library(fredr)
This vignette is intended to introduce the user to fredr functions for the Releases endpoint of the FRED API.
FRED series are added to the FRED database over time in releases. Each FRED release is assigned an integer identifier. The following examples illustrate usage of the Releases endpoint functions in fredr.
The function fredr_releases()
returns a set of all FRED releases matching the request. The data returned is a tibble in which each row represents a FRED release. The default call returns all FRED releases:
fredr_releases()
#> # A tibble: 291 x 7
#> id realtime_start realtime_end name press_release link notes
#> <int> <chr> <chr> <chr> <lgl> <chr> <chr>
#> 1 9 2020-11-11 2020-11-11 Advance M… TRUE http://… "The U.S…
#> 2 10 2020-11-11 2020-11-11 Consumer … TRUE http://… <NA>
#> 3 11 2020-11-11 2020-11-11 Employmen… TRUE http://… <NA>
#> 4 13 2020-11-11 2020-11-11 G.17 Indu… TRUE http://… <NA>
#> 5 14 2020-11-11 2020-11-11 G.19 Cons… TRUE http://… <NA>
#> 6 15 2020-11-11 2020-11-11 G.5 Forei… TRUE http://… <NA>
#> 7 17 2020-11-11 2020-11-11 H.10 Fore… TRUE http://… <NA>
#> 8 18 2020-11-11 2020-11-11 H.15 Sele… TRUE http://… <NA>
#> 9 19 2020-11-11 2020-11-11 H.3 Aggre… TRUE http://… "The Boa…
#> 10 20 2020-11-11 2020-11-11 H.4.1 Fac… TRUE http://… <NA>
#> # … with 281 more rows
The function fredr_releases_dates()
returns a set of release dates for all FRED releases. The data returned is a tibble where each row represents a release date for a release. For example, to get all release dates (up to the limit of 1000
) ordered by descending release date:
fredr_releases_dates()
#> # A tibble: 1,000 x 3
#> release_id release_name date
#> <int> <chr> <chr>
#> 1 72 Daily Treasury Inflation-Indexed Securities 2020-11…
#> 2 279 Economic Policy Uncertainty 2020-11…
#> 3 287 Nikkei Indexes 2020-11…
#> 4 354 An Arbitrage-Free Three-Factor Term Structure Model and … 2020-11…
#> 5 200 CBOE Market Statistics 2020-11…
#> 6 441 Coinbase Cryptocurrencies 2020-11…
#> 7 86 Commercial Paper 2020-11…
#> 8 72 Daily Treasury Inflation-Indexed Securities 2020-11…
#> 9 279 Economic Policy Uncertainty 2020-11…
#> 10 378 Federal Funds Data 2020-11…
#> # … with 990 more rows
To instead order the results by ascending release ID:
fredr_releases_dates(
sort_order = "asc",
order_by = "release_id"
)#> # A tibble: 1,000 x 3
#> release_id release_name date
#> <int> <chr> <chr>
#> 1 9 Advance Monthly Sales for Retail and Food Services 2020-01-16
#> 2 9 Advance Monthly Sales for Retail and Food Services 2020-02-14
#> 3 9 Advance Monthly Sales for Retail and Food Services 2020-03-17
#> 4 9 Advance Monthly Sales for Retail and Food Services 2020-04-15
#> 5 9 Advance Monthly Sales for Retail and Food Services 2020-05-15
#> 6 9 Advance Monthly Sales for Retail and Food Services 2020-06-16
#> 7 9 Advance Monthly Sales for Retail and Food Services 2020-07-16
#> 8 9 Advance Monthly Sales for Retail and Food Services 2020-08-14
#> 9 9 Advance Monthly Sales for Retail and Food Services 2020-09-16
#> 10 9 Advance Monthly Sales for Retail and Food Services 2020-10-16
#> # … with 990 more rows
The function fredr_release()
returns data for a single FRED release specified by release_id
. The data returned is a tibble where each row represents the specified release. For example, to get release data for the Employment Cost Index release:
fredr_release(release_id = 11L)
#> # A tibble: 1 x 6
#> id realtime_start realtime_end name press_release link
#> <int> <chr> <chr> <chr> <lgl> <chr>
#> 1 11 2020-11-11 2020-11-11 Employment C… TRUE http://www.bls.…
The function fredr_release_dates()
returns a set of release dates for a single FRED release specified by release_id
. The data returned is a tibble where each row represents a release date for the release specified. For example, to get release dates for the Employment Cost Index release:
fredr_release_dates(release_id = 11L)
#> # A tibble: 108 x 2
#> release_id date
#> <int> <chr>
#> 1 11 1996-10-29
#> 2 11 1997-01-28
#> 3 11 1997-04-29
#> 4 11 1997-07-29
#> 5 11 1997-10-28
#> 6 11 1998-01-27
#> 7 11 1998-04-30
#> 8 11 1998-07-30
#> 9 11 1998-10-29
#> 10 11 1999-01-28
#> # … with 98 more rows
The function fredr_release_series()
returns a set of series belonging to the FRED release specified by release_id
