This repository contains the code and analysis for exploring the Employee Attrition dataset. The dataset provides insights into employee attrition rates within a company, along with various factors that might influence attrition.
The dataset used for this analysis is named HR-Employee-Attrition.csv. It includes information about employees such as age, job role, department, satisfaction level, etc. Additionally, it contains a binary column indicating whether an employee has left the company (1) or is still employed (0). Source: https://www.kaggle.com/datasets/patelprashant/employee-attrition?select=WA_Fn-UseC_-HR-Employee-Attrition.csv
The analysis is conducted using Python programming language and popular data science libraries such as Pandas, NumPy, and Matplotlib. The main objectives of the analysis include:
- Exploratory Data Analysis (EDA) to understand the distribution of various features.
- Identification of factors that may contribute to employee attrition.
- Building predictive models to forecast employee attrition.
The analysis provides valuable insights into employee attrition within the company, highlighting key factors that contribute to attrition rates. Visualizations and statistical summaries aid in understanding the trends and patterns observed in the data.
Future work could involve:
- Fine-tuning predictive models to improve accuracy.
- Conducting more in-depth analysis on specific departments or job roles.
- Exploring external factors that may influence employee attrition.