2

Dataframecopy1

    copy1
Source: local data frame [4 x 4]
Groups: GM [2]

      GM Avg.Start.Time Avg.Close.Time Avg.Last.Task.Duration
  (fctr)         (fctr)         (fctr)                  (int)
1   ED          13:15          16:16                    181
2   ED          16:12          17:44                     92
3   LD          15:32          17:27                    115
4   LD          14:38          17:11                    153

我想计算Avg.Close.TimeGM

我努力了:

copy1$Avg.Start.Time <-strptime(copy1$Avg.Start.Time, "%H:%M")
copy1%>%group_by(GM)%>%
        summarise(mean(copy1$Avg.Start.Time,na.rm=T))

但是得到这个:

Error: column 'Avg.Start.Time' has unsupported type : POSIXlt, POSIXt

我也尝试过使用lubridate

copy1$Avg.Start.Time <- hm(copy1$Avg.Start.Time)

mean(copy1$Avg.Start.Time,na.rm = T)

但是得到“0”

任何想法如何计算Avg.Start.TimePer GM

4

3 回答 3

2

您需要先将列转换为时间格式,

copy1$Avg.Start.Time <- as.POSIXct(copy1$Avg.Start.Time, format = "%H:%M")

然后,您可以使用aggregatefrom base R 来获取mean每个GM

aggregate(Avg.Start.Time~GM, copy1, mean)

#  GM      Avg.Start.Time
#1 ED 2016-08-24 14:43:30
#2 LD 2016-08-24 15:05:00

如果你想要它的HH:MM格式,你可以把它包起来format

aggregate(Avg.Start.Time~GM, copy1, function(x) format(mean(x),format = "%H:%M"))

#  GM Avg.Start.Time
#1 ED          14:43
#2 LD          15:05
于 2016-08-24T12:32:10.757 回答
2

我们可以用data.table

library(data.table)
setDT(copy1)[,.(Avg.Start.Time = mean(as.POSIXct(Avg.Start.Time, format = "%M:%S")))  , GM]
于 2016-08-24T13:20:14.023 回答
2

您可以使用as.POSIXct来进行转换,其结果可用于mean

result <- copy1%>%group_by(GM)%>%
  summarise(mean(as.POSIXct(Avg.Start.Time, format="%M:%S"),na.rm=T))

但是,这会将当前日期添加到时间:

print(result)
## A tibble: 2 x 2
##      GM mean(as.POSIXct(copy1$Avg.Start.Time,...
##  <fctr>                                   <time>
##1     ED                      2016-08-24 00:14:54
##2     LD                      2016-08-24 00:15:05

正如OP所指出的,我们可以format删除日期的结果:

result <- copy1%>%group_by(GM)%>%
  summarise(Avg.Start.Time=format(mean(as.POSIXct(Avg.Start.Time, format="%M:%S"),na.rm=T), format="%M:%S"))
## A tibble: 2 x 2
##      GM Avg.Start.Time
##  <fctr>          <chr>
##1     ED          14:43
##2     LD          15:05
于 2016-08-24T12:30:13.233 回答