Try something like this:
text1='"id","gender","age","category1","category2","category3","category4","category5","category6","category7","category8","category9","category10"
1,"Male",22,"movies","music","travel","cloths","grocery",,,,,
2,"Male",28,"travel","books","movies",,,,,,,
3,"Female",27,"rent","fuel","grocery","cloths",,,,,,
4,"Female",22,"rent","grocery","travel","movies","cloths",,,,,
5,"Female",22,"rent","online-shopping","utiliy",,,,,,,'
d1 <- read.table(text=text1, sep=",", head=T, as.is=T)
library(reshape2)
d2 <- melt(d1, id.vars=c("id","gender","age"))
names(d2)[5] <- "category"
names(d2)[4] <- "rank"
d2$rank <- gsub("category", "", d2$rank)
head(d2)
# id gender age rank category
# 1 1 Male 22 1 movies
# 2 2 Male 28 1 travel
# 3 3 Female 27 1 rent
# 4 4 Female 22 1 rent
# 5 5 Female 22 1 rent
# 6 1 Male 22 2 music