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Why would you (not) choose R over Python for Data Science?

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  • 3
    tidyverse, RStudio and native data frames.
  • 4
    Because Python is a well-thought-out language
  • 2
    Because often I have to embed analyses into existing python applications. The choice is actually quite obvious then ;)
  • 5
    Python is generic, people know it, and it works well enough. R is specialised, fewer people know it, it works *very* well at what it does, but for most of us the significant additional time to learn it just isn't worth the advantages it brings.
  • 2
    Python is general purpose.
    R is generally used by researchers or people looking to do only analysis

    Python is good for when you want to build an application or a system.

    R is good for data exploration and research.
  • 2
    Depends on what kind of data you're working with. A one-off standard dataset means I'll use python/pandas/numpy because its quick and painless, but if i need to continuously process big data, I'm going R. It's faster with larger datasets and with more transformations.
  • 1
    I actually like R.
    I can say that I find it nice and fun for extracting the most out of a data set.
    I used it to help my job, but never as the core of my job because:
    a) I am not doing a data analysis based job
    b) I find it quite hard to program a complex yet clean code for big programs
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