code: def test_pandas_run_hdbscan_default(
      _hdbscan, numeric_data, monkeypatch_HDBSCAN
  ):
      widget = _run_hdbscan(numeric_data, min_cluster_size=10)
      assert isinstance(
          widget.clusters, np.ndarray
      ), "Cluster labels was not a numpy array"
      assert isinstance(
          widget, ClusterWidget
      ), "Fit object was not a ClusterWidget"
      assert (
          widget.n_clusters == 1
      ), "n_clusters on the widget does not match expected value"
      print(repr(widget))
      assert isinstance(
          widget.estimator, _hdbscan.HDBSCAN
      ), "Estimator is not HDBSCAN"
  
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 18 for calling a global function with example usage: test_pandas_run_hdbscan_default(_hdbscan, numeric_data, monkeypatch_HDBSCAN) without return types