Hi:

An alternative approach with a few less keystrokes, using the plyr package:

library(plyr)

# Create some example data files, populate them and write them out using
write.csv:
fnames <- c(paste('file0', 1:9, '.csv', sep = ''))
for(i in seq_along(fnames)) {
     d <- data.frame(x = rnorm(3), y = rpois(3, 10), z = round(runif(3), 3))
     write.csv(d, fnames[i], row.names = FALSE, quote = FALSE)
   }

This generates files file01.csv -> file09.csv. Each file has three lines
with three variables. Now use ldply to read them back in using read.csv():

u <- ldply(fnames, read.csv)
> u
             x  y     z
1  -0.77367688 17 0.496
2  -0.79069791 11 0.323
3   0.69257133  9 0.229
4   0.55484202 14 0.428
5  -0.67254503  4 0.702
6   0.15010483 10 0.802
...  [27 lines in all]

ldply() is one way to circumvent the do.call(rbind, lapply(...)) mantra when
the final output is to be a data frame.

HTH,
Dennis

On Fri, Oct 8, 2010 at 8:30 AM, Joshua Wiley <jwiley.psych@gmail.com> wrote:

> Hi Xinli,
>
> You will probable have to tweak this some for it to work for you, but
> it at least gives you an idea.
>
> First put all your files in one directory, then you use the
> list.files() function to read into R the names of every file in that
> directory (this is easier than typing all 100 something names).  Now,
> you can use lapply() to 'apply' the function, read.csv() to each file
> name.  In my example, I set header = TRUE just to show you how you can
> specify arguments to the function you are calling with lapply().  This
> will result in a list with each element being the results of
> read.csv().  Finally, since all the columns are the same, we can just
> rbind() every data frame together.  That is accomplished the outer
> function, do.call(), whose first argument is "rbind" and second is the
> output of lapply().
>
> filenames <- list.files(path = "~/")
> do.call("rbind", lapply(filenames, read.csv, header = TRUE))
>
> Hope that helps,
>
> Josh
>
> On Fri, Oct 8, 2010 at 4:32 AM, XINLI LI <lihawaii@gmail.com> wrote:
> > Hi Joshua:
> >
> >     Thank you very much for your help. I have more than 100 files, and do
> > you have a better way to merge the files into one dataset, there all have
> > the same columns.
> >
> >    Thanks,
> >
> >    xinli
> >
> > On Thu, Oct 7, 2010 at 11:28 PM, Joshua Wiley <jwiley.psych@gmail.com>
> > wrote:
> >>
> >> Hi Xing,
> >>
> >> This depends somewhat on what you mean by "merge", and how many files
> >> you are talking about.  Supposing you are dealing with few enough
> >> files you can do it manually:
> >>
> >> dat1 <- read.csv("yourfile1.csv")
> >> dat2 <- read.csv("yourfile2.csv")
> >> ...
> >> datn <- read.csv("yourfilen.csv")
> >>
> >> If each file contains unique variables:
> >>
> >> complete.dat <- cbind(dat1, dat2, ... , datn)
> >>
> >> if each one is just a continuation rowise:
> >>
> >> complete.dat <- rbind(dat1, dat2, ... , datn)
> >>
> >> If they are all sort of related but in no consistent way, and do not
> need
> >> to be:
> >>
> >> complete.dat <- list(dat1, dat2, ... , datn)
> >>
> >> If you need some fancier merging than just columnwise or rowwise, look
> >> at merge().  For documentation on these features see:
> >>
> >> ?data.frame # to find out more about data frames (which is what read.csv
> >> uses)
> >> ?list # for details about what a list is
> >> ?read.table
> >> ?read.csv # just a special wrapper for read.table
> >> ?cbind # for column binding
> >> ?rbind # for row binding
> >> ?merge # for more specialized merging
> >> example(merge) # for examples using merge()
> >>
> >> HTH,
> >>
> >> Josh
> >>
> >> On Thu, Oct 7, 2010 at 8:19 PM, XINLI LI <lihawaii@gmail.com> wrote:
> >> > Dear R Group:
> >> >
> >> >    How to import multiple csv files and merge into one dataset.
> >> >
> >> > Thanks and Regards,
> >> >
> >> >   Xing
> >> >
> >> >        [[alternative HTML version deleted]]
> >> >
> >> > ______________________________________________
> >> > R-help@r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-help
> >> > PLEASE do read the posting guide
> >> > http://www.R-project.org/posting-guide.html
> >> > and provide commented, minimal, self-contained, reproducible code.
> >> >
> >>
> >>
> >>
> >> --
> >> Joshua Wiley
> >> Ph.D. Student, Health Psychology
> >> University of California, Los Angeles
> >> http://www.joshuawiley.com/
> >
> >
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> University of California, Los Angeles
> http://www.joshuawiley.com/
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

	[[alternative HTML version deleted]]

