Fredeco documentation!

Readme

Description

This python package allows its users to retrieve economic data provided by FRED® API. Although fredeco uses FRED® API, it is not endorsed or certified by the Federal Reserve Bank of St. Louis.

Features

• Retrieve a time series, when indicating the ID of the related indicator;

• Retrieve several time series, indicating their IDs;

• Search for all indicators related to the keywords indicated by the user;

• Find all indicators of a category of series, by indicating the ID of the category;

• Find the dates of all release of an indicator;

• Find the information related to an indicator, such as the notes where the source of data can be found.

Installation

$ pip install fredeco

Dependencies

• pandas

• numpy

• requests

• datetime

Usage

The usage of the package is explained in this section, whereas some examples are provided in the Examples section of the full documentation web page of the package. It is strongly recommanded to read that section.

• Each user of fredeco should have his own FRED® API key. To accomodate a new user of fredeco. One of the functions of the package, request_api_key() allows the user to open the webpage to request a FRED® API key.

• To retrieve data, the user of fredeco should indicate the ID of an indicator, such as GDP for the US Gross Domestic Product, and GDPCA for the US Real Gross Domestic Product. Data related to an economic indicator, with the function fred_series(), or several indicators, with the function fred_multi_series(), can be retreived. Remember that each user should have her/his own API key as explained previously.

• fredeco allows its users to retrieve information about an indicator, as illustrated in the section Examples. To retrieve information about an indicator, the function fred_info_series() should be used.

• Sometimes, a user may not know the ID of an indicator for which she/he whish to retrieve data. The user may indicate one or several keywords in the function fred_search() to search for indicators.

• fredeco allows its users to quickly explore key statistics and information related to data retrieved, as follows, where df is a data frame of one or several indicators retrieved from FRED® API. The explore() function does not require the user to add a FRED® API key. However, it cannot be used for data frame where the columns names are not FRED® indicators ID. Indeed, in addition to providing some statistics about the indicators, it also retrieves and provides information related to their unit of measurement and their title.

• The package fredeco has two modules: fredData, where one can find the functions to retrieve and explore FRED® indicators; fredSearch, where once can search for information related to data provided by FRED® API. The search index, in the documentation, can be used to see the description of each function.

License and terms of use

• fredeco is created by Raulin L. Cadet. It is licensed under the terms of the MIT license.

• By using the package fredeco, you are also agreeing to be bound by the FRED® API Terms of Use. The link to these Terms of Use is: Here.

Examples of usage

Import modules needed

In addition to the modules of fredeco, matplotlib is imported because it will be used to quickly plot data retrieved from FRED® API. My API key is not provided, for the illustrations below. It is saved in the object my_fred_key.

from fredeco.fredData import fred_series, fred_multi_series, explore
from fredeco.fredSearch import fred_list_series, fred_info_series, fred_search, fred_vintagedates
import matplotlib

Retrieve data

Below, data related to the US GDP are retrieved.

df_one=fred_series(series='GDP',fred_api=my_fred_key)
df_one.tail(5)

	GDP
Dates
2019-01-01	21380.976
2020-01-01	21060.474
2021-01-01	23315.081
2022-01-01	25462.722
2023-01-01	NaN

Below data related to several indicators are retrieved.

df_multi=fred_multi_series(series=['GDP','GDPCA'],fred_api=my_fred_key)
df_multi.tail(5)

	GDP	GDPCA
Dates
2019-01-01	21380.976	19036.052
2020-01-01	21060.474	18509.143
2021-01-01	23315.081	19609.812
2022-01-01	25462.722	20014.128
2023-01-01	NaN	NaN

Search for information

If a user want to look for indicators related to price index, fredeco allows to search for them as follows.

