Agriculture
22 columns
200 rows
8 formats

Agri-Market Price Fluctuation Records

This dataset provides daily synthetic records of market prices for major crops across multiple regions, enriched with weather conditions and demand/supply shock indicators. It enables detailed analysis of price fluctuations, the impact of environmental and market events, and supports forecasting and agri-finance risk assessment. The dataset is ideal for researchers, policymakers, and financial institutions focused on agricultural markets.

last updated 12 Jul 2025
by GoMask

The brief that made it

Time-series analysis and forecasting of crop prices

Sample rows

preview · 8 of 200 rows · all 22 columns

record_idstring	weather_eventstring	weather_temperature_cfloat	demand_shockboolean	crop_idstring	datedate	region_idstring	region_namestring	market_idstring	market_namestring	crop_namestring	varietystring	unitstring	price_minfloat	price_maxfloat	price_modalfloat	volume_tradedfloat	weather_precipitation_mmfloat	supply_shockboolean	demand_shock_descriptionstring	supply_shock_descriptionstring	notesstring
REC00001	normal	13.5	false	CRP-WHEAT	2023-01-05	RGN-NW	Northwest Plains	MKT-NW-001	Amritsar Mandi	Wheat	Sharbati	quintal	2100	2225	2175	11500	2	false	blank	blank	Steady wheat arrivals; normal trading day and pricing.
REC00002	normal	24	false	CRP-TOMATO	2023-02-10	RGN-SC	South Central	MKT-SC-004	Hyderabad Main Market	Tomato	blank	kg	15.35	20	18	9850	0	false	blank	blank	Tomato prices stable; moderate supply, no unusual activity.
REC00003	flood	29.5	false	CRP-MAIZE	2023-07-17	RGN-WEST	Western States	MKT-WEST-002	Ahmedabad Agro Market	Maize	Yellow Dent	quintal	1770	1860	1820	8700	18.2	true	blank	Flooding delayed arrivals, causing temporary supply shortage.	Flood impacted logistics; prices marginally up, low arrivals.
REC00004	coldwave	8	false	CRP-POTATO	2023-12-17	RGN-NORTH	Northern Belt	MKT-NORTH-003	Lucknow Sabzi Mandi	Potato	Kufri Jyoti	kg	11.5	14.8	12.6	14650	0	true	blank	Coldwave reduced harvesting activity, limiting supply.	Coldwave led to restricted trading hours; prices marginally up.
REC00005	normal	31	false	CRP-RICE	2023-04-18	RGN-EAST	Eastern Plains	MKT-EAST-001	Kolkata Central Market	Rice	Swarna	kg	35	41	39.5	10500	8.4	false	blank	blank	Rice arrivals consistent; standard market operation.
REC00006	heatwave	34	false	CRP-OKRA	2023-06-09	RGN-EE	Eastern Expanse	MKT-EE-002	Bhubaneswar Market	Okra	blank	kg	18.8	23.6	21	6100	2.6	true	blank	Heatwave stressed crops, causing supply drop and price rise.	Heatwave led to reduced okra volume, higher modal prices.
REC00007	normal	33.2	false	CRP-ONION	2023-05-30	RGN-NW	Northwest Plains	MKT-NW-003	Jaipur Sabzi Mandi	Onion	Nasik Red	kg	19	22	20.5	12950	0	false	blank	blank	High onion arrivals; prices within expected range.
REC00008	flood	32	false	CRP-BANANA	2023-08-19	RGN-SOUTH	Southern States	MKT-SOUTH-002	Madurai Veg Market	Banana	Robusta	kg	27.5	32	29.8	5325	10.2	true	blank	Flooding in South disrupted banana supply chain.	Flood affected supply; prices rose, arrivals were limited.
REC00009	normal	29	false	CRP-GUAVA	2023-09-06	RGN-EE	Eastern Expanse	MKT-EE-003	Patna Fruit Market	Guava	blank	kg	24	28	26	2850	20	false	blank	blank	Guava trading smooth; moderate volume and pricing.
REC00010	coldwave	-4	false	CRP-APPLE	2023-01-01	RGN-NORTH	Northern Belt	MKT-NORTH-004	Dehradun Agro Market	Apple	Red Delicious	kg	0	0	0	0	0	true	blank	Market closed due to coldwave; no trading activity.	Coldwave closure—no trading or price data available.
REC00011	normal	19	true	CRP-CHICKPEA	2023-03-11	RGN-NW	Northwest Plains	MKT-NW-002	Ludhiana Grain Yard	Chickpea	Kabuli	kg	44	51	47.5	4200	4.1	false	Festival demand surge led to higher chickpea prices.	blank	Increased demand for festival; higher prices observed.
REC00012	normal	20	false	CRP-SOYBEAN	2023-02-16	RGN-EAST	Eastern Plains	MKT-EAST-002	Durgapur Market	Soybean	blank	quintal	4130	4250	4210	5800	1.5	false	blank	blank	Soybean arrivals steady; trade volume normal.
REC00013	heatwave	34.5	false	CRP-GARLIC	2023-06-24	RGN-SC	South Central	MKT-SC-003	Warangal Market	Garlic	Large Clove	kg	150	170	160	890	5.1	true	blank	Heatwave reduced garlic output; prices rose.	Lower arrivals due to heat stress; garlic prices up.
REC00014	normal	27.5	false	CRP-GRAPE	2023-10-10	RGN-WEST	Western States	MKT-WEST-003	Pune Fruit Market	Grape	Thompson Seedless	kg	65	78	73	970	1	false	blank	blank	Premium grape season; moderate volumes, good quality.
REC00015	other	25	false	CRP-PEAR	2023-08-05	RGN-EE	Eastern Expanse	MKT-EE-004	Ranchi Main Market	Pear	blank	kg	86	98	94	180	10.5	false	blank	blank	Low volume specialty fruit; niche market buyers.
REC00016	normal	30	false	CRP-MUSTARD	2023-07-22	RGN-NORTH	Northern Belt	MKT-NORTH-005	Kanpur Agro Market	Mustard	Yellow Sarson	quintal	5050	5200	5130	3300	14.7	false	blank	blank	Mustard trading steady; prices within expected range.
REC00017	normal	20.8	true	CRP-BARLEY	2023-03-23	RGN-NW	Northwest Plains	MKT-NW-004	Bikaner Mandi	Barley	Feed Grade	kg	22	26	24	2800	5	false	Barley demand increased due to brewery contract.	blank	Brewery contract increased demand; higher prices.
REC00018	other	19	false	CRP-TOMATO	2023-12-31	RGN-SOUTH	Southern States	MKT-SOUTH-001	Bangalore Central	Tomato	blank	kg	0	0	0	0	0	true	blank	Market closed for year-end maintenance.	No trading; market closed for annual maintenance.
REC00019	normal	26.1	false	CRP-PEA	2023-04-14	RGN-NORTH	Northern Belt	MKT-NORTH-001	Delhi Azadpur	Pea	Green Shelling	kg	34	43	39	3100	12.5	false	blank	blank	Spring pea arrivals; prices as expected.
REC00020	heatwave	36	false	CRP-MAIZE	2023-06-01	RGN-NW	Northwest Plains	MKT-NW-005	Jodhpur Main Market	Maize	White Maize	quintal	1755	1830	1790	7650	0	true	blank	Heatwave slowed harvest; maize arrivals reduced.	Maize volume below average due to heatwave stress.

