Add variables to dataset based on hierarchies
Source:R/map_hierarchies_to_data.R
map_hierarchies_to_data.RdUses hierarchies_as_vars to transform hierarchies, followed by mapping to the dataset.
Usage
map_hierarchies_to_data(
data,
hierarchies,
when_overwritten = warning,
add_comment = TRUE,
...
)Arguments
- data
A data frame containing variables with names matching the names of the hierarchies.
- hierarchies
List of hierarchies in the same format as input to
AutoHierarchies- when_overwritten
A function to be called when existing column(s) are overwritten. Supply
stopto invoke an error,warningfor a warning (default),messageto display an informational message, orNULLto do nothing.- add_comment
Logical. When
TRUE(default), a comment attribute will be added to the output data frame, containing the names of the variables that were added.- ...
Further parameters sent to
hierarchies_as_vars
Examples
# Examples similar those from hierarchies_as_vars
z <- SSBtoolsData("sprt_emp_withEU")
year_formula <- c("y_14 = 2014", "y_15_16 = y_all - y_14", "y_all = 2014 + 2015 + 2016")
geo_dim_list <- FindDimLists(z[, c("geo", "eu")], total = "Europe")[[1]]
age_hierarchy <- SSBtoolsData("sprt_emp_ageHier")
map_hierarchies_to_data(z, list(age = age_hierarchy, geo = geo_dim_list,
year = year_formula))
#> age geo year ths_per eu age_level_1 geo_level_1 geo_level_2
#> 1 Y15-29 Spain 2014 66.9 EU Y15-64 EU Europe
#> 2 Y15-29 Iceland 2014 1.8 nonEU Y15-64 nonEU Europe
#> 3 Y15-29 Portugal 2014 11.6 EU Y15-64 EU Europe
#> 4 Y30-64 Spain 2014 120.3 EU Y15-64 EU Europe
#> 5 Y30-64 Iceland 2014 1.5 nonEU Y15-64 nonEU Europe
#> 6 Y30-64 Portugal 2014 20.2 EU Y15-64 EU Europe
#> 7 Y15-29 Spain 2015 63.4 EU Y15-64 EU Europe
#> 8 Y15-29 Iceland 2015 1.9 nonEU Y15-64 nonEU Europe
#> 9 Y15-29 Portugal 2015 14.2 EU Y15-64 EU Europe
#> 10 Y30-64 Spain 2015 119.6 EU Y15-64 EU Europe
#> 11 Y30-64 Iceland 2015 1.6 nonEU Y15-64 nonEU Europe
#> 12 Y30-64 Portugal 2015 24.3 EU Y15-64 EU Europe
#> 13 Y15-29 Spain 2016 69.1 EU Y15-64 EU Europe
#> 14 Y15-29 Iceland 2016 1.9 nonEU Y15-64 nonEU Europe
#> 15 Y15-29 Portugal 2016 12.7 EU Y15-64 EU Europe
#> 16 Y30-64 Spain 2016 122.1 EU Y15-64 EU Europe
#> 17 Y30-64 Iceland 2016 1.9 nonEU Y15-64 nonEU Europe
#> 18 Y30-64 Portugal 2016 25.8 EU Y15-64 EU Europe
#> year_level_1 year_level_2
#> 1 y_14 y_all
#> 2 y_14 y_all
#> 3 y_14 y_all
#> 4 y_14 y_all
#> 5 y_14 y_all
#> 6 y_14 y_all
#> 7 y_15_16 y_all
#> 8 y_15_16 y_all
#> 9 y_15_16 y_all
#> 10 y_15_16 y_all
#> 11 y_15_16 y_all
#> 12 y_15_16 y_all
#> 13 y_15_16 y_all
#> 14 y_15_16 y_all
#> 15 y_15_16 y_all
#> 16 y_15_16 y_all
#> 17 y_15_16 y_all
#> 18 y_15_16 y_all
map_hierarchies_to_data(data.frame(f = c("A", "B", "C", "D", "E", "A")), list(f =
c("AB = A + B", "AC = A + C", "CD = C + D", "ABCD = AB + CD")))
#> f f_level_1 f_level_2 f_level_3
#> 1 A AB AC ABCD
#> 2 B AB <NA> ABCD
#> 3 C CD AC ABCD
#> 4 D CD <NA> ABCD
#> 5 E <NA> <NA> <NA>
#> 6 A AB AC ABCD
# Examples demonstrating when_overwritten and add_comment
a <- map_hierarchies_to_data(z, list(age = age_hierarchy, geo = geo_dim_list))
comment(a)
#> [1] "age_level_1" "geo_level_1" "geo_level_2"
b <- map_hierarchies_to_data(a[-7], list(age = age_hierarchy, geo = geo_dim_list),
when_overwritten = message, add_comment = FALSE)
#> Overwritten columns: age_level_1, geo_level_2
comment(b)
#> NULL