Loop through df and create new df in R - r

Question

I have a df (10 rows, 15 columns)
df<-data.frame(replicate(15,sample(0:1,10,rep=TRUE)))
I want to loop over each column, do something to each row and create a new df with the answer.
I actually want to do a linear regression on each column. I get back a list for each column. For example I have a second df with what I want to put into the lm. df2<-data.frame(replicate(2,sample(0:1,10,rep=TRUE)))
I then want to do something like:
new_df <- data.frame()
for (i in 1:ncol(df)){
j<-lm(df[,i] ~ df2$X1 + df2$X2)
temp_df<-j$residuals
new_df[,i]<-cbind(new_df,temp_df)
}
I get the error:
Error in data.frame(..., check.names = FALSE) : arguments imply
differing number of rows: 0, 8
I have checked other similar posts but they always seem to involve a function or something similarly complex for a newbie like me. Please help

Answer 1

This can be done without loops but for your understanding, using loops we can do
new_df <- df
for (i in names(df)) {
j<-lm(df[,i] ~ df$X1 + df$X2)
new_df[i] <- j$residuals
}
You are initialising an empty dataframe with 0 rows and 0 columns initially as new_df and hence when you are trying to assign the value to it, it gives you an error. Instead of that assign original df to new_df as they both are going to share the same structure and then use the above.

Answer 2

Update
Based on the new example
lst1 <- lapply(names(df), function(nm) {dat <- cbind(df[nm], df2[c('X1', 'X2')])
lm(paste0(nm, "~ X1 + X2"), data = dat)$residuals})
out <- setNames(data.frame(lst1), names(df))
Also, this doesn't need any loop
out2 <- lm(as.matrix(df) ~ X1 + X2, data = cbind(df, df2))$residuals
Old
We can do this easily without any loop
new_df <- df + 10
---
If we need a loop, it can be done with `lapply`
new_df <- df
new_df[] <- lapply(df, function(x) x + 10)
---
Or with a `for` loop
lst1 <- vector('list', ncol(df))
for(i in seq_along(df)) lst1[[i]] <- df[, i] + 10
new_df <- as.data.frame(lst1)
data
set.seed(24)
df <- data.frame(replicate(15,sample(0:1,10,rep=TRUE)))
df2 <- data.frame(replicate(2,sample(0:1,10,rep=TRUE)))

Answer 3

I would do as suggested by akrun. But if you do need (or want) to loop for some reasons you can use:
df<-data.frame(replicate(15,sample(0:1,10,rep=TRUE)))
new_df <- data.frame(replicate(15, rep(NA, 10)))
for (i in 1:ncol(df)){
new_df[ ,i] <- df[ , i] + 10
}