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BUG: Fix return type of loc/iloc #61054

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6 changes: 4 additions & 2 deletions pandas/core/indexing.py
Original file line number Diff line number Diff line change
@@ -1066,8 +1066,10 @@ def _getitem_lowerdim(self, tup: tuple):

tup = self._validate_key_length(tup)

for i, key in enumerate(tup):
if is_label_like(key):
# Reverse tuple so that we are indexing along columns before rows
# and avoid unintended dtype inference. # GH60600
for i, key in zip(range(len(tup) - 1, -1, -1), reversed(tup)):
if is_label_like(key) or is_list_like(key):
# We don't need to check for tuples here because those are
# caught by the _is_nested_tuple_indexer check above.
section = self._getitem_axis(key, axis=i)
2 changes: 1 addition & 1 deletion pandas/tests/indexing/multiindex/test_loc.py
Original file line number Diff line number Diff line change
@@ -757,7 +757,7 @@ def test_missing_keys_raises_keyerror(self):
df = DataFrame(np.arange(12).reshape(4, 3), columns=["A", "B", "C"])
df2 = df.set_index(["A", "B"])

with pytest.raises(KeyError, match="1"):
with pytest.raises(KeyError, match="6"):
df2.loc[(1, 6)]

def test_missing_key_raises_keyerror2(self):
12 changes: 10 additions & 2 deletions pandas/tests/indexing/test_loc.py
Original file line number Diff line number Diff line change
@@ -60,6 +60,14 @@ def test_not_change_nan_loc(series, new_series, expected_ser):
tm.assert_frame_equal(df.notna(), ~expected)


def test_loc_dtype():
# GH 60600
df = DataFrame([["a", 1.0, 2.0], ["b", 3.0, 4.0]])
result = df.loc[0, [1, 2]]
expected = df[[1, 2]].loc[0]
tm.assert_series_equal(result, expected)


class TestLoc:
def test_none_values_on_string_columns(self, using_infer_string):
# Issue #32218
@@ -441,7 +449,7 @@ def test_loc_to_fail(self):

msg = (
rf"\"None of \[Index\(\[1, 2\], dtype='{np.dtype(int)}'\)\] are "
r"in the \[index\]\""
r"in the \[columns\]\""
)
with pytest.raises(KeyError, match=msg):
df.loc[[1, 2], [1, 2]]
@@ -807,7 +815,7 @@ def test_loc_setitem_frame_mixed_labels(self):

result = df.loc[0, [1, 2]]
expected = Series(
[1, 3], index=Index([1, 2], dtype=object), dtype=object, name=0
[1, 3], index=Index([1, 2], dtype=object), dtype="int64", name=0
)
tm.assert_series_equal(result, expected)

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