BUG: loc.setitem raising ValueError when df has duplicate columns #39278
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phofl
commented
Jan 19, 2021
phofl
commented
- closes BUG: Setting values to slice fails with duplicated column name #38521
- tests added / passed
- Ensure all linting tests pass, see here for how to run them
- whatsnew entry
phofl
added
the
Indexing
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Is there a more elegant way to check if an element occurs only once in an index? |
| expected = DataFrame([[1, 2, 5], [3, 4, 6]], columns=[0, 1, "0 - Name"]) | ||
| tm.assert_frame_equal(df, expected) | ||
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| def test_setitem_empty_df_duplicate_columns(self): |
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do we need tests for Series?
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Don't think so, indexer has to be a tuple to land there, which is only valid for dataframes I think?
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its weird, but you could do series.loc[("foo",)]
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Yep, definitely weird :)
But this is already converted before reaching that point.
df = Series(index=["a", "b", "b"], dtype="float64")
df.loc[("a", )] = 1
This results in indexer=0. Tested the same with a MultiIndex Series, also 0 there
pandas/core/indexing.py
Outdated
| ) | ||
| and item_labels.is_unique | ||
| and len(item_labels.get_indexer_for([item_labels[indexer[info_axis]]])) | ||
| == 1 |
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lets separate this out into a nested condition and define item_labels[indexer[info_axis]] once, then reuse it on L1856
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Failure unrelated |
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thanks @phofl |
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