diff --git a/Load Data(Task 1).ipynb b/Load Data(Task 1).ipynb
new file mode 100644
index 0000000..4290ab0
--- /dev/null
+++ b/Load Data(Task 1).ipynb	
@@ -0,0 +1,287 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## DATA VISUALIZATION"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Note\n",
+    "***\n",
+    "If you are starting the notebook from this task, you can run cells from all the previous tasks in the kernel by going to the top menu and Kernel > Restart and Run All\n",
+    "***"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 1: Loading the Data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly.offline as py\n",
+    "py.init_notebook_mode(connected=True)\n",
+    "import plotly.graph_objs as go\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 2: Quick Visualizations with Custom Bar Charts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 3: Plot Life Expectancy vs GDP per Capita"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 4: Customize Interactive Bubble Charts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 5: Create Interactive Animations and Facet Plots "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 6: Represent Geographic Data as Animated Maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 7: Interactive Line Plots and Area Plots "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Load Data(Task 1).py b/Load Data(Task 1).py
new file mode 100644
index 0000000..eca4c0c
--- /dev/null
+++ b/Load Data(Task 1).py	
@@ -0,0 +1,5 @@
+import plotly.offline as py
+py.init_notebook_mode(connected=True)
+import plotly.graph_objs as go
+import pandas as pd
+import numpy as np
\ No newline at end of file
diff --git a/Quick Visualizations(Task 2).ipynb b/Quick Visualizations(Task 2).ipynb
new file mode 100644
index 0000000..daa9285
--- /dev/null
+++ b/Quick Visualizations(Task 2).ipynb	
@@ -0,0 +1,2506 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## DATA VISUALIZATION"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### NOTE\n",
+    "***\n",
+    "If you are starting the notebook from this task, you can run cells from all the previous tasks in the kernel by going to the top menu and Kernel > Restart and Run All\n",
+    "***"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 1: Loading the Data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.offline as py\n",
+    "py.init_notebook_mode(connected=True)\n",
+    "import plotly.graph_objs as go\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "linkText": "Export to plotly.com",
+        "plotlyServerURL": "https://plotly.com",
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+          "x": 4.55,
+          "xanchor": "left",
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+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
+          },
+          "showarrow": false,
+          "text": "<b>iso_alpha</b>",
+          "x": 5.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
+         },
+         {
+          "align": "left",
+          "font": {
+           "color": "#ffffff"
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+          "showarrow": false,
+          "text": "<b>iso_num</b>",
+          "x": 6.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 0,
+          "yref": "y"
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+         {
+          "align": "left",
+          "font": {
+           "color": "#000000"
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+          "showarrow": false,
+          "text": "Afghanistan",
+          "x": -0.45,
+          "xanchor": "left",
+          "xref": "x",
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+          "yref": "y"
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+         {
+          "align": "left",
+          "font": {
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+          "font": {
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+          "yref": "y"
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+          "yref": "y"
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+          "align": "left",
+          "font": {
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+          "font": {
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+          "showarrow": false,
+          "text": "AFG",
+          "x": 5.55,
+          "xanchor": "left",
+          "xref": "x",
+          "y": 2,
+          "yref": "y"
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+         {
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+          "x": 2.55,
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+          "xref": "x",
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+          "yref": "y"
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+          "x": 4.55,
+          "xanchor": "left",
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+          "font": {
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+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })\n",
+       "                };\n",
+       "                });\n",
+       "            </script>\n",
+       "        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from plotly.figure_factory import create_table\n",
+    "import plotly.express as px\n",
+    "\n",
+    "gapminder = px.data.gapminder()\n",
+    "\n",
+    "table = create_table(gapminder.head(10))\n",
+    "py.iplot(table)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "pandas.core.frame.DataFrame"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(gapminder)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 2: Quick Visualizations with Custom Bar Charts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 3: Plot Life Expectancy vs GDP per Capita"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 4: Customize Interactive Bubble Charts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 5: Create Interactive Animations and Facet Plots \n",
+    "***\n",
+    "Note: If you are starting the notebook from this task, you can run cells from all the previous tasks in the kernel by going to the top menu and Kernel > Restart and Run All\n",
+    "***"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 6: Represent Geographic Data as Animated Maps\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Task 7: Interactive Line Plots and Area Plots \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Quick Visualizations(task 2).py b/Quick Visualizations(task 2).py
new file mode 100644
index 0000000..6e93f48
--- /dev/null
+++ b/Quick Visualizations(task 2).py	
@@ -0,0 +1,22 @@
+# Task 1 : Loading Data
+
+import plotly.offline as py
+py.init_notebook_mode(connected=True)
+import plotly.graph_objs as go
+import pandas as pd
+import numpy as np
+
+'''
+The code below has some errors.
+You need to find them and correct them
+Of Course, I will help you.
+'''
+
+
+from plotly.figure_factory
+import plotly.express as px
+
+gapminder = px.data.gapminder()
+
+table = create_table(gapminder.head(10))
+py.iplot(table)
\ No newline at end of file
diff --git a/README.md b/README.md
index 67a8307..add87e4 100644
--- a/README.md
+++ b/README.md
@@ -1,49 +1,35 @@
-# learn-lang
+# Data-Visualization
 
