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Market-Level Minimum, Maximum, and Modal Prices
Retail & Consumer Behavior
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About
Prices of various agricultural commodities across India are provided, detailing minimum, maximum, and modal price points based on market, district, and state locations. This data captures the fluctuation of prices for hundreds of day-to-day commodities, offering insights crucial for understanding market dynamics and agricultural economics. The data was gathered to investigate how prices change over time and geography, and to explore the economic factors affecting farmers.
Columns
- Commodity Name: The specific name of the agricultural product being tracked. Over 250 unique commodities are represented, including common items like Onion and Tomato. (String)
- State: The Indian State where the price record originated. (String)
- District: The District within the State associated with the record. (String)
- Market: The specific local market where the price data was obtained. This includes nearly 2,400 distinct markets. (String)
- Min Price: The minimum recorded price for the commodity. The price is reported after conversion from Quintal to Kilogram. (Float)
- Max Price: The maximum recorded price for the commodity. The price is reported after conversion from Quintal to Kilogram. (Float)
- Modal Price: The most frequently occurring price point for the commodity. The price is reported after conversion from Quintal to Kilogram. (Float)
- Date: The date of collection for the price observation.
Distribution
The data is structured for use, typically provided in a CSV file format. It contains approximately 837,000 valid records, covering 348 unique agricultural commodities. The sample file size is around 62.31 MB. Prices span a wide range, with minimum prices reaching up to 80.2k and maximum prices up to 74.2k in the recorded unit.
Usage
- Price Volatility Research: Analyzing the daily changes and seasonality in agricultural commodity costs.
- Profit Planning: Identifying periods and regions where specific commodities can be cultivated to achieve greater profit.
- Market Demand Assessment: Using price data to infer local and regional demand patterns for crops.
- Geographical Price Comparison: Analyzing how price discrepancies arise between different markets, even those within the same district.
- Economic Modeling: Potential for linking commodity pricing trends with external economic indicators, such as fuel price changes.
Coverage
The geographic scope is entirely focused on India, capturing detailed agricultural price data across numerous states, districts, and local markets. The data's temporal coverage spans a significant period, running from May 2019 through to October 2021.
License
CC0: Public Domain
Who Can Use It
- Agricultural Analysts: To develop predictive models for future crop price movements.
- Government Bodies/Researchers: To assess food security, market intervention needs, and farmer income challenges.
- Business Intelligence Professionals: To inform sourcing and logistical decisions in the food supply chain.
- Students and Academics: For economic research projects focusing on price mechanisms and agricultural market efficiency in India.
Dataset Name Suggestions
- Indian Agricultural Market Prices by Location (2019-2021)
- Agri Commodity Price Fluctuation Data (India)
- Market-Level Minimum, Maximum, and Modal Prices
Attributes
Original Data Source: Market-Level Minimum, Maximum, and Modal Prices
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