Suggestions from Marie

transform.Rmd

@@ -419,19 +419,22 @@ There are many functions for creating new variables that you can use with `mutat
     start with `min_rank()`. It does the most usual type of ranking 
     (e.g. 1st, 2nd, 2nd, 4th). The default gives smallest values the small
     ranks; use `desc(x)` to give the largest values the smallest ranks. 
-    If `min_rank()` doesn't do what you need, look at the variants 
-    `row_number()`, `dense_rank()`, `percent_rank()`, `cume_dist()`,  
-    `ntile()`.
     
     ```{r}
     y <- c(1, 2, 2, NA, 3, 4)
-    tibble(
-      row_number(y),
-      min_rank(y),
-      dense_rank(y),
-      percent_rank(y),
-      cume_dist(y)
-    )
+    min_rank(y)
+    min_rank(desc(y))
+    ```
+    
+    If `min_rank()` doesn't do what you need, look at the variants
+    `row_number()`, `dense_rank()`, `percent_rank()`, `cume_dist()`,
+    `ntile()`.  See their help pages for more details.
+    
+    ```{r}
+    row_number(y)
+    dense_rank(y)
+    percent_rank(y)
+    cume_dist(y)
     ```
 
 ### Exercises