🌍 COVID-19 Data Visualization & Comparison Tool

📊 Analyze and Compare COVID-19 Trends Across Countries

Project Overview

This project provides an interactive and customizable platform for visualizing and comparing various COVID-19 metrics, such as cases, deaths, recoveries, and more, between any two countries. It leverages powerful data manipulation and visualization tools to give insights into the impact of the pandemic across different regions and over time.

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Key Features

• Flexible Country Comparison:

  • Users can select any two countries to compare COVID-19 data, such as cases, deaths, or recoveries.

• Customizable Metrics:

  • The tool allows users to choose which metric they want to visualize (e.g., daily cases, monthly deaths, recoveries).

• Data Aggregation by Time Period:

  • Aggregates daily data into monthly totals, offering a clearer long-term trend view.

• Dynamic Visualizations:

  • Interactive line graphs to display trends over time, easily comparing selected countries.
  • Custom color-coded plots for each country, making it easy to differentiate between them.

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Technologies Used

• Python

  • Efficient scripting and data analysis.

• Pandas

  • Data manipulation: filtering, grouping, and aggregating.
  • Time-based operations for converting daily data to monthly or weekly summaries.

• Matplotlib

  • To generate high-quality visualizations comparing countries and COVID-19 metrics.

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Visualizations

This project generates line graphs to compare COVID-19 trends over time, such as confirmed cases, deaths, or recoveries between two selected countries. The user can select which metric to visualize and which countries to compare.

Example Output:

• Orange Line: Selected metric for Country A.
• Blue Line: Selected metric for Country B.

Graph comparing COVID-19 metrics (e.g., cases, deaths, recoveries) between two countries.

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How to Run the Project

1. Clone the repository.
2. Install the necessary libraries:

   pip install pandas matplotlib

3. Run the script and select the desired countries and COVID-19 metric (e.g., cases, deaths, recoveries) to visualize the comparison.
4. View the generated plots in your preferred environment.

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Future Improvements

• Expand the tool to allow comparisons across more than two countries.
• Implement an interactive UI with dropdowns for country and metric selection.
• Add support for more COVID-19 metrics, such as vaccination rates and hospitalizations.
• Integrate with live COVID-19 data APIs for real-time analysis.