Data Science Wars: R vs. Python

The great team over at DataCamp, an online site for learning R , has put together another wonderful infographic. This time, the topic is Data Science Wars (R versus Python). This has been a rather hot topic for quite some time. I even wrote about the debate back in 2013, R vs Python, The Great Debate.

DataCamp did an amazing job packing information into the infographic. Honestly, it is impressive they were able to pack so much information into a single infographic. Some of the topics covered are:

  • History
  • Who uses the language?
  • Community
  • Purpose of the language
  • Popularity
  • And way more great stuff

Enough about the description. Have a look for yourself. It is packed with great arguments for your next “R vs Python” debate.

R vs Python for data analysis
R vs Python for data analysis

About Ryan Swanstrom

Creator of Data Science 101

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14 Comments on “Data Science Wars: R vs. Python”

  1. R has a brighter future. In addition to data science/machine learning scenarios, Microsoft has planed to fully integrate R into Azure Cloud Computing as well as SQL Server 2016.

  2. For me, they are complementary. Process data in Python and explore it in R. R is best suited for interactive, statistical exploration, and in this respect, is currently nicer than available Python tools. Python is more elegant for almost everything else… more as a general tool. Obviously, both can do either things. Ultimately, it is about the available libraries and the communities, more than the languages.

  3. I like the graphic. I complety disagree on why people choose one other the other. There r at least 3 types of data scientists. The back end strong programmer who knows something about DS and ports tools to Java. The statistidcian who is much less of a programmer who has use of R’s more advanced optimizations and s typical marketing type DS who does a littles of everything, including writing complex programs and lubraries for deployment as well as the teams shared use. Theres only one choice for that person, Python.

    1. Thanks for the comment, Daniel. I agree. Different data scientists do different things; thus, a different tool is needed. I think the main point of the infographic is the positives of each one. Both R and Python are great, and which to use depends upon the task at hand.


  4. A large proportion of the youngest generations these days learn python as a first language.
    The older generations who have specific tasks may prefer R.

    1. Yes, python has become the most popular language taught in computer science departments. However, I do not know of any math or statistics departments that use python. They all use R, or some other math programming language like Matlab. Therefore, I think the first language learned might depend upon the background of the person.

      Thanks for commenting Yau,

  5. For people new to the field of Data Science it can become quite confusing to decide which language they should learn , some of the top choices are Python and R and this article does a really great job at comparing them both. We believe that both have a bright future.

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