# A tibble: 10,200 x 19
year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time
<int> <int> <int> <int> <int> <dbl> <int> <int>
1 2013 1 1 811 630 101 1047 830
2 2013 1 1 848 1835 853 1001 1950
3 2013 1 1 957 733 144 1056 853
4 2013 1 1 1114 900 134 1447 1222
5 2013 1 1 1505 1310 115 1638 1431
6 2013 1 1 1525 1340 105 1831 1626
7 2013 1 1 1549 1445 64 1912 1656
8 2013 1 1 1558 1359 119 1718 1515
9 2013 1 1 1732 1630 62 2028 1825
10 2013 1 1 1803 1620 103 2008 1750
# ... with 10,190 more rows, and 11 more variables: arr_delay <dbl>,
# carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
# air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm># A tibble: 91,394 x 19
year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time
<int> <int> <int> <int> <int> <dbl> <int> <int>
1 2013 1 1 517 515 2 830 819
2 2013 1 1 533 529 4 850 830
3 2013 1 1 542 540 2 923 850
4 2013 1 1 554 558 -4 740 728
5 2013 1 1 558 600 -2 753 745
6 2013 1 1 558 600 -2 924 917
7 2013 1 1 558 600 -2 923 937
8 2013 1 1 559 600 -1 941 910
9 2013 1 1 559 600 -1 854 902
10 2013 1 1 606 610 -4 858 910
# ... with 91,384 more rows, and 11 more variables: arr_delay <dbl>,
# carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
# air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm># A tibble: 9,313 x 19
year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time
<int> <int> <int> <int> <int> <dbl> <int> <int>
1 2013 1 1 517 515 2 830 819
2 2013 1 1 533 529 4 850 830
3 2013 1 1 623 627 -4 933 932
4 2013 1 1 728 732 -4 1041 1038
5 2013 1 1 739 739 0 1104 1038
6 2013 1 1 908 908 0 1228 1219
7 2013 1 1 1028 1026 2 1350 1339
8 2013 1 1 1044 1045 -1 1352 1351
9 2013 1 1 1114 900 134 1447 1222
10 2013 1 1 1205 1200 5 1503 1505
# ... with 9,303 more rows, and 11 more variables: arr_delay <dbl>,
# carrier <chr>, flight <int>, tailnum <chr>, origin <chr>, dest <chr>,
# air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm>