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One Year with R

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Re: One Year with R

#111

Post by mellavora »

ourlordcaffeine wrote: post #29
indeed30 wrote: post #12

I love R more than any other language I have ever used. Perhaps more than any piece of software I've ever used. All of these points are valid, and yes, it's messy, and if you try to write the same type of code that you would in Python, it will frustrate you. And yet.. it somehow works. It makes data analysis and statistical modelling a pleasure. It somehow gives off a sense of lightness, and makes it easy to investig…

The main issue I've had is speed. As soon as you have problems that can't be vectorized, models that take 30 hours to run in R take 30 minutes in python.

Example, please?

This seems highly unlikely, based on my 20+ years with R. Yes, using wrong data structures/algorithms can lead to slow code, but switching languages won't fix this.

rprof and microbenchmark are your friends if you really need to optimize your code.

and (as in python, and as several others have pointed out), if you have something especially challenging, write it in C/C++/fortran instead, and link it to R.

Re: One Year with R

#112

Post by stadeschuldt »

tel wrote: post #61

R, and by R I mean R+tidyverse, is the world's best graphing calculator attached to an OK scheme. To which I mean R is a highly optimized, well-oiled machine if you're using it for its highly-optimized, well-oiled purposes. I tend to have notebooks full of tiny fragments like this dat_min %>% group_by(ymd = make_date(year(date), month(date), day(date))) %>% summarize(vol_btc=sum(vol_btc), vol_usdt=sum(vol_usdt), trad…

Great stuff. Could you maybe share a bit of these "3 dozen" scripts? This could be super helpful.

Re: One Year with R

#113

Post by ekianjo »

tel wrote: post #61

R, and by R I mean R+tidyverse, is the world's best graphing calculator attached to an OK scheme. To which I mean R is a highly optimized, well-oiled machine if you're using it for its highly-optimized, well-oiled purposes. I tend to have notebooks full of tiny fragments like this dat_min %>% group_by(ymd = make_date(year(date), month(date), day(date))) %>% summarize(vol_btc=sum(vol_btc), vol_usdt=sum(vol_usdt), trad…

Looks like your notebooks focus on crypto currencies :-) Good use case for data analysis!

Re: One Year with R

#114

Post by hadley »

CapmCrackaWaka wrote: post #59

I would say about 90% of the posts / articles / comments I see on the internet which discuss R are usually of the "meta" format. They talk about R's strengths or weaknesses, about the difference between R and Python, about how much they love or hate R, or any other high level subject. I can't remember the last time I saw a project someone did in R, or a tutorial on how to do something in R, get very much traction any…

They don't often come with code, but one of my recent sources of R programming joy is the folks posting their generative art to twitter: https://twitter.com/search?q=%23rstats%20%23generativeart&sr...

Re: One Year with R

#115

Post by ekianjo »

horsawlarway wrote: post #96
indeed30 wrote: post #12

I love R more than any other language I have ever used. Perhaps more than any piece of software I've ever used. All of these points are valid, and yes, it's messy, and if you try to write the same type of code that you would in Python, it will frustrate you. And yet.. it somehow works. It makes data analysis and statistical modelling a pleasure. It somehow gives off a sense of lightness, and makes it easy to investig…

Coming from Matlab, I have the opposite feeling. I truly, genuinely dislike the language. I think it's very productive, and I appreciate that Matlab costs an arm and a leg (and god help you once you start paying for some of the nicer packages on top) - but Matlab has spoiled me immensely on the language front. To me, Matlab feels like a language that was designed with an intent to appeal to folks with some understand…

> R feels like a language that was built for people who were using excel,

I don't think so. Most people who come to R after years of Excel find it just as alien as you do.

Re: One Year with R

#116

Post by zhdc1 »

dagw wrote: post #16
musingsole wrote: post #10

Earlier quoted context omitted.

I don't understand the use case for SPSS. My local university is training their neuroscience researchers on it, which seems so odd in 2022 with Julia or python sitting right there.

