class_docstr: Explanation object specific to PR explainer.
class_docstr_tok: ["Explanation","object","specific","to","PR","explainer","."]
docstr: Provides interactive visualizations.
  
  Args:
      key: Either a scalar or list
          that indexes the internal object for sub-plotting.
          If an overall visualization is requested, pass None.
  
  Returns:
      A Plotly figure.
docstr_tok: ["Provides","interactive","visualizations",".","Args",":","key",":","Either","a","scalar","or","list","that","indexes","the","internal","object","for","sub-plotting",".","If","an","overall","visualization","is","requested",",","pass","None",".","Returns",":","A","Plotly","figure","."]
code: def visualize(self, key=None):
      """Provides interactive visualizations.
  
      Args:
          key: Either a scalar or list
              that indexes the internal object for sub-plotting.
              If an overall visualization is requested, pass None.
  
      Returns:
          A Plotly figure.
      """
      from ..visual.plot import plot_performance_curve
  
      data_dict = self.data(key)
      if data_dict is None:
          return None
  
      return plot_performance_curve(
          data_dict,
          xtitle="Recall",
          ytitle="Precision",
          baseline=False,
          title="PR Curve: " + self.name,
          auc_prefix="Average Precision",
      )
  
imports: from itertools import count
  from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class
  from sklearn.metrics import roc_curve, auc
  from sklearn.metrics import precision_recall_curve, average_precision_score
  import numpy
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_predict import determine_classes, unify_predict_fn
  from ..utils._unify_data import unify_data
label_desc: Use image node_id 3 for calling the PRExplanation obj's underlying member method code with example usage: obj.visualize(key) and returns: plot_performance_curve, None