Data Import

It is necessary to import the sample textbook data into R before you start working on your homework.

Excel File

Quite often, the sample data is in Excel format, and needs to be imported into R prior to use. For this, we use the read.xls function from the gdata package. It reads from an Excel spreadsheet and returns a data frame. The following shows how to load an Excel spreadsheet named "mydata.xls". As the package is not in the core R library, it has to be installed and loaded into the R workspace.

> library(gdata)                   # load the gdata package
> help(read.xls)                   # documentation
> mydata = read.xls("mydata.xls")  # read from first sheet

Minitab File

If the data file is in Minitab Portable Worksheet format, it can be opened with the read.mtp function from the foreign package. It returns a list of components in the Minitab worksheet.

> library(foreign)                 # load the foreign package
> help(read.mtp)                   # documentation
> mydata = read.mtp("mydata.mtp")  # read from .mtp file

SPSS File

For the data files in SPSS format, it can be opened with the read.spss function from the foreign package. There is a "to.data.frame" option for choosing whether a data frame is to be returned.

> library(foreign) # load the foreign package
> help(read.spss) # documentation
> mydata = read.spss("myfile", to.data.frame=TRUE)

Table File

A data table can resides in a text file. The cells inside the table are separated by blank characters. Here is an example of a table with 4 rows and 3 columns.

100   a1   b1
200   a2   b2
300   a3   b3
400   a4   b4

Now copy and paste the table above in a file named "mydata.txt" with a text editor. Then load the data into the workspace with the read.table function.

> mydata = read.table("mydata.txt")  # read text file
> mydata                             # print data frame
   V1 V2 V3
1 100 a1 b1
2 200 a2 b2
3 300 a3 b3
4 400 a4 b4

For further detail of the read.table function, please consult the R documentation.

> help(read.table)

CSV File

The sample data can also be in comma separated values (CSV) format. Each cell inside such data file is separated by a special character, which usually is a comma, although other characters can be used as well.

The first row of the data file should contain the column names instead of the actual data. Here is a sample of the expected format.

Col1,Col2,Col3
100,a1,b1
200,a2,b2
300,a3,b3

After we copy and paste the data above in a file named "mydata.csv" with a text editor, we can read the data with the read.csv function.

> mydata = read.csv("mydata.csv")  # read csv file
> mydata                           # print data frame
  Col1 Col2 Col3
1  100   a1   b1
2  200   a2   b2
3  300   a3   b3

In various European locales, as the comma character serves as decimal point, the read.csv2 function should be used instead. For further detail of the read.csv and read.csv2 functions, please consult the R documentation.

> help(read.csv)

Working Directory

Finally, the code samples above assume the data files are located in the R working directory, which can be found with the getwd() function.

> getwd() # get the current working directory

You can select a different working directory with the setwd() function, and avoid entering the full path of the data files.

> setwd("<new path>") # set the working directory to "<new path>"

The forward slash should be used as the path separator even on Windows platform.

> setwd("C:/MyDoc") # set the working directory to "C:\MyDoc"

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An R Introduction to Statistics