class_docstr: A frequency distribution tells us the frequency of each vocabulary
  item in the text. In general, it could count any kind of observable
  event. It is a distribution because it tells us how the total
  number of word tokens in the text are distributed across the
  vocabulary items.
  
  
  Parameters
  ----------
  features : list, default: None
      The list of feature names from the vectorizer, ordered by index. E.g.
      a lexicon that specifies the unique vocabulary of the corpus. This
      can be typically fetched using the ``get_feature_names()`` method of
      the transformer in Scikit-Learn.
  
  ax : matplotlib axes, default: None
      The axes to plot the figure on.
  
  n: integer, default: 50
      Top N tokens to be plotted.
  
  orient : 'h' or 'v', default: 'h'
      Specifies a horizontal or vertical bar chart.
  
  color : string
      Specify color for bars
  
  kwargs : dict
      Pass any additional keyword arguments to the super class.
  
  These parameters can be influenced later on in the visualization
  process, but can and should be set as early as possible.
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docstr: The finalize method executes any subclass-specific axes
  finalization steps. The user calls show & show calls finalize.
  
  Parameters
  ----------
  kwargs: generic keyword arguments.
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code: def finalize(self, **kwargs):
      """
      The finalize method executes any subclass-specific axes
      finalization steps. The user calls show & show calls finalize.
  
      Parameters
      ----------
      kwargs: generic keyword arguments.
  
      """
      # Set the title
      self.set_title(
          "Frequency Distribution of Top {} tokens".format(self.N)
      )
  
      # Create the vocab, count, and hapaxes labels
      infolabel = "vocab: {:,}\nwords: {:,}\nhapax: {:,}".format(
          self.vocab_, self.words_, self.hapaxes_
      )
  
      self.ax.text(
          0.68,
          0.97,
          infolabel,
          transform=self.ax.transAxes,
          fontsize=9,
          verticalalignment="top",
          bbox={
              "boxstyle": "round",
              "facecolor": "white",
              "alpha": 0.8,
          },
      )
  
      # Set the legend and the grid
      self.ax.legend(loc="upper right", frameon=True)
  
file_path: yellowbrick/yellowbrick/text/freqdist.py
imports: import numpy
  from operator import itemgetter
  from yellowbrick.text.base import TextVisualizer
  from yellowbrick.exceptions import YellowbrickValueError
label_desc: Use image node_id 5 for calling the FrequencyVisualizer obj's underlying member method code with example usage: obj.finalize() without return types