R Cookbook

Chapter 4. Input and Output

Introduction

All statistical work begins with data, and most data is stuck inside files and databases. Dealing with input is probably the first step of implementing any significant statistical project.

All statistical work ends with reporting numbers back to a client, even if you are the client. Formatting and producing output is probably the climax of your project.

Casual R users can solve their input problems by using basic functions such as read.csv to read CSV files and read.table to read more complicated, tabular data. They can use print, cat, and format to produce simple reports.

Users with heavy-duty input/output (I/O) needs are strongly encouraged to read the R Data Import/Export guide, available on CRAN at http://cran.r-project.org/doc/manuals/R-data.pdf. This manual includes important information on reading data from sources such as spreadsheets, binary files, other statistical systems, and relational databases.

A Philosophical Note

Several of my Statistical Analysis System (SAS) friends are disappointed with the input facilities of R. They point out that SAS has an elaborate set of commands for reading and parsing input files in many formats. R does not, and this leads them to conclude that R is not ready for real work. After all, if it can’t read your data, what good is it?

I think they do not understand the design philosophy behind R, which is based on a statistical package called S. The authors of S worked at Bell Labs and were steeped in the Unix ...