I've looked for similar threads but can't find a solution.
I've grouped the below dataset by carrier and created new variables to see average and sum delay times successfully. Now I simply want to arrange the data by avg delay, but when I put the below code in it's returning the same data for every row. Can anyone help me figure out where I went wrong?
Using dplyr package, dataset is "flights", have filtered out the na values using:
filter(!is.na(dep_delay), !is.na(arr_delay)). 
I got the data and excercise from section 5.6.7 of this resource http://r4ds.had.co.nz/transform.html#exercises-11
bycarrier %>%  
  transmute(  
    arrsum = sum(arr_delay),  
    arravg = mean(arr_delay),  
    depsum = sum(dep_delay),  
    depavg = mean(dep_delay)   
  ) %>%  
  arrange(desc(arravg))
Returns:
Adding missing grouping variables: `carrier`
Source: local data frame [327,346 x 5]
Groups: carrier [16]
   carrier arrsum  arravg depsum   depavg  
     <chr>  <dbl>   <dbl>  <dbl>    <dbl>  
1       F9  14928 21.9207  13757 20.20117  
2       F9  14928 21.9207  13757 20.20117  
3       F9  14928 21.9207  13757 20.20117  
4       F9  14928 21.9207  13757 20.20117  
5       F9  14928 21.9207  13757 20.20117  
6       F9  14928 21.9207  13757 20.20117  
7       F9  14928 21.9207  13757 20.20117  
8       F9  14928 21.9207  13757 20.20117  
9       F9  14928 21.9207  13757 20.20117  
10      F9  14928 21.9207  13757 20.20117  
# ... with 327,336 more rows  
 
     
    