docstr: Identify whether feature contains only unique values, i.e. it has no duplicated values
  Useful to provide a faster way to calculate the probability of a value being selected in a variable
  
  Returns
  -------
  List[int]
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code: def is_column_unique(self, i: int) -> bool:
      """
      Identify whether feature contains only unique values, i.e. it has no duplicated values
      Useful to provide a faster way to calculate the probability of a value being selected in a variable
  
      Returns
      -------
      List[int]
      """
      if self._unique_columns[i] is None:
          self._unique_columns[i] = (
              len(np.unique(self.get_column(i))) == self._n_obsv
          )
      return self._unique_columns[i]
  
imports: from operator import gt, le
  from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from .errors import NoSplittableVariableException
  from .splitcondition import SplitCondition
label_desc: Use image node_id 9 for calling the CovariateMatrix obj's underlying member method code with example usage: obj.is_column_unique(i) and returns: self