issue_comments

Thanks, it finally worked.

I suppose re-projecting it on a 0-360 would be the only way around this specific issue.

A custom Xarray index would help, e.g., PeriodicBoundaryIndex (#7031) or a GeographicIndex leveraging libraries like S2Geometry or H3.

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 themethodkeyword 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.

TBH, I had to do some research before figuring out what was going on :).

Float indexes are often a source of pain, unfortunately!

...also for my ability to know what's going on, apparently :). Thanks a lot @benbovy .

Yes, that would be great to raise a more informative error. We could also put an issue in upstream if pandas itself has the same issue.

Pandas docs seem stricter than the implementation. From this snippet from pandas source code monotonicity is only required after get_loc fails.

My concern with checking first is that code like below will stop working (if I understand correctly). Is has unique but (alphabetically) unsorted coords (although its order may have meaning for the user). I regularly select a slice by specifying the labels corresponding to the first and last elements I want to extract.

I would suggest in this case to just try while catching any KeyError and raising with a nicer message instead of always checking first.

import xarray as xr da = xr.DataArray([0, 1, 2, 3], coords={'x': ['zero', 'one', 'two', 'three']}) da.sel(x=slice('zero', 'two')) Out[1]: <xarray.DataArray (x: 3)> array([0, 1, 2]) Coordinates: * x (x) <U5 'zero' 'one' 'two'

It looks like the error is because of the non-monotonic coordinate labels for the "lon" coordinate in nc_bug rather than a float precision issue. The "lon" coordinate seems monotonic for nc_ok so it works.

When a slice is given as indexer, Xarray internally calls pandas.Index.slice_indexer(), which requires that the index must be ordered and unique (docs). Unfortunately, Pandas does not mention it while it raises a KeyError. Should we first check the index in Xarray and raise a nicer error message if it is not unique / ordered?

Ah, right. Does it select a value with just nc_bug.sel(lon = 161.001, tolerance=0.1)? Because the lon value which that selects is probably the value you need to use in the slice.

Float indexes are often a source of pain, unfortunately!

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) ```

Generally this is because the floats aren't exactly the same value — does passing tolerance=0.1 help?