US Inflation
The US inflation picture in one clean Parquet - the official price indices desks and the Fed actually watch, not scraped retail prices. Headline CPI, core CPI (ex food & energy), the food and energy CPI components, the Fed's preferred PCE and core PCE deflators, and producer prices (PPI all-commodities + final demand) - monthly, aligned on date, back to 1990. Public domain at origin (BLS + BEA); FRED is just the retrieval pipe, so resale stays clean.
- Source
- FRED
- Licence
- Redistributable open data
- Updates
- Monthly
- Data through
- 2026-06-01
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- 8 official measures - CPI, core CPI, food CPI, energy CPI, PCE, core PCE, PPI (commodities + final demand)
- Monthly, aligned on date, back to 1990; ready to join to rates/liquidity
- Public domain at origin (BLS + BEA) - attribute the agency, not FRED
- The indices behind every Fed decision and inflation headline
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | Always US | 100.0% | 1 |
| ts | timestamp (UTC) | Observation month | 100.0% | 438 |
| measure | str | CPI / Core CPI / PCE / Core PCE / PPI | 100.0% | 8 |
| value | float | Index value | 100.0% | 1,788 |
| unit | str | Index base | 100.0% | 4 |
| res_min | int | Native resolution (monthly) | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: FRED (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("us-inflation_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 1 zones
US
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