ENH #61033: Add coalesce_keys option to DataFrame.join for preserving join keys #61678
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This adds a coalesce_keys keyword to DataFrame.join to allow
preservation of both join key columns (id and id_right),
instead of automatically coalescing them into a single column.
This is especially useful in full outer joins, where retaining
information about unmatched keys from both sides is important.
Example:
df1.join(df2, on=id, coalesce_keys=False)
This will result in both id and id_right columns being preserved,
rather than merged into a single id.
Includes:
- Modifications to join internals (core/reshape/merge.py)
- A dedicated test file (test_merge_coalesce.py) covering:
- Preservation of join keys when coalesce_keys=False
- Comparison with default behavior (coalesce_keys=True)
- Full outer joins with asymmetric key presence
Co-authored-by: Maria Pereira <[email protected]>
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Add coalesce_keys option to DataFrame.join for preserving join keys
This adds a coalesce_keys keyword to DataFrame.join to allow preservation
of both join key columns (id and id_right), instead of automatically
coalescing them into a single column.
This is especially useful in full outer joins, where retaining information
about unmatched keys from both sides is important.
Example:
df1.join(df2, on=id, coalesce_keys=False)
This will result in both id and id_right columns being preserved, rather
than merged into a single id.
Includes:
Modifications to join internals (core/reshape/merge.py)
A dedicated test file (test_merge_coalesce.py) covering:
All code checks passed.