DOC: .get_slice_bound in MultiIndex needs documentation. (pandas-dev#29967)

Author: proost

pandas/core/indexes/multi.py

@@ -1,6 +1,7 @@
 from collections import OrderedDict
 import datetime
 from sys import getsizeof
+from typing import Hashable, Sequence, Union
 import warnings
 
 import numpy as np
@@ -1266,17 +1267,10 @@ def _get_grouper_for_level(self, mapper, level):
             # Remove unobserved levels from level_index
             level_index = level_index.take(uniques)
 
-<<<<<<< HEAD
-        if not level_index.tolist():
-            grouper = level_index
-        else:
-            grouper = level_index.take(codes)
-=======
         if len(level_index):
             grouper = level_index.take(codes)
         else:
             grouper = level_index.take(codes, fill_value=True)
->>>>>>> upstream/master
 
         return grouper, codes, level_index
 
@@ -2436,8 +2430,53 @@ def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
 
         return target, indexer
 
-    def get_slice_bound(self, label, side, kind):
+    def get_slice_bound(
+        self, label: Union[Hashable, Sequence[Hashable]], side: str, kind: str
+    ) -> int:
+        """
+        For an ordered MultiIndex, compute slice bound
+        that corresponds to given label.
+
+        Returns leftmost (one-past-the-rightmost if `side=='right') position
+        of given label.
 
+        Parameters
+        ----------
+        label : object or tuple of objects
+        side : {'left', 'right'}
+        kind : {'loc', 'getitem'}
+
+        Returns
+        -------
+        int
+            Index of label.
+
+        Notes
+        -----
+        This method only works if level 0 index of the MultiIndex is lexsorted.
+
+        Examples
+        --------
+        >>> mi = pd.MultiIndex.from_arrays([list('abbc'), list('gefd')])
+
+        Get the locations from the leftmost 'b' in the first level
+        until the end of the multiindex:
+
+        >>> mi.get_slice_bound('b', side="left", kind="loc")
+        1
+
+        Like above, but if you get the locations from the rightmost
+        'b' in the first level and 'f' in the second level:
+
+        >>> mi.get_slice_bound(('b','f'), side="right", kind="loc")
+        3
+
+        See Also
+        --------
+        MultiIndex.get_loc : Get location for a label or a tuple of labels.
+        MultiIndex.get_locs : Get location for a label/slice/list/mask or a
+                              sequence of such.
+        """
         if not isinstance(label, tuple):
             label = (label,)
         return self._partial_tup_index(label, side=side)

pandas/tests/indexes/test_base.py

@@ -2233,30 +2233,6 @@ def test_groupby(self):
 
         tm.assert_dict_equal(result, expected)
 
-    def test_groupby_nan_index_value(self):
-        df = pd.DataFrame([["x", np.nan, 1]], columns=["A", "B", "C"]).set_index(
-            ["A", "B"]
-        )
-        result = df.groupby(level=["A", "B"]).C.sum()
-        result = np.asarray(result)
-
-        s = Series([])
-        s.name = "C"
-        expected = s.astype("int64")
-        expected = np.asarray(expected)
-        tm.assert_numpy_array_equal(result, expected)
-
-        df = pd.DataFrame(
-            [["x", np.nan, 1, 2], [None, "y", 3, 4]], columns=["A", "B", "C", "D"]
-        ).set_index(["A", "B", "C"])
-        result = df.groupby(level=["A", "B"]).D.sum()
-        s = Series([])
-        s.name = "D"
-        expected = s.astype("int64")
-        result = np.asarray(result)
-        expected = np.asarray(expected)
-        tm.assert_numpy_array_equal(result, expected)
-
     @pytest.mark.parametrize(
         "mi,expected",
         [