code: def test_pandas_find_clusters_default(
      numeric_data, monkeypatch_KMeans
  ):
      widget = _find_clusters(numeric_data)
      assert isinstance(widget.clusters, np.ndarray)
      assert isinstance(widget, ClusterWidget)
      assert widget.cluster_range == (2, 20)
      assert (
          widget.search
      ), "`search` attribute was not true on widget for cluster search"
      assert (
          widget.metric == "silhouette_score"
      ), "`metric` did not default to `silhouette_score`"
      assert isinstance(
          widget.scores, list
      ), "metric `scores` on widget is not a list"
  
imports: import numpy
  import pytest
  import matplotlib
  from matplotlib.axes import Axes
  from sklearn.cluster import KMeans
  from sklearn.preprocessing import StandardScaler
  import plotly
  import data_describe
  from data_describe.compat import _is_dataframe
  from data_describe.core.clustering import ClusterWidget, _pandas_compute_cluster, _run_kmeans, _find_clusters, _fit_kmeans, _run_hdbscan
label_desc: Use image node_id 15 for calling a global function with example usage: test_pandas_find_clusters_default(numeric_data, monkeypatch_KMeans) without return types