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Quickstart Guide

If you're new to the Federal Reserve Economic Data (FRED) API, or if you're new to using our client, this guide should provide you with all you need to know to start requesting economic data.

Installation

Install via pip:

pip install FRB

Git clone from the command line:

git clone http://github.com/avelkoski/FRB.git

Download directly from Github.

FRED API Key

Visit the Federal Reserve Bank of St. Louis to obtain your personalized API Key.

Configuration

Default parameters can be set within fred/config.py or optionally when you instantiate Fred(). These include api_key and response_type. In order to request data from FRED, you must configure the client with your api_key.

Note

Economic data are revised from time-to-time. A real-time period marks when information was known to be true. In FRED, the real-time period defaults to the current date (e.g. the parameters realtime_start and realtime_end, which define the real-time period, are set to today's date). Data are interpreted as facts known to be true as of today (most recent figure or revision). The real-time period can be set as an optional parameter in most functions. See our discussion :ref:`FRED vs. ALFRED <fva-label>` for additional details.

Usage

Instantiate FRED with your API key and preferred response format:

from fred import Fred
fr = Fred(api_key='abcdefghijklmnopqrstuvwxyz123456',response_type='df')

If you do not include response_type, the default response is xml. Available response types include xml, json, dict, df, numpy, csv, tab, and pipe.

Categories

Economic data categories represent classes of data series that are regarded as having similar characteristics. Categories are often made up of subcategories along with economic data series.

Details

To request category details, provide a category ID to the details method of the category client:

res = fr.category.details(1)
print res

The response includes the category ID, name, and parent category ID associated with the requested category. The parent category ID is 0 if the category has no parents.

id name parent_id
1 Production & Business Activity 0

Children

Get the child categories for a specified parent category.

res = fr.category.children(1)
print res

The response includes the category ID, name, and parent category ID associated with a given child category. The parent category ID is 1 because we requested its children.

id name parent_id
32262 Business Cycle Expansions & Contractions 1
32436 Construction 1
33490 Finance Companies 1
32216 Health Insurance 1
97 Housing 1
3 Industrial Production & Capacity Utilization 1
32295 Institute for Supply Management Report on Busi... 1
32429 Manufacturing 1
6 Retail Trade 1
33441 Services 1
33492 Technology 1
33202 Transportation 1
33203 Wholesale Trade 1

Related

To request categories related to a given category, provide the category ID to the related method of the category client:

res = fr.category.related(32073)
print res

The response includes the category ID, name, and parent category ID associated with a given related category.

id name parent_id
149 Arkansas 27281
150 Illinois 27281
151 Indiana 27281
152 Kentucky 27281
153 Mississippi 27281
154 Missouri 27281
193 Tennessee 27281

Series

Get economic data series associated with a category. In this request, we add optional parameters to help refine our response. We limit the number of records to 5, request series with the tags trade and goods, order the response by popularity (descending):

params = {
         'limit':5,
         'tag_names':'trade;goods',
         'order_by':'popularity',
         'sort_order':'desc'
         }

res = fr.category.series(125,params=params)
print res

The response includes the series frequency, observation period, and popularity, among other descriptive features.

frequency frequency_short id last_updated observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Monthly M BOPGSTB Timestamp('2016-01-07 16:46:02') Timestamp('2015-11-01 00:00:00') Timestamp('1992-01-01 00:00:00') 61 Timestamp('2016-01-09 00:00:00') Timestamp('2016-01-09 00:00:00') Seasonally Adjusted SA Trade Balance: Goods, and Services Balance of Payments Basis Millions of Dollars Mil. of $
Monthly M BOPGTB Timestamp('2016-01-07 16:46:02') Timestamp('2015-11-01 00:00:00') Timestamp('1992-01-01 00:00:00') 42 Timestamp('2016-01-09 00:00:00') Timestamp('2016-01-09 00:00:00') Seasonally Adjusted SA Trade Balance: Goods, Balance of Payments Basis Millions of Dollars Mil. of $

Tags

Get the FRED tags associated with a category.

params = {
         'limit':10
         }

res = fr.category.tags(125,params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given category tag.

