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fred-economic-data

Query FRED macroeconomic indicators and metadata via a Python client.

48|6|Updated Mar 9, 2026
Search Tags:#api#time-series#data-transformation#fred#economic-data#geofred#regional-data
One-click install
npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill fred-economic-data-qinyan-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fred-economic-data
Source: https://github.com/qinyan-ai/qinyan-academic-skills/tree/main/skills/15-%E9%87%91%E8%9E%8D%E4%B8%8E%E7%BB%8F%E6%B5%8E%E6%95%B0%E6%8D%AE/fred-economic-data
Command: npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill fred-economic-data-qinyan-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

FRED data access often requires manual API calls and parsing to fetch time series data and metadata. This Skill provides a unified Python client to query FRED endpoints and work with macroeconomic indicators efficiently.

Core Features & Use Cases

  • Series metadata retrieval: Fetch series info such as title, frequency, units, and date range.
  • Observations access: Retrieve time-series observations with transformations (percentage change, rate, etc.).
  • Regional data (GeoFRED): Get state/county/msa data for mapping and analysis.
  • Use Case: A researcher can quickly assemble an economic dashboard by combining GDP, unemployment, and CPI data with regional breakdowns.

Quick Start

Query GDP data using the provided FREDQuery helper and print the most recent observation.

Frequently Asked Questions about fred-economic-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fetch FRED macroeconomic time-series data programmatically?▼

You can fetch FRED macroeconomic time-series data by using a Python client to query observations across core endpoints, retrieving indicators with metadata, caching, and retry logic for efficient access.

Can I retrieve regional economic data from GeoFRED for mapping and analysis?▼

Yes, you can retrieve regional economic data from GeoFRED by querying the client for state, county, and msa data, providing the geographic breakdowns needed for mapping and analysis.

What transformations are supported when querying FRED observations?▼

Querying FRED observations supports data transformations such as percentage change and rate calculations, allowing you to retrieve processed time-series data directly from the API endpoints.

Do I need a FRED API key to access macroeconomic indicators and series metadata?▼

Yes, accessing FRED macroeconomic indicators and series metadata requires a FRED API key, which the Python client handles internally alongside caching and retry logic for reliable queries.

How does the Python client handle FRED API rate limits and connection errors?▼

The Python client handles FRED API rate limits and connection errors by implementing internal caching and retry logic, ensuring stable data retrieval when querying multiple economic indicators.

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