Let xarray return np.nan for count in empty bins.

Xarray passes through min_count=1 so this is pretty clean.
I removed the xarray test since it needn't live here

Author: dcherian

dask_groupby/core.py

@@ -1146,15 +1146,14 @@ def groupby_reduce(
     )
     reduction.fill_value[func] = _get_fill_value(reduction.dtype, reduction.fill_value[func])
 
-    # TODO: delete?
-    # if fill_value is None:
-    #     fill_value = reduction.fill_value[func]
-
     if min_count is not None:
-        assert func in ["nansum", "nanprod"]
+        # Let this pass so that xarray can keep return np.nan for bins with
+        # no observations. The restriction of min_count to nansum, nanprod
+        # seems to be an Xarray limitation so there's no reason we need to copy it.
         # nansum, nanprod have fill_value=0, 1
         # overwrite than when min_count is set
-        fill_value = np.nan
+        if func in ["nansum", "nanprod"] and fill_value is None:
+            fill_value = np.nan
 
     # TODO: handle reduction being something custom not present in numpy_groupies
     if not is_duck_dask_array(array) and not is_duck_dask_array(by):

tests/test_core.py

@@ -116,10 +116,7 @@ def test_groupby_reduce(
 
 @pytest.mark.parametrize("engine", ["numpy", "numba"])
 @pytest.mark.parametrize("size", ((12,), (12, 5)))
-@pytest.mark.parametrize(
-    "func",
-    ALL_FUNCS,
-)
+@pytest.mark.parametrize("func", ALL_FUNCS)
 def test_groupby_reduce_all(size, func, engine):
 
     by = np.ones(size[-1])

tests/test_xarray.py

@@ -290,10 +290,6 @@ def test_xarray_groupby_bins(chunks):
     )
     xr.testing.assert_equal(actual, expected)
 
-    # TODO: fix this test?
-    # expected_xr = array.groupby_bins(labels, bins=[1, 2, 4, 5]).count() #.fillna(0)
-    # xr.testing.assert_equal(actual, expected_xr)
-
     da = xr.DataArray(np.random.randn(2, 3, 4))
     bins = [-1, 0, 1, 2]
     with xr.set_options(use_numpy_groupies=False):