scipy.stats.mstats.trimboth#
- scipy.stats.mstats.trimboth(data, proportiontocut=0.2, inclusive=(True, True), axis=None)[source]#
Trims the smallest and largest data values.
Trims the data by masking the
int(proportiontocut * n)smallest andint(proportiontocut * n)largest values of data along the given axis, where n is the number of unmasked values before trimming.- Parameters
- datandarray
Data to trim.
- proportiontocutfloat, optional
Percentage of trimming (as a float between 0 and 1). If n is the number of unmasked values before trimming, the number of values after trimming is
(1 - 2*proportiontocut) * n. Default is 0.2.- inclusive{(bool, bool) tuple}, optional
Tuple indicating whether the number of data being masked on each side should be rounded (True) or truncated (False).
- axisint, optional
Axis along which to perform the trimming. If None, the input array is first flattened.