DEPR: Previous implementation of DataFrame.stack (#55448)

* DEPR: Previous implementation of DataFrame.stack * Remove DataFrame.stack docs on dropping missing values
pandas-dev · Oct 17, 2023 · a83f6aa · a83f6aa
1 parent 8738635
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diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst
@@ -265,6 +265,7 @@ Other Deprecations
 - Deprecated the ``fastpath`` keyword in the :class:`Series` constructor (:issue:`20110`)
 - Deprecated the extension test classes ``BaseNoReduceTests``, ``BaseBooleanReduceTests``, and ``BaseNumericReduceTests``, use ``BaseReduceTests`` instead (:issue:`54663`)
 - Deprecated the option ``mode.data_manager`` and the ``ArrayManager``; only the ``BlockManager`` will be available in future versions (:issue:`55043`)
+- Deprecated the previous implementation of :class:`DataFrame.stack`; specify ``future_stack=True`` to adopt the future version (:issue:`53515`)
 - Deprecating downcasting the results of :meth:`DataFrame.fillna`, :meth:`Series.fillna`, :meth:`DataFrame.ffill`, :meth:`Series.ffill`, :meth:`DataFrame.bfill`, :meth:`Series.bfill` in object-dtype cases. To opt in to the future version, use ``pd.set_option("future.no_silent_downcasting", True)`` (:issue:`54261`)
 -
 

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
@@ -9499,40 +9499,27 @@ def stack(
         dog  weight  kg    3.0
              height  m     4.0
         dtype: float64
-
-        **Dropping missing values**
-
-        >>> df_multi_level_cols3 = pd.DataFrame([[None, 1.0], [2.0, 3.0]],
-        ...                                     index=['cat', 'dog'],
-        ...                                     columns=multicol2)
-
-        Note that rows where all values are missing are dropped by
-        default but this behaviour can be controlled via the dropna
-        keyword parameter:
-
-        >>> df_multi_level_cols3
-            weight height
-                kg      m
-        cat    NaN    1.0
-        dog    2.0    3.0
-        >>> df_multi_level_cols3.stack(dropna=False)
-                weight  height
-        cat kg     NaN     NaN
-            m      NaN     1.0
-        dog kg     2.0     NaN
-            m      NaN     3.0
-        >>> df_multi_level_cols3.stack(dropna=True)
-                weight  height
-        cat m      NaN     1.0
-        dog kg     2.0     NaN
-            m      NaN     3.0
         """
         if not future_stack:
             from pandas.core.reshape.reshape import (
                 stack,
                 stack_multiple,
             )
 
+            if (
+                dropna is not lib.no_default
+                or sort is not lib.no_default
+                or self.columns.nlevels > 1
+            ):
+                warnings.warn(
+                    "The previous implementation of stack is deprecated and will be "
+                    "removed in a future version of pandas. See the What's New notes "
+                    "for pandas 2.1.0 for details. Specify future_stack=True to adopt "
+                    "the new implementation and silence this warning.",
+                    FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
+
             if dropna is lib.no_default:
                 dropna = True
             if sort is lib.no_default:

diff --git a/pandas/tests/extension/base/reshaping.py b/pandas/tests/extension/base/reshaping.py
@@ -249,6 +249,9 @@ def test_merge_on_extension_array_duplicates(self, data):
         )
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:The previous implementation of stack is deprecated"
+    )
     @pytest.mark.parametrize(
         "columns",
         [

diff --git a/pandas/tests/extension/test_sparse.py b/pandas/tests/extension/test_sparse.py
@@ -133,6 +133,9 @@ def test_concat_mixed_dtypes(self, data):
         )
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:The previous implementation of stack is deprecated"
+    )
     @pytest.mark.parametrize(
         "columns",
         [