HI,
I also have no trouble in reading the example data you gave, which BTW do not
have any duplicate rownames. I guess there must be some rows in the original
dataset that must be repeated. For example:
comb_model<-read.table(text="
Estimate Std.Error tvalue Pr(>|t|)
(Intercept) 3.593793 0.012537 286.656 0.000000000
as.factor(dow)1 0.027378 0.007348 3.726 0.000196109
as.factor(dow)2 0.034211 0.007348 4.656 0.000003288
as.factor(dow)3 0.013481 0.007393 1.823 0.068281371
as.factor(dow)4 0.020708 0.007358 2.814 0.004903774
as.factor(dow)5 0.030164 0.007327 4.117 0.000038886
as.factor(dow)6 0.021723 0.007327 2.965 0.003039448
as.factor(dow)6 0.021723 0.007327 2.965 0.003039448
as.factor(fluepi) 0.044272 0.014697 3.012 0.002601912
o3max 0.003441 0.001723 1.998 0.045785798
o3max 0.004881 0.00281 1.885 0.00540889
",sep="",header=TRUE,row.names=NULL)
#here there are two types of repeats, rownames only repeated (o3max) and whole
rows repeated (as.factor(dow)6)
#If I wanted to delete the repeated rows.
comb_model2<-unique(comb_model[duplicated(comb_model)|duplicated(comb_model,fromLast=TRUE),])
comb_model3<-rbind(comb_model[!(duplicated(comb_model)|duplicated(comb_model,fromLast=TRUE)),],comb_model2)
mat2<-as.matrix(comb_model3[,2:5]) #matrix can have repeated rownames
row.names(mat2)<-comb_model3[,1]
#changing repeated rownames to unique rownames
mat3<-mat2[duplicated(rownames(mat2))|duplicated(rownames(mat2),fromLast=TRUE),]
rownames(mat3)<-paste(rownames(mat3),letters[1:nrow(mat3)],sep="")
mat4<-mat2[!(duplicated(rownames(mat2))|duplicated(rownames(mat2),fromLast=TRUE)),]
library(plyr)
comb_model4<-join(as.data.frame(mat4),as.data.frame(mat3),type="full")
rownames(comb_model4)<-c(rownames(mat4),rownames(mat3))
#instead of join(), you could use ?merge()
#comb_model4<-merge(as.data.frame(mat4),as.data.frame(mat3),all=TRUE,sort=FALSE)
#rownames(comb_model4)<-c(rownames(mat4),rownames(mat3))colnames(comb_model4)[4]<-"Pr(>|t|)"
comb_model4
# Estimate Std.Error tvalue Pr(>|t|)
#(Intercept) 3.593793 0.012537 286.656 0.000000000
#as.factor(dow)1 0.027378 0.007348 3.726 0.000196109
#as.factor(dow)2 0.034211 0.007348 4.656 0.000003288
#as.factor(dow)3 0.013481 0.007393 1.823 0.068281371
#as.factor(dow)4 0.020708 0.007358 2.814 0.004903774
#as.factor(dow)5 0.030164 0.007327 4.117 0.000038886
#as.factor(fluepi) 0.044272 0.014697 3.012 0.002601912
#as.factor(dow)6 0.021723 0.007327 2.965 0.003039448
#o3maxa 0.003441 0.001723 1.998 0.045785798
#o3maxb 0.004881 0.002810 1.885 0.005408890
#Another way will be to use
?rbind() comb_model4<-rbind(as.data.frame(mat4),as.data.frame(mat3)) # no need
colnames(comb_model4)[4]<-"Pr(>|t|)"
A.K.
----- Original Message -----
From: PavloEs <nici...@gmail.com>
To: r-help@r-project.org
Cc:
Sent: Monday, November 12, 2012 10:45 AM
Subject: [R] Matrix to data frame conversion
I have a matrix which I wanted to convert to a data frame. As I could not
succeed and resorted to export to csv and reimport it again. Why did I fail
in the attempt and how can I achieve what I wanted without this
roundabouts?
The original matrix:
> str(comb_model0)
num [1:90, 1:4] 3.5938 0.0274 0.0342 0.0135 0.0207 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:90] "(Intercept)" "as.factor(dow)1" "as.factor(dow)2"
"as.factor(dow)3" ...
..$ : chr [1:4] "Estimate" "Std. Error" "t value" "Pr(>|t|)"
> dim(comb_model0)
[1] 90 4
> class(comb_model0)
[1] "matrix"
>
>
> head(comb_model0,10)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.593793 0.012537 286.656 0.000000000
as.factor(dow)1 0.027378 0.007348 3.726 0.000196109
as.factor(dow)2 0.034211 0.007348 4.656 0.000003288
as.factor(dow)3 0.013481 0.007393 1.823 0.068281371
as.factor(dow)4 0.020708 0.007358 2.814 0.004903774
as.factor(dow)5 0.030164 0.007327 4.117 0.000038886
as.factor(dow)6 0.021723 0.007327 2.965 0.003039448
as.factor(fluepi) 0.044272 0.014697 3.012 0.002601912
o3max 0.003441 0.001723 1.998 0.045785798
One of the many conversion attempts:
> xx<-as.data.frame(comb_model0)
> xx
Error in data.frame(Estimate = c(" 3.59379258", " 0.02737812", "
0.03421067", :
duplicate row.names: (Intercept), as.factor(dow)1, as.factor(dow)2,
as.factor(dow)3, as.factor(dow)4, as.factor(dow)5, as.factor(dow)6,
as.factor(fluepi)
write.csv(comb_model0, "test.csv")
test<-read.csv("test.csv")
class(test)
[1] "data.frame"
> dim(test)
[1] 90 5
head(test,9)
X Estimate Std..Error t.value
Pr...t..
1 (Intercept) 3.59379258 0.012537 286.65611
0.000000000
2 as.factor(dow)1 0.02737812 0.007348 3.72596
0.000196109
3 as.factor(dow)2 0.03421067 0.007348 4.65575
0.000003288
4 as.factor(dow)3 0.01348142 0.007393 1.82343
0.068281371
5 as.factor(dow)4 0.02070761 0.007358 2.81419
0.004903774
6 as.factor(dow)5 0.03016411 0.007327 4.11665
0.000038886
7 as.factor(dow)6 0.02172334 0.007327 2.96476
0.003039448
8 as.factor(fluepi) 0.04427231 0.014697 3.01232 0.002601912
9 o3max 0.00344111 0.001723 1.99772
0.045785798
--
View this message in context:
http://r.789695.n4.nabble.com/Matrix-to-data-frame-conversion-tp4649311.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
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.
______________________________________________
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.
