🦠 COVID-19 Global Data — Data Visualization

CodeAlpha Data Analytics Internship | Task 3

📌 Project Overview

Data Visualization on COVID-19 Global Dataset using Python. Transformed raw data into compelling visual formats like charts, graphs and dashboards.

🛠️ Tools & Libraries

• Python, Pandas, NumPy, Matplotlib, Seaborn

📁 Dataset

• COVID-19 Global Data (15 Countries)
• Features: Total Cases, Deaths, Recovered, Death Rate, Recovery Rate, Cases Per Million

🔍 Visualization Steps# # 🦠 COVID-19 Global Data — Data Visualization

CodeAlpha Data Analytics Internship | Task 3

📌 Project Overview

Data Visualization on COVID-19 Global Dataset using Python. Transformed raw data into compelling visual formats like charts, graphs and dashboards.

🛠️ Tools & Libraries

• Python, Pandas, NumPy, Matplotlib, Seaborn

📁 Dataset

• COVID-19 Global Data (15 Countries)
• Features: Total Cases, Deaths, Recovered, Death Rate, Recovery Rate, Cases Per Million

🔍 Visualization Steps

1. Data Loading & Metric Calculation
2. Total Cases by Country
3. Death Rate Analysis
4. Recovery Rate Analysis
5. Cases vs Deaths Scatter Plot
6. Cases Per Million Population
7. Stacked Bar Chart
8. Correlation Heatmap

📊 Key Insights

• USA has highest total cases (103M+)
• Mexico has highest death rate
• Most countries have 95%+ recovery rate
• Higher population does not always mean higher cases per million

🚀 How to Run

pip install pandas numpy matplotlib seaborn python data_visualization.py

👤 Author

Dharshini | CodeAlpha Data Analytics Intern

👤 Author

Dharshini | CodeAlpha Data Analytics Intern