I have a data frame where I essentially have an ID#, a year, and a status code. Here is an example of it:
我有一个数据框架,其中包含ID#、一年和状态代码。这里有一个例子:
> df <- data.frame(ID=c(100,100,100,102,102,102),
Year=c(2010,2011,2012,2010,2011,2012),
Status=c("c","d","d","d","c","c"))
> df
ID Year Status
1 100 2010 c
2 100 2011 d
3 100 2012 d
4 102 2010 d
5 102 2011 c
6 102 2012 c
I want to add a 4th column (df$def
) as a binary based on the ID#'s status, however, once the status is "d" I need that to carry through the remaining years despite the status potentially changing to "c". I can write the simple IF statement to have a 0 for "c" and 1 for "d", but am having trouble factoring the dates moving forward.
我想要添加第4列(df$def)作为一个基于ID的二进制文件,但是,一旦状态为“d”,我需要它在剩余的年份中进行,尽管状态可能会变成“c”。我可以把简单的IF语句写成0表示“c”,1表示“d”,但我在分解日期时遇到了麻烦。
I would like the final table to look like this:
我希望最后的表格是这样的:
df
ID Year Status Def
1 100 2010 c 0
2 100 2011 d 1
3 100 2012 d 1
4 102 2010 d 1
5 102 2011 c 1
6 102 2012 c 1
Thanks for the help!
谢谢你的帮助!
3 个解决方案
#1
1
You could use:
您可以使用:
within(df, {def<- ave(Status=='d', ID, FUN=cumsum);def[def>1] <- 1 })
# ID Year Status def
#1 100 2010 c 0
#2 100 2011 d 1
#3 100 2012 d 1
#4 102 2010 d 1
#5 102 2011 c 1
#6 102 2012 c 1
Or for bigger dataset, you could use data.table
或者对于更大的数据集,可以使用data.table
library(data.table)
setDT(df)[, Def:=cumsum(Status=='d'), by=ID][ Def>1, Def:=1][]
# ID Year Status Def
#1: 100 2010 c 0
#2: 100 2011 d 1
#3: 100 2012 d 1
#4: 102 2010 d 1
#5: 102 2011 c 1
#6: 102 2012 c 1
Or you could use split
或者你可以用split
res <- unsplit(lapply(split(df, df$ID), function(x) {
indx <- which(x$Status=='d')
x$Def <- 0
if(length(indx)>0){
indx1 <- indx[1]
x$Def[indx1:nrow(x)] <- 1
}
x}), df$ID)
res
# ID Year Status Def
#1 100 2010 c 0
#2 100 2011 d 1
#3 100 2012 d 1
#4 102 2010 d 1
#5 102 2011 c 1
#6 102 2012 c 1
#2
1
You can try using the function by()
to get the cumulative sum by ID (not allowing it to go over 1)
您可以尝试使用by()函数来通过ID获取累积和(不允许它超过1)
df$def <- ifelse(df$Status == "c", 0, 1)
df$def <- pmin(1, unlist(by(df$def, df$ID, cumsum)))
#3
1
Here's another way:
这是另一种方式:
within(df, {
Def <-
ave(as.character(Status), ID,
FUN=function(x) ifelse(seq_along(x) < which.max(x == 'd'), 0, 1))
})
# ID Year Status Def
# 1 100 2010 c 0
# 2 100 2011 d 1
# 3 100 2012 d 1
# 4 102 2010 d 1
# 5 102 2011 c 1
# 6 102 2012 c 1
#1
1
You could use:
您可以使用:
within(df, {def<- ave(Status=='d', ID, FUN=cumsum);def[def>1] <- 1 })
# ID Year Status def
#1 100 2010 c 0
#2 100 2011 d 1
#3 100 2012 d 1
#4 102 2010 d 1
#5 102 2011 c 1
#6 102 2012 c 1
Or for bigger dataset, you could use data.table
或者对于更大的数据集,可以使用data.table
library(data.table)
setDT(df)[, Def:=cumsum(Status=='d'), by=ID][ Def>1, Def:=1][]
# ID Year Status Def
#1: 100 2010 c 0
#2: 100 2011 d 1
#3: 100 2012 d 1
#4: 102 2010 d 1
#5: 102 2011 c 1
#6: 102 2012 c 1
Or you could use split
或者你可以用split
res <- unsplit(lapply(split(df, df$ID), function(x) {
indx <- which(x$Status=='d')
x$Def <- 0
if(length(indx)>0){
indx1 <- indx[1]
x$Def[indx1:nrow(x)] <- 1
}
x}), df$ID)
res
# ID Year Status Def
#1 100 2010 c 0
#2 100 2011 d 1
#3 100 2012 d 1
#4 102 2010 d 1
#5 102 2011 c 1
#6 102 2012 c 1
#2
1
You can try using the function by()
to get the cumulative sum by ID (not allowing it to go over 1)
您可以尝试使用by()函数来通过ID获取累积和(不允许它超过1)
df$def <- ifelse(df$Status == "c", 0, 1)
df$def <- pmin(1, unlist(by(df$def, df$ID, cumsum)))
#3
1
Here's another way:
这是另一种方式:
within(df, {
Def <-
ave(as.character(Status), ID,
FUN=function(x) ifelse(seq_along(x) < which.max(x == 'd'), 0, 1))
})
# ID Year Status Def
# 1 100 2010 c 0
# 2 100 2011 d 1
# 3 100 2012 d 1
# 4 102 2010 d 1
# 5 102 2011 c 1
# 6 102 2012 c 1