Count features for different ids in columns in R in faster way

Question

I am trying to process a 20 GB data file in R. I have 16 gigs RAM and i7 processor. I am reading the data using :

y<-read.table(file=\"sample.csv\", header =          


        

Answer 1

How about table()?

> set.seed(5)
> ids <- sample(1:3, 12, TRUE)
> features <- sample(1:4, 12, TRUE)
> cbind(ids, features)
      ids features
 [1,]   1        2
 [2,]   3        3
 [3,]   3        2
 [4,]   1        1
 [5,]   1        2
 [6,]   3        4
 [7,]   2        3
 [8,]   3        4
 [9,]   3        4
[10,]   1        3
[11,]   1        1
[12,]   2        1

> table(ids, features)
   features
ids 1 2 3 4
  1 2 2 1 0
  2 1 0 1 0
  3 0 1 1 3

So for example feature 4 appears 3 times in id 3.

EDIT: You can use as.data.frame() to "flatten" the table and get:

> as.data.frame(table(ids, features))
   ids features Freq
1    1        1    2
2    2        1    1
3    3        1    0
4    1        2    2
5    2        2    0
6    3        2    1
7    1        3    1
8    2        3    1
9    3        3    1
10   1        4    0
11   2        4    0
12   3        4    3