将 dcast.data.table 与日期值和聚合一起使用

Question

正在尝试解决这个问题。假设你有一个 data.table:

dt <- data.table (person=c('bob', 'bob', 'bob'), 
                  door=c('front door', 'front door', 'front door'),
                  type=c('timeIn', 'timeIn', 'timeOut'),
                  time=c(
as.POSIXct('2016 12 02 06 05 01', format = '%Y %m %d %H %M %S'),
as.POSIXct('2016 12 02 06 05 02', format = '%Y %m %d %H %M %S'),
as.POSIXct('2016 12 02 06 05 03', format = '%Y %m %d %H %M %S')                     )
)

我想把它旋转成这样

person        door        timeIn             timeOut

bob           front door  min(<date/time>) max(<date/time>)

我似乎无法获得 dcast 的正确语法。data.table。我试过了

dcast.data.table(
  dt, person + door ~ type, 
  value.var = 'time', 
  fun.aggregate = function(x) ifelse(type == 'timeIn', min(x), max(x))
)

这会引发错误：

Aggregating function(s) should take vector inputs and return a single value (length=1).

我也试过：

 dcast.data.table(dt, person + door ~ type, value.var = 'time')

但是结果把我的日期丢掉了

   person       door timeIn timeOut
1:    bob front door      2       1

如有任何建议，我们将不胜感激。 TIA

Answer 1

这将是实现您的目标的一种方式。我修改了您的 dt 并创建了以下数据集。对于每个人，我寻找了 timeIn 的最小时间和 timeOut 的最大时间。然后，我将 dcast() 应用于结果。

#   person       door    type                time
#1:    bob front door  timeIn 2016-12-02 06:05:01
#2:    bob front door  timeIn 2016-12-02 06:05:02
#3:    bob front door timeOut 2016-12-02 06:05:03
#4:    bob front door timeOut 2016-12-02 06:05:05
#5:    ana front door  timeIn 2016-12-02 07:06:01
#6:    ana front door  timeIn 2016-12-02 07:06:02
#7:    ana front door timeOut 2016-12-02 07:06:03
#8:    ana front door timeOut 2016-12-02 07:06:05

library(data.table)

dcast(
   dt[, .SD[(type == "timeIn" & time == min(time))|(type == "timeOut" & time == max(time))], by = person],
   person + door ~ type)

#   person       door              timeIn             timeOut
#1:    ana front door 2016-12-02 07:06:01 2016-12-02 07:06:05
#2:    bob front door 2016-12-02 06:05:01 2016-12-02 06:05:05

数据

dt <- structure(list(person = c("bob", "bob", "bob", "bob", "ana", 
"ana", "ana", "ana"), door = c("front door", "front door", "front door", 
"front door", "front door", "front door", "front door", "front door"
), type = c("timeIn", "timeIn", "timeOut", "timeOut", "timeIn", 
"timeIn", "timeOut", "timeOut"), time = structure(c(1480658701, 
1480658702, 1480658703, 1480658705, 1480662361, 1480662362, 1480662363, 
1480662365), class = c("POSIXct", "POSIXt"))), .Names = c("person", 
"door", "type", "time"), row.names = c(NA, -8L), class = c("data.table", 
"data.frame"))

Answer 2

有多种方法可以使用 dcast 获得所需的结果。 jazzurro 的解决方案在重塑结果之前进行聚合。这里的方法直接使用 dcast 但可能需要一些 post 处理。我们正在使用 jazzurro 的数据，这些数据经过调整以遵守 UTC 时区和 data.table.

