Exploratory Data Analysis and Visualization using Python
This project analyzes rainfall patterns in India over multiple decades using Python.
The goal is to explore rainfall trends across different states and regions, understand seasonality, and identify long-term shifts that may inform agriculture, water management, and climate policy.
The project performs Exploratory Data Analysis (EDA) and builds interactive visualizations to communicate key insights.
✅ Analyze seasonal rainfall trends across India
✅ Explore state-wise rainfall variation
✅ Identify year-on-year trends and anomalies
✅ Support potential forecasting and long-term planning
✅ Communicate findings through clear visualizations
| Column | Description |
|---|---|
| Year | Year of observation |
| State/UT | State or Union Territory |
| JAN-FEB | Rainfall in Jan-Feb (mm) |
| MAR-MAY | Rainfall in Mar-May (mm) |
| JUN-SEP | Rainfall in Jun-Sep (mm) |
| OCT-DEC | Rainfall in Oct-Dec (mm) |
| ANNUAL | Total annual rainfall (mm) |
Source: [Indian Government Open Data / Kaggle - Rainfall in India dataset]
- Python 3
- pandas — Data manipulation & analysis
- matplotlib — Data visualization
- seaborn — Advanced visualization
- numpy — Numerical analysis
- Load dataset using pandas
- Handle missing values
- Explore data structure & basic statistics
- Analyze national annual rainfall trends
- Explore seasonal variation (monsoon vs non-monsoon months)
- Identify state-wise rainfall patterns
- Compare rainfall trends across states
- Highlight extreme rainfall years and anomalies
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Line plots of annual rainfall trends
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Bar plots of Average Monthly Rainfall
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Bar plots of Seasonal Rainfall Distribution
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Line plots of the Impact_of_climate_change_on_rainfall
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Plot of Annual Rainfall Forcast
✅ Significant seasonal variation — Jun-Sep monsoon dominates rainfall totals
✅ Certain states show high inter-annual variability (e.g., coastal regions)
✅ Trends suggest possible changes in monsoon intensity over recent decades
✅ Understanding rainfall trends is critical for agriculture planning and water resource management
✅ Support for climate-resilient agriculture planning
✅ Insights for state-level water resource management
✅ Historical analysis can inform future forecasting models
✅ Helps policy makers understand long-term climate shifts
- Rainfall Trends in India → Main Python analysis notebook
- rainfall_area-wt_India_1901-2015 → Dataset used for the project
Dataset source: Indian Government Open Data / Kaggle. Thanks to the open data community for making this dataset available.
For questions or collaboration opportunities, feel free to connect!