class_docstr: Сlass for storing, cleaning and processing your dataset
class_docstr_tok: ["\u0421lass","for","storing",",","cleaning","and","processing","your","dataset"]
docstr: Description of check_data_format:
      Check that data is not pd.DataFrame or empty
  
  Args:
      data (undefined): dataset
  Return:
      True or Exception
docstr_tok: ["Description","of","check_data_format",":","Check","that","data","is","not","pd.DataFrame","or","empty","Args",":","data","(","undefined",")",":","dataset","Return",":","True","or","Exception"]
code: def check_data_format(self, data):
      """
      Description of check_data_format:
          Check that data is not pd.DataFrame or empty
  
      Args:
          data (undefined): dataset
      Return:
          True or Exception
      """
      data_tmp = pd.DataFrame(data)
      if data_tmp is None or data_tmp.empty:
          raise Exception("data is not pd.DataFrame or empty")
      else:
          if isinstance(data, pd.Series) or isinstance(
              data, pd.DataFrame
          ):
              return True
          elif isinstance(data, np.ndarray):
              return True
          elif type(data) == dask.dataframe.core.DataFrame:
              return True
          else:
              False
  
imports: import pandas
  import numpy
  from itertools import combinations
  from sklearn.preprocessing import StandardScaler
  from category_encoders import HashingEncoder, SumEncoder, PolynomialEncoder, BackwardDifferenceEncoder
  from category_encoders import OneHotEncoder, HelmertEncoder, OrdinalEncoder, CountEncoder, BaseNEncoder
  from category_encoders import TargetEncoder, CatBoostEncoder, WOEEncoder, JamesSteinEncoder
  from category_encoders.glmm import GLMMEncoder
  from sklearn.preprocessing import LabelEncoder
  from category_encoders.wrapper import PolynomialWrapper
  from .encoders import FrequencyEncoder
  from .None import settings
  import pdb
  import copy
  import dask
  import dask.dataframe
label_desc: Use image node_id 2 for calling the DataBunch obj's underlying member method code with example usage: obj.check_data_format(data) and returns: True, True, True