Python API for Federal Reserve Economic Data (FRED) from St. Louis Fed
fredapi is a Python API for the FRED data provided by the Federal Reserve Bank of St. Louis. fredapi provides a wrapper in python to the FRED web service, and also provides several conveninent methods for parsing and analyzing point-in-time data (i.e. historic data revisions) from ALFRED
fredapi makes use of pandas and returns data to you in a pandas Series or DataFrame
pip install fredapi
First you need an API key, you can apply for one for free on the FRED website. Once you have your API key, you can set it in one of three ways:
- set it to the evironment variable FRED_API_KEY
- save it to a file and use the ‘api_key_file’ parameter
- pass it directly as the ‘api_key’ parameter
from fredapi import Fred fred = Fred(api_key='insert api key here') data = fred.get_series('SP500')
Working with data revisions
Many economic data series contain frequent revisions. fredapi provides several convenient methods for handling data revisions and answering the quesion of what-data-was-known-when.
In ALFRED there is the concept of a vintage date. Basically every observation can have three dates associated with it: date, realtime_start and realtime_end.
- date: the date the value is for
- realtime_start: the first date the value is valid
- realitime_end: the last date the value is valid
For instance, there has been three observations (data points) for the GDP of 2014 Q1:
<observation realtime_start="2014-04-30" realtime_end="2014-05-28" date="2014-01-01" value="17149.6"/> <observation realtime_start="2014-05-29" realtime_end="2014-06-24" date="2014-01-01" value="17101.3"/> <observation realtime_start="2014-06-25" realtime_end="2014-07-29" date="2014-01-01" value="17016.0"/>
This means the GDP value for Q1 2014 has been released three times. First release was on 4/30/2014 for a value of 17149.6, and then there have been two revisions on 5/29/2014 and 6/25/2014 for revised values of 17101.3 and 17016.0, respectively.
Get first data release only (i.e. ignore revisions)
data = fred.get_series_first_release('GDP')
Get latest data
Note that this is the same as simply calling get_series()
data = fred.get_series_latest_release('GDP')
Get latest data known on a given date
Get all data release dates
This returns a DataFrame with all the data from ALFRED
df = fred.get_series_all_releases('GDP') df.tail()
Get all vintage dates
vintage_dates = fred.get_series_vintage_dates('GDP')
Search for data series
You can always search for data series on the FRED website. But sometimes it can be more convenient to search programmatically. fredapi provides a search() method that does a fulltext search and returns a DataFrame of results.
You can also search by release id and category id with various options
df1 = fred.search_by_release(11) df2 = fred.search_by_category(101, limit=10, order_by='popularity', sort_order='desc')
- I have a blog post with more examples written in an IPython notebook
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