Yes, please do some reading first and give take a crack at your data first.
This will only be a fruitful endeavor for you after you get some working knowledge of R. Hadley is compiling a nice book online that I think is very helpful to read through: https://github.com/hadley/devtools/wiki/Introduction The section on "functional looping patterns" will be immediately useful (once you have a bit more background working with R): http://github.com/hadley/devtools/wiki/functionals#looping-patterns It's really a great resource and you should spend the time to read through it. Once you read and understand the looping-patterns section, you'll be able to handle your data like a pro and you can move on to asking more interesting questions ;-) If something is unclear there, though, please do raise that issue. HTH, -steve On Sun, Aug 18, 2013 at 7:22 AM, Bert Gunter <gunter.ber...@gene.com> wrote: > This is ridiculous! > > Please read "An Introduction to R" (ships with R) or other online R > tutorial. There are many good ones. There are also probably online > courses. Please make an effort to learn the basics before posting > further here. > > -- Bert > > > > On Sun, Aug 18, 2013 at 7:13 AM, Dylan Doyle <ddoyle....@gmail.com> wrote: >> Hello all thank-you for your speedy replies , >> >> Here is the first few lines from the head function >> >> brewery_id brewery_name review_time review_overall review_aroma >> review_appearance review_profilename >> 1 10325 Vecchio Birraio 1234817823 1.5 >> 2.0 2.5 stcules >> 2 10325 Vecchio Birraio 1235915097 3.0 >> 2.5 3.0 stcules >> 3 10325 Vecchio Birraio 1235916604 3.0 >> 2.5 3.0 stcules >> 4 10325 Vecchio Birraio 1234725145 3.0 >> 3.0 3.5 stcules >> 5 1075 Caldera Brewing Company 1293735206 4.0 >> 4.5 4.0 johnmichaelsen >> 6 1075 Caldera Brewing Company 1325524659 3.0 >> 3.5 3.5 oline73 >> >> beer_style review_palate review_taste beer_name >> beer_abv beer_beerid >> 1 Hefeweizen 1.5 1.5 Sausa >> Weizen 5.0 47986 >> 2 English Strong Ale 3.0 3.0 >> Red Moon 6.2 48213 >> 3 Foreign / Export Stout 3.0 3.0 Black Horse >> Black Beer 6.5 48215 >> 4 German Pilsener 2.5 3.0 >> Sausa Pils 5.0 47969 >> 5 American Double / Imperial IPA 4.0 4.5 >> Cauldron DIPA 7.7 64883 >> 6 Herbed / Spiced Beer 3.0 3.5 Caldera >> Ginger Beer 4.7 52159 >> >> ' >> I have only discovered how to import the data set , and run some basic r >> functions on it my goal is to be able to answer questions like what are the >> top 10 pilsner's , or the brewer with the highest abv average. Also using >> two factors such as best beer aroma and appearance, which beer style should >> I try. Let me know if i can give you any more information you might need to >> help me. >> >> Thanks again , >> >> Dylan >> >>> >> >> >> >> On Sun, Aug 18, 2013 at 4:16 AM, Paul Bernal <paulberna...@gmail.com> wrote: >> >>> Thank you so much Steve. >>> >>> The computer I'm currently working with is a 32 bit windows 7 OS. And RAM >>> is only 4GB so I guess thats a big limitation. >>> El 18/08/2013 03:11, "Steve Lianoglou" <lianoglou.st...@gene.com> >>> escribió: >>> >>> > Hi Paul, >>> > >>> > On Sun, Aug 18, 2013 at 12:56 AM, Paul Bernal <paulberna...@gmail.com> >>> > wrote: >>> > > Thanks a lot for the valuable information. >>> > > >>> > > Now my question would necessarily be, how many columns can R handle, >>> > > provided that I have millions of rows and, in general, whats the >>> maximum >>> > > amount of rows and columns that R can effortlessly handle? >>> > >>> > This is all determined by your RAM. >>> > >>> > Prior to R-3.0, R could only handle vectors of length 2^31 - 1. If you >>> > were working with a matrix, that meant that you could only have that >>> > many elements in the entire matrix. >>> > >>> > If you were working with a data.frame, you