An important note- The equivelent call in R would be something like
r
N <- nrow(x)
scale(x, scale= apply(x, 2, sd) * sqrt(N-1/N))
This is because R uses degrees of freedom = 1 to calculate standard deviation.
Multiplying the standard deviation by sqrt(N-1/N) 'undoes' this correction.
The StandardScaler of sklearn uses degrees of freedom = 0 for its calculation, so results
should be similar.
Scales columns to mean 0 and unit variance
An important note- The equivelent call in R would be something like
r N <- nrow(x) scale(x, scale= apply(x, 2, sd) * sqrt(N-1/N))
This is because R uses degrees of freedom = 1 to calculate standard deviation. Multiplying the standard deviation by sqrt(N-1/N) 'undoes' this correction.
The StandardScaler of sklearn uses degrees of freedom = 0 for its calculation, so results should be similar.