--- license: mit task_categories: - time-series-forecasting tags: - nigeria - agriculture - food-systems - synthetic - weather-and-climate size_categories: - 100K ⚠️ **Synthetic dataset** — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. # Nigeria Agriculture – Farm Weather Stations ## Dataset Description Daily weather: temp, rainfall, humidity, wind, solar radiation. **Category**: Weather & Climate **Rows**: 150,000 **Format**: CSV, Parquet **License**: MIT **Synthetic**: Yes (generated using reference data from FAO, NBS, NiMet, FMARD) ## Dataset Structure ### Schema - **state**: string - **date**: string - **temp_c**: float - **rainfall_mm**: float - **humidity_pct**: float - **wind_kmh**: float - **solar_mj_m2**: float ### Sample Data ``` | state | date | temp_c | rainfall_mm | humidity_pct | wind_kmh | solar_mj_m2 | |:--------|:-----------|---------:|--------------:|---------------:|-----------:|--------------:| | Rivers | 2022-09-26 | 24.9 | 9.5 | 92 | 12.2 | 16.7 | | Ondo | 2022-08-05 | 24.5 | 15.8 | 61.2 | 3.6 | 20.5 | | Yobe | 2023-10-30 | 29.2 | 2.1 | 80.4 | 1.7 | 23.1 | | Oyo | 2023-03-26 | 27.6 | 1.2 | 60 | 3.4 | 17.9 | | Ebonyi | 2024-08-09 | 27.9 | 1.8 | 66.8 | 9.7 | 19.5 | ``` ## Data Generation Methodology This dataset was synthetically generated using: 1. **Reference Sources**: - FAO (Food and Agriculture Organization) - crop yields, production data - NBS (National Bureau of Statistics, Nigeria) - farm characteristics, surveys - NiMet (Nigerian Meteorological Agency) - weather patterns - FMARD (Federal Ministry of Agriculture and Rural Development) - extension guides - IITA (International Institute of Tropical Agriculture) - agronomic research 2. **Domain Constraints**: - Crop calendars and phenology (planting/harvest windows) - Agro-ecological zone characteristics (Sahel, Sudan Savanna, Guinea Savanna, Rainforest) - Nigeria-specific realities (smallholder dominance, market dynamics, conflict zones) - Statistical distributions matching national agricultural patterns 3. **Quality Assurance**: - Distribution testing (KS test, chi-square) - Correlation validation (rainfall-yield, fertilizer-yield, yield-price) - Causal consistency (DAG-based generation) - Multi-scale coherence (farm → state aggregations) - Ethical considerations (representative, unbiased) See `QUALITY_ASSURANCE.md` in the repository for full methodology. ## Use Cases - **Machine Learning**: Yield prediction, price forecasting, pest detection, supply chain optimization - **Policy Analysis**: Agricultural program evaluation, subsidy impact assessment, food security planning - **Research**: Climate-agriculture interactions, market dynamics, technology adoption patterns - **Education**: Teaching agricultural economics, data science applications in agriculture ## Limitations - **Synthetic data**: While grounded in real distributions, individual records are not real observations - **Simplified dynamics**: Some complex interactions (e.g., multi-generational pest populations) are simplified - **Temporal scope**: Covers 2022-2025; may not reflect longer-term trends or future climate scenarios - **Spatial resolution**: State/LGA level; does not capture micro-level heterogeneity within localities ## Citation If you use this dataset, please cite: ```bibtex @dataset{nigeria_agriculture_2025, title = {Nigeria Agriculture – Farm Weather Stations}, author = {Electric Sheep Africa}, year = {2025}, publisher = {Hugging Face}, url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_agriculture_farm_weather_stations} } ``` ## Related Datasets This dataset is part of the **Nigeria Agriculture & Food Systems** collection: - https://huggingface.co/collections/electricsheepafrica/nigeria-agriculture-and-food-systems ## Contact For questions, feedback, or collaboration: - **Organization**: Electric Sheep Africa - **Collection**: Nigeria Agriculture & Food Systems - **Repository**: https://github.com/electricsheepafrica/nigerian-datasets ## Changelog ### Version 1.0.0 (October 2025) - Initial release - 150,000 synthetic records - Quality-assured using FAO/NBS/NiMet reference data