US industrial production and capacity use (monthly)

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Monthly US industrial-production panel, 1919-01 onward: the Federal Reserve Board G.17 Industrial Production total index (2017=100, seasonally adjusted) and total-industry capacity utilization percent (from 1967-01), redistributed keyless via FRED fredgraph.csv, with month-over-month and year-over-year IP change, IP deviation from its trailing-12-month mean, and capacity-utilization deviation from its trailing-12-month mean. The catalog's only US production-level series — regional Fed surveys carry sentiment, durable orders carry demand flow, StatCan carries Canadian industry. Who joins this: sales teams weight manufacturing-exposed territories and pipeline by the production regime; shops read factory momentum as a supply-chain and durable-demand leading indicator; subscription businesses use capacity tightness as a pricing-power feature.

Source: US Industrial Production (FRED, keyless)
Rows: 1,292
Columns: 11
Source cadence: Monthly
Last refreshed: Oct 1, 2026
Theme: economy

Column	Type	Description
date	date	First day of the observation month (G.17 monthly calendar). The panel join key. (unit: date)
year_month	string	Calendar month as YYYY-MM. (unit: string)
country	string	Country name (shared normalization layer). (unit: string)
country_code	string	ISO 3166-1 alpha-3 country code (USA). (unit: string)
ip_index	float	Industrial Production: Total Index (FRED INDPRO, Board of Governors G.17), 2017=100, seasonally adjusted. (unit: index 2017=100)
capacity_util_pct	float	Capacity Utilization: Total Industry (FRED TCU, Board of Governors G.17), percent, seasonally adjusted. Null before 1967-01. (unit: percent)
ip_mom_pct	float	Month-over-month percent change of the IP index (null on the first panel month). (unit: percent)
ip_yoy_pct	float	Year-over-year percent change of the IP index (null for the first 12 panel months). (unit: percent)
ip_vs_12m_avg_pct	float	IP index deviation from its trailing-12-month mean, in percent (null until 12 observations). (unit: percent)
caputil_vs_12m_avg_pp	float	Capacity-utilization deviation from its trailing-12-month mean, in percentage points (null until 12 TCU observations; null wherever TCU is null). (unit: percentage points)
row_hash	string	Deterministic 16-hex sha256 of date + IP index + capacity utilization (idempotency key). (unit: string)

First 10 sample rows — a preview, not the complete dataset.

date	year_month	country	country_code	ip_index	capacity_util_pct	ip_mom_pct	ip_yoy_pct	ip_vs_12m_avg_pct	caputil_vs_12m_avg_pp	row_hash
1919-01-01	1919-01	United States	USA	4.874	—	—	—	—	—	c5555cfbfef4bfb0
1919-02-01	1919-02	United States	USA	4.659	—	-4.419	—	—	—	8381a4a8762d969a
1919-03-01	1919-03	United States	USA	4.524	—	-2.891	—	—	—	c4fb9ee8b4be577a
1919-04-01	1919-04	United States	USA	4.605	—	1.786	—	—	—	410f96ccb7828196
1919-05-01	1919-05	United States	USA	4.632	—	0.584	—	—	—	bd76a7ae0f4dded3
1919-06-01	1919-06	United States	USA	4.928	—	6.395	—	—	—	bbc29a70a78b5de1
1919-07-01	1919-07	United States	USA	5.224	—	6.011	—	—	—	cc84f1a44bd0c7a2
1919-08-01	1919-08	United States	USA	5.305	—	1.547	—	—	—	71539634c6983b60
1919-09-01	1919-09	United States	USA	5.197	—	-2.03	—	—	—	1e70e7fb1fee8e26
1919-10-01	1919-10	United States	USA	5.143	—	-1.035	—	—	—	4eba109846fc6892

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/fred_industrial_production_intel/us_industrial_production_monthly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/fred_industrial_production_intel/us_industrial_production_monthly").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/fred_industrial_production_intel/us_industrial_production_monthly

Tip: fetch /llms.txt for the full machine-readable catalog.

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Pinned to snapshot 20261001T102255Z-5fb79691dab8 and its content hash, so readers get exactly the data you used.

APA

US Industrial Production (FRED, keyless). (2026). US industrial production and capacity use (monthly) [Data set, snapshot 20261001T102255Z-5fb79691dab8, sha256 5fb79691dab8]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/en/datasets/fred_industrial_production_intel/us_industrial_production_monthly?snapshot=20261001T102255Z-5fb79691dab8

BibTeX

@misc{dz_fred_industrial_production_intel_us_indu_5fb79691,
  title        = {{US industrial production and capacity use (monthly)}},
  author       = {{US Industrial Production (FRED, keyless)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/fred_industrial_production_intel/us_industrial_production_monthly?snapshot=20261001T102255Z-5fb79691dab8}},
  note         = {Snapshot 20261001T102255Z-5fb79691dab8, sha256 5fb79691dab81482308a02cb5c2d50b67ea8dcacb5868ae47b273b410c50dd65; accessed 2026-10-01}
}

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US industrial production and capacity use (monthly)

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