I'm new to R and I'm looking to add apply a function that randomly samples rows until a sum is reached but that repeats this within groups.
I found this question that helped me [1]: Random sampling until sum is reached but I can't figure out where within the code to include code that allows me to sum within a group.
So far my code looks like this:
`set.seed(42)
library(dplyr)
sample_in_range <- function(src_tbl, min_sum = 32, max_sum = 34, max_iter = 100) {
for(i in 1:max_iter) {
output <- src_tbl %>%
sample_n(nrow(src_tbl)) %>%
mutate(ID = as.character(SAMPLE_ID),
cuml = cumsum(Samasa_A.nasus)) %>%
filter(cuml <= max_sum)
if(max(output$cuml) >= min_sum) return(output)
}
}
output_sam <- sample_in_range(AA_sam_list)
output_sam`
Samasa_A.nasus is the column that I want to cumulative sum until the sum reaches 33, and repeat this for each category (factor) of YQTR
My data looks like this:
SUMMER", "2016 _ SUMMER",
"2016 _ SUMMER", "2016 _ SUMMER", "2016 _ SUMMER", "2016 _ SUMMER",
"2016 _ SUMMER", "2016 _ SUMMER", "2016 _ SUMMER", "2016 _ SUMMER",
"2016 _ SUMMER", "2016 _ SUMMER", "2016 _ FALL", "2016 _ FALL",
"2016 _ FALL", "2016 _ FALL", "2016 _ FALL", "2016 _ FALL", "2016 _ FALL",
"2016 _ FALL", "2016 _ FALL", "2016 _ FALL", "2016 _ FALL", "2016 _ WINTER",
"2016 _ WINTER", "2016 _ WINTER", "2016 _ WINTER", "2016 _ WINTER",
"2016 _ WINTER", "2016 _ WINTER", "2016 _ WINTER", "2016 _ WINTER",
"2016 _ WINTER", "2016 _ SPRING", "2017 _ SUMMER", "2017 _ SUMMER",
"2017 _ SUMMER", "2017 _ SUMMER", "2017 _ SUMMER", "2017 _ SUMMER",
"2017 _ WINTER", "2017 _ WINTER", "2017 _ WINTER", "2017 _ WINTER",
"2017 _ WINTER", "2017 _ WINTER", "2017 _ WINTER", "2017 _ WINTER",
"2017 _ WINTER", "2017 _ WINTER", "2017 _ SPRING", "2017 _ SPRING",
"2017 _ SPRING", "2018 _ SUMMER", "2018 _ SUMMER", "2018 _ SUMMER",
"2018 _ SUMMER", "2018 _ SUMMER", "2018 _ SUMMER", "2018 _ SUMMER",
"2018 _ SUMMER", "2018 _ FALL", "2018 _ WINTER", "2018 _ WINTER",
"2018 _ SPRING", "2018 _ SPRING", "2018 _ SPRING", "2018 _ SPRING",
"2018 _ SPRING", "2018 _ SPRING", "2018 _ SPRING", "2018 _ SPRING"
), QTR = c("I", "I", "I", "I", "I", "I", "I", "I", "I", "I",
"I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I",
"I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I",
"I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I", "I",
"I", "I", "I", "I", "I", "I", "II", "II", "II", "II", "II", "II",
"II", "II", "II", "II", "II", "I", "I", "I", "I", "I", "I", "II",
"II", "II", "II", "II", "II", "II", "II", "II", "II", "II", "II",
"II", "I", "I", "I", "I", "I", "I", "I", "I", "I", "II", "II",
