class_docstr: Shared set-up, checks and methods across creation transformers.
class_docstr_tok: ["Shared","set-up",",","checks","and","methods","across","creation","transformers","."]
docstr: Common input and transformer checks.
  
  Parameters
  ----------
  X: pandas dataframe of shape = [n_samples, n_features]
      The data to transform.
  
  Returns
  -------
  X_new: Pandas dataframe
      The dataframe with the original variables plus the new variables.
docstr_tok: ["Common","input","and","transformer","checks",".","Parameters","--","--","--","--","--","X",":","pandas","dataframe","of","shape","=","[","n_samples",",","n_features","]","The","data","to","transform",".","Returns","--","--","--","-","X_new",":","Pandas","dataframe","The","dataframe","with","the","original","variables","plus","the","new","variables","."]
code: def transform(self, X: pd.DataFrame) -> pd.DataFrame:
      """
      Common input and transformer checks.
  
      Parameters
      ----------
      X: pandas dataframe of shape = [n_samples, n_features]
          The data to transform.
  
      Returns
      -------
      X_new: Pandas dataframe
          The dataframe with the original variables plus the new variables.
      """
  
      # Check method fit has been called
      check_is_fitted(self)
  
      # check that input is a dataframe
      X = check_X(X)
  
      # Check if input data contains same number of columns as dataframe used to fit.
      _check_X_matches_training_df(X, self.n_features_in_)
  
      # check if dataset contains na
      if self.missing_values == "raise":
          _check_contains_na(X, self.variables_)
          _check_contains_inf(X, self.variables_)
          if hasattr(self, "reference"):
              _check_contains_na(X, self.reference)
              _check_contains_inf(X, self.reference)
  
      # reorder variables to match train set
      X = X[self.feature_names_in_]
  
      return X
  
file_path: feature_engine/feature_engine/creation/base_creation.py
imports: from typing import List, Optional, Union
  import pandas
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.utils.validation import check_is_fitted
  from feature_engine._base_transformers.mixins import GetFeatureNamesOutMixin
  from feature_engine._check_input_parameters.check_init_input_params import _check_param_drop_original, _check_param_missing_values
  from feature_engine._variable_handling.variable_type_selection import _find_or_check_numerical_variables
  from feature_engine.dataframe_checks import _check_contains_inf, _check_contains_na, _check_X_matches_training_df, check_X
  from feature_engine.tags import _return_tags
label_desc: Use image node_id 3 for calling the BaseCreation obj's underlying member method code with example usage: obj.transform(X) and returns: X