Import multiple data frames CSV - column separation - r

Question

I have a csv file with multiple data frames that are all separated by a column (So 4 columns of data, empty column, 4 columns of data, etc.). Is there a nice way to read in the file and have R create a separate df for each of those contiguous sets of columns? Then I would be able to use lapply across all of these dfs.
Thanks for your help.

Answer 1

Read in the whole csv file, then use lapply to separately capture each four-column data frame into a list. Then use rbind to stack all the data frames into a single data frame.
dat = read.csv("YourFile.csv")
# Set this based on how many separate data frames are in your csv file
num.df = ncol(dat)/5 # Per #zx8754's comment
# This will tell the function the column numbers where
# each data frame starts
start.cols = seq(1, 1 + 5*(num.df-1), 5)
df.list = lapply(start.cols, function(x) {
# Capture the next 4 columns
df = dat[, x:(x+3)]
# Use whatever names are appropriate here. This is just
# to make sure all of the data frames have the same column names
# so that rbind won't throw an error
names(df) = c(paste0("col", 1:4))
return(df)
})
# rbind all the data frames into a single data frame
df = do.call(rbind, df.list)

Answer 2

You can take advantage of colClasses:
Example data:
h1 h2 h3 h1.1 h2.1 h3.1 h1.2 h2.2 h3.2
1 1 6 3 1 8 8 1 5 2
2 2 1 1 6 5 8 1 3 1
3 3 2 6 1 2 3 1 2 5
Then you can loop through the number of dataframes you wan't and read the file:
ngroups <- 3 #number of dataframes to read
datacols <- 3 #number of columns to read
fulldata <- list()
for (i in 1:ngroups) {
nskip <- (datacols+1)*(i-1)
cols.to.read <- c(rep("NULL", nskip), rep(NA, datacols), rep("NULL", (datacols+1)*(ngroups-i+1)-1)) #creates a list of NULLs and NAs. NULLs = don't read, NA = read
fulldata[[i]] <- read.csv("test.csv", colClasses=cols.to.read)
}
Result:
fulldata
[[1]]
h1 h2 h3
1 1 6 3
2 2 1 1
3 3 2 6
[[2]]
h1.1 h2.1 h3.1
1 1 8 8
2 6 5 8
3 1 2 3
[[3]]
h1.2 h2.2 h3.2
1 1 5 2
2 1 3 1
3 1 2 5
This works, but I believe the answers reading the file only once would be faster, since reading the same file over and over again doesn't sound like the optimal procedure.

Answer 3

First read in all your data into one large dataframe:
maindf <- read.table(yourfile)
Lets say n is the number of dataframes inside your csv file:
for (i in 0:n-1){
assign(paste0("df",i+1),maindf[,(1+4*i):(4+4*i)])
}
The result should be n dataframes that can be accessed like this: df1, df2,...dfn.
I didnt test it, because no sample data was provided.