我有一个像这样的矩阵:
实际上只有数百或数千个值。
我需要做的是返回每行的最小值以及行/列名称。
因此对于示例中的第1行“BAC”,BAC / CSCO的最小值为0.92,因此我需要返回类似的内容:
BAC / CSCO 0.92
然后对矩阵中的每一行重复此操作。
非常感谢协助。我认为申请是诀窍,但我无法得到正确的组合。
答案 0 :(得分:15)
X <- matrix(runif(20), nrow=4)
rownames(X) <- paste0("foo", seq(nrow(X)))
colnames(X) <- paste0("bar", seq(ncol(X)))
result <- t(sapply(seq(nrow(X)), function(i) {
j <- which.min(X[i,])
c(paste(rownames(X)[i], colnames(X)[j], sep='/'), X[i,j])
}))
print(X)
print(result)
会给你:
bar1 bar2 bar3 bar4 bar5
foo1 0.2085419 0.6290522 0.12730378 0.17775105 0.3239684
foo2 0.8061464 0.7948392 0.09330563 0.06698921 0.5557932
foo3 0.1790950 0.7788139 0.35787944 0.39117325 0.2578457
foo4 0.9099254 0.4048508 0.54791272 0.38674301 0.3272156
和
[,1] [,2]
[1,] "foo1/bar3" "0.127303782384843"
[2,] "foo2/bar4" "0.0669892099685967"
[3,] "foo3/bar1" "0.179094966035336"
[4,] "foo4/bar5" "0.327215566998348"
答案 1 :(得分:3)
或apply()
#CREATE THE DATA
df<-data.frame(matrix(data=round(x=rnorm(100,10,1),digits=3),nrow=10),
row.names=c("A","B","C","D","E","F","G","H","I","J"))
colnames(df)<-c("AD","BD","CD","DD","ED","FD","GD","HD","ID","JD")
#RUN THROUGH THE DF
mins<-apply(df,2,function(x)return(array(which.min(x))))
mins<-data.frame(col=names(mins),row=mins)
df$mins<-apply(mins,1,FUN=function(x)return(paste(x["col"],
rownames(df[as.numeric(x["row"]),]),
df[as.numeric(x["row"]),x["col"]],
sep="/")))
> df
AD BD CD DD ED FD GD HD ID JD mins
A 9.292 11.568 10.489 9.512 7.755 8.545 9.989 9.660 9.240 9.913 AD/G/8.477
B 11.972 11.297 9.221 10.936 8.665 9.154 10.620 8.335 11.149 11.382 BD/F/7.588
C 9.910 9.762 11.744 8.938 11.283 8.750 8.719 10.929 9.158 10.168 CD/G/8.481
D 9.986 8.776 9.922 9.016 10.691 10.667 9.876 11.417 10.391 10.823 DD/C/8.938
E 8.877 9.672 9.024 10.424 9.033 8.709 10.176 9.937 10.891 9.779 ED/A/7.755
F 8.656 7.588 10.071 9.549 8.654 7.965 11.693 9.019 8.665 8.971 FD/F/7.965
G 8.477 9.686 8.481 10.925 11.034 12.021 10.642 11.087 10.398 9.989 GD/C/8.719
H 9.578 11.660 10.864 9.801 9.188 11.006 11.282 10.139 9.888 8.775 HD/B/8.335
I 11.361 10.131 10.502 11.195 11.802 10.817 10.141 9.614 10.676 7.404 ID/F/8.665
J 11.754 11.096 9.645 10.496 11.772 9.336 8.887 11.124 9.211 11.169 JD/I/7.404