COVID-19 Global Data Tracker

Overview

The COVID-19 Global Data Tracker is a Python-based project that visualizes and analyzes global COVID-19 data. It uses the Our World in Data (OWID) dataset to provide insights into cases, deaths, vaccinations, and other key metrics.

Features

• Data Collection: Automatically loads the OWID dataset (owid-covid-data.csv).
• Data Visualization:
  • Total cases, deaths, and vaccinations over time.
  • Daily new cases and death rates for selected countries.
  • Choropleth maps for global COVID-19 metrics.
• Analysis:
  • Death rate trends.
  • Vaccination progress across countries.

Project Structure

• COVID19_Global_Data_Tracker.ipynb: Jupyter Notebook containing the code for data loading, analysis, and visualization.
• owid-covid-data.csv: Dataset file containing global COVID-19 data.
• README.md: Documentation for the project.

Data Source

The project uses the Our World in Data (OWID) dataset. You can download the dataset from: https://covid.ourworldindata.org/data/owid-covid-data.csv

How to Run

1. Clone the repository and navigate to the project directory.
2. Ensure you have Python installed along with the required libraries:

   pip install pandas matplotlib seaborn plotly

3. Open the COVID19_Global_Data_Tracker.ipynb file in Jupyter Notebook or any compatible IDE.
4. Run the cells sequentially to load the data, analyze it, and generate visualizations.

Visualizations

The project generates the following visualizations:

1. Total Cases Over Time: Line plot showing cumulative cases for selected countries.

2. Daily New Cases: Line plot showing daily new cases for selected countries.

3. Death Rate Over Time: Line plot showing the death rate for selected countries.

4. Total Vaccinations Over Time: Line plot showing cumulative vaccinations for selected countries.

5. Choropleth Map: Interactive map visualizing global COVID-19 metrics.

Requirements

• Python 3.x
• Libraries: pandas, matplotlib, seaborn, plotly

Example Code

Loading the Dataset

import pandas as pd

df = pd.read_csv('owid-covid-data.csv')

print(df.head())

Visualizing Total Cases Over Time

Total cases over time

import matplotlib.pyplot as plt
plt.figure(figsize=(12, 6))
for country in countries:
    data = df_filtered[df_filtered['location'] == country]
    plt.plot(data['date'], data['total_cases'], label=country)
plt.title('Total COVID-19 Cases Over Time')
plt.xlabel('Date')
plt.ylabel('Total Cases')
plt.legend()
plt.grid()
plt.show()

Acknowledgments

• Our World in Data for providing the dataset.
• Libraries used: pandas, matplotlib, seaborn, plotly.