As the COVID-19 keeps unleashing its havoc, the world continues to get pushed into the crisis of the great economic recession, more and more companies start to cut down their underperforming employees. Companies firing hundreds and thousands of Employees is a typical headline today. Cutting down employees or reducing an employee salary is a tough decision to take.
To predict Employee Attrition by the given data about his/her past history.
Numpy, Pandas, IPython, Scikit-Learn, Matplotlib, Seaborn.
I am using the data provided by IBM. This notebook belongs to a Kaggle competition https://www.kaggle.com/c/summeranalytics2020 organized by Consultacy and Analytics club of IIT, Guwahati.
The various columns are : d - an anonymous id given to an Employee
Age - Age of an Employee
Attrition - Did the Employee leave the company, 0-No, 1-Yes
BusinessTravel - Travlling frequency of an Employee
Department - Work Department
DistanceFromHome - Distance of office from home
EducationField - Field of Education
EmployeeNumber - Number of Employees in the division of a given Employee
EnvironmentSatisfaction - Work Environment Satisfaction
Gender - Gender of Employee
MartialStatus - Martial Status of an employee
MonthlyIncome - Monthly Income of Employee in USD
NumCompaniesWorked - Number of Companies in which Employee has worked before joining this Company
OverTime - Does The person work overtime
PercentSalaryHike - Average annual salary hike in percentages
StockOptionLevel - Company stocks given to an Employee
TotalWorkingYears - Total working experience of an employee
TrainingTimesLastYear - No. of trainings an employee went through last year
YearsAtCompany - Number of years worked at this company
YearsInCurrentRole - Number of years in current role
YearsSinceLastPromotion - Number of years since last promotion
YearsWithCurrManager - Number of years with the current manager
Education
1 'Below College' 2 'College' 3 'Bachelor' 4 'Master' 5 'Doctor'
EnvironmentSatisfaction
1 'Low' 2 'Medium' 3 'High' 4 'Very High'
JobInvolvement
1 'Low' 2 'Medium' 3 'High' 4 'Very High'
JobSatisfaction
1 'Low' 2 'Medium' 3 'High' 4 'Very High'
PerformanceRating
1 'Low' 2 'Good' 3 'Excellent' 4 'Outstanding'
Behaviour
1 'Good' 2 'Bad' 3 'Not Rated'
CommunicationSkill
1 'Bad' 2 'Average' 3 'Good' 4 'Better' 5 'Best'
StockOptionLevel
0 'No stocks' 1 'Less Stocks' 2 'Moderate Stocks' 3 'A lot of Stocks'