하루에 cumulative dplyr로 시간별 관찰

Question

하루에 모든 시간별 관찰 (열 : gdd10)을 요약하고 세 가지 요인 (치료, 담당자 및 깊이)별로 그룹화 할 수있었습니다. 나는 시간의 전체 기간 동안 하루에 새로 만든 gdd10 합계를 축적하고 싶은, 그러나

##Summarise by Day 
gdd10<- tempsub%>% 
group_by(Date = as.Date.character(Date), Treatment,Rep,Depth)%>% 
summarise(sum = sum(gdd10)) %>% 
arrange(sum) 

: 나는 다음과 같은 코드를 사용했다. 그래서 나는 치료, Rep, Depth별로 그룹화 된 누적 합계를 얻었습니다.

내가 좋아하는 것 :

##Cumulate sum over entire period 
gdd10csum<- gdd10%>% 
group_by(Treatment,Rep,Depth)%>% 
mutate(cumsum = cumsum(sum)) %>% 
arrange(cumsum) 

ggplot보고, 그것은이 코드는 전체 기간에 걸쳐 요약하지 않는 것을 알 수 : 나는 (cumsum in grouped data with dplyr 기준)에 다음 코드를 시도 치료, 담당자 및 심도별로 그룹화하여 전체 기간 동안 날짜별로 누적 (cumsum) 값을 하나씩 갖는 것. 이 코드의 잘못된 점은 무엇입니까?