fred_search(text='price index',fred_api=my_fred_key)

	id	realtime_start	realtime_end	title	observation_start	observation_end	frequency	frequency_short	units	units_short	seasonal_adjustment	seasonal_adjustment_short	last_updated	popularity	group_popularity	notes
0	CPIAUCSL	2023-07-11	2023-07-11	Consumer Price Index for All Urban Consumers: ...	1947-01-01	2023-05-01	Monthly	M	Index 1982-1984=100	Index 1982-1984=100	Seasonally Adjusted	SA	2023-06-13 07:44:03-05	94	94	The Consumer Price Index for All Urban Consume...
1	CPIAUCNS	2023-07-11	2023-07-11	Consumer Price Index for All Urban Consumers: ...	1913-01-01	2023-05-01	Monthly	M	Index 1982-1984=100	Index 1982-1984=100	Not Seasonally Adjusted	NSA	2023-06-13 07:44:06-05	71	94	Handbook of Methods (https://www.bls.gov/opub/...
2	CSUSHPINSA	2023-07-11	2023-07-11	S&P/Case-Shiller U.S. National Home Price Index	1987-01-01	2023-04-01	Monthly	M	Index Jan 2000=100	Index Jan 2000=100	Not Seasonally Adjusted	NSA	2023-06-27 08:13:02-05	90	92	For more information regarding the index, plea...
3	CUUS0000SA0	2023-07-11	2023-07-11	Consumer Price Index for All Urban Consumers: ...	1984-01-01	2022-07-01	Semiannual	SA	Index 1982-1984=100	Index 1982-1984=100	Not Seasonally Adjusted	NSA	2023-01-12 07:38:17-06	43	94	NaN
4	CSUSHPISA	2023-07-11	2023-07-11	S&P/Case-Shiller U.S. National Home Price Index	1987-01-01	2023-04-01	Monthly	M	Index Jan 2000=100	Index Jan 2000=100	Seasonally Adjusted	SA	2023-06-27 08:13:03-05	80	92	For more information regarding the index, plea...
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
995	CUUS0000SAF113	2023-07-11	2023-07-11	Consumer Price Index for All Urban Consumers: ...	1984-01-01	2022-07-01	Semiannual	SA	Index 1982-1984=100	Index 1982-1984=100	Not Seasonally Adjusted	NSA	2023-01-12 07:37:52-06	1	27	NaN
996	CUUS0000SAF116	2023-07-11	2023-07-11	Consumer Price Index for All Urban Consumers: ...	1984-01-01	2022-07-01	Semiannual	SA	Index 1982-1984=100	Index 1982-1984=100	Not Seasonally Adjusted	NSA	2023-01-12 07:37:58-06	1	27	NaN
997	RTFPNAJPA632NRUG	2023-07-11	2023-07-11	Total Factor Productivity at Constant National...	1954-01-01	2019-01-01	Annual	A	Index 2017=1	Index 2017=1	Not Seasonally Adjusted	NSA	2023-02-27 14:32:04-06	26	26	Source ID: rtfpna\n\nWhen using these data in ...
998	CPALTT01CHM657N	2023-07-11	2023-07-11	Consumer Price Index: All Items: Total: Total ...	1960-01-01	2023-05-01	Monthly	M	Growth rate previous period	Growth rate previous period	Not Seasonally Adjusted	NSA	2023-06-23 12:37:05-05	17	26	OECD descriptor ID: CPALTT01\nOECD unit ID: GP...
999	CHECPIALLMINMEI	2023-07-11	2023-07-11	Consumer Price Index: All Items: Total: Total ...	1960-01-01	2023-05-01	Monthly	M	Index 2015=100	Index 2015=100	Not Seasonally Adjusted	NSA	2023-06-23 12:37:06-05	12	26	Copyright, 2016, OECD. Reprinted with permissi...

1000 rows × 16 columns

To request information about an economic indicator, such as GDPCA, the package fredeco can be used as follows:

fred_info_series(fred_api=my_fred_key,series='GDPCA')

{'realtime_start': '2023-07-11',
 'realtime_end': '2023-07-11',
 'seriess': [{'id': 'GDPCA',
   'realtime_start': '2023-07-11',
   'realtime_end': '2023-07-11',
   'title': 'Real Gross Domestic Product',
   'observation_start': '1929-01-01',
   'observation_end': '2022-01-01',
   'frequency': 'Annual',
   'frequency_short': 'A',
   'units': 'Billions of Chained 2012 Dollars',
   'units_short': 'Bil. of Chn. 2012 $',
   'seasonal_adjustment': 'Not Seasonally Adjusted',
   'seasonal_adjustment_short': 'NSA',
   'last_updated': '2023-03-30 07:54:04-05',
   'popularity': 52,
   'notes': 'BEA Account Code: A191RX\n\nA Guide to the National Income and Product Accounts of the United States (http://www.bea.gov/national/pdf/nipaguid.pdf) (NIPA)'}]}

These information are essential to know, to use for analysis. For example, the last information provided, the notes, indicate the source of data. The source should be provided, when using data retrieved from FRED® API.

