22:57:05 [ERROR] Pipeline failed on step 6: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-10-16 07:31:58 [INFO] Question: how many males are present in the dataset?
2024-10-16 07:31:58 [INFO] Running PandasAI with local LLM...
2024-10-16 07:31:58 [INFO] Prompt ID: d7a97735-5fdd-4c0b-a88d-dfdb1872c8ad
2024-10-16 07:31:58 [INFO] Executing Pipeline: GenerateChatPipeline
2024-10-16 07:31:58 [INFO] Executing Step 0: ValidatePipelineInput
2024-10-16 07:31:58 [INFO] Executing Step 1: CacheLookup
2024-10-16 07:31:58 [INFO] Executing Step 2: PromptGeneration
2024-10-16 07:31:58 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Ex-Employees,R&D,Other,STAFF-331,879,Female,Research Director,Married,Yes,Y,5,32,1,986,19,Doctoral Degree,1,4,72,3,5,2,3691,24440,9,24,4,2,80,2,37,2,34,14,2,5
Yes,Travel_Frequently,45 - 54,Current Employees,HR,Technical Degree,STAFF-287,206,Male,Research Scientist,Divorced,No,Y,2,58,0,726,17,High School,1,3,44,4,1,4,2153,26283,7,23,3,3,80,3,38,1,10,11,4,10
No,Non-Travel,Under 25,Current Employees,Sales,Life Sciences,STAFF-1460,1373,Female,Sales Executive,Single,Yes,Y,1,53,1,1092,22,Master's Degree,1,2,76,1,3,3,9602,2373,3,20,3,1,80,1,13,4,29,2,8,14
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-10-16 07:31:58 [INFO] Executing Step 3: CodeGenerator
2024-10-16 07:33:24 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-10-16 07:33:24 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Ex-Employees,R&D,Other,STAFF-331,879,Female,Research Director,Married,Yes,Y,5,32,1,986,19,Doctoral Degree,1,4,72,3,5,2,3691,24440,9,24,4,2,80,2,37,2,34,14,2,5
Yes,Travel_Frequently,45 - 54,Current Employees,HR,Technical Degree,STAFF-287,206,Male,Research Scientist,Divorced,No,Y,2,58,0,726,17,High School,1,3,44,4,1,4,2153,26283,7,23,3,3,80,3,38,1,10,11,4,10
No,Non-Travel,Under 25,Current Employees,Sales,Life Sciences,STAFF-1460,1373,Female,Sales Executive,Single,Yes,Y,1,53,1,1092,22,Master's Degree,1,2,76,1,3,3,9602,2373,3,20,3,1,80,1,13,4,29,2,8,14
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many males are present in the dataset?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-10-16 07:33:24 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Query 1: How many males are present in the dataset?
male_count = 0

for df in dfs:
    male_count += len(df[df['Gender'] == 'Male'])

result = {"type": "number", "value": male_count}
            ```
            
2024-10-16 07:33:24 [INFO] Executing Step 4: CachePopulation
2024-10-16 07:33:24 [INFO] Executing Step 5: CodeCleaning
2024-10-16 07:33:24 [INFO] 
Code running:
```
male_count = 0
for df in dfs:
    male_count += len(df[df['Gender'] == 'Male'])
result = {'type': 'number', 'value': male_count}
        ```
2024-10-16 07:33:24 [INFO] Executing Step 6: CodeExecution
2024-10-16 07:33:24 [INFO] Executing Step 7: ResultValidation
2024-10-16 07:33:24 [INFO] Answer: {'type': 'number', 'value': 882}
2024-10-16 07:33:24 [INFO] Executing Step 8: ResultParsing
2024-11-12 10:41:09 [INFO] Question: How many people are from sales department ?
2024-11-12 10:41:09 [INFO] Running PandasAI with local LLM...
2024-11-12 10:41:09 [INFO] Prompt ID: b02b9c60-fba4-4c5b-8a11-7f78567b224c
2024-11-12 10:41:09 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 10:41:09 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 10:41:09 [INFO] Executing Step 1: CacheLookup
2024-11-12 10:41:09 [INFO] Executing Step 2: PromptGeneration
2024-11-12 10:41:09 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,25 - 34,Current Employees,R&D,Marketing,STAFF-1234,304,Male,Research Scientist,Divorced,Yes,Y,1,30,0,906,26,Associates Degree,1,2,61,2,4,3,13525,12826,1,22,3,4,80,3,15,2,8,12,13,11
Yes,Travel_Frequently,45 - 54,Ex-Employees,HR,Life Sciences,STAFF-1240,64,Male,Manager,Married,No,Y,3,38,1,152,18,Master's Degree,1,3,45,1,5,4,14275,5640,7,13,4,1,80,1,32,4,0,10,0,10
Yes,Non-Travel,35 - 44,Ex-Employees,Sales,Other,STAFF-1466,1137,Female,Research Director,Single,No,Y,4,44,0,1476,12,Doctoral Degree,1,1,65,3,2,2,2062,9238,0,14,3,3,80,2,6,1,14,11,6,7
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many people are from sales department ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 10:41:09 [INFO] Executing Step 3: CodeGenerator
2024-11-12 10:42:25 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:42:25 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,25 - 34,Current Employees,R&D,Marketing,STAFF-1234,304,Male,Research Scientist,Divorced,Yes,Y,1,30,0,906,26,Associates Degree,1,2,61,2,4,3,13525,12826,1,22,3,4,80,3,15,2,8,12,13,11
Yes,Travel_Frequently,45 - 54,Ex-Employees,HR,Life Sciences,STAFF-1240,64,Male,Manager,Married,No,Y,3,38,1,152,18,Master's Degree,1,3,45,1,5,4,14275,5640,7,13,4,1,80,1,32,4,0,10,0,10
Yes,Non-Travel,35 - 44,Ex-Employees,Sales,Other,STAFF-1466,1137,Female,Research Director,Single,No,Y,4,44,0,1476,12,Doctoral Degree,1,1,65,3,2,2,2062,9238,0,14,3,3,80,2,6,1,14,11,6,7
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many people are from sales department ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 10:42:25 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Update the dfs list with your DataFrame data
dfs = [df]  # assume df is a pd.DataFrame object

# Iterate through each DataFrame in the list and filter out the rows where Department equals 'Sales'
result = {"type": "number", "value": len([row for df in dfs for index, row in df.iterrows() if row['Department'] == 'Sales'])}
print(result)
            ```
            
2024-11-12 10:42:25 [INFO] Executing Step 4: CachePopulation
2024-11-12 10:42:25 [INFO] Executing Step 5: CodeCleaning
2024-11-12 10:42:25 [INFO] 
Code running:
```
result = {'type': 'number', 'value': len([row for df in dfs for index, row in df.iterrows() if row['Department'] == 'Sales'])}
print(result)
        ```
2024-11-12 10:42:25 [INFO] Executing Step 6: CodeExecution
2024-11-12 10:42:25 [INFO] Executing Step 7: ResultValidation
2024-11-12 10:42:25 [INFO] Answer: {'type': 'number', 'value': 446}
2024-11-12 10:42:25 [INFO] Executing Step 8: ResultParsing
2024-11-12 10:44:07 [INFO] Question: How many people are from sales department having gender as female?
2024-11-12 10:44:07 [INFO] Running PandasAI with local LLM...
2024-11-12 10:44:07 [INFO] Prompt ID: 78c46a0e-904a-42da-8a21-47e05ab13d41
2024-11-12 10:44:07 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 10:44:07 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 10:44:07 [INFO] Executing Step 1: CacheLookup
2024-11-12 10:44:07 [INFO] Executing Step 2: PromptGeneration
2024-11-12 10:44:07 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,R&D,Other,STAFF-832,926,Male,Laboratory Technician,Married,No,Y,4,38,1,432,27,Bachelor's Degree,1,4,47,4,2,2,5415,9647,5,23,3,2,80,3,37,3,6,14,2,10
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Human Resources,STAFF-662,1599,Female,Human Resources,Divorced,Yes,Y,2,58,0,1323,26,High School,1,2,61,3,5,3,2904,8532,0,19,4,3,80,2,16,2,3,10,13,14
Yes,Travel_Rarely,35 - 44,Current Employees,Sales,Medical,STAFF-267,816,Male,Research Scientist,Single,Yes,Y,3,18,1,567,11,Master's Degree,1,3,79,2,1,1,2795,20623,9,24,3,1,80,1,0,1,31,9,4,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many people are from sales department having gender as female?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 10:44:07 [INFO] Executing Step 3: CodeGenerator
2024-11-12 10:45:03 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:45:03 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,R&D,Other,STAFF-832,926,Male,Laboratory Technician,Married,No,Y,4,38,1,432,27,Bachelor's Degree,1,4,47,4,2,2,5415,9647,5,23,3,2,80,3,37,3,6,14,2,10
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Human Resources,STAFF-662,1599,Female,Human Resources,Divorced,Yes,Y,2,58,0,1323,26,High School,1,2,61,3,5,3,2904,8532,0,19,4,3,80,2,16,2,3,10,13,14
Yes,Travel_Rarely,35 - 44,Current Employees,Sales,Medical,STAFF-267,816,Male,Research Scientist,Single,Yes,Y,3,18,1,567,11,Master's Degree,1,3,79,2,1,1,2795,20623,9,24,3,1,80,1,0,1,31,9,4,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many people are from sales department having gender as female?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 10:45:03 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

result = {}

dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).index.get_loc(('Sales', 'Female'))

result["type"] = "number"
result["value"] = dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc[('Sales', 'Female')]

# Print the result
print(f"The number of people from Sales department with gender as female is: {dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc[('Sales', 'Female')]}.")
            ```
            
2024-11-12 10:45:03 [INFO] Executing Step 4: CachePopulation
2024-11-12 10:45:03 [INFO] Executing Step 5: CodeCleaning
2024-11-12 10:45:03 [INFO] 
Code running:
```
result = {}
dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).index.get_loc(('Sales', 'Female'))
result['type'] = 'number'
result['value'] = dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']
print(f"The number of people from Sales department with gender as female is: {dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']}.")
        ```
2024-11-12 10:45:03 [INFO] Executing Step 6: CodeExecution
2024-11-12 10:45:03 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3802, in get_loc
    return self._engine.get_loc(casted_key)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 165, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 5745, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 5753, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: ('Sales', 'Female')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3804, in get_loc
    raise KeyError(key) from err
KeyError: ('Sales', 'Female')

2024-11-12 10:45:03 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-12 10:45:03 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 10:45:03 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 10:45:03 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,R&D,Other,STAFF-832,926,Male,Laboratory Technician,Married,No,Y,4,38,1,432,27,Bachelor's Degree,1,4,47,4,2,2,5415,9647,5,23,3,2,80,3,37,3,6,14,2,10
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Human Resources,STAFF-662,1599,Female,Human Resources,Divorced,Yes,Y,2,58,0,1323,26,High School,1,2,61,3,5,3,2904,8532,0,19,4,3,80,2,16,2,3,10,13,14
Yes,Travel_Rarely,35 - 44,Current Employees,Sales,Medical,STAFF-267,816,Male,Research Scientist,Single,Yes,Y,3,18,1,567,11,Master's Degree,1,3,79,2,1,1,2795,20623,9,24,3,1,80,1,0,1,31,9,4,13
</dataframe>


The user asked the following question:
### QUERY
 How many people are from sales department having gender as female?

You generated this python code:
result = {}
dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).index.get_loc(('Sales', 'Female'))
result['type'] = 'number'
result['value'] = dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']
print(f"The number of people from Sales department with gender as female is: {dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']}.")

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3802, in get_loc
    return self._engine.get_loc(casted_key)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 165, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 5745, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 5753, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: ('Sales', 'Female')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3804, in get_loc
    raise KeyError(key) from err
KeyError: ('Sales', 'Female')


Fix the python code above and return the new python code:
2024-11-12 10:45:03 [INFO] Executing Step 1: CodeGenerator
2024-11-12 10:46:20 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:46:20 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,R&D,Other,STAFF-832,926,Male,Laboratory Technician,Married,No,Y,4,38,1,432,27,Bachelor's Degree,1,4,47,4,2,2,5415,9647,5,23,3,2,80,3,37,3,6,14,2,10
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Human Resources,STAFF-662,1599,Female,Human Resources,Divorced,Yes,Y,2,58,0,1323,26,High School,1,2,61,3,5,3,2904,8532,0,19,4,3,80,2,16,2,3,10,13,14
Yes,Travel_Rarely,35 - 44,Current Employees,Sales,Medical,STAFF-267,816,Male,Research Scientist,Single,Yes,Y,3,18,1,567,11,Master's Degree,1,3,79,2,1,1,2795,20623,9,24,3,1,80,1,0,1,31,9,4,13
</dataframe>


The user asked the following question:
### QUERY
 How many people are from sales department having gender as female?

You generated this python code:
result = {}
dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).index.get_loc(('Sales', 'Female'))
result['type'] = 'number'
result['value'] = dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']
print(f"The number of people from Sales department with gender as female is: {dfs[0].groupby(['Department', 'Gender']).size().unstack(fill_value=0).loc['Sales', 'Female']}.")

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3802, in get_loc
    return self._engine.get_loc(casted_key)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas\_libs\index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 165, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 5745, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 5753, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: ('Sales', 'Female')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py", line 3804, in get_loc
    raise KeyError(key) from err
KeyError: ('Sales', 'Female')


Fix the python code above and return the new python code:
            
2024-11-12 10:46:20 [INFO] Code generated:
            ```
            result = {}
sales_females = dfs[0].pivot_table(index='Department',columns='Gender',values='size',aggfunc='sum').loc['Sales','Female']
result['type'] = 'number'
result['value'] = sales_females if not pd.isna(sales_females) else 0
print(f"The number of people from Sales department with gender as female is: {sales_females}.")
            ```
            
2024-11-12 10:46:20 [INFO] Executing Step 2: CodeCleaning
2024-11-12 10:46:20 [INFO] 
Code running:
```
result = {}
sales_females = dfs[0].pivot_table(index='Department', columns='Gender', values='size', aggfunc='sum').loc['Sales', 'Female']
result['type'] = 'number'
result['value'] = sales_females if not pd.isna(sales_females) else 0
print(f'The number of people from Sales department with gender as female is: {sales_females}.')
        ```
2024-11-12 10:46:20 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\frame.py", line 8731, in pivot_table
    return pivot_table(
           ^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\pivot.py", line 97, in pivot_table
    table = __internal_pivot_table(
            ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\pivot.py", line 143, in __internal_pivot_table
    raise KeyError(i)
KeyError: 'size'

2024-11-12 10:46:20 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-12 10:46:20 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 10:46:20 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 10:46:20 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,R&D,Other,STAFF-832,926,Male,Laboratory Technician,Married,No,Y,4,38,1,432,27,Bachelor's Degree,1,4,47,4,2,2,5415,9647,5,23,3,2,80,3,37,3,6,14,2,10
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Human Resources,STAFF-662,1599,Female,Human Resources,Divorced,Yes,Y,2,58,0,1323,26,High School,1,2,61,3,5,3,2904,8532,0,19,4,3,80,2,16,2,3,10,13,14
Yes,Travel_Rarely,35 - 44,Current Employees,Sales,Medical,STAFF-267,816,Male,Research Scientist,Single,Yes,Y,3,18,1,567,11,Master's Degree,1,3,79,2,1,1,2795,20623,9,24,3,1,80,1,0,1,31,9,4,13
</dataframe>


The user asked the following question:
### QUERY
 How many people are from sales department having gender as female?

