all_quant_labs {labelr}R Documentation

Add Quantile-based Value Labels to All Numeric Vars that Meet Specifications

Description

Add variable-specific quantile-based value labels to all numeric variables of a data.frame that meet specified conditions.

Usage

all_quant_labs(data, qtiles = 5, not.vars = NULL, unique.vals.thresh = 10)

allq(data, qtiles = 5, not.vars = NULL, unique.vals.thresh = 10)

Arguments

data

a data.frame.

qtiles

the number of quantile categories to employ (e.g., 4 would indicate quartiles, 5 would indicate quintiles, 10 for deciles, etc.).

not.vars

used to specify any numeric variables that should be exempted from this operation.

unique.vals.thresh

an integer. Numeric variables with fewer than this many unique variables will be exempted from the operation (i.e., will NOT receive quantile value labels).

Details

Note: allq is a compact alias for all_quant_labs: they do the same thing, and the former is easier to type.

Numerical variables that feature decimals or large numbers of distinct values are not eligible to receive conventional add_val_labs()-style value labels. all_quant_labs allows one to label such variables based on quantile thresholds.

Value

A data.frame, with new variable value labels added.

Examples

# mtcars demo
df <- mtcars
get_val_labs(df) # none
# add quintile val labs for all numeric vars with >10 unique vals
df <- all_quant_labs(data = df, qtiles = 5, unique.vals.thresh = 10)
get_val_labs(df) # here now
headl(df) # show them; note this is labelr::headl(), not utils::head()

[Package labelr version 0.1.7 Index]