hadley

19 ms·

1. 181.▲
   by hadley 11y ago

   I think it's the 80-20 rule at play. You can solve 80% of a problem with the same 20% of the options. But the last 20% is different and you need a very large class of packages to cover the long-tail of needs.
2. 182.▲
   by hadley 11y ago

   I don't think R's OO is great; but it's mostly misunderstood because it's fundamentally different to most popular modern languages. Interesting Julia, uses exactly the same model as R (I.e. Generic functions not message
3. 183.▲
   by hadley 11y ago

   R does have some pretty cool tools for after the fact debugging, like dump.frames, but few people know about them.
4. 184.▲
   by hadley 11y ago

   Revolution analytics isn't a copyright holder of R, so no.
5. 185.▲
   by hadley 11y ago

   No, that's not their own implementation. It's GNU r bundled with some extras
6. 186.▲
   by hadley 11y ago

   I'll choose to take that as a compliment :p
7. 187.▲
   by hadley 11y ago

   You're very welcome :)
8. 188.▲
   by hadley 11y ago

   They're basically identical. The website is updated a bit more frequently, but the updates are mainly minor wording fixes, and get incorporated whenever the book gets re-printed (every 6-12 months)
9. 189.▲
   by hadley 11y ago

   Personally I prefer the website because I can normally remember which chapter something is in, and then I can find-in-page to quickly jump to what I was thinking about.
10. 190.▲
    by hadley 11y ago

    Thanks for the kind words!
11. 191.▲
    by hadley 12y ago

    Badly written R is impenetrable. So is badly written R. I suspect your standards for so-so R code are vastly different to mine. R and Python really are very similar as languages. R is more functional, but that shouldn't impede your abi
12. 192.▲
    by hadley 12y ago

    If you want people to understand your code, you need to treat it like writing: rewrite, rewrite, rewrite. The language itself is almost irrelevant: you can write horrible code in Python and beautiful code in R.
13. 193.▲
    by hadley 12y ago

    At the time I wrote ggplot2, R really was the only game in town. But I strongly believe that R has excellent features to support data science: non-standard evaluation, NAs at a very low level, data frames, first class functions, ...
14. 194.▲
    by hadley 12y ago

    See also http://github.com/hadley/purrr
15. 195.▲
    by hadley 12y ago

    How does the API communicate between the client and the server? Any interest in talking to it from R? (I'd be happy to help)
16. 196.▲
    by hadley 12y ago

    I think there's steady growth in active R repos that's masked by the huge impact of Hopkin's Coursera course on reproducible research. Tens of thousands of people fork a repo for a homework ( https://github.com&#x2F
17. 197.▲
    by hadley 12y ago

    FWIW that's not an official move by CRAN, it's just an interested individual mirroring all CRAN packages
18. 198.▲
    by hadley 12y ago

    Debugging is partly waiting on lldb work for windows, which looks like has taken off recently.
19. 199.▲
    by hadley 12y ago

    In my opinion the majority of code in R is extremely well suited to its domain. That means it does not look like the python code you are used to, and I'd recommend learning more about why R works the way it does, e.g. at http:/&#
20. 200.▲
    by hadley 12y ago

    Weird to have a list of programming and data resources and not even mention R.
21. 201.▲
    by hadley 12y ago

    prop.test(c(13, 8), c(152, 152)): 2-sample test for equality of proportions with continuity correction data: c(13, 8) out of c(152, 152) X-squared = 0.8184, df = 1, p-value = 0.3656 alternative hypothesis: two.sided 95 percent confidence i
22. 202.▲
    by hadley 12y ago

    I found the title very hard to parse. It would be better as: "Why Oakland Is a Tech Start-up Game Changer"
23. 203.▲
    by hadley 12y ago

    Data tables are extremely fast but I think their concision makes it harder to learn and code that uses it is harder to read after you've written it. It's very reminiscent of APL.
24. 204.▲
    by hadley 12y ago

    What's wrong with Rcpp? And what's wrong with GPL? Unless you're planning on distributing your code, you shouldn't even need to think about it.
25. 205.▲
    by hadley 12y ago

    That benchmark is only for joins? That's a pretty small part of analytic workflows in my experience.
26. 206.▲
    by hadley 12y ago

    I thought that before writing dplyr, but now I see that there a big differences. Relational databases are designed to work with large datasets on disk, and to accept changes very rapidly. The demands for in memory data analytics are quite d
27. 207.▲
    by hadley 12y ago

    That's not true. If you index with 0 you get a zero length vector back
28. 208.▲
    by hadley 12y ago

    You probably want options(error = recover). If you're not getting line numbers you need to upgrade R. You might find http://adv-r.had.co.nz/Exceptions-Debugging.html helpful.
29. 209.▲
    by hadley 12y ago

    Thanks!
30. 210.▲
    by hadley 12y ago

    There are way worse things you can do than that! e.g. `(` <- function(x) { if (is.numeric(x) && runif(1) < 0.1) { x * 1.1 } else { x } } ;)