I am trying to accomplish two things, I am a little bit rusty and unsure how to do this. I am trying to get the top 10 longest running procedure. I am doing that by getting the max. I need the max time by month, in order to do the second item, which is to graph by month the top 10 longest (max) running loads. In my ggplot, I only get the top 10 but only for January. How could I get the top 10 for every month by year? Here is what I tried. I also attached a picture of my problem. For example, REFRESH_FINAID:LOAD_MGT_STDUENT_PERIOD_DEF has a max time of 851, how do I move to the next highest load and get a list of 10. I show that process 10 times
data_max5 <- data %>%
select(Run_Month_Name,RUN_YEAR,Map_Group,Elapsed_time_seconds_num) %>%
group_by(Run_Month_Name, Map_Group) %>%
mutate(max_time = max(Elapsed_time_seconds_num),
average_time = mean(Elapsed_time_seconds_num)) %>%
arrange(desc(max_time), .by_group = T) %>%
filter(row_number(max_time) == 1) %>%
top_n(10, max_time) %>%
slice(1:10) %>%
ungroup()
data_max5 %>%
head(10, Map_Group, Run_Month_Name) %>%
# ungroup() %>%
ggplot(aes(x = fct_rev(fct_reorder(Map_Group,max_time)), y = max_time, fill= Map_Group))+
geom_col(position = "dodge") +
theme(axis.text.x = element_text(angle = 90, hjust = 1),legend.position = "none") +
labs( x = "Map_Group") +
scale_y_continuous(limits = c(0,900), breaks = seq(0 ,900, by = 15))+
coord_flip()+
facet_wrap(~Run_Month_Name, ncol = 3, drop = TRUE) ```
```structure(list(Run_Month_Name = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L), levels = c("January", "February", "March",
"April", "May", "June", "July", "August", "September", "October",
"November", "December"), class = c("ordered", "factor")), RUN_YEAR = c("2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022", "2022", "2022", "2022", "2022", "2022",
"2022", "2022", "2022"), Map_Group = structure(c(1L, 2L, 3L,
4L, 5L, 6L, 7L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L,
30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L,
37L, 38L, 39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 21L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 31L, 32L,
33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L,
31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L,
29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 21L, 22L, 23L, 24L, 25L,
26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
39L, 40L, 41L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L,
38L, 39L, 40L, 41L), levels = c("REFRESH_FINAID: LOAD_MGT_STUDENT_PERIOD_DEF",
"REFRESH_FINAID_CUNM: LOAD_MRT_FINAID_APPLI_CUNM", "REFRESH_FINAID_CUNM: LOAD_MRT_U_DEF_FIELDS_NYR_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_GORADID_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_GORDPRF_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_GTVDIRO_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_GZBISON_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_ADGRPS_ALL_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_ADMIN_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_ANS_OFFICES_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_ANSWERS_COV_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_APPT_SLOTS_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_APPTS_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_EVENT_PROF_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_EVENTS_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_LOCATIONS_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_OFFICES_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_QUESTIONS_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_VISIT_OFFICE_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_LCI_VISITS_COVID_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_LERN_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MGT_WF_INPROCESS_WRK_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MGT_YEAR_TYPE_DEF_CUNM",
"REFRESH_GENERAL_CUNM: LOAD_MST_PZBUNMH_ACL_CUNM", "REFRESH_GENERAL_CUNM: LOAD_MST_SPRIDEN_ACL_CUNM",
"REFRESH_STUDENT: LOAD_ACSTUCHG_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_COURSE_EQUIV_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_INSTR_DEL_MODE_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_SCHED_OFFERING_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_SECFEES_REPEAT_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_SZBEXAM_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_SZBWEBA_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_SZRANNC_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_SZRGFWF_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_SZRHOUS_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_SZRRCRD_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_SZRVOTE_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_SZTLAWX_CUNM", "REFRESH_STUDENT_CUNM: LOAD_MST_WAIT_LISTED_CUNM",
"REFRESH_STUDENT_CUNM: LOAD_MST_WEBID_CUNM", "REFRESH_STUDENT_CUNM: LOAD_VZEN_ORIENTATION_CUNM"
), class = "factor"), Elapsed_time_seconds_num = c(727, 56, 10,
35, 0, 0, 32, 436, 100, 7, 8, 239, 7, 0, 40, 119, 6, 1, 9, 0,
0, 2, 1, 1, 0, 5, 10, 806, 56, 10, 18, 0, 0, 23, 193, 14, 6,
3, 137, 8, 0, 43, 128, 7, 1, 10, 1, 0, 2, 1, 1, 0, 7, 11, 673,
50, 11, 18, 0, 0, 19, 6, 0, 161, 106, 3, 1, 110, 6, 1, 49, 159,
13, 3, 11, 2, 2, 5, 3, 4, 1, 11, 15, 719, 59, 12, 19, 0, 0, 16,
5, 0, 148, 94, 4, 2, 93, 7, 1, 49, 141, 5, 1, 11, 1, 0, 3, 1,
1, 0, 9, 15, 693, 64, 13, 21, 0, 0, 12, 2, 1, 159, 88, 3, 2,
97, 10, 1, 45, 127, 5, 1, 9, 1, 0, 2, 1, 1, 0, 6, 11, 751, 54,
10, 16, 0, 0, 16, 6, 1, 127, 79, 4, 2, 104, 5, 1, 44, 126, 4,
1, 9, 1, 0, 2, 1, 1, 0, 4, 11, 708, 47, 9, 19, 0, 0, 15, 4, 0,
173, 92, 6, 3, 106, 6, 1, 45, 126, 6, 1, 9, 1, 1, 2, 1, 1, 0,
5, 12, 715, 47, 9, 22, 0, 0, 15, 4, 1, 163, 5, 3, 103, 6, 1,
44, 119, 1, 9, 1, 1, 2, 1, 1, 0, 4, 10, 700, 59, 11, 23, 0, 0,
16, 4, 2, 156, 102, 4, 3, 89, 7, 2, 46, 121, 5, 2, 10, 1, 1,
3, 1, 1, 0, 5, 14, 712, 55, 11, 20, 0, 0, 17, 4, 2, 164, 81,
3, 6, 103, 7, 2, 45, 133, 5, 1, 10, 1, 1, 2, 1, 1, 0, 7, 12,
1, 733, 74, 11, 22, 0, 0, 28, 5, 2, 189, 81, 6, 8, 127, 7, 2,
49, 129, 5, 2, 12, 1, 1, 3, 1, 2, 0, 5, 19, 1, 720, 58, 10, 92,
2, 0, 47, 22, 13, 70, 370, 8, 10, 19, 28, 15, 7, 29, 12, 65,
300, 145, 43, 5, 206, 14, 1, 46, 132, 6, 2, 10, 1, 1, 2, 1, 2,
