Question

我在timefact

中有一列时间

> head(foo)
  cnrd_marsh            timefact timefact_hour
1         БЧ 2016-04-07 14:34:00            14
2         БЧ 2016-04-07 14:15:00            14
3         БЧ 2016-04-07 14:10:00            14
4         БЧ 2016-04-07 13:58:00            13
5         БЧ 2016-04-07 13:57:00            13
6         БЧ 2016-04-07 13:39:00            13

我的目标是创建第四列，其中包含整数值，这些值表示给定行与其上方行之间的分钟数差异（difftime）。此外，我需要排除timefact_hour与上面的行不同的所有情况，或者cnrd_marsh与上面的行不同。换句话说，我只需要找到与上一行共享相同hour和相同cnrd_marsh的行的差异。

以下代码似乎首先工作，NA值在正确的位置，但是，更进一步，NA值应该变成看似随机的负数。

library(data.table)
setDT(foo)[, timefact_diff := shift(minute(timefact) - 
                                  shift(minute(timefact), type = "lead")), 
            by = timefact_hour]

   > head(foo)
  cnrd_marsh            timefact timefact_hour timefact_diff
1         БЧ 2016-04-07 14:34:00            14            NA
2         БЧ 2016-04-07 14:15:00            14            19
3         БЧ 2016-04-07 14:10:00            14             5
4         БЧ 2016-04-07 13:58:00            13            NA
5         БЧ 2016-04-07 13:57:00            13             1
6         БЧ 2016-04-07 13:39:00            13            18
> tail(foo)
    cnrd_marsh            timefact timefact_hour timefact_diff
95          БЧ 2016-04-07 15:23:00            15             3
96          БЧ 2016-04-07 14:58:00            14           -24
97          БЧ 2016-04-07 14:53:00            14             5
98          БЧ 2016-04-07 14:44:00            14             9
99          БЧ 2016-04-07 14:43:00            14             1
100         БЧ 2016-04-07 14:27:00            14            16

为什么会发生这种情况？如何在timefact_hour和cnrd_marsh中应用给定行的值应与上述值匹配的规则？

以下是示例数据：

> dput(foo)
structure(list(cnrd_marsh = structure(c(91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 91L, 
91L, 91L, 91L, 91L), .Label = c("", "1", "10", "11", "11К", 
"12", "13", "14", "15", "16", "17", "18", "19", "1К", "2", "20", 
"21", "22", "23", "24", "26", "27", "28", "29", "3", "30", "31", 
"32", "33", "33К", "34", "34К", "35", "36", "37", "38", "39", 
"4", "40", "41", "42", "43", "43К", "44", "45", "47", "48", 
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", 
"6", "60", "61", "62", "63", "63К", "64", "65", "66", "67", 
"7", "70", "70К", "71", "72", "73", "74", "76", "77", "78", 
"79", "8", "80", "81", "82", "83", "84", "85", "86", "88", "9", 
"БК", "БЧ"), class = "factor"), timefact = structure(c(1460057640, 
1460056500, 1460056200, 1460055480, 1460055420, 1460054340, 1460052480, 
1460052360, 1460051340, 1460051040, 1460050440, 1460050380, 1460049360, 
1460048160, 1460048040, 1460046960, 1460046720, 1460046300, 1460045340, 
1460045160, 1460043540, 1460042880, 1460042520, 1460041920, 1460041140, 
1460040120, 1460039760, 1460038860, 1460038620, 1460038080, 1460038020, 
1460037240, 1460036280, 1460035800, 1460034960, 1460034780, 1460034120, 
1460034060, 1460033340, 1460032500, 1460032140, 1460031300, 1460031000, 
1460030340, 1460030340, 1460029800, 1460029200, 1460028300, 1460025720, 
1460090700, 1460088660, 1460088600, 1460087760, 1460087580, 1460086980, 
1460086980, 1460086320, 1460085300, 1460085180, 1460084340, 1460084160, 
1460083620, 1460083620, 1460082780, 1460081820, 1460081760, 1460080740, 
1460080500, 1460080200, 1460079360, 1460079180, 1460077260, 1460076840, 
1460076600, 1460076360, 1460075820, 1460074740, 1460070660, 1460070480, 
1460069100, 1460068800, 1460068140, 1460068140, 1460067060, 1460063880, 
1460063460, 1460062380, 1460062080, 1460061360, 1460061300, 1460059920, 
1460057880, 1460057640, 1460060760, 1460060580, 1460059080, 1460058780, 
1460058240, 1460058180, 1460057220), class = c("POSIXct", "POSIXt"
), tzone = "EST"), timefact_hour = c(14L, 14L, 14L, 13L, 13L, 
13L, 13L, 13L, 12L, 12L, 12L, 12L, 12L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 10L, 10L, 10L, 10L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 
5L, 23L, 23L, 23L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 21L, 21L, 
21L, 21L, 21L, 21L, 21L, 20L, 20L, 20L, 20L, 20L, 20L, 19L, 19L, 
19L, 19L, 19L, 18L, 18L, 17L, 17L, 17L, 17L, 17L, 16L, 16L, 15L, 
15L, 15L, 15L, 15L, 14L, 14L, 15L, 15L, 14L, 14L, 14L, 14L, 14L
)), .Names = c("cnrd_marsh", "timefact", "timefact_hour"), row.names = c(NA, 
-100L), class = "data.frame")

Answer 1

您可能会滞后timefact_hour和cnrd_marsh，然后测试您的情况：

foo[, previous_hour := shift(timefact_hour, type = "lag")]
foo[, previous_cnrd := shift(cnrd_marsh, type = "lag")]
foo = foo[!(previous_hour != timefact_hour | previous_cnrd != cnrd_marsh)]

在有条件的连续行上迭代difftime

1 个答案: