3/4.5.7 Exercise 2

[maxwellely]

The question asked in the book is "Find the flights that are most delayed upon departure from each destination.

The answer offered in the solutions book is -

> flights |> 
+   group_by(dest) |> 
+   arrange(dest, desc(dep_delay)) |> 
+   slice_head(n = 5) |> 
+   relocate(dest,dep_delay)

However, this code doesn't output the flights that are most delayed upon departure from each destination, but instead the flights that are overall the most delayed.

# A tibble: 517 × 19
# Groups:   dest [105]
   dest  dep_delay  year month   day dep_time sched_dep_time arr_time sched_arr_time arr_delay carrier flight tailnum
   <chr>     <dbl> <int> <int> <int>    <int>          <int>    <int>          <int>     <dbl> <chr>    <int> <chr>  
 1 ABQ         142  2013    12    14     2223           2001      133           2304       149 B6          65 N659JB 
 2 ABQ         139  2013    12    17     2220           2001      120           2304       136 B6          65 N556JB 
 3 ABQ         125  2013     7    30     2212           2007       57           2259       118 B6        1505 N621JB 
 4 ABQ         125  2013     9     2     2212           2007       48           2259       109 B6        1505 N569JB 
 5 ABQ         119  2013     7    23     2206           2007      116           2259       137 B6        1505 N589JB 
 6 ACK         219  2013     7    23     1139            800     1250            909       221 B6        1491 N192JB 
 7 ACK         138  2013     7     2     1018            800     1119            909       130 B6        1491 N231JB 
 8 ACK         117  2013     7     4      957            800     1106            909       117 B6        1491 N306JB 
 9 ACK         101  2013     5    30     1321           1140     1419           1247        92 B6        1191 N203JB 
10 ACK         100  2013     6    24      940            800     1111            909       122 B6        1491 N348JB 
# ℹ 507 more rows
# ℹ 6 more variables: origin <chr>, air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm>
# ℹ Use `print(n = ...)` to see more rows

I could be wrong, but I believe this is the code needed to show the flights that are most delayed upon departure from each destination.

> flights |> 
+   group_by(dest) |> 
+   slice_max(dep_delay) |> 
+   arrange(desc(dep_delay)) |> 
+   relocate(dest,dep_delay)

This code outputs one row for each destination. I used arrange, but I don't even know if it is strictly necessary with what the question is asking.

# A tibble: 105 × 19
# Groups:   dest [105]
   dest  dep_delay  year month   day dep_time sched_dep_time arr_time sched_arr_time arr_delay carrier flight tailnum
   <chr>     <dbl> <int> <int> <int>    <int>          <int>    <int>          <int>     <dbl> <chr>    <int> <chr>  
 1 HNL        1301  2013     1     9      641            900     1242           1530      1272 HA          51 N384HA 
 2 CMH        1137  2013     6    15     1432           1935     1607           2120      1127 MQ        3535 N504MQ 
 3 ORD        1126  2013     1    10     1121           1635     1239           1810      1109 MQ        3695 N517MQ 
 4 SFO        1014  2013     9    20     1139           1845     1457           2210      1007 AA         177 N338AA 
 5 CVG        1005  2013     7    22      845           1600     1044           1815       989 MQ        3075 N665MQ 
 6 TPA         960  2013     4    10     1100           1900     1342           2211       931 DL        2391 N959DL 
 7 MSP         911  2013     3    17     2321            810      135           1020       915 DL        2119 N927DA 
 8 PDX         899  2013     6    27      959           1900     1236           2226       850 DL        2007 N3762Y 
 9 ATL         898  2013     7    22     2257            759      121           1026       895 DL        2047 N6716C 
10 MIA         896  2013    12     5      756           1700     1058           2020       878 AA         172 N5DMAA 
# ℹ 95 more rows
# ℹ 6 more variables: origin <chr>, air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm>
# ℹ Use `print(n = ...)` to see more rows

If I misunderstood the question or the answer, please let me know. I am using this book to learn, so it is possible I don't know something the author of this solution does.

Thanks!

[clarelgibson]

I agree with @maxwellely 's solution.