"II", "II", "II", "II", "II", "II", "II", "II"), COLLECTION_ID = c("AA-2015-02-DIETA",
"AA-2015-02-DIETA", "AA-2015-02-DIETA", "AA-2015-02-DIETA", "AA-2015-03-DIETA",
"AA-2015-03-DIETA", "AA-2015-03-DIETA", "AA-2015-05-DIETA", "AA-2015-05-DIETA",
"AA-2015-06-DIETA", "AA-2015-06-DIETA", "AA-2015-06-DIETA", "AA-2016-01-DIETA",
"AA-2016-01-DIETA", "AA-2016-01-DIETA", "AA-2016-01-DIETA", "AA-2016-01-DIETA",
"AA-2016-01-DIETA", "AA-2016-01-DIETA", "AA-2016-01-DIETA", "AA-2016-01-DIETA",
"AA-2016-01-DIETA", "AA-2016-01-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA",
"AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA",
"AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA",
"AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA", "AA-2016-02-DIETA",
"AA-2016-03-DIETA", "AA-2016-03-DIETA", "AA-2016-03-DIETA", "AA-2016-03-DIETA",
"AA-2016-03-DIETA", "AA-2016-03-DIETA", "AA-2016-03-DIETA", "AA-2016-04-DIETA",
"AA-2016-04-DIETA", "AA-2016-04-DIETA", "AA-2016-04-DIETA", "AA-2016-04-DIETA",
"AA-2016-05-DIETA", "AA-2016-05-DIETA", "AA-2016-05-DIETA", "AA-2016-05-DIETA",
"AA-2016-05-DIETA", "AA-2016-06-DIETA", "AA-2016-08-DIETA", "AA-2016-08-DIETA",
"AA-2016-08-DIETA", "AA-2016-09-DIETA", "AA-2016-09-DIETA", "AA-2016-09-DIETA",
"AA-2016-09-DIETA", "AA-2016-09-DIETA", "AA-2016-09-DIETA", "AA-2016-09-DIETA",
"AA-2016-11-DIETA", "AA-2017-01-DIETA", "AA-2017-01-DIETA", "AA-2017-02-DIETA",
"AA-2017-02-DIETA", "AA-2017-02-DIETA", "AA-2017-03-DIETA", "AA-2017-07-DIETA",
"AA-2017-07-DIETA", "AA-2017-08-DIETA", "AA-2017-09-DIETA", "AA-2017-09-DIETA",
"AA-2017-09-DIETA", "AA-2017-09-DIETA", "AA-2017-09-DIETA", "AA-2017-09-DIETA",
"AA-2017-09-DIETA", "AA-2017-12-DIETA", "AA-2017-12-DIETA", "AA-2017-12-DIETA",
"AA-2018-01-DIETA", "AA-2018-02-DIETA", "AA-2018-02-DIETA", "AA-2018-03-DIETA",
"AA-2018-03-DIETA", "AA-2018-03-DIETA", "AA-2018-03-DIETA", "AA-2018-03-DIETA",
"AA-2018-06-DIETA", "AA-2018-07-DIETA", "AA-2018-07-DIETA", "AA-2018-09-DIETA",
"AA-2018-09-DIETA", "AA-2018-09-DIETA", "AA-2018-09-DIETA", "AA-2018-11-DIETA",
"AA-2018-12-DIETA", "AA-2018-12-DIETA", "AA-2018-12-DIETA"),
SAMPLE = c(8L, 11L, 15L, 21L, 3L, 8L, 27L, 9L, 22L, 17L,
21L, 30L, 3L, 5L, 9L, 18L, 19L, 20L, 25L, 26L, 30L, 33L,
37L, 1L, 2L, 3L, 4L, 6L, 10L, 16L, 24L, 33L, 35L, 37L, 45L,
46L, 47L, 2L, 3L, 6L, 8L, 21L, 32L, 34L, 12L, 20L, 25L, 33L,
36L, 8L, 31L, 35L, 39L, 40L, 9L, 4L, 5L, 33L, 5L, 14L, 23L,
24L, 28L, 34L, 35L, 9L, 13L, 30L, 10L, 19L, 29L, 26L, 16L,
22L, 4L, 4L, 10L, 16L, 24L, 25L, 26L, 35L, 2L, 5L, 12L, 34L,
14L, 30L, 1L, 16L, 29L, 36L, 40L, 27L, 5L, 22L, 1L, 12L,
17L, 34L, 38L, 12L, 29L, 38L), SAMPLE_ID = c("AA-02-2015-008",
