I have been trying to find a simpler solution to my problem. I have a data set containing many columns:
S.No A B C D E F........N
1 2 3 2 5 7 9........20
2 4 3 5 4 4 5........3
.
.
.
.
3000 4 5 6 3 5 3 6 .........2
I would like to replace the df$C and df$D columns based on the df$A and df$B column values (ordered pairs).
I have this relation in a smaller data frame (df2) where Z and Q correspond to A and B of df. I need to populate C and D values of df based on R and S values of df2.
Z Q R S
1 2 0.3 4
1 3 -0.3 -4
2 2 -0.2 -5
2 3 -0.5 -1
.
.
.
.
Currently, I am using the brute force for and if loop wherein I am comparing the values from every row in df for columns df$A and df$B with df2$Z and df2$Q and then populating C and D columns of df based on R and S values in df2. Since I have more than a million values, the loops seems to run forever.
Is there a smarter way to do the same ?