def _build_sensor_output_data()

in sagemaker/source/dl_utils/dataset.py [0:0]

• 12 lines of code
• 3 McCabe index (conditional complexity)

    def _build_sensor_output_data(self, df, should_standardize, mean_dict):
        labels = df['target']
        
        df = df.drop(columns=['target'],
            errors='ignore')   
        
        data = []
        for sensor_header in self.sensor_headers:
            data_i = df.iloc[:, df.columns.str.contains(sensor_header)].values
            if should_standardize:
                mean, std = mean_dict[sensor_header]
                data_i = (data_i - mean)/std
            data.append(data_i)
        
        return np.array(data).transpose((1,2,0)), labels.values