0, 5, 10, 0), max_time = c(851, 88, 15, 50, 2, 2, 49, 436, 146,
11, 11, 267, 12, 1, 43, 136, 10, 2, 12, 1, 1, 3, 2, 2, 0, 8,
15, 851, 113, 22, 41, 2, 2, 34, 394, 106, 11, 8, 256, 10, 1,
44, 140, 11, 2, 12, 1, 1, 3, 1, 2, 0, 8, 16, 882, 102, 18, 58,
1, 2, 52, 6, 1, 371, 119, 18, 9, 291, 13, 1, 51, 159, 13, 3,
13, 2, 2, 8, 3, 4, 1, 11, 22, 757, 70, 18, 88, 1, 2, 53, 9, 3,
329, 138, 85, 106, 322, 12, 2, 50, 148, 7, 2, 12, 1, 1, 3, 1,
1, 0, 9, 16, 779, 96, 43, 28, 0, 1, 135, 51, 17, 242, 100, 19,
21, 124, 10, 1, 49, 143, 7, 2, 11, 1, 1, 5, 1, 1, 0, 6, 14, 793,
75, 20, 33, 2, 2, 69, 28, 26, 290, 126, 48, 26, 175, 11, 1, 47,
129, 6, 2, 10, 1, 1, 3, 1, 1, 0, 6, 14, 802, 67, 15, 123, 0,
0, 26, 12, 7, 213, 105, 68, 14, 137, 14, 2, 48, 135, 9, 2, 10,
1, 1, 3, 1, 2, 0, 6, 13, 750, 71, 29, 141, 1, 1, 80, 12, 107,
403, 47, 50, 293, 16, 2, 48, 135, 2, 11, 1, 1, 3, 2, 2, 0, 7,
15, 790, 88, 13, 64, 15, 15, 74, 20, 4, 284, 110, 12, 40, 228,
13, 2, 50, 139, 7, 2, 13, 1, 1, 3, 2, 2, 0, 6, 20, 754, 85, 16,
32, 11, 10, 46, 35, 6, 257, 116, 11, 53, 163, 12, 3, 49, 142,
9, 3, 15, 2, 2, 5, 1, 3, 0, 11, 23, 1, 789, 85, 19, 54, 10, 16,
86, 63, 42, 295, 143, 34, 65, 212, 14, 7, 54, 157, 8, 3, 13,
2, 1, 4, 2, 3, 0, 6, 21, 1, 740, 77, 30, 92, 23, 23, 119, 95,
15, 76, 462, 8, 10, 19, 28, 15, 14, 30, 14, 70, 427, 150, 43,
114, 380, 14, 3, 49, 157, 7, 3, 12, 2, 2, 4, 2, 3, 0, 8, 16,
1), average_time = c(724.035714285714, 58.1071428571429, 10.1785714285714,
27.3928571428571, 0.178571428571429, 0.178571428571429, 28.9642857142857,
254.285714285714, 67.2857142857143, 4.42857142857143, 3.64285714285714,
172.035714285714, 7.21428571428571, 0.928571428571429, 41.25,
124.821428571429, 6.75, 1.10714285714286, 10.1428571428571, 0.714285714285714,
0.0714285714285714, 2.25, 0.928571428571429, 1.07142857142857,
0, 6.14285714285714, 11.8214285714286, 762.28, 63.76, 11, 26.36,
0.2, 0.28, 22.84, 236.48, 55.56, 5.08, 3.12, 165.84, 7, 0.8,
42.56, 127.32, 7.12, 1.16, 10.4, 0.72, 0.12, 2.36, 0.92, 1.08,
0, 6.44, 12.28, 766.241379310345, 70.6896551724138, 11.9310344827586,
27.3103448275862, 0.137931034482759, 0.241379310344828, 22.4137931034483,
4.33333333333333, 0.5, 216.103448275862, 94.8275862068966, 4.96551724137931,
2.93103448275862, 143.379310344828, 8.17241379310345, 0.931034482758621,
45.1379310344828, 135.379310344828, 7.37931034482759, 1.41379310344828,
10.4137931034483, 0.862068965517241, 0.448275862068966, 3.06896551724138,
0.862068965517241, 1.17241379310345, 0.0344827586206897, 6.68965517241379,
14.551724137931, 720.466666666667, 50.1, 10.0666666666667, 21.6,
0.0666666666666667, 0.0666666666666667, 14.8, 4.26666666666667,
0.933333333333333, 164.6, 96.4666666666667, 10.0666666666667,
9.73333333333333, 110.266666666667, 7.7, 1, 45.0666666666667,
131.966666666667, 5.3, 1.2, 8.9, 0.766666666666667, 0.166666666666667,
2.16666666666667, 0.833333333333333, 1, 0, 5.2, 11.1, 730.689655172414,
54.7931034482759, 11.5172413793103, 19.2068965517241, 0, 0.0344827586206897,
18.5172413793103, 5.89655172413793, 1.41379310344828, 163.551724137931,
88.0689655172414, 4.79310344827586, 5.13793103448276, 99.7241379310345,
