我需要订购重复项(首次访问,第二次访问,第三次访问...作为另一个变量中的类别)。所以我可以设法让它们按变量排序。 例如:
tagof
我需要的是建立一个给我的东西:
ids<-c("a", "a", "b", "c", "c", "c")
Dates<-c("2012-06-09", "2012-05-17", "2012-07-13", "2012-08-25", "2013-04-11", "2014-11-03")
mydata<-data.frame(ids, Dates)
ids Dates
a 2012-06-09
a 2012-05-17
b 2012-07-13
c 2012-08-25
c 2013-04-11
c 2014-11-03
然后:
ids Dates order
a 2012-06-09 First
a 2012-05-17 Second
b 2012-07-13 First
c 2012-08-25 First
c 2013-04-11 Second
c 2014-11-03 Third
答案 0 :(得分:1)
使用基础R中的data.table
包和reshape
函数:
library(data.table)
setDT(mydata)
mydata[, order := 1:.N, by = ids]
mydata <- reshape(mydata, timevar = "order", idvar = "ids", direction = "wide")
setnames(mydata, "ids", "ids2")
setnames(mydata, "Dates.1", "first")
setnames(mydata, "Dates.2", "second")
setnames(mydata, "Dates.3", "third")
ids2 first second third
1: a 2012-06-09 2012-05-17 NA
2: b 2012-07-13 NA NA
3: c 2012-08-25 2013-04-11 2014-11-03
答案 1 :(得分:1)
只有基数R,你可以这样做:
mydata$order <- ave(mydata$Dates, mydata$ids, FUN = seq_along)
reshape(mydata, idvar = "ids", timevar = "order", direction="wide")
# ids Dates.1 Dates.2 Dates.3
# 1 a 2012-06-09 2012-05-17 <NA>
# 3 b 2012-07-13 <NA> <NA>
# 4 c 2012-08-25 2013-04-11 2014-11-03
答案 2 :(得分:0)
使用tidyverse
,你可以这样做:
library(tidyverse)
mydata.ordered <- mydata %>%
mutate(Dates = as.Date(Dates)) %>%
group_by(ids) %>%
arrange(Dates) %>%
mutate(order = rep(c("First", "Second", "Third"), length.out = n()))
mydata.spread <- mydata.ordered %>%
spread(order, Dates)
# A tibble: 3 x 4
# Groups: ids [3]
# ids First Second Third
# * <fct> <date> <date> <date>
# 1 a 2012-05-17 2012-06-09 NA
# 2 b 2012-07-13 NA NA
# 3 c 2012-08-25 2013-04-11 2014-11-03
答案 3 :(得分:0)
使用dplyr
和tidyr
库:
ordinal <- c("First", "Second", "Third")
ordinal.df <- data.frame(ordinal = seq_along(ordinal), order = ordinal)
group_by(mydata, ids) %>%
mutate(ordinal = 1:n()) %>%
left_join(ordinal.df) %>%
select(-ordinal) %>%
spread(key = "order", value = "Dates")
# A tibble: 3 x 4
# Groups: ids [3]
ids First Second Third
* <fct> <fct> <fct> <fct>
1 a 2012-06-09 2012-05-17 NA
2 b 2012-07-13 NA NA
3 c 2012-08-25 2013-04-11 2014-11-03