issue_comments: 427054269

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https://github.com/pydata/xarray/pull/2458#issuecomment-427054269 https://api.github.com/repos/pydata/xarray/issues/2458 427054269 MDEyOklzc3VlQ29tbWVudDQyNzA1NDI2OQ== 6628425 2018-10-04T15:05:20Z 2018-10-04T15:05:20Z MEMBER

Do you think there would be a benefit to implementing a TimeGrouper class based on panda's ?

My instinct would be to first pursue the simple approach that @shoyer has started here. If it turns out that passing a pandas.Series rather than a pandas.Grouper instance in line 236 of groupby.py prevents us from replicating some important behavior of resample, then it might be something to think about.

As of yet, while there are a few details that need to be added to Stephan's implementation (e.g., as he notes in the to-do comment, proper handling of the closed, label, and base arguments; there is some other complexity regarding how to handle gaps in the time series, etc.), I do not (yet) see any reason why these couldn't be handled with some modifications to the current approach. The logic in TimeGrouper is definitely a good reference for how to handle the different arguments to resample, but if we can, I think it would be nice to avoid the complexity of defining a new Grouper class. 

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