R vs Python 

I know, you would not believe how much practice it requires. [j/k] Search on "lightboard videos".

@@IBMTechnology just write normal and mirror the video in post. wouldn't it work that way?

They were just trying

I’m just Going by😮🙃 Oops sorry 2:18

Only time will tell if investing Julia is worthwhile. For now it is an interesting prospect with unclear future. It is great if it does exactly what you need now or as a hobby.

What a nice video to be like and share.

Yes, he's Martin Keen, IBMer and "The Homebrew Challenge" dude.

dayumm bro, fr, I went back and had a look, ong bro, he can fr go viral istg

He looks more like Ole Gunnar Solskjaer honestly. Super sub that comes in and scores (explains something so easily to me) after a dull goalless game with nothing significant (me spending days stuck being confused).

🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣🤣i was like, where have i seen this face before...seeing this comment made me realize where

Pandas is a disaster. I don't know how it could become an industry standard. Sadly it's very obvious the creators of the video have no direct experience with these tools. Not only missing numpy's name, but saying things like "Python supports csv and json while R support xls" or "Python is good for data wrangling thanks to pandas, while R is good in statistical analysis" -- these are simply not true, absolutely misleading.

@@ultrasoft5555 so which one is best according to you? python or R

​@@ultrasoft5555 this is definitely not misleading, Python can actually read json and csv files, web developer's usually use json files, even those using Django use json files. And the pandas library has functions that enable reading csv, I think it's called read_csv or something like that. And that guy literally explained what numpty is, that was intentional.

@@MKgobe the idea that python “ONLY” supports those is the problem. Python can read any file format under the sun (specific packages for everything from xlsx to avro, parquet etc ) I am pretty sure python supports more formats simply because it is multi purpose. Also - in visualization, the guy has probably never seen libraries like plotly, seaborn etc. Hec, even a package that copies ggplot2 exists in python.

@@MrPrabhatRastogi I recently switched to python from R. I'm by no means an expert, but the fact that he said if you like cool visualizations go for R, made this whole video kind of sus for me, cuz I love visualization and plotly seems to work better in python and seaborn can look even better than ggplot2 imo. Even though coding ggplot2 is much easier than plotly or seaborn, you cannot beat how smooth and nice those libraries look.

This is a really underrated usage of R, especially when you have the DBI package able to work with the major open source implementations of SQL databases. I manage a server hosting a lot of Shiny apps that rely on SQLite databases to work properly and the update routine of ETL is done using R scripts running on a daily basis with cronjobs.

is 37 late to become programer want to learn R and python

@@elvinmustafov7313 nope, but you should consider getting good spine inusrance, 40 strugle is real, progamming languges are not flavors they are desing to solove certain issues and make money cough java-script, python is the most easy lanaguage, like you never down the path of programming go for python just to get taste of it, when it comes to data,ml,AI python is go to, but that does not mean R is usesless R is there to solve satiscal learning,visulaization and much more.

@@elvinmustafov7313 As he said R is easy to get into. Start with c it'll make easier and give a better understanding and will took few months or just go with R if you have lesser time

@@EDMisalive tring to learn R and and Python this was advice and opinion of few programers that i know

@@elvinmustafov7313 as a general rule of thought personally its never too latge for anything ( maybe it sounds a bit cheesy but I believe it to be quite true)

the most wise comment

I use python for stats all the time, works great. I used to use R but I'll probably never go back

I agree with you

Now tell me what is machine learning all about...

I'd concur if Machine learning was only Neural Networks, which for some people it may be.

I'm currently learning Python for automation stuff and want to know R only for data analysis. Is this the best approach in your opinion since you know both.

​@@hugowesley4074 If you learn python first

Python borrowed a lot from R

Rated R

Python is a great glue language.

No it's not. It's just very specific.

Well...if you need to do statistical tests in Python, you'll be suffering.

This is how I feel whenever this debate comes up, a lot of people think R just does 1 or 2 things really well. But, the reality is packages like Shiny, Rmarkdown, and some ML libraries are misunderstood or just ignored for how good they are (community and documentation). Also, I have rarely had problems with learning a new R package that works in the base R code format, because everyone uses a similar coding format. Whereas Python packages are harder to pick apart, because people base their coding formats on different formats.

@BaroDrinksBeer Shiny is a criminally underrated part of R, along with Plumber APIs. I managed to create a significant saving for a company by making them cut an expensive PowerBI license and substitute all the dashboards for Shiny on a cloud server. Worked like a charm. Reactive modules with pre trained ML models in .rds files, with a daily retraining routine for the new data using cronjobs.

