Arrange a grouped_df by group variable not working

I have a data.frame that contains client names, years, and several revenue numbers from each year.

df <- data.frame(client = rep(c("Client A","Client B", "Client C"),3), 
                 year = rep(c(2014,2013,2012), each=3), 
                 rev = rep(c(10,20,30),3)
                )

I want to end up with a data.frame that aggregates the revenue by client and year. I then want to sort the data.frame by year then by descending revenue.

library(dplyr)
df1 <- df %>% 
        group_by(client, year) %>%
        summarise(tot = sum(rev)) %>%
        arrange(year, desc(tot))

However, when using the code above the arrange() function doesn't change the order of the grouped data.frame at all. When I run the below code and coerce to a normal data.frame it works.

   library(dplyr)
    df1 <- df %>% 
            group_by(client, year) %>%
            summarise(tot = sum(rev)) %>%
            data.frame() %>%
            arrange(year, desc(tot))

Am I missing something or will I need to do this every time when trying to arrange a grouped_df by a grouped variable?

R Version: 3.1.1 dplyr package version: 0.3.0.2

EDIT 11/13/2017: As noted by lucacerone, beginning with dplyr 0.5, arrange once again ignores groups when sorting. So my original code now works in the way I initially expected it would.

arrange() once again ignores grouping, reverting back to the behaviour of dplyr 0.3 and earlier. This makes arrange() inconsistent with other dplyr verbs, but I think this behaviour is generally more useful. Regardless, it’s not going to change again, as more changes will just cause more confusion.

Solution

Try switching the order of your group_by statement:

df %>% 
  group_by(year, client) %>%
  summarise(tot = sum(rev)) %>%
  arrange(year, desc(tot))

I think arrange is ordering within groups; after summarize, the last group is dropped, so this means in your first example it's arranging rows within the client group. Switching the order to group_by(year, client) seems to fix it because the client group gets dropped after summarize.

Alternatively, there is the ungroup() function

df %>% 
  group_by(client, year) %>%
  summarise(tot = sum(rev)) %>%
  ungroup() %>%
  arrange(year, desc(tot))

Edit, @lucacerone: since dplyr 0.5 this does not work anymore:

Breaking changes arrange() once again ignores grouping, reverting back to the behaviour of dplyr 0.3 and earlier. This makes arrange() inconsistent with other dplyr verbs, but I think this behaviour is generally more useful. Regardless, it’s not going to change again, as more changes will just cause more confusion.