def concatenate(self, otherts, **kwargs):
    'Concatenate with another TimeSeries. This function will check and\n        remove any duplicate times. It will keep the column values from the\n        original time series to which the new time series is being added.\n\n        Parameters\n        ----------\n        otherts : `~sunpy.timeseries.TimeSeries`\n            Another time series.\n\n        same_source : `bool` Optional\n            Set to true to check if the sources of the time series match.\n\n        Returns\n        -------\n        newts : `~sunpy.timeseries.TimeSeries`\n            A new time series.\n\n        Debate: decide if we want to be able to concatenate multiple time series\n        at once.\n        '
    if (self == otherts):
        return self
    same_source = kwargs.get('same_source', False)
    if (same_source and (not isinstance(otherts, self.__class__))):
        raise TypeError('TimeSeries classes must match if specified.')
    meta = self.meta.concatenate(otherts.meta)
    data = pd.concat([self.data.copy(), otherts.data], **kwargs)
    units = OrderedDict()
    units.update(self.units)
    units.update(otherts.units)
    if (self.__class__ == otherts.__class__):
        object = self.__class__(data.sort_index(), meta, units)
    else:
        object = GenericTimeSeries(data.sort_index(), meta, units)
    object._sanitize_metadata()
    object._sanitize_units()
    return object
Concatenate with another TimeSeries. This function will check and
remove any duplicate times. It will keep the column values from the
original time series to which the new time series is being added.

Parameters
----------
otherts : `~sunpy.timeseries.TimeSeries`
    Another time series.

same_source : `bool` Optional
    Set to true to check if the sources of the time series match.

Returns
-------
newts : `~sunpy.timeseries.TimeSeries`
    A new time series.

Debate: decide if we want to be able to concatenate multiple time series
at once.
def concatenate(self, otherts, **kwargs):
    'Concatenate with another TimeSeries. This function will check and\n        remove any duplicate times. It will keep the column values from the\n        original time series to which the new time series is being added.\n\n        Parameters\n        ----------\n        otherts : `~sunpy.timeseries.TimeSeries`\n            Another time series.\n\n        same_source : `bool` Optional\n            Set to true to check if the sources of the time series match.\n\n        Returns\n        -------\n        newts : `~sunpy.timeseries.TimeSeries`\n            A new time series.\n\n        Debate: decide if we want to be able to concatenate multiple time series\n        at once.\n        '
    if (self == otherts):
        return self
    same_source = kwargs.get('same_source', False)
    if (same_source and (not isinstance(otherts, self.__class__))):
        raise TypeError('TimeSeries classes must match if specified.')
    meta = self.meta.concatenate(otherts.meta)
    data = pd.concat([self.data.copy(), otherts.data], **kwargs)
    units = OrderedDict()
    units.update(self.units)
    units.update(otherts.units)
    if (self.__class__ == otherts.__class__):
        object = self.__class__(data.sort_index(), meta, units)
    else:
        object = GenericTimeSeries(data.sort_index(), meta, units)
    object._sanitize_metadata()
    object._sanitize_units()
    return object