My view is slightly different: R and more specify Tidyverse (packages / R dialect) is the clear leader in supporting fully reproducible workflows where the pipeline ends with reporting - reporting includes interactive web applications all the way down to static documents. The Python community has not been as strongly engaged in the reproducibility discussion outside of enterprise execution pipelines. They simply stop before reporting and that stopping point is premature. (Edit: typo misspelling corrected)

Hi Robert. I one of the 'people who have only used excel'. Can you tell learning R is easier for people like me? (Fyi I'm learning phyton as my first language atm)

@@Kei3th1424 why R is easier? One of my observations is that when in Excel, you're somewhat writing codes when you type out formulas that contain functions. The way u work with data in R is very similar in terms of the functional approach whereas if u go to python the syntax will be a bit more alien with heavier emphasis on object oriented designs and quite frankly a less intuitive way of working with data in pandas especially that makes it hard to learn for first time programmers.

What is your take on Julia vs R?

​@@hansisbrucker813Julia still has to prove mass adoption. R is the successor to S and thus much older then Python and Statisticians publish new algorithms in R whereas Python is taught to many beginners. Both will be around in twenty years. Can you say the same about Julia? There is no doubt that Julia is great in what it does but so were BASIC and PROLOG and Smalltalk languages. If Julia is good for what you do with it today, then go for it. If learning a language is a long time investment of your time and effort, choose something established.

For me it's the opposite. I learned programming with R, and feel like Python is much less intuitive.

Started with Python for Data Analysis. Later tried R tidyverse. Oh dear, i hate python workflow now: pandas, numpy, seaborn - its all feels as an awful crutch

I learned R because i loved their dataframe structure. Now with pandas, R can go pound sand.

Pandas is an awkward attempt to add dataframe objects in python that resemble the way R works.

I mean except for the fact that Python can be used to build massive code bases and complicated infrastructure easily, then sure, they are even... Ever wonder why a lot of companies use Python for their code base and nobody uses R?

R uses actual logic.

R was created with the aim of making it easier for humans or data analysts to perform computations, not to make it easier for computers to do their job. So, the logic more closer to human. For example, index start from 1 like you start count from 1, right?

Some may think R is weird for there is no variable type that can contain only one number, others may think Python is weird for the lack of curly braces around blocks. None of these are real obstacles in learning a programming language.

R is object orientated as well as functional and using both in both languages makes a lot of sense. Do you really think that any of this makes an important difference between these languages? I don't think these are the decisive differences.

Python is much better for readability. It's too easy to write opaque R code. Python also has features like dictionaries, comprehensions and lambda functions that make coding more pleasant. R also sucks with data outside of dataframes. Matrices are much harder to work with than numpy arrays.

Tidyverse is a collection of libraries. It isn't even right to compare Pandas to Tidyverse. In this respect, you'd be better off comparing Tidyverse to Anaconda. It's really just a weird claim when matplotlib, pandas, numpy, seaborn, scikit learn, pycaret, yellowbrick all have just have incredible documentation. Not to mention, the combination of "Read the Docs" and "Sphinx" make open source package documentation a breeze. Why? Because good programming requires good inline documentation. Both of these tools make it incredible easy to take your inline documentation and build/distribute it to the open source community. It's just weird to say python libraries don't have great documentation when its just wrong. A preference for functional programming through dplyr and tidyr is not enough to say "R is better for data analysis." In Pandas, there too is support for a more functional approach through the pipe method. Additionally, dplyr and tidyr combined do not have anywhere near the amount of methods available for data manipulating. On a more important note about Pandas pipe, it allows for user defined functions for applying transformations on dataframes or series. Why is this important? Because it provides better encapsulation, more options to the developer, and improved readability. To be clear, you cannot, out of the box combine dplyr's (or tidyr) select, mutate, groupby, ect with a custom function via the pipe operator. dplyr has a not so friendly work around for providing this functionality where the user needs to google search through and figure out that they need a parameter called ".data" which is something very specific to dplyr's implementation and not at all obvious. This is a huge limitation when it requires the developer to take their work to a production setting. Or, even more simply, share their work with others and debug their code themselves. Don't even get me started on the data-masking that the tidyverse paradigm has created in the R community. While it makes data operations more concise, it comes at the expense of polluting the name space of the environment making the developer blind to what variables have been created in global scope increasing the risk of collisions.