could have data.frames with >>> > 2^31-1 rows, and I guess as many columns, since data.frames are really >>> > a list of vectors, the entire thing doesn't have to be in one >>> > contiguous block (and addressable that way) >>> > >>> > R-3.0 introduced "Long Vectors" (search for that section in the release >>> > notes): >>> > >>> > https://stat.ethz.ch/pipermail/r-announce/2013/000561.html >>> > >>> > It almost doubles the size of a vector that R can handle (assuming you >>> > are running 64bit). So, if you've got the RAM, you can have a >>> > data.frame/data.table w/ billion(s) of rows, in theory. >>> > >>> > To figure out how much data you can handle on your machine, you need >>> > to know the size of real/integer/whatever and the number of elements >>> > of those you will have so you can calculate the amount of RAM you need >>> > to load it all up. >>> > >>> > Lastly, I should mention there are packages that let you work with >>> > "out of memory" data, like bigmemory, biglm, ff. Look at the HPC Task >>> > view for more info along those lines: >>> > >>> > http://cran.r-project.org/web/views/HighPerformanceComputing.html >>> > >>> > >>> > > >>> > > Best regards and again thank you for the help, >>> > > >>> > > Paul >>> > > El 18/08/2013 02:35, "Steve Lianoglou" <lianoglou.st...@gene.com> >>> > escribió: >>> > > >>> > >> Hi Paul, >>> > >> >>> > >> First: please keep your replies on list (use reply-all when replying >>> > >> to R-help lists) so that others can help but also the lists can be >>> > >> used as a resource for others. >>> > >> >>> > >> Now: >>> > >> >>> > >> On Aug 18, 2013, at 12:20 AM, Paul Bernal <paulberna...@gmail.com> >>> > wrote: >>> > >> >>> > >> > Can R really handle millions of rows of data? >>> > >> >>> > >> Yup. >>> > >> >>> > >> > I thought it was not possible. >>> > >> >>> > >> Surprise :-) >>> > >> >>> > >> As I type, I'm working with a ~5.5 million row data.table pretty >>> > >> effortlessly. >>> > >> >>> > >> Columns matter too, of course -- RAM is RAM, after all and you've got >>> > >> to be able to fit the whole thing into it if you want to use >>> > >> data.table. Once loaded, though, data.table enables one to do >>> > >> split/apply/combine calculations over these data quite efficiently. >>> > >> The first time I used it, I was honestly blown away. >>> > >> >>> > >> If you find yourself wanting to work with such data, you could do >>> > >> worse than read through data.table's vignette and FAQ and give it a >>> > >> spin. >>> > >> >>> > >> HTH, >>> > >> >>> > >> -steve >>> > >> >>> > >> -- >>> > >> Steve Lianoglou >>> > >> Computational Biologist >>> > >> Bioinformatics and Computational Biology >>> > >> Genentech >>> > >> >>> > > >>> > > [[alternative HTML version deleted]] >>> > > >>> > > >>> > > ______________________________________________ >>> > > R-help@r-project.org mailing list >>> > > https://stat.ethz.ch/mailman/listinfo/r-help >>> > > PLEASE do read the posting guide >>> > http://www.R-project.org/posting-guide.html >>> > > and provide commented, minimal, self-contained, reproducible code. >>> > > >>> > >>> > >>> > >>> > -- >>> > Steve Lianoglou >>> > Computational Biologist >>> > Bioinformatics and Computational Biology >>> > Genentech >>> > >>> >>> [[alternative HTML version deleted]] >>> >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >>> >> >> [[alternative HTML version deleted]] >> >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > > > -- > > Bert Gunter > Genentech Nonclinical Biostatistics > > Internal Contact Info: > Phone: 467-7374 > Website: > http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Steve Lianoglou Computational Biologist Bioinformatics and Computational Biology Genentech ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.