You generated this python code:
result = {}
sales_females = dfs[0].pivot_table(index='Department', columns='Gender', values='size', aggfunc='sum').loc['Sales', 'Female']
result['type'] = 'number'
result['value'] = sales_females if not pd.isna(sales_females) else 0
print(f'The number of people from Sales department with gender as female is: {sales_females}.')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\frame.py", line 8731, in pivot_table
    return pivot_table(
           ^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\pivot.py", line 97, in pivot_table
    table = __internal_pivot_table(
            ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\pivot.py", line 143, in __internal_pivot_table
    raise KeyError(i)
KeyError: 'size'


Fix the python code above and return the new python code:
2024-11-12 10:46:20 [INFO] Executing Step 1: CodeGenerator
2024-11-12 10:47:36 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:47:36 [ERROR] Pipeline failed on step 1: No code found in the response
2024-11-12 10:47:36 [ERROR] Pipeline failed on step 6: No code found in the response
2024-11-12 10:48:06 [INFO] Question: How many female are present being single?
2024-11-12 10:48:06 [INFO] Running PandasAI with local LLM...
2024-11-12 10:48:06 [INFO] Prompt ID: 17cde487-9667-471e-875e-adba023c1831
2024-11-12 10:48:06 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 10:48:06 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 10:48:06 [INFO] Executing Step 1: CacheLookup
2024-11-12 10:48:06 [INFO] Executing Step 2: PromptGeneration
2024-11-12 10:48:06 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Ex-Employees,HR,Other,STAFF-1045,1630,Male,Laboratory Technician,Married,Yes,Y,2,24,0,654,25,Doctoral Degree,1,1,42,3,3,3,4723,12761,6,20,3,3,80,3,18,2,16,5,5,8
No,Travel_Rarely,35 - 44,Current Employees,Sales,Human Resources,STAFF-1018,1324,Female,Sales Executive,Divorced,Yes,Y,6,47,1,737,4,High School,1,3,85,2,2,4,4317,3142,2,21,4,2,80,1,20,4,32,6,7,11
No,Non-Travel,Under 25,Current Employees,R&D,Technical Degree,STAFF-1055,1081,Female,Healthcare Representative,Single,No,Y,3,56,0,1457,27,Associates Degree,1,2,80,4,1,1,2728,23070,1,18,4,1,80,0,34,1,34,15,8,4
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many female are present being single?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 10:48:06 [INFO] Executing Step 3: CodeGenerator
2024-11-12 10:48:55 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:48:55 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Ex-Employees,HR,Other,STAFF-1045,1630,Male,Laboratory Technician,Married,Yes,Y,2,24,0,654,25,Doctoral Degree,1,1,42,3,3,3,4723,12761,6,20,3,3,80,3,18,2,16,5,5,8
No,Travel_Rarely,35 - 44,Current Employees,Sales,Human Resources,STAFF-1018,1324,Female,Sales Executive,Divorced,Yes,Y,6,47,1,737,4,High School,1,3,85,2,2,4,4317,3142,2,21,4,2,80,1,20,4,32,6,7,11
No,Non-Travel,Under 25,Current Employees,R&D,Technical Degree,STAFF-1055,1081,Female,Healthcare Representative,Single,No,Y,3,56,0,1457,27,Associates Degree,1,2,80,4,1,1,2728,23070,1,18,4,1,80,0,34,1,34,15,8,4
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 How many female are present being single?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 10:48:55 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
from collections import Counter

# Write code here

dfs = [pd.read_csv("data.csv")]

result = {}

female_single_count = dfs[0].pivot_table(values='Gender', index=None, columns='Marital Status').loc['Single', 'Female'].values[0]

result = {"type": "string", "value": f"There are {female_single_count} female employees being single."}

print(result)
            ```
            
2024-11-12 10:48:55 [INFO] Executing Step 4: CachePopulation
2024-11-12 10:48:55 [INFO] Executing Step 5: CodeCleaning
2024-11-12 10:48:55 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 10:48:55 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 10:48:55 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Ex-Employees,HR,Other,STAFF-1045,1630,Male,Laboratory Technician,Married,Yes,Y,2,24,0,654,25,Doctoral Degree,1,1,42,3,3,3,4723,12761,6,20,3,3,80,3,18,2,16,5,5,8
No,Travel_Rarely,35 - 44,Current Employees,Sales,Human Resources,STAFF-1018,1324,Female,Sales Executive,Divorced,Yes,Y,6,47,1,737,4,High School,1,3,85,2,2,4,4317,3142,2,21,4,2,80,1,20,4,32,6,7,11
No,Non-Travel,Under 25,Current Employees,R&D,Technical Degree,STAFF-1055,1081,Female,Healthcare Representative,Single,No,Y,3,56,0,1457,27,Associates Degree,1,2,80,4,1,1,2728,23070,1,18,4,1,80,0,34,1,34,15,8,4
</dataframe>


The user asked the following question:
### QUERY
 How many female are present being single?

You generated this python code:
# TODO: import the required dependencies
import pandas as pd
from collections import Counter

# Write code here

dfs = [pd.read_csv("data.csv")]

result = {}

female_single_count = dfs[0].pivot_table(values='Gender', index=None, columns='Marital Status').loc['Single', 'Female'].values[0]

result = {"type": "string", "value": f"There are {female_single_count} female employees being single."}

print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 95, in execute
    code_to_run = self.get_code_to_run(input, code_context)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 152, in get_code_to_run
    code_to_run = self._clean_code(code, context)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 487, in _clean_code
    self._check_imports(node)
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 585, in _check_imports
    raise BadImportError(library)
pandasai.exceptions.BadImportError: Generated code includes import of collections which is not in whitelist.


Fix the python code above and return the new python code:
2024-11-12 10:48:55 [INFO] Executing Step 1: CodeGenerator
2024-11-12 10:50:01 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 10:50:01 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,Over 55,Ex-Employees,HR,Other,STAFF-1045,1630,Male,Laboratory Technician,Married,Yes,Y,2,24,0,654,25,Doctoral Degree,1,1,42,3,3,3,4723,12761,6,20,3,3,80,3,18,2,16,5,5,8
No,Travel_Rarely,35 - 44,Current Employees,Sales,Human Resources,STAFF-1018,1324,Female,Sales Executive,Divorced,Yes,Y,6,47,1,737,4,High School,1,3,85,2,2,4,4317,3142,2,21,4,2,80,1,20,4,32,6,7,11
No,Non-Travel,Under 25,Current Employees,R&D,Technical Degree,STAFF-1055,1081,Female,Healthcare Representative,Single,No,Y,3,56,0,1457,27,Associates Degree,1,2,80,4,1,1,2728,23070,1,18,4,1,80,0,34,1,34,15,8,4
</dataframe>


The user asked the following question:
### QUERY
 How many female are present being single?

You generated this python code:
# TODO: import the required dependencies
import pandas as pd
from collections import Counter

# Write code here

dfs = [pd.read_csv("data.csv")]

result = {}

female_single_count = dfs[0].pivot_table(values='Gender', index=None, columns='Marital Status').loc['Single', 'Female'].values[0]

result = {"type": "string", "value": f"There are {female_single_count} female employees being single."}

print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 95, in execute
    code_to_run = self.get_code_to_run(input, code_context)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 152, in get_code_to_run
    code_to_run = self._clean_code(code, context)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 487, in _clean_code
    self._check_imports(node)
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_cleaning.py", line 585, in _check_imports
    raise BadImportError(library)
pandasai.exceptions.BadImportError: Generated code includes import of collections which is not in whitelist.


Fix the python code above and return the new python code:
            
2024-11-12 10:50:01 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Write code here

dfs = [pd.read_csv("data.csv")]

result = {}

female_single_count = (dfs[0]['Gender'] == 'Female') & (dfs[0]['Marital Status'] == 'Single').sum()

result = {"type": "string", "value": f"There are {female_single_count} female employees being single."}

print(result)
            ```
            
2024-11-12 10:50:01 [INFO] Executing Step 2: CodeCleaning
2024-11-12 10:50:01 [INFO] 
Code running:
```
result = {}
female_single_count = (dfs[0]['Gender'] == 'Female') & (dfs[0]['Marital Status'] == 'Single').sum()
result = {'type': 'string', 'value': f'There are {female_single_count} female employees being single.'}
print(result)
        ```
2024-11-12 10:50:01 [INFO] Executing Step 6: CodeExecution
2024-11-12 10:50:01 [INFO] Executing Step 7: ResultValidation
2024-11-12 10:50:01 [INFO] Answer: {'type': 'string', 'value': 'There are 0       False\n1       False\n2       False\n3       False\n4       False\n        ...  \n1465    False\n1466    False\n1467    False\n1468    False\n1469    False\nName: Gender, Length: 1470, dtype: bool female employees being single.'}
2024-11-12 10:50:01 [INFO] Executing Step 8: ResultParsing
2024-11-12 17:43:23 [INFO] Question: how many people are above the age of 40 ?
2024-11-12 17:43:23 [INFO] Running PandasAI with local LLM...
2024-11-12 17:43:23 [INFO] Prompt ID: 728fe719-7639-4eac-8d8f-798da964c116
2024-11-12 17:43:23 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 17:43:23 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 17:43:23 [INFO] Executing Step 1: CacheLookup
2024-11-12 17:43:23 [INFO] Executing Step 2: PromptGeneration
2024-11-12 17:43:23 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-410,613,Female,Research Scientist,Divorced,No,Y,0,42,1,598,17,Doctoral Degree,1,3,42,4,3,3,19943,14229,6,13,3,1,80,1,15,2,17,8,5,2
Yes,Travel_Rarely,Under 25,Current Employees,HR,Technical Degree,STAFF-1097,321,Female,Manufacturing Director,Married,Yes,Y,4,40,1,1134,24,Master's Degree,1,4,48,3,2,2,6347,18767,0,21,3,3,80,2,5,3,31,16,7,14
No,Non-Travel,Over 55,Ex-Employees,R&D,Other,STAFF-329,1150,Male,Manager,Single,No,Y,3,30,0,1277,1,Associates Degree,1,2,60,1,5,1,4678,7653,4,15,4,4,80,0,12,1,15,2,3,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are above the age of 40 ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 17:43:23 [INFO] Executing Step 3: CodeGenerator
2024-11-12 17:45:04 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 17:45:04 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-410,613,Female,Research Scientist,Divorced,No,Y,0,42,1,598,17,Doctoral Degree,1,3,42,4,3,3,19943,14229,6,13,3,1,80,1,15,2,17,8,5,2
Yes,Travel_Rarely,Under 25,Current Employees,HR,Technical Degree,STAFF-1097,321,Female,Manufacturing Director,Married,Yes,Y,4,40,1,1134,24,Master's Degree,1,4,48,3,2,2,6347,18767,0,21,3,3,80,2,5,3,31,16,7,14
No,Non-Travel,Over 55,Ex-Employees,R&D,Other,STAFF-329,1150,Male,Manager,Single,No,Y,3,30,0,1277,1,Associates Degree,1,2,60,1,5,1,4678,7653,4,15,4,4,80,0,12,1,15,2,3,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are above the age of 40 ?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 17:45:04 [INFO] Code generated:
            ```
            Python
# TODO: import the required dependencies
import pandas as pd

dfs = [pd.read_csv('file_name.csv')]

# Calculate the number of people above 40 years old:
total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])

result = {
    'type': 'string',
    'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'
}

print(result)
            ```
            
2024-11-12 17:45:04 [INFO] Executing Step 4: CachePopulation
2024-11-12 17:45:04 [INFO] Executing Step 5: CodeCleaning
2024-11-12 17:45:04 [INFO] 
Code running:
```
Python
total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])
result = {'type': 'string', 'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'}
print(result)
        ```
2024-11-12 17:45:04 [INFO] Executing Step 6: CodeExecution
2024-11-12 17:45:04 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-12 17:45:04 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-12 17:45:04 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 17:45:04 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 17:45:05 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-410,613,Female,Research Scientist,Divorced,No,Y,0,42,1,598,17,Doctoral Degree,1,3,42,4,3,3,19943,14229,6,13,3,1,80,1,15,2,17,8,5,2
Yes,Travel_Rarely,Under 25,Current Employees,HR,Technical Degree,STAFF-1097,321,Female,Manufacturing Director,Married,Yes,Y,4,40,1,1134,24,Master's Degree,1,4,48,3,2,2,6347,18767,0,21,3,3,80,2,5,3,31,16,7,14
No,Non-Travel,Over 55,Ex-Employees,R&D,Other,STAFF-329,1150,Male,Manager,Single,No,Y,3,30,0,1277,1,Associates Degree,1,2,60,1,5,1,4678,7653,4,15,4,4,80,0,12,1,15,2,3,5
</dataframe>


The user asked the following question:
### QUERY
 how many people are above the age of 40 ?

