Python vs. R comparison (by a die-hard Python fan)
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- Опубликовано: 22 авг 2024
- Which programming language is better for machine learning; Python or R? I don't think there is a black and white sort of answer to this questions. Depending on what you want to do, which programming language you should use will change. At the end of the day, these languages are tools.
I, personally, use Python most, if not all, of the time. I dabbled with R at some point during college but cannot say I'm an expert on it. Don't get in the Python or R hating bandwagon though. As tempting as it might be. You might need them one day!
Judging by the resources online and what both language's strengths are, here is a quick comparison for you.
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Good video but as an analyst who uses both languages I have to say that R is built for Data Science/Data Analysis (it´s not just a statistically focused language - Tidyverse is better than anything Python has to offer) especially Time Series where R blows Python out of the water. In general if I want to do any kind of stand alone analysis (data cleaning, analysis & visualization) I go with R. If I want to do machine learning/web scraping/build an analytical application/complex data pipelines I go with Python.
Absolutely agree, Tidyverse is cool 😎
I agree with you, Tidyverse just makes the whole process of data cleaning and analysis much easier and intuitive.
R has a data wrangling and visualization framework called Tidyverse which is better than python libraries such as pandas , polars, matplotlib and seaborn. When it comes for machine learning in my opinion both languages have comparable framework/libraries , with 'R Tidymodels performing as well as scikit-learn on python additionally for time series (statistical models ) there is no room that python is better than R
Eventually i am not going to talk about deep learning because when you meet people you realize that the most of us still working with tabular data and traditional machine learning
One crucial advantage of R is that it is been used by researchers. If you want to use a very special kind of a ML algorithm that was established in a relatively unknown paper there is no way somebody implemented it in a Python module. However the authors of the paper themselves probably coded it and publsihed a R lib. So if you want to keep up with scientific literature and use them in your own work R is the way to go.
Noooo, you forgot to look at Tidymodels in the Machine Learning comparison section. It has really changed the game for ML in R.
Oh no :( Disadvantages of not being an R person. I'll look into it! Thank you. :)
@@misraturp I'm only recently picking up more Python and am all for sharing between the communities as they both have a lot of strengths.
yeah, caret is quite old now. The guy who created it, Max Kuhn, is one of the folks working on Tidymodels, which has been round for maybe 5 years or so at this point.
I have been using Python for a while and heard of R but now I'm intrigued with what it offers for statistic analysis. Will look into R. Thank you very much for this video
Best of luck!
Another big advantage of Python is that you are one it's instructors...❤❤❤❤❤❤❤❤❤❤
You are so kind
I'm using both, but R seems to be more difficult to learn for me, I sill don't know why...
I feel more confortable using Python and Jupyter.
Thank you so much for the good comparison! Video of this quality are rare!
Like some people said, Python is production oriented and R research oriented (but you could do both with Python or R). In the end, one get a big advantage learning both. I think Python visualization is slowly catching up with R (even if the gap remain). There are also other libraries for machine/deep learning in R (tidymodels and torch/keras for instance), but they are not as mature as those from Python as you said.
Thank you again!
Glad you enjoyed it!
Hey Misra, I prefer python as well 🤗 Thank you so much for your great content, you helped me so much with your videos already and I love the way you explain things!! 🥰
Happy to hear that! Thank you :)
I prefer R
thanks for the comparison! didn't know that the ggplot2 in R is one of the best visualization libaries available. maybe I should learn R in the future but will keep using Python for the moment
Go for it!
Hi Misra, thanks for your summary. I came to Python via R. For complex visualizations I use R and HTML( Knit) exports. However, a good alternative for Python that I have been using for 2 weeks is Datalore...
Thanks for sharing!
Great video, look into the Tidymodels framework, it is becoming increasingly famous for ML, and it builds on the Tidyverse syntax and logic.
Thank you for the awesome videos.
Which is better for DataViz, GGplot2 or Origin?
R at the beginning was very simple to write and understand.
R was similar to other programming languages (Python, Matlab...).
Unfortunately Hadley Wickham and the Rstudio team destroyed this simplicity by adding the %>%, |> pipe (supposedly for compact code) and the tidyverse, tibble ...
I also thought like you, force yourself to write with pipes one day and you will never give them up again
although i would love it if you could talk about microframeworks like cherrpy for a guy who wants to make basi food ordering apps with this
R is best
None of these. I will use x86 Assembly language for my next project since it is easy to use.
Awesome!
🤦🏻
haha. Yeah, it might take forever to write, but when it's done, it will be blazingly fast!
exactly what i was looking for...and i am learning streamlit cherrypy and flask python framework
Flask 👍🏻
@@bay-bicerdover everyone says if you dont use django ..you end up building django
Good one
Thanks!
I love Python ❤