DEPR: Deprecate n-dim indexing for Series

Closes pandas-dev#27837

Author: TomAugspurger

doc/source/whatsnew/v1.1.0.rst

@@ -788,6 +788,7 @@ Deprecations
 - :meth:`Categorical.to_dense` is deprecated and will be removed in a future version, use ``np.asarray(cat)`` instead (:issue:`32639`)
 - The ``fastpath`` keyword in the ``SingleBlockManager`` constructor is deprecated and will be removed in a future version (:issue:`33092`)
 - Providing ``suffixes`` as a ``set`` in :func:`pandas.merge` is deprecated. Provide a tuple instead (:issue:`33740`, :issue:`34741`).
+- Indexing a series with a multi-dimensional indexer like ``[:, None]`` to return an ndarray now raises a ``FutureWarning``. Convert to a NumPy array before indexing instead (:issue:`27837`)
 - :meth:`Index.is_mixed` is deprecated and will be removed in a future version, check ``index.inferred_type`` directly instead (:issue:`32922`)
 
 - Passing any arguments but the first one to  :func:`read_html` as

pandas/core/indexers.py

@@ -295,7 +295,7 @@ def length_of_indexer(indexer, target=None) -> int:
     raise AssertionError("cannot find the length of the indexer")
 
 
-def deprecate_ndim_indexing(result):
+def deprecate_ndim_indexing(result, stacklevel=3):
     """
     Helper function to raise the deprecation warning for multi-dimensional
     indexing on 1D Series/Index.
@@ -306,11 +306,11 @@ def deprecate_ndim_indexing(result):
     """
     if np.ndim(result) > 1:
         warnings.warn(
-            "Support for multi-dimensional indexing (e.g. `index[:, None]`) "
-            "on an Index is deprecated and will be removed in a future "
+            "Support for multi-dimensional indexing (e.g. `obj[:, None]`) "
+            "on is deprecated and will be removed in a future "
             "version.  Convert to a numpy array before indexing instead.",
-            DeprecationWarning,
-            stacklevel=3,
+            FutureWarning,
+            stacklevel=stacklevel,
         )
 
 

pandas/core/series.py

@@ -78,7 +78,7 @@
     sanitize_array,
 )
 from pandas.core.generic import NDFrame
-from pandas.core.indexers import unpack_1tuple
+from pandas.core.indexers import deprecate_ndim_indexing, unpack_1tuple
 from pandas.core.indexes.accessors import CombinedDatetimelikeProperties
 from pandas.core.indexes.api import Float64Index, Index, MultiIndex, ensure_index
 import pandas.core.indexes.base as ibase
@@ -950,13 +950,9 @@ def _get_with(self, key):
     def _get_values_tuple(self, key):
         # mpl hackaround
         if com.any_none(*key):
-            # suppress warning from slicing the index with a 2d indexer.
-            # eventually we'll want Series itself to warn.
-            with warnings.catch_warnings():
-                warnings.filterwarnings(
-                    "ignore", "Support for multi-dim", DeprecationWarning
-                )
-                return self._get_values(key)
+            result = self._get_values(key)
+            deprecate_ndim_indexing(result, stacklevel=5)
+            return result
 
         if not isinstance(self.index, MultiIndex):
             raise ValueError("Can only tuple-index with a MultiIndex")

pandas/tests/series/indexing/test_getitem.py

@@ -51,11 +51,7 @@ class TestSeriesGetitemSlices:
     def test_getitem_slice_2d(self, datetime_series):
         # GH#30588 multi-dimensional indexing deprecated
 
-        # This is currently failing because the test was relying on
-        # the DeprecationWarning coming through Index.__getitem__.
-        # We want to implement a warning specifically for Series.__getitem__
-        # at which point this will become a Deprecation/FutureWarning
-        with tm.assert_produces_warning(None):
+        with tm.assert_produces_warning(FutureWarning):
             # GH#30867 Don't want to support this long-term, but
             # for now ensure that the warning from Index
             # doesn't comes through via Series.__getitem__.
@@ -135,3 +131,9 @@ def test_getitem_generator(string_series):
     expected = string_series[string_series > 0]
     tm.assert_series_equal(result, expected)
     tm.assert_series_equal(result2, expected)
+
+
+def test_getitem_ndim_deprecated():
+    s = pd.Series([0, 1])
+    with tm.assert_produces_warning(FutureWarning):
+        s[:, None]