class_docstr: Plot functions for mixed type x & y axes:
  
  Methods:
      - bar
      - bar_stacked
      - lollipop
      - parallel
class_docstr_tok: ["Plot","functions","for","mixed","type","x","&","y","axes",":","Methods",":","-","bar","-","bar_stacked","-","lollipop","-","parallel"]
docstr: Bar chart.
  
  Note:
      To change the orientation set x_axis_type or y_axis_type
      argument of the Chart object.
  
  Args:
      data_frame (pandas.DataFrame): Data source for the plot.
      categorical_columns (str or list): Column name to plot on
          the categorical axis.
      numeric_column (str): Column name to plot on the numerical axis.
      color_column (str, optional): Column name to group by on
          the color dimension.
      color_order (list, optional): List of values within the
          'color_column' for specific color sort.
      categorical_order_by (str or array-like, optional):
          Dimension for ordering the categorical axis. Default 'values'.
          - 'values': Order categorical axis by the numerical
              axis values. Default.
          - 'labels': Order categorical axis by the categorical labels.
          - array-like object (list, tuple, np.array): New labels
              to conform the categorical axis to.
      categorical_order_ascending (bool, optional): Sort order of the
          categorical axis. Default False.
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code: def bar(
      self,
      data_frame,
      categorical_columns,
      numeric_column,
      color_column=None,
      color_order=None,
      categorical_order_by="values",
      categorical_order_ascending=False,
  ):
      """Bar chart.
  
      Note:
          To change the orientation set x_axis_type or y_axis_type
          argument of the Chart object.
  
      Args:
          data_frame (pandas.DataFrame): Data source for the plot.
          categorical_columns (str or list): Column name to plot on
              the categorical axis.
          numeric_column (str): Column name to plot on the numerical axis.
          color_column (str, optional): Column name to group by on
              the color dimension.
          color_order (list, optional): List of values within the
              'color_column' for specific color sort.
          categorical_order_by (str or array-like, optional):
              Dimension for ordering the categorical axis. Default 'values'.
              - 'values': Order categorical axis by the numerical
                  axis values. Default.
              - 'labels': Order categorical axis by the categorical labels.
              - array-like object (list, tuple, np.array): New labels
                  to conform the categorical axis to.
          categorical_order_ascending (bool, optional): Sort order of the
              categorical axis. Default False.
      """
      vertical = self._chart.axes._vertical
  
      source, factors, _ = self._construct_source(
          data_frame,
          categorical_columns,
          numeric_column,
          categorical_order_by=categorical_order_by,
          categorical_order_ascending=categorical_order_ascending,
          color_column=color_column,
      )
  
      colors, color_values = self._get_color_and_order(
          data_frame, color_column, color_order, categorical_columns
      )
  
      if color_column is None:
          colors = colors[0]
  
      self._set_categorical_axis_default_factors(vertical, factors)
      self._set_categorical_axis_default_range(
          vertical, data_frame, numeric_column
      )
      bar_width = self._get_bar_width(factors)
  
      if color_column:
          legend = bokeh.core.properties.field("color_column")
          legend = "color_column"
      else:
          legend = None
  
      if vertical:
          self._plot_with_legend(
              self._chart.figure.vbar,
              legend_group=legend,
              x="factors",
              width=bar_width,
              top=numeric_column,
              bottom=0,
              line_color="white",
              source=source,
              fill_color=colors,
          )
  
      else:
          self._plot_with_legend(
              self._chart.figure.hbar,
              legend_group=legend,
              y="factors",
              height=bar_width,
              right=numeric_column,
              left=0,
              line_color="white",
              source=source,
              fill_color=colors,
          )
  
      # Set legend defaults if there are multiple series.
      if color_column is not None:
          self._chart.style._apply_settings("legend")
      return self._chart
  
imports: import bokeh
  import pandas
  import numpy
  from chartify._core.colors import Color, color_palettes
  from chartify._core.axes import NumericalYMixin, NumericalXMixin
  from scipy.stats import gaussian_kde
label_desc: Use image node_id 10 for calling the PlotMixedTypeXY obj's underlying member method code with example usage: obj.bar(data_frame, categorical_columns, numeric_column, color_column, color_order, categorical_order_by, categorical_order_ascending) and returns: self