code: def trimmed_var(
      a,
      limits=(0.1, 0.1),
      inclusive=(1, 1),
      relative=True,
      axis=None,
      ddof=0,
  ):
      """Returns the trimmed variance of the data along the given axis.
  
      %s
      ddof : {0,integer}, optional
          Means Delta Degrees of Freedom. The denominator used during computations
          is (n-ddof). DDOF=0 corresponds to a biased estimate, DDOF=1 to an un-
          biased estimate of the variance.
  
      """ % trimdoc
      if (not isinstance(limits, tuple)) and isinstance(limits, float):
          limits = (limits, limits)
      if relative:
          out = trimr(a, limits=limits, inclusive=inclusive, axis=axis)
      else:
          out = trima(a, limits=limits, inclusive=inclusive)
  
      return out.var(axis=axis, ddof=ddof)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy import ndarray
  import numpy.ma
  from numpy.ma import masked, nomask
  from scipy._lib.six import iteritems
  import itertools
  import warnings
  from collections import namedtuple
  from .None import distributions
  import scipy.special
  from ._stats_mstats_common import _find_repeats, linregress, theilslopes, siegelslopes
label_desc: Use image node_id 32 for calling a global function with example usage: trimmed_var(a, limits, inclusive, relative, axis, ddof) and returns: out