Importing data into R is fairly simple. For Stata and Systat, use the foreign package. For SPSS and SAS I would recommend the Hmisc package for ease and functionality. See the Quick-R section on packages, for information on obtaining and installing the these packages. Example of importing data are provided below.
From A Comma Delimited Text File
# first row contains variable names, comma is separator # assign the variable id to row names # note the / instead of \ on mswindows systems mydata <- read.table("c:/mydata.csv", header=TRUE, sep=",", row.names="id")
(To practice importing a csv file, try this exercise.)
One of the best ways to read an Excel file is to export it to a comma delimited file and import it using the method above. Alternatively you can use the xlsx package to access Excel files. The first row should contain variable/column names.
# read in the first worksheet from the workbook myexcel.xlsx # first row contains variable names library(xlsx) mydata <- read.xlsx("c:/myexcel.xlsx", 1) # read in the worksheet named mysheet mydata <- read.xlsx("c:/myexcel.xlsx", sheetName = "mysheet")
(To practice, try this exercise on importing an Excel worksheet into R.)
# save SPSS dataset in trasport format get file='c:\mydata.sav'. export outfile='c:\mydata.por'. # in R library(Hmisc) mydata <- spss.get("c:/mydata.por", use.value.labels=TRUE) # last option converts value labels to R factors
(To practice importing SPSS data with the foreign package, try this exercise.)
# save SAS dataset in trasport format libname out xport 'c:/mydata.xpt'; data out.mydata; set sasuser.mydata; run; # in R library(Hmisc) mydata <- sasxport.get("c:/mydata.xpt") # character variables are converted to R factors
# input Stata file library(foreign) mydata <- read.dta("c:/mydata.dta")
(To practice importing Stata data with the foreign package, try this exercise.)
# input Systat file library(foreign) mydata <- read.systat("c:/mydata.dta")
Try this interactive course: Importing Data in R (Part 1), to work with csv and xlsx files in R. To work with SAS, Stata, and other formats try Part 2.