The purpose of this project is to explore what variables are good predictors for attrition rates in Fortune 1000 companies and also we will create a model that will predict if an employee will leave their company voluntarily or not. Finally, we will look at other trends associated with specific jobs and attrition rates.

Problem Statement

I am assigned to conduct exploratory data analysis (EDA) to determine factors that lead to attrition.

1. Identify any job role specific trends that may exist in the data set (e.g., “Data Scientists have the highest job satisfaction”).
2. Identify at least the top three factors that contribute to turnover.
3. Ceate derived attributes/variables.
4. Identify any other interesting trends and observations from the analysis.

Each of the analysis should be backed up by robust experimentation and where applicable, the appropriate visualization.

Datasets

CaseStudy2-data.csv: Complete Employee data set with employee attrition CaseStudy2CompSet No Salary.csv: A 300 oberserved data set without the Monthly Incomes. CaseStudy2CompSet No Attrition.csv: A 300 oberserved data set without the Attrition field

Data Definitions:

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'

RelationshipSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'

WorkLifeBalance 1 'Bad' 2 'Good' 3 'Better' 4 'Best'