Question

I’m looking to speed up a loop that assigns a rating to rows based on different conditions. The are six different ratings to be assigned (0 to 5) based on different conditions. I tried to do this using a for loop with if statements for each condition, but with millions of rows to go through this really is no option. I do not even know how long it took to finish. It had been running for hours though before I manually stopped it.

The rules are:

Rating 0: if df$Bounce >= 75 and df$time<10 and df$view<1
Rating 1: if df$Bounce >= 75 or df$Assist<1
Rating 2: if df$Bounce < 75 and df$Assist<2
Rating 3: if df$Bounce < 75 and df$Assist<3
Rating 4: if df$Bounce < 75 and df$Assist<=4
Rating 5: if df$Bounce < 75 and df$Assist>=5

I’ve got more of these ‘slow’ statements in my script, so the answer to this question will speed up a lot of processes!

A small example dataset

tc <- textConnection('
belongID   uniqID   Bounce     Assist   time   view    
   1           101     90       10       7       0      
   1           102     75        0       8      10
   2           103     10       30       4       2
   2           104     50        3       1      10
   2           105     74        2       5       4
   3           106      5        1       2       8  ')

df <- read.table(tc,header=TRUE)

The outcome should result in the same dataset with a new column Rating and the ratings according to the rules:

belongID   uniqID   Bounce     Assist   time   view     Rating    
   1           101     90       10       7       0       0
   1           102     75        0       8      10       1
   2           103     10       30       4       2       5
   2           104     50        3       1      10       4
   2           105     74        2       5       4       3
   3           106      5        1       2       8       2

Edit: changed rating 1 condition!

Answer 1

Here is a simple algorithm in a function that does what you ask. Since this contains only three rules it should be really fast. (However, I make the implicit assumption that Assist is always an integer.)

rating <- function(Bounce, Assist, time, view){
  x <- pmin(5, Assist + 1)
  x[Bounce >= 75 & time<10 & view<1] <- 0
  x[Bounce >= 75 & Assist < 1] <- 1
  x
}

within(df, rating <- rating(Bounce, Assist, time, view))

  belongID uniqID Bounce Assist time view rating
1        1    101     90     10    7    0      0
2        1    102     75      0    8   10      1
3        2    103     10     30    4    2      5
4        2    104     50      3    1   10      4
5        2    105     74      2    5    4      3
6        3    106      5      1    2    8      2