def trimboth(data, proportiontocut=<NUM_LIT>, inclusive=(True,True), axis=None):
return trimr(data, limits=(proportiontocut,proportiontocut),<EOL>inclusive=inclusive, axis=axis)<EOL>
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
----------
data : ndarray
    Data to trim.
proportiontocut : 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``.
    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).
axis : int, optional
    Axis along which to perform the trimming.
    If None, the input array is first flattened.