A Comprehensive Agricultural Dataset designed for XAI in Crop Data-Driven Decision Making for the Indian Population

This dataset presents a comprehensive agricultural data repository developed to support crop prediction, yield estimation, irrigation analysis, and data-driven agricultural decision-making for the Indian population. The dataset integrates multiple verified governmental and institutional agricultural data sources into a unified machine learning-ready tabular dataset. It combines climate, soil, fertilizer, irrigation, groundwater, and crop production information to support agricultural analytics, explainable AI (XAI), precision farming, and sustainable agriculture research. Dataset Characteristics:- Total Records: 1,194,806- Total Features: 36- Geographic Coverage: All 28 Indian states- Temporal Coverage: 1980 onwards- Data Formats: CSV and XLSX Features Included:- Rainfall- Humidity- Soil Type- Nitrogen (N)- Phosphorus (P)- Potassium (K)- Crop Type- Crop Season- Production- Yield- Irrigation Information- Groundwater Information- State and District-Level Agricultural Data The dataset was constructed through multi-source integration, preprocessing, text standardisation, unit normalisation, composite key-based merging, and missing-value handling to ensure consistency and reliability for machine learning and research applications. Potential Applications:- Crop recommendation systems- Crop yield prediction- Agricultural production forecasting- Smart irrigation analysis- Precision farming- Explainable AI (XAI)- Sustainable agriculture research This dataset is intended strictly for research and academic purposes.