. The data returned is a tibble where each row represents a series in the release specified. For example, to get series in the Employment Cost Index release:
fredr_release_series(release_id = 10L)
#> # A tibble: 1,000 x 16
#> id realtime_start realtime_end title observation_sta… observation_end
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 CPIA… 2020-11-11 2020-11-11 Cons… 1914-12-01 2020-09-01
#> 2 CPIA… 2020-11-11 2020-11-11 Cons… 1947-01-01 2020-09-01
#> 3 CPIA… 2020-11-11 2020-11-11 Cons… 1913-01-01 2020-09-01
#> 4 CPIA… 2020-11-11 2020-11-11 Cons… 1947-01-01 2020-09-01
#> 5 CPIE… 2020-11-11 2020-11-11 Cons… 1993-01-01 2020-09-01
#> 6 CPIE… 2020-11-11 2020-11-11 Cons… 1993-01-01 2020-09-01
#> 7 CPIE… 2020-11-11 2020-11-11 Cons… 1957-01-01 2020-09-01
#> 8 CPIE… 2020-11-11 2020-11-11 Cons… 1957-01-01 2020-09-01
#> 9 CPIF… 2020-11-11 2020-11-11 Cons… 1967-01-01 2020-09-01
#> 10 CPIF… 2020-11-11 2020-11-11 Cons… 1967-01-01 2020-09-01
#> # … with 990 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>
Note the parameters available to filter series belonging to a release:
fredr_release_series(
release_id = 10L,
filter_variable = "frequency",
filter_value = "Monthly",
order_by = "popularity",
sort_order = "desc",
limit = 10L
)#> # A tibble: 10 x 16
#> id realtime_start realtime_end title observation_sta… observation_end
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 CPIA… 2020-11-11 2020-11-11 Cons… 1947-01-01 2020-09-01
#> 2 CPIL… 2020-11-11 2020-11-11 Cons… 1957-01-01 2020-09-01
#> 3 CPIA… 2020-11-11 2020-11-11 Cons… 1913-01-01 2020-09-01
#> 4 CUUR… 2020-11-11 2020-11-11 Cons… 1913-01-01 2020-09-01
#> 5 CPIM… 2020-11-11 2020-11-11 Cons… 1947-01-01 2020-09-01
#> 6 CUUR… 2020-11-11 2020-11-11 Cons… 1914-12-01 2020-09-01
#> 7 CPIF… 2020-11-11 2020-11-11 Cons… 1967-01-01 2020-09-01
#> 8 CUSR… 2020-11-11 2020-11-11 Cons… 1953-01-01 2020-09-01
#> 9 CWUR… 2020-11-11 2020-11-11 Cons… 1913-01-01 2020-09-01
#> 10 CPIA… 2020-11-11 2020-11-11 Cons… 1947-01-01 2020-09-01
#> # … 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>
The function fredr_release_sources()
returns a set of FRED sources for the FRED release specified by release_id
. The data returned is a tibble where each row represents a source. For example, to get the sources for the Consumer Price Index release:
fredr_release_sources(release_id = 10L)
#> # A tibble: 1 x 5
#> id realtime_start realtime_end name link
#> <int> <chr> <chr> <chr> <chr>
#> 1 22 2020-11-11 2020-11-11 U.S. Bureau of Labor Stat… https://www.bls.…
The function fredr_release_tables()
returns a set of FRED release table trees for the FRED release specified by release_id
. The data returned is a tibble where each row represents an element of the table tree’s children: the column name
gives the element ID and the column value
stores data nodes for the element (e.g. element ID, release ID, parent ID, element type, element name, children, etc.). For example, to get the table tree for the Consumer Price Index release:
<- fredr_release_tables(release_id = 10L)
cpi_tbl
cpi_tbl#> # A tibble: 2 x 2
#> name value
#> <chr> <list>
#> 1 34481 <named list [9]>
#> 2 36712 <named list [9]>
The above table has two elements: 34481
and 36712
. Inspect an element (a list) by selecting its row and unnesting the row element value
using tibble::deframe()
:
library(dplyr)
#> Warning: package 'dplyr' was built under R version 4.0.2
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(tibble)
%>%
cpi_tbl slice(2) %>%
deframe()
#> $`36712`
#> $`36712`$element_id
#> [1] 36712
#>
#> $`36712`$release_id
#> [1] 10
#>
#> $`36712`$series_id
#> NULL
#>
#> $`36712`$parent_id
#> NULL
#>
#> $`36712`$line
#> NULL
#>
#> $`36712`$type
#> [1] "section"
#>
#> $`36712`$name
#> [1] "Consumer Price Index Special Aggregate Indices"
#>
#> $`36712`$level
#> [1] "0"
#>
#> $`36712`$children
#> list()
You can extract the tree hierarchy of a deeper element in the table by specifying an element_id
. From the previous example, if you wanted to get the subtree for child element 36712
of the Consumer Price Index table:
fredr_release_tables(
release_id = 10L,
element_id = 36712L
)#> # A tibble: 4 x 2
#> name value
#> <chr> <list>
#> 1 36713 <named list [9]>
#> 2 36801 <named list [9]>
#> 3 37003 <named list [9]>
#> 4 37691 <named list [9]>