Assimilate all value labels of multiple variables as part of a GADSdat or all_GADSdat object.
Details
Assimilation can be performed using all existing value labels or a look up table containing at least all existing value labels.
Missing codes are reused based on the meta data of the first variable in varNames.
Examples
# Example data set
facs_df <- data.frame(id = 1:3, fac1 = c("Eng", "Aus", "Ger"),
fac2 = c("Ger", "Franz", "Ita"),
fac3 = c("Kor", "Chi", "Alg"),
stringsAsFactors = TRUE)
facs_gads <- import_DF(facs_df)
assimilateValLabels(facs_gads, varNames = paste0("fac", 1:3))
#> $dat
#> id fac1 fac2 fac3
#> 1 1 4 6 8
#> 2 2 2 5 3
#> 3 3 6 7 1
#>
#> $labels
#> varName varLabel format display_width labeled value valLabel missings
#> 1 id <NA> <NA> NA no NA <NA> <NA>
#> 2 fac1 <NA> F10.0 NA yes 1 Alg valid
#> 3 fac1 <NA> F10.0 NA yes 2 Aus valid
#> 4 fac1 <NA> F10.0 NA yes 3 Chi valid
#> 5 fac1 <NA> F10.0 NA yes 4 Eng valid
#> 6 fac1 <NA> F10.0 NA yes 5 Franz valid
#> 7 fac1 <NA> F10.0 NA yes 6 Ger valid
#> 8 fac1 <NA> F10.0 NA yes 7 Ita valid
#> 9 fac1 <NA> F10.0 NA yes 8 Kor valid
#> 10 fac2 <NA> F10.0 NA yes 1 Alg valid
#> 11 fac2 <NA> F10.0 NA yes 2 Aus valid
#> 12 fac2 <NA> F10.0 NA yes 3 Chi valid
#> 13 fac2 <NA> F10.0 NA yes 4 Eng valid
#> 14 fac2 <NA> F10.0 NA yes 5 Franz valid
#> 15 fac2 <NA> F10.0 NA yes 6 Ger valid
#> 16 fac2 <NA> F10.0 NA yes 7 Ita valid
#> 17 fac2 <NA> F10.0 NA yes 8 Kor valid
#> 18 fac3 <NA> F10.0 NA yes 1 Alg valid
#> 19 fac3 <NA> F10.0 NA yes 2 Aus valid
#> 20 fac3 <NA> F10.0 NA yes 3 Chi valid
#> 21 fac3 <NA> F10.0 NA yes 4 Eng valid
#> 22 fac3 <NA> F10.0 NA yes 5 Franz valid
#> 23 fac3 <NA> F10.0 NA yes 6 Ger valid
#> 24 fac3 <NA> F10.0 NA yes 7 Ita valid
#> 25 fac3 <NA> F10.0 NA yes 8 Kor valid
#>
#> attr(,"class")
#> [1] "GADSdat" "list"