的 CRAN 版本 1.10.0

1。让 `ifelse` 开始工作

如 Q 中所述，

dcast(
  dt, person + door ~ type, 
  value.var = 'time', 
  fun.aggregate = function(x) ifelse(type == 'timeIn', min(x), max(x))
)

returns 错误信息。错误消息的全文包括使用 fill 参数的提示。不幸的是，ifelse() 不遵守 POSIXct class（有关详细信息，请参阅 ?ifelse），因此需要强制执行。

与

dcast(
  dt, person + door ~ type, 
  value.var = 'time', 
  fun.aggregate = function(x) 
    lubridate::as_datetime(ifelse(type == 'timeIn', min(x), max(x))),
  fill = 0
)

我们确实得到了

#   person       door              timeIn             timeOut
#1:    ana front door 2016-12-02 07:06:01 2016-12-02 07:06:05
#2:    bob front door 2016-12-02 06:05:01 2016-12-02 06:05:05

2。替代 `ifelse`

ifelse 的帮助页面建议

(tmp <- yes; tmp[!test] <- no[!test]; tmp)

作为备选方案。按照这个建议，

dcast(
  dt, person + door ~ type, 
  value.var = 'time', 
  fun.aggregate = function(x) {
    test <- type == "timeIn"; tmp <- min(x); tmp[!test] = max(x)[!test]; tmp
    }
)

returns

#   person       door              timeIn             timeOut
#1:    ana front door 2016-12-02 07:06:01 2016-12-02 07:06:05
#2:    bob front door 2016-12-02 06:05:01 2016-12-02 06:05:05

请注意，fill 参数和 POSIXct 的强制都不需要。

3。使用增强 `dcast`

使用最新版本的dcast.data.table，我们可以向fun.aggregate提供函数列表：

dcast(dt, person + door ~ type, value.var = 'time', fun = list(min, max))

returns

#   person       door     time_min_timeIn    time_min_timeOut     time_max_timeIn    time_max_timeOut
#1:    ana front door 2016-12-02 07:06:01 2016-12-02 07:06:03 2016-12-02 07:06:02 2016-12-02 07:06:05
#2:    bob front door 2016-12-02 06:05:01 2016-12-02 06:05:03 2016-12-02 06:05:02 2016-12-02 06:05:05

我们可以通过

删除不需要的列并重命名其他列

dcast(dt, person + door ~ type, value.var = 'time', fun = list(min, max))[
  , .(person, door, timeIn = time_min_timeIn, timeOut = time_max_timeOut)]

这让我们

#   person       door              timeIn             timeOut
#1:    ana front door 2016-12-02 07:06:01 2016-12-02 07:06:05
#2:    bob front door 2016-12-02 06:05:01 2016-12-02 06:05:05

数据

如上所述，我们使用的是jazzurro的数据

dt <- structure(list(person = c("bob", "bob", "bob", "bob", "ana", 
"ana", "ana", "ana"), door = c("front door", "front door", "front door", 
"front door", "front door", "front door", "front door", "front door"
), type = c("timeIn", "timeIn", "timeOut", "timeOut", "timeIn", 
"timeIn", "timeOut", "timeOut"), time = structure(c(1480658701, 
1480658702, 1480658703, 1480658705, 1480662361, 1480662362, 1480662363, 
1480662365), class = c("POSIXct", "POSIXt"))), .Names = c("person", 
"door", "type", "time"), row.names = c(NA, -8L), class = c("data.table", 
"data.frame"))

但将时区强制为 UTC。

有

dt[, time := lubridate::with_tz(time, "UTC")]

我们有

dt
#   person       door    type                time
#1:    bob front door  timeIn 2016-12-02 06:05:01
#2:    bob front door  timeIn 2016-12-02 06:05:02
#3:    bob front door timeOut 2016-12-02 06:05:03
#4:    bob front door timeOut 2016-12-02 06:05:05
#5:    ana front door  timeIn 2016-12-02 07:06:01
#6:    ana front door  timeIn 2016-12-02 07:06:02
#7:    ana front door timeOut 2016-12-02 07:06:03
#8:    ana front door timeOut 2016-12-02 07:06:05

独立于本地时区。

将 dcast.data.table 与日期值和聚合一起使用

Using dcast.data.table with date values and aggregation

r

data.table

dcast

1。让 ifelse 开始工作

2。替代 ifelse

3。使用增强 dcast

数据

1。让 `ifelse` 开始工作

2。替代 `ifelse`

3。使用增强 `dcast`