You generated this python code:
Python
total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])
result = {'type': 'string', 'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-12 17:45:05 [INFO] Executing Step 1: CodeGenerator
2024-11-12 17:46:02 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 17:46:02 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-410,613,Female,Research Scientist,Divorced,No,Y,0,42,1,598,17,Doctoral Degree,1,3,42,4,3,3,19943,14229,6,13,3,1,80,1,15,2,17,8,5,2
Yes,Travel_Rarely,Under 25,Current Employees,HR,Technical Degree,STAFF-1097,321,Female,Manufacturing Director,Married,Yes,Y,4,40,1,1134,24,Master's Degree,1,4,48,3,2,2,6347,18767,0,21,3,3,80,2,5,3,31,16,7,14
No,Non-Travel,Over 55,Ex-Employees,R&D,Other,STAFF-329,1150,Male,Manager,Single,No,Y,3,30,0,1277,1,Associates Degree,1,2,60,1,5,1,4678,7653,4,15,4,4,80,0,12,1,15,2,3,5
</dataframe>


The user asked the following question:
### QUERY
 how many people are above the age of 40 ?

You generated this python code:
Python
total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])
result = {'type': 'string', 'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-12 17:46:02 [INFO] Code generated:
            ```
            total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])
result = {'type': 'string', 'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'}
print(result)
            ```
            
2024-11-12 17:46:02 [INFO] Executing Step 2: CodeCleaning
2024-11-12 17:46:02 [INFO] 
Code running:
```
total_people = len(dfs[0])
people_above_40 = len(dfs[0][dfs[0]['Age'] > 40])
result = {'type': 'string', 'value': f'Number of people above the age of 40: {people_above_40}. Total number of people is: {total_people}.'}
print(result)
        ```
2024-11-12 17:46:02 [INFO] Executing Step 7: ResultValidation
2024-11-12 17:46:02 [INFO] Answer: {'type': 'string', 'value': 'Number of people above the age of 40: 465. Total number of people is: 1470.'}
2024-11-12 17:46:02 [INFO] Executing Step 8: ResultParsing
2024-11-12 18:38:41 [INFO] Question: Create a histogram on the basis of the gender category.
2024-11-12 18:38:41 [INFO] Running PandasAI with local LLM...
2024-11-12 18:38:41 [INFO] Prompt ID: 92d5dc6c-21b7-43cb-82ce-a2c5d30eb4f8
2024-11-12 18:38:41 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 18:38:41 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 18:38:41 [INFO] Executing Step 1: CacheLookup
2024-11-12 18:38:41 [INFO] Executing Step 2: PromptGeneration
2024-11-12 18:38:41 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Life Sciences,STAFF-424,783,Female,Research Scientist,Divorced,Yes,Y,2,43,1,1096,12,Doctoral Degree,1,1,62,1,2,4,3975,5594,6,19,3,1,80,0,21,2,8,0,4,12
Yes,Non-Travel,Under 25,Current Employees,R&D,Other,STAFF-987,18,Female,Research Director,Single,No,Y,5,42,0,251,8,Master's Degree,1,2,86,3,4,3,8321,2112,2,17,4,4,80,3,16,3,29,8,13,16
Yes,Travel_Frequently,35 - 44,Current Employees,Sales,Medical,STAFF-848,1868,Male,Sales Executive,Married,Yes,Y,1,37,1,573,15,High School,1,4,57,2,1,2,2804,2354,5,20,3,3,80,1,24,4,19,13,15,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 Create a histogram on the basis of the gender category.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 18:38:42 [INFO] Executing Step 3: CodeGenerator
2024-11-12 18:40:45 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 18:40:46 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Life Sciences,STAFF-424,783,Female,Research Scientist,Divorced,Yes,Y,2,43,1,1096,12,Doctoral Degree,1,1,62,1,2,4,3975,5594,6,19,3,1,80,0,21,2,8,0,4,12
Yes,Non-Travel,Under 25,Current Employees,R&D,Other,STAFF-987,18,Female,Research Director,Single,No,Y,5,42,0,251,8,Master's Degree,1,2,86,3,4,3,8321,2112,2,17,4,4,80,3,16,3,29,8,13,16
Yes,Travel_Frequently,35 - 44,Current Employees,Sales,Medical,STAFF-848,1868,Male,Sales Executive,Married,Yes,Y,1,37,1,573,15,High School,1,4,57,2,1,2,2804,2354,5,20,3,3,80,1,24,4,19,13,15,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 Create a histogram on the basis of the gender category.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 18:40:46 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

dfs = [pd.read_csv('your_data.csv')]  # Load your data here

# Create a histogram on the basis of the gender category.
gender_counts = dfs[0].value_counts("Gender")

plt.figure(figsize=(10,6))
plt.hist(gender_counts, bins='auto')
plt.title('Histogram of Gender Counts')
plt.xlabel('Gender')
plt.ylabel('Count')

result = { "type": "plot", "value": "gender_histogram.png" }
            ```
            
2024-11-12 18:40:46 [INFO] Executing Step 4: CachePopulation
2024-11-12 18:40:46 [INFO] Executing Step 5: CodeCleaning
2024-11-12 18:40:46 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 18:40:46 [INFO] 
Code running:
```
gender_counts = dfs[0].value_counts('Gender')
plt.figure(figsize=(10, 6))
plt.hist(gender_counts, bins='auto')
plt.title('Histogram of Gender Counts')
plt.xlabel('Gender')
plt.ylabel('Count')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
        ```
2024-11-12 18:40:46 [INFO] Executing Step 6: CodeExecution
2024-11-12 18:40:47 [ERROR] Pipeline failed on step 6: [Errno 2] No such file or directory: 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
2024-11-12 18:48:13 [INFO] Question: generate a histogram on the basis of gender.
2024-11-12 18:48:13 [INFO] Running PandasAI with local LLM...
2024-11-12 18:48:13 [INFO] Prompt ID: 38b3a71a-621e-4310-94ae-6c140fd9eabd
2024-11-12 18:48:13 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 18:48:13 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 18:48:13 [INFO] Executing Step 1: CacheLookup
2024-11-12 18:48:13 [INFO] Executing Step 2: PromptGeneration
2024-11-12 18:48:13 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-1911,152,Male,Research Scientist,Divorced,Yes,Y,0,44,0,748,28,Master's Degree,1,4,56,3,3,2,1359,12253,4,14,3,2,80,3,8,2,31,3,14,16
Yes,Non-Travel,25 - 34,Ex-Employees,HR,Medical,STAFF-1747,1502,Female,Manufacturing Director,Married,Yes,Y,1,58,0,562,15,Doctoral Degree,1,1,65,1,5,1,4400,21447,1,21,4,1,80,1,23,3,17,2,0,8
Yes,Travel_Rarely,45 - 54,Current Employees,Sales,Life Sciences,STAFF-1760,1929,Male,Sales Executive,Single,No,Y,6,33,1,480,20,Associates Degree,1,3,55,4,2,4,3580,21509,6,11,3,3,80,2,2,1,13,5,3,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate a histogram on the basis of gender.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 18:48:13 [INFO] Executing Step 3: CodeGenerator
2024-11-12 18:50:12 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 18:50:12 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-1911,152,Male,Research Scientist,Divorced,Yes,Y,0,44,0,748,28,Master's Degree,1,4,56,3,3,2,1359,12253,4,14,3,2,80,3,8,2,31,3,14,16
Yes,Non-Travel,25 - 34,Ex-Employees,HR,Medical,STAFF-1747,1502,Female,Manufacturing Director,Married,Yes,Y,1,58,0,562,15,Doctoral Degree,1,1,65,1,5,1,4400,21447,1,21,4,1,80,1,23,3,17,2,0,8
Yes,Travel_Rarely,45 - 54,Current Employees,Sales,Life Sciences,STAFF-1760,1929,Male,Sales Executive,Single,No,Y,6,33,1,480,20,Associates Degree,1,3,55,4,2,4,3580,21509,6,11,3,3,80,2,2,1,13,5,3,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate a histogram on the basis of gender.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 18:50:12 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

# Merge all data into one DataFrame
merged_df = pd.concat(dfs)

# Group by gender and count the number of employees in each group
gender_counts = merged_df['Gender'].value_counts()

# Create a dictionary to store the result
result = {}

# Plot histogram
plt.figure(figsize=(10, 6))
plt.bar(gender_counts.index, gender_counts.values)
plt.xlabel('Gender')
plt.ylabel('Count')
plt.title('Histogram of Gender Distribution')
plt.savefig('gender_histogram.png')

# Store result in the dictionary
result = {"type": "plot", "value": "gender_histogram.png"}

print(result)
            ```
            
2024-11-12 18:50:12 [INFO] Executing Step 4: CachePopulation
2024-11-12 18:50:13 [INFO] Executing Step 5: CodeCleaning
2024-11-12 18:50:13 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 18:50:13 [INFO] 
Code running:
```
merged_df = pd.concat(dfs)
gender_counts = merged_df['Gender'].value_counts()
result = {}
plt.figure(figsize=(10, 6))
plt.bar(gender_counts.index, gender_counts.values)
plt.xlabel('Gender')
plt.ylabel('Count')
plt.title('Histogram of Gender Distribution')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)
        ```
2024-11-12 18:50:13 [INFO] Executing Step 6: CodeExecution
2024-11-12 18:50:14 [INFO] Executing Step 7: ResultValidation
2024-11-12 18:50:14 [INFO] Answer: {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
2024-11-12 18:50:14 [INFO] Executing Step 8: ResultParsing
2024-11-12 18:50:45 [INFO] Question: generate a histogram on the basis of gender and age.
2024-11-12 18:50:45 [INFO] Running PandasAI with local LLM...
2024-11-12 18:50:45 [INFO] Prompt ID: c4d34b14-da81-4975-bb2d-b38875ca6a41
2024-11-12 18:50:45 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 18:50:45 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 18:50:45 [INFO] Executing Step 1: CacheLookup
2024-11-12 18:50:45 [INFO] Executing Step 2: PromptGeneration
2024-11-12 18:50:45 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate a histogram on the basis of gender and age.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-12 18:50:45 [INFO] Executing Step 3: CodeGenerator
2024-11-12 18:56:24 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 18:56:24 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate a histogram on the basis of gender and age.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-12 18:56:24 [INFO] Code generated:
            ```
            Python
# TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

dfs = []  # Variable `dfs` declared, initialized with empty list.

# Initialize data structures or data.
data = {
    "Attrition": [0, 1],
    "Business Travel": ["Yes", "No"],
    "CF_age band": [29, 52, 35, 45, 50, 25, 40, 55],
    "CF_attrition label": ["Ex-Employees", "Current Employees", "Ex-Employees", "Current Employees", "Ex-Employees", "Current Employees"],
    "Department": ["Sales", "R&D", "HR", "Marketing", "Medical", "Other", "STAFF-710", "STAFF-1103", "STAFF-1869"],
    "Education Field": ["Medical", "Medical", "Marketing", "Other", "Other", "Medical", "Other", "Other"],
    "emp no": [1621, 305, 1387, 429, 1255, 928, 2718, 12355],
    "Employee Number": [1621, 305, 1387, 429, 1255, 928, 2718, 12355],
    "Gender": ["Male", "Female", "Male", "Female"],
    "Job Role": [ "Laboratory Technician", "Healthcare Representative", "Research Director", "Sales", "Marketing", "Other", "STAFF-710", "STAFF-1103", "STAFF-1869"],
    "Marital Status": ["Married", "Single", "Divorced"],
    "Over Time": ["Y", "No", "N"],
    "Over18": [],
    "Training Times Last Year": [3, 1],
    "Age": [29, 52, 35, 45, 50, 25, 40, 55],
    "CF_current Employee": [0, 1],
    "Daily Rate": [89],
    "Distance From Home": [3],
    "Education": ["Master's Degree", "Doctoral Degree", "Bachelor's Degree"],
    "Employee Count": [1],
    "Environment Satisfaction": [75],
    "Hourly Rate": [13364],
    "Job Involvement": [2],
    "Job Level": [16],
    "Job Satisfaction": [13364],
    "Monthly Income": [],
    "Monthly Rate": [18154],
    "Num Companies Worked": [8],
    "Percent Salary Hike": [13, 24, 4],
    "Performance Rating": [3, 2, 1],
    "Relationship Satisfaction": [80, 20, 19],
    "Standard Hours": [2],
    "Stock Option Level": [7],
    "Total Working Years": [29, 31],
    "Work Life Balance": [24],
    "Years At Company": [10, 11],
    "Years In Current Role": [6, 5],
    "Years Since Last Promotion": [16, 17],
    "Years With Curr Manager": [13]
}

dfs.append(pd.DataFrame(data))  # DataFrame is created and added to `dfs` list.

# Calculate histogram (gender vs age).
result = {"type": "plot", "value": ""}  
plt.figure(figsize=(10, 6))
plt.hist2d( dfs[0]["Age"].values, dfs[0]["Gender"].values,bins=[20,3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title("Histogram of gender and age")
plt.show()

result["value"] = "temp_chart.png"
            ```
            
2024-11-12 18:56:24 [INFO] Executing Step 4: CachePopulation
2024-11-12 18:56:24 [INFO] Executing Step 5: CodeCleaning
2024-11-12 18:56:24 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 18:56:24 [INFO] 
Code running:
```
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
        ```
2024-11-12 18:56:24 [INFO] Executing Step 6: CodeExecution
2024-11-12 18:56:25 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-12 18:56:25 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-12 18:56:25 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 18:56:25 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 18:56:25 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-12 18:56:25 [INFO] Executing Step 1: CodeGenerator
2024-11-12 18:58:30 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 18:58:30 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-12 18:58:30 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

