This project is a Python-based application for analyzing and visualizing COVID-19 data using data science and interactive GUIs.
It includes:
- A Tkinter-based desktop interface
- A Streamlit-based web application
You can download the COVID-19 dataset used in this project from the following link:
- Load and clean COVID-19 datasets
- Visualize confirmed cases, deaths, and recoveries
- Interactive desktop app using Tkinter
- Web-based interactive dashboard using Streamlit
- Filter data by country and time
- Imported and cleaned COVID-19 datasets using
pandas - Performed statistical analysis on global COVID-19 trends
- Visualized the data using
matplotlibandseaborn - Built a GUI using Tkinter to allow users to explore data and view charts
- Developed a Streamlit web dashboard for interactive data viewing
- Implemented filtering features by country and date range
pip install pandas matplotlib seaborn streamlit# Run the Tkinter app
python tk_app.py
# Run the Streamlit app
streamlit run streamlit_app.pyhttp://localhost:8501covid19-code.ipynb– Main Jupyter notebook for data analysis and UI logictk_app.py– Python file for the Tkinter interfaceapp.py– Python file for the Streamlit dashboardscreenshots/– Folder containing UI imagesREADME.md– Project documentation
- Python 3.7 or higher
pandasmatplotlibseabornstreamlittkinter(usually included with Python)
Developed by Mohamed Younis