series_id large_stringlengths 11 15 | date date32 | value float64 -4.4 9.2 |
|---|---|---|
PRS30006011 | 2026-01-01 | -0.8 |
PRS30006011 | 2026-04-01 | -0.3 |
PRS30006012 | 2026-01-01 | -0.6 |
PRS30006012 | 2026-04-01 | 0 |
PRS30006021 | 2026-01-01 | 0.5 |
PRS30006021 | 2026-04-01 | 0.8 |
PRS30006022 | 2026-01-01 | 0.6 |
PRS30006022 | 2026-04-01 | 2.8 |
PRS30006031 | 2026-01-01 | -0.3 |
PRS30006031 | 2026-04-01 | 0.5 |
PRS30006032 | 2026-01-01 | 0 |
PRS30006032 | 2026-04-01 | 2.9 |
PRS30006061 | 2026-01-01 | 4.7 |
PRS30006061 | 2026-04-01 | 5 |
PRS30006101 | 2026-01-01 | 5 |
PRS30006101 | 2026-04-01 | 4.5 |
PRS30006102 | 2026-01-01 | 5.5 |
PRS30006102 | 2026-04-01 | 2.1 |
PRS30006151 | 2026-01-01 | 2.3 |
PRS30006151 | 2026-04-01 | 0.7 |
PRS30006152 | 2026-01-01 | 1.9 |
PRS30006152 | 2026-04-01 | -3.7 |
PRS30006161 | 2026-01-01 | 1.8 |
PRS30006161 | 2026-04-01 | 1.9 |
PRS30006162 | 2026-01-01 | 2.8 |
PRS30006162 | 2026-04-01 | 5.3 |
PRS31006011 | 2026-01-01 | -0.5 |
PRS31006011 | 2026-04-01 | 0 |
PRS31006012 | 2026-01-01 | 0.2 |
PRS31006012 | 2026-04-01 | 1 |
PRS31006021 | 2026-01-01 | 0.4 |
PRS31006021 | 2026-04-01 | 1 |
PRS31006031 | 2026-01-01 | -0.1 |
PRS31006031 | 2026-04-01 | 1 |
PRS31006032 | 2026-01-01 | 0.3 |
PRS31006032 | 2026-04-01 | 5.1 |
PRS31006041 | 2026-01-01 | 2.5 |
PRS31006041 | 2026-04-01 | 3.6 |
PRS31006042 | 2026-01-01 | 5.2 |
PRS31006042 | 2026-04-01 | 8.9 |
PRS31006061 | 2026-01-01 | 6.3 |
PRS31006061 | 2026-04-01 | 6.7 |
PRS31006062 | 2026-01-01 | 7.9 |
PRS31006062 | 2026-04-01 | 6.5 |
PRS31006091 | 2026-01-01 | 2.7 |
PRS31006091 | 2026-04-01 | 2.5 |
PRS31006092 | 2026-01-01 | 4.9 |
PRS31006092 | 2026-04-01 | 3.6 |
PRS31006101 | 2026-01-01 | 6.4 |
PRS31006101 | 2026-04-01 | 5.6 |
PRS31006102 | 2026-01-01 | 7.6 |
PRS31006102 | 2026-04-01 | 1.4 |
PRS31006152 | 2026-01-01 | 3.9 |
PRS31006152 | 2026-04-01 | -4.4 |
PRS31006161 | 2026-01-01 | 3 |
PRS31006161 | 2026-04-01 | 3.5 |
PRS31006162 | 2026-01-01 | 5.1 |
PRS31006162 | 2026-04-01 | 7.8 |
PRS32006011 | 2026-01-01 | -1.3 |
PRS32006011 | 2026-04-01 | -1 |
PRS32006012 | 2026-01-01 | -1.8 |
PRS32006012 | 2026-04-01 | -1.5 |
PRS32006021 | 2026-01-01 | 0.7 |
PRS32006021 | 2026-04-01 | 0.5 |
PRS32006031 | 2026-01-01 | -0.6 |
PRS32006031 | 2026-04-01 | -0.4 |
PRS32006032 | 2026-01-01 | -0.5 |
PRS32006032 | 2026-04-01 | -0.6 |
PRS32006042 | 2026-01-01 | -1.2 |
PRS32006042 | 2026-04-01 | 1.4 |
PRS32006061 | 2026-01-01 | 1.7 |
PRS32006061 | 2026-04-01 | 1.7 |
PRS32006062 | 2026-01-01 | 0.9 |
PRS32006062 | 2026-04-01 | 2.2 |
PRS32006091 | 2026-01-01 | -0.2 |
PRS32006091 | 2026-04-01 | -0.2 |
PRS32006092 | 2026-01-01 | -0.6 |
PRS32006092 | 2026-04-01 | 2.1 |
PRS32006101 | 2026-01-01 | 2.3 |
PRS32006101 | 2026-04-01 | 2.2 |
PRS32006102 | 2026-01-01 | 1.5 |
PRS32006102 | 2026-04-01 | 2.9 |
PRS32006151 | 2026-01-01 | -0.4 |
PRS32006151 | 2026-04-01 | -1.6 |
PRS32006152 | 2026-01-01 | -2 |
PRS32006152 | 2026-04-01 | -3 |
PRS32006161 | 2026-01-01 | 0.5 |
PRS32006161 | 2026-04-01 | 0.3 |
PRS32006162 | 2026-01-01 | 0.6 |
PRS32006162 | 2026-04-01 | 3 |
PRS84006011 | 2026-01-01 | 0 |
PRS84006011 | 2026-04-01 | 0.2 |
PRS84006012 | 2026-01-01 | -0.4 |
PRS84006012 | 2026-04-01 | 0.6 |
PRS84006021 | 2026-01-01 | 0.4 |
PRS84006021 | 2026-04-01 | 0.2 |
PRS84006022 | 2026-01-01 | 1.3 |
PRS84006022 | 2026-04-01 | -0.2 |
PRS84006031 | 2026-01-01 | 0.4 |
PRS84006031 | 2026-04-01 | 0.4 |
US macro data: Productivity (137 series)
137 productivity series from US government sources, cleaned into one consistent format and ready for pandas. This free package holds the last 12 months (2025-10-26 on) of each series' latest values. It is refreshed weekly.
import pandas as pd
df = pd.read_parquet("hf://datasets/FinzData/macro-productivity/data/long.parquet") # series_id, date, value
