Hi,
I tried this method but it seems that there is something wrong with my
data frame:
when I type in:
> qplot(x=as.factor(Categorie),y=Total,data=mydata)
It displays a graph with 2 points in each category...
but if I add the parameter geom="histogram"
> qplot(x=as.factor(Categorie),y=Total,data=mydata,geom="histogram")
Error in storage.mode(test) <- "logical" :
object "y" not found
any hint about this...
thx, Stéphane.
========================================================
the real data frame
Categorie Part
Total chr1 chr2 pl
1 Amino acid biosynthesis common
3.03 4.55 1.68 0.00
2 Purines, pyrimidines, nucleosides, and nucleotides common
1.65 2.37 1.06 0.00
3 Fatty acid and phospholipid metabolism common
1.52 1.77 1.55 0.00
4 Biosynthesis of cofactors, prosthetic groups, and carriers common
2.85 4.68 1.02 0.00
5 Central intermediary metabolism common
3.40 3.19 4.57 0.00
6 Energy metabolism common
11.81 12.49 13.87 0.17
7 Transport and binding proteins common
10.51 13.56 7.85 4.27
8 DNA metabolism common
1.95 2.81 0.98 1.03
9 Transcription common
2.08 3.13 1.06 0.34
10 Protein synthesis common
2.51 4.58 0.27 0.00
11 Protein fate common
2.23 3.26 1.20 0.68
12 Regulatory functions common
7.63 7.30 9.88 0.68
13 Signal transduction common
1.88 2.06 2.13 0.00
14 Cell envelope common
2.76 3.41 2.53 0.17
15 Cellular processes common
7.21 7.90 7.71 1.54
16 Mobile and extrachromosomal element functions common
1.08 0.22 0.40 8.38
17 Unknown function common
20.75 22.45 22.38 5.30
18 Amino acid biosynthesis specific
0.35 0.16 0.71 0.00
19 Purines, pyrimidines, nucleosides, and nucleotides specific
0.17 0.06 0.35 0.00
20 Fatty acid and phospholipid metabolism specific
0.08 0.09 0.09 0.00
21 Biosynthesis of cofactors, prosthetic groups, and carriers specific
0.18 0.19 0.22 0.00
22 Central intermediary metabolism specific
0.42 0.09 0.98 0.00
23 Energy metabolism specific
2.05 0.70 3.90 2.22
24 Transport and binding proteins specific
1.98 0.85 3.24 3.25
25 DNA metabolism specific
0.63 0.22 0.22 4.44
26 Transcription specific
0.17 0.06 0.22 0.51
27 Protein synthesis specific
0.20 0.03 0.49 0.00
28 Protein fate specific
0.30 0.32 0.31 0.17
29 Regulatory functions specific
1.58 0.66 2.79 1.88
30 Signal transduction specific
0.27 0.06 0.62 0.00
31 Cell envelope specific
0.83 0.63 1.33 0.00
32 Cellular processes specific
1.38 0.38 1.95 4.62
33 Mobile and extrachromosomal element functions specific
3.56 1.14 0.44 28.72
34 Unknown function specific
11.63 6.17 16.00 24.27
Domenico Vistocco wrote:
> Perhaps this could be useful:
> > x=scan()
> 11.81 10.51 1.95 2.08 2.51 2.05 1.98 0.63 0.17 0.20
> 12.49 13.56 2.81 3.13 4.58 0.70 0.85 0.22 0.06 0.03
>
> > x=matrix(x,5,4,byrow=T)
> > rownames(x)=paste("comp",1:5,sep="")
> > colnames(x)=paste("c",1:4,sep="")
>
> > library(ggplot2)
> > dfm=melt(x)
> > qplot(as.factor(x=X1),y=value,geom="histogram",data=dfm,fill=X2)
>
> domenico vistocco
>
> Stéphane CRUVEILLER wrote:
>> Dear R-Users,
>>
>> I would like to know whether it is possible to draw several
>> stacked barplots (i.e. side by side on the same sheet)...
>>
>>
>> my data look like :
>>
>> Cond1 Cond1' Cond2 Cond2'
>> Compartment 1 11,81 2,05 12,49 0,70 Compartment 2
>> 10,51 1,98 13,56 0,85
>> Compartment 3 1,95 0,63 2,81 0,22 Compartment 4
>> 2,08 0,17 3,13 0,06 Compartment 5 2,51 0,20
>> 4,58 0,03
>>
>> ps: Cond1' values should be stacked on Cond1, Cond2' on Cond 2 and so
>> on... and series 1 and 2
>> should be side by side for each compartement....
>>
>> Thanks for any help.
>>
>> Stéphane.
>>
>>
>
--
"La science a certes quelques magnifiques réussites à son actif mais
à tout prendre, je préfère de loin être heureux plutôt qu'avoir raison."
D. Adams
--
AGC website <http://www.genoscope.cns.fr/agc>
Stéphane CRUVEILLER Ph. D.
Genoscope - Centre National de Séquencage
Atelier de Génomique Comparative
2, Rue Gaston Cremieux CP 5706
91057 Evry Cedex - France
Phone: +33 (0)1 60 87 84 58
Fax: +33 (0)1 60 87 25 14
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