Covid--19-data-analysis
Covid–19-data-analysis
This project is a dashboard representation of the Covid-19 on power bi for better analysis
🦠 COVID-19 Data Analysis Dashboard
📌 Project Title:
COVID-19 Data Analysis
📖 Problem Statement:
Understanding COVID-19 trends across countries and WHO regions helps in planning informed public health policies, allocating healthcare resources, and identifying high-risk zones.
🎯 Objective:
To analyze global COVID-19 data and visualize:
- Overall and country-wise case trends
- Recovery and death rates
- Weekly growth and new case surges
- WHO region-wise comparisons
🧾 Dataset Attributes:
The dataset used contains the following columns:
| Column Name | Description |
|---|---|
Country/Region |
Name of the country or region |
Confirmed |
Total confirmed cases |
Deaths |
Total deaths |
Recovered |
Total recoveries |
Active |
Currently active cases |
New cases |
New cases reported in the latest update |
New deaths |
New deaths reported in the latest update |
New recovered |
New recoveries reported in the latest update |
Deaths / 100 Cases |
Deaths per 100 confirmed cases (mortality rate) |
Recovered / 100 Cases |
Recoveries per 100 confirmed cases |
Deaths / 100 Recovered |
Deaths per 100 recoveries |
Confirmed last week |
Total confirmed cases one week ago |
1 week change |
Change in cases over one week |
1 week % increase |
Weekly case growth rate (%) |
WHO Region |
World Health Organization region classification |
🛠️ Tools Used:
- Power BI – for interactive visualizations and dashboards
- Python (optional) – for initial data cleaning or preprocessing
- CSV dataset – structured pandemic data
📊 Visualizations Created in Power BI:
- Cards – Total Confirmed, Deaths, Recovered, and Active
- Bar Charts – Top 10 countries by:
- Confirmed cases
- New daily cases
- Stacked Area Chart – Composition of confirmed cases (Active, Recovered, Deaths)
- Scatter Plot – Deaths per 100 cases vs Recovery per 100 cases
- Matrix with Conditional Formatting – Weekly % growth (simulated heatmap)
- Stacked Bar Chart – WHO region-wise summary (Confirmed, Deaths, Recoveries)
- Slicers – Filter dashboard by
Country/RegionorWHO Region
📈 Key Insights:
- Countries such as the USA, India, and Brazil report the highest confirmed cases.
- Recovery rates exceed 85% in many regions, but death rates vary significantly.
- Weekly % increase highlights ongoing surges in certain regions.
- Americas and Europe show highest case burden, while SE Asia shows better recovery efficiency.
- Data Source: WHO or public COVID-19 APIs/datasets (based on actual data source used)
- Visuals & Dashboard: Created using Power BI Desktop
- python code and liabraries : To visualize the data on numpy , pandas , matplotlib and seaborn
✅ Outcome:
A comprehensive visual story that presents the spread, severity, and recovery trends of COVID-19 globally — enabling better public health insights and communication.