To search for the list of economic indicators in a category, such as the category ID 125, one can proceed as follows.

df_list=fred_list_series(fred_api=my_fred_key,category_id=125)
df_list.head(5)

	id	realtime_start	realtime_end	title	observation_start	observation_end	frequency	frequency_short	units	units_short	seasonal_adjustment	seasonal_adjustment_short	last_updated	popularity	group_popularity	notes
0	AITGCBN	2023-07-11	2023-07-11	Advance U.S. International Trade in Goods: Bal...	2023-05-01	2023-05-01	Monthly	M	Millions of Dollars	Mil. of $	Not Seasonally Adjusted	NSA	2023-06-28 07:31:03-05	2	23	This advance estimate represents the current m...
1	AITGCBS	2023-07-11	2023-07-11	Advance U.S. International Trade in Goods: Bal...	2023-05-01	2023-05-01	Monthly	M	Millions of Dollars	Mil. of $	Seasonally Adjusted	SA	2023-06-28 07:31:01-05	23	23	This advance estimate represents the current m...
2	BOPBCA	2023-07-11	2023-07-11	Balance on Current Account (DISCONTINUED)	1960-01-01	2014-01-01	Quarterly	Q	Billions of Dollars	Bil. of $	Seasonally Adjusted	SA	2014-06-18 08:41:28-05	7	8	This series has been discontinued as a result ...
3	BOPBCAA	2023-07-11	2023-07-11	Balance on Current Account (DISCONTINUED)	1960-01-01	2013-01-01	Annual	A	Billions of Dollars	Bil. of $	Not Seasonally Adjusted	NSA	2014-06-18 08:41:28-05	2	8	This series has been discontinued as a result ...
4	BOPBCAN	2023-07-11	2023-07-11	Balance on Current Account (DISCONTINUED)	1960-01-01	2014-01-01	Quarterly	Q	Billions of Dollars	Bil. of $	Not Seasonally Adjusted	NSA	2014-06-18 08:41:28-05	1	8	This series has been discontinued as a result ...

The code below allows to retrieve a list of the dates of the releases of an indicator. The illustration below considers the indicator ID FEDFUNDS.

fred_vintagedates(fred_api=my_fred_key, series='FEDFUNDS')

