From 387d65c4f1af255050fa6409e03cdc7ada96bfa5 Mon Sep 17 00:00:00 2001
From: "Jennifer (Jenny) Bryan" <jenny@stat.ubc.ca>
Date: Thu, 7 Jan 2016 10:00:03 -0800
Subject: [PATCH] extra `)`

---
 relational-data.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/relational-data.Rmd b/relational-data.Rmd
index ea10328..283bea2 100644
--- a/relational-data.Rmd
+++ b/relational-data.Rmd
@@ -236,7 +236,7 @@ dplyr              | merge
 `inner_join(x, y)` | `merge(x, y)`
 `left_join(x, y)`  | `merge(x, y, all.x = 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.