code: def test_na_vals_reg_plot_raise_warning():
      X, y = load_diabetes(return_X_y=True)
      X = pd.DataFrame(X)
      y[::50] = np.NaN
      X["target_col"] = y
      with pytest.warns(
          UserWarning,
          match="Missing values in target_col have "
          "been removed for regression",
      ):
          plot(X, "target_col")
      with pytest.warns(
          UserWarning,
          match="Missing values in target_col have "
          "been removed for regression",
      ):
          plot_regression_continuous(X, target_col="target_col")
      with pytest.warns(
          UserWarning,
          match="Missing values in target_col have "
          "been removed for regression",
      ):
          plot_regression_categorical(X, target_col="target_col")
  
imports: import pytest
  import numpy
  import pandas
  import matplotlib.pyplot
  import warnings
  import itertools
  from sklearn.datasets import make_regression, make_blobs, load_digits, fetch_openml, load_diabetes
  from sklearn.preprocessing import KBinsDiscretizer
  from dabl.preprocessing import clean, detect_types, guess_ordinal
  from dabl.plot.supervised import plot, plot_classification_categorical, plot_classification_continuous, plot_regression_categorical, plot_regression_continuous
  from dabl.utils import data_df_from_bunch
  from dabl import set_config
label_desc: Use image node_id 18 for calling a global function with example usage: test_na_vals_reg_plot_raise_warning() without return types