Avoid Index DeprecationWarning in Series getitem

xref pandas-dev#30867

Author: TomAugspurger

pandas/core/indexes/base.py

@@ -4168,6 +4168,13 @@ def __setitem__(self, key, value):
         raise TypeError("Index does not support mutable operations")
 
     def __getitem__(self, key):
+        # To support the deprecation of Index[:, None] returning an
+        # ndarray with a warning, we use a helper method _getitem_deprecate_nd.
+        # Series[:, None] eventaully calls that with warn=False, via
+        # SingleBlockManager.get_slice
+        return self._getitem_deprecate_nd(key)
+
+    def _getitem_deprecate_nd(self, key, warn=True):
         """
         Override numpy.ndarray's __getitem__ method to work as desired.
 
@@ -4199,7 +4206,8 @@ def __getitem__(self, key):
         result = getitem(key)
         if not is_scalar(result):
             if np.ndim(result) > 1:
-                deprecate_ndim_indexing(result)
+                if warn:
+                    deprecate_ndim_indexing(result)
                 return result
             return promote(result)
         else:

pandas/core/internals/managers.py

@@ -1505,7 +1505,11 @@ def get_slice(self, slobj, axis=0):
         if axis >= self.ndim:
             raise IndexError("Requested axis not found in manager")
 
-        return type(self)(self._block._slice(slobj), self.index[slobj], fastpath=True)
+        return type(self)(
+            self._block._slice(slobj),
+            self.index._getitem_deprecate_nd(slobj, warn=False),
+            fastpath=True,
+        )
 
     @property
     def index(self):

pandas/tests/series/indexing/test_indexing.py

@@ -925,3 +925,12 @@ def test_uint_drop(any_int_dtype):
     series.loc[0] = 4
     expected = pd.Series([4, 2, 3], dtype=any_int_dtype)
     tm.assert_series_equal(series, expected)
+
+
+def test_getitem_2d_no_warning():
+    # https://github.com/pandas-dev/pandas/issues/30867
+    # Unclear that we want to support this long-term, but
+    # for now ensure that no warning from Index comes through.
+    series = pd.Series([1, 2, 3], index=[1, 2, 3])
+    with tm.assert_produces_warning(None):
+        series[:, None]