Global Air Quality Index Analysis – Power BI Project Explanation
Yeh Power BI dashboard “Global Air Quality Index (AQI)” ke analysis ke liye banaya gaya hai. Isme alag-alag pollutant components jaise CO, NO2, Ozone, PM2.5 ka visualization diya gaya hai. Dashboard me kai countries aur unke cities ka comparison bhi hai.
🧩 Dashboard ke Key Components (Top Cards):
- Average of AQI Value –
72.01:- Yeh batata hai duniya bhar ka average AQI value.
- Avg of CO AQI Value –
1.37 - Avg of NO2 AQI Value –
3.06 - Avg of Ozone AQI Value –
35.19 - Avg PM2.5 AQI Value –
68.52
Project ke liye dataset ko yaha se download kijiye: https://www.kaggle.com/datasets/sazidthe1/global-air-pollution-data
📊 Visualizations and Graphs Explanation:
📉 1. Bottom 8 Countries with Lower PM2.5 AQI Value:
- Finland, Sweden, Papua New Guinea jaise countries ki PM2.5 value sabse kam hai (yaani hawa sabse saaf hai).
🧮 2. Count of City by CO AQI Category:
- Zyada tar cities (23,460) “Good” category me aati hain.
🌀 3. Count of City by Ozone AQI Category (Donut Chart):
- 89.8% cities me ozone AQI “Good” hai.
📏 4. Count of City by PM2.5 AQI Category:
- Is bar chart me dikhaya gaya hai kitni cities “Good”, “Moderate”, ya “Unhealthy” hain.
🌫 5. Top 10 Countries by Higher Avg AQI:
- Republic of Korea sabse zyada average AQI value (421) ke saath top pe hai.
🟢 6. Top 8 Countries by Higher Avg CO AQI:
- Pie chart ke through countries ka breakdown diya gaya hai jinme CO pollution zyada hai.
🧪 7. Top 10 Countries by Higher Avg NO2 AQI:
- Yeh chart countries ka NO2 ke basis pe comparison karta hai – Korea, Kuwait, El Salvador etc.
🍃 8. Count of City by AQI Category (Pie Chart):
- Pie chart se dikh raha hai ki 42.3% cities ki air quality “Good” hai, jabki kuch cities “Unhealthy” ya “Hazardous” me bhi aati hain.
🔍 Filter Panel (Top Right Corner):
- Country aur City ke dropdown filters use karke aap analysis ko country-specific ya city-specific bana sakte ho.
💡 Power BI Concepts Used in Is Project:
- Card Visuals: KPI highlights (Avg AQI, PM2.5 etc.)
- Bar/Column Charts: Country/city-wise comparisons
- Pie & Donut Charts: Percentage-wise category distribution
- TreeMap: Complex comparison of countries by pollutant levels
- Slicers: Interactive filters for Country/City
- Data Modeling: Air quality data ko pollutants ke basis pe relational banaya gaya hoga (Power BI Data Model)
🧠 Learning Outcomes (Seekhne layak):
- Real-time data visualization with pollution metrics
- Interactive dashboard building
- Power BI ke chart types aur slicer functionality ka use
- Country-level air pollution insights banana