docstr: Returns the data as a pandas dataframe.
docstr_tok: ["Returns","the","data","as","a","pandas","dataframe","."]
code: def data(self):
      """Returns the data as a pandas dataframe."""
      if self.continuous_cols and self.categorical_cols:
          data = pd.DataFrame(
              np.concatenate(
                  [self.categorical_X, self.continuous_X], axis=1
              ),
              columns=self.categorical_cols + self.continuous_cols,
          )
      elif self.continuous_cols:
          data = pd.DataFrame(
              self.continuous_X, columns=self.continuous_cols
          )
      elif self.categorical_cols:
          data = pd.DataFrame(
              self.categorical_X, columns=self.categorical_cols
          )
      else:
          data = pd.DataFrame()
      for i, t in enumerate(self.target):
          data[t] = self.y[:, i]
      return data
  
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 2 for calling the TabularDataset obj's underlying member method code with example usage: obj.data() and returns: data