code: def _binding_helper(
      f, kwargs, column_sort, column_id, column_kind, column_value
  ):
      def wrapped_feature_extraction(x):
          if column_sort is not None:
              x = x.sort_values(column_sort)
  
          chunk = Timeseries(
              x[column_id].iloc[0],
              x[column_kind].iloc[0],
              x[column_value],
          )
          result = f(chunk, **kwargs)
  
          result = pd.DataFrame(
              result, columns=[column_id, "variable", "value"]
          )
          result["value"] = result["value"].astype("double")
  
          return result[[column_id, "variable", "value"]]
  
      return wrapped_feature_extraction
  
imports: import itertools
  from collections import defaultdict, namedtuple
  from typing import Iterable, Sized
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: _binding_helper(f, kwargs, column_sort, column_id, column_kind, column_value) and returns: wrapped_feature_extraction, result