code: def data_check(data,target):
      
  
      # Check pandas or numpy
      if isinstance(data, pd.DataFrame) or isinstance(data, pd.core.frame.DataFrame):
          data_index = data.index         
          if target is None:
              transformed_data = data.ix[:,0].values
              data_name = str(data.columns.values[0])
          else:
              transformed_data = data[target].values          
              data_name = str(target)                 
          is_pandas = True
          
      elif isinstance(data, np.ndarray):
          data_name = "Series"        
          is_pandas = False
          if any(isinstance(i, np.ndarray) for i in data):
              if target is None:
                  transformed_data = data[0]          
                  data_index = list(range(len(data[0])))
              else:
                  transformed_data = data[target]         
                  data_index = list(range(len(data[target])))
          else:
              transformed_data = data                 
              data_index = list(range(len(data)))
      else:
          raise Exception("The data input is not pandas or numpy compatible!")
      
      return transformed_data, data_name, is_pandas, data_index
docs: Checks data type
  
      Parameters
      ----------
      data : pd.DataFrame or np.array
          Field to specify the time series data that will be used.
      
      target : int or str
          Target column
          
      Returns
      ----------
      transformed_data : np.array
          Raw data array for use in the model
          
      data_name : str
          Name of the data
      
      is_pandas : Boolean
          True if pandas data, else numpy
      
      data_index : np.array
          The time indices for the data