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International Crop Yield Prediction Data
Data Science and Analytics
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About
Examines the relationship between environmental factors and agricultural productivity across various countries. This data contains information on crop yields, average rainfall, pesticide usage, and average temperature, providing valuable insights for agricultural analysis and crop yield prediction models.
Columns
- Area: The country or region where the data was recorded.
- Item: The specific type of agricultural crop or product.
- Year: The year the data was collected, ranging from 1990 to 2013.
- hg/ha_yield: Crop yield measured in hectograms per hectare (hg/ha).
- average_rain_fall_mm_per_year: The average annual rainfall in millimetres.
- pesticides_tonnes: The total amount of pesticides used, measured in tonnes.
- avg_temp: The average annual temperature in degrees Celsius.
Distribution
The data is provided in a single CSV file (
yield_df.csv) with a size of 1.57 MB. It is structured with 28,242 entries and 7 columns, with no missing values.Usage
Ideal for building predictive models to forecast crop yields based on environmental variables. It can be used for agricultural research to understand the impact of climate change and pesticide use on farming output. Additionally, it supports business analytics for supply chain management and agricultural investment strategies.
Coverage
- Geographic: Covers 101 different countries and regions globally, with India being the most frequently represented country.
- Time Range: The data spans the years from 1990 to 2013.
- Demographic: Not applicable.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For developing and training machine learning models for crop yield prediction.
- Agricultural Researchers: To analyse long-term trends in crop production and the effects of environmental factors.
- Policymakers: To inform agricultural policies related to sustainability, pesticide regulation, and climate change adaptation.
- Business Analysts: For market analysis and forecasting in the agribusiness sector.
Dataset Name Suggestions
- Global Crop Yield and Environmental Factors
- Agricultural Productivity and Climate Data (1990-2013)
- International Crop Yield Prediction Data
- Crop Production and Environmental Metrics
- World Agricultural Yields Dataset
Attributes
Original Data Source: International Crop Yield Prediction Data
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