My favorite operator is the pipe operator. When I first found out you could do a simple `ls | more` to read long outputs, it was an eye opening experience. In Clojure, we have the threading macros, `->` and `->>` that do a very similar thing. In R, we have `%>%` and now the native `|>`. Whenever a language has this operator and it is widely used, I know I am going to love it.
One Year with R
91–100 of 266 posts
Re: One Year with R
#92I support bioinformatics researchers and my R problem isn't the language itself but the increasing fragile tower of packages that users cobble together. At this point, I see R users (typically PhD students and post-docs) doing "science" in R by playing with parameters to functions in poorly-understood packages and publishing papers on which parameters are "best" for data generated from some specialty source. A very c…
> I see R users (typically PhD students and post-docs) doing "science" in R by playing with parameters to functions in poorly-understood packages and publishing papers on which parameters are "best" for data generated from some specialty source.
That's a lot of bioinformatics, and not specific to R. It is a huge issue with anything vaguely pushbutton in the bioinformatics domain.
Re: One Year with R
#93Earlier quoted context omitted.
Do you have any specific examples that illustrate the general problem? I'd love to better understand what you're looking for in docs.
Thanks for taking my aggressive comment with such spirit, it really speaks to a good community. (Sleep training an infant has me a bit frazzled) I should have been more specific, the ... frustration for me comes up mostly in ggplot, Which usually directs you to layer(). Which gets parameter string documentation like: * geom - The geometric object to use display the data * stat - The statistical transformation to use…
I think the issue with some of this documentation is that for other packages, the function documentation is largely self contained. If I look up glm() it tells me how to use glm(). However, for ggplot2 there is an assumption that you have some level of knowledge of how the pieces should be strung together. So when I know I want a boxplot, and I find geom_boxplot() documentation it wonderfully describes the options for itself, and gives examples for it's use. But sometimes it doesn't give a good idea of the context of how the other pieces might interact. It makes complete sense if you read the book and just want to refresh your memory, but if you are coming in as a new user it really can be difficult to use the documentation exclusively.
Re: One Year with R
#94Earlier quoted context omitted.
I don't see how R specifically addresses the reproducibility problem, It's been around for almost 30 years and before its recent rise in popularity, lots of science was done in C, perl, fortran etc. Not to mention that actual dependency versioning is pretty poor. I struggle to run other people's R code after about 6 months (especially if they used the tidyverse as it pulls in hundreds of unstable dependencies) and no…
1. Before R commercial statistical packages were mainly used. You can, in principle, just use assembler too and develop everything yourself but it isn't practical. Regarding C/C++ and Fortran, many R packages are, in fact, wrappers around code in those or other languages making it easier to access them. From that point of view R can be regarded as a glue language. 2. Regarding keeping versions straight, all past vers…
> Before R commercial statistical packages were mainly used.
Maybe in your field, I work in bioinformatics - before R, perl was widely used as a high-level language.
> Regarding keeping versions straight, all past versions of packages in the CRAN repository are kept on CRAN...
This is woefully inadequate if you need to replicate somebody else's environment. Nobody should think manually guessing and then typing in each package version and hoping they're compatible is a viable option. Not to mention even if you specify an older version of a package it doesn't pull in compatible dependencies, it just pulls in the latest version. There's renv but it's not reached widespread use.
> Regarding tidyverse dependencies you can reduce the number of packages you load by not using library(tidyverse) and instead load the specific packages you need. This will result in fewer packages being loaded
We're talking about replicating other people's work. We don't have any control over their code, and R users are largely ignorant of best-software practices.
Re: One Year with R
#95R, 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…
I also use R for any heavy data manipulation, but I primarily use the data.table package. The efficiency that both of these packages unlock is absolutely unparalleled in any other tabular data manipulation library, in any other language that I have used. And R has the top 2!! My skin writhes every time I need to type: table.loc[(table.column > 2) | (table.column2 when I want to subset a table.
Not to mention the auto complete that comes with RStudio. Is there any way to get equivalent functionality in Jupyter?