"AA-02-2015-011", "AA-02-2015-015", "AA-02-2015-021", "AA-03-2015-003",
"AA-03-2015-008", "AA-03-2015-027", "AA-05-2015-009", "AA-05-2015-022",
"AA-06-2015-017", "AA-06-2015-021", "AA-06-2015-030", "AA-01-2016-003",
"AA-01-2016-005", "AA-01-2016-009", "AA-01-2016-018", "AA-01-2016-019",
"AA-01-2016-020", "AA-01-2016-025", "AA-01-2016-026", "AA-01-2016-030",
"AA-01-2016-033", "AA-01-2016-037", "AA-02-2016-001", "AA-02-2016-002",
"AA-02-2016-003", "AA-02-2016-004", "AA-02-2016-006", "AA-02-2016-010",
"AA-02-2016-016", "AA-02-2016-024", "AA-02-2016-033", "AA-02-2016-035",
"AA-02-2016-037", "AA-02-2016-045", "AA-02-2016-046", "AA-02-2016-047",
"AA-03-2016-002", "AA-03-2016-003", "AA-03-2016-006", "AA-03-2016-008",
"AA-03-2016-021", "AA-03-2016-032", "AA-03-2016-034", "AA-04-2016-012",
"AA-04-2016-020", "AA-04-2016-025", "AA-04-2016-033", "AA-04-2016-036",
"AA-05-2016-008", "AA-05-2016-031", "AA-05-2016-035", "AA-05-2016-039",
"AA-05-2016-040", "AA-06-2016-009", "AA-08-2016-004", "AA-08-2016-005",
"AA-08-2016-033", "AA-09-2016-005", "AA-09-2016-014", "AA-09-2016-023",
"AA-09-2016-024", "AA-09-2016-028", "AA-09-2016-034", "AA-09-2016-035",
"AA-11-2016-009", "AA-01-2017-013", "AA-01-2017-030", "AA-02-2017-010",
"AA-02-2017-019", "AA-02-2017-029", "AA-03-2017-026", "AA-07-2017-016",
"AA-07-2017-022", "AA-08-2017-004", "AA-09-2017-004", "AA-09-2017-010",
"AA-09-2017-016", "AA-09-2017-024", "AA-09-2017-025", "AA-09-2017-026",
"AA-09-2017-035", "AA-12-2017-002", "AA-12-2017-005", "AA-12-2017-012",
"AA-2018-01-034", "AA-2018-02-014", "AA-2018-02-030", "AA-2018-03-001",
"AA-2018-03-016", "AA-2018-03-029", "AA-2018-03-036", "AA-2018-03-040",
"AA-2018-06-027", "AA-2018-08-005", "AA-2018-08-022", "AA-2018-10-001",
"AA-2018-10-012", "AA-2018-10-017", "AA-2018-10-034", "AA-2018-11-038",
"AA-2018-12-012", "AA-2018-12-029", "AA-2018-12-038"), DATA_ID = c("AA - 2015 - SUMMER - 8",
"AA - 2015 - SUMMER - 11", "AA - 2015 - SUMMER - 15", "AA - 2015 - SUMMER - 21",
"AA - 2015 - SUMMER - 33", "AA - 2015 - SUMMER - 38", "AA - 2015 - SUMMER - 57",
"AA - 2015 - FALL - 43", "AA - 2015 - FALL - 56", "AA - 2015 - FALL - 84",
"AA - 2015 - FALL - 88", "AA - 2015 - FALL - 97", "AA - 2016 - SUMMER - 3",
"AA - 2016 - SUMMER - 5", "AA - 2016 - SUMMER - 9", "AA - 2016 - SUMMER - 18",
"AA - 2016 - SUMMER - 19", "AA - 2016 - SUMMER - 20", "AA - 2016 - SUMMER - 25",
"AA - 2016 - SUMMER - 26", "AA - 2016 - SUMMER - 30", "AA - 2016 - SUMMER - 33",
"AA - 2016 - SUMMER - 37", "AA - 2016 - SUMMER - 43", "AA - 2016 - SUMMER - 44",
"AA - 2016 - SUMMER - 45", "AA - 2016 - SUMMER - 46", "AA - 2016 - SUMMER - 48",
"AA - 2016 - SUMMER - 52", "AA - 2016 - SUMMER - 58", "AA - 2016 - SUMMER - 66",