['1996-12-03',
 '1997-01-07',
 '1997-02-04',
 '1997-03-04',
 '1997-04-08',
 '1997-05-06',
 '1997-06-03',
 '1997-07-08',
 '1997-08-05',
 '1997-09-02',
 '1997-10-07',
 '1997-11-04',
 '1997-12-02',
 '1997-12-10',
 '1998-01-06',
 '1998-02-03',
 '1998-03-03',
 '1998-04-07',
 '1998-05-05',
 '1998-06-02',
 '1998-07-07',
 '1998-08-04',
 '1998-09-08',
 '1998-10-06',
 '1998-11-03',
 '1998-12-08',
 '1999-01-05',
 '1999-02-02',
 '1999-03-02',
 '1999-04-06',
 '1999-05-04',
 '1999-06-08',
 '1999-07-06',
 '1999-08-03',
 '1999-09-07',
 '1999-10-05',
 '1999-11-02',
 '1999-12-07',
 '2000-01-04',
 '2000-02-08',
 '2000-03-07',
 '2000-04-04',
 '2000-05-02',
 '2000-06-06',
 '2000-07-05',
 '2000-08-08',
 '2000-09-05',
 '2000-10-03',
 '2000-11-07',
 '2000-12-05',
 '2001-01-02',
 '2001-02-06',
 '2001-03-06',
 '2001-04-03',
 '2001-05-08',
 '2001-06-05',
 '2001-07-03',
 '2001-08-07',
 '2001-09-04',
 '2001-10-02',
 '2001-11-06',
 '2001-12-04',
 '2002-01-08',
 '2002-02-04',
 '2002-03-04',
 '2002-04-01',
 '2002-05-06',
 '2002-06-03',
 '2002-07-01',
 '2002-08-05',
 '2002-09-03',
 '2002-10-07',
 '2002-11-04',
 '2002-12-02',
 '2003-01-06',
 '2003-02-03',
 '2003-03-03',
 '2003-04-07',
 '2003-05-05',
 '2003-06-02',
 '2003-07-07',
 '2003-08-04',
 '2003-09-02',
 '2003-10-06',
 '2003-11-03',
 '2003-12-01',
 '2004-01-05',
 '2004-02-02',
 '2004-03-01',
 '2004-04-05',
 '2004-05-03',
 '2004-06-07',
 '2004-07-06',
 '2004-08-02',
 '2004-09-07',
 '2004-10-04',
 '2004-11-01',
 '2004-12-06',
 '2005-01-03',
 '2005-02-07',
 '2005-03-07',
 '2005-04-04',
 '2005-05-02',
 '2005-06-06',
 '2005-07-05',
 '2005-08-01',
 '2005-09-06',
 '2005-10-03',
 '2005-11-07',
 '2005-12-05',
 '2006-01-03',
 '2006-02-06',
 '2006-03-06',
 '2006-04-03',
 '2006-05-01',
 '2006-06-05',
 '2006-07-03',
 '2006-08-07',
 '2006-09-05',
 '2006-10-02',
 '2006-11-06',
 '2006-12-04',
 '2007-01-03',
 '2007-02-05',
 '2007-03-05',
 '2007-04-02',
 '2007-05-07',
 '2007-06-04',
 '2007-07-02',
 '2007-08-06',
 '2007-09-04',
 '2007-10-01',
 '2007-11-05',
 '2007-12-03',
 '2008-01-07',
 '2008-02-04',
 '2008-03-03',
 '2008-04-07',
 '2008-05-05',
 '2008-06-02',
 '2008-07-07',
 '2008-08-04',
 '2008-09-02',
 '2008-10-06',
 '2008-11-03',
 '2008-12-01',
 '2009-01-05',
 '2009-02-02',
 '2009-03-02',
 '2009-04-06',
 '2009-05-04',
 '2009-06-01',
 '2009-07-06',
 '2009-08-03',
 '2009-09-08',
 '2009-10-05',
 '2009-11-02',
 '2009-12-07',
 '2010-01-04',
 '2010-02-01',
 '2010-03-01',
 '2010-04-05',
 '2010-05-03',
 '2010-06-07',
 '2010-07-06',
 '2010-08-02',
 '2010-09-07',
 '2010-10-04',
 '2010-11-01',
 '2010-12-06',
 '2011-01-03',
 '2011-01-10',
 '2011-01-11',
 '2011-02-07',
 '2011-03-07',
 '2011-04-04',
 '2011-05-02',
 '2011-06-06',
 '2011-07-05',
 '2011-08-01',
 '2011-09-06',
 '2011-10-11',
 '2011-11-07',
 '2011-12-05',
 '2012-01-09',
 '2012-02-06',
 '2012-03-05',
 '2012-04-02',
 '2012-05-07',
 '2012-06-04',
 '2012-07-02',
 '2012-08-06',
 '2012-09-04',
 '2012-10-01',
 '2012-11-05',
 '2012-12-10',
 '2013-01-07',
 '2013-02-04',
 '2013-03-04',
 '2013-04-04',
 '2013-05-06',
 '2013-06-10',
 '2013-07-08',
 '2013-08-12',
 '2013-09-03',
 '2013-10-07',
 '2013-11-04',
 '2013-12-02',
 '2014-01-06',
 '2014-02-03',
 '2014-03-04',
 '2014-04-07',
 '2014-05-05',
 '2014-06-02',
 '2014-07-10',
 '2014-08-04',
 '2014-09-02',
 '2014-10-06',
 '2014-11-03',
 '2014-12-01',
 '2015-01-05',
 '2015-02-02',
 '2015-03-02',
 '2015-04-06',
 '2015-05-04',
 '2015-06-01',
 '2015-07-01',
 '2015-08-03',
 '2015-09-14',
 '2015-10-05',
 '2015-11-02',
 '2015-12-07',
 '2016-01-04',
 '2016-02-01',
 '2016-03-07',
 '2016-04-04',
 '2016-05-02',
 '2016-06-06',
 '2016-07-05',
 '2016-08-01',
 '2016-09-06',
 '2016-10-03',
 '2016-11-03',
 '2016-12-01',
 '2017-01-03',
 '2017-02-01',
 '2017-03-01',
 '2017-04-03',
 '2017-05-01',
 '2017-06-01',
 '2017-07-03',
 '2017-08-01',
 '2017-09-01',
 '2017-10-02',
 '2017-11-01',
 '2017-12-01',
 '2018-01-02',
 '2018-02-01',
 '2018-03-01',
 '2018-04-02',
 '2018-05-01',
 '2018-06-01',
 '2018-07-02',
 '2018-08-01',
 '2018-09-04',
 '2018-10-01',
 '2018-11-01',
 '2018-12-03',
 '2019-01-02',
 '2019-02-01',
 '2019-03-01',
 '2019-04-01',
 '2019-05-01',
 '2019-06-03',
 '2019-07-01',
 '2019-08-01',
 '2019-09-03',
 '2019-10-01',
 '2019-11-01',
 '2019-12-02',
 '2020-01-02',
 '2020-02-03',
 '2020-03-02',
 '2020-04-01',
 '2020-05-01',
 '2020-06-01',
 '2020-07-01',
 '2020-07-21',
 '2020-08-03',
 '2020-08-05',
 '2020-09-01',
 '2020-10-01',
 '2020-10-13',
 '2020-11-02',
 '2020-12-01',
 '2021-01-04',
 '2021-02-01',
 '2021-03-01',
 '2021-04-01',
 '2021-05-03',
 '2021-06-01',
 '2021-07-01',
 '2021-08-02',
 '2021-09-01',
 '2021-10-01',
 '2021-11-01',
 '2021-12-01',
 '2022-01-03',
 '2022-02-01',
 '2022-03-01',
 '2022-04-01',
 '2022-05-02',
 '2022-06-01',
 '2022-07-01',
 '2022-08-01',
 '2022-09-01',
 '2022-10-03',
 '2022-11-01',
 '2022-12-01',
 '2023-01-03',
 '2023-02-01',
 '2023-03-01',
 '2023-04-03',
 '2023-05-01',
 '2023-06-01',
 '2023-07-03']

