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/3237#issuecomment-524075569,https://api.github.com/repos/pydata/xarray/issues/3237,524075569,MDEyOklzc3VlQ29tbWVudDUyNDA3NTU2OQ==,13190237,2019-08-22T21:00:34Z,2019-08-22T21:00:34Z,CONTRIBUTOR,"Thanks @shoyer. Cool, then this was easier than I expected. I added the patch and nanargmax/min to the nputils in #3244. What do you think?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,483280810
https://github.com/pydata/xarray/issues/3237#issuecomment-523952983,https://api.github.com/repos/pydata/xarray/issues/3237,523952983,MDEyOklzc3VlQ29tbWVudDUyMzk1Mjk4Mw==,13190237,2019-08-22T15:22:33Z,2019-08-22T15:22:33Z,CONTRIBUTOR,"Those little changes do solve the MCVE, but break at least one test. I don't have enough of an understanding of the (nan)ops logic in xarray to get around the issue. But may be this helps:
#### The change
```
diff --git a/xarray/core/nanops.py b/xarray/core/nanops.py
index 9ba4eae2..784a1d01 100644
--- a/xarray/core/nanops.py
+++ b/xarray/core/nanops.py
@@ -91,17 +91,9 @@ def nanargmin(a, axis=None):
     fill_value = dtypes.get_pos_infinity(a.dtype)
     if a.dtype.kind == ""O"":
         return _nan_argminmax_object(""argmin"", fill_value, a, axis=axis)
-    a, mask = _replace_nan(a, fill_value)
-    if isinstance(a, dask_array_type):
-        res = dask_array.argmin(a, axis=axis)
-    else:
-        res = np.argmin(a, axis=axis)
 
-    if mask is not None:
-        mask = mask.all(axis=axis)
-        if mask.any():
-            raise ValueError(""All-NaN slice encountered"")
-    return res
+    module = dask_array if isinstance(a, dask_array_type) else nputils
+    return module.nanargmin(a, axis=axis)
 
 
 def nanargmax(a, axis=None):
@@ -109,17 +101,8 @@ def nanargmax(a, axis=None):
     if a.dtype.kind == ""O"":
         return _nan_argminmax_object(""argmax"", fill_value, a, axis=axis)
 
-    a, mask = _replace_nan(a, fill_value)
-    if isinstance(a, dask_array_type):
-        res = dask_array.argmax(a, axis=axis)
-    else:
-        res = np.argmax(a, axis=axis)
-
-    if mask is not None:
-        mask = mask.all(axis=axis)
-        if mask.any():
-            raise ValueError(""All-NaN slice encountered"")
-    return res
+    module = dask_array if isinstance(a, dask_array_type) else nputils
+    return module.nanargmax(a, axis=axis)
 
 
 def nansum(a, axis=None, dtype=None, out=None, min_count=None):

```
#### The failing test

``` python       
...                                                                                                
___________ TestVariable.test_reduce ________________                                                                                                                                                     
...

    def f(values, axis=None, skipna=None, **kwargs):
        if kwargs.pop(""out"", None) is not None:
            raise TypeError(""`out` is not valid for {}"".format(name))
    
        values = asarray(values)
    
        if coerce_strings and values.dtype.kind in ""SU"":
            values = values.astype(object)
    
        func = None
        if skipna or (skipna is None and values.dtype.kind in ""cfO""):
            nanname = ""nan"" + name
            func = getattr(nanops, nanname)
        else:
            func = _dask_or_eager_func(name)
    
        try:
            return func(values, axis=axis, **kwargs)
        except AttributeError:
            if isinstance(values, dask_array_type):
                try:  # dask/dask#3133 dask sometimes needs dtype argument
                    # if func does not accept dtype, then raises TypeError
                    return func(values, axis=axis, dtype=values.dtype, **kwargs)
                except (AttributeError, TypeError):
                    msg = ""%s is not yet implemented on dask arrays"" % name
            else:
                msg = (
                    ""%s is not available with skipna=False with the ""
                    ""installed version of numpy; upgrade to numpy 1.12 ""
                    ""or newer to use skipna=True or skipna=None"" % name
                )
>           raise NotImplementedError(msg)
E           NotImplementedError: argmax is not available with skipna=False with the installed version of numpy; upgrade to numpy 1.12 or newer to use skipna=True or skipna=None

...
```
Note: I habe numpy 1.17 instaleed so the error msg here seems missleading.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,483280810