Avoid the for loops-R-CodePudding

I have two data frames, x and y. For each value of x[,2], I look if the value is equal to the value of the elements of y[,1]. If so, I add a third column in the first data frame that contains the values of y[,2].

I managed to do that with loops, but how can I do this using vectors?

x=data.frame(1:15,15:1)
y=data.frame(3:5,c(7.2,8.5,0.3))

for ( i in 1:nrow(x)) { 

  for (j in 1:nrow(y)) {

    if (x[i,2]==y[j,1]){

      x[i,3]=y[j,2]

    }else{

    }
  }
}

CodePudding user response：

Use a join instead of loops - based on the loop comparision, the second column of 'x' is compared with the first column of 'y', thus those columns are used in the on, assign (:=) the second column (col2) from the second dataset to create the new column 'col3' in first data

library(data.table)
setDT(x)[y, col3 := i.col2, on = .(col2 = col1)]

-output

> x
    col1 col2 col3
 1:    1   15   NA
 2:    2   14   NA
 3:    3   13   NA
 4:    4   12   NA
 5:    5   11   NA
 6:    6   10   NA
 7:    7    9   NA
 8:    8    8   NA
 9:    9    7   NA
10:   10    6   NA
11:   11    5  0.3
12:   12    4  8.5
13:   13    3  7.2
14:   14    2   NA
15:   15    1   NA

data

x <- data.frame(col1 = 1:15, col2 = 15:1)
y <- data.frame(col1 = 3:5, col2 = c(7.2,8.5,0.3))

CodePudding user response：

Here is dplyr way how to avoid the for - loop:

library(dplyr)
x %>% 
  mutate(V3 = ifelse(V2 %in% y$V1, y$V2, NA))

   V1 V2  V3
1   1 15  NA
2   2 14  NA
3   3 13  NA
4   4 12  NA
5   5 11  NA
6   6 10  NA
7   7  9  NA
8   8  8  NA
9   9  7  NA
10 10  6  NA
11 11  5 8.5
12 12  4 0.3
13 13  3 7.2
14 14  2  NA
15 15  1  NA