Explore data

After retrieving data, one can use a fredeco function to get some statistics and other informations about them. This is possible for one or several indicators, as illustrated below. We use the df_one and df_multi, the objects where have been stored data retrieved previously.

explore(fred_api=my_fred_key,data=df_one)

	GDP
Units	Billions of Dollars
N	76
Mean	6873.642447
Median	4188.2975
Std	7055.960951
Min	249.616
Max	25462.722
CV	1.019748
25% quantile	795.633
50% quantile	4188.2975
75% quantile	11646.6365
skewness	0.916755
kurtosis	-0.34893

explore(fred_api=my_fred_key,data=df_multi)

	GDP	GDPCA
Units	Billions of Dollars	Billions of Chained 2012 Dollars
N	76	77
Mean	6873.642447	9018.846338
Median	4188.2975	7637.704
Std	7055.960951	5516.176475
Min	249.616	2036.204
Max	25462.722	20014.128
CV	1.019748	0.607643
25% quantile	795.633	4173.424
50% quantile	4188.2975	7637.704
75% quantile	11646.6365	13865.519
skewness	0.916755	0.449427
kurtosis	-0.34893	-1.146103

To explore data retrieved, one can quickly plot them, using the package matplotlib. That’s why it has been called with import matplotlib previously.

df_one.tail(20).plot()

<Axes: xlabel='Dates'>

df_multi.tail(20).plot()

<Axes: xlabel='Dates'>

fredeco

fredeco package

Submodules

fredeco.fredData module

fredeco.fredData.explore(fred_api, data)

Explore some key statistics of a data frame of indicators retreived from FRED®.

This function returns a data frame with some information related to each economic indicator of the data frame x. Most of the information provided are statistics calculated by the function for each one of the indicators. All columns names should be FRED® indicators IDs.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website.

• x (data frame) – a data frame of indicators retreived from FRED®. All columns names should be FRED® indicators IDs.

Example

from fredeco.fredData import explore

explore(fred_api=’4e5rty8wfr’,df)

fredeco.fredData.fred_multi_series(series, fred_api, frequency='a', starttime='1776-07-04', endtime='9999-12-31', transform='lin')

Retrieve data for several economic indicators from FRED® API.

This method return a data frame of several variables.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website.

• series (str) – A time series ID, such as GDP.

