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BUG: loc casting to float for scalar with MultiIndex df #41374
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Original file line number | Diff line number | Diff line change |
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@@ -886,26 +886,22 @@ def _getitem_nested_tuple(self, tup: tuple): | |
# handle the multi-axis by taking sections and reducing | ||
# this is iterative | ||
obj = self.obj | ||
axis = 0 | ||
for key in tup: | ||
# GH#41369 Loop in reverse order ensures indexing along columns before rows | ||
# which selects only necessary blocks which avoids dtype conversion if possible | ||
axis = len(tup) - 1 | ||
for key in tup[::-1]: | ||
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if com.is_null_slice(key): | ||
axis += 1 | ||
axis -= 1 | ||
continue | ||
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current_ndim = obj.ndim | ||
obj = getattr(obj, self.name)._getitem_axis(key, axis=axis) | ||
axis += 1 | ||
axis -= 1 | ||
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# if we have a scalar, we are done | ||
if is_scalar(obj) or not hasattr(obj, "ndim"): | ||
break | ||
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# has the dim of the obj changed? | ||
# GH 7199 | ||
if obj.ndim < current_ndim: | ||
axis -= 1 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. i take it this is unreachable? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. No, in theory this is reachable, but does not make sense anymore. We are counting from the maximum number of dimensions backwards, so even if we reduce the dimension we have already reduced our axis to the new maximum number. DataFrame example: |
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return obj | ||
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def _convert_to_indexer(self, key, axis: int, is_setter: bool = False): | ||
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Original file line number | Diff line number | Diff line change |
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@@ -831,3 +831,16 @@ def test_mi_add_cell_missing_row_non_unique(): | |
columns=MultiIndex.from_product([[1, 2], ["A", "B"]]), | ||
) | ||
tm.assert_frame_equal(result, expected) | ||
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def test_loc_get_scalar_casting_to_float(): | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. can you add the .iloc example as well (to assert that its also an int as on master). There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Done |
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# GH#41369 | ||
df = DataFrame( | ||
{"a": 1.0, "b": 2}, index=MultiIndex.from_arrays([[3], [4]], names=["c", "d"]) | ||
) | ||
result = df.loc[(3, 4), "b"] | ||
assert result == 2 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. this test passes on master. 2.0 == 2 is True. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Added an isinstance check |
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assert isinstance(result, np.int64) | ||
result = df.loc[[(3, 4)], "b"].iloc[0] | ||
assert result == 2 | ||
assert isinstance(result, np.int64) |
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"is from has" typo?
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Yes thanks, opened #41808