R similar column names ifelse - r

Question

adding reproducible code as suggested by answers
Qs<-paste0("Q2_", 1:18)
set.seed(15)
maindata <- data.frame(ID=1:5)
for(q in Qs) {
maindata[,q] <- sample(1:20,5,replace=T)
}
I have below code. Is their a better to achieve the output without writing each line? If i thought of writing the for loop for iterating over questions 1 to 18 but felt that for loop might not be too efficient...
ifelse(maindata$Q2_1 > 2 & maindata$Q2_1< 11 & !is.na(maindata$Q2_1), 1, 0 )+
ifelse(maindata$Q2_2 > 2 & maindata$Q2_2< 11 & !is.na(maindata$Q2_2), 1, 0)+
ifelse(maindata$Q2_3 > 2 & maindata$Q2_3< 11 & !is.na(maindata$Q2_3), 1, 0)+
ifelse(maindata$Q2_4 > 2 & maindata$Q2_4< 11 & !is.na(maindata$Q2_4), 1, 0)+
ifelse(maindata$Q2_5 > 2 & maindata$Q2_5< 11 & !is.na(maindata$Q2_5), 1, 0)+
ifelse(maindata$Q2_6 > 2 & maindata$Q2_6< 11 & !is.na(maindata$Q2_6), 1, 0)+
ifelse(maindata$Q2_7 > 2 & maindata$Q2_7< 11 & !is.na(maindata$Q2_7), 1, 0)+
ifelse(maindata$Q2_8 > 2 & maindata$Q2_8< 11 & !is.na(maindata$Q2_8), 1, 0)+
ifelse(maindata$Q2_9 > 2 & maindata$Q2_9< 11 & !is.na(maindata$Q2_9), 1, 0)+
ifelse(maindata$Q2_10 > 2 & maindata$Q2_10< 11 & !is.na(maindata$Q2_10), 1, 0)+
ifelse(maindata$Q2_11 > 2 & maindata$Q2_11< 11 & !is.na(maindata$Q2_11), 1, 0)+
ifelse(maindata$Q2_12 > 2 & maindata$Q2_12< 11 & !is.na(maindata$Q2_12), 1, 0)+
ifelse(maindata$Q2_13 > 2 & maindata$Q2_13< 11 & !is.na(maindata$Q2_13), 1, 0)+
ifelse(maindata$Q2_14 > 2 & maindata$Q2_14< 11 & !is.na(maindata$Q2_14), 1, 0)+
ifelse(maindata$Q2_15 > 2 & maindata$Q2_15< 11 & !is.na(maindata$Q2_15), 1, 0)+
ifelse(maindata$Q2_16 > 2 & maindata$Q2_16< 11 & !is.na(maindata$Q2_16), 1, 0)+
ifelse(maindata$Q2_17 > 2 & maindata$Q2_17< 11 & !is.na(maindata$Q2_17), 1, 0)+
ifelse(maindata$Q2_18 > 2 & maindata$Q2_18< 11 & !is.na(maindata$Q2_18), 1, 0)

Answer 1

Well, here's one way. First, let's create some sample data
Qs<-paste0("Q2_", 1:18)
set.seed(15)
maindata <- data.frame(ID=1:5)
for(q in Qs) {
maindata[,q] <- sample(1:20,5,replace=T)
}
Here we make a list of all the question names (Qs) and we create a data.frame with 5 rows where each column contains values sampled from 1:20. If we want the score for each line for each individual, we can do
score <- rowSums(sapply(Qs, function(q)
maindata[,q] > 2 & maindata[,q] <11 & !is.na(maindata[,q]) )+0)
Here I use sapply to iterate over the question names. Then i wrote the formula once and swap in the different question names. Here I return a simple logical value and add zero to convert FALSE to 0 and TRUE to 1. Then I use rowSums to app up scores across rows. We can see the results with
cbind(maindata[,"ID", drop=F], score)
# ID score
# 1 1 9
# 2 2 8
# 3 3 4
# 4 4 6
# 5 5 10