#!/usr/local/bin/R # Xavier Fernández i Marín # February 2007 # http://xavier-fim.net # This script is only an example of the way we can import and export data with R ### Import and export of data from text files (ASCII, txt, csv) # First, create some artificial data to export data.to.export <- data.frame(a=rnorm(10), b=rnorm(10, 3), row.names=1:10) # Export the table to be used with spreadsheets or other programs write.table(data.to.export, file="file.csv", sep=";") # To import again this data, simply use read.table(file="file.csv", sep=";") # Or, if you want to put it in a data.frame called 'data' data <- read.table(file="file.csv", sep=";") ### From spreadsheets (like OpenOffice Calc, Microsoft Excel, etc...) # save the sheet as .csv or 'comma separated values' and remember with # character you have used to separate columns (variables) # Supose that the file is 'file.csv'. # The next example will work to import file called 'file.csv', which is a text # file that uses ';' to separate columns, and its first row is the header. data <- read.table("file.csv", sep=";", header=T) ### From other statistical software # To import (and, in some cases, export) data with other statistical packages # such are SPSS, Stata, SAS, we have to load the package called 'foreign'. As # it does not come with the standard installation we will have to install it # before we can continue library(foreign) help(package="foreign") # to see what the options of 'foreign' are # Next command reads the file 'file_in_spss_format.sav' into a data frame that # will be called 'data.from.spss'. data.from.spss <- read.spss("file.sav", to.data.frame=T) # Next command reads the file 'file_in_stata_format.dta' into a data frame that # will be called 'data.from.stata'. data.from.stata <- read.dta("file.dta") # Next command will create a stata file called 'file_in_stata_format.dta' with # the contents of our data frame called 'data'. write.dta(data, file="file_in_stata_format.dta")