class_docstr: Container for distributions.
  
  This class (object) is returned from the ``distribution`` function. The
  attributes documented below can be accessed or extracted.
  
  Attributes:
      input_data: The input data
      spike_value: Measure of the "spikey"ness metric, which diagnoses spikey
          histograms where the tallest bin is ``n`` times taller than the average bin.
      skew_value: Measure of the skewness metric.
      spike_factor: The threshold factor used to diagnose "spikey"ness.
      skew_factor: The threshold factor used to diagnose skew.
docstr: Distribution Plots.
  
  Args:
      input_data: The input data
      spike_value: Measure of the "spikey"ness metric, which diagnoses spikey
          histograms where the tallest bin is ``n`` times taller than the average bin.
      skew_value: Measure of the skewness metric.
      spike_factor: The threshold factor used to diagnose "spikey"ness.
      skew_factor: The threshold factor used to diagnose skew.
      viz_backend: The visualization backend.
docstr_tok: ["Distribution","Plots",".","Args",":","input_data",":","The","input","data","spike_value",":","Measure","of","the","``","spikey","''","ness","metric",",","which","diagnoses","spikey","histograms","where","the","tallest","bin","is","``","n","``","times","taller","than","the","average","bin",".","skew_value",":","Measure","of","the","skewness","metric",".","spike_factor",":","The","threshold","factor","used","to","diagnose","``","spikey","''","ness",".","skew_factor",":","The","threshold","factor","used","to","diagnose","skew",".","viz_backend",":","The","visualization","backend","."]
code: def __init__(
      self,
      input_data=None,
      spike_value=None,
      skew_value=None,
      spike_factor=None,
      skew_factor=None,
      viz_backend=None,
  ):
      """Distribution Plots.
  
      Args:
          input_data: The input data
          spike_value: Measure of the "spikey"ness metric, which diagnoses spikey
              histograms where the tallest bin is ``n`` times taller than the average bin.
          skew_value: Measure of the skewness metric.
          spike_factor: The threshold factor used to diagnose "spikey"ness.
          skew_factor: The threshold factor used to diagnose skew.
          viz_backend: The visualization backend.
      """
      self.input_data = input_data
      self.spike_value = spike_value
      self.skew_value = skew_value
      self.spike_factor = spike_factor
      self.skew_factor = skew_factor
      self.viz_backend = viz_backend
  
imports: from typing import Dict, Any, Optional
  from matplotlib.figure import Figure
  from matplotlib.gridspec import GridSpec
  import seaborn
  import numpy
  from data_describe.config._config import get_option
  from data_describe.metrics.univariate import spikey, skewed
  from data_describe._widget import BaseWidget
  from data_describe.compat import _is_dataframe
  from data_describe.backends import _get_viz_backend, _get_compute_backend
label_desc: Use image node_id 1 to create a new DistributionWidget object from inherited base classes: BaseWidget with example: obj = DistributionWidget(input_data, spike_value, skew_value, spike_factor, skew_factor, viz_backend)