• frequency (str) – The frequency of data. The default value is ‘a’ for annual data; ‘q’ is for quarterly data; ‘m’ is for monthly data

• starttime (str) – The first date, as a string, of the time series data to retrieve. The default value is ‘1776-07-04’.

• endtime (str) – The last date, as a string, of the time series data to retrieve. The default value is ‘9999-12-31’.

• transform (str) –

Example

from fredeco.fredData import fred_multi_series

fred_multi_series(series=[‘GDP’,’GDPCA’],fred_api=’4e5rty8wfr’)

fredeco.fredData.fred_series(series, fred_api, frequency='a', starttime='1776-07-04', endtime='9999-12-31', transform='lin')

Retreive and economic indicator from FRED® API

Parameters:

• series (str) – A time series ID, such as GDP.

• fred_api (str) –

• website. (Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED) –

• frequency (str) – The frequency of data. The default value is ‘a’ for annual data; ‘q’ is for quarterly data; ‘m’ is for monthly data

• starttime (str) – The first date, as a string, of the time series data to retrieve. The default value is ‘1776-07-04’.

• endtime (str) – The last date, as a string, of the time series data to retrieve. The default value is ‘9999-12-31’.

• transform (str) –

Example

from fredeco.fredData import fred_series

fred_series(series=’GDP’,fred_api=’4e5rty8wfr’)

fredeco.fredData.units(data)

Unit of each series of data frame of FRED® data.

This function returns a list

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website.

• data (data frame) – a data frame of indicators retreived from FRED®. All columns names should be FRED® indicators IDs.

Example

from fredeco.fredData import units

units(fred_api=’4e5rty8wfr’,df)

fredeco.fredKey module

fredeco.fredKey.request_api_key()

Get a FRED® API Key, from FRED® website.

This function open the webpage where the user can request for a FRED® API Key. The API Key is necessary to use the current Python package

fredeco.fredSearch module

fredeco.fredSearch.fred_info_series(fred_api, series)

Find the information that describe an economic indicator.

This function returns a dictionnary of information that describe a series, such as its title, if it is seasonally adjusted or not, the date of last update, the unit used as measure, the notes where data source may be found etc.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website.

• series (str) – A time series ID.

Example

from fredeco.fredSearch import fred_info_series

fred_info_series(series=’GDP’,fred_api=fred_api)

fredeco.fredSearch.fred_list_series(fred_api, category_id=0)

Find the series of a category

This function returns a data frame with information related to all series for a specific category of data provided by FRED.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website.

• category_id (int) – The id for a category of series. The default value is 0, which is the root category.

Example

from fredeco.fredSearch import fred_list_series

fred_list_series(fred_api, category_id=125)

fredeco.fredSearch.fred_search(fred_api, text)

Search for series related to one or several keywords.

This function returns a data frame of variables related to the keywords indicated by the user. The data frame provide several information for the series provided, such as their id, title, frequency, units of measurement, some notes related to their respective source etc.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website. Your registered FRED API keys. You can request an API key: https://fredaccount.stlouisfed.org/apikeys

• str (text) – The keywords to look for among the variables available in FRED data.

Example

from fredeco.fredSearch import fred_info_series

fred_search(fred_api,text=’Price index’)

fredeco.fredSearch.fred_vintagedates(fred_api, series)

Historical dates of release of new or revised data

This function returns a list of historical dates of release of new or revised data for a specific series.

Parameters:

• fred_api (str) – Your registered FRED API keys. You can use the function fredKey.request_api_key() to request an API key on the FRED website. Your registered FRED API keys. You can request an API key: https://fredaccount.stlouisfed.org/apikeys

• series (str) – A time series ID.

Example

from fredeco.fredSearch import fred_vintagedates

fredSearch.fred_vintagedates(fred_api,series=’GDP’)

Module contents

Changelog

Release 2. fredeco 0.1.1 - Date: 2023-07-14

Added

• Added CHANGELOG.rst to the root of the package, and changelog.rst in docssource.

• Added the text of changelog in documentation.

• Added more information in the project metadata, via pyproject.toml.

Fixed

• Fixed some errors in documentation.

Release 1. fredeco 0.1.0 - Date: 2023-07-12

Added

• First release of fredeco.

Indices and tables

• Index

• Module Index

• Search Page