How to make a rank column in R

Question

I have a database with columns M1, M2 and M3. These M values correspond to the values obtained by each method. My idea is now to make a rank column for each of them. For M1 and M2, the rank will be from the highest value to the lowest value and M3 in reverse. I made the output table for you to see.

df1<-structure(list(M1 = c(400,300, 200, 50), M2 = c(500,200, 10, 100), M3 = c(420,330, 230, 51)), class = "data.frame", row.names = c(NA,-4L))

> df1
   M1  M2  M3
1 400 500 420
2 300 200 330
3 200 10 230
4  50 100  51

Output

> df1
   M1  rank M2  rank M3 rank
1 400   1   500  1   420  4    
2 300   2   200  2   330  3
3 200   3   10   4   230  2
4  50   4   100  3   51   1

Adjust rankings:

I used the code, but in a case I'm working on, my rankings looked like this:

Answer 1

What I would do to achieve this result would be to transform each of the df columns into factors, and then convert them into numeric again. This could be accomplished in basic R, but for simplicity I report the tidyverse code:

library(tidyverse)

df1 = df1 %>% 
  mutate(Rank1 = as.numeric(as.factor(M1))) %>% 
  mutate(Rank2 = as.numeric(as.factor(M2))) %>% 
  mutate(Rank3 = as.numeric(fct_rev(as.factor(M3))))

Answer 2

Another possible solution, based on dplyr:

library(dplyr)

df1 %>% 
  mutate(across(-3, ~ dense_rank(desc(.x)), .names = "{.col}_rank"),
         across(3, ~ dense_rank(.x), .names = "{.col}_rank")) %>% 
  relocate(sort(names(.)))

#>    M1 M1_rank  M2 M2_rank  M3 M3_rank
#> 1 400       1 500       1 420       4
#> 2 300       2 200       2 330       3
#> 3 200       3  10       4 230       2
#> 4  50       4 100       3  51       1