Package 'normalize'

Normalize numeric data

Description

Center and scale vectors, matrices, data frames, or lists of these objects.

Usage

normalize(x, center = TRUE, scale = TRUE, ...)

## Default S3 method:
normalize(x, ...)

## S3 method for class 'numeric'
normalize(x, center = TRUE, scale = TRUE, ...)

## S3 method for class 'matrix'
normalize(
  x,
  center = TRUE,
  scale = TRUE,
  byrow = FALSE,
  ignore = integer(),
  jointly = list(),
  ...
)

## S3 method for class 'data.frame'
normalize(
  x,
  center = TRUE,
  scale = TRUE,
  byrow = FALSE,
  ignore = integer(),
  jointly = list(),
  ...
)

## S3 method for class 'list'
normalize(x, center = TRUE, scale = TRUE, ...)

Arguments

x	An object to be normalized.
center	[logical(1)] Should values be centered to zero mean?
scale	[logical(1)] Should values be scaled to unit variance?
...	Further arguments to be passed to or from other methods.
byrow	[logical(1)] Only relevant if x has two dimensions (rows and columns). In this case, set to TRUE to normalize row-wise or FALSE to normalize column-wise (default).
ignore	[integer()] Only relevant if x has two dimensions (rows and columns). Indices to leave unchanged. With byrow = TRUE, these are row indices. With byrow = FALSE, these are column indices. This is useful, for example, to keep identifier or non-numeric columns in a data frame.
jointly	[list()] Only relevant if x has two dimensions (rows and columns). A list of disjoint index groups to normalize jointly. With byrow = TRUE, these are row indices. With byrow = FALSE, these are column indices.

Value

A normalized version of x, preserving attributes where possible. Lists return a list with each element normalized. The centering and scaling values used are stored in the "center" and "scale" attributes where relevant.

Examples

# can normalize vectors, matrices, data.frames, and lists of such types
normalize(
  list(
    c(-3, 0, 3),
    matrix(1:12, nrow = 3, ncol = 4),
    data.frame(a = 1:3, b = 4:6, c = 7:9, d = 10:12)
  )
)

# can ignore columns (or rows)
normalize(
  data.frame(a = 1:3, b = c("A", "B", "C"), c = 7:9, d = 10:12),
  ignore = 2
)

# can normalize columns (or rows) jointly
normalize(
  matrix(1:12, nrow = 3, ncol = 4),
  jointly = list(1:2, 3:4)
)

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