Read multiple CSV files into separate data frames

Suppose we have files file1.csv, file2.csv, ... , and file100.csv in directory C:\R\Data and we want to read them all into separate data frames (e.g. file1, file2, ... , and file100).

The reason for this is that, despite having similar names they have different file structures, so it is not that useful to have them in a list.

I could use lapply but that returns a single list containing 100 data frames. Instead I want these data frames in the Global Environment.

How do I read multiple files directly into the global environment? Or, alternatively, How do I unpack the contents of a list of data frames into it?

Thank you all for replying.

For completeness here is my final answer for loading any number of (tab) delimited files, in this case with 6 columns of data each where column 1 is characters, 2 is factor, and remainder numeric:

##Read files named xyz1111.csv, xyz2222.csv, etc.
filenames <- list.files(path="../Data/original_data",
    pattern="xyz+.*csv")

##Create list of data frame names without the ".csv" part 
names <-substr(filenames,1,7)

###Load all files
for(i in names){
    filepath <- file.path("../Data/original_data/",paste(i,".csv",sep=""))
    assign(i, read.delim(filepath,
    colClasses=c("character","factor",rep("numeric",4)),
    sep = "\t"))
}

Quick draft, untested:

1. Use list.files() aka dir() to dynamically generate your list of files.

2. This returns a vector, just run along the vector in a for loop.

3. Read the i-th file, then use assign() to place the content into a new variable file_i

That should do the trick for you.