HR Employee Attrition Analysis

Project Overview

This project studies why employees leave a company.
The goal is to understand employee attrition and find patterns in the data.

Objective

• Understand why employees leave the company
• Identify groups of employees with high attrition
• Analyze the impact of salary, department, overtime, and job satisfaction

Tools Used

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook
• Excel

Dataset

IBM HR Analytics Employee Attrition Dataset

The dataset includes information about employees such as:

• Age
• Department
• Job Role
• Salary
• Job Satisfaction
• Overtime
• Attrition (Yes or No)

What I Did

• Cleaned and prepared the dataset using Python and Pandas
• Explored the data to find patterns related to employee attrition
• Created charts to visualize important trends
• Built an Excel dashboard to show key insights

Key Insights

• Employees who work overtime leave the company more often
• Employees with low job satisfaction have higher attrition
• Employees with lower monthly income are more likely to leave

Visualizations

https://public.tableau.com/app/profile/praneel.reddy.kanduri/viz/HR_Employee_Attrition_twbx/HREmployeeAttritionAnalysisDashboard The project includes charts such as:

• Attrition Distribution
• Attrition by Department
• Income vs Attrition
• Job Satisfaction vs Attrition

Project Files

• HR_Employee_Attrition_Analysis.ipynb – Python analysis
• HR_Attrition_Cleaned.csv – Cleaned dataset
• HR_Employee_Attrition_Dashboard.xlsx – Excel dashboard with charts and KPIs

Data Analytics Portfolio

This project is part of my Data Analytics portfolio.

View my GitHub: https://github.com/Praneel22

Other Project

Retail Sales Data Analysis
https://github.com/Praneel22/Superstore-Sales-Data-Analysis

Author

Praneel Reddy