code: def _encode_date_columns(self, data: DataFrame) -> DataFrame:
      added_features = []
      for field_name, freq, format in self.config.date_columns:
          data = self.make_date(data, field_name, format)
          data, _new_feats = self.add_datepart(
              data, field_name, frequency=freq, prefix=None, drop=True
          )
          added_features += _new_feats
      return data, added_features
  
imports: import re
  import warnings
  from enum import Enum
  from pathlib import Path
  from typing import Dict, Iterable, List, Optional, Tuple, Union
  import joblib
  import numpy
  import pandas
  import pytorch_lightning
  import torch
  from omegaconf import DictConfig
  from pandas import DataFrame, DatetimeTZDtype, to_datetime
  from pandas.tseries import offsets
  from pandas.tseries.frequencies import to_offset
  from sklearn.base import TransformerMixin, copy
  from sklearn.preprocessing import FunctionTransformer, LabelEncoder, PowerTransformer, QuantileTransformer, StandardScaler
  from torch.utils.data import DataLoader, Dataset
  from pytorch_tabular.config import InferredConfig
  from pytorch_tabular.utils import get_logger
  from .categorical_encoders import OrdinalEncoder
label_desc: Use image node_id 16 for calling the TabularDatamodule obj's underlying member method code with example usage: obj._encode_date_columns(data) and returns: data,  added_features