Teaching someone who knows a bit of Excel and very little programming how to do statistical analysis in SPSS is easy and lets you focus on the statistics. Teaching them to do statistical analysis in Julia will involve you spending 80% of your time teaching them Julia and maybe 20% of your time teaching them statistical analysis.

> Teaching them to do statistical analysis in Julia will involve you spending 80% of your time teaching them Julia and maybe 20% of your time teaching them statistical analysis.

This works until they run into a use case that doesn't involve running various forms of regression analysis on panel data.

In the parent comment's case, I could imagine that there's an expectation that someone doing neuroscience research will eventually have to expand beyond what's possible in SPSS. In this case, it may make sense to go through the effort of teaching them how to program in Python or Julia.

Re: One Year with R

#117

Post by delusional »

tel wrote: post #61

R, and by R I mean R+tidyverse, is the world's best graphing calculator attached to an OK scheme. To which I mean R is a highly optimized, well-oiled machine if you're using it for its highly-optimized, well-oiled purposes. I tend to have notebooks full of tiny fragments like this dat_min %>% group_by(ymd = make_date(year(date), month(date), day(date))) %>% summarize(vol_btc=sum(vol_btc), vol_usdt=sum(vol_usdt), trad…

> R is a highly optimized, well-oiled machine if you're using it for its highly-optimized, well-oiled purposes.

This hits home for me. We are just starting to use R for risk modeling where I work. R, more than any language I've ever used, makes me appreciate "worse is better". From a theoretical "aesthetic" perspective R is a mess. Yet for data processing all those theoretical concerns don't matter. It just works.

It's honestly kind of humbling that something so theoretically messy can be so practically coherent. It makes me question my assumptions about simplicity.

Re: One Year with R

#118

Post by mellavora »

em500 wrote: post #23

The common trope with R is that statisticians and love it and developers hate it. The the main reason that statisticians love it is that the libraries useful to them are much better in R than elsewhere (though Python keeps encroaching in that turf, and "real developers" dislike Python a lot less than they do R). The main reasons that developers hate it is that it is very unlike almost all other languages that they're…

> "real developers" dislike Python a lot less than they do R

I thought that was real Scottmen.

Because real Scottsmen prefer:

table.loc[(table.column > 2) | (table.column2 to

table[column > 2 & column2 and everyone knows this!

not to mention, if you aren't managing 100 virtual environments and 100 conda environments (with different syntax for requirements), you aren't a real scottsman!

Re: One Year with R

#119

Post by jdougan »

peatmoss wrote: post #100
tel wrote: post #61

R, and by R I mean R+tidyverse, is the world's best graphing calculator attached to an OK scheme. To which I mean R is a highly optimized, well-oiled machine if you're using it for its highly-optimized, well-oiled purposes. I tend to have notebooks full of tiny fragments like this dat_min %>% group_by(ymd = make_date(year(date), month(date), day(date))) %>% summarize(vol_btc=sum(vol_btc), vol_usdt=sum(vol_usdt), trad…

> best graphing calculator attached to an OK scheme. I discovered "How To Design Programs" somewhere late in my first year of using R. Like most beginning R coders with nominal experience in other languages, I wrote a lot of monolithic scripts in a very imperative style. HtDP gave me a mental framework for decomposing larger problems into bite-sized chunks. The lispy roots of R lent itself particularly well to the mo…

There is an better alternate universe where xlisp-stat doesn't fall behind and S doesn't happen.

Re: One Year with R

#120

Post by _jordan »

kome wrote: post #3

For my use case, R is absolutely terrible compared to some for profit statistical package / language. Using R feel like using an outdated, complicated and messy tool. But guess what: it's free.

JMP and stata are really solid tools, but I feel like the advantage stems from the fact that they help me discover new statistical methods. In the GUI I can see an option for something I never seen before, read the documentation, and therefore expand my stats skillset. This type of discoverability is a bit harder with R/Python just due to the nature of it being purely script driven.
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