CLN: fixed formatting, typing, and isort issues

Author: jacobaustin123

pandas/core/frame.py

@@ -15,7 +15,7 @@
 import itertools
 import sys
 from textwrap import dedent
-from typing import FrozenSet, List, Optional, Set, Type, Union, Callable
+from typing import Callable, FrozenSet, List, Optional, Set, Type, Union
 import warnings
 
 import numpy as np
@@ -4977,7 +4977,7 @@ def sort_values(
         inplace=False,
         kind="quicksort",
         na_position="last",
-        key : Callable = None
+        key : Union[Callable, None] = None
     ):
         inplace = validate_bool_kwarg(inplace, "inplace")
         axis = self._get_axis_number(axis)
@@ -5029,7 +5029,7 @@ def sort_index(
         na_position="last",
         sort_remaining=True,
         by=None,
-        key : Callable = None
+        key : Union[Callable, None] = None
     ):
 
         # TODO: this can be combined with Series.sort_index impl as

pandas/core/indexes/base.py

@@ -1,7 +1,7 @@
 from datetime import datetime, timedelta
 import operator
 from textwrap import dedent
-from typing import Union, Callable
+from typing import Callable, Union
 import warnings
 
 import numpy as np

pandas/core/series.py

@@ -5,7 +5,7 @@
 from io import StringIO
 from shutil import get_terminal_size
 from textwrap import dedent
-from typing import Any, Callable
+from typing import Any, Callable, Union
 import warnings
 
 import numpy as np
@@ -3019,7 +3019,7 @@ def sort_values(
         inplace=False,
         kind="quicksort",
         na_position="last",
-        key : Callable = None
+        key: Union[Callable, None] = None
     ):
         """
         Sort by the values.
@@ -3042,7 +3042,7 @@ def sort_values(
         na_position : {'first' or 'last'}, default 'last'
             Argument 'first' puts NaNs at the beginning, 'last' puts NaNs at
             the end.
-        key : Callable, default None
+        key : Union[Callable, None], default None
             If not None, apply the key function to every value before
             sorting. Identical to key argument in built-in sorted function.
 
@@ -3220,7 +3220,7 @@ def sort_index(
         kind="quicksort",
         na_position="last",
         sort_remaining=True,
-        key : Callable = None
+        key : Union[Callable, None] = None
     ):
         """
         Sort Series by index labels.
@@ -3249,7 +3249,7 @@ def sort_index(
         sort_remaining : bool, default True
             If True and sorting by level and index is multilevel, sort by other
             levels too (in order) after sorting by specified level.
-        key : Callable, default None
+        key : Union[Callable, None], default None
             If not None, apply the key function to every index element before
             sorting. Identical to key argument in built-in sorted function.
 

pandas/core/sorting.py

@@ -1,6 +1,7 @@
 """ miscellaneous sorting / groupby utilities """
+from typing import Callable, Union
+
 import numpy as np
-from typing import Callable
 
 from pandas._libs import algos, hashtable, lib
 from pandas._libs.hashtable import unique_label_indices
@@ -189,7 +190,7 @@ def indexer_from_factorized(labels, shape, compress=True):
     return get_group_index_sorter(ids, ngroups)
 
 
-def lexsort_indexer(keys, orders=None, na_position="last", key : Callable = None):
+def lexsort_indexer(keys, orders=None, na_position="last", key : Union[Callable, None] = None):
     from pandas.core.arrays import Categorical
 
     labels = []
@@ -201,7 +202,7 @@ def lexsort_indexer(keys, orders=None, na_position="last", key : Callable = None
 
     if key:
         key_func = np.vectorize(key)
-        keys = [key_func(key) for key in keys]
+        keys = [key_func(key) if key.size != 0 else key for key in keys]
 
     for key, order in zip(keys, orders):
 
@@ -239,7 +240,7 @@ def lexsort_indexer(keys, orders=None, na_position="last", key : Callable = None
     return indexer_from_factorized(labels, shape)
 
 
-def nargsort(items, kind="quicksort", ascending=True, na_position="last", key : Callable = None):
+def nargsort(items, kind="quicksort", ascending=True, na_position="last", key: Union[Callable, None] = None):
     """
     This is intended to be a drop-in replacement for np.argsort which
     handles NaNs. It adds ascending and na_position parameters.
@@ -258,7 +259,12 @@ def nargsort(items, kind="quicksort", ascending=True, na_position="last", key :
     if key is not None:
         key_func = np.vectorize(key)
         masked = np.ma.MaskedArray(items, mask)
-        vals = np.asarray(key_func(masked))   # revert from masked
+
+        if masked.size == 0:
+            vals = np.array([])  # vectorize fails on empty object arrays
+        else:
+            vals = np.asarray(key_func(masked))   # revert from masked
+
         return nargsort(vals, kind=kind, ascending=ascending, na_position=na_position, key=None)
 
     idx = np.arange(len(items))

pandas/tests/frame/test_sorting.py

@@ -649,6 +649,13 @@ def test_sort_value_key_nan(self):
         expected = df.sort_values(1, key=str.lower, ascending=False)
         assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize('key', [None, lambda x : x])
+    def test_sort_value_key_empty(self, key):
+        df = DataFrame(np.array([]))
+        
+        df.sort_values(0, key=key)
+        df.sort_index(key=key)
+
     def test_sort_index(self):
         # GH13496