search for: cell_cols

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2018 May 25
2
how to make the code more efficient using lapply
...ite slow. How to make it faster using lapply function ? Thanks in advance! temp.df<-c() # create an empty list to store the extracted result from each excel file inside for-loop for (i in list.files()) { # loop through each excel file in the directory temp<-read_xlsx(i,sheet=1,range=cell_cols(c(1,30,38:42))) # from package "readxl" to read in excel file temp<-temp[grep("^geneA$|^geneB$|^geneC$",temp$Id),] # extract rows based on temp$id names(temp)<-gsub("^.*] ","",names(temp)) # clean up column names temp.df<-append(temp.df,...
2018 May 25
0
how to make the code more efficient using lapply
...move that section outside of the loop. It will be executed when the loop finishes. As it is you are calling list.files() each time through the loop which could be slow. In any case here's a possible way to do it. Warning: untested! f <- function(fn) { temp<-read_xlsx(fn,sheet=1,range=cell_cols(c(1,30,38:42))) temp<-temp[temp$Id %in% c("geneA","geneB","geneC"),] } myL <- lapply( X=list.files(), FUN=f ) temp.df.all<-do.call("rbind",myL) names(temp.df.all)<-gsub("^.*] ","",names(temp.df.all)) write_xlsx(temp.df.all, p...
2018 May 25
1
how to make the code more efficient using lapply
...down (though probably not by much). Call it outside the loop, save the results in a vector, and use the vector inside the loop. Here's another way (also untested). infiles <- list.files() nfiles <- length(infiles) ## read the first file dfall <- read_xlsx(infiles[1], sheet=1, range=cell_cols(c(1,30,38:42))) dfall <- dfall[dfall$Id %in% c("geneA","geneB","geneC") , ] ## I'm going to assume the colnames are all the same on input ## if that's wrong, then they have to be fixed inside the loop ## read the remaining files, appending their contents e...