Frameworks_Assignment

Overview

This project analyzes the CORD-19 COVID-19 research metadata dataset and presents insights through a Streamlit web application.
It demonstrates the use of Python frameworks for:

• Data loading and cleaning
• Exploratory data analysis (EDA)
• Visualization of research trends
• Building an interactive web app

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Objectives

• Practice loading and exploring a real-world dataset
• Apply data cleaning techniques with Pandas
• Create visualizations with Matplotlib & Seaborn
• Build an interactive app using Streamlit
• Present data insights in an accessible way

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Repository Structure

Frameworks_Assignment/ │── app.py # Streamlit web app │── analysis.py # Data loading, cleaning, and visualization logic │── requirements.txt # Python dependencies │── metadata.csv # Dataset (sampled from CORD-19 metadata) │── README.md # Project documentation

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Installation

Clone this repository:

git clone https://github.com/Ikamunya-web/Frameworks_Assignment.git cd Frameworks_Assignment

Install dependencies:

pip install -r requirements.txt

Running the Project

Run the Streamlit app: streamlit run app.py

Features

Load and clean CORD-19 metadata dataset Analyze publications by year, journal, and keywords Visualize trends with bar charts, histograms, and word clouds Interactive filters in the Streamlit app

Tools & Libraries

Pandas → Data manipulation & cleaning

Matplotlib → Plotting

Seaborn → Prettier statistical plots

Streamlit → Web app framework

WordCloud → Generating word cloud of paper titles

Example Visualizations

Number of publications per year

Top publishing journals

Word cloud of paper titles

Distribution of papers by source

Dataset

Source: CORD-19 Research Challenge (Kaggle)

File used: metadata.csv (subset for assignment)

Reflection

This project shows how Python frameworks simplify the data science workflow:

Pandas → Clean & explore data

Matplotlib/Seaborn → Visualize insights

Streamlit → Share findings interactively