code: def read_p_race_given_first_name_file():
      rename_dict = {
          "firstname": "first_name",
          "obs": "count",
          "pctwhite": "white",
          "pctblack": "black",
          "pctapi": "api",
          "pcthispanic": "hispanic",
          "pctaian": "native",
          "pct2prace": "multiple",
      }
      p_race_given_first_name_df = pd.read_csv(
          curr_path + "/resources/firstnames.csv", index_col="firstname"
      ).rename(columns=rename_dict)
      p_race_given_first_name_df.index = (
          p_race_given_first_name_df.index.str.upper()
      )
      p_race_given_first_name_df[races_columns] = (
          p_race_given_first_name_df[races_columns] / 100.0
      )
      return p_race_given_first_name_df[["count"] + races_columns]
  
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 2 for calling a global function with example usage: read_p_race_given_first_name_file() and returns: p_race_given_first_name_df