code: def cat_group(dfx, kpix, n_group=10):
      """
      Category Reduction for Categorical Variables
  
      Args
      ----
  
      dfx : dataframe
          The inputs data dataframe.
  
      kpix : string
          The column of the feature.
  
      n_group : int, optional (default = 10)
          The number of top category values to be remained, other category values will be put into "Other".
  
      Returns
      -------
      The transformed categorical feature value list.
      """
      if dfx[kpix].nunique() > n_group:
          # get the top categories
          top = dfx[kpix].isin(dfx[kpix].value_counts().index[:n_group])
          dfx.loc[~top, kpix] = "Other"
          return dfx[kpix].values
      else:
          return dfx[kpix].values
  
file_path: causalml/causalml/inference/tree/utils.py
imports: import time
  from typing import Callable
  import numpy
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: cat_group(dfx, kpix, n_group) and returns: dfx, dfx