created group_id name notes popularity series_count
2012-02-27 16:18:19 src bea US. Bureau of Economic Analysis 86 45
2012-02-27 16:18:19 geot nation Country Level 100 45
2012-02-27 16:18:19 geo usa United States of America 100 45
2012-02-27 16:18:19 gen balance   63 39
2012-02-27 16:18:19 seas nsa Not seasonally adjusted 97 28
2012-02-27 16:18:19 freq quarterly   88 28
2012-02-27 16:18:19 gen discontinued   69 21
2012-02-27 16:18:19 seas sa Seasonally adjusted 93 17
2012-02-27 16:18:19 freq annual   84 14
2012-02-27 16:18:19 gen services   71 14

Related tags

Get the related FRED tags for one or more FRED tags within a category.

params = {
         'tag_group_id':'gen',
         'limit':10,
         'exclude_tag_names':'services',
         'sort_order':'asc'
         }

res = fr.category.related_tags(125,tag_names='bea',params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given category tag.

created group_id name notes popularity series_count
2012-02-27 16:18:19 gen investment   66 3
2013-11-13 22:08:31 gen merchandise   33 3
2012-02-27 16:18:19 gen primary   54 3
2012-02-27 16:18:19 gen secondary   29 3
2012-02-27 16:18:19 gen transfers   48 3
2012-02-27 16:18:19 gen goods   71 4
2012-02-27 16:18:19 gen trade   59 4
2012-02-27 16:18:19 gen capital account   47 6
2012-02-27 16:18:19 gen current account   57 6
2012-02-27 16:18:19 gen net   67 6

Releases

A release is a distribution of an economic data series. Releases are often maintained by different parties, including the Federal Reserve Bank, Bureau of Labor Statistics, Bureau of Economic Analysis, and Census Bureau.

All releases

Get all releases of economic data.

params = {
         'limit':5,
         }

res = fr.release.all_releases(params=params)
print res

The response includes the release ID, name, and link (among other items) associated with the requested release.

id link name press_release realtime_end realtime_start
9 http://www.census.gov/retail/ Advance Monthly Sales for Retail and Food Serv... True 2016-01-09 2016-01-09
10 http://www.bls.gov/cpi/ Consumer Price Index True 2016-01-09 2016-01-09
11 http://www.bls.gov/ncs/ect/ Employment Cost Index True 2016-01-09 2016-01-09
13 http://www.federalreserve.gov/releases/g17/ G.17 Industrial Production and Capacity Utiliz... True 2016-01-09 2016-01-09
14 http://www.federalreserve.gov/releases/g19/ G.19 Consumer Credit True 2016-01-09 2016-01-09

All dates

Get release dates for all releases of economic data.

params = {
         'limit':5,
         }

res = fr.release.all_dates(params=params)
print res

The response includes the date, release ID, name of the release:

date release_id release_name
2016-01-08 302 Cleveland Financial Stress Index
2016-01-08 86 Commercial Paper
2016-01-08 72 Daily Treasury Inflation-Indexed Securities
2016-01-08 279 Economic Policy Uncertainty
2016-01-08 50 Employment Situation

Details

To request release details, provide a release ID to the details method of the release client:

res = fr.release.details(51)
print res

The response includes the release ID, name, and link (among other items) associated with the requested release.

id link name press_release realtime_end realtime_start
51 http://www.bea.gov/newsreleases/international/... U.S. International Trade in Goods and Services True 2016-01-09 2016-01-09

Dates

Get release dates for a release of economic data:

params = {
         'limit':5,
         }

res = fr.release.dates(51,params=params)
print res

The response includes the date of the release and the realease_id.

date release_id
1997-01-17 51
1997-02-19 51
1997-03-20 51
1997-04-17 51
1997-04-25 51

Series

Get the series on a release of economic data:

params = {
         'limit':2,
         }

res = fr.release.series(51,params=params)
print res

The response includes the series frequency, observation period, and popularity, among other descriptive features.

frequency frequency_short id last_updated notes observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Monthly M BOMTVLM133S Timestamp('2016-01-07 16:46:01') NaN Timestamp('2015-11-01 00:00:00') Timestamp('1992-01-01 00:00:00') 0 Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00') Seasonally Adjusted SA U.S. Imports of Services - Travel Million of Dollars Mil. of $
Monthly M BOMVGMM133S Timestamp('2014-10-20 14:27:37') BEA has introduced new table presentations, including a new presentation of services, as part of a comprehensive restructuring of BEAu2019s international economic accounts.For more information see http://www.bea.gov/international/revision-2014.htm. Timestamp('2013-12-01 00:00:00') Timestamp('1992-01-01 00:00:00') 7 Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00') Seasonally Adjusted SA U.S. Imports of Services: U.S. Government Miscellaneous Services (DISCONTINUED) Millions of Dollars Mil. of $

