🌍 COVID-19 Global Data Tracker

This project is a comprehensive COVID-19 Global Data Tracker that analyzes and visualizes key pandemic trends using data from Our World in Data. It highlights total cases, deaths, and vaccination progress across selected countries, helping to understand the

global and regional impact of the virus.

📁 Dataset

Source: Our World in Data - COVID-19 Dataset

Data File Used: owid-covid-data.csv

🎯 Objectives

Clean and process global COVID-19 data.

Track and visualize pandemic trends over time.

Compare metrics such as infections, deaths, and vaccinations among countries.

Compute and analyze death rates and vaccine coverage.

🌐 Countries Tracked

Zimbabwe

Zambia

Angola

Afghanistan

Albania

Algeria

Andorra

Antigua

Austria

Botswana

Brazil

📊 Key Visualizations

Total COVID-19 Cases Over Time

Total COVID-19 Deaths Over Time

Daily New Cases

Death Rate Over Time (total_deaths / total_cases)

Total COVID-19 Cases by Country (Bar Chart)

Correlation Heatmap between numerical COVID-19 metrics

Cumulative Vaccinations Over Time

Fully Vaccinated Population (% of population)

Vaccinated vs. Unvaccinated (Brazil - Pie Chart)

🧪 Data Handling

Filtered for selected countries of interest.

Handled missing values using linear interpolation.

Converted date columns to datetime objects.

Dropped rows with critical missing values (date, total_cases, etc.).

🛠️ Tools & Technologies

Python

Pandas – Data cleaning and manipulation

Matplotlib – Line, bar, and pie charts

Seaborn – Heatmaps and styled plots

📌 Notes

Latest data for vaccinated/unvaccinated pie chart is pulled for Brazil. If missing, fallback values are used.

Vaccination data shown as percentage of population using people_fully_vaccinated_per_hundred.