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Merge pull request #22 from jennybc/patch-1 

extra `)`
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Hadley Wickham 2016-01-07 14:39:01 -06:00
parent 5d33dd0b50 387d65c4f1
commit b68a0fea04
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relational-data.Rmd
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@ -236,7 +236,7 @@ dplyr | merge
`inner_join(x, y)` | `merge(x, y)` `inner_join(x, y)` | `merge(x, y)`
`left_join(x, y)` | `merge(x, y, all.x = TRUE)` `left_join(x, y)` | `merge(x, y, all.x = TRUE)`
`right_join(x, y)` | `merge(x, y, all.y = TRUE)`, `right_join(x, y)` | `merge(x, y, all.y = TRUE)`,
`full_join(x, y)` | `merge(x, y, all.x = TRUE), all.y = TRUE)` `full_join(x, y)` | `merge(x, y, all.x = TRUE, all.y = TRUE)`
The advantages of the specific dplyr verbs is that they more clearly convey the intent of your code: the difference between the joins is really important but concealed in the arguments of `merge()`. dplyr's joins are considerably faster and don't mess with the order of the rows. The advantages of the specific dplyr verbs is that they more clearly convey the intent of your code: the difference between the joins is really important but concealed in the arguments of `merge()`. dplyr's joins are considerably faster and don't mess with the order of the rows.