code: def plot_disparity_bubble_chart(
      disparity_df,
      metrics_list,
      attribute,
      fairness_threshold=1.25,
      chart_height=None,
      chart_width=Disparity_Chart.full_width,
      accessibility_mode=False,
  ):
      """Draws bubble chart to visualize disparity in selected metrics versus that of a
      reference group for a given attribute.
  
      :param disparity_df: a dataframe generated by the Aequitas Bias class
      :type disparity_df: pandas.core.frame.DataFrame
      :param metrics_list: a list of the metrics of interest
      :type metrics_list: list
      :param attribute: an attribute to plot
      :type attribute: str
      :param fairness_threshold: a value for the maximum allowed disparity, defaults to 1.25
      :type fairness_threshold: float, optional
      :param chart_height: a value (in pixels) for the height of the chart
      :type chart_height: int, optional
      :param chart_width: a value (in pixels) for the width of the chart
      :type chart_width: int, optional
      :param accessibility_mode: a switch for the display of more accessible visual elements, defaults to False
      :type accessibility_mode: bool, optional
  
      :return: the full disparities chart
      :rtype: Altair chart object
      """
  
      (
          plot_table,
          metrics,
          ref_group,
          global_scales,
          chart_height,
          chart_width,
          selection,
      ) = Initializer.prepare_bubble_chart(
          disparity_df,
          metrics_list,
          attribute,
          fairness_threshold,
          chart_height,
          chart_width,
          Disparity_Chart,
          accessibility_mode,
      )
  
      # GET MAIN CHART COMPONENTS
      main_chart = get_disparity_bubble_chart_components(
          plot_table,
          metrics,
          ref_group,
          global_scales,
          selection,
          fairness_threshold,
          chart_height,
          chart_width,
          accessibility_mode,
      )
  
      # ADD LEGEND
      legend = draw_legend(global_scales, selection, chart_width)
      full_chart = main_chart + legend
  
      # FINALIZE CHART
      disparity_chart = (
          full_chart.configure_view(
              strokeWidth=0,
          )
          .configure_axisLeft(
              labelFontSize=Metric_Axis.label_font_size,
              labelColor=Metric_Axis.label_color,
              labelFont=FONT,
          )
          .configure_title(
              font=FONT,
              fontWeight=Chart_Title.font_weight,
              fontSize=Chart_Title.font_size,
              color=Chart_Title.font_color,
              anchor=Chart_Title.anchor,
              offset=Chart_Title.offset,
          )
          .properties(
              height=chart_height,
              width=chart_width,
              title=f"Disparities on {attribute.title()}",
              padding={
                  "top": Disparity_Chart.full_chart_padding,
                  "bottom": -FONT_SIZE_SMALL * 2 / 3 * len(metrics_list)
                  + Disparity_Chart.full_chart_padding,
                  "left": Disparity_Chart.full_chart_padding,
                  "right": Disparity_Chart.full_chart_padding,
              },
              usermeta=get_chart_metadata("disparity_chart"),
          )
          .resolve_scale(y="independent", size="independent")
      )
  
      return disparity_chart
  
imports: import math
  import altair
  import pandas
  from aequitas.plot.commons.helpers import no_axis, transform_ratio, get_chart_metadata
  from aequitas.plot.commons.legend import draw_legend
  from aequitas.plot.commons.scales import get_chart_size_range
  from aequitas.plot.commons.tooltips import get_tooltip_text_group_size, get_tooltip_text_disparity_explanation
  from aequitas.plot.commons.style.classes import Metric_Axis, Axis, Annotation, Reference_Rule, Threshold_Rule, Threshold_Band, Bubble, Chart_Title
  from aequitas.plot.commons.style.text import FONT, FONT_SIZE_SMALL
  from aequitas.plot.commons.style.sizes import Disparity_Chart
  from aequitas.plot.commons import initializers
  from aequitas.plot.commons import labels
label_desc: Use image node_id 13 for calling a global function with example usage: plot_disparity_bubble_chart(disparity_df, metrics_list, attribute, fairness_threshold, chart_height, chart_width, accessibility_mode) and returns: disparity_chart