Tags

Get the FRED tags associated with a release.

params = {
         'limit':10
         }

res = fr.release.tags(51,params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given release tag.

created group_id name notes popularity series_count
2012-02-27 16:18:19 src bea US. Bureau of Economic Analysis 86 57
2012-02-27 16:18:19 src census US. Bureau of the Census 79 57
2012-02-27 16:18:19 freq monthly   94 57
2012-02-27 16:18:19 geot nation Country Level 100 57
2012-02-27 16:18:19 geo usa United States of America 100 57
2012-02-27 16:18:19 seas sa Seasonally adjusted 93 41
2012-02-27 16:18:19 gen services   71 38
2012-02-27 16:18:19 gen exports   63 27
2012-02-27 16:18:19 gen imports   61 27
2012-02-27 16:18:19 gen goods   71 24

Related tags

Get the related FRED tags for one or more FRED tags within a release.

params = {
         'tag_group_id':'gen',
         'limit':10,
         'exclude_tag_names':'services',
         'sort_order':'asc'
         }

res = fr.release.related_tags(51,tag_names='bea',params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given release tag.

created group_id name notes popularity series_count
2012-02-27 16:18:19 gen balance   63 1
2012-02-27 16:18:19 gen trade   59 1
2013-01-28 20:10:13 gen bop Balance of Payments 56 3
2012-02-27 16:18:19 gen exports   63 9
2012-02-27 16:18:19 gen imports   61 9
2012-02-27 16:18:19 gen goods   71 19

Series

Economic data series are quantitative measures used to describe various components of the economy. Series consist of data measured over a time interval.

Details

To request series details, provide a series ID to the details method of the series client:

res = fr.series.details('GNPCA')
print res

The response includes the series frequency, observation period, and popularity, among other descriptive features.

frequency frequency_short id last_updated notes observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Annual A GNPCA Timestamp('2015-07-30 14:03:15') BEA Account Code: A001RX1 Timestamp('2014-01-01 00:00:00') Timestamp('1929-01-01 00:00:00') 28 Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00') Not Seasonally Adjusted NSA Real Gross National Product Billions of Chained 2009 Dollars Bil. of Chn. 2009 $

Categories

Get the categories for an economic data series:

res = fr.series.categories('GNPCA')
print res

The response includes category ID, name, and parent ID:

id name parent_id
106 GDP/GNP 18

Release

Get the release for an economic data series:

res = fr.series.release('GNPCA')
print res

The response includes the release ID, name, and a link to the release:

id link name press_release realtime_end realtime_start
53 http://www.bea.gov/national/index.htm Gross Domestic Product True Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00')

Observations

Get the observations or data values for an economic data series:

params = {
         'limit':5,
         'output_type':1
         }

res = fr.series.observations('GNPCA',params=params)
print res

The response includes the date, real-time period, and value of the observation:

date realtime_end realtime_start value
1929-01-01 2016-01-10 2016-01-10 1066.8
1930-01-01 2016-01-10 2016-01-10 976.3
1931-01-01 2016-01-10 2016-01-10 912.9
1932-01-01 2016-01-10 2016-01-10 794.8
1933-01-01 2016-01-10 2016-01-10 784.0

Tags

Get the tags for an economic data series:

res = fr.series.tags('GNPCA')
print res

The response includes the tag group_id, name, and series_count associated with a given series search.

created group_id name notes popularity series_count
2012-02-27 16:18:19 seas nsa Not seasonally adjusted 97 326950
2012-02-27 16:18:19 geo usa United States of America 100 248427
2012-02-27 16:18:19 freq annual   84 222080
2012-02-27 16:18:19 geot nation Country Level 100 163584
2012-02-27 16:18:19 src bea US. Bureau of Economic Analysis 86 22902
2012-08-16 20:21:17 rls nipa National Income and Product Accounts 83 11765
2012-02-27 16:18:19 gen real Inflation Adjusted Data 82 9282
2012-02-27 16:18:19 gen gnp Gross National Product 57 437

Updates

Get economic data series sorted by when observations were updated on the FRED server:

params = {
         'limit':2,
         }

res = fr.series.updates('GNPCA',params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given series search.

frequency frequency_short id last_updated notes observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Daily D RUTOP200TR 2016-01-09 01:56:42

The Russell Top 200® Index measures the performance of the largest cap segment of the U.S. equity universe. The Russell Top 200® Index is a subset of the Russell 3000® Index. It includes approximately 200 of the largest securities based on a combination of their market cap and current index membership and represents approximately 68% of the U.S. market. The Russell Top 200® Index is constructed to provide a comprehensive and unbiased barometer for this very large cap segment and is completely reconstituted annually to ensure new and growing equities are reflected.

