Update fct_lump() usage

Fixes hadley#855

factors.Rmd

@@ -336,22 +336,21 @@ gss_cat %>%
 ```
 
 Sometimes you just want to lump together all the small groups to make a plot or table simpler.
-That's the job of `fct_lump()`:
+That's the job of the `fct_lump_*()` family of functions.
+`fct_lump_lowfreq()` is a simple starting point that progressively lumps the smallest groups categories into "Other", always keeping "Other" as the smallest category.
 
 ```{r}
 gss_cat %>%
-  mutate(relig = fct_lump(relig)) %>%
+  mutate(relig = fct_lump_lowfreq(relig)) %>%
   count(relig)
 ```
 
-The default behaviour is to progressively lump together the smallest groups, ensuring that the aggregate is still the smallest group.
-In this case it's not very helpful: it is true that the majority of Americans in this survey are Protestant, but we've probably over collapsed.
-
-Instead, we can use the `n` parameter to specify how many groups (excluding other) we want to keep:
+In this case it's not very helpful: it is true that the majority of Americans in this survey are Protestant, but we'd probably like to see some more details!
+Instead, we can use the `fct_lump_n()` to specify that we want exactly 10 groups:
 
 ```{r}
 gss_cat %>%
-  mutate(relig = fct_lump(relig, n = 10)) %>%
+  mutate(relig = fct_lump_n(relig, n = 10)) %>%
   count(relig, sort = TRUE) %>%
   print(n = Inf)
 ```
@@ -360,7 +359,8 @@ gss_cat %>%
 
 1.  How have the proportions of people identifying as Democrat, Republican, and Independent changed over time?
 
-1.  How could you collapse `rincome` into a small set of categories?
-
-1.  Notice there are 9 groups (excluding other) in the `fct_lump` example above. Why not 10? (Hint: type `?fct_lump`, and find the default for the argument `other_level` is "Other".)
+2.  How could you collapse `rincome` into a small set of categories?
 
+3.  Notice there are 9 groups (excluding other) in the `fct_lump` example above.
+    Why not 10?
+    (Hint: type `?fct_lump`, and find the default for the argument `other_level` is "Other".)