[R] Sorting of columns of a matrix
arun
smartpink111 at yahoo.com
Wed Aug 29 17:56:40 CEST 2012
HI,
I guess this might be what you want.
dat1<-structure(c(0.585528817843856, 0.709466017509524, 0, -0.453497173462763,
0.605887455840393, -1.81795596770373, 0.630098551068391,
-0.276184105225216,
-0.284159743943371, -0.919322002474128, -0.116247806352002,
1.81731204370422,
0.370627864257954, 0.520216457554957, -0.750531994502331,
0.816899839520583,
-0.886357521243213, -0.331577589942552, 1.12071265166956,
0.298723699267293,
0.779621924555324, 0, -0.644328429231302, -1.55313740522969,
-1.59770951669631, 1.80509751881082, -0.481647363694637, 0.620379801298422,
0.612123492650849, -0.162310976918126, 0.81187317855386, 2.19683354634753,
2.04919033740619, 1.63244563948047, 0.254271192814055, 0.491188279272559,
-0.324086578737118, -1.66205024385863, 1.76773385087297, 0,
1.12851083359018,
-2.38035806139704, -1.06026555215253, 0.937140540182908, 0.854451720330554,
1.46072940310409, -1.4130987778892, 0.567403253424482, 0.583187653435685,
-1.30679883346442), .Dim = c(5L, 10L))
colnames(dat1)<-paste0("x",1:10)
dat2<-apply(dat1,2,sort,decreasing=TRUE)
dat2[-which(rowSums(dat2==0)>0),]
# x1 x2 x3 x4 x5 x6 x7
#[1,] 0.7094660 0.6300986 1.817312 1.1207127 0.7796219 1.8050975 2.1968335
#[2,] -0.4534972 -1.8179560 -0.750532 -0.8863575 -1.5977095 -0.4816474 0.2542712
# x8 x9 x10
#[1,] 1.767734 1.128511 1.460729
#[2,] -1.662050 -2.380358 -1.413099
A.K.
----- Original Message -----
From: Nico Met <nicomet80 at gmail.com>
To: r-help at r-project.org
Cc:
Sent: Wednesday, August 29, 2012 9:24 AM
Subject: [R] Sorting of columns of a matrix
Dear all,
Please suggest me how can I do it.
I have a matrix which look like following:
x1 x2 x3 t1 .01 0.3 0 t2 0 0.1 0.01 t3 0 .01 .01 t4 0 0 t5 5 0 0 t6
0 0 0 t7 0 0 0 t8 0 0 0 t9 0.6 0 0 t10 0 0 0.66 t11 0 0.6 0.11 t12 0
0.4 0
I want to sort decreasing order in each column based on rows. and then to
display only those rows which has a value. The expected out put matrix will
look like
x1 x2 x3 t9 0.6 t11 0.6 t10 0.66 t1 .01 t12 0.4 t11 0.11 t1 0.3 t2 .01
t2 0.1 t3 .01
many thanks
Nico
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