This series is a total market index, which assumes that all cash distributions are reinvested, in addition to tracking the price movements.

For more information, go to the source at: http://www.russell.com/indexes/americas/indexes/default.page?

2016-01-08 00:00:00 1978-12-31 00:00:00 23 2016-01-10 00:00:00 2016-01-10 00:00:00 Not Seasonally Adjusted NSA Russell Top 200® Total Market Index Index Index
Daily D RUTOP200PR 2016-01-09 01:56:41

The Russell Top 200® Index measures the performance of the largest cap segment of the U.S. equity universe. The Russell Top 200® Index is a subset of the Russell 3000® Index. It includes approximately 200 of the largest securities based on a combination of their market cap and current index membership and represents approximately 68% of the U.S. market. The Russell Top 200® Index is constructed to provide a comprehensive and unbiased barometer for this very large cap segment and is completely reconstituted annually to ensure new and growing equities are reflected.

For more information, go to the source at: http://www.russell.com/indexes/americas/indexes/default.page?
2016-01-08 00:00:00 1978-12-31 00:00:00 16 2016-01-10 00:00:00 2016-01-10 00:00:00 Not Seasonally Adjusted NSA Russell Top 200® Price Index Index Index

Vintage dates

Get the dates in history when a series' data values were revised or new data values were released:

params = {
         'limit':10,
         'sort_order':'desc'
         }

res = fr.series.vintage_dates('GNPCA',params=params)
print res

The response includes vintage_dates:

0
2015-07-30
2015-03-27
2014-07-30
2014-03-27
2013-07-31
2013-03-28
2012-07-27
2012-03-29
2011-07-29
2011-03-25

Search

Get economic data series that match keywords:

params = {
         'limit':2,
         }

res = fr.series.search('money service index',params=params)
print res

The response includes the series frequency, observation period, and popularity, among other descriptive features.

frequency frequency_short id last_updated notes observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Monthly M MSIM1P Timestamp('2014-01-17 13:16:45') The MSI measure the flow of monetary services received each period by households and firms from their holdings of monetary assets (levels of the indexes are sometimes referred to as Divisia monetary aggregates). Timestamp('2013-12-01 00:00:00') Timestamp('1967-01-01 00:00:00') 30 Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00') Seasonally Adjusted SA Monetary Services Index: M1 (preferred) Billions of Dollars Bil. of $
Monthly M MSIMZMP Timestamp('2014-01-17 13:16:42') The MSI measure the flow of monetary services received each period by households and firms from their holdings of monetary assets (levels of the indexes are sometimes referred to as Divisia monetary aggregates).rnPreferred benchmark rate equals 100 basis points plus the largest rate in the set of rates. rnAlternative benchmark rate equals the larger of the preferred benchmark rate and the Baa corporate bond yield. Timestamp('2013-12-01 00:00:00') Timestamp('1967-01-01 00:00:00') 24 Timestamp('2016-01-10 00:00:00') Timestamp('2016-01-10 00:00:00') Seasonally Adjusted SA Monetary Services Index: MZM (preferred) Billions of Dollars Bil. of $

Search tags

Get the tags for a series search:

params = {
         'limit':5
         }

res = fr.series.search_tags('money service index',params=params)
print res

The response includes the tag group_id, name, and series_count associated with a given series search.

created group_id name notes popularity series_count
2012-08-29 15:22:19 gen academic data Time series data created mainly by academia to address growing demand in understanding specific concerns in the economy that are not well modeled by ordinary statistical agencies. 62 25
2013-06-21 15:22:49 src anderson & jones Richard Anderson and Barry Jones 35 25
2014-11-17 19:34:12 src anderson, richard g.   37 25
2012-02-27 16:18:19 gen divisia Monetary Services Indexes 35 25
2012-02-27 16:18:19 src frb stl Federal Reserve Bank of St. Louis (source) 83 25

Search releated tags

Get the related tags for a series search:

params = {
         'limit':5,
         'order_by':'popularity',
         'sort_order':'desc'
         }

res = fr.series.search_related_tags('mortgage rate','30-year;frb',params=params)

The response includes the tag group_id, name, and series_count associated with a given series search.

created group_id name notes popularity series_count
2012-02-27 16:18:19 geot nation Country Level 100 3
2012-02-27 16:18:19 geo usa United States of America 100 3
2012-02-27 16:18:19 seas nsa Not seasonally adjusted 97 3
2012-02-27 16:18:19 freq monthly   94 1
2012-05-29 15:14:19 gen interest rate   91 3

Sources

Economic data series derive from a variety of sources,including the Federal Reserve Bank, Bureau of Labor Statistics,Bureau of Economic Analysis, and Census Bureau.

