code: def _get_mask(X, value_to_mask):
      
      if is_scalar_nan(value_to_mask):
          if X.dtype.kind == "f":
              return np.isnan(X)
          elif X.dtype.kind in ("i", "u"):
              # can't have NaNs in integer array.
              return np.zeros(X.shape, dtype=bool)
          else:
              # np.isnan does not work on object dtypes.
              return _object_dtype_isnan(X)
      else:
          # X == value_to_mask with object dytpes does not always perform
          # element-wise for old versions of numpy
          return np.equal(X, value_to_mask)
docs: Compute the boolean mask X == missing_values.