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/pull/2612#issuecomment-451726877,https://api.github.com/repos/pydata/xarray/issues/2612,451726877,MDEyOklzc3VlQ29tbWVudDQ1MTcyNjg3Nw==,1217238,2019-01-06T09:13:56Z,2019-01-06T09:13:56Z,MEMBER,"Indeed, thank you @fujiisoup !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-451421221,https://api.github.com/repos/pydata/xarray/issues/2612,451421221,MDEyOklzc3VlQ29tbWVudDQ1MTQyMTIyMQ==,10050469,2019-01-04T11:36:00Z,2019-01-04T11:36:00Z,MEMBER,This is (one more time) an extremely useful addition to xarray - thanks so much @fujiisoup !,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-451350667,https://api.github.com/repos/pydata/xarray/issues/2612,451350667,MDEyOklzc3VlQ29tbWVudDQ1MTM1MDY2Nw==,1217238,2019-01-04T04:22:18Z,2019-01-04T04:22:18Z,MEMBER,I plan to merge this tomorrow unless anyone else has further suggestions.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-449220785,https://api.github.com/repos/pydata/xarray/issues/2612,449220785,MDEyOklzc3VlQ29tbWVudDQ0OTIyMDc4NQ==,2443309,2018-12-21T02:35:49Z,2018-12-21T02:35:49Z,MEMBER,"+1, on `'exact'`. I like the idea of making users be explicit about when to pad or trim edge cells.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-449214046,https://api.github.com/repos/pydata/xarray/issues/2612,449214046,MDEyOklzc3VlQ29tbWVudDQ0OTIxNDA0Ng==,1217238,2018-12-21T02:00:53Z,2018-12-21T02:00:53Z,MEMBER,"@pydata/xarray any opinions on what the default value for the `boundary` argument to `coarsen()` should be?

Personally, I like `boundary='exact'`, but I also work mostly with simulated data with dimensions setup to be exact powers of 2 :). ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-449158415,https://api.github.com/repos/pydata/xarray/issues/2612,449158415,MDEyOklzc3VlQ29tbWVudDQ0OTE1ODQxNQ==,6815844,2018-12-20T22:38:19Z,2018-12-20T22:39:20Z,MEMBER,"During writing the test codes, I realized that the default `boundary='exact'` is a little annoying.
It would be rare that the length of the data is exactly a multiple of the window size; we almost always need to type `bounary='trim'` or the other.
I personally think that `boundary='pad'` is also a good default, as it is a similar behaviour to `rolling`.

The down side of this is that it can make a uniformly spaced data an inhomogeneously spaced one.
It is something what users may not expect.
(probably `boundary='exact` is safer)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-449142367,https://api.github.com/repos/pydata/xarray/issues/2612,449142367,MDEyOklzc3VlQ29tbWVudDQ0OTE0MjM2Nw==,6815844,2018-12-20T21:33:22Z,2018-12-20T21:33:22Z,MEMBER,"Updated.
The main change is
1. API updated to
```python
dataset.coarsen(self, dim=None, boundary='exact', side='left',
                            coordinate_func='mean', **dim_kwargs):
```
based on comments.

2. nanmean for DateTime was implemented.
This is a kind of backward incompatible.
Previously, we raised an Error if mean is applied to a datetime array.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-448721612,https://api.github.com/repos/pydata/xarray/issues/2612,448721612,MDEyOklzc3VlQ29tbWVudDQ0ODcyMTYxMg==,1217238,2018-12-19T19:48:02Z,2018-12-19T19:48:02Z,MEMBER,"I do think it would be nice for `resample()` to work with numbers and along multiple dimensions, but that's definitely a bigger project.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-448719698,https://api.github.com/repos/pydata/xarray/issues/2612,448719698,MDEyOklzc3VlQ29tbWVudDQ0ODcxOTY5OA==,5635139,2018-12-19T19:41:53Z,2018-12-19T19:41:53Z,MEMBER,"Perfect, thanks for pointing that out (I've generally been a bit out of the loop recently...)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-448718248,https://api.github.com/repos/pydata/xarray/issues/2612,448718248,MDEyOklzc3VlQ29tbWVudDQ0ODcxODI0OA==,1217238,2018-12-19T19:37:09Z,2018-12-19T19:37:09Z,MEMBER,"@max-sixty we discussed this a little bit: https://github.com/pydata/xarray/issues/2525#issuecomment-434477550

The main difference is that resample is coordinate based, whereas this is integer position based which makes the implementation considerably simpler.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-448717771,https://api.github.com/repos/pydata/xarray/issues/2612,448717771,MDEyOklzc3VlQ29tbWVudDQ0ODcxNzc3MQ==,5635139,2018-12-19T19:35:29Z,2018-12-19T19:35:29Z,MEMBER,"> I think it's multi-dimensional resampling / rolling. resample & rolling operate one dimension at a time.

Thanks. If this is multi-dimensional resampling / rolling, could we implement this functionality within those methods, enabling multiple dimensions?

Potentially the implementations are different enough that the arguments don't have enough overlap?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-447924905,https://api.github.com/repos/pydata/xarray/issues/2612,447924905,MDEyOklzc3VlQ29tbWVudDQ0NzkyNDkwNQ==,2448579,2018-12-17T17:17:18Z,2018-12-17T17:17:18Z,MEMBER,@max-sixty I think it's multi-dimensional resampling / rolling. resample & rolling operate one dimension at a time.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-447912054,https://api.github.com/repos/pydata/xarray/issues/2612,447912054,MDEyOklzc3VlQ29tbWVudDQ0NzkxMjA1NA==,5635139,2018-12-17T16:41:58Z,2018-12-17T16:41:58Z,MEMBER,Forgive me if this has an obvious answer: to what extent is this downsampling? Could this be done with `resample`?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-447736226,https://api.github.com/repos/pydata/xarray/issues/2612,447736226,MDEyOklzc3VlQ29tbWVudDQ0NzczNjIyNg==,6815844,2018-12-17T06:27:35Z,2018-12-17T06:27:35Z,MEMBER,"@dcherian 
Thanks.
> (da.time - da.time[0]).mean() + da.time[0]
I would add mean for datetime-arrays.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755
https://github.com/pydata/xarray/pull/2612#issuecomment-447664380,https://api.github.com/repos/pydata/xarray/issues/2612,447664380,MDEyOklzc3VlQ29tbWVudDQ0NzY2NDM4MA==,2448579,2018-12-16T18:18:55Z,2018-12-16T18:18:55Z,MEMBER,"`(da.time - da.time[0]).mean() + da.time[0]`

Or we could default to `min()` and add an `loffset` kwarg like `resample` (https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.resample.html)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,391477755