Agricultural Yield Prediction Dataset with Weather, Soil, and Crop Data

247,000 rows of data integrating weather, soil, fertilizer, irrigation, and crop information for yield prediction. The dataset was sourced from Kaggle, though the author and specific collection methodology are unspecified. Its temporal and geographic coverage are not detailed in the provided description.

Use Cases

• Predict crop yields based on integrated weather and soil data.
• Analyze the impact of fertilizer application rates on yield outcomes.
• Model the relationship between irrigation practices and agricultural productivity.
• Train machine learning models for precision agriculture recommendations.

Strengths

• Contains 247,000 rows of data.
• Integrates multiple data types mentioned in the description: weather, soil, fertilizer, irrigation, and crop data.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle