HR Analytics Dataset

Unlocking HR Insights: Data-driven Decisions

@kaggle.saadharoon27_hr_analytics_dataset

Table List

1 table(80.57 KB)

Hr Analytics

@kaggle.saadharoon27_hr_analytics_dataset.hr_analytics

80.57 KB
1480 rows
38 columns

empid EmpID	age Age	agegroup AgeGroup	attrition Attrition	businesstravel BusinessTravel	dailyrate DailyRate	department Department	distancefromhome DistanceFromHome	education Education	educationfield EducationField	employeecount EmployeeCount	employeenumber EmployeeNumber	environmentsatisfaction EnvironmentSatisfaction	gender Gender	hourlyrate HourlyRate	jobinvolvement JobInvolvement	joblevel JobLevel	jobrole JobRole	jobsatisfaction JobSatisfaction	maritalstatus MaritalStatus	monthlyincome MonthlyIncome	salaryslab SalarySlab	monthlyrate MonthlyRate	numcompaniesworked NumCompaniesWorked	over18 Over18	overtime OverTime	percentsalaryhike PercentSalaryHike	performancerating PerformanceRating	relationshipsatisfaction RelationshipSatisfaction	standardhours StandardHours	totalworkingyears TotalWorkingYears	trainingtimeslastyear TrainingTimesLastYear	worklifebalance WorkLifeBalance	yearsatcompany YearsAtCompany
RM297	18	18-25	Yes	Travel_Rarely	230	Research & Development	3	3	Life Sciences	1	405	3	Male	54	3	1	Laboratory Technician	3	Single	1420	Upto 5k	25233	1	Y	No	13	3	3	80		2	3
RM302	18	18-25	No	Travel_Rarely	812	Sales	10	3	Medical	1	411	4	Female	69	2	1	Sales Representative	3	Single	1200	Upto 5k	9724	1	Y	No	12	3	1	80		2	3
RM458	18	18-25	Yes	Travel_Frequently	1306	Sales	5	3	Marketing	1	614	2	Male	69	3	1	Sales Representative	2	Single	1878	Upto 5k	8059	1	Y	Yes	14	3	4	80		3	3
RM728	18	18-25	No	Non-Travel	287	Research & Development	5	2	Life Sciences	1	1012	2	Male	73	3	1	Research Scientist	4	Single	1051	Upto 5k	13493	1	Y	No	15	3	4	80		2	3
RM829	18	18-25	Yes	Non-Travel	247	Research & Development	8	1	Medical	1	1156	3	Male	80	3	1	Laboratory Technician	3	Single	1904	Upto 5k	13556	1	Y	No	12	3	4	80			3
RM973	18	18-25	No	Non-Travel	1124	Research & Development	1	3	Life Sciences	1	1368	4	Female	97	3	1	Laboratory Technician	4	Single	1611	Upto 5k	19305	1	Y	No	15	3	3	80		5	4
RM1154	18	18-25	Yes	Travel_Frequently	544	Sales	3	2	Medical	1	1624	2	Female	70	3	1	Sales Representative	4	Single	1569	Upto 5k	18420	1	Y	Yes	12	3	3	80		2	4
RM1312	18	18-25	No	Non-Travel	1431	Research & Development	14	3	Medical	1	1839	2	Female	33	3	1	Research Scientist	3	Single	1514	Upto 5k	8018	1	Y	No	16	3	3	80		4	1
RM128	19	18-25	Yes	Travel_Rarely	528	Sales	22	1	Marketing	1	167	4	Male	50	3	1	Sales Representative	3	Single	1675	Upto 5k	26820	1	Y	Yes	19	3	4	80		2	2
RM150	19	18-25	No	Travel_Rarely	1181	Research & Development	3	1	Medical	1	201	2	Female	79	3	1	Laboratory Technician	2	Single	1483	Upto 5k	16102	1	Y	No	14	3	4	80	1	3	3	1


CREATE TABLE hr_analytics (
  "empid" VARCHAR,
  "age" BIGINT,
  "agegroup" VARCHAR,
  "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,
  "salaryslab" VARCHAR,
  "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" DOUBLE
);