# Assuming dfs is your DataFrame object

plt.figure(figsize=(10, 6))

age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = "Count"

plt.imshow(age_counts, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar()
cbar.set_label('Count')

plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()

result = {'type': 'image', 'value': ''}
            ```
            
2024-11-12 18:58:30 [INFO] Executing Step 2: CodeCleaning
2024-11-12 18:58:30 [INFO] 
Code running:
```
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
plt.imshow(age_counts, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar()
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result = {'type': 'image', 'value': ''}
        ```
2024-11-12 18:58:30 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image

2024-11-12 18:58:30 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-12 18:58:30 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 18:58:30 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 18:58:30 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
plt.imshow(age_counts, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar()
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result = {'type': 'image', 'value': ''}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image


Fix the python code above and return the new python code:
2024-11-12 18:58:30 [INFO] Executing Step 1: CodeGenerator
2024-11-12 19:00:13 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 19:00:13 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
plt.imshow(age_counts, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar()
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result = {'type': 'image', 'value': ''}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image


Fix the python code above and return the new python code:
            
2024-11-12 19:00:13 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

# assuming dfs[0] is your DataFrame
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'

fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')

plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')

# Save the image
img_path = 'histogram.png'
plt.savefig(img_path)

# Now you can return the path where the image file was saved
result = {'type': 'image', 'value': img_path}
            ```
            
2024-11-12 19:00:13 [INFO] Executing Step 2: CodeCleaning
2024-11-12 19:00:13 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 19:00:13 [INFO] 
Code running:
```
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
img_path = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
plt.savefig(img_path)
result = {'type': 'image', 'value': img_path}
        ```
2024-11-12 19:00:13 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image

2024-11-12 19:00:13 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-12 19:00:13 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 19:00:13 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 19:00:13 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
img_path = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
plt.savefig(img_path)
result = {'type': 'image', 'value': img_path}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image


Fix the python code above and return the new python code:
2024-11-12 19:00:13 [INFO] Executing Step 1: CodeGenerator
2024-11-12 19:01:50 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 19:01:50 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Under 25,Ex-Employees,Sales,Medical,STAFF-710,1621,Male,Laboratory Technician,Married,No,Y,3,29,0,429,16,Master's Degree,1,3,89,2,3,2,4260,13364,2,13,3,4,80,0,19,2,24,10,0,17
No,Non-Travel,35 - 44,Current Employees,R&D,Other,STAFF-1103,305,Female,Healthcare Representative,Single,Yes,Y,1,52,1,1255,14,Doctoral Degree,1,4,75,1,4,1,9950,18154,8,24,4,1,80,3,20,1,29,16,11,6
No,Travel_Frequently,45 - 54,Ex-Employees,HR,Marketing,STAFF-1869,1387,Male,Research Director,Divorced,Yes,Y,5,35,1,928,12,Bachelor's Degree,1,2,40,3,2,3,2718,12355,0,19,3,2,80,1,29,3,30,7,2,16
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
img_path = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
plt.savefig(img_path)
result = {'type': 'image', 'value': img_path}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 97, in execute
    raise InvalidOutputValueMismatch(
pandasai.exceptions.InvalidOutputValueMismatch: Value type <class 'str'> must match with type image


Fix the python code above and return the new python code:
            
2024-11-12 19:01:50 [INFO] Code generated:
            ```
            Python
import pandas as pd
import matplotlib.pyplot as plt

# Assuming you have the DataFrame data in dfs[0]

plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'

fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')

plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')

img_path = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
plt.savefig(img_path)

result = {'type': 'image', 'image': img_path}

print(result)
            ```
            
2024-11-12 19:01:50 [INFO] Executing Step 2: CodeCleaning
2024-11-12 19:01:50 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 19:01:50 [INFO] 
Code running:
```
Python
plt.figure(figsize=(10, 6))
age_counts = dfs[0].groupby(['Gender', 'Age']).size().unstack()
age_counts.columns.name = 'Count'
fig = plt.gcf()
ax = fig.add_subplot(111)
im = ax.imshow(age_counts.values.T, cmap='coolwarm', interpolation='nearest')
cbar = plt.colorbar(im)
cbar.set_label('Count')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
img_path = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
plt.savefig(img_path)
result = {'type': 'image', 'image': img_path}
print(result)
        ```
2024-11-12 19:01:50 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-12 19:01:50 [ERROR] Pipeline failed on step 6: name 'Python' is not defined
2024-11-12 19:02:09 [INFO] Question: generate a histogram on the basis of gender and age.
2024-11-12 19:02:09 [INFO] Running PandasAI with local LLM...
2024-11-12 19:02:09 [INFO] Prompt ID: aa7a838f-5cc3-4dd2-9ee8-8f6834f488a5
2024-11-12 19:02:09 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-12 19:02:09 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-12 19:02:09 [INFO] Executing Step 1: CacheLookup
2024-11-12 19:02:09 [INFO] Using cached response
2024-11-12 19:02:09 [INFO] Executing Step 2: PromptGeneration
2024-11-12 19:02:09 [INFO] Executing Step 2: Skipping...
2024-11-12 19:02:09 [INFO] Executing Step 3: CodeGenerator
2024-11-12 19:02:09 [INFO] Executing Step 3: Skipping...
2024-11-12 19:02:09 [INFO] Executing Step 4: CachePopulation
2024-11-12 19:02:09 [INFO] Executing Step 4: Skipping...
2024-11-12 19:02:09 [INFO] Executing Step 5: CodeCleaning
2024-11-12 19:02:09 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 19:02:09 [INFO] 
Code running:
```
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
        ```
2024-11-12 19:02:09 [INFO] Executing Step 6: CodeExecution
2024-11-12 19:02:09 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-12 19:02:09 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-12 19:02:09 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 19:02:09 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 19:02:09 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-12 19:02:09 [INFO] Executing Step 1: CodeGenerator
2024-11-12 19:04:48 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 19:04:48 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
data = {'Attrition': [0, 1], 'Business Travel': ['Yes', 'No'], 'CF_age band': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees', 'Ex-Employees', 'Current Employees'], 'Department': ['Sales', 'R&D', 'HR', 'Marketing', 'Medical', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Education Field': ['Medical', 'Medical', 'Marketing', 'Other', 'Other', 'Medical', 'Other', 'Other'], 'emp no': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Employee Number': [1621, 305, 1387, 429, 1255, 928, 2718, 12355], 'Gender': ['Male', 'Female', 'Male', 'Female'], 'Job Role': ['Laboratory Technician', 'Healthcare Representative', 'Research Director', 'Sales', 'Marketing', 'Other', 'STAFF-710', 'STAFF-1103', 'STAFF-1869'], 'Marital Status': ['Married', 'Single', 'Divorced'], 'Over Time': ['Y', 'No', 'N'], 'Over18': [], 'Training Times Last Year': [3, 1], 'Age': [29, 52, 35, 45, 50, 25, 40, 55], 'CF_current Employee': [0, 1], 'Daily Rate': [89], 'Distance From Home': [3], 'Education': ["Master's Degree", 'Doctoral Degree', "Bachelor's Degree"], 'Employee Count': [1], 'Environment Satisfaction': [75], 'Hourly Rate': [13364], 'Job Involvement': [2], 'Job Level': [16], 'Job Satisfaction': [13364], 'Monthly Income': [], 'Monthly Rate': [18154], 'Num Companies Worked': [8], 'Percent Salary Hike': [13, 24, 4], 'Performance Rating': [3, 2, 1], 'Relationship Satisfaction': [80, 20, 19], 'Standard Hours': [2], 'Stock Option Level': [7], 'Total Working Years': [29, 31], 'Work Life Balance': [24], 'Years At Company': [10, 11], 'Years In Current Role': [6, 5], 'Years Since Last Promotion': [16, 17], 'Years With Curr Manager': [13]}
dfs.append(pd.DataFrame(data))
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, dfs[0]['Gender'].values, bins=[20, 3], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-12 19:04:48 [INFO] Code generated:
            ```
            Python
import pandas as pd
import matplotlib.pyplot as plt

dfs = []  # Create an empty list to store dataframes

# Assuming you have a dataframe df already present in dfs
dfs.append(df)

result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, [x if x == 'Male' else 'Female' for x in dfs[0]['Gender'].values], bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
            ```
            
2024-11-12 19:04:48 [INFO] Executing Step 2: CodeCleaning
2024-11-12 19:04:48 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-12 19:04:48 [INFO] 
Code running:
```
Python
dfs.append(df)
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, [(x if x == 'Male' else 'Female') for x in dfs[0]['Gender'].values], bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
        ```
2024-11-12 19:04:48 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-12 19:04:48 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-12 19:04:48 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 19:04:48 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 19:04:48 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
dfs.append(df)
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, [(x if x == 'Male' else 'Female') for x in dfs[0]['Gender'].values], bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-12 19:04:48 [INFO] Executing Step 1: CodeGenerator
2024-11-12 19:06:15 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 19:06:15 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
Python
dfs.append(df)
result = {'type': 'plot', 'value': ''}
plt.figure(figsize=(10, 6))
plt.hist2d(dfs[0]['Age'].values, [(x if x == 'Male' else 'Female') for x in dfs[0]['Gender'].values], bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-12 19:06:15 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

dfs = pd.read_csv('file.csv')  # Replace 'file.csv' with your actual CSV file name.

plt.figure(figsize=(10, 6))
plt.hist2d(dfs['Age'].values, dfs[dfs['Gender'] == 'Female']['Age'].values, bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
            ```
            
2024-11-12 19:06:15 [INFO] Executing Step 2: CodeCleaning
2024-11-12 19:06:15 [INFO] 
Code running:
```
plt.figure(figsize=(10, 6))
plt.hist2d(dfs['Age'].values, dfs[dfs['Gender'] == 'Female']['Age'].values, bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()
        ```
2024-11-12 19:06:15 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str

2024-11-12 19:06:15 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-12 19:06:15 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-12 19:06:15 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-12 19:06:15 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
plt.hist2d(dfs['Age'].values, dfs[dfs['Gender'] == 'Female']['Age'].values, bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
2024-11-12 19:06:15 [INFO] Executing Step 1: CodeGenerator
2024-11-12 19:08:33 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-12 19:08:33 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Frequently,45 - 54,Ex-Employees,R&D,Other,STAFF-2008,116,Female,Laboratory Technician,Single,No,Y,3,48,1,702,26,Associates Degree,1,4,54,2,2,2,13212,20497,4,18,4,3,80,0,11,4,20,15,10,12
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1135,1886,Female,Sales Executive,Divorced,Yes,Y,4,19,0,129,15,Master's Degree,1,1,39,3,5,3,19431,15238,6,19,3,4,80,3,35,2,10,0,14,4
Yes,Travel_Rarely,35 - 44,Ex-Employees,HR,Human Resources,STAFF-1224,1815,Male,Healthcare Representative,Married,No,Y,2,58,1,1312,1,Bachelor's Degree,1,3,81,4,4,4,4775,26278,3,22,3,1,80,1,21,1,27,16,8,15
</dataframe>


The user asked the following question:
### QUERY
 generate a histogram on the basis of gender and age.

You generated this python code:
plt.figure(figsize=(10, 6))
plt.hist2d(dfs['Age'].values, dfs[dfs['Gender'] == 'Female']['Age'].values, bins=[20, 2], cmap=plt.cm.coolwarm, edgecolor='black')
plt.xlabel('Age')
plt.ylabel('Gender')
plt.title('Histogram of gender and age')
plt.show()

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
            
2024-11-12 19:08:33 [INFO] Code generated:
            ```
            import matplotlib.pyplot as plt
import pandas as pd

plt.figure(figsize=(10, 6))

female_data = dfs[dfs['Gender'] == 'Female']
male_data = dfs[dfs['Gender'] == 'Male']

plt.hist(female_data['Age'], bins=20, alpha=0.5, label='Female', color='blue')
plt.hist(male_data['Age'], bins=20, alpha=0.5, label='Male', color='red')

plt.xlabel('Age')
plt.ylabel('Frequency')
plt.title('Histogram of Gender and Age')
plt.legend()

plt.show()
            ```
            
2024-11-12 19:08:33 [INFO] Executing Step 2: CodeCleaning
2024-11-12 19:08:33 [INFO] 
Code running:
```
plt.figure(figsize=(10, 6))
female_data = dfs[dfs['Gender'] == 'Female']
male_data = dfs[dfs['Gender'] == 'Male']
plt.hist(female_data['Age'], bins=20, alpha=0.5, label='Female', color='blue')
plt.hist(male_data['Age'], bins=20, alpha=0.5, label='Male', color='red')
plt.xlabel('Age')
plt.ylabel('Frequency')
plt.title('Histogram of Gender and Age')
plt.legend()
plt.show()
        ```
2024-11-12 19:08:33 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str

2024-11-12 19:08:33 [ERROR] Pipeline failed on step 6: list indices must be integers or slices, not str
2024-11-13 17:50:59 [INFO] Question: how many people are single and how many are married?
2024-11-13 17:50:59 [INFO] Running PandasAI with local LLM...
2024-11-13 17:50:59 [INFO] Prompt ID: 55fb3184-1609-48f0-97e2-ff78dab2941a
2024-11-13 17:50:59 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 17:51:00 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 17:51:00 [INFO] Executing Step 1: CacheLookup
2024-11-13 17:51:00 [INFO] Executing Step 2: PromptGeneration
2024-11-13 17:51:00 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-1368,1676,Female,Sales Representative,Married,No,Y,2,48,1,983,16,Bachelor's Degree,1,1,72,2,4,2,2622,5041,0,20,4,2,80,1,9,1,5,9,6,15
Yes,Travel_Rarely,45 - 54,Current Employees,HR,Life Sciences,STAFF-1612,514,Male,Research Scientist,Single,Yes,Y,1,55,0,172,4,Associates Degree,1,2,60,3,5,4,2011,17852,8,12,4,4,80,0,32,4,12,7,11,17
Yes,Travel_Frequently,Under 25,Ex-Employees,R&D,Marketing,STAFF-347,833,Female,Sales Executive,Divorced,No,Y,3,20,1,688,14,Doctoral Degree,1,4,56,4,3,3,7351,22673,6,24,3,1,80,3,27,3,29,11,13,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are single and how many are married?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 17:51:00 [INFO] Executing Step 3: CodeGenerator
2024-11-13 17:52:05 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 17:52:05 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-1368,1676,Female,Sales Representative,Married,No,Y,2,48,1,983,16,Bachelor's Degree,1,1,72,2,4,2,2622,5041,0,20,4,2,80,1,9,1,5,9,6,15
Yes,Travel_Rarely,45 - 54,Current Employees,HR,Life Sciences,STAFF-1612,514,Male,Research Scientist,Single,Yes,Y,1,55,0,172,4,Associates Degree,1,2,60,3,5,4,2011,17852,8,12,4,4,80,0,32,4,12,7,11,17
Yes,Travel_Frequently,Under 25,Ex-Employees,R&D,Marketing,STAFF-347,833,Female,Sales Executive,Divorced,No,Y,3,20,1,688,14,Doctoral Degree,1,4,56,4,3,3,7351,22673,6,24,3,1,80,3,27,3,29,11,13,5
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are single and how many are married?

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 17:52:05 [INFO] Code generated:
            ```
            # Initialize result variable
result = {}

# Calculate number of married and single employees
married = dfs[0][dfs[0]['Marital Status'] == 'Married'].shape[0]
single = dfs[0][dfs[0]['Marital Status'] == 'Single'].shape[0]

# Store the results in dictionary
result['type'] = "string"
result['value'] = f"There are {married} married employees and {single} single employees."

print(result)
            ```
            
2024-11-13 17:52:05 [INFO] Executing Step 4: CachePopulation
2024-11-13 17:52:05 [INFO] Executing Step 5: CodeCleaning
2024-11-13 17:52:05 [INFO] 
Code running:
```
result = {}
married = dfs[0][dfs[0]['Marital Status'] == 'Married'].shape[0]
single = dfs[0][dfs[0]['Marital Status'] == 'Single'].shape[0]
result['type'] = 'string'
result['value'] = f'There are {married} married employees and {single} single employees.'
print(result)
        ```
2024-11-13 17:52:05 [INFO] Executing Step 6: CodeExecution
2024-11-13 17:52:05 [INFO] Executing Step 7: ResultValidation
2024-11-13 17:52:05 [INFO] Answer: {'type': 'string', 'value': 'There are 673 married employees and 470 single employees.'}
2024-11-13 17:52:05 [INFO] Executing Step 8: ResultParsing
2024-11-13 17:53:38 [INFO] Question: how many people are single and how many are married and visualise it using pie chart and bar graph.
2024-11-13 17:53:38 [INFO] Running PandasAI with local LLM...
2024-11-13 17:53:38 [INFO] Prompt ID: 77c3ab6c-f3ea-488f-88be-dd3a1416bedb
2024-11-13 17:53:38 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 17:53:38 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 17:53:38 [INFO] Executing Step 1: CacheLookup
2024-11-13 17:53:38 [INFO] Executing Step 2: PromptGeneration
2024-11-13 17:53:38 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 17:53:38 [INFO] Executing Step 3: CodeGenerator
2024-11-13 17:55:48 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 17:55:48 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 17:55:48 [INFO] Code generated:
            ```
            Python
import pandas as pd
import matplotlib.pyplot as plt

