USDA ERS Farm-to-Consumer Price Spreads
USDA ERS Farm-to-Consumer Price Spreads
USDA ERS publishes separate CSV and XLSX files comparing retail food prices with farm values for dairy, fruit, vegetables, juice and field-crop foods and market baskets. Long-form files carry commodity, year, attribute and value fields for retail cost, farm value, price spread, farm share or indexes, and no key is needed.
Required Attribution:
Provider citation: “U.S. Department of Agriculture, Economic Research Service. Price spreads from farm to consumer.”
Coverage
The data use annual U.S. national-average retail and farm prices; coverage varies by series and current methodology, with fresh-fruit and vegetable baskets available since 2000 and the current dairy basket since 2016. Files update annually as inputs become available, while listed file dates differ by product. The checked fresh-apples CSV covered 2008–2025 with 54 rows across three attributes.
Verdict
This provides an annual signal for how retail food value is divided between farm receipts and the downstream marketing spread. National averages do not represent local, brand or package-specific prices, and many inputs lack accuracy measures or confidence intervals. ERS periodically replaces series, baskets and conversion factors, so archived and current histories can contain structural breaks. Updates are annual and lag the underlying price year.
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Use in your agent
Load USDA fresh-apple price spreads into pandas and Parquet. Checked against the provider's documentation on Nov 1, 2026.
Access
- No account or key. Each current commodity table has a public CSV download.
Request
curl -O 'https://www.ers.usda.gov/media/5736/fresh-apples.csv?v=15561'Format
Long-form CSV with Commodity, Year, Attribute and Value; attributes in this file cover retail price, farm value and farm share.
Load into pandas and Parquet
Needs Python 3 with requests, pandas and pyarrow.
"""USDA ERS fresh-apple farm-to-consumer price spreads -> pandas -> Parquet."""
import io
import requests
import pandas as pd
URL = "https://www.ers.usda.gov/media/5736/fresh-apples.csv?v=15561"
r = requests.get(URL, timeout=60)
r.raise_for_status()
df = pd.read_csv(io.BytesIO(r.content), encoding="utf-8-sig")
df.to_parquet("usda_price_spreads_fresh_apples.parquet", index=False)
print(len(df), "rows", df["Year"].min(), "to", df["Year"].max(),
df["Attribute"].nunique(), "attributes")Run by us on 2026-11-01 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 54 rows 2008 to 2025 3 attributes
Limits
- Rate limit: Not stated.
- Each CSV covers one food or market basket rather than the whole product.
- Current files update annually as underlying inputs become available.
Quirks
- Units are embedded in Attribute labels rather than a separate unit column.
- Series are national annual averages and should not be interpreted as local prices.
- Basket definitions, source price series and conversion factors can change; use archived tables when a prior methodology is required.
Terms and attribution
- The documentation supplies a USDA ERS citation.
- No separate data licence is stated on the checked product pages.
Sources
- https://www.ers.usda.gov/data-products/price-spreads-from-farm-to-consumer/documentation: “Data for individual foods and market baskets are updated annually as the underlying data on retail prices, farm prices, and co-products values become available.”
- https://www.ers.usda.gov/data-products/price-spreads-from-farm-to-consumer/documentation: “Price Spreads from Farm to Consumer uses U.S. annual, national-average prices to compare the value of foods at retail and on the farm.”
- https://www.ers.usda.gov/data-products/price-spreads-from-farm-to-consumer/documentation: “Many of the farm and retail price data used to calculate statistics do not include accuracy measures.”
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