def extract(self, column_name):
    'Returns a new time series with the chosen column.\n\n        Parameters\n        ----------\n        column_name : `str`\n            A valid column name.\n\n        Returns\n        -------\n        newts : `~sunpy.timeseries.TimeSeries`\n            A new time series with only the selected column.\n        '
    '\n        # TODO allow the extract function to pick more than one column\n        if isinstance(self, pandas.Series):\n            return self\n        else:\n            return GenericTimeSeries(self.data[column_name], TimeSeriesMetaData(self.meta.metadata.copy()))\n        '
    data = self.data[[column_name]].dropna()
    object = GenericTimeSeries(data.sort_index(), TimeSeriesMetaData(copy.copy(self.meta.metadata)), copy.copy(self.units))
    object._sanitize_metadata()
    object._sanitize_units()
    return object
Returns a new time series with the chosen column.

Parameters
----------
column_name : `str`
    A valid column name.

Returns
-------
newts : `~sunpy.timeseries.TimeSeries`
    A new time series with only the selected column.
def extract(self, column_name):
    'Returns a new time series with the chosen column.\n\n        Parameters\n        ----------\n        column_name : `str`\n            A valid column name.\n\n        Returns\n        -------\n        newts : `~sunpy.timeseries.TimeSeries`\n            A new time series with only the selected column.\n        '
    '\n        # TODO allow the extract function to pick more than one column\n        if isinstance(self, pandas.Series):\n            return self\n        else:\n            return GenericTimeSeries(self.data[column_name], TimeSeriesMetaData(self.meta.metadata.copy()))\n        '
    data = self.data[[column_name]].dropna()
    object = GenericTimeSeries(data.sort_index(), TimeSeriesMetaData(copy.copy(self.meta.metadata)), copy.copy(self.units))
    object._sanitize_metadata()
    object._sanitize_units()
    return object