代码之家 › 专栏 › 技术社区 › MSS

为什么在使用聚合时第二年之后会出现错误的日期?

period subset r

1

MSS · 技术社区 · 9 年前

df$date<-as.Date(df$date)
z <-aggregate(df$variable, 
               list(Dts = cut(as.Date(df$date, format="%d/%m/%Y"), 
                              breaks="8 day")), FUN=sum)

我有不同的年份,我的数据如下:

structure(list(date = structure(c(5583, 5584, 5585, 5586, 5587, 
5588, 5589, 5590, 5591, 5592, 5593, 5594, 5595, 5596, 5597, 5598, 
5599, 5600, 5601, 5602, 5603, 5604, 5605, 5606, 5607, 5608, 5609, 
5610, 5611, 5612, 5613, 5614, 5615, 5616, 5617, 5618, 5619, 5620, 
5621, 5622, 5623, 5624, 5625, 5626, 5627, 5628, 5629, 5630, 5631, 
5632, 5633, 5634, 5635, 5636, 5637, 5638, 5639, 5640, 5641, 5642, 
5643, 5644, 5645, 5646, 5948, 5949, 5950, 5951, 5952, 5953, 5954, 
5955, 5956, 5957, 5958, 5959, 5960, 5961, 5962, 5963, 5964, 5965, 
5966, 5967, 5968, 5969, 5970, 5971, 5972, 5973, 5974, 5975, 5976, 
5977, 5978, 5979, 5980, 5981, 5982, 5983, 5984, 5985, 5986, 5987, 
5988, 5989, 5990, 5991, 5992, 5993, 5994, 5995, 5996, 5997, 5998, 
5999, 6000, 6001, 6002, 6003, 6004, 6005, 6006, 6007, 6008, 6009, 
6010, 6011, 6313, 6314, 6315, 6316, 6317, 6318, 6319, 6320, 6321, 
6322, 6323, 6324, 6325, 6326, 6327, 6328, 6329, 6330, 6331, 6332, 
6333, 6334, 6335, 6336, 6337, 6338, 6339, 6340, 6341, 6342, 6343, 
6344, 6345, 6346, 6347, 6348, 6349, 6350, 6351, 6352, 6353, 6354, 
6355, 6356, 6357, 6358, 6359, 6360, 6361, 6362, 6363, 6364, 6365, 
6366, 6367, 6368, 6369, 6370, 6371, 6372, 6373, 6374, 6375, 6376
), class = "Date"), variable = c(2, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0)), .Names = c("date", "variable"), row.names = c(105L, 
106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 
117L, 118L, 119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 
128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L, 
139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 147L, 148L, 149L, 
150L, 151L, 152L, 153L, 154L, 155L, 156L, 157L, 158L, 159L, 160L, 
161L, 162L, 163L, 164L, 165L, 166L, 167L, 168L, 470L, 471L, 472L, 
473L, 474L, 475L, 476L, 477L, 478L, 479L, 480L, 481L, 482L, 483L, 
484L, 485L, 486L, 487L, 488L, 489L, 490L, 491L, 492L, 493L, 494L, 
495L, 496L, 497L, 498L, 499L, 500L, 501L, 502L, 503L, 504L, 505L, 
506L, 507L, 508L, 509L, 510L, 511L, 512L, 513L, 514L, 515L, 516L, 
517L, 518L, 519L, 520L, 521L, 522L, 523L, 524L, 525L, 526L, 527L, 
528L, 529L, 530L, 531L, 532L, 533L, 835L, 836L, 837L, 838L, 839L, 
840L, 841L, 842L, 843L, 844L, 845L, 846L, 847L, 848L, 849L, 850L, 
851L, 852L, 853L, 854L, 855L, 856L, 857L, 858L, 859L, 860L, 861L, 
862L, 863L, 864L, 865L, 866L, 867L, 868L, 869L, 870L, 871L, 872L, 
873L, 874L, 875L, 876L, 877L, 878L, 879L, 880L, 881L, 882L, 883L, 
884L, 885L, 886L, 887L, 888L, 889L, 890L, 891L, 892L, 893L, 894L, 
895L, 896L, 897L, 898L), class = "data.frame")

这是我得到的输出,第9行应该再次从1986-04-15开始:

          Dts  x
1  1985-04-15  2
2  1985-04-23  0
3  1985-05-01  0
4  1985-05-09  0
5  1985-05-17  0
6  1985-05-25  0
7  1985-06-02  0
8  1985-06-10  0
9  1986-04-10  0
10 1986-04-18  0
11 1986-04-26  0
12 1986-05-04 NA
13 1986-05-12 NA
14 1986-05-20 NA
15 1986-05-28 NA
16 1986-06-05 NA
17 1986-06-13 NA
18 1987-04-13  0
19 1987-04-21  0
20 1987-04-29  0
21 1987-05-07  0
22 1987-05-15  0
23 1987-05-23  0
24 1987-05-31  0
25 1987-06-08  0
26 1987-06-16  0

数据在那里,但我不知道出了什么问题。非常感谢你的帮助。

1 回复 | 直到 9 年前

1

eipi10 9 年前

如果你从1985年4月15日开始以8天为增量,那么1986年4月10日将是其中一个8天周期的开始。这里有一种方法可以使用一年中与1985年使用的其他年份相同的休息日:

cut 函数,将1985-04-15表示的一年中的某一天除以8得到余数。然后使用此选项选择以下范围内的所有日期: df$date 切 作用

library(lubridate)
library(dplyr)

index = yday(df$date[1]) %% 8 
dates = seq(min(df$date), max(df$date), "1 day")
breaks = dates[yday(dates) %% 8 == index]

# Ensure that leap years have same breaks as other years
breaks = if_else(year(breaks) %in% seq(1980,2020,4) & yday(breaks) > yday(as.Date("1980-02-28")), 
                 breaks + 1, breaks)

aggregate(df$variable, list(Dts = cut(df$date, breaks=breaks)), FUN=sum)

          Dts  x
1  1985-04-15  2
2  1985-04-23  0
3  1985-05-01  0
4  1985-05-09  0
5  1985-05-17  0
6  1985-05-25  0
7  1985-06-02  0
8  1985-06-10  0
9  1986-04-15  0
10 1986-04-23  0
11 1986-05-01  0
12 1986-05-09 NA
13 1986-05-17 NA
14 1986-05-25 NA
15 1986-06-02 NA
16 1986-06-10 NA
17 1987-04-15  0
18 1987-04-23  0
19 1987-05-01  0
20 1987-05-09  0
21 1987-05-17  0
22 1987-05-25  0
23 1987-06-02  0