code: def _seaborn_viz_bar(
      data, x: str, contrast: Optional[str] = None, **kwargs
  ):
      """Plot a bar chart (count plot) for categorical features.
  
      Args:
          data (DataFrame): The data
          x (str): The name of the column to plot.
          contrast (str, optional): The name of the column to use for multiple histograms.
          **kwargs: Keyword arguments passed to seaborn.countplot
  
      Returns:
          Seaborn Axis Object
      """
      default_bar_kwargs = {"orient": "h"}
      bar_kwargs = {**default_bar_kwargs, **(kwargs or {})}
      if contrast:
          ax = sns.countplot(x=x, hue=contrast, data=data, **bar_kwargs)
      else:
          ax = sns.countplot(x=x, data=data, **bar_kwargs)
      return ax
  
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 8 for calling a global function with example usage: _seaborn_viz_bar(data, x, contrast) and returns: ax