All sources

Get all sources:

params = {
         'limit':10
         }

res = fr.source.sources(params=params)
print res

The response includes source ID, name, and link to the source:

id link name realtime_end realtime_start
1 http://www.federalreserve.gov/ Board of Governors of the Federal Reserve System (US) 2016-01-10 00:00:00 2016-01-10 00:00:00
3 http://www.philadelphiafed.org/ Federal Reserve Bank of Philadelphia 2016-01-10 00:00:00 2016-01-10 00:00:00
4 http://www.stlouisfed.org/ Federal Reserve Bank of St. Louis 2016-01-10 00:00:00 2016-01-10 00:00:00
6 http://www.ffiec.gov/ Federal Financial Institutions Examination Council (US) 2016-01-10 00:00:00 2016-01-10 00:00:00
11 http://www.dowjones.com Dow Jones & Company 2016-01-10 00:00:00 2016-01-10 00:00:00
13 http://www.ism.ws/ Institute for Supply Management 2016-01-10 00:00:00 2016-01-10 00:00:00
14 https://www.umich.edu/ University of Michigan 2016-01-10 00:00:00 2016-01-10 00:00:00
15 http://www.whitehouse.gov/cea/ Council of Economic Advisers (US) 2016-01-10 00:00:00 2016-01-10 00:00:00
16 http://www.whitehouse.gov/omb/ US. Office of Management and Budget 2016-01-10 00:00:00 2016-01-10 00:00:00
17 http://www.cbo.gov/ US. Congressional Budget Office 2016-01-10 00:00:00 2016-01-10 00:00:00

Details

To request source details, provide a source ID to the details method of the source client:

res = fr.source.details(1)
print res

The response includes the series frequency, observation period, and popularity, among other descriptive features.

id link name realtime_end realtime_start
1 http://www.federalreserve.gov/ Board of Governors of the Federal Reserve System (US) 2016-01-10 00:00:00 2016-01-10 00:00:00

Releases

To request source details, provide a source ID to the details method of the source client:

params = {
         'limit':10
         }

res = fr.source.releases(1,params=params)
print res

The response includes the source ID, name, and a link to the source:

id link name notes press_release realtime_end realtime_start
13 http://www.federalreserve.gov/releases/g17/ G.17 Industrial Production and Capacity Utilization   True 2016-01-10 00:00:00 2016-01-10 00:00:00
14 http://www.federalreserve.gov/releases/g19/ G.19 Consumer Credit   True 2016-01-10 00:00:00 2016-01-10 00:00:00
15 http://www.federalreserve.gov/releases/g5/ G.5 Foreign Exchange Rates   True 2016-01-10 00:00:00 2016-01-10 00:00:00
17 http://www.federalreserve.gov/releases/h10/ H.10 Foreign Exchange Rates   True 2016-01-10 00:00:00 2016-01-10 00:00:00
18 http://www.federalreserve.gov/releases/h15/ H.15 Selected Interest Rates   True 2016-01-10 00:00:00 2016-01-10 00:00:00
19 http://www.federalreserve.gov/releases/h3/ H.3 Aggregate Reserves of Depository Institutions and the Monetary Base   True 2016-01-10 00:00:00 2016-01-10 00:00:00
20 http://www.federalreserve.gov/releases/h41/ H.4.1 Factors Affecting Reserve Balances   True 2016-01-10 00:00:00 2016-01-10 00:00:00
21 http://www.federalreserve.gov/releases/h6/ H.6 Money Stock Measures   True 2016-01-10 00:00:00 2016-01-10 00:00:00
22 http://www.federalreserve.gov/releases/h8/ H.8 Assets and Liabilities of Commercial Banks in the United States   True 2016-01-10 00:00:00 2016-01-10 00:00:00
52 http://www.federalreserve.gov/releases/z1/ Z.1 Financial Accounts of the United States
The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy�s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)
Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks�or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector�s health and the performance of the economy as a whole. Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve�s Z.1 statistical release. (1) Teplin, Albert M. �The U.S. Flow of Funds Accounts and Their Uses.� Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf. (2) Board of Governors of the Federal Reserve System. �Guide to the Flow of Funds Accounts.� 2000, http://www.federalreserve.gov/apps/fof/.
True 2016-01-10 00:00:00 2016-01-10 00:00:00

Tags

Economic data series derive from a variety of sources,including the Federal Reserve Bank, Bureau of Labor Statistics,Bureau of Economic Analysis, and Census Bureau.

