CORD-19 Data Explorer

Beginner-friendly project for exploring the CORD-19 metadata.csv dataset and creating an interactive Streamlit app.

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📂 Project Structure

Framework_Assignment/
├─ metadata.csv           # dataset (downloaded separately)
├─ notebook.ipynb         # Jupyter notebook with step-by-step analysis
├─ app.py                 # Streamlit app
├─ requirements.txt       # dependencies
└─ README.md              # this file

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⚙️ Installation

1. Clone the repository or download it.

git clone <your-repo-url>
cd Framework_Assignment

2. (Optional) Create a virtual environment:

python -m venv venv
source venv/bin/activate   # macOS/Linux
venv\Scripts\activate      # Windows

3. Install required packages:

pip install -r requirements.txt

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📊 Jupyter Notebook

1. Open Jupyter Notebook:

jupyter notebook

2. Run through notebook.ipynb step by step to:
   • Load and clean the metadata
   • Explore basic statistics
   • Create visualizations

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🌐 Streamlit App

1. Make sure you have metadata.csv in the same folder as app.py.

2. Run the app:

streamlit run app.py

3. The app will open in your browser. Use the sidebar to filter year range and number of rows loaded.

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✅ Expected Outcomes

• A Jupyter Notebook showing:
  • Basic exploration of the dataset
  • Data cleaning steps
  • Visualizations (publications by year, top journals, word frequencies)
• A working Streamlit app to interactively explore results

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📝 Notes

• If the dataset is too large, load a sample with nrows=10000.
• Word cloud is optional and requires the wordcloud package.
• Push this repo to GitHub as Framework_Assignment and submit the repo URL for your assignment.