What the 200 rows show

from the 200-row sample

Coldwave (weather event) stands out: mean weather_temperature_c is 4.5, against 25.7 for the rest.

10%demand_shock = true
26.6median weather_temperature_c
4units
7regions
23region names
54crop names

Mean weather_temperature_c by weather_event200 rows

weather_temperature_c200 rows, in bands of 5

Median 26.6, from -6.2 to 36.7.

crop_id200 rows · top 10 of 32 values

CRP-RICE15
CRP-TOMATO14
CRP-WHEAT13
CRP-POTATO12
CRP-ONION11
CRP-MAIZE10
CRP-OKRA10
CRP-MUSTARD10
CRP-PEA10
CRP-BANANA9

22 columns by typefrom the column list below

string 13
float 6
date 1
boolean 2

Columns

22 columns in four groups

blueprint · 22 columns
column	type	description	example
Text 13 columns
`record_id`	string	Unique identifier for each daily market price recordunique	REC00001
`region_id`	string	Unique identifier for the region where the market operates7 regions	RGN-NW
`region_name`	string	Name of the region (e.g., state, province, or district)	Northwest Plains
`market_id`	string	Unique identifier for the specific market within the region	MKT-NW-001
`market_name`	string	Name of the specific market	Amritsar Mandi
`crop_id`	string	Unique identifier for the crop	CRP-WHEAT
`crop_name`	string	Name of the crop (e.g., wheat, rice, maize)	Wheat
`variety`	string	Crop variety or grade (if applicable)optional	Sharbati
`unit`	string	Unit of measurement for the price (e.g., kg, quintal, ton)4 units	quintal
`weather_event`	string	Categorical weather event impacting the market (e.g., normal, drought, flood, storm)7 values · optional	normal
`demand_shock_description`	string	Short description of the demand shock event (if any)optional	Festival demand surge led…
`supply_shock_description`	string	Short description of the supply shock event (if any)optional	Flooding delayed arrivals…
`notes`	string	Additional notes or remarks about the recordoptional	Steady wheat arrivals; no…
Numbers 6 columns
`price_min`	float	Minimum price observed for the crop in the market on the given date0 or more	2100
`price_max`	float	Maximum price observed for the crop in the market on the given date0 or more	2225
`price_modal`	float	Most frequently observed price (modal price) for the crop in the market on the given date0 or more	2175
`volume_traded`	float	Total volume of the crop traded in the market on the given date (in the specified unit)0 or more · optional	11500
`weather_temperature_c`	float	Average temperature (in Celsius) in the region on the given dateoptional	13.5
`weather_precipitation_mm`	float	Total precipitation (in millimeters) in the region on the given date0 or more · optional	2
Dates and times 1 column
`date`	date	Date of the market price record	2023-01-05
True or false 2 columns
`demand_shock`	boolean	Indicates if there was a sudden change in demand (true/false) on the given dateoptional	false
`supply_shock`	boolean	Indicates if there was a sudden change in supply (true/false) on the given dateoptional	false

Use it for

An agriculture dashboard
The demand_shock rate, weather_temperature_c by weather_event and a breakdown of crop_id. Excel, Power BI or Tableau.
Why do the 18 coldwave rows have a mean weather_temperature_c of 4.5?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records200
REC0000113.5normal
REC0001119normal
REC0001720.8normal
A software demo
Believable records with date, region_id and region_name to fill a screen in front of a buyer.

This dataset200 rows22 columns

Yours1,000 rows22 columnsregion_id: UK only

blueprint · agri-market-price-fluctuation-records

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 22 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Each record: commodity, market, date, price
Weather and demand events impact price
Supply chain disruptions simulated seasonally
Missing values for select dates
Currency conversion for international markets

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: agri-market-price-fluctuation-records

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

An agriculture dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Agriculture

What should your data show?