id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1319621859,I_kwDOAMm_X85Op9Tj,6837,Clarify difference between `.load()` and `.compute()`,4806877,open,0,,,8,2022-07-27T14:07:33Z,2022-07-27T22:30:22Z,,CONTRIBUTOR,,,,"### What is your issue?

I just realized that the difference between `.load()` and `.compute()` is that `.load()` operates inplace and `.compute()` returns a new xarray object.I have 2 suggestions for how this could be clearer:

1. Docs: the API docs for each method could reference the other.
2. Code: this might be too big a change, but maybe `.load()` should not return anything. Consider this example from pandas:
   ```python
   import pandas as pd

   df = pd.DataFrame({""air"": []})
   df.rename({""air"": ""foo""}, axis=1, inplace=True)
   # returns None since df is renamed inplace
   ```
   this matches the behavior of inplace actions in Python itself like `list.append` or `dict.update`. This would be a major breaking change though, and it might be easier to just remove `.load()` entirely.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6837/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
572295802,MDU6SXNzdWU1NzIyOTU4MDI=,3806,Turn on _repr_html_ by default?,4806877,closed,0,,,3,2020-02-27T19:12:57Z,2020-03-02T23:01:44Z,2020-03-02T23:01:44Z,CONTRIBUTOR,,,,"I just wanted to open this to discuss turning the _repr_html_ on by default. This PR https://github.com/pydata/xarray/pull/3425 added it as a style option, but I suspect that more people will use if it is on by default. Does that seem like a reasonable change?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3806/reactions"", ""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
525970896,MDU6SXNzdWU1MjU5NzA4OTY=,3553,ENH: Plotting backend options,4806877,open,0,,,0,2019-11-20T17:54:45Z,2019-12-17T11:38:58Z,,CONTRIBUTOR,,,,"Since pandas has implemented entry_points based plotting backends, it seems reasonable that xarray would do the same. This would make it even easier to produce holoviews plots (rendered in bokeh via hvplot), by using the `plot` method rather than by importing hvplot directly.

#### Example
<!-- In order for the maintainers to efficiently understand and prioritize issues, we ask you post a ""Minimal, Complete and Verifiable Example"" (MCVE): http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports -->

```python
import xarray as xr
air = xr.tutorial.open_dataset('air_temperature').load().air
xr.options.plotting.backend = 'holoviews'

air.isel(time=500).plot()
```
<img width=""748"" alt=""Screen Shot 2019-11-20 at 12 44 26 PM"" src=""https://user-images.githubusercontent.com/4806877/69263575-953b2200-0b93-11ea-9e00-959e6bbee79d.png"">
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3553/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
378898407,MDU6SXNzdWUzNzg4OTg0MDc=,2550,Include filename or path in open_mfdataset,4806877,closed,0,,,19,2018-11-08T20:13:31Z,2018-12-30T01:00:36Z,2018-12-30T01:00:36Z,CONTRIBUTOR,,,,"When reading from multiple files, sometimes there is information encoded in the filename. For example in these grib files the time: `./ST4.2018092500.01h`, `./ST4.2018092501.01h`. It seems like a generally useful thing would be to allow the passing of a `kwargs` (such as `path_as_coord` or something) that would define a set of coords with one for the data from each file. 

I think the code change would be small:

```python 
if path_as_coord:
    ds = ds.assign_coords(path=file_name)
```

In use it would be like: 

```python
>>>xr.open_mfdataset(['./ST4.2018092500.01h', './ST4.2018092501.01h'], engine='pynio', concat_dim='path')
<xarray.Dataset>
Dimensions:               (x: 881, y: 1121, time: 2)
Coordinates:
    lat             (x, y) float32 23.116999 ... 45.618984
    lon             (x, y) float32 -119.023 ... -59.954613
  * path            (path) <U20 './ST4.2018092500.01h' './ST4.2018092501.01h'
Dimensions without coordinates: x, y
Data variables:
    var_0  (time, x, y) float32 dask.array<shape=(2, 881, 1121), chunksize=(1, 881, 1121)>
    var_1   (time, x, y) float32 dask.array<shape=(2, 881, 1121), chunksize=(1, 881, 1121)>
```

For context I have implemented something similar in dask: https://github.com/dask/dask/pull/3908","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2550/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
72145600,MDU6SXNzdWU3MjE0NTYwMA==,406,millisecond and microseconds support,4806877,closed,0,,987654,5,2015-04-30T12:38:27Z,2015-05-01T20:33:10Z,2015-05-01T20:33:10Z,CONTRIBUTOR,,,,"netcdf4python supports milliseconds and microseconds:

https://github.com/Unidata/netcdf4-python/commit/22d439d6d3602171dc2c23bca0ade31d3c49ad20

would it be possible to support in X-ray?
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/406/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue