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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_traindata(self) -> np.ndarray: """ Pulls all available data and concatenates for model training :return: 2d array of points """

        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