class_docstr: Summarize the results of the XShiftDetector.  It will render the results as markdown in jupyter.
  This will contain the detection status (True if detected), the details of the hypothesis test (test
  statistic, pvalue), and the feature importances for the detection.
code: def __init__(
      self,
      headers: bool = False,
      namespace: Optional[str] = None,
      **kwargs,
  ) -> None:
      super().__init__(namespace, **kwargs)
      self.headers = headers
  
file_path: autogluon/eda/src/autogluon/eda/visualization/shift.py
imports: from typing import Optional
  from ..None import AnalysisState
  from .base import AbstractVisualization
  from .jupyter import JupyterMixin
label_desc: Use image node_id 1 to create a new XShiftSummary object from inherited base classes: AbstractVisualization, JupyterMixin with example: obj = XShiftSummary(headers, namespace)