cbind

I am using R to cbind about ~11000 files using: dat <- do.call('bind_cols',lapply(lfiles,read.delim)) which is unbelievably slow. I am using R because my downstream processing like creating plots etc is in R. What are some fast alternatives to concatenating thousands of files by columns? I have three types of files for which I want this done. They look like this: [centos@ip data]$ head C021_0011_001786_tumor_RNASeq.abundance.tsv target_id length eff_length est_counts tpm ENST00000619216.1 68 26.6432 10.9074 5.69241 ENST00000473358.1 712 525.473 0 0 ENST00000469289.1 535 348.721 0 0

Here is the code that I am working with: x <- c("Yes","No","No","Yes","Maybe") y <- t(1:10) z <- t(11:20) rbind.data.frame(ifelse(x == "Yes",y,z)) This produces X1L X12L X13L X4L X15L 1 1 12 13 4 15 The desired outcome is: x 1 Yes 1 2 3 4 5 6 7 8 9 10 2 No 11 12 13 14 15 16 17 18 19 20 3 No 11 12 13 14 15 16 17 18 19 20 4 Yes 1 2 3 4 5 6 7 8 9 10 5 Maybe 11 12 13 14 15 16 17 18 19 20 I was thinking that I could use an ifelse statement with the rbind.data.frame() or cbind.data.frame() function. So if x == "Yes" then that would be combined with a vector "y". As shown in the first row of the

Not sure why this is happening. I have a dataframe df2 with the variables below: EVTYPE TOTAL_FATALITIES TOTAL_INJURIES (fctr) (dbl) (dbl) 1 TORNADO 5633 91346 2 EXCESSIVE HEAT 1903 6525 3 FLASH FLOOD 978 1777 4 HEAT 937 2100 5 LIGHTNING 816 5230 6 TSTM WIND 504 6957 > df2$TOTAL_FATALITIES [1] 5633 1903 978 937 816 504 470 368 248 224 206 204 172 160 133 127 103 101 101 > df2$EVTYPE [1] TORNADO EXCESSIVE HEAT FLASH FLOOD HEAT LIGHTNING [6] TSTM WIND FLOOD RIP CURRENT HIGH WIND AVALANCHE [11] WINTER STORM RIP CURRENTS HEAT WAVE EXTREME COLD THUNDERSTORM WIND [16] HEAVY SNOW STRONG WIND BLIZZARD

#use readtable to create data frames of following unzipped files below x.train <- read.table("UCI HAR Dataset/train/X_train.txt") subject.train <- read.table("UCI HAR Dataset/train/subject_train.txt") y.train <- read.table("UCI HAR Dataset/train/y_train.txt") x.test <- read.table("UCI HAR Dataset/test/X_test.txt") subject.test <- read.table("UCI HAR Dataset/test/subject_test.txt") y.test <- read.table("UCI HAR Dataset/test/y_test.txt") features <- read.table("UCI HAR Dataset/features.txt") activity.labels <- read.table("UCI HAR Dataset/activity_labels.txt") colnames(x.test) <- features[,2]

I have data like the SampleData below, which has lists of different length that I'd like to combine in to a data frame like the Desired Result below. I've tried using lapply and cbind.na from the qpcR package like the example below, but for some reason it won't let me turn the result into a data frame. If I just used two of the lists and cbind.na it will combine them and add the NA to the end like I want, but when I try using it in lapply it just leaves them as a list of different length lists. Any tips are greatly appreciated. SampleData<-list(list(1,2,3),list(1,2),list(3,4,6,7)) Desired

Please forgive me if I missed an answer to such a simple question. I want to use cbind() to bind two columns. One of them is a single entry shorter in length. Can I have R supply an NA for the missing value? The documentation discusses a deparse.level argument but this doesn't seem to be my solution. Further, if I may be so bold, would there also be a quick way to prepend the shorter column with NA 's? Try this: x <- c(1:5) y <- c(4:1) length(y) = length(x) cbind(x,y) x y [1,] 1 4 [2,] 2 3 [3,] 3 2 [4,] 4 1 [5,] 5 NA or this: x <- c(4:1) y <- c(1:5) length(x) = length(y) cbind(x,y) x y [1,] 4