View source: R/scale_data_frame.R
scale_data_frame  R Documentation 
scale_data_frame
centers and/or
scales the columns of a data frame (or matrix).
scale_data_frame(x, center = TRUE, scale = TRUE)
x 
a data frame or a numeric matrix (or vector). For matrices or vectors,

center 
either a logical value or numericalike vector of length
equal to the number of columns of 
scale 
either a logical value or a numericalike vector of length
equal to the number of columns of 
The value of center
determines how column centering is
performed. If center
is a numericalike vector with length equal to
the number of numeric/logical columns of x
, then each column of x
has
the corresponding value from center
subtracted from it. If
center
is TRUE
then centering is done by subtracting the
column means (omitting NA
s) of x
from their
corresponding columns, and if center
is FALSE
, no
centering is done.
The value of scale
determines how column scaling is performed
(after centering). If scale
is a numericalike vector with length
equal to the number of numeric/logiocal columns of x
, then each column of
x
is divided by the corresponding value from scale
.
If scale
is TRUE
then scaling is done by dividing the
(centered) columns of x
by their standard deviations if
center
is TRUE
, and the root mean square otherwise.
If scale
is FALSE
, no scaling is done.
The rootmeansquare for a (possibly centered) column is defined as
\sqrt{\sum(x^2)/(n1)}
, where x
is
a vector of the nonmissing values and n
is the number of
nonmissing values. In the case center = TRUE
, this is the
same as the standard deviation, but in general it is not. (To scale
by the standard deviations without centering, use
scale(x, center = FALSE, scale = apply(x, 2, sd, na.rm = TRUE))
.)
For scale.default
, the centered, scaled data frame. Nonnumeric columns are ignored.
Note that logicals are treated as 0/1numerics to be consistent with scale()
.
The numeric centering and scalings used (if any) are returned as attributes
"scaled:center"
and "scaled:scale"
 but only for the numeric/logical columns.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
sweep
which allows centering (and scaling) with
arbitrary statistics.
require(stats)
data(iris)
summary(scale_data_frame(iris))
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