code: def __create_group_rank_variable(attribute_df, metric):
      """Creates the disparity rank variable for the given metric, centered around 0 (the Reference Group's value)."""
  
      # RANK
      attribute_df[f"{metric}_disparity_rank"] = attribute_df[
          f"{metric}_disparity_scaled"
      ].rank(method="first")
  
      # REFERENCE GROUP RANK
      reference_rank = attribute_df.loc[
          attribute_df[f"{metric}_parity_result"] == "Reference"
      ][f"{metric}_disparity_rank"].iloc[0]
  
      # CENTERED RANK
      attribute_df[f"{metric}_disparity_rank"] = (
          attribute_df[f"{metric}_disparity_rank"] - reference_rank
      )
  
imports: import altair
  import pandas
  from aequitas.plot.commons.helpers import no_axis, transform_ratio, format_number, get_chart_metadata
  from aequitas.plot.commons.tooltips import get_tooltip_text_group_size, get_tooltip_text_disparity_explanation, get_tooltip_text_parity_test_explanation
  from aequitas.plot.commons.style.classes import Title, Subtitle, Parity_Result, Annotation, Legend
  from aequitas.plot.commons.style.text import FONT
  from aequitas.plot.commons.style.sizes import Summary_Chart
  from aequitas.plot.commons import initializers
  from aequitas.plot.commons import validators
  from aequitas.plot.commons import labels
label_desc: Use image node_id 11 for calling a global function with example usage: __create_group_rank_variable(attribute_df, metric) without return types