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license: other
license_name: public-domain-source-us-government
pretty_name: "US Macro Data: Production"
language:
- en
tags:
- finance
- economics
- macroeconomics
- time-series
- fred
- production
- quant
- backtesting
size_categories:
- 1K<n<10K
configs:
- config_name: long
data_files: data/long.parquet
default: true
- config_name: wide_monthly
data_files: data/wide_monthly.parquet
- config_name: wide_quarterly
data_files: data/wide_quarterly.parquet
---
# US macro data: Production (120 series)
120 production series from US government sources, cleaned into one consistent format and ready for pandas.
This free package holds the **last 12 months** (2025-11-02 on) of each series' latest values. It is refreshed weekly.
```python
import pandas as pd
df = pd.read_parquet("hf://datasets/FinzData/macro-production/data/long.parquet") # series_id, date, value
wide = pd.read_parquet("hf://datasets/FinzData/macro-production/data/wide_monthly.parquet") # one column per series
```
or `datasets.load_dataset("FinzData/macro-production")`. Wide tables by frequency: `wide_monthly` (105 series), `wide_quarterly` (15 series). `series.csv` lists every series
with its title, units, frequency and how far back the full history goes.
## The full history, point in time, through one API
The FinzData API serves every series back to its first observation, **every revision** (what was known on any past
date, so backtests do not peek at later revisions), and **daily updates**, in the same format:
```python
import finzdata as fz # pip install finzdata
c = fz.Client() # free API key: https://api.finzdata.com/
c.macro("INDPRO") # full history, latest values
c.macro("INDPRO", vintage="first") # as first released
c.macro("INDPRO", as_of="2020-03-01") # exactly what was known on that date
c.macro_series(category="production") # the catalogue for this category
```
## Most-watched series in this package
| ID | Title | Units | Frequency | Full history from |
|---|---|---|---|---|
| `INDPRO` | Industrial Production: Total Index | Index 2017=100 | Monthly | 1919 |
| `IPMAN` | Industrial Production: Manufacturing (NAICS) | Index 2017=100 | Monthly | 1972 |
| `TCU` | Capacity Utilization: Total Index | Percent | Monthly | 1967 |
| `DGORDER` | Manufacturers' New Orders: Durable Goods | Millions of Dollars | Monthly | 1958 |
| `DAUPSA` | Domestic Auto Production | Thousands of Units | Monthly | 1993 |
| `MCUMFN` | Capacity Utilization: Manufacturing (NAICS) | Percent | Monthly | 1972 |
| `OUTMS` | Manufacturing Sector: Real Sectoral Output for All Workers | Index 2017=100 | Quarterly | 1949 |
| `C307RX1Q020SBEA` | Real private fixed investment: Nonresidential: Structures: Manufacturing | Billions of Chained 2017 Dollars | Quarterly | 1995 |
| `MNFCTRIRSA` | Manufacturers: Inventories to Sales Ratio | Ratio | Monthly, End of Period | 1992 |
| `IPG3344S` | Industrial Production: Manufacturing: Durable Goods: Semiconductor and Other Electronic Component (NAICS = 3344) | Index 2017=100 | Monthly | 1972 |
| `A34SNO` | Manufacturers' New Orders: Computers and Electronic Products | Millions of Dollars | Monthly | 1992 |
| `IPG3361T3S` | Industrial Production: Manufacturing: Durable Goods: Motor Vehicles and Parts (NAICS = 3361-3) | Index 2017=100 | Monthly | 1972 |
| `IPMANSICS` | Industrial Production: Manufacturing (SIC) | Index 2017=100 | Monthly | 1919 |
| `GOMA` | Gross Output by Industry: Manufacturing | Billions of Dollars | Quarterly | 2005 |
| `CAPUTLG3311A2S` | Capacity Utilization: Manufacturing: Durable Goods: Iron and Steel Products (NAICS = 3311,2) | Percent | Monthly | 1972 |
| `ADXTNO` | Manufacturers' New Orders: Durable Goods Excluding Transportation | Millions of Dollars | Monthly | 1992 |
| `BSCICP02USM460S` | Business Tendency Surveys (Manufacturing): Confidence Indicators: Composite Indicators: National Indicator for United States | Percent | Monthly | 1950 |
| `C307RC1Q027SBEA` | Private fixed investment: Nonresidential: Structures: Manufacturing | Billions of Dollars | Quarterly | 1958 |
| `IPG325S` | Industrial Production: Manufacturing: Nondurable Goods: Chemical (NAICS = 325) | Index 2017=100 | Monthly | 1972 |
| `ACOGNO` | Manufacturers' New Orders: Consumer Goods | Millions of Dollars | Monthly | 1992 |
| `IPB50001N` | Industrial Production: Total Index | Index 2017=100 | Monthly | 1919 |
| `IPN3311A2RS` | Industrial Production: Manufacturing: Durable Goods: Raw Steel (NAICS = 3311,2pt.) | Index 2017=100 | Monthly | 1972 |
| `RVAMA` | Real Value Added by Industry: Manufacturing | Billions of Chained 2017 Dollars | Quarterly | 2005 |
| `IPG334S` | Industrial Production: Manufacturing: Durable Goods: Computer and Electronic Product (NAICS = 334) | Index 2017=100 | Monthly | 1972 |
| `IPUTIL` | Industrial Production: Utilities: Electric and Gas Utilities (NAICS = 2211,2) | Index 2017=100 | Monthly | 1939 |
All 120 series: `series.csv`. Browse them at https://finzdata.com/macro/category/production.
## More from FinzData
- Every macro category: https://huggingface.co/FinzData · index on GitHub: https://github.com/FinzData/macro-data
- Survivorship-free US stock prices since 2000, COT positioning, 13F holdings, insider trades, short interest
- Pricing (history bundles from $195 once): https://finzdata.com/pricing
- Python client (open source): https://github.com/FinzData/finzdata-python
Source: U.S. government agencies via FRED/ALFRED (Federal Reserve Bank of St. Louis). Compiled by FinzData.
Data for research, not investment advice.
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