There is more to open source statistics than R and other things your Professor never told you
There is a disturbing trend I see in members of R Community particularly in its evangelical wing, in claiming R is the panacea and cure for all things statistical. No one software can and will be able to handle all the parts of the data analytics pipeline equally well, there will always be trade-offs based on perceptual assessments of both current needs and future trends.
While an employee of a proprietary software company can and will always claim that his software is the best and fastest for everything, what has happened over the past few years is that analytics open source software people have been neatly split into Pythonistas and R Users.
This is a disturbing trend. Rather than mimick and copy libraries and packages between R and Python, there should be a movement for greater inter-operability and transparency in cross training. Why cant you teach Pandas in a R Meetup and Why cant you learn ggplot2 in a Python meetup.
United we stand and both R and Python communities will gain. Divided, the opponents of open source will end up appropriating the work of the community and laugh all the way to the bank.
More R and More Python. Like Rum with Cola. Not Seperately, but together. Is that a pipe dream, or will that benefit industry? I would love to see atleast one big startup making products and services in both!
DECISION STATS 