datawizard (version 0.4.0)

normalize: Normalize numeric variable to 0-1 range

Description

Performs a normalization of data, i.e., it scales variables in the range 0 -

1. This is a special case of data_rescale().

Usage

normalize(x, ...)
# S3 method for numeric
normalize(x, include_bounds = TRUE, verbose = TRUE, ...)
# S3 method for data.frame
normalize(
  x,
  include_bounds = TRUE,
  select = NULL,
  exclude = NULL,
  ignore_case = FALSE,
  verbose = TRUE,
  ...
)

Arguments

x

A numeric vector, (grouped) data frame, or matrix. See 'Details'.

...

Arguments passed to or from other methods.

include_bounds

Logical, if TRUE, return value may include 0 and 1. If FALSE, the return value is compressed, using Smithson and Verkuilen's (2006) formula (x * (n - 1) + 0.5) / n, to avoid zeros and ones in the normalized variables. This can be useful in case of beta-regression, where the response variable is not allowed to include zeros and ones.

verbose

Toggle warnings and messages on or off.

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 normalized object.

Details

• If x is a matrix, normalization is performed across all values (not column- or row-wise). For column-wise normalization, convert the matrix to a data.frame.

• If x is a grouped data frame (grouped_df), normalization is performed separately for each group.

References

Smithson M, Verkuilen J (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(1), 54<U+2013>71.

See Also

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

Examples

# NOT RUN {
normalize(c(0, 1, 5, -5, -2))
normalize(c(0, 1, 5, -5, -2), include_bounds = FALSE)

head(normalize(trees))

# }