Python vs. R

Which is better for Data Science?

...

>Data Science

I love this meme.

So R is not a performance language, but it does have a shitlord of packages for data analysis and machine learning, I believe this makes it more powerful than python

>air jerk off motion

UHH DATA UHH IT'S SO BIG


Literally a gay field

pandas, numpy, scipy, and sklearn have more functionality than R

>Data Science
what the fuck are you even talking about?

R is worse because it looks like complete shit and gives me a headache to behold.

matlab

>1 indexed arrays

>ctrl+F
>Julia
>no results

I gotta say R gives me a hardon too often. Once you get past its brain-numbing basic design, it's really rather nice to use to turn raw data into easy to read results.

Bioinformatic fag here.

>Bioinformatic fag here.
Where? I'm still at uni in a yuropoor country and soonish I have to decide to specialize in something. The two areas I'm interested in is bioinformatics and fault tolerant systems/formal verification etc.
Money and jobbs are no porblem with the later, ont he other hand bioinformatics has the sense of doing something good.
How hard would you think it'd be to get e job doing bioinf if I decided that academia isn't for me?

Python.

Data science is just software engineering that uses machine learning/statistics. Python is much more useful.

Python for tech companies, R/SAS for finance and healthcare

Improving, maintaining and observing data collecting algorithms. It's not some meme buzzword like claims. It has existed for years.

>doing "data science" in julia
>implying your aren't just importing python packages

pmsl

Go away, this is Veeky Forums we do not want logic here.

I usually use Python to gather / manage / prepare the data and then use R to analyze it. Ggplot is just to awesome not to use it

they're the same shit

came here to say this
why would I use an inferior language?

...

gave up on using ggplot once I got JMP.

R arrays are indexed by 1 as well, nigger

Depends, Astros use both, but probably R more often
Most people in my field still use IDL/GDL just because of maturity
Honestly it doesn't really matter
I did find Python a little easier starting off if that matters to you

come back when julia is stable

R for data analysis/exploration, Python for larger scale programming projects.

Fortran and Mathematica as well.

Friendly reminder that R stands for Retarded.

Not that user but fault tolerant systems are sweet, or at least in EE

no, it IS a buzzword. you're literally just doing statistics and maybe a teeny tiny bit of database management.

They're both fine. Use whichever language has the packages you need.

if so then engineering is also a buzzword

In my graduate work I've been using both. The official language of my lab is Py3, but I use R to quickly look at my data and run tests. If it looks good, I'll import it into Python and analyze as necessary.

t. Physics grad student

It's just referring to a specific manner in which those things are used. Why would you want to use a sentence to explain what two words can?

I only have Python under my belt. Should I learn R still? I've been told Python is taking over quickly and on job qualifications I always see
>Python preferred

Python is always going to be a better choice for proper programming tasks, but for data exploration and analysis you still can't beat R, I think. The data structures, data transformation functions, and conventions of indexing are all designed around making data analysis as easy as they can be.

Don't think of R as a programming language (even though it completely is). If you want a programming language, use Python.

it doesn't matter just get good at something

woulf be helpful if you typed what kind of bioinformatics youre interested in. Genomicd? Population genetics? Structural bioinformatics?

If you're not using Spark Scala you've already lost

>R + Python = $115,531 + $94,139 = ...
...= $209,670

why not both?

Engineering has always been a buzzword.

sh,c

anything other than R.