US Core CPI Inflation — Monthly Dataset (1957–2026)
Core CPI strips out volatile food and energy prices to reveal the underlying inflation trend — the measure the Federal Reserve watches most closely for policy decisions. Why core measures matter — and how they relate to other deflators — is detailed in the complete guide to inflation. Monthly observations of FRED series CPILFESL and year-over-year change since 1957.
Dataset: US Core CPI Inflation (1957–2026) · Updated 2026-03-01
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Source: FRED series CPILFESL · Federal Reserve Bank of St. Louis
Macro Takeaway
This indicator is a key component of the macro-financial monitoring framework. Its current level relative to its historical distribution — captured in the percentile and z-score above — provides immediate context for whether conditions are historically normal, stretched, or compressed.
Cross-referencing with the 10-year Treasury yield and the yield curve spread helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | US Core CPI Inflation (1957–2026) |
|---|---|
| Geography | United States |
| Frequency | Monthly |
| Period | 1957–2026 |
| Variables | date, core_cpi_index, core_cpi_yoy |
| Format | CSV, Excel (XLSX) |
| Sources | Federal Reserve Bank of St. Louis — FRED |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation date |
core_cpi_index | Float | core_cpi_index value |
core_cpi_yoy | Float | Core CPI year-over-year change, percent |
Column names match the CSV headers exactly.
Download the Complete Dataset
The full dataset is available in CSV and Excel formats.
FRED Direct CSV Access
The underlying data is available from FRED under series code CPILFESL:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=CPILFESL
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/us-core-cpi.csv
This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.
Using the Dataset in Python
import pandas as pd url = "https://eco3min.fr/dataset/us-core-cpi.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["core_cpi_yoy"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/us-core-cpi.csv" df <- read_csv(url) head(df) summary(df$core_cpi_yoy)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
The primary data source is the Federal Reserve’s FRED database, series CPILFESL. The data is published by the relevant US government agency and made available through FRED with consistent formatting and metadata.
This dataset is updated monthly (15th of each month, 08:00 UTC) via automated pull from the FRED API.
Historical Regimes
Historical regime analysis for this dataset will be added in a future update. The key stats block above provides immediate context for the current reading relative to the full historical distribution.
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Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
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Sources
- Federal Reserve Bank of St. Louis — FRED database
Dataset Reference
Last updated — 12 May 2026
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