code: def test_pandas_compute_cluster(numeric_data, monkeypatch_KMeans):
      widget = _pandas_compute_cluster(numeric_data, method="kmeans")
      assert isinstance(
          widget.clusters, np.ndarray
      ), "Cluster labels was not a numpy array"
      assert isinstance(
          widget, ClusterWidget
      ), "Fit object was not a ClusterWidget"
      assert hasattr(widget, "scaler"), "Missing sklearn StandardScaler"
      assert isinstance(
          widget.scaler, StandardScaler
      ), "Scaler attribute is not an instance of sklearn StandardScaler"
      assert hasattr(widget, "input_data"), "Missing input data"
      assert hasattr(widget, "scaled_data"), "Missing scaled data"
  
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 10 for calling a global function with example usage: test_pandas_compute_cluster(numeric_data, monkeypatch_KMeans) without return types