DEPR: ignoring empty entries in pd.concat

doc/source/whatsnew/v3.0.0.rst

@@ -200,6 +200,7 @@ Other Deprecations
 Removal of prior version deprecations/changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 - :class:`.DataFrameGroupBy.idxmin`, :class:`.DataFrameGroupBy.idxmax`, :class:`.SeriesGroupBy.idxmin`, and :class:`.SeriesGroupBy.idxmax` will now raise a ``ValueError`` when used with ``skipna=False`` and an NA value is encountered (:issue:`10694`)
+- :func:`concat` no longer ignores empty objects when determining output dtypes (:issue:`39122`)
 - :func:`read_excel`, :func:`read_json`, :func:`read_html`, and :func:`read_xml` no longer accept raw string or byte representation of the data. That type of data must be wrapped in a :py:class:`StringIO` or :py:class:`BytesIO` (:issue:`53767`)
 - :meth:`DataFrame.groupby` with ``as_index=False`` and aggregation methods will no longer exclude from the result the groupings that do not arise from the input (:issue:`49519`)
 - :meth:`Series.dt.to_pydatetime` now returns a :class:`Series` of :py:class:`datetime.datetime` objects (:issue:`52459`)

pandas/core/dtypes/concat.py

@@ -8,12 +8,10 @@
     TYPE_CHECKING,
     cast,
 )
-import warnings
 
 import numpy as np
 
 from pandas._libs import lib
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.astype import astype_array
 from pandas.core.dtypes.cast import (
@@ -101,28 +99,10 @@ def concat_compat(
     # Creating an empty array directly is tempting, but the winnings would be
     # marginal given that it would still require shape & dtype calculation and
     # np.concatenate which has them both implemented is compiled.
-    orig = to_concat
     non_empties = [x for x in to_concat if _is_nonempty(x, axis)]
-    if non_empties and axis == 0 and not ea_compat_axis:
-        # ea_compat_axis see GH#39574
-        to_concat = non_empties
 
     any_ea, kinds, target_dtype = _get_result_dtype(to_concat, non_empties)
 
-    if len(to_concat) < len(orig):
-        _, _, alt_dtype = _get_result_dtype(orig, non_empties)
-        if alt_dtype != target_dtype:
-            # GH#39122
-            warnings.warn(
-                "The behavior of array concatenation with empty entries is "
-                "deprecated. In a future version, this will no longer exclude "
-                "empty items when determining the result dtype. "
-                "To retain the old behavior, exclude the empty entries before "
-                "the concat operation.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-
     if target_dtype is not None:
         to_concat = [astype_array(arr, target_dtype, copy=False) for arr in to_concat]
 

pandas/tests/dtypes/test_concat.py

@@ -12,12 +12,9 @@ def test_concat_mismatched_categoricals_with_empty():
     ser1 = Series(["a", "b", "c"], dtype="category")
     ser2 = Series([], dtype="category")
 
-    msg = "The behavior of array concatenation with empty entries is deprecated"
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        result = _concat.concat_compat([ser1._values, ser2._values])
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        expected = pd.concat([ser1, ser2])._values
-    tm.assert_categorical_equal(result, expected)
+    result = _concat.concat_compat([ser1._values, ser2._values])
+    expected = pd.concat([ser1, ser2])._values
+    tm.assert_numpy_array_equal(result, expected)
 
 
 def test_concat_single_dataframe_tz_aware():

pandas/tests/groupby/test_groupby.py

@@ -224,8 +224,6 @@ def f3(x):
 
     df2 = DataFrame({"a": [3, 2, 2, 2], "b": range(4), "c": range(5, 9)})
 
-    depr_msg = "The behavior of array concatenation with empty entries is deprecated"
-
     # correct result
     msg = "DataFrameGroupBy.apply operated on the grouping columns"
     with tm.assert_produces_warning(DeprecationWarning, match=msg):
@@ -245,8 +243,7 @@ def f3(x):
     with pytest.raises(AssertionError, match=msg):
         df.groupby("a").apply(f3)
     with pytest.raises(AssertionError, match=msg):
-        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
-            df2.groupby("a").apply(f3)
+        df2.groupby("a").apply(f3)
 
 
 def test_attr_wrapper(ts):

pandas/tests/indexes/test_base.py

@@ -636,9 +636,7 @@ def test_append_empty_preserve_name(self, name, expected):
         left = Index([], name="foo")
         right = Index([1, 2, 3], name=name)
 
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = left.append(right)
+        result = left.append(right)
         assert result.name == expected
 
