Introduction

This vignette is intended to introduce the user to fredr functions for the Categories endpoint of the FRED API.

FRED series are assigned categories. Each FRED category is assigned an integer identifier. For example:

“Population, Employment, & Labor Markets” (category_id = 10)
“National Accounts” (category_id = 32992)
“Production & Business Activity” (category_id = 1)
“Housing” (category_id = 97)

Categories are organized in a hierarchical structure where parent categories contain children categories. All categories are children of the root category (category_id = 0). The following examples illustrate usage of the Categories endpoint functions in fredr.

Get a FRED category

fredr_category() returns minimal information for a single category specified by category_id. The data returned is a tibble in which each row represents a category. The default is the root category.

fredr_category() 
#> # A tibble: 1 x 3
#>      id name       parent_id
#> * <int> <chr>          <int>
#> 1     0 Categories         0

fredr_category(category_id = 97L)
#> # A tibble: 1 x 3
#>      id name    parent_id
#> * <int> <chr>       <int>
#> 1    97 Housing         1

Get the children of a FRED category

fredr_category_children() returns minimal information (child ID, name, and parent ID) for all child categories of the parent category specified by category_id. The data returned is a tibble in which each row represents child category of the parent specified. The default is the root category.

fredr_category_children()
#> # A tibble: 8 x 3
#>      id name                                    parent_id
#> * <int> <chr>                                       <int>
#> 1 32991 Money, Banking, & Finance                       0
#> 2    10 Population, Employment, & Labor Markets         0
#> 3 32992 National Accounts                               0
#> 4     1 Production & Business Activity                  0
#> 5 32455 Prices                                          0
#> 6 32263 International Data                              0
#> 7  3008 U.S. Regional Data                              0
#> 8 33060 Academic Data                                   0

fredr_category_children(category_id = 1L)
#> # A tibble: 12 x 3
#>       id name                                         parent_id
#>  * <int> <chr>                                            <int>
#>  1 32262 Business Cycle Expansions & Contractions             1
#>  2 32436 Construction                                         1
#>  3 33490 Finance Companies                                    1
#>  4 32216 Health Insurance                                     1
#>  5    97 Housing                                              1
#>  6     3 Industrial Production & Capacity Utilization         1
#>  7 32429 Manufacturing                                        1
#>  8     6 Retail Trade                                         1
#>  9 33441 Services                                             1
#> 10 33492 Technology                                           1
#> 11 33202 Transportation                                       1
#> 12 33203 Wholesale Trade                                      1

Get a related FRED category

fredr_category_related() returns minimal information (ID, name, and parent ID) for all related categories to the category specified by category_id. The data returned is a tibble in which each row represents category related to the one specified. Note that not all categories have related categories. The default is the root category.

fredr_category_related()
#> # A tibble: 0 x 0

fredr_category_related(category_id = 4L) # Employment Cost Index
#> # A tibble: 1 x 3
#>      id name                                    parent_id
#> * <int> <chr>                                       <int>
#> 1    10 Population, Employment, & Labor Markets         0

Get series in a category

fredr_category_series() returns detailed information for the FRED series belonging to the category specified by category_id. The data returned is a tibble in which each row represents a series belonging to the category specified. The default is the root category. For example, to get the top 100 quarterly series in the “Housing” category, ordering the results so that the most recently updated series appear first:

fredr_category_series(
  category_id = 97L, # Housing
  limit = 100L,
  order_by = "last_updated",
  filter_variable = "frequency",
  filter_value = "Quarterly"
)
#> # A tibble: 25 x 16
#>    id    realtime_start realtime_end title observation_sta… observation_end
#>  * <chr> <chr>          <chr>        <chr> <chr>            <chr>          
#>  1 ETOT… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  2 RHOR… 2018-07-22     2018-07-22   Home… 1965-01-01       2018-01-01     
#>  3 RRVR… 2018-07-22     2018-07-22   Rent… 1956-01-01       2018-01-01     
#>  4 EOWN… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  5 EREN… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  6 ERNT… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  7 ESAL… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  8 EVAC… 2018-07-22     2018-07-22   Hous… 2000-04-01       2018-01-01     
#>  9 RHVR… 2018-07-22     2018-07-22   Home… 1956-01-01       2018-01-01     
#> 10 RSAH… 2018-07-22     2018-07-22   Home… 1980-01-01       2018-01-01     
#> # ... with 15 more rows, and 10 more variables: frequency <chr>,
#> #   frequency_short <chr>, units <chr>, units_short <chr>,
#> #   seasonal_adjustment <chr>, seasonal_adjustment_short <chr>,
#> #   last_updated <chr>, popularity <int>, group_popularity <int>,
#> #   notes <chr>

