for循环&如果功能在R [英] for loop & if function in R
问题描述
ID类别
1 a
1 b
1 c
2 a
2 b
3 a
3 b
4 a
5 a
我想使用if函数的for循环来添加另一列来计算每个分组ID，就像以下数列：
ID类别计数
1 a 1
1 b 2
1 c 3
2 a 1
2 b 2
3 a 1
3 b 2
4 a 1
5 a 1
我的代码是（输出是表名）：
<$ p $ （输出1 [i，1] ==输出[i-1,1]）{
输出1 [ i，rn]< - output1 [i-1，rn] + 1
}
else {
output1 [i，rn]< -1
}
}
<但是结果会返回，因为所有计数列的值都是1。
$ $ $ $ $ $ $ $> ID类别Co unt
1 a 1
1 b 1
1 c 1
2 a 1
2 b 1
3 a 1
3 b 1
4 a 1
5 a 1
请帮我...谢谢
有些软件包和矢量化的方法可以完成这个任务，但是如果你在循环练习，
$ b
output1 $ rn < - 1
for（i in 2：nrow（output1））{
if（output1 [i，1] == output1 [i-1,1]）{
output1 [i，rn] < - output1 [i-1，rn] + 1
}
else {
output1 [i，rn] <-1
}
}
使用原始代码，当您调用 output1 [i-1，rn] + 1 时你的循环的第三行，你引用了第一遍中不存在的行。通过首先创建行并使用值 1 填充它，可以给循环显式引用一些内容。
output1
＃ID类别
＃1 1 a 1
＃2 1 b 2
＃3 1 c 3
＃4 2 a 1
＃5 2 b 2
＃6 3 a 1
＃7 3 b 2
＃8 4 a 1
＃9 5 a 1
使用包dplyr，您可以快速完成：
library（dplyr）
output1％>％group_by（ID）％>％mutate（rn = 1：n（））
或用data.table：
setDT（output1）[，rn：= 1：.N，by = ID]
使用 base R ，您也可以使用：
output1 $ rn < - with（output1，ave（as.character（category），ID，FUN = seq））
这两个软件包中有插图和教程并在R控制台中搜索？ave 以获得最后的方法。
I was writing a loop with if function in R. The table is like below:
ID category
1 a
1 b
1 c
2 a
2 b
3 a
3 b
4 a
5 a
I want to use the for loop with if function to add another column to count each grouped ID, like below count column: ID category Count
1 a 1
1 b 2
1 c 3
2 a 1
2 b 2
3 a 1
3 b 2
4 a 1
5 a 1
My code is (output is the table name):
for (i in 2:nrow(output1)){
if(output1[i,1] == output[i-1,1]){
output1[i,"rn"]<- output1[i-1,"rn"]+1
}
else{
output1[i,"rn"]<-1
}
}
But the result returns as all count column values are all "1".
ID category Count
1 a 1
1 b 1
1 c 1
2 a 1
2 b 1
3 a 1
3 b 1
4 a 1
5 a 1
Please help me out... Thanks
There are packages and vectorized ways to do this task, but if you are practicing with loops try:
output1$rn <- 1
for (i in 2:nrow(output1)){
if(output1[i,1] == output1[i-1,1]){
output1[i,"rn"]<- output1[i-1,"rn"]+1
}
else{
output1[i,"rn"]<-1
}
}
With your original code, when you made this call output1[i-1,"rn"]+1 in the third line of your loop, you were referencing a row that didn't exist on the first pass. By first creating the row and filling it with the value 1, you give the loop something explicit to refer to.
output1
# ID category rn
# 1 1 a 1
# 2 1 b 2
# 3 1 c 3
# 4 2 a 1
# 5 2 b 2
# 6 3 a 1
# 7 3 b 2
# 8 4 a 1
# 9 5 a 1
With the package dplyr you can accomplish it quickly with:
library(dplyr)
output1 %>% group_by(ID) %>% mutate(rn = 1:n())
Or with data.table:
library(data.table)
setDT(output1)[,rn := 1:.N, by=ID]
With base R you can also use:
output1$rn <- with(output1, ave(as.character(category), ID, FUN=seq))
There are vignettes and tutorials on the two packages mentioned, and by searching ?ave in the R console for the last approach.
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