🦠 Frameworks_Assignment – CORD-19 Metadata Explorer

📌 Overview

This project provides a reproducible workflow for analyzing the CORD-19 metadata.csv file.
It includes:

• A Jupyter Notebook for interactive exploration
• A Python script for automated analysis
• A Streamlit dashboard for interactive visualization

⚠️ Note: The full CORD-19 dataset is very large. For this project, only download metadata.csv from Kaggle:
CORD-19 Research Challenge
Place it inside the data/ folder as data/metadata.csv.

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📂 Project Structure

• requirements.txt → Python dependencies
• notebooks/analysis.ipynb → Jupyter Notebook (exploration & cleaning)
• analysis.py → Script version of the analysis
• streamlit_app/app.py → Streamlit web application
• data/metadata.csv → Dataset (not included in repo, must be downloaded separately)

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🚀 Quick Start

1. Install dependencies

   pip install -r requirements.txt

2. Download the dataset

Download the dataset and place metadata.csv into the data/ folder.

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3. Run the analysis

jupyter notebook notebooks/analysis.ipynb
# or
python analysis.py

4. Launch the Streamlit app

streamlit run streamlit_app/app.py

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📝Notes

Both the notebook and script include error handling for missing files/columns.

The Streamlit app supports filtering by publication year and provides:

📈 Number of publications over time

📊 Top journals chart

📝 Word frequency insights from titles

👀 A preview of the dataset