code: def test_pandas_xgboost_support(iris_train):
      xgboost = pytest.importorskip("xgboost")
      pd = pytest.importorskip("pandas")
      X, y, feature_names, target_names = iris_train
      X = pd.DataFrame(X)
      y = pd.Series(y)
      est = xgboost.XGBClassifier()
      est.fit(X, y)
      # we expect no exception to be raised here when using xgboost with pd.DataFrame
      perm = PermutationImportance(est).fit(X, y)
  
imports: import pytest
  import numpy
  from sklearn.base import is_classifier, is_regressor
  from sklearn.svm import SVR, SVC
  from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
  from sklearn.model_selection import train_test_split, cross_val_score
  from sklearn.pipeline import make_pipeline
  from sklearn.feature_selection import SelectFromModel
  from sklearn.linear_model import LogisticRegression
  import eli5
  from eli5.sklearn import PermutationImportance
  from .utils import format_as_all
label_desc: Use image node_id 12 for calling a global function with example usage: test_pandas_xgboost_support(iris_train) without return types