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HR Employee Attrition Prediction Data
NLP / Natural Language Processing
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About
This dataset focuses on HR Analytics, specifically designed for employee attrition prediction. It aids in interpreting organisational data by identifying people-related trends, enabling HR Departments to take proactive steps to maintain a smooth and profitable organisation. Addressing the intricate challenge of attrition in a corporate setting, this dataset supports the deployment of machine learning models to forecast potential attrition cases, thereby assisting HR personnel in implementing necessary employee retention strategies.
Columns
- Age: Age of the employee.
- Attrition: Indicates employee attrition (true/false).
- BusinessTravel: How frequently an employee travels for business purposes.
- DailyRate: Daily wage of an employee.
- Department: Employee department.
- DistanceFromHome: Distance from home to office in kilometres.
- Education: Qualification of employee (masked).
- EducationField: Stream of education.
- EmployeeCount: Employee count (constant value of 1).
- EmployeeNumber: Unique employee number.
- EnvironmentSatisfaction: Level of environment satisfaction.
- Gender: Gender of employee (Male/Female).
- HourlyRate: Employee hourly rate.
- JobInvolvement: Level of job involvement.
- JobLevel: Level of job.
- JobRole: Job role of an employee.
- JobSatisfaction: Indicates if the employee is satisfied.
- MaritalStatus: Employee's marital status.
- MonthlyIncome: Income of an employee per month.
- MonthlyRate: Monthly rate of an employee.
- NumCompaniesWorked: Number of companies worked for.
- Over18: Indicates if the employee is over 18 years old (constant true).
- OverTime: Indicates if the employee works overtime.
- PercentSalaryHike: Percentage of salary hike.
- PerformanceRating: Employee performance rate.
- RelationshipSatisfaction: Level of relationship satisfaction.
- StandardHours: Standard work hours per week (constant value of 80).
- StockOptionLevel: Company stock option level.
- TotalWorkingYears: Total working years.
- TrainingTimesLastYear: Number of training times in the last year.
- WorkLifeBalance: Level of work-life balance.
- YearsAtCompany: Total years at the current company.
- YearsInCurrentRole: Years in the current role.
- YearsSinceLastPromotion: Years since the last promotion.
- YearsWithCurrManager: Years with the current manager.
Distribution
The dataset is typically provided as a CSV file (HR-Employee-Attrition.csv), with a size of approximately 227.98 kB. It contains 35 columns and consists of 1,470 records or rows, with no missing values identified across its primary fields.
Usage
This dataset is ideal for:
- Predicting employee attrition using machine learning models.
- Identifying key factors influencing employee turnover.
- Data cleaning exercises, including deleting redundant columns, renaming columns, dropping duplicates, and handling NaN values.
- Data visualisation tasks, such as plotting correlation maps for numeric variables and exploring relationships between various HR metrics (e.g., Overtime and Age, Total Working Years, Education Level).
- Exploratory data analysis to uncover trends and insights in HR data.
Coverage
The dataset's scope is primarily focused on employee-specific attributes related to work, demographics, and satisfaction. While specific geographic and time ranges are not detailed in the available information, the data covers various aspects of an individual's employment and personal context within a corporate setup, including age ranges from 18 to 60, different departments (e.g., Research & Development, Sales), and diverse job roles.
License
CC0: Public Domain
Who Can Use It
- HR Professionals: To understand and address attrition challenges and develop retention strategies.
- People Managers: To proactively identify employees at risk of leaving and intervene effectively.
- Data Analysts and Scientists: For building predictive models, conducting statistical analysis, and generating insightful reports on workforce dynamics.
- Researchers: For academic studies on organisational behaviour, employee satisfaction, and human resource management.
- Business Intelligence Specialists: To create dashboards and visualise trends related to employee retention.
Dataset Name Suggestions
- HR Employee Attrition Prediction Data
- Workforce Attrition Analytics Dataset
- Employee Retention Prediction Model Data
- HR Organisational Data Insights
- Corporate Attrition Factors Dataset
Attributes
Original Data Source: HR Employee Attrition Prediction Data
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