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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 extract_features(self, data_frame, pre=''):
 """ This method extracts all the features available to the Finger Tapping Processor class. :param data_frame: the data frame :type data_frame: pandas.DataFrame :return: 'frequency', 'moving_frequency','continuous_frequency','mean_moving_time','incoordination_score', \ 'mean_alnt_target_distance','kinesia_scores', 'akinesia_times','dysmetria_score' :rtype: list """

        try:
            return {pre+'frequency': self.frequency(data_frame)[0],
                    pre+'mean_moving_time': self.mean_moving_time(data_frame)[0],
                    pre+'incoordination_score': self.incoordination_score(data_frame)[0],
                    pre+'mean_alnt_target_distance': self.mean_alnt_target_distance(data_frame)[0],
                    pre+'kinesia_scores': self.kinesia_scores(data_frame)[0],
                    pre+'akinesia_times': self.akinesia_times(data_frame)[0],
                    pre+'dysmetria_score': self.dysmetria_score(data_frame)[0]}
        except:
            logging.error("Error on FingerTappingProcessor process, extract features: %s", sys.exc_info()[0])