Crop Yield Prediction Dataset

Columns and Features:

1. Country (Area): Represents the countries or regions where agricultural data is collected. The categorical nature of this column makes it suitable for cross-regional analysis and comparing global trends.
2. Crop Type (Item): This column specifies the agricultural product, including a wide variety of crops like grains, fruits, and vegetables. Understanding specific crop characteristics aids in precision farming and resource management.
3. Year of Record: Represents the year for which the data is documented. This column supports historical trend analysis and helps in modeling long-term effects of climate change or policy shifts on crop yields.
4. Yield per Hectare (hg/ha): Indicates the crop yield measured in hectograms per hectare, reflecting the efficiency of agricultural production. Yield rates can help monitor productivity and evaluate farming practices in different areas.
5. Annual Rainfall (mm/year): Tracks the average annual rainfall in millimeters for each country. Rainfall is critical for crop health, soil conditions, and water management strategies, making this column essential for predicting crop yield.
6. Pesticide Usage (tonnes): Captures the amount of pesticides applied, measured in tonnes. This column allows researchers to assess the relationship between pesticide usage and yield, as well as the environmental impacts of agricultural practices.

Potential Uses of the Dataset:

• Yield Prediction: The dataset can be utilized to develop machine learning models for predicting crop yields based on historical data and environmental factors.
• Sustainability Analysis: Researchers can analyze the relationship between pesticide use, yield, and environmental sustainability. Insights from this data can help design more sustainable farming practices.
• Climate Change Impact: By evaluating long-term trends in temperature and rainfall, the dataset helps model the impact of climate change on agricultural productivity and aids in adaptive strategies for farmers.