Arnand - 1 year ago 66
R Question

# faster nested for loop R

I would like to speed up my solution in R.

I' ve got two Dataframes, let's say:
df_one:

``````A | B | C | D | same
1 | 3 | 2 | 4 | NA
6 | 5 | 1 | 3 | NA
5 | 3 | 7 | 3 | NA
3 | 4 | 8 | 3 | NA
``````

And df_two:

``````A | B
1 | 3
6 | 2
5 | 3
``````

If both the instances in column A and B are the same (or in a sequence of .5), I want a 1, otherwise an 0 in an extra column in df_one (df_one\$same).

I did this with the following code:

``````df_one\$same <- NA

for (i in 1:nrow(df_one)) {
for (j in 1:nrow(df_two)) {
distance <- seq(df_two[j, 2]-.5, df_two[j, 2]+.5, by = .1)
print(i)
if ((df_one[i, 1] == df_two[j, 1]) & (df_one[i, 2] %in% df_two[i, 2])){
df_one[i, 5] <- 1
break}
else{df_one[i, 5] <- 0}
}
}
``````

Can anyone help me with a faster solution?

A quicker solution to what I think you are asking is to use `left_join` from `dplyr` and check explicitly for the matches.

``````left_join(df_one, df_two, by = "A") %>%
mutate(same = B.x == B.y)
``````

gives

``````  A B.x C D  same B.y
1 1   3 2 4  TRUE   3
2 6   5 1 3 FALSE   2
3 5   3 7 3  TRUE   3
4 3   4 8 3    NA  NA
``````
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