Book Image

Mastering Data analysis with R

By : Gergely Daróczi
Book Image

Mastering Data analysis with R

By: Gergely Daróczi

Overview of this book

Table of Contents (19 chapters)
Mastering Data Analysis with R
Credits
www.PacktPub.com
Preface

Importing data from other statistical systems


In a recent academic project, where my task was to implement some financial models in R, I got the demo dataset to be analyzed as Stata dta files. Working as a contractor at the university, without access to any Stata installations, it might have been problematic to read the binary file format of another statistical software, but as the dta file format is documented and the specification is publicly available at http://www.stata.com/help.cgi?dta, some members of the Core R Team have already implemented an R parser in the form of the read.dta function in the foreign package.

To this end, loading (and often writing) Stata—or for example SPSS, SAS, Weka, Minitab, Octave, or dBase files—just cannot be easier in R. Please see the complete list of supported file formats and examples in the package documentation or in the R Data Import/Export manual: http://cran.r-project.org/doc/manuals/r-release/R-data.html#Importing-from-other-statistical-systems.