{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/7"},{"label":"WWW/HTTP","url":"https://skillfed.io/packages/category/internet-www-http/3"}],"enrichment":{"capability":"fredapi wraps the FRED web service to fetch U.S. Federal Reserve economic data and return it as pandas Series or DataFrames, with built-in support for handling data revisions and vintage dates.","skillfed_tags":["economic-data","time-series","federal-reserve"],"use_cases":["Fetch historical economic indicators like GDP, unemployment, or inflation for time-series analysis and forecasting.","Retrieve first-release vs. revised data to study how economic estimates change over time and impact trading or policy decisions.","Search the FRED catalog programmatically to find relevant economic series without leaving your Python notebook.","Build a data pipeline that pulls the latest economic data on a schedule and stores it for dashboard or reporting systems.","Analyze point-in-time data to understand what information was available at specific dates in the past."],"what_it_does":"fredapi is a Python wrapper around the Federal Reserve Economic Data (FRED) web service provided by the St. Louis Fed. It lets you fetch economic time series data\u2014like GDP, unemployment rates, or stock indices\u2014directly into pandas DataFrames or Series for analysis. The package also handles a key feature of economic data: revisions. Economic statistics are often released, then revised as more complete information becomes available, and fredapi provides methods to retrieve first releases, latest values, or data as it was known on a specific date.\n\nYou'll need a free API key from the FRED website to use it. Once set up, you can search for series by name, fetch data by series ID, and work with vintage dates to answer questions like 'what did we know about GDP on this date in the past?' The package depends only on pandas, so installation is lightweight.","worth_installing":"Yes, if you need to work with U.S. Federal Reserve economic data. The package is stable, has low install friction, and integrates cleanly with pandas. The main caveats: the license is unclear (verify before commercial use), the package is aging with no release in 831 days (though the repo is still active), and you must obtain a free FRED API key. For economic research, data journalism, or financial analysis, it's a solid choice."},"id":"fredapi","links":{"html":"https://skillfed.io/packages/fredapi","md":"https://skillfed.io/packages/fredapi.md","pypi":"https://pypi.org/project/fredapi/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-05-05","license_spdx":null,"license_treatment":"unclear","name":"fredapi","python_support":"unspecified","summary":"Python API for Federal Reserve Economic Data (FRED) from St. Louis Fed"},"popularity":{"monthly_downloads":1331765,"position":4043,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.5.2"}