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Another Book on Data Science – Learn R and Python in Parallel

anotherbookondatascience.com

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Re: Another Book on Data Science – Learn R and Python in Parallel

#11

Post by wjn0 »

clarityPhone wrote: post #2

I skimmed through the book, and think it does a very poor job at showcasing how R and Python are juxtaposed in industry. To be fair, the book advertises showing R and Python code side-by-side. And that’s what it does. But it does it unlike how the languages are most often used in industry. As a quick example, I saw no tidyverse code, which is essentially the only thing keeping R in the game. Learning R from this book…

I agree for the most part, but R does have a few things beyond the tidyverse: built-in dataframe support, lots of domain-specific packages, more consistent interfaces for basic statistics and machine learning models, etc. Python is definitely better for matrices (because of NumPy) and anything involving custom gradient descent methods (because of TensorFlow).

I think 90% of data science content is for beginners because anything more advanced isn't best described as data science. As soon as you get beyond the initial stages of data analysis (cleaning and processing data), you're doing something best described as some other word (statistics, machine learning, etc.) - although, granted, there isn't much content in these areas if you don't know _exactly_ what you're looking for.

Re: Another Book on Data Science – Learn R and Python in Parallel

#12

Post by adamnemecek »

thomasfedb wrote: post #10
adamnemecek wrote: post #3

Julia is hands down much better than either of these languages. Don't waste your time.

What's a good resource for a R user looking to jump over to Julia?

https://learnxinyminutes.com/docs/julia/

https://juliaobserver.com

The website is decent. Read the standard library https://github.com/JuliaLang/julia/tree/master/stdlib

search github for cool projects https://github.com/JuliaInterop/RCall.jl

Re: Another Book on Data Science – Learn R and Python in Parallel

#13

Post by bryanrasmussen »

clarityPhone wrote: post #2

I skimmed through the book, and think it does a very poor job at showcasing how R and Python are juxtaposed in industry. To be fair, the book advertises showing R and Python code side-by-side. And that’s what it does. But it does it unlike how the languages are most often used in industry. As a quick example, I saw no tidyverse code, which is essentially the only thing keeping R in the game. Learning R from this book…

Theodore Sturgeon update: 90% of all programming books are geared at beginners.

Re: Another Book on Data Science – Learn R and Python in Parallel

#14

Post by locoman88 »

adamnemecek wrote: post #3

Julia is hands down much better than either of these languages. Don't waste your time.

That's an opinion my friend, not a fact. If you want to be taken seriously, be sure to be careful in your assertions and always have hard data to back them up

Re: Another Book on Data Science – Learn R and Python in Parallel

#15

Post by s_Hogg »

adamnemecek wrote: post #3

Julia is hands down much better than either of these languages. Don't waste your time.

So? This whole argument over which programming language is the best all seems a bit tools-first to me. I used to program in R and was a package owner, but switched to python because it had stuff I needed (TF before it ever got ported to R).

Nowadays I program in python because it has all I need. If something comes out in Julia that makes the cost of picking up another language worth it then I'll do it without a second thought. Until then, why bother? The don't waste your time argument can cut both ways, you know.

To clarify: I see no inherent reason to not program in Julia or any other language. But you work with whatever gets your job done efficiently and right now that's neither of those languages for a lot of people.

Re: Another Book on Data Science – Learn R and Python in Parallel

#16

Post by adamnemecek »

s_Hogg wrote: post #15
adamnemecek wrote: post #3

Julia is hands down much better than either of these languages. Don't waste your time.

So? This whole argument over which programming language is the best all seems a bit tools-first to me. I used to program in R and was a package owner, but switched to python because it had stuff I needed (TF before it ever got ported to R). Nowadays I program in python because it has all I need. If something comes out in Julia that makes the cost of picking up another language worth it then I'll do it without a secon…

> This whole argument over which programming language is the best all seems a bit tools-first to me.

Not really, syntax and semantics are adjoints.

Re: Another Book on Data Science – Learn R and Python in Parallel

#17

Post by s_Hogg »

adamnemecek wrote: post #16
s_Hogg wrote: post #15

Earlier quoted context omitted.

So? This whole argument over which programming language is the best all seems a bit tools-first to me. I used to program in R and was a package owner, but switched to python because it had stuff I needed (TF before it ever got ported to R). Nowadays I program in python because it has all I need. If something comes out in Julia that makes the cost of picking up another language worth it then I'll do it without a secon…

> This whole argument over which programming language is the best all seems a bit tools-first to me. Not really, syntax and semantics are adjoints.

Exactly: you're talking about semantics.

In a great many cases, they aren't a first-order issue - which is where my objection to a blanket "don't waste your time" claim comes from.

Re: Another Book on Data Science – Learn R and Python in Parallel

#18

Post by adamnemecek »

s_Hogg wrote: post #17
adamnemecek wrote: post #16

Earlier quoted context omitted.

> This whole argument over which programming language is the best all seems a bit tools-first to me. Not really, syntax and semantics are adjoints.

Exactly: you're talking about semantics. In a great many cases, they aren't a first-order issue - which is where my objection to a blanket "don't waste your time" claim comes from.

What is there besides semantics?

Re: Another Book on Data Science – Learn R and Python in Parallel

#19

Post by huac »

mruts wrote: post #6
adamnemecek wrote: post #3

Julia is hands down much better than either of these languages. Don't waste your time.

I whole heartedly agree. Python is garbage for data science. If an industrial grade NN library was written for it, plus some quant libraries, I think most people would switch. I work in finance doing data science-y things and have yet to meet anyone who doesn’t think that Python is a pile of garbage. People used to make the easy to learn argument, but Julia is even easier. And more elegant, extensible, and faster.

You, uh, don't like PyTorch and TensorFlow? I can't tell if this is sarcastic.
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