I have a large data table Divvy (over 2.4 million records) that appears as such (some columns removed):

```
X   trip_id     from_station_id.x   to_station_id.x 
 1  1109420     94                  69
 2  1109421     69                  216
 3  1109427     240                 245
 4  1109431     113                 94
 5  1109433     127                 332
 3  1109429     240                 245

```

I would like to find the number of trips from each station to each opposing station. So for example, 

```
From X     To Y     Sum
94         69       1
240        245      2

```

etc. and then join it back to the inital table using dplyr to make something like the below and then limit it to distinct from\_station\_id/to\_combos, which I'll use to map routes (I have lat/long for each station):

```
X   trip_id     from_station_id.x   to_station_id.x   Sum 
 1  1109420     94                  69                1
 2  1109421     69                  216               1
 3  1109427     240                 245               2
 4  1109431     113                 94                1
 5  1109433     127                 332               1
 3  1109429     240                 245               1

```

I successfully used count to get some of this, such as:

```
count(Divvy$from_station_id.x==94 & Divvy$to_station_id.x == 69)
  x    freq
1 FALSE 2454553
2  TRUE      81

```

But this is obviously labor intensive as there are 300 unique stations, so well over 44k poss combinations. I created a helper table thinking I could loop it. 

```
n <- select(Divvy, from_station_id.y )

  from_station_id.x 
1                94                
2                69                
3               240               
4               113               
5               113               
6               127               

   count(Divvy$from_station_id.x==n[1,1] & Divvy$to_station_id.x == n[2,1])

      x    freq
1 FALSE 2454553
2  TRUE      81

```

I felt like a loop such as 

```
output <- matrix(ncol=variables, nrow=iterations)

output <- matrix()
for(i in 1:n)(output[i, count(Divvy$from_station_id.x==n[1,1] & Divvy$to_station_id.x == n[2,1]))

```

should work but come to think of it that will still only return 300 rows, not 44k, so it would have to then loop back and do n[2] & n[1] etc...

I felt like there might also be a quicker dplyr solution that would let me return a count of each combo and append it directly without the extra steps/table creation, but I haven't found it. 

I'm newer to R and I have searched around/think I'm close, but I can't quite connect that last dot of joining that result to Divvy. Any help appreciated.