code: def _parse_met(content):
          
          col_names = ['year', 'month', 'day', 'hour', 'minute',
                       'wind_direction', 'wind_speed', 'wind_gust',
                       'wave_height', 'dominant_wave_period', 'average_wave_period',
                       'dominant_wave_direction', 'pressure',
                       'air_temperature', 'water_temperature', 'dewpoint',
                       'visibility', '3hr_pressure_tendency', 'water_level_above_mean']
  
          col_units = {'wind_direction': 'degrees',
                       'wind_speed': 'meters/second',
                       'wind_gust': 'meters/second',
                       'wave_height': 'meters',
                       'dominant_wave_period': 'seconds',
                       'average_wave_period': 'seconds',
                       'dominant_wave_direction': 'degrees',
                       'pressure': 'hPa',
                       'air_temperature': 'degC',
                       'water_temperature': 'degC',
                       'dewpoint': 'degC',
                       'visibility': 'nautical_mile',
                       '3hr_pressure_tendency': 'hPa',
                       'water_level_above_mean': 'feet',
                       'time': None}
  
          df = pd.read_table(StringIO(content), comment='#', na_values='MM',
                             names=col_names, sep=r'\s+')
          df['time'] = pd.to_datetime(df[['year', 'month', 'day', 'hour', 'minute']], utc=True)
          df = df.drop(columns=['year', 'month', 'day', 'hour', 'minute'])
          df.units = col_units
          return df
docs: Parse standard meteorological data from NDBC buoys.
  
          Parameters
          ----------
          content : str
              Data to parse
  
          Returns
          -------
              :class:`pandas.DataFrame` containing the data