Reputation: 359
I want to create a loop from data in df1
it's important the data is taken one ID value at a time.
I'm unsure how this can be done with R.
#original dataset
id=c(1,1,1,2,2,2,3,3,3)
dob=c("11-08","12-04","04-03","10-04","03-07","06-02","12-09","01-01","03-08")
count=c(1,6,3,2,5,6,8,6,4)
outcome=rep(1:0,length.out=9)
df1=data.frame(id,dob,count,outcome)
#changes for each value this needs to be completed separately for each value
df2<-df1[df1$id==1,]
df2<-df2[,-4]
addition<-df2$count+45
df2<-cbind(df2,addition)
df3<-df1[df1$id==2,]
df3<-df3[,-4]
addition<-df3$count+45
df3<-cbind(df3,addition)
df4<-df1[df1$id==3,]
df4<-df4[,-4]
addition<-df4$count+45
df4<-cbind(df4,addition)
df5<-rbind(df2,df3,df4)
df5<-rbind(df2,df3,df4)
1 1 11-08 1 46
2 1 12-04 6 51
3 1 04-03 3 48
4 2 10-04 2 47
5 2 03-07 5 50
6 2 06-02 6 51
7 3 12-09 8 53
8 3 01-01 6 51
9 3 03-08 4 49
Upvotes: 0
Views: 47
Reputation: 887391
In the present context (could be a simplified example) it doesn't even need that to loop, as we can directly add the 'count' with a number
df1$addition <- df1$count + 45
However, if it is a complicated operation and needs to look into the 'id' separately, then do a group_by
operation
library(dplyr)
df1 %>%
group_by(id) %>%
mutate(addition = count + 45)
# A tibble: 9 x 5
# Groups: id [3]
# id dob count outcome addition
# <dbl> <fct> <dbl> <int> <dbl>
#1 1 11-08 1 1 46
#2 1 12-04 6 0 51
#3 1 04-03 3 1 48
#4 2 10-04 2 0 47
#5 2 03-07 5 1 50
#6 2 06-02 6 0 51
#7 3 12-09 8 1 53
#8 3 01-01 6 0 51
#9 3 03-08 4 1 49
Also, data.table
syntax would be
library(data.table)
setDT(df1)[, addition := count + 45, by = id]
or simply
setDT(df1)[, addition := count + 45]
Upvotes: 1