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Problems writing cross-join in dplyr #4206
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romainfrancois
added
tables 🧮
joins and set operations
feature
a feature request or enhancement
labels
Mar 4, 2019
joins are not part of our immediate focus for the next series. This is probably something that can be incubated in another package for the time being. |
In the join refactoring I'm working on currently, this turns out to be a trivial fix so it's likely to make it in 1.0.0 |
hadley
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that referenced
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Jan 13, 2020
Now based on a common approach to modifying x rather than creating a new data frame. New `join_rows()` and `join_cols()` provide common toolset for generate row and col indices. New `filter_join()` and `mutate_join()` reduce duplication in joining code. Tests have been completely rewritten from scratch to focus on the concepts of preserving x (type, row order, and column order) that have become more clear. The test for both empty suffixes has been removed. This mildly weakens the guarantees offered by the join functions, but makes `nest_join()` work as it used to. I don't think adding extra logic to make it error in regular joins is worth it. * Fixes #4206: refactoring revealed a trivial implementation (mostly just removing an exiting error message) * Fixes #4225: the data frame method now does all the work * Fixes #4589: refactoring revealed that `nest_join(keep = T)` could share code with `full_join(keep = T)`
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Sometimes one wants a cross-join, but the obvious way to write that in
dplyr
does not work (though it does work fordbplyr
).Created on 2019-02-20 by the reprex package (v0.2.1)
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