-There are many language learning tools so why have I created another one? This question might be tormenting you but let me tell you what is the new in this tool.
+This is a simple data science project through which one can learn to create quick and easy interactive data visualizations with the help of a high level data visualization library in python : Plotly.
 
+About the Data:
+[Data Source](https://www.gapminder.org/tools/#$state$time$value=2007;;&chart-type=bubbles)
 
-### Old Conventional Process
-While learning a new language, you come across various phrases of it which you don't know the translation.
-To know its translation, you
+### Features:
+  Python, 
+  Pandas, 
+  Plotly, 
+  Putting Animation in Visualizations, 
+  Making Interactive Plots, 
+  Techniques to enhance Visualization, 
+  Represent Geopgraphic data
+  
+  
+  
+##### Tasks will be added frequently
 
-1.  select the text
-2. copy it
-3. open the browser
-4. search for google translate
-5. paste the text there,
 
-and then it is finally that you know the exact translation.
-This is a very tedious process.
 
-### New Process Using Tool
-This tool allows to cut short the boring process of 5 steps to just 1 step.
 
-1. select the text
+### In this project, you have following tasks to do:
 
-That is it.
-By just one step, you will be knowing the complete exact translation.
+#### 1: Loading the Data 
+#### 2: Plotting quick Visualizations with Custom Bar Charts
+#### 3: Plotting more data. 
+#### 4: Customize Interactive Bubble Charts
+#### 5: Create Interactive Animations and Facet Plots 
+#### 6: Represent Geographic Data as Animated Maps
+#### 7: Interactive Line Plots and Area Plots 
 
-Along with translation, you will also know proper pronunciation as this will also speak the text in the proper accent of the language.
 
-### How to make it work
-
-For the script to run successfully, certain modules are required.
-
-To download those modules, you can either simply run the f1.py file from this repository which will automatically download all the prerequisite modules,
-
-or you can download the manually by typing following commands
-
-
-`$ pip3 install googletrans`
-
-`$pip3 install google-speech`
-
-`$sudo apt-get install sox libsox-fmt-mp3`
-
-`$sudo aptitude install xclip`
-
-
-
-##### Currently this is for linux users only.
-##### For windows, I will be uploading another version soon.
+##### Some Visualizations Example From this Project have been provided above.
diff --git a/Sample Visualizations/Screenshot from 2020-05-07 20-27-51.png b/Sample Visualizations/Screenshot from 2020-05-07 20-27-51.png
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new file mode 100644
index 0000000..2556ac2
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diff --git a/Tasks/Task_1.pdf b/Tasks/Task_1.pdf
new file mode 100644
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diff --git a/Tasks/Task_2.pdf b/Tasks/Task_2.pdf
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diff --git a/Tasks/Task_3.pdf b/Tasks/Task_3.pdf
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diff --git a/f1.py b/f1.py
deleted file mode 100644
index 2b36480..0000000
--- a/f1.py
+++ /dev/null
@@ -1,13 +0,0 @@
-import subprocess
-
-#adds googletrans module
-subprocess.call('(pip3 install googletrans)', shell = True)
-
-#adds google-speech module
-subprocess.call('(pip3 install google-speech)', shell = True)
-
-#installs sox library for google-speech
-subprocess.call('(sudo apt-get install sox libsox-fmt-mp3)', shell = True)
-
-#installs xclip
-subprocess.call('(sudo aptitude install xclip)', shell = True)
diff --git a/tool.py b/tool.py
deleted file mode 100644
index d8e06f6..0000000
--- a/tool.py
+++ /dev/null
@@ -1,55 +0,0 @@
-from googletrans import Translator
-from google_speech import Speech
-import subprocess
-import time
-
-ts = Translator()
-
-LangCodes = {'afrikaans': 'af', 'albanian': 'sq', 'amharic': 'am', 'arabic': 'ar', 'armenian': 'hy', 'azerbaijani': 'az', 'basque': 'eu', 'belarusian': 'be',
- 'bengali': 'bn', 'bosnian': 'bs', 'bulgarian': 'bg', 'catalan': 'ca', 'cebuano': 'ceb', 'chichewa': 'ny', 'chinese (simplified)': 'zh-cn',
- 'chinese (traditional)': 'zh-tw', 'corsican': 'co', 'croatian': 'hr', 'czech': 'cs', 'danish': 'da', 'dutch': 'nl', 'english': 'en', 'esperanto': 'eo',
- 'estonian': 'et', 'filipino': 'tl', 'finnish': 'fi', 'french': 'fr', 'frisian': 'fy', 'galician': 'gl', 'georgian': 'ka', 'german': 'de', 'greek': 'el',
- 'gujarati': 'gu', 'haitian creole': 'ht', 'hausa': 'ha', 'hawaiian': 'haw', 'hebrew': 'iw', 'hindi': 'hi', 'hmong': 'hmn', 'hungarian': 'hu', 'icelandic': 'is',
- 'igbo': 'ig', 'indonesian': 'id', 'irish': 'ga', 'italian': 'it', 'japanese': 'ja', 'javanese': 'jw', 'kannada': 'kn', 'kazakh': 'kk', 'khmer': 'km',
- 'korean': 'ko', 'kurdish (kurmanji)': 'ku', 'kyrgyz': 'ky', 'lao': 'lo', 'latin': 'la', 'latvian': 'lv', 'lithuanian': 'lt', 'luxembourgish': 'lb',
- 'macedonian': 'mk', 'malagasy': 'mg', 'malay': 'ms', 'malayalam': 'ml', 'maltese': 'mt', 'maori': 'mi', 'marathi': 'mr', 'mongolian': 'mn',
- 'myanmar (burmese)': 'my', 'nepali': 'ne', 'norwegian': 'no', 'pashto': 'ps', 'persian': 'fa', 'polish': 'pl', 'portuguese': 'pt', 'punjabi': 'pa',
- 'romanian': 'ro', 'russian': 'ru', 'samoan': 'sm', 'scots gaelic': 'gd', 'serbian': 'sr', 'sesotho': 'st', 'shona': 'sn', 'sindhi': 'sd', 'sinhala': 'si',
- 'slovak': 'sk', 'slovenian': 'sl', 'somali': 'so', 'spanish': 'es', 'sundanese': 'su', 'swahili': 'sw', 'swedish': 'sv', 'tajik': 'tg', 'tamil': 'ta',
- 'telugu': 'te', 'thai': 'th', 'turkish': 'tr', 'ukrainian': 'uk', 'urdu': 'ur', 'uzbek': 'uz', 'vietnamese': 'vi', 'welsh': 'cy', 'xhosa': 'xh',
- 'yiddish': 'yi', 'yoruba': 'yo', 'zulu': 'zu', 'Filipino': 'fil', 'Hebrew': 'he'}
-
-
-lang = input('Enter the language you want translation into: ')
-
-try:
-	dest = LangCodes[lang]
-except:
-	dest = 'en'
-
-previnp=''
-
-while(True):	
-
-	subprocess.call('(xclip -o > test.txt)', shell=True)
-
-	f = open('test.txt','r+')
-	inp = f.read()
-
-	if inp == previnp:
-		continue
-
-	src = ts.detect(inp)
-
-	s = ts.translate(inp,dest=dest,src=src.lang)
-	print(s.text)
-	snd = Speech(s.text, 'en')
-	snd.play()
-	print()
-	previnp = inp
-	time.sleep(3)
-	f.truncate(0)
-	f.close()
-
-
-