To return all series in the “National Accounts” tagged with “usa” and not “gnp”, ordering the results such that higher frequency series appear first:

fredr_category_series(
  category_id = 32992L, # National Accounts
  order_by = "frequency",
  sort_order = "desc",
  tag_names = "usa",
  exclude_tag_names = "gnp"
)
#> # A tibble: 4 x 16
#>   id    realtime_start realtime_end title observation_sta… observation_end
#> * <chr> <chr>          <chr>        <chr> <chr>            <chr>          
#> 1 PCRG… 2018-07-22     2018-07-22   Tota… 2001-01-01       2016-01-01     
#> 2 NGMP… 2018-07-22     2018-07-22   Tota… 2001-01-01       2016-01-01     
#> 3 RGMP… 2018-07-22     2018-07-22   Tota… 2001-01-01       2016-01-01     
#> 4 QGMP… 2018-07-22     2018-07-22   Tota… 2001-01-01       2016-01-01     
#> # ... with 10 more variables: frequency <chr>, frequency_short <chr>,
#> #   units <chr>, units_short <chr>, seasonal_adjustment <chr>,
#> #   seasonal_adjustment_short <chr>, last_updated <chr>, popularity <int>,
#> #   group_popularity <int>, notes <chr>

Get tags within a FRED category

fredr_category_tags() returns information for the FRED tags assigned to series in the category specified by category_id. The data returned is a tibble in which each row represents a tag assigned to a series in the category specified. The default is the root category. For example, to get all “source” tags belonging to series in the “Retail Trade” category:

fredr_category_tags(
  category_id = 6L,
  tag_group_id = "src"
)
#> # A tibble: 3 x 6
#>   name    group_id notes            created        popularity series_count
#> * <chr>   <chr>    <chr>            <chr>               <int>        <int>
#> 1 census  src      Census           2012-02-27 10…         78          380
#> 2 bea     src      Bureau of Econo… 2012-02-27 10…         79            4
#> 3 frb stl src      St. Louis Fed    2012-02-27 10…         64            4

To search for tags with the words “usa” in the “Production & Business Activity” category, ordering the results by popularity:

fredr_category_tags(
  category_id = 1L,
  search_text = "usa",
  order_by = "popularity",
  sort_order = "desc"
)
#> # A tibble: 2 x 6
#>   name   group_id notes            created         popularity series_count
#> * <chr>  <chr>    <chr>            <chr>                <int>        <int>
#> 1 usa    geo      United States o… 2012-02-27 10:…         99           10
#> 2 census src      Census           2012-02-27 10:…         78           10

Get related tags within a FRED category

fredr_category_related_tags() returns a set of FRED tags assigned to series in the category specified by category_id that are related to the tags specified in the tag_names parameter. The data returned is a tibble in which each row represents a tag related to a tag assigned to a series in the specified category. The default is the root category. For example, to get all tags except “rate” in the “Retail Trade” category related to the tags “business” and “monthly”, ordering the results alphabetically:

fredr_category_related_tags(
  category_id = 1L,
  tag_names = "business;monthly",
  exclude_tag_names = "rate",
  order_by = "name"
)
#> # A tibble: 10 x 6
#>    name      group_id notes            created     popularity series_count
#>  * <chr>     <chr>    <chr>            <chr>            <int>        <int>
#>  1 census    src      Census           2012-02-27…         78            6
#>  2 headline… gen      ""               2013-11-19…         52            1
#>  3 inventor… gen      ""               2012-02-27…         46            4
#>  4 mtis      rls      Manufacturing &… 2012-08-16…         36            6
#>  5 nation    geot     ""               2012-02-27…        100            6
#>  6 nsa       seas     Not Seasonally … 2012-02-27…        100            3
#>  7 ratio     gen      ""               2012-02-27…         51            2
#>  8 sa        seas     Seasonally Adju… 2012-02-27…         87            3
#>  9 sales     gen      ""               2012-02-27…         61            4
#> 10 usa       geo      United States o… 2012-02-27…         99            6

FRED Categories

Sam Boysel

2018-07-22

Introduction

Get a FRED category

Get the children of a FRED category

Get series in a category

Get tags within a FRED category