An insightful comment below about “pyper vs rpy2” was made by Dr Xiao-Qin Xia, the developer of pyper. 1) While Rpy2 package and objects has many methods to learn, R interpreter is wrapped as a Python object in PypeR without special methods, that means the user can learn to use PypeR in minutes. 2) While […]
Within Python, there are two packages allowing pythonians to call R functions from a Python program. Below is a comparison between RPY2 and PYPER. The design of this study is very simple: 1) read a 100 by 100,000 data matrix into a pandas DataFrame 2) convert the pandas DataFrame to a R data frame 3) […]
Different from RPy2, PypeR provides another simple way to access R from Python through pipes (http://www.jstatsoft.org/v35/c02/paper). This handy feature enables data analysts to do the data munging with python and the statistical analysis with R by passing objects interactively between two computing systems. Below is a simple demonstration on how to call R within Python […]
SQLite is a light-weight database with zero-configuration. Being fast, reliable, and simple, SQLite is a good choice to store / query large data, e.g. terabytes, and is well supported by both Python and R.
Yet Another Blog in Statistical Computing 