R or Python: Which Should You Learn in 2024?
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- čas přidán 1. 06. 2024
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In this video we're revisiting the R vs Python comparison in the year 2024. How do they stand in recent job reports and in indices like PyPL or the TIOBE index? - Věda a technologie
Both, but I am biased towards R.
Hi I have watched one of your video comparing R and Python a few year ago. At that time, I started learning Python. Then following your advices I learned R (that I really love). I would say that R is prefered for people with a math/stat background. Then I learned Julia and Nim for perfromance. Overall your advice helped me a lot, thank you!
Yes, have to live in both worlds since I am still in school but I have to say I am definitely doing more in Python now that I have been deep diving into ML and AI. The course I am taking in Natural Language Processing is definitely just Python based because of NLTK. Looking forward to your next videos and just keep them coming. Best to you and yours.
The Angry Statistician.
For me the problem with Python was the comp science knowledge that becomes almost mandatory to move forward. Whereas in R, the quality of tutorials and the IDE make it such that you don't need to know a lot of CS knowledge to get the most out of it. I personally believe as a non CS grad python will get surprisingly difficult as you get further along.
Also as for the popularity ratings, Baby shark was the most popular CZcams video doesn't mean everybody should watch it, just meant the kids loved it. So my point is popularity doesn't mean most important. Remember, the world ran just fine before Python came along.
The "popularity" could just be fresh grads searching for tutorials and not mission critical infrastructure.
I have friends who are data scientist and a lot of them us R as well as the college phd students etc. python is like for everyone and everything
For everyone and everything is right!
I'm a newbie of R and I like it. Thanks for the great video.
My university economics program uses R. I learned both for obvious reasons
R is the best
The language is pure liquid shit but unfortunately is a necessity in data science.
asking for comments could boost your visabilty too.
i am not 100% certain, but a lot of youtubers ask for them and so it migth be a booster as well
If you're in healthcare or pharma, the other language to know is SAS. I know, it's old hat, but it has a simple syntax, a rich macro language and it is certified for use in FDA-regulated industries.
I’m a neurobiologist PhD… I’ve been using R for years and I’m aiming to work outside academia, now I’m learning python and isn’t that straight forward to me perhaps due to school bias… but python seems to be the norm outside academia and that’s why I’m trying to learn.
For me the greatest difference between the two languages is the mentality. R users are taught basic programming fundamentals and learn that for every solution there is a package they can use. Python users are taught programming first and how the language is used to create packages. So R users learn to use the language at a higher level, and when they go deeper then things get messy. Also in 2024 I wouldn't keep putting labels such as R for statistics and Python general purpose etc. This kind of labels is absolutely nonsense.
So I’m in a MS business analytics degree, and we had the opportunity to learn R programming. So I learned it, still learning it as we speak and becoming really efficient and effective at it as I go on Kaggle and practice with different types of datasets.
But so many companies are requiring Python. I just came to the conclusion that im not going to overwhelm myself and just stick with R and SQl and just say it is what it is. I’m not Superman out here, and these companies must stop acting like Gods and show some flexibility
For me, my preferred language for data analysis, modeling and plotting is definitely R. But when it comes to web scraping, specifically using selenium, Python is much better
True, Selenium in Python works better than RSelenium. In R I would recommand hayalbaz for web browser automation using Chromote (but rvest will soon have that too). In Python, Playwrights is amazing!
the same video you did last year i think R or Python it depends of the jobs will achieve ..R i think stay alive for longer ...python is everywhere and all the experts use python maybe easy or i dont know open source or something else
Yeah R has a passionate development community and isn’t going anywhere, soon at least.
I'm pretty much an R user but I too would suggest Python to someone new.
But the popularity and usage is also a self fulfilling prophecy. R as said is for statisticians while python includes way more people.
And ChatGPT will only expand this preference as the training model has more examples with Python. It's way easier to obtain an hallucinations for R.
So is R useless ? Hell no, as Richard said it's more entry level and some categories like biostatisticians or doctors will have less issues with R
Also when not doing ML, R is way more "reproducible-friendly" with the tidyverse
A one-time analysis or exploratory analysis is way faster to write
But of course that's from someone using both languages and biased
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Still the message is:
For a general user Python is king
But some people shouldn't dismiss R
It all depends on the work activities
It's also worth adding that R is much better developed in fields of classic statistics and ML as well as econometrics. Thus it very popular (equally or even more than python) in financial fields like f.e. credit risk.
Greta comparison. I'm a pythonista considering jumping to a second language!. Which-one should I choose, R or Julia?
I like Julia but unless you’re specifically doing scientific computing where speed is of the utmost importance, I’d learn R as your second language.
@@RichardOnData Isn't it like Julia has some computation problems? I'm on community's discord and sometimes I see posts about problems with the language itself.
Very objective take. As much as I love R I am seeing myself using Python a lot more. Especially for MLOps. Python is such a nice glue language that you have to use it eventually.
You really do. To me, not being strong in Python is unsustainable in a data science career long term.
r is for data scientists while python is for general like games etc.mugo and data data and mugo
i like R
Julia is the light and the way
R
I wish perl, the regex 👑 king, was still in the race. But, Python is definitely the bigger bang for the kind buck now!
You're evil
Python syntax feels very clunky for getting the job done. R just makes sense, but I have an econometrics background, not cs