code: def get_p_first_name_given_race_df():
      # p(first|race) = (p(race|first) * p(first)) / p(race)
      total_count = p_race_given_first_name_df["count"].sum()
      p_first_name = p_race_given_first_name_df["count"] / total_count
      p_race = (
          p_race_given_first_name_df[races_columns]
          .multiply(p_race_given_first_name_df["count"].values, axis=0)
          .sum(axis=0)
          .div(total_count)
      )
      p_first_name_given_race_df = (
          p_race_given_first_name_df[races_columns]
          .multiply(p_first_name, axis=0)
          .div(p_race, axis=1)
          .fillna(value=0)
      )
      return p_first_name_given_race_df
  
file_path: bias-detector/bias_detector/p_groups_lookup.py
imports: import pandas
  import numpy
  import os
  import sys
label_desc: Use image node_id 4 for calling a global function with example usage: get_p_first_name_given_race_df() and returns: p_first_name_given_race_df