class_docstr: Class defining categorical distribution type functionality
docstr: Expand the named columns to include category names.
  
  Args:
      idx_col: The original index to column mapping.
  
  Returns:
      Updated index to column mapping.
docstr_tok: ["Expand","the","named","columns","to","include","category","names",".","Args",":","idx_col",":","The","original","index","to","column","mapping",".","Returns",":","Updated","index","to","column","mapping","."]
code: def update_idx_col(self, idx_col: Dict[int, str]) -> Dict[int, str]:
      """
      Expand the named columns to include category names.
  
      Args:
          idx_col: The original index to column mapping.
  
      Returns:
          Updated index to column mapping.
      """
      new_idx_cols = {}
      colname = idx_col.pop(self.idx_group[0])
      for catidx, idx in enumerate(self.idx_group):
          new_idx_cols[idx] = self.make_node_name(colname, catidx)
      return {**idx_col, **new_idx_cols}
  
imports: from copy import deepcopy
  from typing import Dict, List, Tuple
  import numpy
  import torch
  from sklearn.preprocessing import OneHotEncoder
  from torch import nn
  from causalnex.structure.pytorch.dist_type._base import DistTypeBase, ExpandColumnsMixin
  from causalnex.structure.structuremodel import StructureModel
label_desc: Use image node_id 12 for calling the DistTypeCategorical obj's underlying member method code with example usage: obj.update_idx_col(idx_col) and returns: dict