Apply column-wise or row-wise scaling to numeric columns in a matrix or
data.frame prior to constructing a heat_map.
heat_map_scale(x, scale = "column", method = "range")matrix-like object to be scaled.
indicates whether the data should be scaled by "row" or
"column", set to "column" by default.
type of scaling to perform, can be either 'range',
'mean' or 'zscore'. Range scaling normalizes the data to have
limits between 0 and 1. Mean scaling subtracts the mean (calculated
excluding missing values) from each value. Z-score scaling subtracts the
mean from each value and then divides the result by the standard deviation.
# Range scaling
mtcars_scale_range <- heat_map_scale(mtcars,
method = "range")
#> Applying range scaling to each column...
# Mean scaling
mtcars_scale_mean <- heat_map_scale(mtcars,
method = "mean")
#> Applying mean scaling to each column...
# Z-score scaling
mtcars_scale_zscore <- heat_map_scale(mtcars,
method = "zscore")
#> Applying zscore scaling to each column...