class_docstr: Visualize the given SHAP values with a waterfall layout
  
  Parameters
  ----------
  display_rows: bool, default = False
      if `True` then display the row before the explanation chart
  headers: bool, default = False
      if `True` then render headers
  namespace: str, default = None
      namespace to use; can be nested like `ns_a.ns_b.ns_c`
  
  Examples
  --------
  >>> import autogluon.eda.analysis as eda
  >>> import autogluon.eda.visualization as viz
  >>> import autogluon.eda.auto as auto
  >>>
  >>> rows_to_explain = ...  # DataFrame
  >>>
  >>> auto.analyze(
  >>>     train_data=..., model=...,
  >>>     anlz_facets=[
  >>>         eda.explain.ShapAnalysis(rows_to_explain),
  >>>     ],
  >>>     viz_facets=[
  >>>         viz.explain.ExplainWaterfallPlot(),
  >>>     ]
  >>> )
  
  See Also
  --------
  :py:class:`~shap.KernelExplainer`
  :py:class:`~autogluon.eda.analysis.explain.ShapAnalysis`
class_docstr_tok: ["Visualize","the","given","SHAP","values","with","a","waterfall","layout","Parameters","--","--","--","--","--","display_rows",":","bool",",","default","=","False","if","`","True","`","then","display","the","row","before","the","explanation","chart","headers",":","bool",",","default","=","False","if","`","True","`","then","render","headers","namespace",":","str",",","default","=","None","namespace","to","use",";","can","be","nested","like","`","ns_a.ns_b.ns_c","`","Examples","--","--","--","--",">",">",">","import","autogluon.eda.analysis","as","eda",">",">",">","import","autogluon.eda.visualization","as","viz",">",">",">","import","autogluon.eda.auto","as","auto",">",">",">",">",">",">","rows_to_explain","=","...","#","DataFrame",">",">",">",">",">",">","auto.analyze","(",">",">",">","train_data=","...",",","model=","...",",",">",">",">","anlz_facets=","[",">",">",">","eda.explain.ShapAnalysis","(","rows_to_explain",")",",",">",">",">","]",",",">",">",">","viz_facets=","[",">",">",">","viz.explain.ExplainWaterfallPlot","(",")",",",">",">",">","]",">",">",">",")","See","Also","--","--","--","--",":","py",":","class",":","`","~shap.KernelExplainer","`",":","py",":","class",":","`","~autogluon.eda.analysis.explain.ShapAnalysis","`"]
code: def _render_internal(
      self,
      expected_value,
      shap_values,
      features,
      explainer,
      feature_names,
      **kwargs,
  ):
      shap.waterfall_plot(
          shap.Explanation(
              shap_values,
              base_values=expected_value,
              output_names=features,
              feature_names=features.index,
          )
      )
  
file_path: autogluon/eda/src/autogluon/eda/visualization/explain.py
imports: from abc import ABC, abstractmethod
  from typing import Optional
  import shap
  from autogluon.eda import AnalysisState
  from autogluon.eda.visualization.base import AbstractVisualization
  from autogluon.eda.visualization.jupyter import JupyterMixin
label_desc: Use image node_id 1 for calling the ExplainWaterfallPlot obj's underlying member method code with example usage: obj._render_internal(expected_value, shap_values, features, explainer, feature_names) without return types