code: def test_pandas_pass():
      tree = DecisionTreeClassifier(random_state=123)
      X_df = pd.DataFrame(X)
      y_ser = pd.Series(y)
      bootstrap_point632_score(
          tree, X_df, y_ser, random_seed=123, method="oob"
      )
      bootstrap_point632_score(
          tree, X_df, y_ser, random_seed=123, method=".632"
      )
      bootstrap_point632_score(
          tree, X_df, y_ser, random_seed=123, method=".632+"
      )
  
imports: import os
  import numpy
  import pandas
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.linear_model import LogisticRegression
  from sklearn.tree import DecisionTreeClassifier
  from mlxtend.data import iris_data
  from mlxtend.evaluate import bootstrap_point632_score
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 1 for calling a global function with example usage: test_pandas_pass() without return types