Rank function to rank multiple variables in R - r

Question

I am trying to rank multiple numeric variables ( around 700+ variables) in the data and am not sure exactly how to do this as I am still pretty new to using R.
I do not want to overwrite the ranked values in the same variable and hence need to create a new rank variable for each of these numeric variables.
From reading the posts, I believe assign and transform function along with rank maybe able to solve this. I tried implementing as below ( sample data and code) and am struggling to get it to work.
The output dataset in addition to variables xcount, xvisit, ysales need to be populated
With variables xcount_rank, xvisit_rank, ysales_rank containing the ranked values.
input <- read.table(header=F, text="101 2 5 6
102 3 4 7
103 9 12 15")
colnames(input) <- c("id","xcount","xvisit","ysales")
input1 <- input[,2:4] #need to rank the numeric variables besides id
for (i in 1:3)
{
transform(input1,
assign(paste(input1[,i],"rank",sep="_")) =
FUN = rank(-input1[,i], ties.method = "first"))
}
input[paste(names(input)[2:4], "rank", sep = "_")] <-
lapply(input[2:4], cut, breaks = 10)
The problem with this approach is that it's creating the rank values as (101, 230] , (230, 450] etc whereas I would like to see the values in the rank variable to be populated as 1, 2 etc up to 10 categories as per the splits I did. Is there any way to achieve this? input[5:7] <- lapply(input[5:7], rank, ties.method = "first")
The approach I tried from the solutions provided below is:
input <- read.table(header=F, text="101 20 5 6
102 2 4 7
103 9 12 15
104 100 8 7
105 450 12 65
109 25 28 145
112 854 56 93")
colnames(input) <- c("id","xcount","xvisit","ysales")
input[paste(names(input)[2:4], "rank", sep = "_")] <-
lapply(input[2:4], cut, breaks = 3)
Current output I get is:
id xcount xvisit ysales xcount_rank xvisit_rank ysales_rank
1 101 20 5 6 (1.15,286] (3.95,21.3] (5.86,52.3]
2 102 2 4 7 (1.15,286] (3.95,21.3] (5.86,52.3]
3 103 9 12 15 (1.15,286] (3.95,21.3] (5.86,52.3]
4 104 100 8 7 (1.15,286] (3.95,21.3] (5.86,52.3]
5 105 450 12 65 (286,570] (3.95,21.3] (52.3,98.7]
6 109 25 28 145 (1.15,286] (21.3,38.7] (98.7,145]
7 112 854 56 93 (570,855] (38.7,56.1] (52.3,98.7]
Desired output:
id xcount xvisit ysales xcount_rank xvisit_rank ysales_rank
1 101 20 5 6 1 1 1
2 102 2 4 7 1 1 1
3 103 9 12 15 1 1 1
4 104 100 8 7 1 1 1
5 105 450 12 65 2 1 2
6 109 25 28 145 1 2 3
Would like to see the records in the group they would fall under if I try to rank the interval values.

Answer 1

Using dplyr
library(dplyr)
nm1 <- paste("rank", names(input)[2:4], sep="_")
input[nm1] <- mutate_each(input[2:4],funs(rank(., ties.method="first")))
input
# id xcount xvisit ysales rank_xcount rank_xvisit rank_ysales
#1 101 2 5 6 1 2 1
#2 102 3 4 7 2 1 2
#3 103 9 12 15 3 3 3
Update
Based on the new input and using cut
input[nm1] <- mutate_each(input[2:4], funs(cut(., breaks=3, labels=FALSE)))
input
# id xcount xvisit ysales rank_xcount rank_xvisit rank_ysales
#1 101 20 5 6 1 1 1
#2 102 2 4 7 1 1 1
#3 103 9 12 15 1 1 1
#4 104 100 8 7 1 1 1
#5 105 450 12 65 2 1 2
#6 109 25 28 145 1 2 3
#7 112 854 56 93 3 3 2