Processing Financial Data with FRED API: Difference between revisions
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Search for a dataset using full text search. The result is a [[Pandas_DataFrames|DataFrame]]. | |||
<syntaxhighlight lang='py'> | <syntaxhighlight lang='py'> | ||
df = fred.search("S&P", limit=1000, order_by=None, sort_order=None, filter=None) | |||
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fred.search("text", limit=1000, order_by=None, sort_order=None, filter=None) | fred.search("text", limit=1000, order_by=None, sort_order=None, filter=None) | ||
</syntaxhighlight> | </syntaxhighlight> |
Revision as of 19:36, 8 October 2023
Internal
Overview
This article describes the sequence of steps required to process financial data obtained from FRED API.
Procedure
Import the package and establish a connection to the FRED backend, providing the API Key obtained as described here.
from fredapi import Fred
fred = Fred(api_key='...')
Search for a dataset using full text search. The result is a DataFrame.
df = fred.search("S&P", limit=1000, order_by=None, sort_order=None, filter=None)
fred.search("text", limit=1000, order_by=None, sort_order=None, filter=None) </syntaxhighlight> Do a full text search for series in the FRED data set. Returns the results as a data frame.