datawizard (version 0.4.0)

data_rescale: Rescale Variables to a New Range

Description

Rescale variables to a new range. Can also be used to reverse-score variables (change the keying/scoring direction).

Usage

data_rescale(x, ...)
change_scale(x, ...)
# S3 method for numeric
data_rescale(x, to = c(0, 100), range = NULL, verbose = TRUE, ...)
# S3 method for data.frame
data_rescale(
  x,
  to = c(0, 100),
  range = NULL,
  select = NULL,
  exclude = NULL,
  ignore_case = FALSE,
  ...
)

Arguments

x

A (grouped) data frame, numeric vector or factor.

...

Arguments passed to or from other methods.

to

Numeric vector of length 2 giving the new range that the variable will have after rescaling. To reverse-score a variable, the range should be given with the maximum value first. See examples.

range

Initial (old) range of values. If NULL, will take the range of the input vector (range(x)).

verbose

Toggle warnings.

select

Variables that will be included when performing the required tasks. Can be either

• a variable specified as a literal variable name (e.g., column_name),

• a string with the variable name (e.g., "column_name"), or a character vector of variable names (e.g., c("col1", "col2", "col3")),

• a formula with variable names (e.g., ~column_1 + column_2),

• a vector of positive integers, giving the positions counting from the left (e.g. 1 or c(1, 3, 5)),

• a vector of negative integers, giving the positions counting from the right (e.g., -1 or -1:-3),

• or one of the following select-helpers: starts_with(""), ends_with(""), contains(""), a range using : or regex("").

If NULL, selects all columns.

exclude

See select, however, column names matched by the pattern from exclude will be excluded instead of selected. If NULL (the default), excludes no columns.

ignore_case

Logical, if TRUE and when one of the select-helpers or a regular expression is used in select, ignores lower/upper case in the search pattern when matching against variable names.

Value

A rescaled object.

See Also

Other transform utilities: data_reverse(), normalize(), ranktransform(), standardize()

Examples

# NOT RUN {
data_rescale(c(0, 1, 5, -5, -2))
data_rescale(c(0, 1, 5, -5, -2), to = c(-5, 5))
data_rescale(c(1, 2, 3, 4, 5), to = c(-2, 2))

# Specify the "theoretical" range of the input vector
data_rescale(c(1, 3, 4), to = c(0, 40), range = c(0, 4))

# Reverse-score a variable
data_rescale(c(1, 2, 3, 4, 5), to = c(5, 1))
data_rescale(c(1, 2, 3, 4, 5), to = c(2, -2))

# Data frames
head(data_rescale(iris, to = c(0, 1)))
head(data_rescale(iris, to = c(0, 1), select = "Sepal.Length"))

# One can specify a list of ranges
head(data_rescale(iris, to = list(
  "Sepal.Length" = c(0, 1),
  "Petal.Length" = c(-1, 0)
)))
# }