2

I'm working with a combined time-date variable (format: 2019-05-25 09:02:52; see code below) for times on which ESM measurements were taken. These measurements fell into fixed intervals and I now want to set all times in the interval to the average of the interval. In the case of the provided example, I want to set all entries between 07:30:00 and 10:30:00 to 09:00:00 (regardless of the date).

         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)

I have tried accomplishing this by using the following code, which has worked for me using regular variables. However, now it doesn't seem to have the desired effect.

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"

This resulted in the following error: 

Error in as.POSIXlt.character(x, tz, ...) : 
  character string is not in a standard unambiguous format"

The only solution I can think of now is first splitting the variable into separate date and time variables, changing the time, and then merging them back. However, that doesn't seem optimal.

It would be great if someone had an alternative way to code this.

> 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)
4

2 回答 2

0

您dput表明您的Scheduled.Time专栏是"factor"格式的，这有点奇怪。我们将其转换为"POSIXct".

daglijst$Scheduled.Time <- as.POSIXct(daglijst$Scheduled.Time)

然后我们可以使用gsubwith正则表达式来提取时间数字（不带":"）并将它们转换为"numeric". 现在我们可能会找到pos位于所需区间内的itions，我们将gsub在具有此位置的子集上应用另一个以替换为"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" ...
于 2019-07-05T08:38:23.403 回答
0

data.table包有一个名为 的函数，as.ITime()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
于 2019-07-02T16:28:11.440 回答