"AA - 2016 - SUMMER - 75", "AA - 2016 - SUMMER - 77", "AA - 2016 - SUMMER - 79",
"AA - 2016 - SUMMER - 87", "AA - 2016 - SUMMER - 88", "AA - 2016 - SUMMER - 89",
"AA - 2016 - SUMMER - 91", "AA - 2016 - SUMMER - 92", "AA - 2016 - SUMMER - 95",
"AA - 2016 - SUMMER - 97", "AA - 2016 - SUMMER - 110", "AA - 2016 - SUMMER - 121",
"AA - 2016 - SUMMER - 123", "AA - 2016 - FALL - 12", "AA - 2016 - FALL - 20",
"AA - 2016 - FALL - 25", "AA - 2016 - FALL - 33", "AA - 2016 - FALL - 36",
"AA - 2016 - FALL - 48", "AA - 2016 - FALL - 71", "AA - 2016 - FALL - 75",
"AA - 2016 - FALL - 79", "AA - 2016 - FALL - 80", "AA - 2016 - FALL - 90",
"AA - 2016 - WINTER - 24", "AA - 2016 - WINTER - 25", "AA - 2016 - WINTER - 53",
"AA - 2016 - WINTER - 66", "AA - 2016 - WINTER - 75", "AA - 2016 - WINTER - 84",
"AA - 2016 - WINTER - 85", "AA - 2016 - WINTER - 89", "AA - 2016 - WINTER - 95",
"AA - 2016 - WINTER - 96", "AA - 2016 - SPRING - 9", "AA - 2017 - SUMMER - 13",
"AA - 2017 - SUMMER - 30", "AA - 2017 - SUMMER - 50", "AA - 2017 - SUMMER - 59",
"AA - 2017 - SUMMER - 69", "AA - 2017 - SUMMER - 106", "AA - 2017 - WINTER - 16",
"AA - 2017 - WINTER - 22", "AA - 2017 - WINTER - 44", "AA - 2017 - WINTER - 74",
"AA - 2017 - WINTER - 80", "AA - 2017 - WINTER - 86", "AA - 2017 - WINTER - 94",
"AA - 2017 - WINTER - 95", "AA - 2017 - WINTER - 96", "AA - 2017 - WINTER - 105",
"AA - 2017 - SPRING - 12", "AA - 2017 - SPRING - 15", "AA - 2017 - SPRING - 22",
"AA - 2018 - SUMMER - 34", "AA - 2018 - SUMMER - 60", "AA - 2018 - SUMMER - 76",
"AA - 2018 - SUMMER - 87", "AA - 2018 - SUMMER - 102", "AA - 2018 - SUMMER - 115",
"AA - 2018 - SUMMER - 122", "AA - 2018 - SUMMER - 126", "AA - 2018 - FALL - 107",
"AA - 2018 - WINTER - 45", "AA - 2018 - WINTER - 62", "AA - 2018 - SPRING - 1",
"AA - 2018 - SPRING - 12", "AA - 2018 - SPRING - 17", "AA - 2018 - SPRING - 34",
"AA - 2018 - SPRING - 78", "AA - 2018 - SPRING - 92", "AA - 2018 - SPRING - 109",
"AA - 2018 - SPRING - 118"), NOSPP_ID = c("2015 - SUMMER - 8",
"2015 - SUMMER - 11", "2015 - SUMMER - 15", "2015 - SUMMER - 21",
"2015 - SUMMER - 33", "2015 - SUMMER - 38", "2015 - SUMMER - 57",
"2015 - FALL - 43", "2015 - FALL - 56", "2015 - FALL - 84",
"2015 - FALL - 88", "2015 - FALL - 97", "2016 - SUMMER - 3",
"2016 - SUMMER - 5", "2016 - SUMMER - 9", "2016 - SUMMER - 18",
"2016 - SUMMER - 19", "2016 - SUMMER - 20", "2016 - SUMMER - 25",
"2016 - SUMMER - 26", "2016 - SUMMER - 30", "2016 - SUMMER - 33",
"2016 - SUMMER - 37", "2016 - SUMMER - 43", "2016 - SUMMER - 44",
"2016 - SUMMER - 45", "2016 - SUMMER - 46", "2016 - SUMMER - 48",
"2016 - SUMMER - 52", "2016 - SUMMER - 58", "2016 - SUMMER - 66",
