如何更改组合时间日期变量（POSIXlt）中的时间？
How to change time in combined time-date variable (POSIXlt)?
我正在使用组合的时间-日期变量（格式：2019-05-25 09:02:52；参见下面的代码）来获取 ESM 测量的时间。这些测量属于固定间隔，我现在想将间隔中的所有时间设置为间隔的平均值。对于提供的示例，我想将 07:30:00 和 10:30:00 之间的所有条目设置为 09:00:00（无论日期如何）。
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)
我尝试使用以下代码来完成此操作，该代码使用常规变量对我很有效。不过，现在看来并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"
这导致了以下错误：
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format"
我现在唯一能想到的解决办法就是先把变量拆分成单独的日期和时间变量，改变时间，然后再合并回来。但是，这似乎不是最佳选择。
如果有人有其他方法来编写此代码，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)
data.table包有一个函数叫做as.ITime()，可以用来处理时间，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
你的dput显示你的Scheduled.Time栏是"factor"格式，有点奇怪。我们把它转换成"POSIXct".
daglijst$Scheduled.Time <- as.POSIXct(daglijst$Scheduled.Time)
然后我们可以使用 gsub 和 regular expressions 来提取时间数字（没有 ":"）并将它们转换为 "numeric"。现在我们可以找到位于所需间隔内的 pos 位置，然后我们将另一个 gsub 应用到具有此位置的子集上以替换为 "09:00:00".
t <- as.numeric(gsub(".*\s(\d+)\:(\d+)\:(\d+).*", "\1\2\3",
daglijst$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" ...
我正在使用组合的时间-日期变量（格式：2019-05-25 09:02:52；参见下面的代码）来获取 ESM 测量的时间。这些测量属于固定间隔，我现在想将间隔中的所有时间设置为间隔的平均值。对于提供的示例，我想将 07:30:00 和 10:30:00 之间的所有条目设置为 09:00:00（无论日期如何）。
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)
我尝试使用以下代码来完成此操作，该代码使用常规变量对我很有效。不过，现在看来并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"
这导致了以下错误：
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format"
我现在唯一能想到的解决办法就是先把变量拆分成单独的日期和时间变量，改变时间，然后再合并回来。但是，这似乎不是最佳选择。
如果有人有其他方法来编写此代码，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)
data.table包有一个函数叫做as.ITime()，可以用来处理时间，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
你的dput显示你的Scheduled.Time栏是"factor"格式，有点奇怪。我们把它转换成"POSIXct".
daglijst$Scheduled.Time <- as.POSIXct(daglijst$Scheduled.Time)
然后我们可以使用 gsub 和 regular expressions 来提取时间数字（没有 ":"）并将它们转换为 "numeric"。现在我们可以找到位于所需间隔内的 pos 位置，然后我们将另一个 gsub 应用到具有此位置的子集上以替换为 "09:00:00".
t <- as.numeric(gsub(".*\s(\d+)\:(\d+)\:(\d+).*", "\1\2\3",
daglijst$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" ...