All tags

Get all tags:

params = {
         'limit':10
         }

res = fr.tag.tags(params=params)
print res

The response includes the group ID, name, and popularity:

created group_id name notes popularity series_count
2012-02-27 16:18:19 seas nsa Not seasonally adjusted 97 326950
2012-02-27 16:18:19 geo usa United States of America 100 248427
2012-02-27 16:18:19 freq annual   84 222080
2012-02-27 16:18:19 geot nation Country Level 100 163584
2012-02-27 16:18:19 src census US. Bureau of the Census 79 121069
2012-02-27 16:18:19 geot county County, Parish, or Borough Level 68 100793
2012-02-27 16:18:19 src bls US. Bureau of Labor Statistics 86 100575
2012-02-27 16:18:19 freq monthly   94 94751
2012-02-27 16:18:19 gen employment   77 88557
2015-12-30 19:26:34 rls saipe Small Area Income and Poverty Estimates (SAIPE) 50 80957

Series

Get series associated with tags:

params = {
         'limit':2
         }

res = fr.tag.series('slovenia;food',params=params)
print res

The response includes the series details:

frequency frequency_short id last_updated notes observation_end observation_start popularity realtime_end realtime_start seasonal_adjustment seasonal_adjustment_short title units units_short
Monthly M 00XEFDSIM086NEST 2015-12-16 16:08:23

The Harmonized Index of Consumer Prices category "Overall Index Excluding Energy, Food, Alcohol, and Tobacco (00XEFOOD)" is a classification of nondurable goods, semi-durable goods, durable goods, and services that includes Clothing Materials (03.1.1), Garments (03.1.2), Other Articles of Clothing and Clothing Accessories (03.1.3), Cleaning, Repair, and Hire of Clothing (03.1.4), Shoes and Other Footwear including Repair and Hire of Footwear (03.2.1/2), Actual Rentals Paid by Tenants including Other Actual Rentals (04.1.1/2), Materials for the Maintenance and Repair of the Dwelling (04.3.1), Services for the Maintenance and Repair of the Dwelling (04.3.2), Water Supply (04.4.1), Refuse Collection (04.4.2), Sewerage Collection (04.4.3), Other Services Relating to the Dwelling, Not Elsewhere Classified (04.4.4), Furniture and Furnishings (05.1.1), Carpets and Other Floor Coverings (05.1.2), Repair of Furniture, Furnishings, and Floor Coverings (05.1.3), Household Textiles (05.2), Major Household Appliances whether Electric or not and Small Electric Household Appliances (05.3.1/2), Repair of Household Appliances (05.3.3), Glassware, Tableware, and Household Utensils (05.4), Major Tools and Equipment and Small Tools and Miscellaneous Accessories (05.5.1/2), Nondurable Household Goods (05.6.1), Domestic Services and Household Services (05.6.2), Pharmaceutical Products (06.1.1), Other Medical Products, Therapeutic Appliances and Equipment (06.1.2/3), Medical and Paramedical Services (06.2.1/3), Dental Services (06.2.2), Hospital Services (06.3), Motor Cars (07.1.1), Motor Cycles, Bicycles, and Animal Drawn Vehicles (07.1.2/3/4), Spare Parts and Accessories for Personal Transport Equipment (07.2.1), Maintenance and Repair of Personal Transport Equipment (07.2.3), Other Services in respect of Personal Transport Equipment (07.2.4), Passenger Transport by Railway (07.3.1), Passenger Transport by Road (07.3.2), Passenger Transport by Air (07.3.3), Passenger Transport by Sea and Inland Waterway (07.3.4), Combined Passenger Transport (07.3.5), Other Purchased Transport Services (07.3.6), Postal Services (08.1), Telephone and Telefax Equipment and Telephone and Telefax Services (08.2/3), Equipment for the Reception, Recording, and Reproduction of Sound and Pictures (09.1.1), Photographic and Cinematographic Equipment and Optical Instruments (09.1.2), Information Processing Equipment (09.1.3), Recording Media (09.1.4), Repair of Audio-Visual, Photographic and Information Processing Equipment (09.1.5), Major Durables for Indoor and Outdoor Recreation including Musical Instruments (09.2.1/2), Maintenance and Repair of Other Major Durables for Recreation and Culture (09.2.3), Games, Toys, and Hobbies (09.3.1), Equipment for Sport, Camping, and Open-Air Recreation (09.3.2), Gardens, Plants, and Flowers (09.3.3), Pets and Related Products including Veterinary and Other Services for Pets (09.3.4/5), Recreational and Sporting Services (09.4.1), Cultural Services (09.4.2), Books (09.5.1), Newspapers and Periodicals (09.5.2), Miscellaneous Printed Matter, Stationery, and Drawing Materials (09.5.3/4), Package Holidays (09.6), Pre-Primary and Primary, Secondary, Post-Secondary Non-Tertiary, Tertiary Education, and Education not definable by Level (10.X), Restaurants, cafés, and the Like (11.1.1), Canteens (11.1.2), Accommodation Services (11.2), Hairdressing Salons and Personal Grooming Establishments (12.1.1), Electric Appliances for Personal Care and Other Appliances, Articles, and Products for Personal Care (12.1.2/3), Jewelry, Clocks, and Watches (12.3.1), Other Personal Effects (12.3.2), Social Protection (12.4), Insurance connected with the Dwelling (12.5.2), Insurance connected with Health (12.5.3), Insurance connected with Transport (12.5.4), Other Insurance (12.5.5) Other Financial Services , Not Elsewhere Classified (12.6.2), and Other Services, Not Elsewhere Classified (12.7).

