A unified interface to access and manipulate various Philippine statistical classifications. It allows users to retrieve, filter, and harmonize classification data, making it easier to work with Philippine statistical data in R.
phscs Packagephscs provides a single, consistent interface to seven Philippine
Statistics Authority (PSA)
classification systems. All data is bundled with the package — no
internet connection or API token required.
| Function | Classification |
|---|---|
get_psgc() |
Philippine Standard Geographic Code |
get_psic() |
Philippine Standard Industrial Classification |
get_psoc() |
Philippine Standard Occupational Classification |
get_psced() |
Philippine Standard Classification of Education |
get_pcoicop() |
Phil. Classification of Individual Consumption According to Purpose |
get_pcpc() |
Philippine Central Product Classification |
get_psccs() |
Philippine Standard Commodity Classification System |
Install from CRAN:
install.packages("phscs")
Or install the development version from GitHub:
# install.packages("pak")
pak::pak("yng-me/phscs")
library(phscs)
# Geographic data — re-exported from the psgc package
get_psgc(geographic_level = "region") |> head(3)
#> psgc_code area_name correspondence_code geographic_level
#> 1 0100000000 Region I (Ilocos Region) 010000000 Reg
#> 3398 0200000000 Region II (Cagayan Valley) 020000000 Reg
#> 5808 0300000000 Region III (Central Luzon) 030000000 Reg
#> old_name city_class income_classification urban_rural island_region
#> 1 <NA> <NA> <NA> <NA> L
#> 3398 <NA> <NA> <NA> <NA> L
#> 5808 <NA> <NA> <NA> <NA> L
# Industrial classification (default: sub-classes)
get_psic() |> head(3)
#> value
#> 1 01111
#> 2 01112
#> 3 01113
#> label
#> 1 Growing of leguminous crops such as: mongo, string beans (sitao), pigeon peas, gisantes, garbanzos, bountiful beans (habichuelas), peas (sitsaro)
#> 2 Growing of groundnuts
#> 3 Growing of oil seeds (except groundnuts) such as soya beans, sunflower and growing of other oil seeds, n.e.c.
# Occupational classification (default: unit groups)
get_psoc() |> head(3)
#> value label
#> 1 1111 Legislators
#> 2 1112 Senior government officials
#> 3 1113 Traditional chiefs and heads of villages
All classification functions share the same interface:
# Choose a level of detail
get_psic(level = "sections")
get_psoc(level = "major")
get_pcoicop(level = "divisions")
# Include the full text description
get_psic(level = "sections", cols = "description")
# Switch to an older edition (where available)
get_pcoicop(version = "2009")
For a full walkthrough of every classification and more examples, see:
vignette("phscs")