pedrobtz/imf.data

A R Interface to IMF Data API

imf.data

The goal of imf.data is to provide an interface to IMF Data via the IMF Data REST API.

Installation

Install the released version of remotes from CRAN:

install.packages("imf.data")

Usage

library(imf.data)

# list all available time-series
list_datasets()
#>               ID                                                        Description
#> 297       AFRREO              Sub-Saharan Africa Regional Economic Outlook (AFRREO)
#> 41  AFRREO201410 Sub-Saharan Africa Regional Economic Outlook (AFRREO) October 2014
#> 110 AFRREO201504   Sub-Saharan Africa Regional Economic Outlook (AFRREO) April 2015
#> 58  AFRREO201510 Sub-Saharan Africa Regional Economic Outlook (AFRREO) October 2015
#> 78  AFRREO201604   Sub-Saharan Africa Regional Economic Outlook (AFRREO) April 2016
#> 21  AFRREO201610 Sub-Saharan Africa Regional Economic Outlook (AFRREO) October 2016
#> 34  AFRREO201704   Sub-Saharan Africa Regional Economic Outlook (AFRREO) April 2017
#>  [ reached 'max' / getOption("max.print") -- omitted 316 rows ]

# load IFS time-series
IFS <- load_datasets("IFS")

# see possible values for dimension 'ref_area'
IFS$dimensions$ref_area
#>   Value         Description
#> 1    AF         Afghanistan
#> 2    AL             Albania
#> 3    DZ             Algeria
#> 4    AD             Andorra
#> 5    AO              Angola
#> 6    AI            Anguilla
#> 7    AG Antigua and Barbuda
#>  [ reached 'max' / getOption("max.print") -- omitted 271 rows ]

# get time-series for GDP of Portugal, with Annual frequency
IFS$get_series(freq = "A", ref_area = "PT", indicator = "NGDP_D_IX")
#>   TIME_PERIOD   A.PT.NGDP_D_IX
#> 1        1995  65.121159550493
#> 2        1996 66.6781968283958
#> 3        1997 69.2687835398304
#> 4        1998 71.9183372769496
#> 5        1999 74.3423648876999
#> 6        2000 76.8850736800294
#> 7        2001 79.7421096759417
#>  [ reached 'max' / getOption("max.print") -- omitted 21 rows ]

# load DOT time-series
DOT <- load_datasets("DOT")

DOT$get_series(freq = "M",
               ref_area = "PT",
               indicator = "TMG_CIF_USD",
               counterpart_area = c("B0","W00"),
               start_period = "2022-01-01",
               end_period = "2022-12-31")
#>   TIME_PERIOD M.PT.TMG_CIF_USD.B0 M.PT.TMG_CIF_USD.W00
#> 1     2022-01         5899.209507          8592.410482
#> 2     2022-02         6625.214152          9306.561169
#> 3     2022-03         7271.456185         10056.201211
#> 4     2022-04         6639.368158          9427.777556
#> 5     2022-05         7095.966482         10432.681421
#>  [ reached 'max' / getOption("max.print") -- omitted 7 rows ]

HPDD <- load_datasets("HPDD")

HPDD$dimensions$indicator
#>        Value       Description
#> 1 GGXWDG_GDP Debt to GDP Ratio

HPDD$get_series(freq = "A",
                ref_area = c("PT","ES"),
                indicator = "GGXWDG_GDP", 
                start_period = "1974")
#>   TIME_PERIOD  A.PT.GGXWDG_GDP  A.ES.GGXWDG_GDP
#> 1        1974 13.5038251401281 8.40504508036064
#> 2        1975 19.1667501320296 7.25030408773679
#> 3        1976 24.5259382117236 13.0038706110036
#> 4        1977 26.8756607793361 15.3279581608194
#> 5        1978 29.8913266186709 14.3281987356424
#>  [ reached 'max' / getOption("max.print") -- omitted 37 rows ]