Use the one you know. I don't find R much better for stats than scipy, or ggplot better than seaborn. But I do find python better for environment management, package development, and none data science projects like webscraping.

This is me, chuckling. I imagine I've seen a proportionally equal amount of opaque and unreadable python code as you may have seen opaque R code. I also imagine, and you might agree, that good coding is partially art and partially experience. So, if you have a language that is good for beginners, you're probably gonna see some bad code written in that language. no? Anyway, Yes, you can write anonymous functions in R -- totally can. Chucking again that the claims, without evidence, about python dictionaries , comprehensions, or matrices are supposed to be dispositive in favor of python. At best it comes down to use-cases. But really, OP's comment -- "choose the language of your community" -- is spot on. There seems to be no end of python-fan vituperative comments using straw-man criteria meant to express strengths when they actually express personal bias -- typically expressed alongside often outdated and just-plain-wrong claim about R. In any case, my comment was aimed at OPs comment about R's utility in data exploration. My position is that R (AND Tidyverse) is clearly better than OPs video suggests (somewhere in the middle-end of the video timeline). Beyond that, OPs recommendation to use R for beginners AND advanced is insightful to say the least. Clearly a strong and sound suggestion. Meanwhile, I can't stop chuckling at this response. I mean, just no. But, look, it's totally fine to have a preference. Not convincing, but if you're community digs Python, keep doing you.

@@BingbongRecto R's equivalent functions to Python's lambda functions are: apply, lapply, sapply, vapply, tapply. Followed by mcapply (multi core apply i.e. parallel processing).

it can be done in R too - what's your point?

@@borisn.1346 but you wouldn t want that!

Why would would I run a backend application in R😂 when fastapi and django rocks

@@fortuneosho8137 yes fastapi is great for modelling.

The answer to this post has certainly changed with the advent of Shiny and then again with the advent of webR. We should all get used to the two languages growing closer together.

JuPyteR is Ju-lia Pyt-hon and R acronym but... The Jupyter system supports over 100 programming languages (called “kernels” in the Jupyter ecosystem) including Python, Java, R, Julia, Matlab, Octave, Scheme, Processing, Scala, and many more. Out of the box, Jupyter will only run the IPython kernel, but additional kernels may be installed. (c)

@@stearin1978 thanks, informative.

Also RStudio supports programming languages other than R

Agree R data table is my choice Python pandas is just terrible if we talk about amount of the code you need for the same operations

R is used on the financial sector and auditing. With R you can make complex statistical analysis.

I'm learning it by myself and I feeling certain difficult to handle this larger range of applications. Do you've knowledges about other data tools?

Came here to say this, that this video is obviously just an excuse to show off his backward writing.

The video is probably mirrored. I assume he is right-handed.

It's a mirrored image

The thing about Python is that it completely half asses both the OOP and functional paradigms, meaning that while being multi-paradigm in theory, I think most Python programmers are better off sticking to good procedural code with common sense applications of other paradigms. Note that I'm not saying that's a bad thing. There's a reason Python is my go to language.

R also has OOP systems: S3, S4, S7, R6, etc. R6 is the equivalent to classes in Python.

What a biased opinion. "Cool people use R. Python is for programmers who do basic shit" lmao

@@MrMaxtng No its true. Any job focusing heavily on data analysis will have you using R. Where I live any actuary has to know R…

This is correct. We work with chemicals and design experiments all day long for optimization purposes. R has so much functionality and and what we chemists know as packages. The science behind our chemical technology is deeply rooted in research work based on Response Surface Methods and Mixture Designs. We're no programmers. We're scientists. And we analyze our data and design our experiments with R.

@@MrMaxtng It is literally the case though.

@@victorst5997 R is also used in Biology and medicine.

Me too learnt about R 3 years after doing my post graduate masters 😢😢😢

Maybe the video was flipped

Was looking for this comment about tidyverse. As a statistician, I first learned python because of its general use and overall simplicity. Both are good for beginners either way. Then moved to R for more advanced work. And the more general and computer science-y I go, the more python I use

Plotly is another option.

Or learn just one of these and then something different such as C++, SQL, HTML/CSS, a Shell, VIM or Emacs. Anything that has less overlap and thus brings more new things to the table!

And which do you prefer?

please take a word about R , now im try to start with it, and have a bit doubt of my choice

What a nice video to be like and share.

Do you agree with this.

You should consider what your team does and what you plan on doing. If in doubt, learn the more General Use language first.

Thanks for your comment. We strive to make videos that mean something to our audience - and when we make mistakes we make light of those. #human