Best Languages for Data Science and Statistics in One Picture

Hundreds of programming languages dominate the data science and statistics market: Python, R, SAS and SQL are standouts. If you're looking to branch out and add a new programming language to your skill set, which one should you learn? This one picture breaks down the differences between the four languages.


Below are more resources for specific languages, including comparisons between languages, and same algorithms illustrated in different languages.

To quickly learn these languages or refresh your skills, check out our cheat sheets.

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Comment by Elina Fransis 3 hours ago

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Comment by learnbay .co on November 14, 2021 at 7:41pm

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Comment by Elina Fransis on November 11, 2021 at 4:03am

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Comment by João Pires on January 31, 2020 at 12:24am

I must confess that I don't agree totally with the info at the image.

Mostly if you're working with large datasets ... there are other options, like NoSQL DB's.

Despite that, the SQL means what? MS SQL? In this case, where are the other ones like Postgres, Oracle, MySQL ... that are heavyweights on the market?

Comment by Stephanie Glen on January 30, 2020 at 6:11am

Thanks for that correction, Jonathan. I've updated the image to reflect both open and closed source versions are available.

Comment by Jonathan Woodard on January 29, 2020 at 10:55am

The "SQL" in the table seems to refer to Microsoft SQL Server. The SQL language is an ISO standard with both closed and open source implementations, not just SQL Server. It's like R in that you can find both paid and free products for it.

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