[R] First time r user
Bert Gunter
gunter.berton at gene.com
Sun Aug 18 16:22:17 CEST 2013
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.dub at 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 <paulbernal07 at 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.steve at gene.com>
>> escribió:
>>
>> > Hi Paul,
>> >
>> > On Sun, Aug 18, 2013 at 12:56 AM, Paul Bernal <paulbernal07 at 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.steve at 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 <paulbernal07 at 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 at 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 at 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 at 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
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