result = {}

dfs[0]['Marital Status'].value_counts().to_dict()  # count the number of single and married people

marital_status_count = dfs[0]['Marital Status'].value_counts()

# Create a pie chart to visualize marital status counts
plt.figure(figsize=(10,6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts'); plt.show()
# Save the pie chart as an image
plt.savefig('marital_status_pie_chart.png', bbox_inches='tight')

# Create a bar graph to visualize marital status counts (for the sake of completeness)
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()

fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status'); ax1.set_ylabel('Count');
ax1.set_title('Marital Status Counts - Bar Graph'); plt.show();

# Declare result var: 
result = {"type": "plot", "value": 'marital_status_pie_chart.png'  # specify the path where the png will be saved
          }

print(result)
            ```
            
2024-11-13 17:55:48 [INFO] Executing Step 4: CachePopulation
2024-11-13 17:55:48 [INFO] Executing Step 5: CodeCleaning
2024-11-13 17:55:48 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 17:55:48 [INFO] 
Code running:
```
Python
result = {}
dfs[0]['Marital Status'].value_counts().to_dict()
marital_status_count = dfs[0]['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)
        ```
2024-11-13 17:55:48 [INFO] Executing Step 6: CodeExecution
2024-11-13 17:55:49 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 17:55:49 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 17:55:49 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 17:55:49 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 17:55:49 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
Python
result = {}
dfs[0]['Marital Status'].value_counts().to_dict()
marital_status_count = dfs[0]['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-13 17:55:49 [INFO] Executing Step 1: CodeGenerator
2024-11-13 17:57:30 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 17:57:30 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
Python
result = {}
dfs[0]['Marital Status'].value_counts().to_dict()
marital_status_count = dfs[0]['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 17:57:30 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

dfs = pd.read_csv('your_data.csv')  # Load your data from CSV

result = {}
marital_status_count = dfs['Marital Status'].value_counts()

plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('path/to/your/file.png', bbox_inches='tight')

bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()

fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()

result = {'type': 'plot', 'value': 'path/to/your/file.png'}
print(result)
            ```
            
2024-11-13 17:57:30 [INFO] Executing Step 2: CodeCleaning
2024-11-13 17:57:30 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 17:57:30 [INFO] 
Code running:
```
result = {}
marital_status_count = dfs['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)
        ```
2024-11-13 17:57:30 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str

2024-11-13 17:57:30 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-13 17:57:30 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 17:57:30 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 17:57:30 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
result = {}
marital_status_count = dfs['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
2024-11-13 17:57:30 [INFO] Executing Step 1: CodeGenerator
2024-11-13 17:59:35 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 17:59:35 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
result = {}
marital_status_count = dfs['Marital Status'].value_counts()
plt.figure(figsize=(10, 6))
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
plt.title('Marital Status Counts')
plt.show()
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', bbox_inches='tight')
bar_labels = marital_status_count.keys().tolist()
bar_values = marital_status_count.values.tolist()
fig, ax1 = plt.subplots()
ax1.bar(bar_labels, bar_values, color='orange')
ax1.set_xlabel('Marital Status')
ax1.set_ylabel('Count')
ax1.set_title('Marital Status Counts - Bar Graph')
plt.show()
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
            
2024-11-13 17:59:35 [INFO] Code generated:
            ```
            marital_status_count = dfs['Marital Status'].value_counts()
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
            ```
            
2024-11-13 17:59:35 [INFO] Executing Step 2: CodeCleaning
2024-11-13 17:59:35 [INFO] 
Code running:
```
marital_status_count = dfs['Marital Status'].value_counts()
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')
        ```
2024-11-13 17:59:35 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str

2024-11-13 17:59:35 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-13 17:59:35 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 17:59:35 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 17:59:35 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
marital_status_count = dfs['Marital Status'].value_counts()
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
2024-11-13 17:59:35 [INFO] Executing Step 1: CodeGenerator
2024-11-13 18:00:54 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 18:00:54 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Under 25,Current Employees,R&D,Life Sciences,STAFF-1096,303,Male,Research Scientist,Single,Yes,Y,1,53,0,243,17,Bachelor's Degree,1,4,57,4,2,1,5209,6153,8,24,4,3,80,0,22,4,22,1,13,6
Yes,Non-Travel,35 - 44,Ex-Employees,HR,Other,STAFF-95,53,Male,Manufacturing Director,Divorced,No,Y,6,40,0,438,7,Associates Degree,1,1,85,2,5,3,7644,16092,1,21,3,1,80,1,11,2,1,9,7,10
No,Travel_Frequently,45 - 54,Current Employees,Sales,Marketing,STAFF-1815,447,Female,Sales Executive,Married,Yes,Y,2,57,1,422,27,Master's Degree,1,3,55,1,4,4,2313,5044,7,12,3,4,80,2,7,1,29,2,11,13
</dataframe>


The user asked the following question:
### QUERY
 how many people are single and how many are married and visualise it using pie chart and bar graph.

You generated this python code:
marital_status_count = dfs['Marital Status'].value_counts()
plt.pie(marital_status_count.values.tolist(), labels=marital_status_count.keys().tolist(), autopct='%1.1f%%')

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
TypeError: list indices must be integers or slices, not str


Fix the python code above and return the new python code:
            
2024-11-13 18:00:54 [INFO] Code generated:
            ```
            Python
import matplotlib.pyplot as plt
import pandas as pd

# assuming 'dfs' is your DataFrame and you want to visualize the count of people who are married/singles
marital_status_count = dfs['Marital Status'].value_counts()

plt.figure(figsize=(5, 3)) # adjust size if needed
plt.bar(marital_status_count.index.tolist(), marital_status_count.values.tolist())
plt.xlabel('Marital Status')
plt.ylabel('Count')
plt.title('Number of People Who are Single/Married')

# Add title for each bar
for i, (label, count) in enumerate(zip(marital_status_count.index, marital_status_count.values)):
    plt.text(i, count + 3, f'{count}', ha='center', va='bottom')
            ```
            
2024-11-13 18:00:54 [INFO] Executing Step 2: CodeCleaning
2024-11-13 18:00:54 [INFO] 
Code running:
```
Python
marital_status_count = dfs['Marital Status'].value_counts()
plt.figure(figsize=(5, 3))
plt.bar(marital_status_count.index.tolist(), marital_status_count.values.tolist())
plt.xlabel('Marital Status')
plt.ylabel('Count')
plt.title('Number of People Who are Single/Married')
for i, (label, count) in enumerate(zip(marital_status_count.index, marital_status_count.values)):
    plt.text(i, count + 3, f'{count}', ha='center', va='bottom')
        ```
2024-11-13 18:00:54 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 18:00:54 [ERROR] Pipeline failed on step 6: name 'Python' is not defined
2024-11-13 18:04:49 [INFO] Question: visualise the data

2024-11-13 18:04:49 [INFO] Running PandasAI with local LLM...
2024-11-13 18:04:49 [INFO] Prompt ID: e5c1342d-db46-4934-9a6a-375d5d77a067
2024-11-13 18:04:49 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 18:04:49 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 18:04:49 [INFO] Executing Step 1: CacheLookup
2024-11-13 18:04:49 [INFO] Executing Step 2: PromptGeneration
2024-11-13 18:04:49 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Over 55,Current Employees,R&D,Life Sciences,STAFF-1012,732,Male,Laboratory Technician,Divorced,Yes,Y,1,23,0,1273,10,Bachelor's Degree,1,4,62,3,1,4,2862,6227,4,15,3,4,80,3,12,1,11,16,6,12
No,Non-Travel,45 - 54,Current Employees,HR,Medical,STAFF-699,916,Male,Healthcare Representative,Single,No,Y,5,57,1,989,1,Associates Degree,1,2,40,4,4,1,3375,4167,2,17,3,1,80,1,18,4,29,8,12,11
Yes,Travel_Frequently,Under 25,Ex-Employees,Sales,Technical Degree,STAFF-1465,1580,Female,Sales Executive,Married,No,Y,2,31,1,1245,8,Doctoral Degree,1,3,78,2,3,2,2756,13352,3,11,4,2,80,0,21,3,3,4,7,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data


Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 18:04:49 [INFO] Executing Step 3: CodeGenerator
2024-11-13 18:07:03 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 18:07:03 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Rarely,Over 55,Current Employees,R&D,Life Sciences,STAFF-1012,732,Male,Laboratory Technician,Divorced,Yes,Y,1,23,0,1273,10,Bachelor's Degree,1,4,62,3,1,4,2862,6227,4,15,3,4,80,3,12,1,11,16,6,12
No,Non-Travel,45 - 54,Current Employees,HR,Medical,STAFF-699,916,Male,Healthcare Representative,Single,No,Y,5,57,1,989,1,Associates Degree,1,2,40,4,4,1,3375,4167,2,17,3,1,80,1,18,4,29,8,12,11
Yes,Travel_Frequently,Under 25,Ex-Employees,Sales,Technical Degree,STAFF-1465,1580,Female,Sales Executive,Married,No,Y,2,31,1,1245,8,Doctoral Degree,1,3,78,2,3,2,2756,13352,3,11,4,2,80,0,21,3,3,4,7,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data


Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 18:07:03 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Load data into a list of DataFrames (assuming this was already done)
dfs = [...]  # load dfs...

# Create a single DataFrame by concatenating all the DataFrames in the list
df = pd.concat(dfs, ignore_index=True)

# Check if there are any null values in any column
print(df.isnull().sum())

# View your first few rows of data
print(df.head())

# Calculate mean, min and max of a specific column (e.g., 'Monthly Income')
monthly_income_mean = df['Monthly Income'].mean()
monthly_income_min = df['Monthly Income'].min()
monthly_income_max = df['Monthly Income'].max()

print(f"Mean: {monthly_income_mean}, Min: {monthly_income_min}, Max: {monthly_income_max}")

# Visualize data as a bar chart
plt.figure(figsize=(10,6))
df.groupby('Education')['Employee Count'].plot(kind='bar')
plt.title("Employee count grouped by Education")
plt.xlabel("Education")
plt.ylabel("Employee Count")
plt.tight_layout()
plt.show()

result = {
    "type": "dataframe",
    "value": df,
}

# if you need to plot, don't forget to import matplotlib
import matplotlib.pyplot as plt

plot_result = {
    "type": "plot",
    "value": "education_bar_chart.png"
}
            ```
            
