DEPR: change pd.concat sort=None to sort=False (pandas-dev#29786)

Author: jbrockmendel

doc/source/whatsnew/v1.0.0.rst

@@ -445,6 +445,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - Removed previously deprecated "order" argument from :func:`factorize` (:issue:`19751`)
 - Removed previously deprecated "v" argument from :meth:`FrozenNDarray.searchsorted`, use "value" instead (:issue:`22672`)
 - :func:`read_stata` and :meth:`DataFrame.to_stata` no longer supports the "encoding" argument (:issue:`21400`)
+- In :func:`concat` the default value for ``sort`` has been changed from ``None`` to ``False`` (:issue:`20613`)
 - Removed previously deprecated "raise_conflict" argument from :meth:`DataFrame.update`, use "errors" instead (:issue:`23585`)
 - Removed previously deprecated keyword "n" from :meth:`DatetimeIndex.shift`, :meth:`TimedeltaIndex.shift`, :meth:`PeriodIndex.shift`, use "periods" instead (:issue:`22458`)
 -

pandas/core/indexes/api.py

@@ -1,6 +1,5 @@
 import textwrap
 from typing import List, Set
-import warnings
 
 from pandas._libs import NaT, lib
 
@@ -211,12 +210,6 @@ def conv(i):
         index = indexes[0]
         for other in indexes[1:]:
             if not index.equals(other):
-
-                if sort is None:
-                    # TODO: remove once pd.concat sort default changes
-                    warnings.warn(_sort_msg, FutureWarning, stacklevel=8)
-                    sort = True
-
                 return _unique_indices(indexes)
 
         name = get_consensus_names(indexes)[0]

pandas/core/reshape/concat.py

@@ -37,7 +37,7 @@ def concat(
     levels=None,
     names=None,
     verify_integrity: bool = False,
-    sort=None,
+    sort: bool = False,
     copy: bool = True,
 ):
     """
@@ -82,18 +82,16 @@ def concat(
     verify_integrity : bool, default False
         Check whether the new concatenated axis contains duplicates. This can
         be very expensive relative to the actual data concatenation.
-    sort : bool, default None
+    sort : bool, default False
         Sort non-concatenation axis if it is not already aligned when `join`
-        is 'outer'. The current default of sorting is deprecated and will
-        change to not-sorting in a future version of pandas.
-
-        Explicitly pass ``sort=True`` to silence the warning and sort.
-        Explicitly pass ``sort=False`` to silence the warning and not sort.
-
+        is 'outer'.
         This has no effect when ``join='inner'``, which already preserves
         the order of the non-concatenation axis.
 
         .. versionadded:: 0.23.0
+        .. versionchanged:: 1.0.0
+
+           Changed to not sort by default.
 
     copy : bool, default True
         If False, do not copy data unnecessarily.

pandas/tests/frame/test_join.py

@@ -195,7 +195,7 @@ def test_join_left_sequence_non_unique_index():
     tm.assert_frame_equal(joined, expected)
 
 
-@pytest.mark.parametrize("sort_kw", [True, False, None])
+@pytest.mark.parametrize("sort_kw", [True, False])
 def test_suppress_future_warning_with_sort_kw(sort_kw):
     a = DataFrame({"col1": [1, 2]}, index=["c", "a"])
 
@@ -213,12 +213,6 @@ def test_suppress_future_warning_with_sort_kw(sort_kw):
     if sort_kw is False:
         expected = expected.reindex(index=["c", "a", "b"])
 
-    if sort_kw is None:
-        # only warn if not explicitly specified
-        ctx = tm.assert_produces_warning(FutureWarning, check_stacklevel=False)
-    else:
-        ctx = tm.assert_produces_warning(None, check_stacklevel=False)
-
-    with ctx:
+    with tm.assert_produces_warning(None, check_stacklevel=False):
         result = a.join([b, c], how="outer", sort=sort_kw)
     tm.assert_frame_equal(result, expected)

pandas/tests/reshape/test_concat.py

@@ -37,16 +37,6 @@ def sort(request):
     return request.param
 
 
-@pytest.fixture(params=[True, False, None])
-def sort_with_none(request):
-    """Boolean sort keyword for concat and DataFrame.append.
-
-    Includes the default of None
-    """
-    # TODO: Replace with sort once keyword changes.
-    return request.param
-
-
 class TestConcatAppendCommon:
     """
     Test common dtype coercion rules between concat and append.
@@ -775,15 +765,13 @@ def test_concat_join_axes_deprecated(self, axis):
         )
 
         expected = pd.concat([one, two], axis=1, sort=False).reindex(index=two.index)
-        with tm.assert_produces_warning(expected_warning=FutureWarning):
-            result = pd.concat([one, two], axis=1, sort=False, join_axes=[two.index])
+        result = pd.concat([one, two], axis=1, sort=False, join_axes=[two.index])
         tm.assert_frame_equal(result, expected)
 
         expected = pd.concat([one, two], axis=0, sort=False).reindex(
             columns=two.columns
         )
-        with tm.assert_produces_warning(expected_warning=FutureWarning):
-            result = pd.concat([one, two], axis=0, sort=False, join_axes=[two.columns])
+        result = pd.concat([one, two], axis=0, sort=False, join_axes=[two.columns])
         tm.assert_frame_equal(result, expected)
 
