In loop over dataframe rows, how to append list to dataframe

Question

In a for loop that loops over rows of a dataframe, I calculate results based on the values in the dataframe columns. How can I append the results (a list) into new columns in the dataframe? Example below is a dummy function, the real function is more complicated, and the approach needs to call the function instead of trying to re-create it. Looking for solutions that compare approaches in base R and tidyverse.

X <- seq(0,9,3)
Y <- seq(0,4,1)
vals <- c(100,200,300)

dummy_func <- function(x,y,z) {
  return(x+y*z)
}

df <- merge(x=data.frame(X), y=data.frame(Y),all.x=TRUE, all.y=TRUE)
print(df)

X	Y
0	0
3	0
6	0
9	0
0	1
3	1
etc	etc

for (row in 1:nrow(df)) {
    result <- dummy_func(df$X[row], df$Y[row], vals)
    # append this result to new columns
}

Desired dataframe:

X	Y	V1	V2	V3
0	0	0	0	0
3	0	3	3	3
6	0	6	6	6
9	0	9	9	9
0	1	100	200	300
3	1	103	203	303
etc	etc	etc	etc	etc

I think I asked a question along very similar lines a while back, where I had a base R approach but wanted to know how to do it in *purrr* / tidyverse methods. https://stackoverflow.com/questions/51978138/add-multiple-output-variables-using-purrr-and-a-predefined-function — thelatemail, Oct 21 '22 at 01:40

score 1 · Accepted Answer · answered Oct 21 '22 at 01:39

Base R attempt, as tidyverse isn't my strength.
Map is the workhorse here, passing the X and Y vectors to the dummy_func() function, while looping over each of the values in vals as the final argument:

df[paste0("V",seq_along(vals))] <- Map(dummy_func, df["X"], df["Y"], vals) 
df
#   X Y  V1  V2   V3
#1  0 0   0   0    0
#2  3 0   3   3    3
#3  6 0   6   6    6
#4  9 0   9   9    9
#5  0 1 100 200  300
#6  3 1 103 203  303
#7  6 1 106 206  306
# ...

this is so much cleaner than a loop, thank you – a11 Oct 21 '22 at 02:26 — a11, Oct 21 '22 at 02:26

In loop over dataframe rows, how to append list to dataframe

1 Answers1