fredapi: Python API for FRED (Federal Reserve Economic Data)
fredapi
is a Python API for the
FRED <http://research.stlouisfed.org/fred2/>
__ data provided by the
Federal Reserve Bank of St. Louis. fredapi
provides a wrapper in
python to the FRED web service <http://api.stlouisfed.org/docs/fred/>
, and also provides
several conveninent methods for parsing and analyzing point-in-time data
(i.e. historic data revisions) from
ALFRED <http://research.stlouisfed.org/tips/alfred/>
fredapi
makes use of pandas
and returns data to you in a
pandas
Series
or DataFrame
Installation
.. code:: sh
pip install fredapi
Basic Usage
First you need an API key, you can apply for one <http://api.stlouisfed.org/api_key.html>
__ 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
.. code:: python
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 <http://research.stlouisfed.org/tips/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:
.. code:: xml
<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)
.. code:: python
data = fred.get_series_first_release('GDP')
Get latest data
~~~~~~~~~~~~~~~
Note that this is the same as simply calling ``get_series()``
.. code:: python
data = fred.get_series_latest_release('GDP')
Get latest data known on a given date
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. code:: python
fred.get_series_as_of_date('GDP', '6/1/2014')
Get all data release dates
~~~~~~~~~~~~~~~~~~~~~~~~~~
This returns a ``DataFrame`` with all the data from ALFRED
.. code:: python
df = fred.get_series_all_releases('GDP')
df.tail()
Get all vintage dates
~~~~~~~~~~~~~~~~~~~~~
.. code:: python
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.
.. code:: python
fred.search('potential gdp')
You can also search by release id and category id with various options
.. code:: python
df1 = fred.search_by_release(11)
df2 = fred.search_by_category(101, limit=10, order_by='popularity', sort_order='desc')
Dependencies
------------
- `pandas <http://pandas.pydata.org/>`__
More Examples
-------------
- I have a `blog post with more examples <http://mortada.net/python-api-for-fred.html>`__ written in an `IPython` notebook