This project focuses on analyzing the unemployment rate in India, especially during the COVID-19 lockdown period in 2020. The analysis explores regional variations, the difference between urban and rural areas, and the massive spikes caused by the pandemic.
- Name: H.M. Hiran Vimukthi Bandara
- Intern ID: CA/DF1/62821
- Domain: Data Science
- Batch: May 2026
- Language: Python
- Libraries: Pandas, NumPy, Matplotlib, Seaborn
- Tools: Jupyter Notebook / Google Colab
- Lockdown Impact: A significant spike in the unemployment rate is observed between April and June 2020.
- Regional Analysis: Different states reacted differently to the pandemic based on their industrial and agricultural dependence.
- Urban vs Rural: The data highlights how urban employment was more volatile compared to rural sectors during the lockdown.
Unemployment_Analysis.ipynb: Main Jupyter Notebook with Python code.Unemployment_Rate_upto_11_2020_2.csv: The dataset used for analysis.Project_Analysis.png: Final visualization of the unemployment trend.
- Clone the repository:
git clone [Your-Repo-Link] - Install dependencies:
pip install pandas matplotlib seaborn - Run the notebook using Jupyter or VS Code.
© 2026 H.M. Hiran Vimukthi Bandara | CodeAlpha Internship