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scipy.stats.mstats.

# trimboth

scipy.stats.mstats.trimboth(data, proportiontocut=0.2, inclusive=(True, True), axis=None)

  Trims the smallest and largest data values.

  Trims the data by masking the `int(proportiontocut * n)` smallest and `int(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.