1.1.14. patsy.standardize¶

patsy.standardize(x, center=True, rescale=True, ddof=0)¶

A stateful transform that standardizes input data, i.e. it subtracts the mean and divides by the sample standard deviation.

Either centering or rescaling or both can be disabled by use of keyword arguments. The ddof argument controls the delta degrees of freedom when computing the standard deviation (cf. numpy.std()). The default of ddof=0 produces the maximum likelihood estimate; use ddof=1 if you prefer the square root of the unbiased estimate of the variance.

If input has multiple columns, standardizes each column separately.

Note

This function computes the mean and standard deviation using a memory-efficient online algorithm, making it suitable for use with large incrementally processed data-sets.