docstr: Find default values for discrete hist estimation based on variable type.
docstr_tok: ["Find","default","values","for","discrete","hist","estimation","based","on","variable","type","."]
code: def _default_discrete(self):
      """Find default values for discrete hist estimation based on variable type."""
      if self.univariate:
          discrete = self.var_types[self.data_variable] == "categorical"
      else:
          discrete_x = self.var_types["x"] == "categorical"
          discrete_y = self.var_types["y"] == "categorical"
          discrete = discrete_x, discrete_y
      return discrete
  
imports: from numbers import Number
  from functools import partial
  import math
  import textwrap
  import warnings
  import numpy
  import pandas
  import matplotlib
  import matplotlib.pyplot
  import matplotlib.transforms
  from matplotlib.cbook import normalize_kwargs
  from matplotlib.colors import to_rgba
  from matplotlib.collections import LineCollection
  from ._base import VectorPlotter
  from ._statistics import ECDF, Histogram, KDE
  from ._stats.counting import Hist
  from .axisgrid import FacetGrid, _facet_docs
  from .utils import remove_na, _get_transform_functions, _kde_support, _check_argument, _assign_default_kwargs, _default_color
  from .palettes import color_palette
  from .external import husl
  from .external.kde import gaussian_kde
  from ._docstrings import DocstringComponents, _core_docs
label_desc: Use image node_id 9 for calling the _DistributionPlotter obj's underlying member method code with example usage: obj._default_discrete() and returns: discrete