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Comment by minimaxir | Hacker News Reader

Ugh, not again.

R is good for tabular data and Python is good for text/image/nontabular data. And there's nothing wrong with knowing and using both languages.

Likewise, the world will not end if you use Python pandas for tabular manipulation or various bespoke R packages for nontabular manipulatition.

This isn't the battle that people should be fighting. It's not even a religious argument like web development stacks where a language can eek out better benchmarks. And as others note, this very article concludes that they both have their advantages.

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> Ugh, not again.

No kidding. If you want to be a "data scientist" (whatever that means), it's good to have a scripting language (Perl, Python, Ruby), a math language (Matlab/Octave, R), and a fast language (probably C). You can torture any one of these to fill the others' roles, but usually it's easier to use the best tool for each job.

There is no way you need to know matlab or R to be a data scientist if you already know Python

"Need to know" might be a stretch but you should be familiar with it.

There's several times I've come across something in R or Matlab that I want to do in Python, and it's easier to port over code/processes if you have an awareness.

I'm a thousand times better at Python then R/Matlab but being familiar with them has helped me a lot.

Since this is a data scientist thread, n=1

You will be a better data scientist if you spend some time exploring the extensive R documentation and lots and lots of real life examples.

On the other hand R and Python (not to forget Latex) are easy to connect so there is not need to choose only one of them. You can call R from Lisp also of course.

>R is good for tabular data and Python is good for text/image/nontabular data.

Everyone I know who's used both prefers Pandas to R for tabular data.

More specifically, tidyverse/dplyr > pandas, in my opinion. Base R manipulation is not good.

It's a matter of taste. I prefer base R over tidyverse.

Let me guess you work in finance

Doesn't pandas allow Python to process tabular data like a champ?

At the risk of ironically causing another religious framework war, I never said pandas was bad/inadequate for tabular data, but R/tidyverse has its perks in that area.

Yes.

This attitude is common for people who only want to learn ONE way of doing things. They buy the illusion that there is a silver bullet for all computing (or data analysis) tasks. In fact computing is the art of using the right tools and languages to solve particular problems.

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