get_val_lab1 {labelr}

Return Look-up Table of One Variable's Value Labels

Description

For a data.frame with value-labeled variables, get_val_lab1 returns a derivative data.frame or vector that shows the value-to-label mapping for each unique value of that value-labeled variable.

Usage

get_val_lab1(data, var, simplify = FALSE)

gvl1(data, var, simplify = FALSE)

Arguments

data

a data.frame.

var

the unquoted name of the variable (column) for which a value-to-label look-up mapping is sought.

simplify

return the mapping as a named vector, not a data.frame (defaults to FALSE).

Details

get_val1 is a variant of get_val_labs that allows you to specify only one var whose value-to-label mapping you wish to look up.

Note 1: As with get_val_labs(), get_val_lab1() exists to provide a visual, human-interpretable quick look at how value labels map to underlying values and is NOT intended for use in automated querying, subsetting, or other manipulation of those value labels. Further: Unlike get_val_labs(), which may return value-to-label mappings for –several– variables of potentially different atomic types, get_val_lab1() limits itself to returning the value labels of a –single– variable (column) of the supplied data.frame.

For this reason, and in contrast to the behavior of get_val_labs(), if get_val_lab1()'s simplify argument is set to FALSE (the default), the returned data.frame will express var values as numeric if this can be done without creating new NA values (i.e., in the sense of as_numv()). In contrast, if simplify is TRUE, the look-up table information will be returned as a named character vector.

Note 2: gvl1 is a compact alias for get_val_lab1: they do the same thing, and the former is easier to type

Value

By default, a three-column data.frame, consisting of "var", "vals", and "labs" columns, where each row corresponds to a unique value of var OR – for variables labeled using add_quant_labs (or add_quant1) – the approximate (i.e., possibly rounded) upper bound of numerical values that fall within that label's range of coverage. If simplify is FALSE, a character vector will returned.

Examples

# add val labs to multiple variables at once
# make a "Likert"-type fake data set to demo
# note, by default, add_val_labs() "vars" arg will do partial matching
# in this case, we catch all vars with "x" in their name
set.seed(272)
dflik <- make_likert_data(scale = 1:7)
vals2label <- 1:7
labs2use <- c(
  "VSD",
  "SD",
  "D",
  "N",
  "A",
  "SA",
  "VSA"
)

dflik <- add_val_labs(
  data = dflik, vars = c("x", "y3"), # note the vars args
  vals = vals2label,
  labs = labs2use,
  partial = TRUE
)

# note, all "x" vars get the labs, as does "y3"
get_val_lab1(dflik, x1)

get_val_lab1(dflik, x1, simplify = TRUE)