issues

What is your issue?

Hi all, Given the minimal working example bellow:

``` python import pandas as pd import xarray as xr

nc = xr.DataArray([[0]], dims=["x", "y"], coords=dict( lon=(["x"], [1]), lat=(["y"], [1])))

times_ = pd.date_range('2020-01-01', '2022-01-01', freq='1d') dt = times_[0] nc = nc.expand_dims(time=times_)

nc.sel(time=dt) nc.loc['time' == dt]

```

The nc.sel() part works like a charm, but the nc.loc[] return KeyError: "not all values found in index 'time'. Try setting the 'method' keyword argument (example: method='nearest').". Any idea what is happening there ? Considering I want to be able to edit the values of nc for certain sets of [x,y,time], my understanding is that I have to use loc[]. But it does not find the value dt whereas sel() does. How can I solve that ?

What happened?

Using floats .sel() on different datasets from the same provider trigger an error. Despite the fact that the concerned dims are all in float32 type (see log).

Attempts with default float, numpy.float32() and numpy.float64() gave the same output.

What did you expect to happen?

Normal behavior of .sel().

Minimal Complete Verifiable Example

```Python import xarray as xr nc_ok = xr.open_dataset('H08_20220929_0000_1H_ROC010_FLDK.02401_02401.nc').load() sub = nc_ok.sel(longitude = slice(161.001, 162.001))

nc_bug = xr.open_dataset('20220925000000-JAXA-L3C_GHRSST-SSTskin-H08_AHI-v2.0_daily-v02.0-fv01.0.nc').load() sub = nc_bug.sel(lon = slice(161.001, 162.001)) ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
• [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python nc_ok = xr.open_dataset('H08_20220929_0000_1H_ROC010_FLDK.02401_02401.nc').load()

nc_ok.longitude Out[12]: <xarray.DataArray 'longitude' (longitude: 2401)> array([ 80. , 80.05 , 80.1 , ..., 199.9 , 199.95001, 200. ], dtype=float32) Coordinates: * longitude (longitude) float32 80.0 80.05 80.1 80.15 ... 199.9 200.0 200.0 Attributes: long_name: longitude units: degrees_east

nc_bug = xr.open_dataset('20220925000000-JAXA-L3C_GHRSST-SSTskin-H08_AHI-v2.0_daily-v02.0-fv01.0.nc').load()

nc_bug.lon Out[14]: <xarray.DataArray 'lon' (lon: 6001)> array([ 80. , 80.02 , 80.04 , ..., -160.04001, -160.02 , -160. ], dtype=float32) Coordinates: * lon (lon) float32 80.0 80.02 80.04 80.06 ... -160.0 -160.0 -160.0 Attributes: long_name: longitude standard_name: longitude axis: X units: degrees_east valid_min: -180.0 valid_max: 180.0 grid_mapping: Equirectangular comment: geographical coordinates, WGS84 projection

sub = nc_ok.sel(longitude = slice(161.001, 162.001))

sub = nc_bug.sel(lon = slice(161.001, 162.001)) Traceback (most recent call last):

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:3800 in get_loc return self._engine.get_loc(casted_key)

File pandas_libs\index.pyx:138 in pandas._libs.index.IndexEngine.get_loc

File pandas_libs\index.pyx:165 in pandas._libs.index.IndexEngine.get_loc

File pandas_libs\hashtable_class_helper.pxi:1577 in pandas._libs.hashtable.Float64HashTable.get_item

File pandas_libs\hashtable_class_helper.pxi:1587 in pandas._libs.hashtable.Float64HashTable.get_item

KeyError: 161.001

The above exception was the direct cause of the following exception:

Traceback (most recent call last):

Cell In [16], line 1 sub = nc_bug.sel(lon = slice(161.001, 162.001))

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)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\indexes.py:150 in _query_slice indexer = index.slice_indexer(

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:6597 in slice_indexer start_slice, end_slice = self.slice_locs(start, end, step=step)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:6805 in slice_locs start_slice = self.get_slice_bound(start, "left")

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:6724 in get_slice_bound raise err

