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'>