     @pytest.mark.parametrize(

pandas/tests/reshape/concat/test_append.py

@@ -162,9 +162,7 @@ def test_append_preserve_index_name(self):
         df2 = DataFrame(data=[[1, 4, 7], [2, 5, 8], [3, 6, 9]], columns=["A", "B", "C"])
         df2 = df2.set_index(["A"])
 
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = df1._append(df2)
+        result = df1._append(df2)
         assert result.index.name == "A"
 
     indexes_can_append = [

pandas/tests/reshape/concat/test_append_common.py

@@ -691,15 +691,12 @@ def test_concat_categorical_empty(self):
 
         s1 = Series([], dtype="category")
         s2 = Series([1, 2], dtype="category")
+        exp = s2.astype(object)
+        tm.assert_series_equal(pd.concat([s1, s2], ignore_index=True), exp)
+        tm.assert_series_equal(s1._append(s2, ignore_index=True), exp)
 
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            tm.assert_series_equal(pd.concat([s1, s2], ignore_index=True), s2)
-            tm.assert_series_equal(s1._append(s2, ignore_index=True), s2)
-
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            tm.assert_series_equal(pd.concat([s2, s1], ignore_index=True), s2)
-            tm.assert_series_equal(s2._append(s1, ignore_index=True), s2)
+        tm.assert_series_equal(pd.concat([s2, s1], ignore_index=True), exp)
+        tm.assert_series_equal(s2._append(s1, ignore_index=True), exp)
 
         s1 = Series([], dtype="category")
         s2 = Series([], dtype="category")
@@ -719,15 +716,12 @@ def test_concat_categorical_empty(self):
         s1 = Series([], dtype="category")
         s2 = Series([np.nan, np.nan])
 
-        # empty Series is ignored
-        exp = Series([np.nan, np.nan])
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            tm.assert_series_equal(pd.concat([s1, s2], ignore_index=True), exp)
-            tm.assert_series_equal(s1._append(s2, ignore_index=True), exp)
+        exp = Series([np.nan, np.nan], dtype=object)
+        tm.assert_series_equal(pd.concat([s1, s2], ignore_index=True), exp)
+        tm.assert_series_equal(s1._append(s2, ignore_index=True), exp)
 
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            tm.assert_series_equal(pd.concat([s2, s1], ignore_index=True), exp)
-            tm.assert_series_equal(s2._append(s1, ignore_index=True), exp)
+        tm.assert_series_equal(pd.concat([s2, s1], ignore_index=True), exp)
+        tm.assert_series_equal(s2._append(s1, ignore_index=True), exp)
 
     def test_categorical_concat_append(self):
         cat = Categorical(["a", "b"], categories=["a", "b"])

pandas/tests/reshape/concat/test_empty.py

@@ -62,11 +62,9 @@ def test_concat_empty_series(self):
 
         s1 = Series([1, 2, 3], name="x")
         s2 = Series(name="y", dtype="float64")
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            res = concat([s1, s2], axis=0)
+        res = concat([s1, s2], axis=0)
         # name will be reset
-        exp = Series([1, 2, 3])
+        exp = Series([1, 2, 3], dtype="float64")
         tm.assert_series_equal(res, exp)
 
         # empty Series with no name

pandas/tests/reshape/concat/test_series.py

@@ -43,10 +43,8 @@ def test_concat_empty_and_non_empty_series_regression(self):
         s1 = Series([1])
         s2 = Series([], dtype=object)
 
-        expected = s1
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = concat([s1, s2])
+        expected = s1.astype(object)
+        result = concat([s1, s2])
         tm.assert_series_equal(result, expected)
 
     def test_concat_series_axis1(self):

pandas/tests/series/methods/test_combine_first.py

@@ -63,11 +63,9 @@ def test_combine_first(self):
         # corner case
         ser = Series([1.0, 2, 3], index=[0, 1, 2])
         empty = Series([], index=[], dtype=object)
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = ser.combine_first(empty)
+        result = ser.combine_first(empty)
         ser.index = ser.index.astype("O")
-        tm.assert_series_equal(ser, result)
+        tm.assert_series_equal(result, ser.astype(object))
 
     def test_combine_first_dt64(self, unit):
         s0 = to_datetime(Series(["2010", np.nan])).dt.as_unit(unit)
@@ -112,10 +110,8 @@ def test_combine_first_timezone_series_with_empty_series(self):
         )
         s1 = Series(range(10), index=time_index)
         s2 = Series(index=time_index)
-        msg = "The behavior of array concatenation with empty entries is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = s1.combine_first(s2)
-        tm.assert_series_equal(result, s1)
+        result = s1.combine_first(s2)
+        tm.assert_series_equal(result, s1.astype(np.float64))
 
     def test_combine_first_preserves_dtype(self):
         # GH51764