有没有一种方法可以用一行代码来变异和创建许多新变量?

时间:2019-12-30 21:55:28

标签: r dplyr

我有类似的东西:

df<-data.frame(group=c(1, 1, 1, 1,1,2, 2, 2, 2), 
               date=c("2000-01-01 11:00:00", "2000-01-03 11:00:00", "2000-01-04 11:20:00", "2000-01-04 14:20:00", "2000-01-05 11:40:00", "2000-01-09 12:20:00", "2000-01-09 13:20:00", "2000-01-10 12:20:00", "2000-01-12 16:20:00"))
  group                date
1     1 2000-01-01 11:00:00
2     1 2000-01-03 11:00:00
3     1 2000-01-04 11:20:00
4     1 2000-01-04 14:20:00
5     1 2000-01-05 11:40:00
6     2 2000-01-09 12:20:00
7     2 2000-01-09 13:20:00
8     2 2000-01-10 12:20:00
9     2 2000-01-12 16:20:00

我想创建许多列来表示日期后24小时,48小时等(例如):

df%>%mutate(first=date+86400, second=date+172800, third=date+259200) 

等等等,我以秒为单位添加一天,但这非常耗时(如果我想要数百列)。我假设有一种迭代的方法。

谢谢

2 个答案:

答案 0 :(得分:5)

如果我们可以使用english包,则可以在使用lapply生成值的同时生成列名

library(english)
df$date <- as.POSIXct(df$date)
df[as.character(ordinal(1:3))] <- lapply(1:3, function(x) df$date + 86400 * x)

可以在一行代码中完成as.POSIXct循环转换,但是我们将不必要地进行多次转换(并非所有单线转换都是有效的)


或与purrr

library(purrr)
library(dplyr)
map_dfc(1:3, ~ tibble(!! as.character(ordinal(.x)) := df$date + 86400 * .x)) %>%
   bind_cols(df, .)
# group                date               first              second               third
#1     1 2000-01-01 11:00:00 2000-01-02 11:00:00 2000-01-03 11:00:00 2000-01-04 11:00:00
#2     1 2000-01-03 11:00:00 2000-01-04 11:00:00 2000-01-05 11:00:00 2000-01-06 11:00:00
#3     1 2000-01-04 11:20:00 2000-01-05 11:20:00 2000-01-06 11:20:00 2000-01-07 11:20:00
#4     1 2000-01-04 14:20:00 2000-01-05 14:20:00 2000-01-06 14:20:00 2000-01-07 14:20:00
#5     1 2000-01-05 11:40:00 2000-01-06 11:40:00 2000-01-07 11:40:00 2000-01-08 11:40:00
#6     2 2000-01-09 12:20:00 2000-01-10 12:20:00 2000-01-11 12:20:00 2000-01-12 12:20:00
#7     2 2000-01-09 13:20:00 2000-01-10 13:20:00 2000-01-11 13:20:00 2000-01-12 13:20:00
#8     2 2000-01-10 12:20:00 2000-01-11 12:20:00 2000-01-12 12:20:00 2000-01-13 12:20:00
#9     2 2000-01-12 16:20:00 2000-01-13 16:20:00 2000-01-14 16:20:00 2000-01-15 16:20:00

答案 1 :(得分:3)

涉及dplyrpurrr的另一种可能性可能是:

map(86400*1:3, ~ df %>%
     transmute(!!paste(.x/3600, "hours", sep = "_") := as.POSIXct(date) + .x)) %>%
 bind_cols(df, .)

  group                date            24_hours            48_hours            72_hours
1     1 2000-01-01 11:00:00 2000-01-02 11:00:00 2000-01-03 11:00:00 2000-01-04 11:00:00
2     1 2000-01-03 11:00:00 2000-01-04 11:00:00 2000-01-05 11:00:00 2000-01-06 11:00:00
3     1 2000-01-04 11:20:00 2000-01-05 11:20:00 2000-01-06 11:20:00 2000-01-07 11:20:00
4     1 2000-01-04 14:20:00 2000-01-05 14:20:00 2000-01-06 14:20:00 2000-01-07 14:20:00
5     1 2000-01-05 11:40:00 2000-01-06 11:40:00 2000-01-07 11:40:00 2000-01-08 11:40:00
6     2 2000-01-09 12:20:00 2000-01-10 12:20:00 2000-01-11 12:20:00 2000-01-12 12:20:00
7     2 2000-01-09 13:20:00 2000-01-10 13:20:00 2000-01-11 13:20:00 2000-01-12 13:20:00
8     2 2000-01-10 12:20:00 2000-01-11 12:20:00 2000-01-12 12:20:00 2000-01-13 12:20:00
9     2 2000-01-12 16:20:00 2000-01-13 16:20:00 2000-01-14 16:20:00 2000-01-15 16:20:00