IBM HR Analytics Employee Attrition & Performance
Predict attrition of your valuable employees
@kaggle.pavansubhasht_ibm_hr_analytics_attrition_dataset
Predict attrition of your valuable employees
@kaggle.pavansubhasht_ibm_hr_analytics_attrition_dataset
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'
CREATE TABLE wa_fn_usec_hr_employee_attrition (
"age" BIGINT,
"attrition" VARCHAR,
"businesstravel" VARCHAR,
"dailyrate" BIGINT,
"department" VARCHAR,
"distancefromhome" BIGINT,
"education" BIGINT,
"educationfield" VARCHAR,
"employeecount" BIGINT,
"employeenumber" BIGINT,
"environmentsatisfaction" BIGINT,
"gender" VARCHAR,
"hourlyrate" BIGINT,
"jobinvolvement" BIGINT,
"joblevel" BIGINT,
"jobrole" VARCHAR,
"jobsatisfaction" BIGINT,
"maritalstatus" VARCHAR,
"monthlyincome" BIGINT,
"monthlyrate" BIGINT,
"numcompaniesworked" BIGINT,
"over18" VARCHAR,
"overtime" VARCHAR,
"percentsalaryhike" BIGINT,
"performancerating" BIGINT,
"relationshipsatisfaction" BIGINT,
"standardhours" BIGINT,
"stockoptionlevel" BIGINT,
"totalworkingyears" BIGINT,
"trainingtimeslastyear" BIGINT,
"worklifebalance" BIGINT,
"yearsatcompany" BIGINT,
"yearsincurrentrole" BIGINT,
"yearssincelastpromotion" BIGINT,
"yearswithcurrmanager" BIGINT
);Anyone who has the link will be able to view this.