> dput(gdd10csum) 
structure(list(Date = structure(c(16941, 16941, 16941, 16941, 
16941, 16941, 16941, 16941, 16941, 16941, 16941, 16942, 16941, 
16941, 16941, 16941, 16942, 16942, 16941, 16942, 16942, 16942, 
16942, 16941, 16941, 16942, 16942, 16941, 16942, 16941, 16941, 
16941, 16941, 16942, 16941, 16942, 16942, 16942, 16941, 16941, 
16941, 16942, 16941, 16941, 16941, 16941, 16941, 16942, 16942, 
16942, 16942, 16942, 16942, 16942, 16942, 16942, 16942, 16942, 
16942, 16942, 16942, 16942, 16942, 16942), class = "Date"), Treatment = structure(c(2L, 
1L, 5L, 3L, 1L, 5L, 2L, 3L, 5L, 5L, 4L, 2L, 4L, 3L, 4L, 4L, 1L, 
5L, 2L, 5L, 3L, 1L, 2L, 2L, 2L, 5L, 3L, 1L, 5L, 5L, 1L, 5L, 1L, 
4L, 3L, 4L, 3L, 4L, 3L, 1L, 4L, 4L, 5L, 3L, 3L, 4L, 4L, 2L, 2L, 
2L, 1L, 5L, 1L, 5L, 1L, 3L, 3L, 4L, 1L, 5L, 3L, 3L, 4L, 4L), .Label = c("Disc", 
"Strip_NT", "Strip_ST", "Vt_high", "Vt_low"), class = "factor"), 
    Rep = structure(c(2L, 1L, 1L, 2L, 2L, 4L, 1L, 3L, 2L, 3L, 
    4L, 2L, 1L, 1L, 2L, 3L, 1L, 1L, 2L, 4L, 2L, 2L, 1L, 1L, 3L, 
    2L, 3L, 1L, 3L, 1L, 4L, 4L, 3L, 4L, 2L, 1L, 1L, 2L, 4L, 2L, 
    1L, 3L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 1L, 1L, 1L, 4L, 4L, 3L, 
    2L, 4L, 1L, 2L, 2L, 3L, 1L, 3L, 2L), .Label = c("1", "2", 
    "3", "4"), class = "factor"), Depth = structure(c(2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 
    1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L), .Label = c("5", "30"), class = "factor"), sum = c(19.264, 
    27.405, 37.078, 40.186, 40.838, 42.793, 44.761, 47.656, 47.842, 
    53.317, 59.739, 40.824, 60.351, 61.321, 62.353, 64.521, 47.445, 
    55.643, 94.985, 59.336, 62.25, 63.425, 64.323, 110.563, 110.912, 
    68.41, 68.735, 116.45, 73.875, 127.29, 129.475, 130.305, 
    133.851, 78.288, 139.362, 79.38, 80.889, 83.889, 147.819, 
    150.538, 150.655, 89.098, 156.007, 159.148, 168.585, 173.395, 
    175.571, 116.011, 128.453, 129.605, 133.488, 140.31, 139.496, 
    143.325, 150.379, 153.905, 157.835, 163.186, 166.053, 174.543, 
    175.186, 176.603, 190.917, 192.106), cumsum = c(19.264, 27.405, 
    37.078, 40.186, 40.838, 42.793, 44.761, 47.656, 47.842, 53.317, 
    59.739, 60.088, 60.351, 61.321, 62.353, 64.521, 74.85, 92.721, 
    94.985, 102.129, 102.436, 104.263, 109.084, 110.563, 110.912, 
    116.252, 116.391, 116.45, 127.192, 127.29, 129.475, 130.305, 
    133.851, 138.027, 139.362, 139.731, 142.21, 146.242, 147.819, 
    150.538, 150.655, 153.619, 156.007, 159.148, 168.585, 173.395, 
    175.571, 210.996, 239.365, 240.168, 249.938, 267.6, 268.971, 
    273.63, 284.23, 293.267, 305.654, 313.841, 316.591, 330.55, 
    334.334, 345.188, 364.312, 367.677)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -64L), vars = list(
    Treatment, Rep, Depth), indices = list(c(27L, 50L), c(1L, 
16L), c(39L, 58L), c(4L, 21L), c(32L, 54L), c(30L, 52L), c(23L, 
49L), c(6L, 22L), c(18L, 47L), c(0L, 11L), c(24L, 48L), c(44L, 
61L), c(13L, 36L), c(34L, 55L), c(3L, 20L), c(43L, 60L), c(7L, 
26L), c(38L, 56L), c(40L, 57L), c(12L, 35L), c(46L, 63L), c(14L, 
37L), c(45L, 62L), c(15L, 41L), c(10L, 33L), c(29L, 51L), c(2L, 
17L), c(42L, 59L), c(8L, 25L), c(9L, 28L), c(31L, 53L), c(5L, 
19L)), drop = TRUE, group_sizes = c(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, 2L, 2L, 2L, 2L, 2L), biggest_group_size = 2L, .Names = c("Date", 
"Treatment", "Rep", "Depth", "sum", "cumsum"), labels = structure(list(
    Treatment = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("Disc", "Strip_NT", 
    "Strip_ST", "Vt_high", "Vt_low"), class = "factor"), Rep = structure(c(1L, 
    1L, 2L, 2L, 3L, 4L, 1L, 1L, 2L, 2L, 3L, 1L, 1L, 2L, 2L, 3L, 
    3L, 4L, 1L, 1L, 2L, 2L, 3L, 3L, 4L, 1L, 1L, 2L, 2L, 3L, 4L, 
    4L), .Label = c("1", "2", "3", "4"), class = "factor"), Depth = structure(c(1L, 
    2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 
    2L), .Label = c("5", "30"), class = "factor")), class = "data.frame", row.names = c(NA, 
-32L), vars = list(Treatment, Rep, Depth), indices = list(c(34L, 
40L), c(1L, 8L), c(48L, 55L), c(5L, 19L), c(41L, 47L), c(37L, 
43L), c(31L, 38L), c(7L, 20L), c(30L, 33L), c(0L, 4L), c(32L, 
36L), c(56L, 61L), c(16L, 27L), c(42L, 50L), c(3L, 17L), c(53L, 
59L), c(9L, 23L), c(46L, 52L), c(49L, 54L), c(15L, 26L), c(60L, 
63L), c(18L, 28L), c(57L, 62L), c(21L, 29L), c(14L, 25L), c(35L, 
44L), c(2L, 12L), c(51L, 58L), c(10L, 22L), c(11L, 24L), c(39L, 
45L), c(6L, 13L)), drop = TRUE, group_sizes = c(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, 2L, 2L, 2L, 2L, 2L), biggest_group_size = 2L, .Names = c("Treatment", 
"Rep", "Depth"))) 

Answer 1

대답은 첫 번째 단계에서 정렬 기능을 제외하는 것입니다 :

##Summarise by Day 
gdd10<- tempsub%>% 
group_by(Date = as.Date.character(Date), Treatment,Rep,Depth)%>% 
summarise(sum = sum(gdd10))