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BUG: Fix .loc/.iloc/.at/iat cast unexpectedly with object dtype #49306

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BUG: Fix .loc/.iloc/.at/iat cast unexpectedly with object dtype #49306

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4c1a66b
BUG: .loc/.iloc/.at/iat cast items of type pd.Series to np.ndarray wi…
Oct 25, 2022
99e2874
fix pre-commit
Oct 25, 2022
e38615a
add issue number in test
xr-chen Oct 25, 2022
717bd88
Update doc/source/whatsnew/v2.0.0.rst
xr-chen Oct 25, 2022
da20a87
Merge branch 'main' into obj
xr-chen Oct 25, 2022
4cce372
add comment
xr-chen Oct 29, 2022
0807269
Merge branch 'main' into obj
xr-chen Oct 29, 2022
b246f77
Merge remote-tracking branch 'upstream/main' into obj
xr-chen Jan 11, 2023
533eeb9
Merge branch 'main' into obj
xr-chen Jan 13, 2023
f60b4ca
Merge remote-tracking branch 'upstream/main' into obj
xr-chen Feb 1, 2023
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v2.0.0.rst
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Expand Up @@ -323,8 +323,8 @@ Indexing
- Bug in :meth:`DataFrame.reindex` casting dtype to ``object`` when :class:`DataFrame` has single extension array column when re-indexing ``columns`` and ``index`` (:issue:`48190`)
- Bug in :func:`~DataFrame.describe` when formatting percentiles in the resulting index showed more decimals than needed (:issue:`46362`)
- Bug in :meth:`DataFrame.compare` does not recognize differences when comparing ``NA`` with value in nullable dtypes (:issue:`48939`)
- Bug in :meth:`Series.loc` casting :class:`Series` to ``np.dnarray`` when assign :class:`Series` at predefined index of ``object`` dtype :class:`Series` (:issue:`48933`)
-

Missing
^^^^^^^
- Bug in :meth:`Index.equals` raising ``TypeError`` when :class:`Index` consists of tuples that contain ``NA`` (:issue:`48446`)
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4 changes: 2 additions & 2 deletions pandas/core/internals/blocks.py
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Expand Up @@ -973,8 +973,8 @@ def setitem(self, indexer, value) -> Block:

# length checking
check_setitem_lengths(indexer, value, values)

value = extract_array(value, extract_numpy=True)
if self.dtype != _dtype_obj:
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Do we even need the extract_array call at all? I think the point of it is to explicitly convert a Series / Index to an object-dtype ndarray. If that's the case you are trying to avoid I don't think even need the condition here

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I think we need the extract_array call, otherwise, some tests in the indexing folder will not pass.

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Interesting - do you know what the failures are? Are they Index-related?

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definitely add a comment here pointing back to the PR/issue

might be np_can_hold_element assumes extract_array has been called, don't quote me on that.

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@xr-chen can you confirm what @jbrockmendel is saying? I'm not sure yet if this is worth doing as is or if we should try to solve the issue comprehensively

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@WillAyd I think he was right, he definitely knows extract_array and np_can_hold_element better than me. Do you have any plans on fixing it comprehensively?

value = extract_array(value, extract_numpy=True)
try:
casted = np_can_hold_element(values.dtype, value)
except LossySetitemError:
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16 changes: 16 additions & 0 deletions pandas/tests/indexing/test_indexing.py
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Expand Up @@ -1112,3 +1112,19 @@ def test_scalar_setitem_series_with_nested_value_length1(value, indexer_sli):
assert (ser.loc[0] == value).all()
else:
assert ser.loc[0] == value


def test_object_dtype_series_set_series_element():
# GH48933
s1 = Series(dtype="O", index=["a", "b"])

s1["a"] = Series()
s1.loc["b"] = Series()

tm.assert_series_equal(s1.loc["a"], Series())
tm.assert_series_equal(s1.loc["b"], Series())

s2 = Series(dtype="O", index=["a", "b"])

s2.iloc[1] = Series()
tm.assert_series_equal(s2.iloc[1], Series())