code: def test_plot_partial_dependence_error(pyplot, data, params, err_msg):
      X, y = data
      estimator = LinearRegression().fit(X, y)
  
      with pytest.raises(ValueError, match=err_msg):
          PartialDependenceDisplay.from_estimator(
              estimator, X, **params
          )
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy.stats.mstats import mquantiles
  from sklearn.compose import make_column_transformer
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_regression
  from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor
  from sklearn.inspection import PartialDependenceDisplay
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.utils._testing import _convert_container
label_desc: Use image node_id 14 for calling a global function with example usage: test_plot_partial_dependence_error(pyplot, data, params, err_msg) without return types