code: def test_pandas_find_clusters_param(numeric_data, monkeypatch_KMeans):
      widget = _find_clusters(numeric_data, cluster_range=(2, 4))
      assert widget.cluster_range == (2, 4)
      with pytest.raises(ValueError):
          _find_clusters(numeric_data, metric="adjusted_rand_score")
      widget = _find_clusters(
          numeric_data,
          metric="adjusted_rand_score",
          target=numeric_data.iloc[:, 0],
      )
      assert hasattr(
          widget, "target"
      ), "Supervised clustering did not record `target` on widget"
  
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 16 for calling a global function with example usage: test_pandas_find_clusters_param(numeric_data, monkeypatch_KMeans) without return types