WHO Air Quality Analysis

Analyze WHO Air Quality data with EDA, PCA, Regression, and Classification. Predict PM2.5 levels and classify regions into High vs Low pollution risk.

Features

• EDA: PM2.5 distribution, correlation heatmap
• PCA: Dimensionality reduction & visualization
• Regression: Linear Regression for PM2.5 prediction
• Classification: Logistic Regression (High vs Low PM2.5)
• Metrics & Plots: R², RMSE, MAE, Confusion Matrix, ROC Curve

Setup

git clone https://github.com/your-username/air-quality-analysis.git
cd air-quality-analysis
pip install -r requirements.txt

Run

python analysis.py

Outputs (plots + metrics) will be saved in the outputs/ folder and displayed in console.

Outputs

• eda_distribution_pm25.png
• eda_correlation.png
• pca_scatter.png
• regression_true_vs_pred.png
• classification_confusion_matrix.png
• classification_roc_curve.png

References

• WHO Air Quality Database