tidycomm (version 0.4.1)

minmax_scale: Rescale numeric continuous variables to new minimum/maximum boundaries

Description

Given a specified minimum and maximum, this function translates each value into a new value within this specified range. The transformation maintains the relative distances between values, resulting in changes to the mean and standard deviations. However, if both the original scale and the transformed scale are z-standardized, they will be equal again, indicating that the relative positions and distributions of the values remain consistent.

Usage

minmax_scale(
  data,
  ...,
  change_to_min = 0,
  change_to_max = 1,
  name = NULL,
  overwrite = FALSE
)

Value

A tdcmm model with the min-max scaled variable(s).

Arguments

data

A tibble or a tdcmm model.

...

Numeric variables to be min-max scaled. If none are provided, all numeric columns will be scaled.

change_to_min

The desired minimum value after scaling.

change_to_max

The desired maximum value after scaling.

name

Optional name for the new scaled variable when a single variable is provided. By default, the name will be the original variable name suffixed with the range. For example, "variable" becomes "variable_3to5". Negative values are prefixed with "neg" to avoid invalid columns names (e.g., -3 to 3 becomes "variable_neg3to5").

overwrite

Logical. If TRUE, it overwrites the original variable(s) with the scaled values. If FALSE (default), a new variable(s) is created.

See Also

Other scaling: categorize_scale(), center_scale(), dummify_scale(), recode_cat_scale(), reverse_scale(), setna_scale(), z_scale()

Examples

WoJ %>% minmax_scale(autonomy_emphasis, change_to_min = 0,
change_to_max = 1)
WoJ %>% minmax_scale(autonomy_emphasis, name = "my_scaled_variable",
change_to_min = 0, change_to_max = 1)
WoJ %>%
  minmax_scale(autonomy_emphasis, change_to_min = 0, change_to_max = 1) %>%
  tab_frequencies(autonomy_emphasis, autonomy_emphasis_0to1)