This data set is well-known in the People Analytics world. When IBM creates a data set that enables you to practice attrition modeling, you pay attention. The data set has 1470 rows and 35 columns.

The data set contains data like age, gender, job satisfaction, environment satisfaction, education field, job role, income, overtime, percentage salary hike, tenure, training time, years in current role, relationship status, and more.

With these variables, IBM has created a fairly complete overview that contains the data of the average HRIS combined with a full engagement survey. The data set is therefore great to predict turnover, or to simply find differences between the group that stayed or that left.





Uncover the factors that lead to employee attrition and explore important questions such as ‘show me a breakdown of distance from home by job role and attrition’ or ‘compare average monthly income by education and attrition’. This is a fictional data set created by IBM data scientists.

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'

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

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