我对R很陌生，所以我想知道如何才能做得更好.我有一个由两列组成的数据表(Day和Sleepstatus).如何根据day列找到睡眠和觉醒的第一次迭代，并改变另一列以指示人何时开始睡眠(第1行睡眠)和何时停止睡眠(第1行觉醒).睡眠时间的剩余时间，列中应显示不适用.
| Day | SleepStatus |
|---|---|
| 1 | Sleeping |
| 1 | Sleeping |
| 1 | Sleeping |
| 1 | Awake |
| 2 | Sleeping |
| 2 | Sleeping |
| 2 | Sleeping |
| 2 | Awake |
所需输出
| Day | SleepStatus | Final Status |
|---|---|---|
| 1 | Sleeping | Start Sleep |
| 1 | Sleeping | NA |
| 1 | Sleeping | Stop Sleep |
| 1 | Awake | NA |
| 2 | Sleeping | Start Sleep |
| 2 | Sleeping | NA |
| 2 | Sleeping | Stop Sleep |
| 2 | Awake | NA |
这是一个潜在的解决方案:
library(data.table)
dt <- data.table::data.table(
Day = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L),
SleepStatus = c("Sleeping","Sleeping","Sleeping",
"Awake","Sleeping","Sleeping","Sleeping","Awake")
)
dt[, `Final Status` := {ifelse(
cumsum(SleepStatus != "Sleeping") != shift(cumsum(SleepStatus != "Sleeping"), fill = 0, type = "lag"),
"Stop Sleep", "Start Sleep")}]
dt[, `Final Status` := {ifelse(
`Final Status` == shift(`Final Status`, fill = "NA", type = "lag"),
NA, `Final Status`)}]
dt
#> Day SleepStatus Final Status
#> 1: 1 Sleeping Start Sleep
#> 2: 1 Sleeping <NA>
#> 3: 1 Sleeping <NA>
#> 4: 1 Awake Stop Sleep
#> 5: 2 Sleeping Start Sleep
#> 6: 2 Sleeping <NA>
#> 7: 2 Sleeping <NA>
#> 8: 2 Awake Stop Sleep
如果您将代码分解为更小的块，那么代码会更有意义.我在下面使用了tidyverse函数，因为我觉得它更容易理解，但我可以将其更改为数据.表语法，如果您愿意的话.
library(data.table)
dt <- data.table::data.table(
Day = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L),
SleepStatus = c("Sleeping","Sleeping","Sleeping",
"Awake","Sleeping","Sleeping","Sleeping","Awake")
)
library(tidyverse)
df <- as.data.frame(dt)
# When the Sleepstatus is not "Sleeping", increment the variable by one
df2 <- df %>%
mutate(Sleeping = cumsum(SleepStatus != "Sleeping"))
df2
#> Day SleepStatus Sleeping
#> 1 1 Sleeping 0
#> 2 1 Sleeping 0
#> 3 1 Sleeping 0
#> 4 1 Awake 1
#> 5 2 Sleeping 1
#> 6 2 Sleeping 1
#> 7 2 Sleeping 1
#> 8 2 Awake 2
# If the previous value in "Sleeping" is different to the current value,
# add the "stop sleeping" flag (i.e. show when "Sleeping" changes)
df3 <- df2 %>%
mutate(Sleep_label = ifelse(Sleeping != lag(Sleeping, default = 0), "Stop sleeping", "Start sleeping"))
df3
#> Day SleepStatus Sleeping Sleep_label
#> 1 1 Sleeping 0 Start sleeping
#> 2 1 Sleeping 0 Start sleeping
#> 3 1 Sleeping 0 Start sleeping
#> 4 1 Awake 1 Stop sleeping
#> 5 2 Sleeping 1 Start sleeping
#> 6 2 Sleeping 1 Start sleeping
#> 7 2 Sleeping 1 Start sleeping
#> 8 2 Awake 2 Stop sleeping
# Then, if the value in Sleep_label is equal to the previous label,
# change it to NA
df4 <- df3 %>%
mutate(Final_status = ifelse(Sleep_label == lag(Sleep_label, default = "NA"), NA, Sleep_label))
df4
#> Day SleepStatus Sleeping Sleep_label Final_status
#> 1 1 Sleeping 0 Start sleeping Start sleeping
#> 2 1 Sleeping 0 Start sleeping <NA>
#> 3 1 Sleeping 0 Start sleeping <NA>
#> 4 1 Awake 1 Stop sleeping Stop sleeping
#> 5 2 Sleeping 1 Start sleeping Start sleeping
#> 6 2 Sleeping 1 Start sleeping <NA>
#> 7 2 Sleeping 1 Start sleeping <NA>
#> 8 2 Awake 2 Stop sleeping Stop sleeping
由reprex package(v2.0.1)于2022年5月20日创建
这有意义吗？还是我只是让事情变得更加混乱？