code: def test_pandas_run_kmeans_specified_cluster(
      numeric_data, monkeypatch_KMeans
  ):
      widget = _run_kmeans(numeric_data, n_clusters=2)
      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 == 2
      ), "n_clusters on the widget does not match expected value"
      assert (
          not widget.search
      ), "`search` equals True although n_cluster is specified"
  
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 14 for calling a global function with example usage: test_pandas_run_kmeans_specified_cluster(numeric_data, monkeypatch_KMeans) without return types