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:6718 in get_slice_bound slc = self.get_loc(label)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:3802 in get_loc raise KeyError(key) from err

KeyError: 161.001

sub = nc_bug.sel(lon = slice(np.float64(161.001), 162.001)) Traceback (most recent call last):

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\pandas\core\indexes\base.py:3800 in get_loc return self._engine.get_loc(casted_key)

File pandas_libs\index.pyx:138 in pandas._libs.index.IndexEngine.get_loc

File pandas_libs\index.pyx:165 in pandas._libs.index.IndexEngine.get_loc

File pandas_libs\hashtable_class_helper.pxi:1577 in pandas._libs.hashtable.Float64HashTable.get_item

File pandas_libs\hashtable_class_helper.pxi:1587 in pandas._libs.hashtable.Float64HashTable.get_item

KeyError: 161.001 ```

Anything else we need to know?

The data are provided by JAXA P-Tree.

Environment

What is your issue?

I stumbled upon the issue of not having a simple DataArray.rolling.quantile() or Dataset.rolling.quantile(), so I tried using the rolling.reduce() alternative, which seems to alter the normal functioning of functions like numpy.nanpercentile. Namely, nanpercentile act like percentile i.e create huge missing chunks the size of rolling as soon as nan are found within the window. Is there a fix to that ?

Here is the code I used to test it out: ``` python import xarray as xr, numpy as np

m,n = 30,56 tab = np.random.uniform(0, 100, size=(m,n)) ds = xr.DataArray(tab) ds.plot.imshow(center=False)

nb_nan = 8 tab.ravel()[np.random.choice(tab.size, nb_nan, replace=False)] = np.nan ds_nan = xr.DataArray(tab) ds_nan.plot.imshow(center=False)

w = 4 roll = ds_nan.rolling({name: w for name in ['dim_0', 'dim_1']}, center = True)

roll_perc = roll.reduce(np.percentile, q=90) roll_perc.plot.imshow(center=False)

roll_perc_nan = roll.reduce(np.nanpercentile, q=90) roll_perc_nan.plot.imshow(center=False)

What is your issue?

I am working with xarray.core.rolling.DataArrayRolling objects and for some obscure reason, they raise the following error when the .argmin() and .argmax() methods are used: ``` window_size = {name: n for name in ['lat', 'lon']} window = data_nc.rolling(window_size, center=True) peak_min = window.argmin() peak_max = window.argmax()

Traceback (most recent call last): Input In [48] in <cell line: 3> File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\rolling.py:122 in method return self._numpy_or_bottleneck_reduce(

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\rolling.py:541 in _numpy_or_bottleneck_reduce return self.reduce(array_agg_func, keep_attrs=keep_attrs, **kwargs)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\rolling.py:428 in reduce result = windows.reduce(

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\dataarray.py:2696 in reduce var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\variable.py:1804 in reduce data = func(self.data, axis=axis, **kwargs)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\xarray\core\duck_array_ops.py:335 in f return func(values, axis=axis, **kwargs)

File <array_function internals>:180 in argmax

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\numpy\core\fromnumeric.py:1216 in argmax return _wrapfunc(a, 'argmax', axis=axis, out=out, **kwds)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\numpy\core\fromnumeric.py:66 in _wrapfunc return _wrapit(obj, method, args, *kwds)

File ~\Installed_Programs\Anaconda3\envs\phd\lib\site-packages\numpy\core\fromnumeric.py:43 in _wrapit result = getattr(asarray(obj), method)(args, *kwds)

TypeError: 'tuple' object cannot be interpreted as an integer

````` As far as I understand, these methods are included based on thexarraydocumentation, so it should work as.min(),.max()or.mean()` are working fine: https://docs.xarray.dev/en/stable/generated/xarray.core.rolling.DataArrayRolling.argmax.html

Any insight on what I am doing wrong ?