Package 'normalize'

Centering and scaling of numeric data

Description

normalize numeric data saved as a vector, matrix, data.frame, or list to have zero mean and / or unit variance

Usage

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

## 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	TRUE to normalize to zero mean or FALSE for no centering
scale	TRUE to normalize to unit variance or FALSE for no scaling
...	further arguments to be passed to or from other methods
byrow	TRUE to normalize row-wise or FALSE to normalize column-wise
ignore	an integer vector of column indices (or row indices if byrow = TRUE) to not normalize
jointly	a list of disjoint integer vectors of column indices (or row indices if byrow = TRUE) to normalize jointly

Value

the normalized input x with the numeric centering and scaling values used (if any) added as attributes "center" and "scale" (ignored columns and rows get centering and scaling values of NA)

Examples

# can normalize numeric vectors, matrices, data.frames, and lists of those
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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