Information provided in the notes pertaining to Special Aggregates HICP classifications can be found from the source at: http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=ACT_OTH_CLS_DLD&StrNom=HICP_2000&StrFormat=HTML&StrLanguageCode=EN&IntKey=22476519.

Copyright, European Union, 1995-2014, http://epp.eurostat.ec.europa.eu/portal/page/portal/about_eurostat/policies/copyright_licence_policy.

2015-11-01 00:00:00 1999-12-01 00:00:00 0 2016-01-10 00:00:00 2016-01-10 00:00:00 Not Seasonally Adjusted NSA Harmonized Index of Consumer Prices: Overall Index Excluding Energy, Food, Alcohol, and Tobacco for Slovenia© Index 2005=100 Index 2005=100
Monthly M 00XESESIM086NEST 2015-12-16 16:08:16

The Harmonized Index of Consumer Prices category "Overall Index Excluding Energy and Seasonal Food (00XESEAS)" is a classification of nondurable goods, semi-durable goods, durable goods, and services that includes Bread and Cereals (01.1.1), Meat (01.1.2), Milk, Cheese, and Eggs (01.1.4), Oils and Fats (01.1.5), Sugar, Jam, Honey, Chocolate, and Confectionery (01.1.8), Food Products, Not Elsewhere Classified (01.1.9), Coffee, Tea, and Cocoa (01.2.1), Mineral Waters, Soft Drinks, and Fruit and Vegetable Juices (01.2.2), Spirits (02.1.1), Wine (02.1.2), Beer (02.1.3), Tobacco (02.2), Clothing Materials (03.1.1), Garments (03.1.2), Other Articles of Clothing and Clothing Accessories (03.1.3), Cleaning, Repair, and Hire of Clothing (03.1.4), Shoes and Other Footwear including Repair and Hire of Footwear (03.2.1/2), Actual Rentals Paid by Tenants including Other Actual Rentals (04.1.1/2), Materials for the Maintenance and Repair of the Dwelling (04.3.1), Services for the Maintenance and Repair of the Dwelling (04.3.2), Water Supply (04.4.1), Refuse Collection (04.4.2), Sewerage Collection (04.4.3), Other Services Relating to the Dwelling, Not Elsewhere Classified (04.4.4), Furniture and Furnishings (05.1.1), Carpets and Other Floor Coverings (05.1.2), Repair of Furniture, Furnishings, and Floor Coverings (05.1.3), Household Textiles (05.2), Major Household Appliances whether Electric or not and Small Electric Household Appliances (05.3.1/2), Repair of Household Appliances (05.3.3), Glassware, Tableware, and Household Utensils (05.4), Major Tools and Equipment and Small Tools and Miscellaneous Accessories (05.5.1/2), Nondurable Household Goods (05.6.1), Domestic Services and Household Services (05.6.2), Pharmaceutical Products (06.1.1), Other Medical Products, Therapeutic Appliances and Equipment (06.1.2/3), Medical and Paramedical Services (06.2.1/3), Dental Services (06.2.2), Hospital Services (06.3), Motor Cars (07.1.1), Motor Cycles, Bicycles, and Animal Drawn Vehicles (07.1.2/3/4), Spare Parts and Accessories for Personal Transport Equipment (07.2.1), Maintenance and Repair of Personal Transport Equipment (07.2.3), Other Services in respect of Personal Transport Equipment (07.2.4), Passenger Transport by Railway (07.3.1), Passenger Transport by Road (07.3.2), Passenger Transport by Air (07.3.3), Passenger Transport by Sea and Inland Waterway (07.3.4), Combined Passenger Transport (07.3.5), Other Purchased