# setup opar <- options("ANSI_OUTPUT"=FALSE) # tldropen library(datapackage, warn.conflicts = FALSE) dir <- system.file("examples/employ", package = "datapackage") dp <- open_datapackage(dir) dp # tldrgetdata dta <- dp |> dp_resource("employment") |> dp_get_data() dta # tldrload dta <- dp_load_from_datapackage(dir, "employment") dta # tldrloadfactor dta <- dp_load_from_datapackage(dir, "employment", convert_categories = "to_factor") dta # tldrloadcode library(codelist) dta <- dp_load_from_datapackage(dir, "employment", convert_categories = "to_code") dta # g1 library(datapackage, warn.conflicts = FALSE) dir <- system.file("examples/employ", package = "datapackage") dp <- open_datapackage(dir) dp # g2 dp_nresources(dp) # g3 dp_resource_names(dp) # g4 employ <- dp_resource(dp, "employment") employ # g5 print(employ, properties = NA) # g6 dta <- dp_get_data(employ) head(dta) # g7 dta <- dp_get_data(dp, "employment") # g8 dp_path(employ) # g10 fn <- dp_path(employ, full_path = TRUE) # g11 dta <- read.csv2(fn) head(dta) # dialect dp_property(employ, "dialect") # income dp_field(employ, "income") # dpapplyschema dp_apply_schema(dta, employ) # g12 dta <- dp_resource(dp, "employment") |> dp_get_data() head(dta) # r1 dp_name(dp) dp_description(dp) dp_description(dp, first_paragraph = TRUE) dp_title(dp) # r2 dp_title(employ) dp_resource(dp, "codelist-employ") |> dp_title() # r3 dp_path(employ) dp_path(employ, full_path = TRUE) # r4 dp_property(employ, "encoding") # c1 dta <- dp_resource(dp, "employment") |> dp_get_data() dta # c2 dp_categorieslist(dta$employ) # c3 dp_to_factor(dta$employ) # c4 dta <- dp_resource(dp, "employment") |> dp_get_data(convert_categories = "to_factor") dta # c4 dta <- dp_resource(dp, "employment") |> dp_get_data(convert_categories = "to_code") dta # codedemo library(codelist) dta[dta$gender == "X", ] dta[dta$gender == as.label("Other"), ] # q1 dir <- tempfile() data(iris) dp_save_as_datapackage(iris, dir) # q2 dp_load_from_datapackage(dir) |> head() # q2 dp_load_from_datapackage(dir, "iris", convert_categories = "to_factor", use_fread = TRUE) # n5 file.remove(file.path(dir, "datapackage.json")) file.remove(file.path(dir, "iris.csv")) file.remove(dir) # setup options(opar)