MatPlot

COVID-19 Data Visualization with Matplotlib

A Python-based data visualization project that analyzes and visualizes global COVID-19 statistics using Matplotlib. The project processes time-series data for confirmed cases, recoveries, and deaths across 190+ countries, producing word clouds, stacked bar charts, comparative line graphs, and per-country trend analyses.

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Features

• Word Cloud -- Generates a word cloud weighted by active case counts, giving an immediate visual sense of which countries carry the largest burden.
• Stacked Bar Charts -- Displays recovery, active, and death proportions per country as percentage-based stacked bars.
• Worldwide Distribution Bars -- Shows each country's share of global recoveries, active cases, or deaths.
• Multi-Country Comparison Graphs -- Plots time-series curves for selected countries on the same axes, with configurable case thresholds.
• Single-Country Trend Lines -- Charts confirmed, recovered, and death curves over time for any individual country.

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Sample Visualizations

Active Cases Word Cloud

Country-Wise Case Breakdown (Stacked Bar)

Multi-Country Death Case Comparison

US COVID-19 Trend Graph

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Tech Stack

Library	Purpose
Python 3	Core language
Pandas	Data loading, cleaning, and aggregation
Matplotlib	All charts and plots
WordCloud	Word cloud generation

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Data Sources

Time-series CSV data sourced from the Johns Hopkins CSSE COVID-19 Dataset, accessed through the Humanitarian Data Exchange (HDX).

The dataset includes daily cumulative counts of confirmed cases, recoveries, and deaths by country from January 2020 onward. Local CSV snapshots are stored in the data/ directory for offline use.

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How to Run

1. Install dependencies

   pip install pandas matplotlib wordcloud

2. Launch Jupyter

   cd CoronaAffectedCountry/MatPlot
   jupyter notebook

3. Run the notebooks

   • Open Bar.ipynb for word clouds and bar chart visualizations.
   • Open Graph.ipynb for time-series line graphs and country comparisons.

4. Refresh data from the live source (optional)

   Pass online=True when instantiating the classes to download the latest CSV data:

   bar = CovidBar(online=True)
   graph = CovidGraph(online=True)

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Project Structure

MatPlot/
├── Bar.ipynb                  # Word clouds, stacked bars, worldwide distribution charts
├── Graph.ipynb                # Time-series line graphs and multi-country comparisons
├── README.md
├── data/
│   ├── Confirmed.csv          # Daily confirmed cases by country
│   ├── Recovered.csv          # Daily recovered cases by country
│   ├── Death.csv              # Daily death cases by country
│   └── Stat_updated.csv       # Computed aggregate statistics
├── images/                    # Saved chart outputs (PNG)
└── utils/
    ├── graph_data_extract.py  # Loads and groups time-series CSVs for line graphs
    └── stat_data_extract.py   # Computes per-country and worldwide percentages for bar charts