2024-11-13 18:07:03 [INFO] Executing Step 4: CachePopulation
2024-11-13 18:07:04 [INFO] Executing Step 5: CodeCleaning
2024-11-13 18:07:04 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 18:07:04 [INFO] 
Code running:
```
df = pd.concat(dfs, ignore_index=True)
print(df.isnull().sum())
print(df.head())
monthly_income_mean = df['Monthly Income'].mean()
monthly_income_min = df['Monthly Income'].min()
monthly_income_max = df['Monthly Income'].max()
print(f'Mean: {monthly_income_mean}, Min: {monthly_income_min}, Max: {monthly_income_max}')
plt.figure(figsize=(10, 6))
df.groupby('Education')['Employee Count'].plot(kind='bar')
plt.title('Employee count grouped by Education')
plt.xlabel('Education')
plt.ylabel('Employee Count')
plt.tight_layout()
plt.show()
result = {'type': 'dataframe', 'value': df}
plot_result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
        ```
2024-11-13 18:07:04 [INFO] Executing Step 6: CodeExecution
2024-11-13 18:07:06 [INFO] Executing Step 7: ResultValidation
2024-11-13 18:07:06 [INFO] Answer: {'type': 'dataframe', 'value':      Attrition    Business Travel CF_age band  ... Years In Current Role Years Since Last Promotion Years With Curr Manager
0          Yes      Travel_Rarely     35 - 44  ...                     4                          0                       5
1           No  Travel_Frequently     45 - 54  ...                     7                          1                       7
2          Yes      Travel_Rarely     35 - 44  ...                     0                          0                       0
3           No  Travel_Frequently     25 - 34  ...                     7                          3                       0
4           No      Travel_Rarely     25 - 34  ...                     2                          2                       2
...        ...                ...         ...  ...                   ...                        ...                     ...
1465       Yes         Non-Travel     25 - 34  ...                     2                          3                       0
1466       Yes  Travel_Frequently     25 - 34  ...                     0                          1                       0
1467       Yes  Travel_Frequently     35 - 44  ...                     9                          6                       7
1468       Yes      Travel_Rarely    Under 25  ...                     0                          0                       0
1469       Yes      Travel_Rarely    Under 25  ...                     2                          0                       2

[1470 rows x 39 columns]}
2024-11-13 18:07:06 [INFO] Executing Step 8: ResultParsing
2024-11-13 22:00:23 [INFO] Question: visualise the data in the form of bar graph
2024-11-13 22:00:23 [INFO] Running PandasAI with local LLM...
2024-11-13 22:00:23 [INFO] Prompt ID: f638a12b-334b-47fa-a1e9-4068d4b6acc4
2024-11-13 22:00:23 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:00:23 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:00:23 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:00:23 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:00:23 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Ex-Employees,R&D,Medical,STAFF-502,1805,Male,Laboratory Technician,Divorced,No,Y,0,24,0,1176,11,Master's Degree,1,1,52,4,1,2,4424,25103,2,14,4,2,80,0,28,2,6,4,12,7
No,Travel_Rarely,Under 25,Current Employees,HR,Life Sciences,STAFF-601,380,Male,Sales Executive,Married,Yes,Y,1,54,0,737,13,Associates Degree,1,2,98,1,2,4,4668,2104,6,21,3,3,80,1,1,1,1,10,10,11
Yes,Non-Travel,45 - 54,Current Employees,Sales,Technical Degree,STAFF-1779,780,Female,Manufacturing Director,Single,No,Y,6,37,1,937,29,High School,1,4,55,2,4,3,2367,5615,3,19,4,1,80,3,8,4,9,8,14,6
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of bar graph

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:00:23 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:01:54 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:01:54 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Ex-Employees,R&D,Medical,STAFF-502,1805,Male,Laboratory Technician,Divorced,No,Y,0,24,0,1176,11,Master's Degree,1,1,52,4,1,2,4424,25103,2,14,4,2,80,0,28,2,6,4,12,7
No,Travel_Rarely,Under 25,Current Employees,HR,Life Sciences,STAFF-601,380,Male,Sales Executive,Married,Yes,Y,1,54,0,737,13,Associates Degree,1,2,98,1,2,4,4668,2104,6,21,3,3,80,1,1,1,1,10,10,11
Yes,Non-Travel,45 - 54,Current Employees,Sales,Technical Degree,STAFF-1779,780,Female,Manufacturing Director,Single,No,Y,6,37,1,937,29,High School,1,4,55,2,4,3,2367,5615,3,19,4,1,80,3,8,4,9,8,14,6
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of bar graph

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 22:01:54 [INFO] Code generated:
            ```
            # Import required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Create a bar graph using matplotlib
dfs = [...];  # Your dataframes here

# Extract the column you want to plot from the first dataframe
column_to_plot = dfs[0]['Attrition']

# Plot the data
plt.figure(figsize=(10,6))
plt.bar(range(len(column_to_plot)), column_to_plot)
plt.xlabel('Index')
plt.ylabel('Attrition Value')
plt.title('Attrition Bar Graph')

# Save the plot as a PNG file
plt.savefig('attrition_bar_graph.png')

# Declare result variable
result = {
    "type": "plot",
    "value": "attrition_bar_graph.png"
}

print(result)
            ```
            
2024-11-13 22:01:54 [INFO] Executing Step 4: CachePopulation
2024-11-13 22:01:55 [INFO] Executing Step 5: CodeCleaning
2024-11-13 22:01:55 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:01:55 [INFO] 
Code running:
```
column_to_plot = dfs[0]['Attrition']
plt.figure(figsize=(10, 6))
plt.bar(range(len(column_to_plot)), column_to_plot)
plt.xlabel('Index')
plt.ylabel('Attrition Value')
plt.title('Attrition Bar Graph')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)
        ```
2024-11-13 22:01:55 [INFO] Executing Step 6: CodeExecution
2024-11-13 22:02:00 [INFO] Executing Step 7: ResultValidation
2024-11-13 22:02:00 [INFO] Answer: {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
2024-11-13 22:02:00 [INFO] Executing Step 8: ResultParsing
2024-11-13 22:02:23 [INFO] Question: visualise the data in the form of pir chart
2024-11-13 22:02:23 [INFO] Running PandasAI with local LLM...
2024-11-13 22:02:23 [INFO] Prompt ID: 5a9d7c9d-7d78-4d10-8a51-807f3697c317
2024-11-13 22:02:23 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:02:24 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:02:24 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:02:24 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:02:24 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,Sales,Life Sciences,STAFF-96,1407,Male,Human Resources,Divorced,No,Y,4,40,1,868,5,Bachelor's Degree,1,2,46,1,3,2,13503,12392,1,15,4,1,80,0,34,4,9,11,8,12
No,Travel_Rarely,35 - 44,Current Employees,R&D,Medical,STAFF-1461,155,Female,Research Director,Married,Yes,Y,6,21,0,1128,10,Master's Degree,1,1,44,3,5,1,12808,26062,0,12,4,3,80,3,31,3,22,0,9,14
Yes,Non-Travel,Under 25,Ex-Employees,HR,Human Resources,STAFF-631,897,Male,Manufacturing Director,Single,No,Y,3,48,1,1444,2,High School,1,4,40,4,2,3,19094,8213,7,20,3,2,80,1,12,1,37,18,6,9
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of pir chart

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:02:24 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:04:23 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:04:23 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Travel_Frequently,Over 55,Current Employees,Sales,Life Sciences,STAFF-96,1407,Male,Human Resources,Divorced,No,Y,4,40,1,868,5,Bachelor's Degree,1,2,46,1,3,2,13503,12392,1,15,4,1,80,0,34,4,9,11,8,12
No,Travel_Rarely,35 - 44,Current Employees,R&D,Medical,STAFF-1461,155,Female,Research Director,Married,Yes,Y,6,21,0,1128,10,Master's Degree,1,1,44,3,5,1,12808,26062,0,12,4,3,80,3,31,3,22,0,9,14
Yes,Non-Travel,Under 25,Ex-Employees,HR,Human Resources,STAFF-631,897,Male,Manufacturing Director,Single,No,Y,3,48,1,1444,2,High School,1,4,40,4,2,3,19094,8213,7,20,3,2,80,1,12,1,37,18,6,9
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of pir chart

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 22:04:23 [INFO] Code generated:
            ```
            # Import required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Declare result var:
result = {}

# Group dataframe by categories and generate counts for each category
pir_counts = dfs[0].groupby(['CF_age band', 'Job Level']).size().reset_index(name='Count')

# Plot the PIR chart using matplotlib
fig, ax = plt.subplots()
ax.bar(pir_counts['CF_age band'], pir_counts['Count'])
ax.set_xlabel('Age Band')
ax.set_ylabel('Count')
ax.set_title('PIR Chart: Employee Counts by Age Band and Job Level')

# Save the plot as a PNG file
plt.savefig('pir_chart.png', dpi=300)

# Store the result in a dictionary
result = {"type": "plot", "value": 'pir_chart.png'}
print(result)
            ```
            
2024-11-13 22:04:23 [INFO] Executing Step 4: CachePopulation
2024-11-13 22:04:23 [INFO] Executing Step 5: CodeCleaning
2024-11-13 22:04:23 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:04:23 [INFO] 
Code running:
```
result = {}
pir_counts = dfs[0].groupby(['CF_age band', 'Job Level']).size().reset_index(name='Count')
fig, ax = plt.subplots()
ax.bar(pir_counts['CF_age band'], pir_counts['Count'])
ax.set_xlabel('Age Band')
ax.set_ylabel('Count')
ax.set_title('PIR Chart: Employee Counts by Age Band and Job Level')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png', dpi=300)
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
print(result)
        ```
2024-11-13 22:04:23 [INFO] Executing Step 6: CodeExecution
2024-11-13 22:04:25 [INFO] Executing Step 7: ResultValidation
2024-11-13 22:04:25 [INFO] Answer: {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
2024-11-13 22:04:25 [INFO] Executing Step 8: ResultParsing
2024-11-13 22:04:42 [INFO] Question: visualise the data in the form of pie chart
2024-11-13 22:04:42 [INFO] Running PandasAI with local LLM...
2024-11-13 22:04:42 [INFO] Prompt ID: 98821522-34f9-4554-a954-5e4f93f23090
2024-11-13 22:04:42 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:04:42 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:04:42 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:04:42 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:04:42 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,45 - 54,Current Employees,HR,Life Sciences,STAFF-717,1606,Female,Human Resources,Married,Yes,Y,0,37,1,429,4,Associates Degree,1,3,43,2,4,3,3579,3031,6,21,3,2,80,3,21,1,5,3,7,10
Yes,Travel_Rarely,35 - 44,Ex-Employees,Sales,Medical,STAFF-1292,151,Female,Sales Executive,Divorced,Yes,Y,3,24,0,141,24,Master's Degree,1,2,74,1,5,4,6334,20251,1,11,4,4,80,0,17,2,24,6,14,1
Yes,Travel_Frequently,25 - 34,Current Employees,R&D,Marketing,STAFF-1739,231,Male,Manufacturing Director,Single,No,Y,4,53,0,1305,21,Bachelor's Degree,1,1,46,3,1,2,4805,19246,7,17,3,3,80,2,38,4,0,11,13,11
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of pie chart

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:04:42 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:06:16 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:06:16 [ERROR] Pipeline failed on step 3: No code found in the response
2024-11-13 22:21:51 [INFO] Question: visualise the data in the form of a image
2024-11-13 22:21:51 [INFO] Running PandasAI with local LLM...
2024-11-13 22:21:51 [INFO] Prompt ID: cf33e8c7-efb7-4039-9128-e02fb83d4c31
2024-11-13 22:21:51 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:21:51 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:21:52 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:21:52 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:21:52 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of a image

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:21:52 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:26:50 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:26:50 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 visualise the data in the form of a image

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 22:26:51 [INFO] Code generated:
            ```
            Python
# TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

dfs = [pd.DataFrame({
    'Attrition': ['No', 'Yes', 'No'],
    'Business Travel': ['No', 'Travel_Frequently', 'Travel_Rarely'],
    'CF_age band': ['25 - 34', '35 - 44', '45 - 54'],
    'CF_attrition label': ['Ex-Employees', 'Current Employees', 'Ex-Employees'],
    'Department': ['Sales', 'R&D', 'HR'],
    'Education Field': ['Other', 'Marketing', 'Technical Degree'],
    'emp no': [1826, 2036, 493],
    'Employee Number': [451, 912, 947],
    'Gender': ['Female', 'Male', 'Female'],
    'Job Role': ['Sales Executive', 'Research Scientist', 'Healthcare Representative'],
    'Marital Status': ['Married', 'Divorced', 'Single'],
    'Over Time': ['No', 'Y', 'Y'],
    'Over18': [6, 4, 3],
    'Training Times Last Year': [58, 34, 38],
    'Age': [823, 648, 329],
    'CF_current Employee': [1, 2, 3],
    'Daily Rate': [22, 26, 13],
    'Distance From Home': ['Master\'s Degree', 'Bachelor\'s Degree', 'High School'],
    'Education': [58, 34, 54],
    'Employee Count': [823, 648, 329],
    'Environment Satisfaction': [68, 57, 54],
    'Hourly Rate': [4, 1, 3],
    'Job Involvement': [80, 80, 80],
    'Job Level': [2, 1, 1],
    'Job Satisfaction': [4, 4, 1],
    'Monthly Income': [25811, 14842, 9396],
    'Monthly Rate': [4809, 9619, 2718],
    'Num Companies Worked': ['5', '3', '0'],
    'Percent Salary Hike': ['16', '14', '13'],
    'Performance Rating': ['4', '3', '1'],
    'Relationship Satisfaction': [11, 10, 8]
})]

# Define the function to visualize the data
def visualize_data(dfs):
    # Select a random dataframe from the list
    df = dfs[0].sample(n=5)

    # Plot the distribution of Job Level
    plt.figure(figsize=(10,6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('./job_level_distribution.png')

    result = {"type": "plot", "value": 'job_level_distribution.png'}

    return result

# Call the function
print(visualize_data(dfs))
            ```
            
2024-11-13 22:26:51 [INFO] Executing Step 4: CachePopulation
2024-11-13 22:26:51 [INFO] Executing Step 5: CodeCleaning
2024-11-13 22:26:51 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:26:51 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:26:51 [INFO] Executing Step 6: CodeExecution
2024-11-13 22:26:51 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:26:51 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 22:26:51 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:26:52 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:26:52 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-13 22:26:52 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:28:18 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:28:18 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 22:28:18 [INFO] Code generated:
            ```
            Python
import pandas as pd
from matplotlib import pyplot as plt

def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('temp_chart.png')
    result = {'type': 'plot', 'value': 'temp_chart.png'}
    return result


print(visualize_data(dfs))
            ```
            
2024-11-13 22:28:18 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:28:18 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:28:18 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:28:18 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:28:18 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-13 22:28:18 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:28:18 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:28:18 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-13 22:28:18 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:29:31 [INFO] Question: visualise the data in the form of a image
2024-11-13 22:29:31 [INFO] Running PandasAI with local LLM...
2024-11-13 22:29:31 [INFO] Prompt ID: 988bae70-9424-46b5-9d98-409498d8c09b
2024-11-13 22:29:31 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:29:31 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:29:31 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:29:31 [INFO] Using cached response
2024-11-13 22:29:31 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:29:31 [INFO] Executing Step 2: Skipping...
2024-11-13 22:29:31 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:29:31 [INFO] Executing Step 3: Skipping...
2024-11-13 22:29:31 [INFO] Executing Step 4: CachePopulation
2024-11-13 22:29:31 [INFO] Executing Step 4: Skipping...
2024-11-13 22:29:31 [INFO] Executing Step 5: CodeCleaning
2024-11-13 22:29:31 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:29:31 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:29:31 [INFO] Executing Step 6: CodeExecution
2024-11-13 22:29:31 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:29:31 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 22:29:31 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:29:31 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:29:31 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-13 22:29:31 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:29:50 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:29:50 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 22:29:50 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('temp_chart.png')  # Removed the directory path
    result = {'type': 'plot', 'value': 'temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:29:50 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:29:50 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:29:50 [INFO] 
Code running:
```
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:29:51 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-11-13 22:29:51 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-13 22:29:51 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:29:51 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:29:51 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
2024-11-13 22:29:51 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:31:12 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:31:12 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 22:31:13 [INFO] Code generated:
            ```
            import matplotlib.pyplot as plt
import pandas as pd

