我有这样的数据集:
Date Tank Time Female.in.Middle Female.in.R.assoc Female.in.L.assoc R.side.of.divider
96 16-May I3 1045 0.6080 0.0646 0.2561 0.0000
97 16-May I3 215 0.5583 0.4210 0.0058 0.0000
100 17-May I3 115 0.5190 0.3346 0.1381 0.0000
102 21-May I3 1030 0.2184 0.3120 0.1335 0.3256
104 30-May I3 1045 0.0092 0.0520 0.2067 0.0000
106 31-May I3 1045 0.0000 0.0000 0.0000 0.0000
L.side.of.Divider Tank.1 Date.Entered M.L.name Male.L.Length Male.L.Weight M.R.name
96 0.0655 I3 15-May green 2 7.8 16.67 pink 1
97 0.0000 I3 15-May green 2 7.8 16.67 pink 1
100 0.0000 I3 15-May green 2 7.8 16.67 pink 1
102 0.0000 I3 15-May green 2 7.8 16.67 pink 1
104 0.6652 I3 15-May green 2 7.8 16.67 pink 1
106 0.9767 I3 15-May green 2 7.8 16.67 pink 1
Male.R.Length Male.R.Weight Side.of.Spawn F.Length F.Weight F.name last.female.spawn.date
96 7.8 20.99 L 4.3 2.84 1c 5-May
97 7.8 20.99 L 4.3 2.84 1c 5-May
100 7.8 20.99 L 4.3 2.84 1c 5-May
102 7.8 20.99 L 4.3 2.84 1c 5-May
104 7.8 20.99 L 4.3 2.84 1c 5-May
106 7.8 20.99 L 4.3 2.84 1c 5-May
spawn.date.in.paradigm X d.in.p dbs X.1 X.2 X.3
96 29-May 1 13 NA NA NA
97 29-May 1 13 NA NA NA
100 29-May 2 12 NA NA NA
102 29-May 6 8 NA NA NA
104 29-May 15 -1 NA NA NA
106 29-May 16 -2 NA NA NA
使用cbind()函数创建一个总计:
rside1c<-cbind(jd1c$Female.in.R.assoc + jd1c$R.side.of.divider)
lside1c<-cbind(jd1c$Female.in.L.assoc + jd1c$L.side.of.Divider)
我想使用rbind()来创建一个表,但它只是将它们放在一起就像一个列表..如果我用rside1c和lside1c的值创建向量,那么它工作得很好..我想跳过此步骤..如何更改此数据才能正常工作?
而不是这个: [,1]
[1,] 0.0646
[2,] 0.4210
[3,] 0.3346
[4,] 0.6376
[5,] 0.0520
[6,] 0.0000
[7,] 0.3216
[8,] 0.0058
[9,] 0.1381
[10,] 0.1335
[11,] 0.8719
[12,] 0.9767
我想这样:
[,1] [,2] [,3] [,4] [,5] [,6]
vr 0.0646 0.4210 0.3346 0.6376 0.0520 0.0000
vl 0.3216 0.0058 0.1381 0.1335 0.8719 0.9767
不这样做:
vr<-c(.0646, .4210, .3346, .6376, .0520, .0)
vl<-c(.3216, .0058, .1381, .1335, .8719, .9767)
tab1<-rbind(vr, vl)
谢谢
答案 0 :(得分:0)
您可以使用t
功能
dat <- data.frame(vr, vl)
dat
# vr vl
#1 0.0646 0.3216
#2 0.4210 0.0058
#3 0.3346 0.1381
#4 0.6376 0.1335
#5 0.0520 0.8719
#6 0.0000 0.9767
t(dat)
# [,1] [,2] [,3] [,4] [,5] [,6]
#vr 0.0646 0.4210 0.3346 0.6376 0.0520 0.0000
#vl 0.3216 0.0058 0.1381 0.1335 0.8719 0.9767