Unemployment Data Analysis using Python

This repository provides a comprehensive analysis of unemployment trends in India using Python. It uses a real-world dataset containing details such as region, unemployment rate, date, and labor participation rate. The goal of this project is to uncover insights about regional unemployment patterns, time-based fluctuations, and their relation to economic factors.

Project Structure

• unemployment.csv – Dataset used for analysis
• unemployment_analysis.ipynb – Jupyter Notebook containing data preprocessing, EDA, and visualizations
• README.md – Project overview and documentation

Tools & Libraries Used

• Python
• Pandas – Data manipulation
• Matplotlib & Seaborn – Data visualization
• Plotly – Interactive charts
• Jupyter Notebook

Key Insights

• Analysis of unemployment rates by state and over time
• Heatmaps and bar plots to show regional unemployment disparities
• Line graphs for temporal trend analysis
• Correlation between labor participation and unemployment

Visualizations

The notebook includes multiple graphs like:

• Unemployment rate over months
• Region-wise comparisons
• Choropleth map of unemployment (if applicable)