def reindex_timeseries(ts_string, new_timestamps):
    """
        get data for timesamp

        :param a JSON string, in pandas-friendly format
        :param a timestamp or list of timestamps (datetimes)
        :returns a pandas data frame, reindexed with the supplied timestamos or None if no data is found
    """
    #If a single timestamp is passed in, turn it into a list
    #Reindexing can't work if it's not a list
    if not isinstance(new_timestamps, list):
        new_timestamps = [new_timestamps]

    #Convert the incoming timestamps to datetimes
    #if they are not datetimes.
    new_timestamps_converted = []
    for t in new_timestamps:
        new_timestamps_converted.append(get_datetime(t))

    new_timestamps = new_timestamps_converted

    seasonal_year = config.get('DEFAULT','seasonal_year', '1678')
    seasonal_key = config.get('DEFAULT', 'seasonal_key', '9999')

    ts = ts_string.replace(seasonal_key, seasonal_year)

    timeseries = pd.read_json(ts)

    idx = timeseries.index

    ts_timestamps = new_timestamps

    #'Fix' the incoming timestamp in case it's a seasonal value
    if type(idx) == pd.DatetimeIndex:
        if set(idx.year) == set([int(seasonal_year)]):
            if isinstance(new_timestamps,  list):
                seasonal_timestamp = []
                for t in ts_timestamps:
                    t_1900 = t.replace(year=int(seasonal_year))
                    seasonal_timestamp.append(t_1900)
                ts_timestamps = seasonal_timestamp

    #Reindex the timeseries to reflect the requested timestamps
    reindexed_ts = timeseries.reindex(ts_timestamps, method='ffill')

    i = reindexed_ts.index

    reindexed_ts.index = pd.Index(new_timestamps, names=i.names)

    #If there are no values at all, just return None
    if len(reindexed_ts.dropna()) == 0:
        return None

    #Replace all numpy NAN values with None
    pandas_ts = reindexed_ts.where(reindexed_ts.notnull(), None)

    return pandas_ts
get data for timesamp

        :param a JSON string, in pandas-friendly format
        :param a timestamp or list of timestamps (datetimes)
        :returns a pandas data frame, reindexed with the supplied timestamos or None if no data is found