code: def pctsum_updates(df, group, ret_col):
      grp_sums = df.groupby(group)[[ret_col]].sum()
      code = (
          "ordinal_data = df.groupby('{col}')[['{ret_col}']].sum()\n"
          "ordinal_data = ordinal_data / ordinal_data.sum()"
      ).format(col=group, ret_col=ret_col)
      return grp_sums / grp_sums.sum(), [code]
  
imports: import numpy
  import pandas
  import plotly.express
  import plotly.graph_objs
  import pprint
  import scipy.stats
  import time
  import dtale.global_state
  import dtale.pandas_util
  from dtale.code_export import build_code_export, build_final_chart_code
  from dtale.column_builders import clean, clean_code
  from dtale.describe import load_describe
  from dtale.query import build_query, load_filterable_data
  from dtale.utils import apply, classify_type, find_dtype, find_dtype_formatter, find_selected_column, get_bool_arg, get_int_arg, get_str_arg, grid_columns, grid_formatter, json_float, json_timestamp, make_list
label_desc: Use image node_id 2 for calling a global function with example usage: pctsum_updates(df, group, ret_col) and returns: unknown,  list