FRED PCEPI — Daily CSV Download (PCE Inflation)
The Personal Consumption Expenditures (PCE) price index is the Federal Reserve’s officially stated target measure for inflation — the 2% goal refers to PCE, not CPI. PCE uses a broader consumption basket with dynamically updated weights. Monthly observations from FRED series PCEPI.
Dataset: US PCE Inflation (1959–2026) · Updated —
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Source: FRED series PCEPI · 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 PCE Inflation (1959–2026) |
|---|---|
| Geography | United States |
| Frequency | Monthly |
| Period | 1959–2026 |
| Variables | date, pce_index, pce_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 |
pce_index | Float | pce_index value |
pce_yoy | Float | PCE price index 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 PCEPI:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=PCEPI
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/us-pce-inflation.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-pce-inflation.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["pce_yoy"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/us-pce-inflation.csv" df <- read_csv(url) head(df) summary(df$pce_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 PCEPI. 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