Transport Services (07.3.6), Postal Services (08.1), Telephone and Telefax Equipment and Telephone and Telefax Services (08.2/3), Equipment for the Reception, Recording, and Reproduction of Sound and Pictures (09.1.1), Photographic and Cinematographic Equipment and Optical Instruments (09.1.2), Information Processing Equipment (09.1.3), Recording Media (09.1.4), Repair of Audio-Visual, Photographic and Information Processing Equipment (09.1.5), Major Durables for Indoor and Outdoor Recreation including Musical Instruments (09.2.1/2), Maintenance and Repair of Other Major Durables for Recreation and Culture (09.2.3), Games, Toys, and Hobbies (09.3.1), Equipment for Sport, Camping, and Open-Air Recreation (09.3.2), Gardens, Plants, and Flowers (09.3.3), Pets and Related Products including Veterinary and Other Services for Pets (09.3.4/5), Recreational and Sporting Services (09.4.1), Cultural Services (09.4.2), Books (09.5.1), Newspapers and Periodicals (09.5.2), Miscellaneous Printed Matter, Stationery, and Drawing Materials (09.5.3/4), Package Holidays (09.6), Pre-Primary and Primary, Secondary, Post-Secondary Non-Tertiary, Tertiary Education, and Education not definable by Level (10.X), Restaurants, cafés, and the Like (11.1.1), Canteens (11.1.2), Accommodation Services (11.2), Hairdressing Salons and Personal Grooming Establishments (12.1.1), Electric Appliances for Personal Care and Other Appliances, Articles, and Products for Personal Care (12.1.2/3), Jewelry, Clocks, and Watches (12.3.1), Other Personal Effects (12.3.2), Social Protection (12.4), Insurance connected with the Dwelling (12.5.2), Insurance connected with Health (12.5.3), Insurance connected with Transport (12.5.4), Other Insurance (12.5.5) Other Financial Services , Not Elsewhere Classified (12.6.2), and Other Services, Not Elsewhere Classified (12.7).

Information provided in the notes pertaining to Special Aggregates HICP classifications can be found from the source at: http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=ACT_OTH_CLS_DLD&StrNom=HICP_2000&StrFormat=HTML&StrLanguageCode=EN&IntKey=22476519.

Copyright, European Union, 1995-2014, http://epp.eurostat.ec.europa.eu/portal/page/portal/about_eurostat/policies/copyright_licence_policy.

2015-11-01 00:00:00 1999-12-01 00:00:00 0 2016-01-10 00:00:00 2016-01-10 00:00:00 Not Seasonally Adjusted NSA Harmonized Index of Consumer Prices: Overall Index Excluding Energy and Seasonal Food for Slovenia© Index 2005=100 Index 2005=100

Related tags

Get related tags:

params = {
         'limit':5,
         'exclude_tag_names':'goods',
         'sort_order':'desc'
         }

res = fr.tag.related_tags('services;quarterly',params=params)
print res

The response includes the group ID, name, and popularity:

created group_id name notes popularity series_count
2012-02-27 16:18:19 geot nation Country Level 100 1752
2012-02-27 16:18:19 seas nsa Not seasonally adjusted 97 1230
2012-02-27 16:18:19 geo usa United States of America 100 1200
2012-08-16 20:21:17 rls mei Main Economic Indicators 77 1172
2012-02-27 16:18:19 src oecd Organisation for Economic Co-operation and Development 77 1172