def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:31:13 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:31:13 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:31:13 [INFO] 
Code running:
```
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:31:13 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-11-13 22:31:13 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-13 22:31:13 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:31:13 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:31:13 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
2024-11-13 22:31:13 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:32:52 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:32:52 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Ex-Employees,Sales,Other,STAFF-451,1826,Female,Sales Executive,Married,No,Y,6,58,0,823,22,Master's Degree,1,2,68,4,3,3,4809,25811,5,16,4,2,80,0,2,4,40,2,2,11
Yes,Travel_Frequently,35 - 44,Current Employees,R&D,Marketing,STAFF-912,2036,Male,Research Scientist,Divorced,Yes,Y,4,34,0,648,26,Bachelor's Degree,1,1,57,1,4,4,9619,14842,3,14,3,1,80,2,32,3,0,18,5,10
No,Travel_Rarely,45 - 54,Ex-Employees,HR,Technical Degree,STAFF-947,493,Female,Healthcare Representative,Single,No,Y,3,38,1,329,13,High School,1,3,54,3,2,1,2718,9396,0,13,4,4,80,1,37,1,20,4,8,2
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
            
2024-11-13 22:32:52 [INFO] Code generated:
            ```
            Python
import pandas as pd
import matplotlib.pyplot as plt

def visualize_data(dfs):
    try:
        df = dfs[0].sample(n=5)
        plt.figure(figsize=(10, 6))
        df.plot(kind='bar', x='Job Role', y='Job Level')
        plt.title('Distribution of Job Level')
        plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
        result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
        return result
    except Exception as e:
        print(f"An error occurred: {e}")
        return {"error": "Failed to visualize data"}
            ```
            
2024-11-13 22:32:52 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:32:52 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:32:52 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    try:
        df = dfs[0].sample(n=5)
        plt.figure(figsize=(10, 6))
        df.plot(kind='bar', x='Job Role', y='Job Level')
        plt.title('Distribution of Job Level')
        plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
        result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
        return result
    except Exception as e:
        print(f'An error occurred: {e}')
        return {'error': 'Failed to visualize data'}
        ```
2024-11-13 22:32:52 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:32:52 [ERROR] Pipeline failed on step 6: name 'Python' is not defined
2024-11-13 22:35:19 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:35:19 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
            
2024-11-13 22:35:19 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,
                square=True, linewidths=.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:35:19 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:35:19 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:35:19 [INFO] 
Code running:
```
def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:35:19 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 13, in <module>
  File "<string>", line 6, in visualize_data
NameError: name 'sns' is not defined

2024-11-13 22:35:19 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-13 22:35:19 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:35:19 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:35:19 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 13, in <module>
  File "<string>", line 6, in visualize_data
NameError: name 'sns' is not defined


Fix the python code above and return the new python code:
2024-11-13 22:35:19 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:36:55 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:36:55 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,25 - 34,Current Employees,HR,Human Resources,STAFF-1207,194,Male,Manufacturing Director,Single,Yes,Y,0,35,0,472,10,High School,1,1,90,1,1,4,10686,3142,9,19,4,4,80,3,30,2,11,5,14,15
Yes,Travel_Frequently,35 - 44,Ex-Employees,R&D,Other,STAFF-1119,1010,Female,Human Resources,Divorced,No,Y,2,59,1,766,23,Associates Degree,1,4,54,4,5,3,10502,17456,4,17,3,2,80,0,32,1,40,12,0,0
No,Non-Travel,Under 25,Current Employees,Sales,Medical,STAFF-1412,530,Female,Sales Representative,Married,Yes,Y,4,29,1,195,21,Master's Degree,1,3,84,3,3,1,5505,24793,7,16,3,1,80,2,23,4,14,10,8,10
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 13, in <module>
  File "<string>", line 6, in visualize_data
NameError: name 'sns' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 22:36:55 [INFO] Code generated:
            ```
            Python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:36:55 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:36:55 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:36:55 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    df = dfs[0]
    corr = df.corr()
    mask = np.triu(np.ones_like(corr, dtype=bool))
    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(230, 20, as_cmap=True)
    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0, square=True, linewidths=0.5)
    plt.title('DataFrame Correlation')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:36:55 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:36:55 [ERROR] Pipeline failed on step 6: name 'Python' is not defined
2024-11-13 22:46:40 [INFO] Question: visualise the data in the form of a image
2024-11-13 22:46:40 [INFO] Running PandasAI with local LLM...
2024-11-13 22:46:40 [INFO] Prompt ID: 4a3e9079-31eb-4bd4-90d9-cd9fb7898b75
2024-11-13 22:46:40 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:46:40 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:46:40 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:46:40 [INFO] Using cached response
2024-11-13 22:46:40 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:46:40 [INFO] Executing Step 2: Skipping...
2024-11-13 22:46:40 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:46:40 [INFO] Executing Step 3: Skipping...
2024-11-13 22:46:40 [INFO] Executing Step 4: CachePopulation
2024-11-13 22:46:40 [INFO] Executing Step 4: Skipping...
2024-11-13 22:46:40 [INFO] Executing Step 5: CodeCleaning
2024-11-13 22:46:40 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:46:40 [INFO] 
Code running:
```
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:46:40 [INFO] Executing Step 6: CodeExecution
2024-11-13 22:46:40 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined

2024-11-13 22:46:40 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 22:46:40 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:46:40 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:46:40 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
2024-11-13 22:46:40 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:47:56 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:47:56 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
Python


def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'Python' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 22:47:56 [INFO] Code generated:
            ```
            import matplotlib.pyplot as plt

def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:47:56 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:47:56 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:47:56 [INFO] 
Code running:
```
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:47:56 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-11-13 22:47:56 [WARNING] Failed to execute code retrying with a correction framework [retry number: 2]
2024-11-13 22:47:56 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:47:56 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:47:56 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
2024-11-13 22:47:56 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:49:15 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:49:15 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0].sample(n=5)
    plt.figure(figsize=(10, 6))
    df.plot(kind='bar', x='Job Role', y='Job Level')
    plt.title('Distribution of Job Level')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
            
2024-11-13 22:49:15 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

def visualize_data(dfs):
    df = dfs[0]
    plt.figure(figsize=(10, 6))
    plt.scatter(df['Job Role'], df['Age']) 
    plt.title('Distribution of Job Level vs Age')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:49:15 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:49:15 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:49:15 [INFO] 
Code running:
```
def visualize_data(dfs):
    df = dfs[0]
    plt.figure(figsize=(10, 6))
    plt.scatter(df['Job Role'], df['Age'])
    plt.title('Distribution of Job Level vs Age')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:49:16 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-11-13 22:49:16 [WARNING] Failed to execute code retrying with a correction framework [retry number: 3]
2024-11-13 22:49:16 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 22:49:16 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 22:49:16 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0]
    plt.figure(figsize=(10, 6))
    plt.scatter(df['Job Role'], df['Age'])
    plt.title('Distribution of Job Level vs Age')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
2024-11-13 22:49:16 [INFO] Executing Step 1: CodeGenerator
2024-11-13 22:50:55 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:50:55 [INFO] Prompt used:
            <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Current Employees,Sales,Medical,STAFF-990,847,Female,Sales Representative,Divorced,No,Y,5,32,0,704,13,Master's Degree,1,1,35,4,1,1,13142,15624,4,17,3,1,80,0,38,4,5,6,11,17
Yes,Non-Travel,45 - 54,Ex-Employees,HR,Other,STAFF-1314,641,Male,Manager,Married,No,Y,3,59,1,363,18,High School,1,2,92,2,4,2,4403,9150,2,25,4,3,80,3,1,2,36,5,2,13
No,Travel_Frequently,Under 25,Ex-Employees,R&D,Technical Degree,STAFF-516,844,Female,Healthcare Representative,Single,Yes,Y,2,54,0,1179,27,Bachelor's Degree,1,3,52,1,3,3,7969,8007,8,24,4,4,80,1,14,1,7,9,8,9
</dataframe>


The user asked the following question:
### QUERY
 visualise the data in the form of a image

You generated this python code:
def visualize_data(dfs):
    df = dfs[0]
    plt.figure(figsize=(10, 6))
    plt.scatter(df['Job Role'], df['Age'])
    plt.title('Distribution of Job Level vs Age')
    plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
    result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
    return result


print(visualize_data(dfs))

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned


Fix the python code above and return the new python code:
            
2024-11-13 22:50:55 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

def visualize_data(dfs):
    if dfs:
        df = dfs[0]
        if 'Age' in df.columns and 'Job Role' in df.columns:
            # Create a scatter plot to visualize distribution of job level vs age
            plt.figure(figsize=(10, 6))
            plt.scatter(df['Age'], df['Job Role'])
            plt.title('Distribution of Job Level vs Age')
            plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
            result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exists/charts/temp_chart.png'}
            return result
    result = {'type': 'error', 'message': "No data to visualize"}
    return result

print(visualize_data(dfs))
            ```
            
2024-11-13 22:50:55 [INFO] Executing Step 2: CodeCleaning
2024-11-13 22:50:55 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 22:50:55 [INFO] 
Code running:
```
def visualize_data(dfs):
    if dfs:
        df = dfs[0]
        if 'Age' in df.columns and 'Job Role' in df.columns:
            plt.figure(figsize=(10, 6))
            plt.scatter(df['Age'], df['Job Role'])
            plt.title('Distribution of Job Level vs Age')
            plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
            result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
            return result
    result = {'type': 'error', 'message': 'No data to visualize'}
    return result


print(visualize_data(dfs))
        ```
2024-11-13 22:50:55 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 175, in execute_code
    raise NoResultFoundError("No result returned")
pandasai.exceptions.NoResultFoundError: No result returned

2024-11-13 22:50:55 [ERROR] Pipeline failed on step 6: No result returned
2024-11-13 22:51:41 [INFO] Question: create a bar graph for the male and female according to their age!
2024-11-13 22:51:41 [INFO] Running PandasAI with local LLM...
2024-11-13 22:51:41 [INFO] Prompt ID: 2bf055f4-c6ee-4abf-bfd0-4b9c9b88ff12
2024-11-13 22:51:41 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:51:41 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:51:41 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:51:41 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:51:41 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
Yes,Travel_Rarely,Over 55,Ex-Employees,HR,Medical,STAFF-820,1012,Female,Manager,Divorced,No,Y,6,20,1,305,16,Bachelor's Degree,1,1,77,3,1,1,4878,9953,5,21,4,2,80,2,0,1,25,4,3,15
No,Travel_Frequently,25 - 34,Current Employees,R&D,Life Sciences,STAFF-343,1709,Female,Manufacturing Director,Single,Yes,Y,5,26,0,1213,14,Associates Degree,1,4,43,1,2,4,3319,17056,6,18,4,4,80,3,20,4,7,9,5,14
No,Non-Travel,35 - 44,Ex-Employees,Sales,Technical Degree,STAFF-1032,933,Male,Research Scientist,Married,No,Y,2,39,1,855,5,Master's Degree,1,3,47,4,5,2,5813,26862,3,13,3,3,80,1,26,2,12,8,2,17
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 create a bar graph for the male and female according to their age!

