📊 Metadata Explorer (Week 8 Python Dataframe Assignment)

This project is a Streamlit web application for exploring the CORD-19 metadata dataset. It allows users to search research papers, filter by publication year, view publication trends, explore top journals, and generate word clouds of paper titles.

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🚀 Features

• Dataset Preview: Displays a sample of the metadata for quick inspection.
• Search Tool: Enter a keyword to search through titles and abstracts.
• Year Filter: Filter publications by year and see how many papers were published.
• Publications Over Time: Line chart showing the trend of publications by year.
• Top Journals: Bar chart of the most common journals in the dataset.
• Word Cloud: Visualization of the most frequent words in paper titles.

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📂 Dataset

• metadata_sample.csv → a smaller, shareable sample (used for GitHub/Streamlit Cloud).

• metadata.csv → the full dataset (~1.5GB).

  • ⚠️ This file is very large and should not be pushed to GitHub.
  • The app will fall back to the sample file if the full dataset is unavailable.

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🛠️ Installation & Setup

1. Clone the repository

    git clone https://github.com/PreciousAnagwu/Week-8-Python-Data-Frame-Assignment.git

2. Create a virtual environment (recommended)

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

3. Install dependencies

   pip install -r requirements.txt

4. Run the Streamlit app

   streamlit run streamlit_app.py

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📦 Requirements

Main Python libraries used:

• pandas
• streamlit
• matplotlib
• seaborn
• wordcloud
• (See requirements.txt for the full list.)

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🌐 Live Deployment

You can view the live app here: 👉 Live Demo

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✨ Acknowledgements

• CORD-19 Dataset provided by Allen Institute for AI.
• Built as part of the PLP Academy Week 8 Python Assignment.