drop_val_labs {labelr}

Drop Value Labels from One or More Variables

Description

Drop all value labels previously applied to one or more variables using add_val_labs, add_quant_labs,add_m1_lab, and related functions (e.g., add_val1) or aliases (e.g., avl).

Note: dvl is a compact alias for drop_val_labs: they do the same thing, and the former is easier to type

Usage

drop_val_labs(data, vars = NULL, partial = FALSE, not.vars = NULL)

dvl(data, vars = NULL, partial = FALSE, not.vars = NULL)

Arguments

data

a data.frame.

vars

a character vector that corresponds to the name(s) (or substring within the name(s), if partial = TRUE) of one or more variables form which value labels will be removed. If NULL, all value labels will be removed from all value-labeled variables.

partial

To drop labels for many, similarly named variables (e.g., "x1" through "x20"), you can provide a substring only and set partial = TRUE (default is FALSE). For example, to drop value labels for colnames "x1" through "x20", you could use vars = c("x"), along with partial = TRUE. Be careful with this, as it also will attempt to drop value labels for columns with colnames "sex" or "tax.bracket" (etc.), because they, too, contain an "x" in their names).

not.vars

use of the partial argument can result in situations where you inadvertently attempt to drop value labels for a variable. For example, if vars="x", and partial=TRUE, then drop_val_labs will attempt to drop labels for not only "x1", "x2","x3", and "x4", but also for "sex", "tax.bracket", and other "x"-containing variable names. Use of not.vars allows you to indicate variables that you wish to exempt from value label- dropping, even if their names contain the string found in vars. Note that not.vars gets priority: setting vars="x", partial=TRUE, and not.vars="x" is tantamount to telling drop_val_labs that you actually do not wish to drop value labels for any of the variables that you specified in vars, resulting in no value labels being dropped.

Details

drop_val_labs works with other labelr functions (e.g., add_val_labs, get_val_labs, use_val_labs, add_lab_cols) to facilitate the creation, accessing, modification, use, or deletion of variable value labels.

Value

A data.frame, with all value labels dropped from specified variables.

Examples

# 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
)

dfdrop <- drop_val_labs(dflik,
  vars = c("x2", "y3"),
  partial = FALSE
)

# var x2's value labels are gone, like we asked for
get_val_labs(dfdrop, "x2")

# var x1's value labels are intact, b/c we didn't ask to drop them
get_val_labs(dfdrop, "x1")

dfxgone <- drop_val_labs(dflik,
  c("x"),
  partial = TRUE
)

# still a lot of value labels, but all are for "y" vars,
# ...none is left for "x" vars
get_val_labs(dfxgone)