here is the question, use the library(nycflights13) from R-studio to answer it. show your code and make it reproducible so I can copy it.

here is my answer to question 6, you may need it, the data is from nycflights13 package

7) Now, using your table from #6, produce the frequency plot shown which conveys frequency counts for the months of April, July, and October for the year 2013 2500 - mmmphelliyi 2000- 1500- 1000 500- 0- Apr Oct Jul dep_time '{r} make_datetime_100 % filter(!is.na(dep_time), !is.na(arr_time)) %>% mutate dep_time make_datetime_100(year, month, day, dep_time), arr_time make_datetime_100(year, month, day, arr_time), sched_dep_time make_datetime_100(year, month, day, sched_dep_time), sched_arr_time make_datetime_100(year, month, day, sched_arr_time) ) %>% select(origin, dest, carrier, arr_time) -> = flights_dt flights_dt X A tibble: 328,063 x 4 origin dest carrier arr_time EWR IAH UA 2013-01-01 08:30:00 LGA IAH UA 2013-01-01 08:50:00 MIA AA 2013-01-01 09:23:00 JFK JFK LGA BON B6 2013-01-01 10:04:00 ATL DL 2013-01-01 08:12:00 EWR ORD UA 2013-01-01 07:40:00 EWR FLL B6 2013-01-01 09:13:00 LGA IAD EV 2013-01-01 07:09:00 JFK MCO B6 2013-01-01 08:38:00 LGA ORD 2013-01-01 07:53:00 1-10 of 328,063 rows Previous 1 2 3 4 4 5 6 100 Next