REFACT: switch to nargsort from sorting.py

pandas/core/indexes/base.py

@@ -86,7 +86,7 @@
 import pandas.core.missing as missing
 from pandas.core.ops import get_op_result_name
 from pandas.core.ops.invalid import make_invalid_op
-from pandas.core.sorting import ensure_key_mapped
+from pandas.core.sorting import ensure_key_mapped, nargsort
 from pandas.core.strings import StringMethods
 
 from pandas.io.formats.printing import (
@@ -4452,25 +4452,12 @@ def sort_values(
  idx = ensure_key_mapped(self, key)
 
  # GH 35584. Sort missing values according to na_position kwarg
+ # ignore na_position for MutiIndex
  if not isinstance(self, ABCMultiIndex):
- bad = isna(idx)
- good = ~bad
- _as = np.arange(len(idx), dtype=np.int64)
- if na_position == "last":
- _as = np.concatenate([_as[good][idx[good].argsort()], _as[bad]])
- if not ascending:
- _as[: np.sum(good)] = _as[: np.sum(good)][::-1]
- elif na_position == "first":
- _as = np.concatenate([_as[bad], _as[good][idx[good].argsort()]])
- if not ascending:
- _as[np.sum(bad) :] = _as[np.sum(bad) :][::-1]
- else:
- raise ValueError(
- "Invalid na_position keyword argument value. "
- f"Can be only 'first' or 'last', '{na_position}' given."
- )
+ _as = nargsort(
+ items=idx, ascending=ascending, na_position=na_position, key=key
+ )
  else:
- # GH 35584. Ignore na_position for MultiIndex
  _as = idx.argsort()
  if not ascending:
  _as = _as[::-1]

pandas/tests/indexes/test_common.py

@@ -409,8 +409,7 @@ def test_sort_values_with_missing(idx, na_position, expected):
  if na_position not in ["first", "last"]:
  with pytest.raises(
  ValueError,
- match="Invalid na_position keyword argument value. "
- f"Can be only 'first' or 'last', '{na_position}' given.",
+ match=f"invalid na_position: {na_position}",
  ):
  idx.sort_values(na_position=na_position)
  else: