Suggestion: adding station as index to multi-station retrievals

[ks905383]

When getting observations from multiple stations:

from ndbc_api import NdbcApi

api = NdbcApi()

# get all standard meterological measurements for stations tplm2 and apam2
stdmet_df = api.get_data(
    station_ids=['tplm2', 'apam2'],
    mode='stdmet',
    start_time='2021-01-01',
    end_time='2022-01-01',
)

stdmet_df

The index of the returned df is only the timestamp, resulting in a non-unique index (because timestamps can be duplicated between different stations). Perhaps it may be useful to make station_id an index as well.

In addition to better leveraging pandas's index-based functions, this would also make it easier to flip between pandas and xarray (since df.to_xarray() uses those indices), for example.

(it's easy enough to do 'manually' through stdmet_df.reset_index().set_index(['station_id','timestamp']), but it may be a neater way of showing this information)

This is related to JOSS review openjournals/joss-reviews#7406.

[CDJellen]

Thank you for this suggestion as well @ks905383, I will include it in the next release. You make an excellent point on index uniqueness. I will include this in the next release.

[CDJellen]

As for #51 , the suggestions are incorporated in #52 and the release in #53. I am scoping an appropriate change which allows for station metadata in the returned xarray Datasets. Thanks again for the suggestions!