TST: ensure groupby get by index value pandas-dev#33439

Author: sam-cohan

doc/source/whatsnew/v1.1.0.rst

@@ -750,6 +750,7 @@ Other
 - Bug in :meth:`DataFrame.__dir__` caused a segfault when using unicode surrogates in a column name (:issue:`25509`)
 - Bug in :meth:`DataFrame.plot.scatter` caused an error when plotting variable marker sizes (:issue:`32904`)
 - :class:`IntegerArray` now implements the ``sum`` operation (:issue:`33172`)
+- Added test for getting values by index value during groupby aggregation (:issue:`33439`)
 
 .. ---------------------------------------------------------------------------
 

pandas/tests/groupby/test_groupby.py

@@ -199,7 +199,7 @@ def test_pass_args_kwargs(ts, tsframe):
     def f(x, q=None, axis=0):
         return np.percentile(x, q, axis=axis)
 
-    g = lambda x: np.percentile(x, 80, axis=0)
+    def g(x): return np.percentile(x, 80, axis=0)
 
     # Series
     ts_grouped = ts.groupby(lambda x: x.month)
@@ -422,7 +422,7 @@ def test_frame_groupby_columns(tsframe):
     assert len(aggregated.columns) == 2
 
     # transform
-    tf = lambda x: x - x.mean()
+    def tf(x): return x - x.mean()
     groupedT = tsframe.T.groupby(mapping, axis=0)
     tm.assert_frame_equal(groupedT.transform(tf).T, grouped.transform(tf))
 
@@ -1020,7 +1020,7 @@ def test_seriesgroupby_name_attr(df):
     assert result.count().name == "C"
     assert result.mean().name == "C"
 
-    testFunc = lambda x: np.sum(x) * 2
+    def testFunc(x): return np.sum(x) * 2
     assert result.agg(testFunc).name == "C"
 
 
@@ -1102,7 +1102,7 @@ def test_series_grouper_noncontig_index():
     grouped = values.groupby(labels)
 
     # accessing the index elements causes segfault
-    f = lambda x: len(set(map(id, x.index)))
+    def f(x): return len(set(map(id, x.index)))
     grouped.agg(f)
 
 
@@ -2012,3 +2012,16 @@ def test_groups_repr_truncates(max_seq_items, expected):
 
         result = df.groupby(np.array(df.a)).groups.__repr__()
         assert result == expected
+
+
+def test_groupby_get_by_index():
+    # GH 33439
+    df = pd.DataFrame({
+        "A": ["S", "W", "W"],
+        "B": [1.0, 1.0, 2.0],
+    })
+    res = df.groupby("A").agg(
+        {"B": lambda x: x.get(x.index[-1])}
+    )
+    expected = pd.DataFrame(dict(A=["S", "W"], B=[1.0, 2.0])).set_index("A")
+    pd.testing.assert_frame_equal(res, expected)