计算R中的累积时间

时间:2017-07-13 19:44:39

标签: r lubridate

我有一个如下所示的数据框:

     POI   LOCAL.DATETIME
1    1     2017-07-11 15:02:13
2    1     2017-07-11 15:20:28
3    2     2017-07-11 15:20:31
4    2     2017-07-11 15:21:13
5    3     2017-07-11 15:21:18
6    3     2017-07-11 15:21:21
7    2     2017-07-11 15:21:25
8    2     2017-07-11 15:21:59
9    1     2017-07-11 15:22:02
10   1     2017-07-11 15:22:05

我希望能够计算(可能是使用lubridate)在每个POI上花费的累积时间,并将它们组合成一个看起来像这样的表:

     POI   TOTAL.TIME
1    1     00:18:18
2    2     00:01:11
3    3     00:00:03

另外,我不知道如何处理POI之间的时间,比如第2行和第3行之间的3秒。我想我可能需要计算从第1行到第3行而不是第1行到第2行的时间

2 个答案:

答案 0 :(得分:2)

要获得每个组周期的总时间,首先需要创建一个组索引。我使用rleid中的data.table您可以计算每个组中花费的总时间,然后使用sum按初始POI进行汇总。

df <- read.table(text="     POI   LOCAL.DATETIME
1     '2017-07-11 15:02:13'
1     '2017-07-11 15:20:28'
2     '2017-07-11 15:20:31'
2     '2017-07-11 15:21:13'
3     '2017-07-11 15:21:18'
3     '2017-07-11 15:21:21'
2     '2017-07-11 15:21:25'
2     '2017-07-11 15:21:59'
1     '2017-07-11 15:22:02'
1     '2017-07-11 15:22:05'",
                 header=TRUE,stringsAsFactors=FALSE)
df$LOCAL.DATETIME <- as.POSIXct(df$LOCAL.DATETIME)

library(dplyr)
df%>%
  mutate(grp=data.table::rleid(POI))%>%
  group_by(grp)%>%
  summarise(POI=max(POI),TOTAL.TIME=difftime(max(LOCAL.DATETIME),
                                     min(LOCAL.DATETIME),units="secs"))%>%
  group_by(POI)%>%
  summarise(TOTAL.TIME=sum(TOTAL.TIME))

# A tibble: 3 × 2
    POI TOTAL.TIME
  <int>     <time>
1     1  1098 secs
2     2    76 secs
3     3     3 secs

要获得分钟和秒数,您可以使用as.period中的lubridate

library(lubridate)
df%>%
  mutate(grp=data.table::rleid(POI))%>%
  group_by(grp)%>%
  summarise(POI=max(POI),TOTAL.TIME=difftime(max(LOCAL.DATETIME),
                                    min(LOCAL.DATETIME),units="secs"))%>%
  group_by(POI)%>%
  summarise(TOTAL.TIME=sum(TOTAL.TIME))%>%
  mutate(TOTAL.TIME =as.period((TOTAL.TIME), unit = "sec"))

    POI   TOTAL.TIME
  <int> <S4: Period>
1     1      18M 18S
2     2       1M 16S
3     3           3S

答案 1 :(得分:0)

另一个data.table选项是为每个POI创建2行的分组,计算它们之间的时差,最后将其总结为POI

library(data.table)

dt <- as.data.table(df)
dt[, grp2 := (seq_len(.N)+1) %/% 2, by = POI]
dt[, time_diff := difftime(LOCAL.DATETIME, shift(LOCAL.DATETIME), unit = "min"), by = .(POI, grp2)]
dt[ , .(TOTAL.TIME = sum(time_diff, na.rm = T)), by = POI]

#   POI     TOTAL.TIME
#1:   1 18.300000 mins
#2:   2  1.266667 mins
#3:   3  0.050000 mins