class_docstr: Encapsulates the data within a split of feature space.
  Primarily used to cache computations on the data for better performance
  
  Parameters
  ----------
  X: np.ndarray
      The subset of the covariate matrix that falls into the split
  y: np.ndarray
      The subset of the target array that falls into the split
  normalize: bool
      Whether to map the target into -0.5, 0.5
  cache: bool
      Whether to cache common values.
      You really only want to turn this off if you're not going to the resulting object for anything (e.g. when testing)
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code: def __add__(self, other: SplitCondition) -> "Data":
      updated_mask = self.X.update_mask(other)
  
      return Data(
          self.X.values,
          self.y.values,
          updated_mask,
          normalize=False,
          unique_columns=self._X._unique_columns,
          splittable_variables=self._X._splittable_variables,
          y_sum=other.carry_y_sum,
          n_obsv=other.carry_n_obsv,
      )
  
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 6 for calling the Data obj's underlying member method code with example usage: obj.__add__(other) and returns: Data