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11 changes: 5 additions & 6 deletions doc/source/whatsnew/v0.24.2.rst
Original file line number Diff line number Diff line change
Expand Up @@ -22,13 +22,14 @@ Fixed Regressions

- Fixed regression in :meth:`DataFrame.all` and :meth:`DataFrame.any` where ``bool_only=True`` was ignored (:issue:`25101`)

- Fixed regression in :meth:`DataFrame.__init__` where mixed type of rows generated `Segmentation fault` (:issue:`25075`)
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Fixed issue in DataFrame construction with passing a mixed list of mixed types could segfault.


.. _whatsnew_0242.enhancements:

Enhancements
^^^^^^^^^^^^

-
-
- The DataFrame class supports list as well as tuples in the ndarray, which previously raised `TypeError`
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this is not needed


.. _whatsnew_0242.bug_fixes:

Expand All @@ -37,9 +38,7 @@ Bug Fixes

**Conversion**

-
-
-
- Fixed bug in :meth:`lib.pyx` where `tuple` to `list` conversion failed (:issue:`25089`)
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this is not needed


**Indexing**

Expand Down Expand Up @@ -94,4 +93,4 @@ Bug Fixes
Contributors
~~~~~~~~~~~~

.. contributors:: v0.24.1..v0.24.2
.. contributors:: v0.24.1..v0.24.2
2 changes: 1 addition & 1 deletion pandas/_libs/lib.pyx
Original file line number Diff line number Diff line change
Expand Up @@ -2277,7 +2277,7 @@ def to_object_array(rows: object, int min_width=0):
result = np.empty((n, k), dtype=object)

for i in range(n):
row = <list>input_rows[i]
row = list(input_rows[i])

for j in range(len(row)):
result[i, j] = row[j]
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7 changes: 7 additions & 0 deletions pandas/tests/frame/test_constructors.py
Original file line number Diff line number Diff line change
Expand Up @@ -1183,6 +1183,13 @@ def test_constructor_mixed_dict_and_Series(self):
index=['a', 'b'])
tm.assert_frame_equal(result, expected)

def test_constructor_mixed_type_rows(self):
data = [[1, 2], (3, 4)]
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add the issue number as a comment

result = DataFrame(data)
data2 = [[1, 2], [3, 4]]
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you can inline data2 to the constructor

expected = DataFrame(data2)
tm.assert_frame_equal(result, expected)

def test_constructor_tuples(self):
result = DataFrame({'A': [(1, 2), (3, 4)]})
expected = DataFrame({'A': Series([(1, 2), (3, 4)])})
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