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/7630#issuecomment-1478617771,https://api.github.com/repos/pydata/xarray/issues/7630,1478617771,IC_kwDOAMm_X85YIeqr,90059220,2023-03-21T21:39:22Z,2023-03-21T21:39:22Z,NONE,"Thanks all, but  it returns the `ValueError: output array is read-only`. Apparently, this is caused by `.expand_dims()` (see https://github.com/pydata/xarray/issues/3813). The work-around seems to be 
```python
nc = nc.expand_dims(time=times_).copy()
```
Though I have no idea why.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1624560934
https://github.com/pydata/xarray/issues/7108#issuecomment-1267830185,https://api.github.com/repos/pydata/xarray/issues/7108,1267830185,IC_kwDOAMm_X85LkY2p,90059220,2022-10-05T02:21:15Z,2022-10-05T02:21:15Z,NONE,"Thanks, it finally worked.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1391699976
https://github.com/pydata/xarray/issues/7108#issuecomment-1266030505,https://api.github.com/repos/pydata/xarray/issues/7108,1266030505,IC_kwDOAMm_X85Ldhep,90059220,2022-10-03T20:49:24Z,2022-10-03T20:49:24Z,NONE,"The values in `nc.lon` are technically ordered 'as they would be on a mercator projected map with origin at 0 N-0 E' considering I am dealing with data around 180 lon. Not that it would mater for pandas/xarray in that case.  I suppose re-projecting it on a 0-360 would be the only way around this specific issue. 

And to answer earlier comments, `sub = nc_bug.sel(lon = 161.001, tolerance=.1)` raised the following: `KeyError: ""not all values found in index 'lon'. Try setting the `method` keyword argument (example: method='nearest').""`
Which, when tried raised `ValueError: index must be monotonic increasing or decreasing`. It is indeed a problem with the order of the index. 

Thanks for your help and your time.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1391699976
https://github.com/pydata/xarray/issues/7108#issuecomment-1263045823,https://api.github.com/repos/pydata/xarray/issues/7108,1263045823,IC_kwDOAMm_X85LSIy_,90059220,2022-09-30T02:58:34Z,2022-09-30T02:58:34Z,NONE,"Returned the following:
`NotImplementedError: cannot use ``method`` argument if any indexers are slice objects`

```
Traceback (most recent call last):

  Cell In [3], line 1
    sub = nc_bug.sel(lon = slice(161.001, 162.001), tolerance=0.1)

  File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\dataset.py:2533 in sel
    query_results = map_index_queries(

  File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\indexing.py:183 in map_index_queries
    results.append(index.sel(labels, **options))  # type: ignore[call-arg]

  File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\indexes.py:377 in sel
    indexer = _query_slice(self.index, label, coord_name, method, tolerance)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1391699976
https://github.com/pydata/xarray/issues/6759#issuecomment-1176948402,https://api.github.com/repos/pydata/xarray/issues/6759,1176948402,IC_kwDOAMm_X85GJs6y,90059220,2022-07-07T01:43:10Z,2022-07-07T01:43:10Z,NONE,"Wow, I should really dig deeper in the documentation sometimes. Thanks a lot, it fixed it. Although it does remove the original `nan`, which can be reintroduced using a mask.
Thank you again for your time.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1296475783
https://github.com/pydata/xarray/issues/6691#issuecomment-1158434252,https://api.github.com/repos/pydata/xarray/issues/6691,1158434252,IC_kwDOAMm_X85FDE3M,90059220,2022-06-17T02:54:27Z,2022-06-17T02:54:27Z,NONE,"Thank you for upgrading this question. Using keewis suggestion:
> We could try to work around this by wrapping `argmin` and `argmax` in a function that ravels / unravels the reduce dimensions.

I had a look into `numpy` documentation and came up with a work around like so:
```python
import numpy as np, xarray as xr

arr = xr.DataArray(np.ones((5,6,7)))
arr[1,3,2], arr[3,1,4] = 0, 2

print('Values:',arr.min(), arr.max())

min_pos = np.concatenate(np.where(arr == arr.min()))
max_pos = np.concatenate(np.where(arr == arr.max()))
print('Indexes on nD:', min_pos, max_pos)
```
It is not perfect I suppose but it is doing the job for now.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1268821199