COVID-19 Data Analysis Project

Overview

This repository contains Python scripts and Jupyter Notebooks for analyzing COVID-19 data using various data science and visualization techniques.

Project Structure

• data_analysis.ipynb: Jupyter Notebook containing the main data analysis script.
• requirements.txt: List of Python packages required to run the scripts.
• README.md: This file, providing an overview of the project.

Features

• Data Loading: Utilizes live data from GitHub repositories provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE).
• Data Processing: Processes global COVID-19 data to calculate statistics such as total cases, deaths, recoveries, mortality rate, and recovery rate.
• Visualization: Generates interactive plots and graphs using matplotlib and pandas to visualize trends in COVID-19 cases globally and by country.
• Machine Learning: Includes time series forecasting using Linear Regression to predict future trends in COVID-19 cases.

Installation

1. Clone the repository:

   git clone https://github.com/your_username/covid19-data-analysis.git
   cd covid19-data-analysis

2. Install dependencies:

   pip install -r requirements.txt

Usage

• Open and run the data_analysis.ipynb Jupyter Notebook to execute the data analysis and visualization scripts.
• Modify parameters or add new analyses as needed for specific research questions.

Contributing

Contributions are welcome! If you want to contribute to this project, follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/new-analysis).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new analysis').
5. Push to the branch (git push origin feature/new-analysis).
6. Create a new Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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