We will start by importing our data using the famous pandas library. This is an overview of the features in our dataset:

• enrollee_id: Unique ID for the candidate;

• city: City code;

• city_development _index: Development index of the city (scaled);

• gender: Gender of the candidate;

• relevent_experience: Relevant experience of candidate;

• enrolled_university: Type of University course enrolled, if any;

• education_level: Education level of the candidate;

• major_discipline: Education major discipline of the candidate;

• experience: Candidate's total experience in years;

• company_size: No of employees in current employer's company;

• company_type: Type of current employer;

• lastnewjob: Difference in years between previous job and current job;

• training_hours: training hours completed;

• target: 0 – Not looking for a job change, 1 – Looking for a job change.

Methods description

Modules and Methods Used

• pandas: Module for data manipulation and analysis;
  • `.read_csv()**: Function to read a CSV file into a DataFrame;
  • .head(): Method to display the first n rows of a DataFrame.