This project provides an in-depth analysis of COVID-19 data, leveraging Python's data science libraries to visualize trends and patterns in the pandemic's spread. The analysis includes:
- Data preprocessing and cleaning using Pandas
- Interactive visualizations with Plotly
- Time series analysis of case numbers and growth rates
- Comparative analysis across different countries and regions
Key features:
- Jupyter notebooks for easy reproduction and modification of the analysis
- Custom functions for data manipulation and visualization
- Up-to-date data sourced from reliable public health repositories
This project showcases the power of data analysis in understanding and tracking the progression of a global pandemic, providing valuable insights for researchers, policymakers, and the general public.