4 Answers
+ 6
Everyone will stick to his own, I guess. Both have similar machine learning and algorithms capabilities, both enjoy vast community of data-related people and powerful libraries.
R has a more statistical approach to data science, while Python a more programming one. But you can still order pizza with a script in R or make advanced statistical analysis in Python, so... ;)
Your call.
+ 6
Today at packtpub they give away "Python Data Analysis", an extensive compendium of data science-related powers of Python.
Downloading *highly* recommended:
https://www.packtpub.com/packt/offers/free-learning
+ 5
It's really a matter of preference. You won't go wrong with either one and both benefit grom being open source and having great communities . R is great for statistics and research, but Python has wider applications.
Are you primarily interested in statistics or research, doing standalone data analysis? Do you want to get into data science easily right away, with great visualization and other tools, even if it's not terribly efficient? Then go with R.
Are you interested in integrating data science with your work or hobby, applying the statistical and analytical techniques to development? Would you rather learn a language that is flexible and elegant, serving you in diferent ways during the project and well beyond, despite knowing it's still catching up (but fast) when it comes to data science packages? Choose Python.
My personl choice would be Python. I'm a little biased because I already use and love it (it was my first progmming laguage, and itÀs more useful to me now than eve3r), but I haven't learned data science yet. Generally, a (practically) single-purpose language just isn't as efficient. But I'd love to hear what people have to say about R!
0
Owo. smart example #Kuba. Thanks