Reading Data in R

Here we will discuss about reading and writing data in R. For reading, (importing) data into R following are some functions.

• read.table(), and read.csv(), for reading tabular data
• readLines() for reading lines of a text file
• source() for reading in R code files (inverse of dump)
• dget() for reading in R code files (inverse of dput)
• load() for reading in saved workspaces.

Writing Data to files

Following are few functions for writing (exporting) data to files.

• write.table(), and write.csv() exports data to wider range of file format including csv and tab-delimited.
• writeLines() write text lines to a text-mode connection.
• dump() takes a vector of names of R objects and produces text representations of the objects on a file (or connection). A dump file can usually be sourced into another R session.
• dput() writes an ASCII text representation of an R object to a file (or connection) or uses one to recreate the object.
• save() writes an external representation of R objects to the specified file.

Reading data files with read.table()

The read.table() function is one of the most commonly used functions for reading data into R. It has a few important arguments.

• file, the name of a file, or a connection
• header, logical indicating if the file has a header line
• sep, a string indicating how the columns are separated
• colClasses, a character vector indicating the class of each column in the data set
• nrows, the number of rows in the dataset
• comment.char, a character string indicating the comment character
• skip, the number of lines to skip from the beginning
• stringsAsFactors, should character variables be coded as factors?

read.table() and read.csv() Examples

data <-read.table("foo.txt")
data <-read.table("D:\\datafiles\\mydata.txt")
data <-read.csv("D:\\datafiles\\mydata.csv")

R will automatically skip lines that begin with a #, figure out how many rows there are (and how much memory needs to be allocated). R also figure out what type of variable is in each column of the table.

Writing data files with write.table()

Following are few important arguments usually used in write.table() function.

• x, the object to be written, typically a data frame
• file, the name of the file which the data are to be written to
• sep, the field separator string
• col.names, a logical value indicating whether the column names of x are to be written along with x, or a character vector of column names to be written
• row.names, a logical value indicating whether the row names of x are to be written along with x, or a character vector of row names to be written
• na, the string to use for missing values in the data

write.table() and write.csv() Examples

x <- data.frame(a = 5, b = 10, c = pi)
write.table(x, file = "data.csv", sep = ",")
write.table(x, "c:\\mydata.txt", sep = "\t")
write.csv(x, file = "data.csv")

Read more about importing and exporting data in R