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# scipy.stats.mstats.trimboth

`scipy.stats.mstats.``trimboth`(data, proportiontocut=0.20000000000000001, inclusive=(True, True), axis=None)
  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: | data : ndarray Data to trim. proportiontocut : {0.2, float} 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. inclusive : {(True, True) tuple} optional Tuple indicating whether the number of data being masked on each side should be rounded (True) or truncated (False). axis : {None, integer}, optional Axis along which to perform the trimming. If None, the input array is first flattened.

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