USDA ERS Feed Grains Database
USDA ERS Feed Grains Database
USDA ERS publishes a machine-readable CSV and Excel workbook of feed-grain supply, use, trade, prices, acreage, production, feed ratios and related series. The CSV fields identify table group, table, commodity, attribute, geography, year, frequency, time period, unit and amount, and no key is needed.
Coverage
The compilation covers U.S. corn, sorghum, barley, oats and hay plus world coarse grains and related feed statistics; the historical series generally reach back to 1866. Series are monthly, quarterly or annual, and the checked all-years files were updated October 13, 2026 with the next update scheduled for November 12, 2026. The checked CSV contained 81,346 rows and 80 commodity labels.
Verdict
This is a long-run supply, demand, price and trade signal for feed costs, grain balances and livestock margins. Frequencies and marketing-year calendars vary by commodity and table, so observations are not automatically comparable on calendar time. Recent annual values can be preliminary or projected, while missing values can mean unreported, discontinued or not-yet-released data. The former custom-query application was discontinued; ingestion should use the all-years files.
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Use in your agent
Load USDA feed-grain history into pandas and Parquet. Checked against the provider's documentation on Nov 1, 2026.
Access
- No account or key. The all-years CSV is a public download.
- The CSV is about 16.5 MB on the checked product page.
Request
curl -O 'https://www.ers.usda.gov/media/5766/feed-grains-yearbook-tables-all-years.csv?v=97927'Format
Long-form CSV with table_group, table_name, commodity_group, commodity, attribute, geography, year, frequency, timeperiod, unit and amount.
Load into pandas and Parquet
Needs Python 3 with requests, pandas and pyarrow.
"""USDA ERS Feed Grains all-years CSV -> pandas -> Parquet. No key."""
import io
import requests
import pandas as pd
URL = "https://www.ers.usda.gov/media/5766/feed-grains-yearbook-tables-all-years.csv?v=97927"
r = requests.get(URL, timeout=60)
r.raise_for_status()
df = pd.read_csv(io.BytesIO(r.content))
df.to_parquet("usda_ers_feed_grains_all_years.parquet", index=False)
print(len(df), "rows", df["year"].min(), "to", df["year"].max(),
df["commodity"].nunique(), "commodities")Run by us on 2026-11-01 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 81346 rows 1866 to 2026 80 commodities
Limits
- Rate limit: Not stated.
- The all-years CSV was listed as 16.52 MB when checked.
- The former custom-query application and associated CSV were discontinued in May 2025.
Quirks
- frequency and timeperiod must be retained because series use monthly, quarterly, annual and differing marketing-year calendars.
- Latest values may be preliminary or projected.
- Missing values can represent unreported observations, discontinued series or data not yet released.
Terms and attribution
- No separate data licence is stated on the checked product pages.
- The product page states no separate licence for the downloadable files.
Sources
- https://www.ers.usda.gov/data-products/feed-grains-database/feed-grains-yearbook-tables: “Data are monthly, quarterly, and/or annual depending upon the data series.”
- https://www.ers.usda.gov/data-products/feed-grains-database/feed-grains-yearbook-tables: “Latest data may be preliminary or projected.”
- https://www.ers.usda.gov/data-products/feed-grains-database/documentation: “the Feed Grains Yearbook Tables—Historical data set generally covers a longer time period (1866–present).”
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