hadley

16 ms·

1. 151.▲
   by hadley 11y ago

   It's part of a suite of data packages for doing analysis, which encompasses visualization, data manipulation, and modeling.
2. 152.▲
   by hadley 11y ago

   Have you tried svglite? It produces pretty decent svgs for web use.
3. 153.▲
   by hadley 11y ago

   Please file bugs on GitHub. It looks like you're using packages built on top of ggplot2 - in particular the maintainer of ggtern seems to have disappeared. Otherwise I'd highly recommend using packrat or similar so you can choose
4. 154.▲
   by hadley 11y ago

   I find that surprising. Do you have benchmarks?
5. 155.▲
   by hadley 11y ago

   Thanks!
6. 156.▲
   by hadley 11y ago

   Thanks! I think I have have underestimated how many people confused bar charts and histograms :/
7. 157.▲
   by hadley 11y ago

   If you have the time, could you please shoot me an email with the lessons you think CRAN could learn from CPAN? Thanks!
8. 158.▲
   by hadley 11y ago

   That's the goal of packrat. (But it's still a work in progress)
9. 159.▲
   by hadley 11y ago

   I get the complaint about one more OO system, but I did consider all the options and I'm pretty sure that this was the best solution, given how few people will be exposed to it. There's also a legitimate learning challenge: if I w
10. 160.▲
    by hadley 11y ago

    This is actually a huge strength for the R community, who by and large are not programmers and just want stuff to work. The fact that the latest version of all CRAN packages actually work together makes life much easier. And for experts the
11. 161.▲
    by hadley 11y ago

    If it does break stuff that you think it shouldn't please let me know. Goal is to do a patch release in a month or two to fix anything I broke accidentally.
12. 162.▲
    by hadley 11y ago

    Which is why ggvis has a different architecture which will make working with large datasets easier. Not to mention the pipe as a unifying interface across ggvis and dplyr which makes it easier to do efficient data manipulation within the vi
13. 163.▲
    by hadley 11y ago

    I'm pretty sure the evaluation bugs have been fixed for a while (subject to some caveats). Unfortunately it's impossible to fix fully in ggplot2 without a massive rewrite, but ggvis doesn't suffer from the same problems. Now
14. 164.▲
    by hadley 11y ago

    Nice work!
15. 165.▲
    by hadley 11y ago

    It's completely not true that ggplot2 defaults were copied without thought from Tufte. A pale grey background is not chart junk because it does not distract the eye (and indeed it actually enhances colour). You are using Tufte's t
16. 166.▲
    by hadley 11y ago

    And like pandas, many of the performance bottlenecks in R have been re-written in C. See dplyr and data.table for packages that solve a similar problem to pandas with similar speed (and for some scenarios they're actually faster!)
17. 167.▲
    by hadley 11y ago

    Working with text data in R is painful, but it's not due to limitations of the language.
18. 168.▲
    by hadley 11y ago

    It does help that I'm one of the few people who are paid to work full-time on nothing but open source R packages that a designed to broadly aid data analysis.
19. 169.▲
    by hadley 11y ago

    Thanks :) The caveat on the ggplot2 book is that building it seems to be really hard because of the nightmare of cross-platform latex. But there will be a physical book out early next year.
20. 170.▲
    by hadley 11y ago

    Thanks!
21. 171.▲
    by hadley 11y ago

    I'd love to hear what precise production problems that you're seeing. I know people are successfully deploying R in production, but I'd like to hear more about the challenges.
22. 172.▲
    by hadley 11y ago

    Also RStudio is growing, so I'm hoping I will have some full-time engineers working with me in the not-too distant future.
23. 173.▲
    by hadley 11y ago

    R _is_ object oriented. But it uses generic function style of OO, rather than message passing, which you're probably more familiar with. (Interestingly Julia also uses generic function style OO)
24. 174.▲
    by hadley 11y ago

    I think there are lots of good R libraries for getting data from various places: DBI (databases), haven (SPSS, Stata, SAS), readxl (xls & xlsx), httr (web apis), readr/data.table (flat files). (Disclaimer: I wrote/contributed
25. 175.▲
    by hadley 11y ago

    I think you're wrong. R is an excellent language, targeted specifically around the problems you commonly see when doing data analysis. On the whole the standard libraries aren't particularly good, but I think the language is good.
26. 176.▲
    by hadley 11y ago

    You're confusing reference counting (which is used primarily for R's copy-on-modify strategy) and its generational garbage collector.
27. 177.▲
    by hadley 11y ago

    I think it's more important to understand the pros and cons of going into technical debt. It's much like real debt: sometimes, by taking on debt in the short term, you can spring board yourself to a better place in the long term.
28. 178.▲
    by hadley 11y ago

    I can't answer in general, but I think I do :)
29. 179.▲
    by hadley 11y ago

    For me at least, there are two thoughts (including mine) at the corresponding question on quora: http://www.quora.com/How-is-Hadley-Wickham-able-to-contribut...
30. 180.▲
    by hadley 11y ago

    Given that you called them facets, I'm going to assume you're familiar with ggplot2. In retrospect, I thinking adding non-Cartesian coordinate systems was a mistake. They are a huge amount of work and only make a handful of charts