<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def calc_track_errors(model_tracks, obs_tracks, track_pairings):
 """ Calculates spatial and temporal translation errors between matched forecast and observed tracks. Args: model_tracks: List of model track STObjects obs_tracks: List of observed track STObjects track_pairings: List of tuples pairing forecast and observed tracks. Returns: pandas DataFrame containing different track errors """

        columns = ['obs_track_id',
                   'translation_error_x',
                   'translation_error_y',
                   'start_time_difference',
                   'end_time_difference',
                   ]
        track_errors = pd.DataFrame(index=list(range(len(model_tracks))),
                                    columns=columns)
        for p, pair in enumerate(track_pairings):
            model_track = model_tracks[pair[0]]
            if type(pair[1]) in [int, np.int64]:
                obs_track = obs_tracks[pair[1]]
            else:
                obs_track = obs_tracks[pair[1][0]]
            model_com = model_track.center_of_mass(model_track.start_time)
            obs_com = obs_track.center_of_mass(obs_track.start_time)
            track_errors.loc[pair[0], 'obs_track_id'] = pair[1] if type(pair[1]) in [int, np.int64] else pair[1][0]
            track_errors.loc[pair[0], 'translation_error_x'] = model_com[0] - obs_com[0]
            track_errors.loc[pair[0], 'translation_error_y'] = model_com[1] - obs_com[1]
            track_errors.loc[pair[0], 'start_time_difference'] = model_track.start_time - obs_track.start_time
            track_errors.loc[pair[0], 'end_time_difference'] = model_track.end_time - obs_track.end_time 
        return track_errors