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/4499#issuecomment-706738427,https://api.github.com/repos/pydata/xarray/issues/4499,706738427,MDEyOklzc3VlQ29tbWVudDcwNjczODQyNw==,10194086,2020-10-11T17:26:25Z,2020-10-11T17:26:25Z,MEMBER,Yes I think the failures are unrelated (#4502),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,718468155
https://github.com/pydata/xarray/pull/4499#issuecomment-706452192,https://api.github.com/repos/pydata/xarray/issues/4499,706452192,MDEyOklzc3VlQ29tbWVudDcwNjQ1MjE5Mg==,2448579,2020-10-10T00:16:57Z,2020-10-10T00:16:57Z,MEMBER,"Upstream dev failures look unrelated to this PR. Seems to be from dask's meta inference
``` python
=================================== FAILURES ===================================
________________ test_argmin_max[x-False-min-True-False-str-1] _________________

dim_num = 1, dtype = <class 'str'>, contains_nan = False, dask = True
func = 'min', skipna = False, aggdim = 'x'

    @pytest.mark.parametrize(""dim_num"", [1, 2])
    @pytest.mark.parametrize(""dtype"", [float, int, np.float32, np.bool_, str])
    @pytest.mark.parametrize(""contains_nan"", [True, False])
    @pytest.mark.parametrize(""dask"", [False, True])
    @pytest.mark.parametrize(""func"", [""min"", ""max""])
    @pytest.mark.parametrize(""skipna"", [False, True])
    @pytest.mark.parametrize(""aggdim"", [""x"", ""y""])
    def test_argmin_max(dim_num, dtype, contains_nan, dask, func, skipna, aggdim):
        # pandas-dev/pandas#16830, we do not check consistency with pandas but
        # just make sure da[da.argmin()] == da.min()
    
        if aggdim == ""y"" and dim_num < 2:
            pytest.skip(""dim not in this test"")
    
        if dask and not has_dask:
            pytest.skip(""requires dask"")
    
        if contains_nan:
            if not skipna:
                pytest.skip(
                    ""numpy's argmin (not nanargmin) does not handle "" ""object-dtype""
                )
            if skipna and np.dtype(dtype).kind in ""iufc"":
                pytest.skip(""numpy's nanargmin raises ValueError for all nan axis"")
        da = construct_dataarray(dim_num, dtype, contains_nan=contains_nan, dask=dask)
    
        with warnings.catch_warnings():
            warnings.filterwarnings(""ignore"", ""All-NaN slice"")
    
            actual = da.isel(
                **{aggdim: getattr(da, ""arg"" + func)(dim=aggdim, skipna=skipna).compute()}
            )
            expected = getattr(da, func)(dim=aggdim, skipna=skipna)
>           assert_allclose(
    
        if dtype and meta.dtype != dtype:
>           meta = meta.astype(dtype)
E           ValueError: invalid literal for int() with base 10: ''

```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,718468155