7, 0.827586206896552, 44.551724137931, 124.758620689655, 5.20689655172414,
1.13793103448276, 8.58620689655172, 0.724137931034483, 0.172413793103448,
2.13793103448276, 0.655172413793103, 0.96551724137931, 0, 4.79310344827586,
10.551724137931, 729.344827586207, 54.0344827586207, 10.5862068965517,
20.2413793103448, 0.103448275862069, 0.103448275862069, 15.8620689655172,
5.17241379310345, 2.31034482758621, 175.793103448276, 89.9655172413793,
5.75862068965517, 4.86206896551724, 106.655172413793, 6.24137931034483,
0.758620689655172, 43.6206896551724, 121.310344827586, 4.72413793103448,
1.10344827586207, 8.51724137931035, 0.620689655172414, 0.137931034482759,
2.03448275862069, 0.655172413793103, 0.862068965517241, 0, 4.51724137931035,
9.68965517241379, 718.233333333333, 49.5, 10.0333333333333, 22.1333333333333,
0, 0, 14, 3.76666666666667, 1.06666666666667, 152.766666666667,
87.0666666666667, 6.6, 4.03333333333333, 103.866666666667, 6.36666666666667,
1.2, 43.7, 121.6, 5.3, 1.16666666666667, 8.7, 0.9, 0.466666666666667,
2.03333333333333, 0.866666666666667, 1.06666666666667, 0, 5,
10, 718.785714285714, 54.4285714285714, 10.75, 26.6071428571429,
0.0714285714285714, 0.0357142857142857, 18.4285714285714, 5.07142857142857,
5.17857142857143, 184.535714285714, 7.35714285714286, 7.89285714285714,
115.857142857143, 7.35714285714286, 1.25, 44.7857142857143, 126.25,
1.32142857142857, 9.25, 0.964285714285714, 0.964285714285714,
2.14285714285714, 1, 1.03571428571429, 0, 5.17857142857143, 11.4285714285714,
728.9, 58.1333333333333, 10.4666666666667, 26.7, 0.5, 0.533333333333333,
20.0333333333333, 6, 1.66666666666667, 191.8, 88.0666666666667,
5.46666666666667, 6.16666666666667, 123.766666666667, 7.26666666666667,
1.4, 46.0666666666667, 129.633333333333, 5.4, 1.3, 9.4, 1, 1,
2.4, 1.03333333333333, 1.2, 0, 4.93333333333333, 12.1666666666667,
694.96875, 58.375, 10.90625, 23.1612903225806, 0.354838709677419,
0.32258064516129, 19.1935483870968, 6.90322580645161, 1.83870967741935,
187.548387096774, 86.5161290322581, 6.51612903225806, 6.64516129032258,
118.387096774194, 7.03225806451613, 1.87096774193548, 46.3870967741936,
128.258064516129, 5.80645161290323, 1.54838709677419, 10.1935483870968,
1.09677419354839, 1.06451612903226, 2.58064516129032, 1, 1.38709677419355,
0, 5.67741935483871, 13.5806451612903, 0.714285714285714, 718.148148148148,
64.3333333333333, 10.4814814814815, 30.4814814814815, 1.25925925925926,
1.14814814814815, 28.9259259259259, 12.1481481481481, 5.40740740740741,
220.851851851852, 106.925925925926, 9.40740740740741, 8.66666666666667,
143.62962962963, 8.74074074074074, 1.92592592592593, 46.4814814814815,
134.592592592593, 5.77777777777778, 1.96296296296296, 10.1851851851852,
1.07407407407407, 1, 2.88888888888889, 1.11111111111111, 1.74074074074074,
0, 5.55555555555556, 13.3333333333333, 0.222222222222222, 717.85,
64.65, 11.15, 35, 1.5, 1.35, 27.45, 12.65, 3.6, 51.55, 284.4,
2.25, 2.4, 4.05, 4.55, 2.35, 2.9, 5.15, 5.7, 49.35, 255.35, 118.45,
10.75, 16.05, 168, 8.95, 1.75, 46.55, 132.3, 5.75, 2.05, 10.15,
1.1, 1.05, 3, 1.1, 1.9, 0, 5.6, 12.45, 0.35)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -356L))```