html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1269#issuecomment-280122805,https://api.github.com/repos/pydata/xarray/issues/1269,280122805,MDEyOklzc3VlQ29tbWVudDI4MDEyMjgwNQ==,1217238,2017-02-15T20:04:07Z,2017-02-15T20:04:07Z,MEMBER,"I think this could be done with minimal GroupBy subclasses to supply the
default dimension argument for aggregation functions. All the machinery on
groupby should already be there.
On Wed, Feb 15, 2017 at 10:59 AM Daniel Rothenberg <notifications@github.com>
wrote:

> @MaximilianR <https://github.com/MaximilianR> Oh, the interface is easy
> enough to do, even maintaining backwards-compatibility (already have that
> working). I was considering going the route done with GroupBy
> <https://github.com/pydata/xarray/blob/93d6963315026f87841c7cf39cc39bb78f555345/xarray/core/groupby.py#L165>
> and the classes that compose it, like DatasetGroupBy
> <https://github.com/pydata/xarray/blob/93d6963315026f87841c7cf39cc39bb78f555345/xarray/core/groupby.py#L586>...
> basically, we just record the wanted resampling dimension and inject the
> grouping/resampling operations we want. Also adds the ability to specialize
> methods like .first() and .last(), which is done under the current
> implementation.
>
> *But*.... if there's a simpler way, that might be preferable!
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
> <https://github.com/pydata/xarray/issues/1269#issuecomment-280104546>, or mute
> the thread
> <https://github.com/notifications/unsubscribe-auth/ABKS1mAUBUkz7ig3fijFmqg6IeDnGgdeks5rc0sJgaJpZM4MAyE5>
> .
>
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161
https://github.com/pydata/xarray/issues/1269#issuecomment-280104546,https://api.github.com/repos/pydata/xarray/issues/1269,280104546,MDEyOklzc3VlQ29tbWVudDI4MDEwNDU0Ng==,4992424,2017-02-15T18:59:17Z,2017-02-15T18:59:17Z,NONE,"@MaximilianR Oh, the interface is easy enough to do, even maintaining backwards-compatibility (already have that working). I was considering going the route done with [GroupBy](https://github.com/pydata/xarray/blob/93d6963315026f87841c7cf39cc39bb78f555345/xarray/core/groupby.py#L165) and the classes that compose it, like [DatasetGroupBy](https://github.com/pydata/xarray/blob/93d6963315026f87841c7cf39cc39bb78f555345/xarray/core/groupby.py#L586)... basically, we just record the wanted resampling dimension and inject the grouping/resampling operations we want. Also adds the ability to specialize methods like `.first()` and `.last()`, which is done under the current implementation.

*But*.... if there's a simpler way, that might be preferable!","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161
https://github.com/pydata/xarray/issues/1269#issuecomment-280101839,https://api.github.com/repos/pydata/xarray/issues/1269,280101839,MDEyOklzc3VlQ29tbWVudDI4MDEwMTgzOQ==,5635139,2017-02-15T18:49:32Z,2017-02-15T18:49:32Z,MEMBER,">the only sticking point I've come across so far is how to have the resulting Data{Array,set}GroupBy object ""remember"" the resampling dimension

I think an interface like `ds.resample(time='24H').mean()` would be much better. We could do that with a wrapper of `pd.TimeGrouper` that also had a `dim` field. Or inheritance 😨 ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161
https://github.com/pydata/xarray/issues/1269#issuecomment-280101190,https://api.github.com/repos/pydata/xarray/issues/1269,280101190,MDEyOklzc3VlQ29tbWVudDI4MDEwMTE5MA==,5635139,2017-02-15T18:47:20Z,2017-02-15T18:47:20Z,MEMBER,Would be great to test for these sorts of issues if we redo this: https://github.com/pydata/xarray/issues/1269,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161
https://github.com/pydata/xarray/issues/1269#issuecomment-279845588,https://api.github.com/repos/pydata/xarray/issues/1269,279845588,MDEyOklzc3VlQ29tbWVudDI3OTg0NTU4OA==,4992424,2017-02-14T21:44:11Z,2017-02-14T21:44:11Z,NONE,"Assuming we want to stick with `pd.TimeGrouper` under the hood, the only sticking point I've come across so far is how to have the resulting `Data{Array,set}GroupBy` object ""remember"" the resampling dimension, e.g. if you have multi-dimensional data and want to compute time means you have to call

``` python
ds.resample(time='24H').mean('time')
```

or else `mean` will operate across all dimensions. Any thoughts, @shoyer?

","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161
https://github.com/pydata/xarray/issues/1269#issuecomment-279810604,https://api.github.com/repos/pydata/xarray/issues/1269,279810604,MDEyOklzc3VlQ29tbWVudDI3OTgxMDYwNA==,4992424,2017-02-14T19:32:01Z,2017-02-14T19:32:01Z,NONE,Let me dig into this a bit right now. My analysis project for this afternoon was already going to require digging into pandas' resampling in more depth anyways.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207587161