code: def get_traindata(self) -> np.ndarray:
          
          traindata = None
          for key, value in self.data.items():
              if key not in ['__header__', '__version__', '__globals__']:
                  if traindata is None:
                      traindata = value[np.where(value[:, 4] != 0)]
                  else:
                      traindata = np.concatenate((traindata, value[np.where(value[:, 4] != 0)]))
          return traindata
docs: Pulls all available data and concatenates for model training
  
          :return: 2d array of points