docstr: Computes and returns local contributions using Shap explainer
  
  Parameters
  ----------
  x : pd.DataFrame
      The observations dataframe used by the model
  
  Returns
  -------
  explain_data : pd.DataFrame or list of pd.DataFrame
      local contributions
docstr_tok: ["Computes","and","returns","local","contributions","using","Shap","explainer","Parameters","--","--","--","--","--","x",":","pd.DataFrame","The","observations","dataframe","used","by","the","model","Returns","--","--","--","-","explain_data",":","pd.DataFrame","or","list","of","pd.DataFrame","local","contributions"]
code: def run_explainer(self, x: pd.DataFrame) -> dict:
      """
      Computes and returns local contributions using Shap explainer
  
      Parameters
      ----------
      x : pd.DataFrame
          The observations dataframe used by the model
  
      Returns
      -------
      explain_data : pd.DataFrame or list of pd.DataFrame
          local contributions
      """
      print("INFO: Shap explainer type -", self.explainer)
      contributions = self.explainer(x, **self.explainer_compute_args)
      explain_data = dict(contributions=contributions.values)
      return explain_data
  
file_path: shapash/shapash/backend/shap_backend.py
imports: import pandas
  import numpy
  import shap
  from shapash.backend.base_backend import BaseBackend
label_desc: Use image node_id 2 for calling the ShapBackend obj's underlying member method code with example usage: obj.run_explainer(x) and returns: explain_data