 
@@ -875,27 +863,19 @@ def test_append_records(self):
         tm.assert_frame_equal(result, expected)
 
     # rewrite sort fixture, since we also want to test default of None
-    def test_append_sorts(self, sort_with_none):
+    def test_append_sorts(self, sort):
         df1 = pd.DataFrame({"a": [1, 2], "b": [1, 2]}, columns=["b", "a"])
         df2 = pd.DataFrame({"a": [1, 2], "c": [3, 4]}, index=[2, 3])
 
-        if sort_with_none is None:
-            # only warn if not explicitly specified
-            # don't check stacklevel since its set for concat, and append
-            # has an extra stack.
-            ctx = tm.assert_produces_warning(FutureWarning, check_stacklevel=False)
-        else:
-            ctx = tm.assert_produces_warning(None)
-
-        with ctx:
-            result = df1.append(df2, sort=sort_with_none)
+        with tm.assert_produces_warning(None):
+            result = df1.append(df2, sort=sort)
 
         # for None / True
         expected = pd.DataFrame(
             {"b": [1, 2, None, None], "a": [1, 2, 1, 2], "c": [None, None, 3, 4]},
             columns=["a", "b", "c"],
         )
-        if sort_with_none is False:
+        if sort is False:
             expected = expected[["b", "a", "c"]]
         tm.assert_frame_equal(result, expected)
 
@@ -2629,7 +2609,7 @@ def test_concat_empty_and_non_empty_series_regression():
     tm.assert_series_equal(result, expected)
 
 
-def test_concat_sorts_columns(sort_with_none):
+def test_concat_sorts_columns(sort):
     # GH-4588
     df1 = pd.DataFrame({"a": [1, 2], "b": [1, 2]}, columns=["b", "a"])
     df2 = pd.DataFrame({"a": [3, 4], "c": [5, 6]})
@@ -2640,58 +2620,44 @@ def test_concat_sorts_columns(sort_with_none):
         columns=["a", "b", "c"],
     )
 
-    if sort_with_none is False:
+    if sort is False:
         expected = expected[["b", "a", "c"]]
 
-    if sort_with_none is None:
-        # only warn if not explicitly specified
-        ctx = tm.assert_produces_warning(FutureWarning)
-    else:
-        ctx = tm.assert_produces_warning(None)
-
     # default
-    with ctx:
-        result = pd.concat([df1, df2], ignore_index=True, sort=sort_with_none)
+    with tm.assert_produces_warning(None):
+        result = pd.concat([df1, df2], ignore_index=True, sort=sort)
     tm.assert_frame_equal(result, expected)
 
 
-def test_concat_sorts_index(sort_with_none):
+def test_concat_sorts_index(sort):
     df1 = pd.DataFrame({"a": [1, 2, 3]}, index=["c", "a", "b"])
     df2 = pd.DataFrame({"b": [1, 2]}, index=["a", "b"])
 
     # For True/None
     expected = pd.DataFrame(
         {"a": [2, 3, 1], "b": [1, 2, None]}, index=["a", "b", "c"], columns=["a", "b"]
     )
-    if sort_with_none is False:
+    if sort is False:
         expected = expected.loc[["c", "a", "b"]]
 
-    if sort_with_none is None:
-        # only warn if not explicitly specified
-        ctx = tm.assert_produces_warning(FutureWarning)
-    else:
-        ctx = tm.assert_produces_warning(None)
-
     # Warn and sort by default
-    with ctx:
-        result = pd.concat([df1, df2], axis=1, sort=sort_with_none)
+    with tm.assert_produces_warning(None):
+        result = pd.concat([df1, df2], axis=1, sort=sort)
     tm.assert_frame_equal(result, expected)
 
 
-def test_concat_inner_sort(sort_with_none):
+def test_concat_inner_sort(sort):
     # https://github.com/pandas-dev/pandas/pull/20613
     df1 = pd.DataFrame({"a": [1, 2], "b": [1, 2], "c": [1, 2]}, columns=["b", "a", "c"])
     df2 = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=[3, 4])
 
     with tm.assert_produces_warning(None):
         # unset sort should *not* warn for inner join
         # since that never sorted
-        result = pd.concat(
-            [df1, df2], sort=sort_with_none, join="inner", ignore_index=True
-        )
+        result = pd.concat([df1, df2], sort=sort, join="inner", ignore_index=True)
 
     expected = pd.DataFrame({"b": [1, 2, 3, 4], "a": [1, 2, 1, 2]}, columns=["b", "a"])
-    if sort_with_none is True:
+    if sort is True:
         expected = expected[["a", "b"]]
     tm.assert_frame_equal(result, expected)