would you know how would I extract from my original data frame, just
these unique rows?
because this gives me only those 3 columns, and I want all columns
from the original data frame
> head(udt)
chr pos gene_id
1 chr1 54490 ENSG00000227232
2 chr1 58814 ENSG00000227232
3 chr1 60351 ENSG00000227232
4 chr1 61920 ENSG00000227232
5 chr1 63671 ENSG00000227232
6 chr1 64931 ENSG00000227232
> head(dt)
chr pos gene_id pval_nominal pval_ret wl wr META
1: chr1 54490 ENSG00000227232 0.608495 0.783778 31.62278 21.2838 0.7475480
2: chr1 58814 ENSG00000227232 0.295211 0.897582 31.62278 21.2838 0.6031214
3: chr1 60351 ENSG00000227232 0.439788 0.867959 31.62278 21.2838 0.6907182
4: chr1 61920 ENSG00000227232 0.319528 0.601809 31.62278 21.2838 0.4032200
5: chr1 63671 ENSG00000227232 0.237739 0.988039 31.62278 21.2838 0.7482519
6: chr1 64931 ENSG00000227232 0.276679 0.907037 31.62278 21.2838 0.5974800
On Fri, Nov 8, 2019 at 9:30 AM Ana Marija <sokovic.anamar...@gmail.com> wrote:
>
> Thank you so much! Converting it to data frame resolved the issue!
>
> On Fri, Nov 8, 2019 at 9:19 AM Gerrit Eichner
> <gerrit.eich...@math.uni-giessen.de> wrote:
> >
> > It seems as if dt is not a (base R) data frame but a
> > data table. I assume, you will have to transform dt
> > into a data frame (maybe with as.data.frame) to be
> > able to apply unique in the suggested way. However,
> > I am not familiar with data tables. Perhaps somebody
> > else can provide a more profound guess.
> >
> > Regards -- Gerrit
> >
> > ---------------------------------------------------------------------
> > Dr. Gerrit Eichner Mathematical Institute, Room 212
> > gerrit.eich...@math.uni-giessen.de Justus-Liebig-University Giessen
> > Tel: +49-(0)641-99-32104 Arndtstr. 2, 35392 Giessen, Germany
> > http://www.uni-giessen.de/eichner
> > ---------------------------------------------------------------------
> >
> > Am 08.11.2019 um 16:02 schrieb Ana Marija:
> > > I tried it but I got this error:
> > >> udt <- unique(dt[c("chr", "pos", "gene_id")])
> > > Error in `[.data.table`(dt, c("chr", "pos", "gene_id")) :
> > > When i is a data.table (or character vector), the columns to join by
> > > must be specified using 'on=' argument (see ?data.table), by keying x
> > > (i.e. sorted, and, marked as sorted, see ?setkey), or by sharing
> > > column names between x and i (i.e., a natural join). Keyed joins might
> > > have further speed benefits on very large data due to x being sorted
> > > in RAM.
> > >
> > > On Fri, Nov 8, 2019 at 8:58 AM Gerrit Eichner
> > > <gerrit.eich...@math.uni-giessen.de> wrote:
> > >>
> > >> Hi, Ana,
> > >>
> > >> doesn't
> > >>
> > >> udt <- unique(dt[c("chr", "pos", "gene_id")])
> > >> nrow(udt)
> > >>
> > >> get close to what you want?
> > >>
> > >> Hth -- Gerrit
> > >>
> > >> ---------------------------------------------------------------------
> > >> Dr. Gerrit Eichner Mathematical Institute, Room 212
> > >> gerrit.eich...@math.uni-giessen.de Justus-Liebig-University Giessen
> > >> Tel: +49-(0)641-99-32104 Arndtstr. 2, 35392 Giessen, Germany
> > >> http://www.uni-giessen.de/eichner
> > >> ---------------------------------------------------------------------
> > >>
> > >> Am 08.11.2019 um 15:38 schrieb Ana Marija:
> > >>> Hello,
> > >>>
> > >>> I have a data frame like this:
> > >>>
> > >>>> head(dt,20)
> > >>> chr pos gene_id pval_nominal pval_ret wl
> > >>> wr
> > >>> 1: chr1 54490 ENSG00000227232 0.6084950 0.7837780 31.62278
> > >>> 21.2838
> > >>> 2: chr1 58814 ENSG00000227232 0.2952110 0.8975820 31.62278
> > >>> 21.2838
> > >>> 3: chr1 60351 ENSG00000227232 0.4397880 0.8679590 31.62278
> > >>> 21.2838
> > >>> 4: chr1 61920 ENSG00000227232 0.3195280 0.6018090 31.62278
> > >>> 21.2838
> > >>> 5: chr1 63671 ENSG00000227232 0.2377390 0.9880390 31.62278
> > >>> 21.2838
> > >>> 6: chr1 64931 ENSG00000227232 0.2766790 0.9070370 31.62278
> > >>> 21.2838
> > >>> 7: chr1 81587 ENSG00000227232 0.6057930 0.6167630 31.62278
> > >>> 21.2838
> > >>> 8: chr1 115746 ENSG00000227232 0.4078770 0.7799110 31.62278
> > >>> 21.2838
> > >>> 9: chr1 135203 ENSG00000227232 0.4078770 0.9299130 31.62278
> > >>> 21.2838
> > >>> 10: chr1 138593 ENSG00000227232 0.8464560 0.5696060 31.62278 21.2838
> > >>>
> > >>> it is very big,
> > >>>> dim(dt)
> > >>> [1] 73719122 8
> > >>>
> > >>> To count number of unique rows for all 3 columns: chr, pos and gene_id
> > >>> I could just join those 3 columns and than count. But how would I find
> > >>> unique number of rows for these 4 columns without joining them?
> > >>>
> > >>> Thanks
> > >>> Ana
> > >>>
> > >>> ______________________________________________
> > >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > >>> 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.
> > >>>
> > >>
> > >> ______________________________________________
> > >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > >> 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.
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