R vs Python



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Python and R are both common and powerful language for data science tasks. In this video Martin Keen, Master Inventor, provides an overview of R and Python and what questions you need to be asking before you choosing how to proceed on your next project.

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32 Comments

  1. Just want to mention that R is based on S which was developed initially in the 1970s then rewritten in C in 1988. R came later as an open source project but it would be fair to say that R is older than Python in that sense. 🤓

  2. Well, most people who are learning to program are learning to program, not just to do statistics. Python is up there with C and Java. Those languages trump R in OOP and device optimization. That’s why Python is recommended more, you can do more than just stats and ML with it.

  3. In my personal experience: if you only need to write some short/quick scripts, R may be better, just a little; if you only need to write some long scripts, both R and Python are suitable; if you need to write a real application, R is far behiand Python. I started with R, but gradually switched to Python. The reasons include: more consistent syntax, more friendly packages, faster evoluation. For now, there left only 2 reasons for me to continue using R: 1. ggplot2: much better than its Python alternatives; 2. the "down" series R packages, because I already setup my writing system with them.

  4. That is my big problem, I probably have to use both and that confuses me. I now found out that there is an R plugin in PyCharm. At first glance it works but not as well as RStudio… Or I am too inexperienced.

  5. I didn’t watch, because I don’t need to. Your comparison is off. You can compare R to Pandas, that would make sense. But I couldn’t imagine a world where you convinced me that R could be more value than the entirety of Python. It’s a competitor to one single library.

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