Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
[test by reto]
Authors: Xiao-Qin Xia, Michael McClelland, Yipeng Wang
Title: PypeR, A Python Package for Using R in Python
Abstract: This article describes PypeR, a Python package which allows the R language to be called in Python using the pipe communication method. By running R through pipe, the Python program gains flexibility in sub-process controls, memory control, and portability across popular operating system platforms, including Windows, GNU Linux and Mac OS X. PypeR can be downloaded at http://rinpy.sourceforge.net/.

Page views:: 17799. Submitted: 2009-10-23. Published: 2010-07-30.
Paper: PypeR, A Python Package for Using R in Python     Download PDF (Downloads: 27802)
Supplements:
PypeR-1.0.tar.gz: Python source package Download (Downloads: 1366; 8KB)
v35c02-examples.py.zip: v35c02-examples.py: Python example code from the paper Download (Downloads: 1440; 1KB)
v35c02-pyper.py.zip: v35c02-pyper.py: Python example code for Table 1 (PypeR) Download (Downloads: 1379; 748B)
v35c02-rpy.py.zip: v35c02-rpy.py: Python example code for Table 1 (RPy) Download (Downloads: 1299; 735B)
v35c02-rpy2.py.zip: v35c02-rpy2.py: Python example code for Table 1 (RPy2) Download (Downloads: 1333; 745B)
DOI: 10.18637/jss.v035.c02

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.