wide = pd.read_parquet("hf://datasets/FinzData/macro-productivity/data/wide_quarterly.parquet") # one column per series
or datasets.load_dataset("FinzData/macro-productivity"). Wide tables by frequency: wide_quarterly (137 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:
import finzdata as fz # pip install finzdata
c = fz.Client() # free API key: https://api.finzdata.com/
c.macro("PRS85006152") # full history, latest values
c.macro("PRS85006152", vintage="first") # as first released
c.macro("PRS85006152", as_of="2020-03-01") # exactly what was known on that date
c.macro_series(category="productivity") # the catalogue for this category
Most-watched series in this package
| ID | Title | Units | Frequency | Full history from |
|---|---|---|---|---|
PRS85006152 |
Nonfarm Business Sector: Real Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
RPSGENAITSIND10 |
Generative Artificial Intelligence, Time Savings: Finance and Insurance | Percent | Quarterly | 2024 |
PRS85006101 |
Nonfarm Business Sector: Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 |
PRS85006151 |
Nonfarm Business Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 |
PRS84006032 |
Business Sector: Hours Worked for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS30006032 |
Manufacturing Sector: Hours Worked for All Workers | Percent Change at Annual Rate | Quarterly | 1987 |
PRS84006092 |
Business Sector: Labor Productivity (Output per Hour) for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS85006102 |
Nonfarm Business Sector: Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS30006151 |
Manufacturing Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 |
PRS84006162 |
Business Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS85006161 |
Nonfarm Business Sector: Output per Worker for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 |
RPSGENAITSIND4 |
Generative Artificial Intelligence, Time Savings: Manufacturing | Percent | Quarterly | 2024 |
RPSGENAITSIND9 |
Generative Artificial Intelligence, Time Savings: Information | Percent | Quarterly | 2024 |
RPSGENAITSOCC3 |
Generative Artificial Intelligence, Time Savings: Computer and Mathematical Occupations | Percent | Quarterly | 2024 |
PRS30006011 |
Manufacturing Sector: Employment for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 |
PRS30006021 |
Manufacturing Sector: Average Weekly Hours for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 |
PRS31006011 |
Manufacturing, Durable Goods Sector: Employment for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 |
PRS85006162 |
Nonfarm Business Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS88003091 |
Nonfinancial Corporations Sector: Labor Productivity (Output per Hour) for Employees | Percent Change from Quarter One Year Ago | Quarterly | 1948 |
RPSGENAITSIND12 |
Generative Artificial Intelligence, Time Savings: Professional, Scientific, and Technical Services | Percent | Quarterly | 2024 |
PRS30006161 |
Manufacturing Sector: Output per Worker for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1988 |
PRS30006162 |
Manufacturing Sector: Output per Worker for All Workers | Percent Change at Annual Rate | Quarterly | 1987 |
PRS84006102 |
Business Sector: Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
PRS84006151 |
Business Sector: Real Hourly Compensation for All Workers | Percent Change from Quarter One Year Ago | Quarterly | 1948 |
PRS84006152 |
Business Sector: Real Hourly Compensation for All Workers | Percent Change at Annual Rate | Quarterly | 1947 |
All 137 series: series.csv. Browse them at https://finzdata.com/macro/category/productivity.
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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