A beginner-friendly project analyzing the CORD-19 dataset.
This project explores COVID-19 research publications metadata and provides an interactive Streamlit web app for visualization.
- Load and clean real-world datasets.
- Explore publication patterns (by year, journal, source).
- Create meaningful visualizations with matplotlib/seaborn.
- Build an interactive web application with Streamlit.
- Python 3.7+
- pandas (data cleaning & manipulation)
- matplotlib & seaborn (visualizations)
- streamlit (web app)
Install everything with:
pip install -r requirements.txt
📂 Project Structure
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Frameworks_Assignment/
│
├── app.py # Streamlit application
├── metadata.csv # CORD-19 metadata (or sample file)
├── notebooks/ # Jupyter notebooks (exploration)
└── README.md # Project documentation
📈 Data Insights
1. Publications by Year
Shows how research output grew over time.
2. Top Journals
Top 10 journals publishing COVID-19 research.
3. Word Cloud of Titles
Most frequent words appearing in paper titles.
4. Distribution by Source
Counts of papers by repository/source.
🚀 Running the App Locally
Clone this repository:
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git clone https://github.com/ShiksAnn/PythonFrameworks.git
cd Frameworks_Assignment
Install dependencies:
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Run the app:
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streamlit run app.py
Then open http://localhost:8501 in your browser.
🌍 Optional: Deploy Online
You can deploy for free using Streamlit Cloud:
Push your repo to GitHub.
Log in to Streamlit Cloud → New app → select your repo.
Choose app.py as the main file.
Done ✅ — you’ll get a public link to share your app.
🤔 Reflection
Challenges: Handling missing data (many rows lacked publication dates/journals), reducing dataset size for testing.
Learnings: Improved skills in pandas cleaning, plotting, and basic Streamlit development.
Next steps: Add NLP analysis of abstracts, author collaboration networks, and deploy app online for public access.
✅ Deliverables:
Jupyter notebook / Python scripts for analysis
Visualizations (charts, word cloud, trends)
Interactive Streamlit application
links
Local URL: http://localhost:8501
Network URL: http://192.168.8.79:8501