fred-economic-data

To retrieve macroeconomic time series from the FRED API, you can query over 800,000 global economic indicators directly. This approach provides a programmatic interface to fetch, clean, and transform data like GDP or unemployment rates for analysis.

Yes, you can apply built-in transformations like percent change, log, or frequency aggregation directly in your API request. This allows you to format macroeconomic time series data immediately without needing extensive post-processing.

Yes, the FRED data skill works with pandas. It uses the requests library to handle API communication and data parsing, returning structured data that integrates seamlessly with pandas for time-series analysis and manipulation.

The best way to access historical vintage data and regional geographic datasets is by querying the Federal Reserve Economic Data API directly. This programmatic interface supports the discovery of specific economic indicators and historical vintage observations.

Yes, you need the requests library to handle API communication and data parsing. It is a required dependency for querying the Federal Reserve Economic Data API and retrieving macroeconomic time series observations programmatically.