Microproduct data guidebeginner

FRED and ALFRED Economic Series

Normalized macroeconomic and regional time series with historical vintages for building release monitors, dashboards, and revision trackers.

Start the guide Open official source

At a glance

Difficulty
Beginner — comfortable for a first prototype
Size
Small · ≤0.1 GB
Formats
JSON, XML
Access
API
API key
Required
Provider
Federal Reserve Bank of St. Louis
Updates
Daily
Data terms
FRED API terms of use and series-specific source rights

From source to product signal

Test a product idea in four steps

FRED normalizes economic series from many publishers, while ALFRED exposes historical vintages. Start with two explicit series and their metadata. Units, frequency, seasonal adjustment, revisions, and reuse rights vary by upstream source and must travel with any comparison.

1

Check the setup

  • Python 3.10 or newer
  • A notebook environment such as Jupyter or Google Colab
  • A free FRED API key saved in the FRED_API_KEY environment variable
2

Access the data

  1. 1.Create a free FRED API key and save it in the FRED_API_KEY environment variable.
  2. 2.Open each series page and record its source, units, frequency, adjustment, and notes.
  3. 3.Request a bounded observation window and retain the retrieval and real-time dates.
Open official source
3

Run the Python example

Install the packages, then run the notebook cell.

python -m pip install pandas requests

import os
import pandas as pd
import requests

def observations(series_id):
    response = requests.get(
        "https://api.stlouisfed.org/fred/series/observations",
        params={
            "api_key": os.environ["FRED_API_KEY"],
            "file_type": "json",
            "series_id": series_id,
            "observation_start": "2024-01-01",
        },
        timeout=30,
    )
    response.raise_for_status()
    return pd.DataFrame(response.json()["observations"])

unemployment = observations("UNRATE")
inflation = observations("CPIAUCSL")
print(unemployment[["date", "value", "realtime_start"]].tail(12))
print(inflation[["date", "value", "realtime_start"]].tail(12))
4

Test a useful signal

Build a two-series economic release monitor

Track recent unemployment and consumer-price observations with their metadata and vintage dates.

  1. 01Record each series source, units, frequency, seasonal adjustment, and permitted use.
  2. 02Retrieve matched recent windows and flag newly released or revised observations.
  3. 03Explain why different units, release schedules, transformations, and vintages prevent naive comparison.

Dataset details

Federal Reserve Bank of St. Louis is a government source. Last verified 2026-08-13. Temporal coverage: varies by series with historical vintages available through ALFRED.

Theme

Markets & Economics

Domains

MacroeconomicsRegional Economics

Data types

Time Series

Tasks

Economic MonitoringRevision AnalysisAlerting

Geography

Global

Formats

JSONXML

Provider

Federal Reserve Bank of St. Louis

Data terms

FRED API terms of use and series-specific source rights