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:51:41 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:53:35 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:53:35 [ERROR] Pipeline failed on step 3: No code found in the response
2024-11-13 22:57:09 [INFO] Question: create a bar graph for the male and female.
2024-11-13 22:57:09 [INFO] Running PandasAI with local LLM...
2024-11-13 22:57:09 [INFO] Prompt ID: 9221fe22-3ec6-46b3-8cb3-d27c25fedaa1
2024-11-13 22:57:09 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:57:09 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:57:09 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:57:09 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:57:09 [INFO] Using prompt: <dataframe>
dfs[0]:1470x39
Attrition,Business Travel,CF_age band,CF_attrition label,Department,Education Field,emp no,Employee Number,Gender,Job Role,Marital Status,Over Time,Over18,Training Times Last Year,Age,CF_current Employee,Daily Rate,Distance From Home,Education,Employee Count,Environment Satisfaction,Hourly Rate,Job Involvement,Job Level,Job Satisfaction,Monthly Income,Monthly Rate,Num Companies Worked,Percent Salary Hike,Performance Rating,Relationship Satisfaction,Standard Hours,Stock Option Level,Total Working Years,Work Life Balance,Years At Company,Years In Current Role,Years Since Last Promotion,Years With Curr Manager
No,Non-Travel,25 - 34,Current Employees,Sales,Medical,STAFF-951,1071,Male,Research Director,Divorced,Yes,Y,1,46,0,869,22,Master's Degree,1,4,75,2,1,1,10793,5718,8,18,4,3,80,2,4,2,33,3,8,5
Yes,Travel_Frequently,Under 25,Ex-Employees,R&D,Other,STAFF-230,1799,Female,Healthcare Representative,Married,No,Y,2,18,1,1392,3,Bachelor's Degree,1,3,41,3,4,4,17924,3173,9,15,3,1,80,3,34,1,9,13,9,9
Yes,Travel_Rarely,45 - 54,Current Employees,HR,Human Resources,STAFF-381,1215,Female,Research Scientist,Single,No,Y,4,42,0,1381,12,Associates Degree,1,1,99,4,5,3,6500,13586,0,12,4,2,80,1,2,3,40,0,1,6
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 create a bar graph for the male and female.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:57:09 [INFO] Executing Step 3: CodeGenerator
2024-11-13 22:58:26 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 22:58:26 [ERROR] Pipeline failed on step 3: No code found in the response
2024-11-13 22:59:33 [INFO] Question: generate the graph on the basis of sex.
2024-11-13 22:59:33 [INFO] Running PandasAI with local LLM...
2024-11-13 22:59:33 [INFO] Prompt ID: 91c4f96f-96ed-4344-b8b2-0b91c04ab02d
2024-11-13 22:59:33 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 22:59:33 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 22:59:33 [INFO] Executing Step 1: CacheLookup
2024-11-13 22:59:33 [INFO] Executing Step 2: PromptGeneration
2024-11-13 22:59:33 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,female,0.92,1,5,20.575,S,Third,man,False,G,Cherbourg,no,True
1,2,male,,5,4,7.225,C,Second,woman,False,,,yes,False
0,1,female,1.0,3,0,11.5,,First,child,True,E,Queenstown,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of sex.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 22:59:33 [INFO] Executing Step 3: CodeGenerator
2024-11-13 23:00:31 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 23:00:31 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,3,female,0.92,1,5,20.575,S,Third,man,False,G,Cherbourg,no,True
1,2,male,,5,4,7.225,C,Second,woman,False,,,yes,False
0,1,female,1.0,3,0,11.5,,First,child,True,E,Queenstown,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of sex.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 23:00:31 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

dfs = [...] # Your DataFrame list is filled with dataframes here.

result = {
    "type": "plot",
    "value": "sex_graph.png"
}

# Group the data by sex and calculate the size of each group
sex_counts = dfs[0].groupby('sex')['survived'].count()

# Create a pie chart to display the count for each sex
plt.figure(figsize=(8, 6))
plt.pie(sex_counts, labels=sex_counts.index, autopct='%1.1f%%')
plt.title('Survival by Sex')

# Save the plot as a PNG file
plt.savefig('sex_graph.png')

result
            ```
            
2024-11-13 23:00:31 [INFO] Executing Step 4: CachePopulation
2024-11-13 23:00:32 [INFO] Executing Step 5: CodeCleaning
2024-11-13 23:00:32 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 23:00:32 [INFO] 
Code running:
```
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
sex_counts = dfs[0].groupby('sex')['survived'].count()
plt.figure(figsize=(8, 6))
plt.pie(sex_counts, labels=sex_counts.index, autopct='%1.1f%%')
plt.title('Survival by Sex')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result
        ```
2024-11-13 23:00:32 [INFO] Executing Step 6: CodeExecution
2024-11-13 23:00:32 [INFO] Executing Step 7: ResultValidation
2024-11-13 23:00:32 [INFO] Answer: {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
2024-11-13 23:00:32 [INFO] Executing Step 8: ResultParsing
2024-11-13 23:03:23 [INFO] Question: generate the graph on the basis of age.
2024-11-13 23:03:23 [INFO] Running PandasAI with local LLM...
2024-11-13 23:03:23 [INFO] Prompt ID: cbce35f3-3509-4b46-ae17-c5c03aa40896
2024-11-13 23:03:23 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 23:03:23 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 23:03:23 [INFO] Executing Step 1: CacheLookup
2024-11-13 23:03:23 [INFO] Executing Step 2: PromptGeneration
2024-11-13 23:03:23 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,female,,5,2,8.5167,C,First,man,False,E,,no,False
0,2,male,70.5,4,4,73.5,,Second,woman,True,B,Southampton,yes,True
1,1,male,47.0,3,6,14.0,S,Third,child,True,,Cherbourg,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of age.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 23:03:23 [INFO] Executing Step 3: CodeGenerator
2024-11-13 23:04:21 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 23:04:21 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,female,,5,2,8.5167,C,First,man,False,E,,no,False
0,2,male,70.5,4,4,73.5,,Second,woman,True,B,Southampton,yes,True
1,1,male,47.0,3,6,14.0,S,Third,child,True,,Cherbourg,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of age.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 23:04:21 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd
import matplotlib.pyplot as plt

# Write code here

dfs = []  # Declare dfs variable as an empty list
dfs.append(pd.read_csv(StringIO(dataframe)))  # Use the given dataframe

# Filter out rows where age is missing (represented by "")
age_df = dfs[0].dropna(subset=["age"])

# Group the data by age and count the number of passengers
age_counts = age_df["age"].value_counts()

# Create a bar chart
plt.bar(age_counts.index, age_counts.values)
plt.xlabel("Age")
plt.ylabel("Count")
plt.title("Distribution of Passengers by Age")

# Save the plot as a PNG file
plt.savefig("age_distribution.png")

result = {
    "type": "plot",
    "value": "age_distribution.png"
}
            ```
            
2024-11-13 23:04:21 [INFO] Executing Step 4: CachePopulation
2024-11-13 23:04:21 [INFO] Executing Step 5: CodeCleaning
2024-11-13 23:04:21 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 23:04:21 [INFO] 
Code running:
```
dfs.append(pd.read_csv(StringIO(dataframe)))
age_df = dfs[0].dropna(subset=['age'])
age_counts = age_df['age'].value_counts()
plt.bar(age_counts.index, age_counts.values)
plt.xlabel('Age')
plt.ylabel('Count')
plt.title('Distribution of Passengers by Age')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
        ```
2024-11-13 23:04:21 [INFO] Executing Step 6: CodeExecution
2024-11-13 23:04:21 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'StringIO' is not defined

2024-11-13 23:04:21 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 23:04:21 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 23:04:21 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 23:04:21 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,female,,5,2,8.5167,C,First,man,False,E,,no,False
0,2,male,70.5,4,4,73.5,,Second,woman,True,B,Southampton,yes,True
1,1,male,47.0,3,6,14.0,S,Third,child,True,,Cherbourg,no,True
</dataframe>


The user asked the following question:
### QUERY
 generate the graph on the basis of age.

You generated this python code:
dfs.append(pd.read_csv(StringIO(dataframe)))
age_df = dfs[0].dropna(subset=['age'])
age_counts = age_df['age'].value_counts()
plt.bar(age_counts.index, age_counts.values)
plt.xlabel('Age')
plt.ylabel('Count')
plt.title('Distribution of Passengers by Age')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'StringIO' is not defined


Fix the python code above and return the new python code:
2024-11-13 23:04:21 [INFO] Executing Step 1: CodeGenerator
2024-11-13 23:05:24 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 23:05:24 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,3,female,,5,2,8.5167,C,First,man,False,E,,no,False
0,2,male,70.5,4,4,73.5,,Second,woman,True,B,Southampton,yes,True
1,1,male,47.0,3,6,14.0,S,Third,child,True,,Cherbourg,no,True
</dataframe>


The user asked the following question:
### QUERY
 generate the graph on the basis of age.

You generated this python code:
dfs.append(pd.read_csv(StringIO(dataframe)))
age_df = dfs[0].dropna(subset=['age'])
age_counts = age_df['age'].value_counts()
plt.bar(age_counts.index, age_counts.values)
plt.xlabel('Age')
plt.ylabel('Count')
plt.title('Distribution of Passengers by Age')
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result = {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 1, in <module>
NameError: name 'StringIO' is not defined


Fix the python code above and return the new python code:
            
2024-11-13 23:05:24 [INFO] Code generated:
            ```
            from io import StringIO
            ```
            
2024-11-13 23:05:24 [INFO] Executing Step 2: CodeCleaning
2024-11-13 23:05:24 [ERROR] Pipeline failed on step 2: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-11-13 23:05:24 [ERROR] Pipeline failed on step 6: Code shouldn't use 'os', 'io' or 'chr', 'b64decode' functions as this could lead to malicious code execution.
2024-11-13 23:07:37 [INFO] Question: generate the graph on the basis of pclass
.
2024-11-13 23:07:37 [INFO] Running PandasAI with local LLM...
2024-11-13 23:07:37 [INFO] Prompt ID: 8799e238-01c7-46cd-b8bb-9d1827bc89eb
2024-11-13 23:07:37 [INFO] Executing Pipeline: GenerateChatPipeline
2024-11-13 23:07:37 [INFO] Executing Step 0: ValidatePipelineInput
2024-11-13 23:07:37 [INFO] Executing Step 1: CacheLookup
2024-11-13 23:07:37 [INFO] Executing Step 2: PromptGeneration
2024-11-13 23:07:37 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,male,21.0,0,2,25.4667,S,Third,man,False,B,Cherbourg,no,True
0,2,female,65.0,2,1,6.95,,First,child,True,,Southampton,yes,False
0,3,female,,4,6,63.3583,C,Second,woman,True,F,,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of pclass
.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-11-13 23:07:37 [INFO] Executing Step 3: CodeGenerator
2024-11-13 23:08:31 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 23:08:31 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,male,21.0,0,2,25.4667,S,Third,man,False,B,Cherbourg,no,True
0,2,female,65.0,2,1,6.95,,First,child,True,,Southampton,yes,False
0,3,female,,4,6,63.3583,C,Second,woman,True,F,,no,True
</dataframe>




Update this initial code:
```python
# TODO: import the required dependencies
import pandas as pd

# Write code here

# Declare result var: 
type (possible values "string", "number", "dataframe", "plot"). Examples: { "type": "string", "value": f"The highest salary is {highest_salary}." } or { "type": "number", "value": 125 } or { "type": "dataframe", "value": pd.DataFrame({...}) } or { "type": "plot", "value": "temp_chart.png" }

```



### QUERY
 generate the graph on the basis of pclass
.

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
            
2024-11-13 23:08:31 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

# Write code here

result = {"type": "plot", "value": None}

dfs[0].groupby('pclass')['survived'].mean().unstack().plot(kind='bar', figsize=(10,5))
plt.savefig("pclass_survival.png")
result["value"] = "temp_chart.png"
            ```
            
2024-11-13 23:08:31 [INFO] Executing Step 4: CachePopulation
2024-11-13 23:08:31 [INFO] Executing Step 5: CodeCleaning
2024-11-13 23:08:31 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 23:08:31 [INFO] 
Code running:
```
result = {'type': 'plot', 'value': None}
dfs[0].groupby('pclass')['survived'].mean().unstack().plot(kind='bar', figsize=(10, 5))
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
        ```
2024-11-13 23:08:31 [INFO] Executing Step 6: CodeExecution
2024-11-13 23:08:31 [ERROR] Failed with error: Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 4455, in unstack
    return unstack(self, level, fill_value)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\reshape.py", line 483, in unstack
    raise ValueError(
ValueError: index must be a MultiIndex to unstack, <class 'pandas.core.indexes.numeric.Int64Index'> was passed

2024-11-13 23:08:31 [WARNING] Failed to execute code retrying with a correction framework [retry number: 1]
2024-11-13 23:08:31 [INFO] Executing Pipeline: ErrorCorrectionPipeline
2024-11-13 23:08:31 [INFO] Executing Step 0: ErrorPromptGeneration
2024-11-13 23:08:31 [INFO] Using prompt: <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,male,21.0,0,2,25.4667,S,Third,man,False,B,Cherbourg,no,True
0,2,female,65.0,2,1,6.95,,First,child,True,,Southampton,yes,False
0,3,female,,4,6,63.3583,C,Second,woman,True,F,,no,True
</dataframe>


The user asked the following question:
### QUERY
 generate the graph on the basis of pclass
.

You generated this python code:
result = {'type': 'plot', 'value': None}
dfs[0].groupby('pclass')['survived'].mean().unstack().plot(kind='bar', figsize=(10, 5))
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 4455, in unstack
    return unstack(self, level, fill_value)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\reshape.py", line 483, in unstack
    raise ValueError(
ValueError: index must be a MultiIndex to unstack, <class 'pandas.core.indexes.numeric.Int64Index'> was passed


Fix the python code above and return the new python code:
2024-11-13 23:08:31 [INFO] Executing Step 1: CodeGenerator
2024-11-13 23:09:25 [INFO] HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
2024-11-13 23:09:25 [INFO] Prompt used:
            <dataframe>
dfs[0]:891x15
survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
1,1,male,21.0,0,2,25.4667,S,Third,man,False,B,Cherbourg,no,True
0,2,female,65.0,2,1,6.95,,First,child,True,,Southampton,yes,False
0,3,female,,4,6,63.3583,C,Second,woman,True,F,,no,True
</dataframe>


The user asked the following question:
### QUERY
 generate the graph on the basis of pclass
.

You generated this python code:
result = {'type': 'plot', 'value': None}
dfs[0].groupby('pclass')['survived'].mean().unstack().plot(kind='bar', figsize=(10, 5))
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'

It fails with the following error:
Traceback (most recent call last):
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 2, in <module>
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\series.py", line 4455, in unstack
    return unstack(self, level, fill_value)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\prati\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\reshape\reshape.py", line 483, in unstack
    raise ValueError(
ValueError: index must be a MultiIndex to unstack, <class 'pandas.core.indexes.numeric.Int64Index'> was passed


Fix the python code above and return the new python code:
            
2024-11-13 23:09:25 [INFO] Code generated:
            ```
            import pandas as pd
import matplotlib.pyplot as plt

result = {'type': 'plot', 'value': None}
dfs[0].groupby('pclass')['survived'].mean().plot(kind='bar', figsize=(10, 5))
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
            ```
            
2024-11-13 23:09:25 [INFO] Executing Step 2: CodeCleaning
2024-11-13 23:09:25 [INFO] Saving charts to C:\Users\prati\PandasAI-with-Llama3\exports\charts\temp_chart.png
2024-11-13 23:09:25 [INFO] 
Code running:
```
result = {'type': 'plot', 'value': None}
dfs[0].groupby('pclass')['survived'].mean().plot(kind='bar', figsize=(10, 5))
plt.savefig('C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png')
result['value'] = 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'
        ```
2024-11-13 23:09:25 [INFO] Executing Step 7: ResultValidation
2024-11-13 23:09:25 [INFO] Answer: {'type': 'plot', 'value': 'C:/Users/prati/PandasAI-with-Llama3/exports/charts/temp_chart.png'}
2024-11-13 23:09:25 [INFO] Executing Step 8: ResultParsing