Data Science. TileDB. Open Source. Quant Research. R. C++. Debian. Linux. Adjunct Clinical Professor, University of Illinois. Lots of coffee. And some running.
That is in response / as a follow-up to @df7cb showing the same in #postgresql but I couldn't reply-tweet with a screenshot ... Also no space for the #rdatatable tag the tweet really needed too.
#TIL 13ths are more often Fridays than other weekdays:
select extract(dow from d), count(*) from generate_series(date 'today' - interval '400 years', date 'today' + interval '400 years', interval '1 day') as g(d) where extract(day from d) = 13 group by 1 order by 1;
@PostgreSQL
For code with, say, Rcpp.h and/or Boost headers (which really are aggregated include statements) it wants to break things up into smaller more concise statements---just as stated---so you may encounter a lot of output.
And the @Debian (source) package(s) have been updated, binaries to follow.
There will also be an updated Docker container via my RQuantLib repo, and I will likely build Ubuntu 19.04 packages via my PPA.
This looks fabulous. Great iniative to show some more @rdatatable awesomeness.
Had actually been thinking that "someone" could also do the SQL examples by @b0rk in @rdatatable too .... There is so much power and beauty in `dt[i, j, by]` and the @rdatatable backend.
Or, and that needs to be said and repeated, lack of breaking changes!
CRAN *really* is just simply fantastically reliable here. I have been updating (nearly) daily for maybe a decade or longer and things just don't break if you choose your package stack wisely.
Signs you code too much and run too little #83: An email from @Strava makes you wonder "hm, what can they teach me about Pull Requests?".
Happy @nymarathon to all runners! Ran a nice BQ (another one those terms...) there 12 years ago followed by a PR in Berlin the next year...