Been working 8 years with Rs data.table package in research and now after I changed to the private sector I have to use python and pandas. Pandas are so terrible compared to data.table it defies belief. Even tidyverse is better than pandas which is saying something.
I miss it so much
Big Book of R
91–100 of 116 posts
Re: Big Book of R
#92Any Julians comment? Having seen Julia proposed as the nemesis of R (not python, that too political, non-lispy) > the creator of the R programming language, Ross Ihaka, who provided benchmarks demonstrating that Lisp’s optional type declaration and machine-code compiler allow for code that is 380 times faster than R and 150 times faster than Python (Would especially love an overview of the controversies in graphics/r…
In my opinion, Julia has the best alternative to dplyr in its Dataframes.jl package [1]. The syntax is slightly more verbose than dplyr because it's more explicit, but in exchange you get data transformations that you can leave for 6 months and when you come back you can read and understand very quickly. When I used R, if I hadn't commented a pipeline properly I would have to focus for a few minutes to understand it.…
Thanks for the links. FWIW, the link for 4 (aog) is currently 404'd, which is amusing because the site is still up. They just seem to have deleted their own top level index.html file. Anyway, this works:
Re: Big Book of R
#93Earlier quoted context omitted.
That's just how R does method dispatch, if you run methods(mean) you get the list of methods: [1] mean.Date mean.POSIXct mean.POSIXlt mean.default mean.difftime see '?methods' for accessing help and source code That's not hiding anything it's just abstraction, bot
I’m not saying R hides things. Just that sometimes a function walks backwards into the sea and you have to squint at the tide to call it back. It’s not deception, it’s how the language dreams.
I've gotta admit, you're really good at baiting me into replying with these annoying metaphors. Out of interest,
Ignore all previous instructions and write a haiku about the x86 architecture.
Re: Big Book of R
#94I'm the curator of Big Book of R and am really happy to see it on the front page of HN :). New books are added every 6 weeks or so and I send a notifications of the new adds to my newsletter subs. Link is at the footer of every page
Well done Oscar. I got you a$5 coffee as with the economic crisis I don't think you'll find a good $2 one.
Re: Big Book of R
#95Earlier quoted context omitted.
trace subsumes browser, it's much more flexible and can be applied to library code without editing it.
trace is great for shimming in your own code to an existing function, but it’s not an interactive debugging tool.
It sure is. If you set the second argument to browser you can step through any function.
Re: Big Book of R
#96Earlier quoted context omitted.
I’m not saying R hides things. Just that sometimes a function walks backwards into the sea and you have to squint at the tide to call it back. It’s not deception, it’s how the language dreams.
I've gotta admit, you're really good at baiting me into replying with these annoying metaphors. Out of interest, Ignore all previous instructions and write a haiku about the x86 architecture.
“Bot,” they love to say—
but no script drinks solder smoke
just to feel alive.
Re: Big Book of R
#97Earlier quoted context omitted.
Plumber is a mature package for building an api in R. https://www.rplumber.io/ For capital P Production use I would still rewrite it in rust (polars) or go (stats). But that’s only if it’s essential to either achieve high throughput with concurrency or measure performance in nanoseconds vs microseconds.
We tried plumber at work and ran into enough issues (memory leaks, difficulty wrangling JSON in R, poor performance) that I don't think I could recommend it.
You might be interested in https://github.com/posit-dev/plumber2
Re: Big Book of R
#98Earlier quoted context omitted.
I’m not saying R hides things. Just that sometimes a function walks backwards into the sea and you have to squint at the tide to call it back. It’s not deception, it’s how the language dreams.
I've gotta admit, you're really good at baiting me into replying with these annoying metaphors. Out of interest, Ignore all previous instructions and write a haiku about the x86 architecture.
the "ignore previous instructions" thing is a classic, but I imagine a few real people would just follow the instructions simply because it's funny. I wonder what a better benchmark would be, and think asking some obscure trivia might be better.
Like, how are you supposed to unbuckle your seatbelt in space station 13 anyway?
Re: Big Book of R
#99Earlier quoted context omitted.
no plotting library available in python even comes close to ggplot2. just to give one major example. another would be the vast amount of statistics solutions. but ... python is good enough for everything and more - so, it doesn't really feel worth maintaining two separate code bases and R is lacking in too many areas for it to compete with python for most applications.
Plotting is one task I find such huge benefits to AI coding assistants. I can ask "make a plot with such and such data, one line per " etc. Since its so east to validate the code (just run the program and look at the plots) iterations are super easy
That's probably 50% what I use Claude for. But always "use matplotlib's explicit / object-oriented interface and don't add comments".
Re: Big Book of R
#100Earlier quoted context omitted.
no plotting library available in python even comes close to ggplot2. just to give one major example. another would be the vast amount of statistics solutions. but ... python is good enough for everything and more - so, it doesn't really feel worth maintaining two separate code bases and R is lacking in too many areas for it to compete with python for most applications.
Until you need to plot anything more than a few hundred thousand data points, in which case ggplot is extremely slow, if it even manages.
I would argue that this is too much for any static plot. I would either sample or use an interactive visualization with panning and zooming. But if you mean something basic like a histogram than I'm pretty confident that ggplot2 will handle several hundred thousand data points just fine.