looping to make new variables R -

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is there cleaner way following using loop solution in r? of now, resorting cutting , pasting, changing reference column want result attached existing data set new variable. thank in advance.

library(tm) library(snowballc) data <- data.frame(c("asd"), c(3)) list <- c("eat", "drink")  text <- c("i eat , drink day")  text <- corpus(vectorsource(text)) text <- tm_map(text, content_transformer(tolower)) text <- tm_map(text, removepunctuation) text <- tm_map(text, removenumbers) text <- tm_map(text, removewords, stopwords('english')) text <- tm_map(text, stemdocument) text <- tm_map(text, stripwhitespace) text <- as.data.frame(text) text <- text$text text <- strsplit(as.matrix(text), ' +') text <- lapply(text, lapply, function(z) paste0(' ', z)) text <- lapply(text, unlist)  implode <- function(..., sep='') {   paste(..., collapse=sep) }  wordproportion <- function(x, corpus) {   y <- length(grep(corpus, x))   return(y/ length(x)) }  estimateproportion <- function (corpus, domain) {   x <- as.data.frame(extractcorpus2(domain)) %>% distinct(text)    x <- implode(x$text, sep=" | ")   x <- unlist(lapply(corpus, wordproportion, x))   x <- findinterval(x, quantile(x[x > 0], seq(0, .9, .1))) }  data$topic_1 <- estimateproportion(text, list)

here loop, have add column titles later because can't use $ way

for (i in 1:n) {  train[,(i + y)] <- estimateproportion(train_corpus, train_lda_term[, i])  # y number of preceding columns , n many columns want add } colnames(train[(1+y):(n+y)] <- paste0("topic_0",1:n)

edit: unless train list, replace train[,(i + y)] train[(i + y)] , colnames names


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