code: def test_easy_preprocessor_transform():
      titanic = load_titanic()
      titanic_clean = clean(titanic)
      X, y = (
          titanic_clean.drop("survived", axis=1),
          titanic_clean.survived,
      )
      X_train, X_val, y_train, y_val = train_test_split(
          X, y, stratify=y, random_state=42
      )
      pipe = make_pipeline(
          EasyPreprocessor(), LogisticRegression(C=0.1)
      )
      pipe.fit(X_train, y_train)
      pipe.predict(X_train)
      pipe.predict(X_val)
  
imports: import os
  import pytest
  import random
  import string
  import warnings
  import numpy
  import pandas
  from sklearn.datasets import load_iris, load_digits
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression
  from dabl.preprocessing import USELESS_TYPES, detect_types, EasyPreprocessor, DirtyFloatCleaner, clean, _FLOAT_REGEX, _float_matching, detect_type_series
  from dabl.utils import data_df_from_bunch
  from dabl.datasets import load_titanic
  from dabl import plot
label_desc: Use image node_id 23 for calling a global function with example usage: test_easy_preprocessor_transform() without return types