我正在使用组合的时间日期变量（格式：2019-05-25 09:02:52；请参见下面的代码）来获取进行ESM测量的时间。这些测量值落入固定的时间间隔，我现在想将时间间隔中的所有时间都设置为时间间隔的平均值。对于提供的示例，我想将所有条目设置为07:30:00到10:30:00到09:00:00（不考虑日期）。
Name Scheduled.Time
1 User #10165 2019-05-25 09:02:52
2 User #10165 2019-05-25 12:01:32
3 User #10165 2019-05-25 15:43:06
4 User #10165 2019-05-26 09:00:26
5 User #10165 2019-05-26 12:18:24
6 User #10165 2019-05-26 16:09:09
> head_daglijst_shrt <- head(daglijst_shrt)
我已尝试通过使用以下代码来完成此任务，以下代码已使用常规变量为我工作。但是，现在似乎没有达到预期的效果。
daglijst$Scheduled.Time["%H:%M:%S"][daglijst$Scheduled.Time["%H:%M:%S"] > "07:30:00" &
daglijst$Scheduled.Time["%H:%M:%S"] > "10:30:00"] <-
"09:00:00"
这导致以下错误：
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format"
我现在唯一想到的解决方案是，首先将变量拆分为单独的日期和时间变量，更改时间，然后将其合并回去。但是，这似乎并不理想。
如果有人有其他方法编写代码，那就太好了。
> head_daglijst_shrt <- dput(head(daglijst_shrt))
structure(list(Name = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("User #10165",
"User #12545", "User #12803", "User #12829", "User #12843", "User #12844",
"User #12845", "User #12847", "User #12848", "User #12849", "User #12853",
"User #12858", "User #12859", "User #12861", "User #12866", "User #12868",
"User #12906", "User #12907"), class = "factor"), Scheduled.Time = structure(c(2L,
5L, 9L, 16L, 17L, 23L), .Label = c("2019-05-25 09:00:00 CEST",
"2019-05-25 09:02:52 CEST", "2019-05-25 09:03:51 CEST", "2019-05-25 09:10:34 CEST",
"2019-05-25 12:01:32 CEST", "2019-05-25 12:02:22 CEST", "2019-05-25 12:16:20 CEST",
"2019-05-25 12:30:00 CEST", "2019-05-25 15:43:06 CEST", "2019-05-25 16:00:00 CEST",
"2019-05-25 16:02:11 CEST", "2019-05-25 16:06:58 CEST", "2019-05-26 08:46:20 CEST",
"2019-05-26 08:47:24 CEST", "2019-05-26 09:00:00 CEST", "2019-05-26 09:00:26 CEST",
"2019-05-26 12:18:24 CEST", "2019-05-26 12:30:00 CEST", "2019-05-26 12:55:19 CEST",
"2019-05-26 12:58:41 CEST", "2019-05-26 15:49:41 CEST", "2019-05-26 16:00:00 CEST",
"2019-05-26 16:09:09 CEST", "2019-05-26 16:12:39 CEST", "2019-05-27 08:41:32 CEST",
"2019-05-27 09:00:00 CEST", "2019-05-27 09:20:49 CEST", "2019-05-27 09:25:17 CEST",
"2019-05-27 12:30:00 CEST", "2019-05-27 12:31:04 CEST", "2019-05-27 12:42:50 CEST",
"2019-05-27 12:58:20 CEST", "2019-05-27 15:55:24 CEST", "2019-05-27 16:00:00 CEST",
"2019-05-27 16:06:00 CEST", "2019-05-27 16:07:35 CEST", "2019-05-28 08:40:38 CEST",
"2019-05-28 08:43:06 CEST", "2019-05-28 09:00:00 CEST", "2019-05-28 09:12:35 CEST",
"2019-05-28 09:16:23 CEST", "2019-05-28 09:21:37 CEST", "2019-05-28 12:11:31 CEST",
"2019-05-28 12:22:47 CEST", "2019-05-28 12:30:00 CEST", "2019-05-28 12:37:53 CEST",
"2019-05-28 12:40:40 CEST", "2019-05-28 15:26:24 CEST", "2019-05-28 15:36:55 CEST",
"2019-05-28 15:48:55 CEST", "2019-05-28 16:00:00 CEST", "2019-05-28 16:13:46 CEST",
"2019-05-29 08:56:52 CEST", "2019-05-29 09:00:00 CEST", "2019-05-29 09:05:01 CEST",
"2019-05-29 09:08:50 CEST", "2019-05-29 09:23:08 CEST", "2019-05-29 12:11:13 CEST",
"2019-05-29 12:17:01 CEST", "2019-05-29 12:30:00 CEST", "2019-05-29 12:38:50 CEST",
"2019-05-29 12:40:33 CEST", "2019-05-29 15:48:42 CEST", "2019-05-29 16:00:00 CEST",
"2019-05-29 16:02:54 CEST", "2019-05-29 16:11:21 CEST", "2019-05-29 16:31:08 CEST",
"2019-05-30 08:45:53 CEST", "2019-05-30 09:00:00 CEST", "2019-05-30 09:01:31 CEST",
"2019-05-30 09:15:48 CEST", "2019-05-30 09:40:29 CEST", "2019-05-30 12:03:07 CEST",
"2019-05-30 12:10:13 CEST", "2019-05-30 12:30:00 CEST", "2019-05-30 12:38:47 CEST",
"2019-05-30 12:49:51 CEST", "2019-05-30 15:42:34 CEST", "2019-05-30 15:58:38 CEST",
