How can I parse CSV data from a character vector to extract a data frame?

Question

The read.table and read.csv functions in R are used to parse a file or URL containing delimited data and produce an R data frame. However, I already have a character vector that contains the CSV delimited data (using comma and \n as column and record delimiters), so I don't need to read it from a file or URL. How can I pass this character vector into read.table, read.csv, or scan() without writing it to a file on disk first and reading it back in? I realize that writing it to disk is possible, but I am looking for a solution that does not require this needless roundtrip and can read data from the character vector directly.

Orford

Answer 1

You can use textConnection() to pass the character vector to read.table(). An example:

x  <- "first,second\nthird,fourth\n"
x1 <- read.table(textConnection(x), sep = ",")
# x1
     V1     V2
1 first second
2 third fourth

Answer found in the R mailing list.

2017 EDIT

Seven years later, I'd probably do it like this:

read.table(text = x, sep = ",")

Splenius

One warning about this approach: textConnection() can be very slow as the number of rows increases. At 223k rows, I'm finding it faster to write to a temporary CSV, and read that in. :( – Decibel

Answer 2

A minor addendum to neilfws's answer. This wrapper function is great for helping answer questions on stackoverflow when the questioner has placed raw data in their question rather than providing a data frame.

textToTable <- function(text, ...)
{
   dfr <- read.table(tc <- textConnection(text), ...)
   close(tc)
   dfr
}

With usage, e.g.

textToTable("first,second\nthird,fourth\n", sep = ",")

Kirimia