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Crop Yield Prediction Data
Data Science and Analytics
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About
This dataset contains agricultural data designed for predicting crop yield, measured in tons per hectare. It comprises 1,000,000 samples and is well-suited for machine learning regression tasks, particularly for forecasting crop productivity based on various influencing factors.
Columns
- Region: The geographical area where the crop is cultivated, including North, East, South, and West.
- Soil_Type: The specific type of soil used for planting the crop, such as Clay, Sandy, Loam, Silt, Peaty, and Chalky.
- Crop: The variety of crop grown, for instance, Wheat, Rice, Maize, Barley, Soybean, and Cotton.
- Rainfall_mm: The total rainfall received in millimetres during the crop's growth period.
- Temperature_Celsius: The average temperature during the crop's growth period, recorded in degrees Celsius.
- Fertilizer_Used: A boolean indicator specifying whether fertiliser was applied (True for Yes, False for No).
- Irrigation_Used: A boolean indicator showing whether irrigation was employed during the crop growth period (True for Yes, False for No).
- Weather_Condition: The primary weather condition experienced during the growing season, including Sunny, Rainy, and Cloudy.
- Days_to_Harvest: The number of days from planting until the crop is ready for harvest.
- Yield_tons_per_hectare: The final crop yield, expressed in tons per hectare.
Distribution
The dataset is provided as a data file, typically in CSV format, named
crop_yield.csv with a size of 93.41 MB. It contains 1,000,000 samples across 10 distinct columns. Specific details regarding row or record counts are readily available within the dataset itself.Usage
This dataset is ideal for regression tasks within machine learning, specifically for predicting crop productivity. It can also be effectively utilised for data analytics, offering insights into agricultural factors influencing yield.
Coverage
The dataset covers geographical regions designated as North, East, South, and West. While specific time ranges are not detailed, the dataset includes 1,000,000 samples, providing a substantial basis for analysis across various agricultural conditions.
License
CC0: Public Domain
Who Can Use It
This dataset is suitable for a range of users including machine learning practitioners, data analysts, agricultural researchers, and students. It is particularly valuable for those focusing on crop yield prediction, agricultural data analysis, or exploring beginner to intermediate machine learning projects.
Dataset Name Suggestions
- Agriculture Crop Yield Dataset
- Crop Yield Prediction Data
- Agricultural Productivity Factors
- Farm Yield Data
- Global Crop Yield Determinants
Attributes
Original Data Source: Crop Yield Prediction Data
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