code: def _filter_threshold(diagnostics, threshold=0.85):
      """Filter the plots by scatter plot diagnostic threshold.
  
      Args:
          diagnostics: The diagnostics generator from pyscagnostics
          threshold: The scatter plot diagnostic threshold value [0,1] for returning a plot
              If a number: Returns all plots where at least one metric is above this threshold
              If a dictionary: Returns plots where the metric is above its threshold
              For example, {"Outlier": 0.9} returns plots with outlier metrics above 0.9
              The available metrics are: Outlier, Convex, Skinny, Skewed, Stringy, Straight, Monotonic, Clumpy, Striated
  
      Returns:
          A dictionary of pairs that match the filter
      """
      if isinstance(threshold, dict):
          return [
              d
              for d in diagnostics
              if all(
                  [d[2][0][m] >= threshold[m] for m in threshold.keys()]
              )
          ]
      else:
          return [
              d
              for d in diagnostics
              if any([v > threshold for v in d[2][0].values()])
          ]
  
file_path: data-describe/data_describe/core/scatter.py
imports: from itertools import combinations
  import warnings
  import seaborn
  from data_describe._widget import BaseWidget
  from data_describe.config._config import get_option
  from data_describe.compat import _is_dataframe, _requires, _compat
  from data_describe.backends import _get_compute_backend, _get_viz_backend
label_desc: Use image node_id 6 for calling a global function with example usage: _filter_threshold(diagnostics, threshold) and returns: unknown, unknown