class_docstr: Container for scatter plots.
  
  This class (object) is returned from the ``scatter_plots`` function. The
  attributes documented below can be accessed or extracted.
  
  Attributes:
      input_data: The input data.
      num_data: Numeric data only
      mode: {'diagnostic', 'matrix', 'all'} The visualization mode.
          **diagnostic**: Plots selected by scagnostics (scatter plot diagnostics)
          **matrix**: Generate the full scatter plot matrix
          **all**: Generate all individual scatter plots
      sample: The sampling method to use. Currently not used.
      diagnostics: The diagnostics from ``pyscagnostics.scagnostics``
      threshold: The scatter plot diagnostic threshold value [0,1] for returning a
          plot. Only used with "diagnostic" mode. For example, ``{"Outlying": 0.9}``
          returns plots with outlier metrics above 0.9. See
          ``pyscagnostics.measure_names`` for a list of metrics.
          **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.
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code: def __repr__(self):
      return "data-describe Scatter Plot Widget"
  
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 3 for calling the ScatterWidget obj's underlying member method code with example usage: obj.__repr__() and returns: str