"2016 - SUMMER - 75", "2016 - SUMMER - 77", "2016 - SUMMER - 79",
"2016 - SUMMER - 87", "2016 - SUMMER - 88", "2016 - SUMMER - 89",
"2016 - SUMMER - 91", "2016 - SUMMER - 92", "2016 - SUMMER - 95",
"2016 - SUMMER - 97", "2016 - SUMMER - 110", "2016 - SUMMER - 121",
"2016 - SUMMER - 123", "2016 - FALL - 12", "2016 - FALL - 20",
"2016 - FALL - 25", "2016 - FALL - 33", "2016 - FALL - 36",
"2016 - FALL - 48", "2016 - FALL - 71", "2016 - FALL - 75",
"2016 - FALL - 79", "2016 - FALL - 80", "2016 - FALL - 90",
"2016 - WINTER - 24", "2016 - WINTER - 25", "2016 - WINTER - 53",
"2016 - WINTER - 66", "2016 - WINTER - 75", "2016 - WINTER - 84",
"2016 - WINTER - 85", "2016 - WINTER - 89", "2016 - WINTER - 95",
"2016 - WINTER - 96", "2016 - SPRING - 9", "2017 - SUMMER - 13",
"2017 - SUMMER - 30", "2017 - SUMMER - 50", "2017 - SUMMER - 59",
"2017 - SUMMER - 69", "2017 - SUMMER - 106", "2017 - WINTER - 16",
"2017 - WINTER - 22", "2017 - WINTER - 44", "2017 - WINTER - 74",
"2017 - WINTER - 80", "2017 - WINTER - 86", "2017 - WINTER - 94",
"2017 - WINTER - 95", "2017 - WINTER - 96", "2017 - WINTER - 105",
"2017 - SPRING - 12", "2017 - SPRING - 15", "2017 - SPRING - 22",
"2018 - SUMMER - 34", "2018 - SUMMER - 60", "2018 - SUMMER - 76",
"2018 - SUMMER - 87", "2018 - SUMMER - 102", "2018 - SUMMER - 115",
"2018 - SUMMER - 122", "2018 - SUMMER - 126", "2018 - FALL - 107",
"2018 - WINTER - 45", "2018 - WINTER - 62", "2018 - SPRING - 1",
"2018 - SPRING - 12", "2018 - SPRING - 17", "2018 - SPRING - 34",
"2018 - SPRING - 78", "2018 - SPRING - 92", "2018 - SPRING - 109",
"2018 - SPRING - 118"), TOTAL_OTO = c(23L, 9L, 1L, 2L, 35L,
31L, 38L, 5L, 20L, 19L, 63L, 1L, 14L, 21L, 2L, 5L, 18L, 31L,
48L, 5L, 12L, 28L, 8L, 6L, 5L, 4L, 25L, 12L, 4L, 39L, 14L,
7L, 5L, 7L, 7L, 1L, 24L, 4L, 27L, 24L, 3L, 2L, 33L, 2L, 7L,
59L, 5L, 22L, 23L, 5L, 11L, 5L, 9L, 9L, 6L, 2L, 39L, 32L,
5L, 136L, 6L, 79L, 39L, 5L, 16L, 1L, 13L, 4L, 22L, 14L, 4L,
3L, 2L, 2L, 2L, 80L, 39L, 2L, 9L, 213L, 6L, 4L, 2L, 3L, 18L,
1L, 83L, 2L, 7L, 5L, 78L, 22L, 40L, 4L, 7L, 5L, 1L, 18L,
22L, 37L, 1L, 13L, 3L, 15L), TOTAL_BEAKS = c(16L, 52L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 4L, 2L, 5L, 2L, 1L, 13L,
8L, 0L, 6L, 3L, 0L, 0L, 1L, 4L, 2L, 25L, 1L, 0L, 2L, 5L,
0L, 4L, 1L, 0L, 9L, 0L, 1L, 5L, 0L, 2L, 1L, 39L, 3L, 0L,
27L, 0L, 0L, 0L, 0L, 0L, 2L, 4L, 0L, 0L, 8L, 21L, 1L, 2L,
8L, 0L, 1L, 11L, 1L, 0L, 23L, 16L, 0L, 0L, 1L, 22L, 0L, 1L,
6L, 3L, 3L, 0L, 2L, 0L, 26L, 1L, 6L, 1L, 0L, 1L, 0L, 5L,
183L, 0L, 32L, 2L, 26L, 0L, 0L, 0L, 0L, 0L, 124L, 6L, 5L,
0L, 0L, 5L), TOTAL_MUNIDA = c(0L, 13L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 8L, 0L, 0L, 0L, 0L,