"2019-05-30 16:00:00 CEST", "2019-05-30 16:13:45 CEST", "2019-05-30 16:32:18 CEST",
"2019-05-31 08:47:19 CEST", "2019-05-31 09:00:00 CEST", "2019-05-31 09:04:27 CEST",
"2019-05-31 09:31:41 CEST", "2019-05-31 12:08:42 CEST", "2019-05-31 12:12:36 CEST",
"2019-05-31 12:25:35 CEST", "2019-05-31 12:30:00 CEST", "2019-05-31 15:48:06 CEST",
"2019-05-31 16:00:00 CEST", "2019-05-31 16:24:20 CEST", "2019-05-31 16:33:39 CEST",
"2019-06-01 08:45:36 CEST", "2019-06-01 08:50:40 CEST", "2019-06-01 08:51:13 CEST",
"2019-06-01 09:00:00 CEST", "2019-06-01 12:11:39 CEST", "2019-06-01 12:30:00 CEST",
"2019-06-01 13:02:12 CEST", "2019-06-01 13:03:23 CEST", "2019-06-01 15:55:42 CEST",
"2019-06-01 16:00:00 CEST", "2019-06-01 16:05:15 CEST", "2019-06-01 16:05:54 CEST",
"2019-06-02 08:39:10 CEST", "2019-06-02 09:00:00 CEST", "2019-06-02 12:16:45 CEST",
"2019-06-02 12:30:00 CEST", "2019-06-02 15:58:12 CEST", "2019-06-02 16:00:00 CEST",
"2019-06-03 09:00:00 CEST", "2019-06-03 09:04:42 CEST", "2019-06-03 09:04:48 CEST",
"2019-06-03 09:07:09 CEST", "2019-06-03 12:30:00 CEST", "2019-06-03 12:36:39 CEST",
"2019-06-03 12:48:58 CEST", "2019-06-03 13:06:20 CEST", "2019-06-03 16:00:00 CEST",
"2019-06-03 16:03:32 CEST", "2019-06-03 17:03:39 CEST", "2019-06-04 09:00:00 CEST",
"2019-06-04 09:24:15 CEST", "2019-06-04 09:55:02 CEST", "2019-06-04 12:30:00 CEST",
"2019-06-04 13:22:21 CEST", "2019-06-04 13:44:38 CEST", "2019-06-04 15:52:51 CEST",
"2019-06-04 15:57:11 CEST", "2019-06-04 16:00:00 CEST", "2019-06-04 16:50:23 CEST",
"2019-06-05 09:00:00 CEST", "2019-06-05 09:11:28 CEST", "2019-06-05 09:14:44 CEST",
"2019-06-05 09:52:18 CEST", "2019-06-05 12:23:50 CEST", "2019-06-05 12:30:00 CEST",
"2019-06-05 13:01:50 CEST", "2019-06-05 13:36:56 CEST", "2019-06-05 15:48:12 CEST",
"2019-06-05 16:00:00 CEST", "2019-06-05 16:09:19 CEST", "2019-06-05 16:44:42 CEST",
"2019-06-06 08:21:00 CEST", "2019-06-06 08:44:06 CEST", "2019-06-06 11:51:50 CEST",
"2019-06-06 12:26:14 CEST", "2019-06-06 15:57:43 CEST", "2019-06-06 16:02:51 CEST"
), class = "factor")), .Names = c("Name", "Scheduled.Time"), row.names = c(NA,
6L), class = "data.frame")
> View(head_daglijst_shrt)
答案 0 :(得分：0)
data.table 包具有一个称为as.ITime()的函数，该函数可用于处理时间，例如：
mydatetime <- as.POSIXct("2019-09-01 10:30:00")
as.ITime(mydatetime) > as.ITime("07:30:00")
## [1] TRUE
as.ITime(mydatetime) > as.ITime("11:30:00")
## [1] FALSE
答案 1 :(得分：0)
您的dput显示您的Scheduled.Time列为"factor"格式，这有点奇怪。我们将其转换为"POSIXct"。
daglijst$Scheduled.Time <- as.POSIXct(daglijst$Scheduled.Time)
然后，我们可以将gsub与regular expressions一起使用以提取时间数字（不包含":"）并将其转换为"numeric"。现在，我们可能会找到位于所需间隔内的pos个位置，然后将另一个gsub应用于具有此位置的子集，以替换为"09:00:00"。
t <- as.numeric(gsub(".*\\s(\\d+)\\:(\\d+)\\:(\\d+).*", "\\1\\2\\3",
daglijst$Scheduled.Time))
# [1] 90252 120132 154306 90026 121824 160909
pos <- which(73000 <= t & t <= 103000)
# [1] 1 4
daglijst$Scheduled.Time[pos] <- gsub("(\\d+)\\:(\\d+)\\:(\\d+)", "09:00:00",
daglijst$Scheduled.Time[pos])
# Name Scheduled.Time
# 1 User #10165 2019-05-25 09:00:00
# 2 User #10165 2019-05-25 12:01:32
# 3 User #10165 2019-05-25 15:43:06
# 4 User #10165 2019-05-26 09:00:00
# 5 User #10165 2019-05-26 12:18:24
# 6 User #10165 2019-05-26 16:09:09
Scheduled.Time是"POSIXct"格式：
str(daglijst)
# 'data.frame': 6 obs. of 2 variables:
# $ Name : Factor w/ 18 levels "User #10165",..: 1 1 1 1 1 1
# $ Scheduled.Time: POSIXct, format: "2019-05-25 09:00:00" "2019-05-25 12:01:32" "2019-05-25 15:43:06" ...