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Exploratory-data-analysis

Exploratory-data-analysis

The dataset was released by Aspiring Minds from the Aspiring Mind Employment Outcome 2015 (AMEO). The study is primarily limited only to students with engineering disciplines. The dataset contains the employment outcomes of engineering graduates as dependent variables (Salary, Job Titles, and Job Locations) along with the standardized scores from three different areas – cognitive skills, technical skills and personality skills. The dataset also contains demographic features. The independent variables are both continuous and categorical in nature. The dataset contains a unique identifier for each candidate.

Database Description:

Number of Independent variables : 40 Number of Data Points: 4000

Libraries Involved:

  1. pandas
  2. Numpy
  3. Seaborn
  4. Matplotlib
  5. Sklearn
  6. scikit-plot
  7. pingouin

Steps Involved:

  1. Importing the libraries
  2. Loading the dataset
  3. Data Preprocessing
  4. train and test data split
  5. Building the model
  6. Compare model performance
  7. selection model based on performance
  8. Evaluation
  9. Plot ROC and AUC curve

#Conclusion:- From the EDA we observe that , the specialization is dependent on the gender.

The fresher who has done CSE and have got into analyst,engineer etc position have an maximum salary of 5.6lakh and minimum of 50k.

With experience the there is a hike in the salary