Re: One Year with R
#96I 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 understanding of traditional procedural programming, but nudged into treating matrices as first class citizens.
R feels like a language that was built for people who were using excel, and have never written a line of code in their life - it's riddled with completely unintuitive, frustrating, intentionally obtuse operators and terms for things that have perfectly fine definitions in normal programming.
The difference is that I have 20+ years of programming experience (including quite a bit of functional programming) that I can easily port over to Matlab, and which becomes literal baggage trying to use R. The end result is that I will use R, but I basically always walk away frustrated and infuriated, even when the problem is solved.
Re: One Year with R
#97R, 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…
My wife is a researcher and started delving into doing her own statistical analysis. It's be fun (and frustrating) learning R with her. I agree that dplyr and the tidyverse are some fantastic packges for a software engineer who thinks about spreadsheets as SQL tables.
I would say the most frustrating part about RStudio is that it is a workbook where you can execute code based on your cursor. For my wife, these workbooks become a total mess because things aren't necessarily run sequentially.
Re: One Year with R
#98I don’t like this. Much of this is: 1. pointing out that, like every other language, base R has idiosyncrasies 2. how use of R is more complex when you’re largely ignorant of the tidyverse, which is crucial for the vast majority of tissue today’s use of R 3. frustration because you’re using a language/ecosystem, that’s targeted for a few specific uses, as a general purpose programming language
> how use of R is more complex when you’re largely ignorant of the tidyverse This. I'm interested in non-flamewar non-religious reasons that the tidyverse is bad. He does give some. I think his complaints about inconsistency and a moving target have some validity. However, the price of not using tidyverse is (roughly) paid in the rest of the article. I would definitely not use R without it. Read his Section 5 on the…
> HN readers - do you have an "up and coming" language that you think has better structured the fundamentals from R, that you hope will someday have enough capabilities you can use it instead of R?
Hope is the operative word here!
I'm writing a language to compete in this area. It's called Mech and I'll be releasing the first beta in October. You can think of it like Matlab + Excel. It's very fast, has default-parallel semantics for operators and functions like Matlab, reactive dataflow like Excel, and supports full interactive coding with no startup/compilation latency issues. It's meant for robots, but I've also designed it to be a better Matlab, and I think it should take on R handily. Fair warning, it's public alpha now so error messages are sparse and the happy path is narrow.
Re: One Year with R
#99Earlier quoted context omitted.
I also use R for any heavy data manipulation, but I primarily use the data.table package. The efficiency that both of these packages unlock is absolutely unparalleled in any other tabular data manipulation library, in any other language that I have used. And R has the top 2!! My skin writhes every time I need to type: table.loc[(table.column > 2) | (table.column2 when I want to subset a table.
Not to mention the auto complete that comes with RStudio. Is there any way to get equivalent functionality in Jupyter?
I use pycharm which has decent autocomplete. Pycharm has its own issue though, it fills out its autocomplete info by looking at the function that created the object, not the object itself. So if a function can return different types, autocomplete won’t work. That’s caused me quite a bit of pain.
Re: One Year with R
#100R, 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 model of thinking presented in that book.
Ever since then, I've pined for the graphing calculator parts in a more modern Scheme. When ggplot and then the tidyverse (neé hadleyverse) came on the scene, I was even more convinced that Scheme, especially Racket, was the ideal future for data science. If R could support a large ecosystem like tidyverse, just imagine what the metaprogramming facilities of Racket could do!
But I think those graphing calculator parts are hard to reproduce. Attempts to clone ggplot2 fall short year after year, because most other languages don't have grid graphics to build on top of. R is a deep ecosystem on "an OK scheme," which is damned hard to beat.
Aside: my first year with R, was in an urban planning masters program and I was terrified of my first big kid statistics course (taught in SPSS). I decided I'd give myself bonus work by learning R. While it was absurd to be doing my stats homework in SPSS, then R, then reviewing HtDP on top of the rest of my course load, I did ace that stats course. :-)