code: def test_explain_prediction_pandas_dot_in_feature_name(boston_train):
      pd = pytest.importorskip("pandas")
      X, y, feature_names = boston_train
      feature_names = [
          "%s.%s" % (name, idx)
          for idx, name in enumerate(feature_names)
      ]
      df = pd.DataFrame(X, columns=feature_names)
  
      reg = XGBRegressor()
      reg.fit(df, y)
      res = explain_prediction(reg, df.iloc[0])
      for expl in format_as_all(res, reg):
          assert "PTRATIO.1" in expl
  
imports: from __future__ import absolute_import
  import pytest
  import numpy
  import scipy.sparse
  from sklearn.feature_extraction.text import CountVectorizer
  import xgboost
  from xgboost import XGBClassifier, XGBRegressor
  from sklearn.pipeline import FeatureUnion
  from sklearn.preprocessing import FunctionTransformer
  from eli5.xgboost import _parse_tree_dump, _xgb_n_targets, _missing_values_set_to_nan, _parent_value, _parse_dump_line, _check_booster_args
  from eli5.explain import explain_prediction, explain_weights
  from eli5.formatters.text import format_as_text
  from eli5.formatters import fields
  from .utils import format_as_all, get_all_features, check_targets_scores
  from .test_sklearn_explain_weights import test_explain_tree_classifier, test_explain_random_forest_and_tree_feature_filter, test_feature_importances_no_remaining, assert_tree_classifier_explained
  from .test_sklearn_explain_prediction import assert_linear_regression_explained, assert_trained_linear_regression_explained, assert_explain_prediction_single_target, test_explain_clf_binary_iris, test_explain_prediction_pandas
label_desc: Use image node_id 20 for calling a global function with example usage: test_explain_prediction_pandas_dot_in_feature_name(boston_train) without return types