📌 Project Overview This project analyzes unemployment data in India using Python to understand unemployment trends, regional differences, rural vs urban patterns, and the impact of COVID-19.

🎯 Objectives Analyze unemployment rate trends over time Compare unemployment between Rural and Urban areas Identify regions with high and low unemployment Investigate the impact of COVID-19 on unemployment Identify monthly patterns Generate useful insights from the data 🛠️ Tools & Technologies Python Pandas NumPy Matplotlib Google Colab 📊 Key Findings Average unemployment rate: 11.79% Rural and Urban unemployment rates were compared Tripura had the highest average unemployment rate at 28.35% Meghalaya had the lowest average unemployment rate at 4.80% Pre-COVID average unemployment: 9.51% COVID-period average unemployment: 17.77% Unemployment increased by 8.26 percentage points during the COVID period May 2020 recorded the highest monthly average unemployment rate: 24.88% 📈 Analysis Performed Data cleaning Exploratory Data Analysis (EDA) Rural vs Urban comparison Regional analysis Time-series trend analysis COVID-19 impact analysis Monthly pattern analysis Correlation analysis 📁 Files unemployment_analysis.ipynb - Complete analysis notebook Unemployment in India.csv - Original dataset cleaned_unemployment_data.csv - Cleaned dataset 🎓 Internship This project was completed as part of the Data Science Internship.