class_docstr: State pattern attached to SmartExplainer. This is the base class that only handles matrices
  of local contributions. The multi-class case is tackled in SmartMultiState.
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docstr: Returns Boolean values depending on
  the signs of local contributions
  stored in dataframe and on the positive parameter.
  
  Parameters
  ----------
  dataframe : pandas.DataFrame
      Local contributions of the model.
  positive : boolean (default=True)
      True to evaluate positive value.
      False to evaluate negative value.
  
  Returns
  -------
  pandas.DataFrame
      Dataframe with boolean value.
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code: def sign_contributions(self, dataframe, positive=True):
      """
      Returns Boolean values depending on
      the signs of local contributions
      stored in dataframe and on the positive parameter.
  
      Parameters
      ----------
      dataframe : pandas.DataFrame
          Local contributions of the model.
      positive : boolean (default=True)
          True to evaluate positive value.
          False to evaluate negative value.
  
      Returns
      -------
      pandas.DataFrame
          Dataframe with boolean value.
      """
      return sign_contributions(dataframe, positive=positive)
  
imports: import numpy
  import pandas
  from shapash.decomposition.contributions import inverse_transform_contributions
  from shapash.decomposition.contributions import rank_contributions, assign_contributions
  from shapash.manipulation.filters import hide_contributions
  from shapash.manipulation.filters import cap_contributions
  from shapash.manipulation.filters import sign_contributions
  from shapash.manipulation.filters import cutoff_contributions
  from shapash.manipulation.filters import combine_masks
  from shapash.manipulation.mask import compute_masked_contributions
  from shapash.manipulation.mask import init_mask
  from shapash.manipulation.summarize import summarize, compute_features_import, group_contributions
label_desc: Use image node_id 8 for calling the SmartState obj's underlying member method code with example usage: obj.sign_contributions(dataframe, positive) and returns: sign_contributions