32L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 24L,
6L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), Anchoveta_E.ringens = c(14L,
8L, 0L, 1L, 2L, 6L, 0L, 0L, 0L, 16L, 2L, 0L, 12L, 1L, 1L,
4L, 17L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
36L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 2L, 0L, 1L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 4L, 0L, 3L, 6L, 4L, 0L, 0L, 9L, 6L,
0L, 21L, 0L, 14L, 8L, 0L, 0L, 0L, 0L, 0L, 4L, 0L, 0L, 0L,
0L, 0L, 0L, 2L, 1L, 0L, 1L, 174L, 5L, 0L, 0L, 0L, 16L, 0L,
33L, 0L, 2L, 0L, 0L, 19L, 9L, 1L, 5L, 3L, 0L, 9L, 0L, 30L,
0L, 0L, 2L, 8L), Camote_N.crockeri = c(0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 25L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), Pejerrey_O.regia = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L,
0L, 0L, 0L, 11L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L),
Samasa_A.nasus = c(9L, 1L, 1L, 1L, 3L, 8L, 4L, 1L, 7L, 3L,
55L, 1L, 2L, 19L, 1L, 1L, 1L, 29L, 23L, 3L, 3L, 2L, 8L, 4L,
2L, 3L, 25L, 8L, 3L, 2L, 13L, 3L, 1L, 3L, 5L, 1L, 24L, 2L,
1L, 23L, 3L, 2L, 26L, 2L, 1L, 1L, 4L, 15L, 23L, 1L, 1L, 1L,
3L, 1L, 1L, 2L, 1L, 1L, 3L, 4L, 2L, 2L, 1L, 5L, 15L, 1L,
8L, 4L, 1L, 14L, 2L, 1L, 2L, 1L, 2L, 1L, 22L, 2L, 6L, 3L,
1L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 5L, 5L, 26L, 3L, 24L, 3L,
1L, 1L, 1L, 1L, 22L, 2L, 1L, 10L, 1L, 4L), Merluza_M.gayi = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 1L, 0L, 26L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 26L, 0L, 0L, 0L, 3L, 0L,
0L, 1L, 1L, 6L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), YQTR = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 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, 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, 5L, 5L, 5L,
5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L), .Label = c("2015 _ I", "2015 _ II",
"2016 _ I", "2016 _ II", "2017 _ I", "2017 _ II", "2018 _ I",
"2018 _ II"), class = "factor"), segID = c(8L, 11L, 15L,
21L, 33L, 38L, 57L, 105L, 118L, 146L, 150L, 159L, 3L, 5L,
9L, 18L, 19L, 20L, 25L, 26L, 30L, 33L, 37L, 43L, 44L, 45L,
46L, 48L, 52L, 58L, 66L, 75L, 77L, 79L, 87L, 88L, 89L, 91L,
92L, 95L, 97L, 110L, 121L, 123L, 141L, 149L, 154L, 162L,
165L, 177L, 200L, 204L, 208L, 209L, 219L, 24L, 25L, 53L,
66L, 75L, 84L, 85L, 89L, 95L, 96L, 110L, 13L, 30L, 50L, 59L,
69L, 106L, 16L, 22L, 44L, 74L, 80L, 86L, 94L, 95L, 96L, 105L,
122L, 125L, 132L, 34L, 60L, 76L, 87L, 102L, 115L, 122L, 126L,
233L, 45L, 62L, 126L, 137L, 142L, 159L, 203L, 217L, 234L,
243L)), row.names = c(NA, -104L), class = "data.frame")
Thank You!
