如何把列表轉化為整齊的矩陣？

mylist<-as.list(iris[,1:4])
result<-sapply(mylist,mean)
result<-lapply(mylist,mean)
#結果
【1】Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
    5.843333     3.057333     3.758000     1.199333 
【2】 $Sepal.Length
[1] 5.843333

$Sepal.Width
[1] 3.057333

$Petal.Length
[1] 3.758
 


$Petal.Width
[1] 1.199333

由上可以發現兩個的輸出型別是不一樣的。【1】是向量，【2】是list.

將list轉化為matrix的操作：

#第一種是先轉成資料框，再轉置
t(as.data.frame(result))
class(A)
[1] "matrix"
#第二種是使用取子集的二元操作符作為sapply的引數
t(sapply(result,'['))
#將result傳入rbind
do.call('rbind',result)
class(C)
[1] "matrix"

常用的函式：

1.tapply()用法：

tapply(X, INDEX, FUN = NULL
 
, ..., default = NA, simplify = TRUE）
#INDEX 為因子（分類變數）

例：

tapply(X=iris$Sepal.Length,INDEX=list(iris$Species),FUN=mean)
#結果
setosa versicolor  virginica 
     5.006      5.936      6.588 

2.類似的函aggregate()

aggregate(x, by, FUN, ..., simplify = TRUE, drop = TRUE)
#x為資料框

例子用這兩個函式簡寫就是：

with(iris,tapply(Sepal.Length,list(Species)
 
,mean))
with(iris,aggregate(Sepal.Length,by=list(Species),mean))
#僅輸出資料結構不一樣，aggregate更加友好，為資料框

3.mapply()函式

mapply(FUN, ..., MoreArgs = NULL, SIMPLIFY = TRUE，USE.NAMES = TRUE)
#兩個引數都要變化，可以用它

例：

 mapply(rep, 1:4, 4:1)
[[1]]
[1] 1 1 1 1

[[2]]
[1] 2 2 2

[[3]]
[1] 3 3

[[4]]
[1] 4

4.outer()函式，類似矩陣計算中的外積，直接對兩個數相乘

outer(X, Y, FUN = "*", ...)
*函數可以自定義
例：
outer(month.abb, 1999:2003, FUN = "paste")
 [,1]       [,2]       [,3]       [,4]       [,5]      
 [1,] "Jan 1999" "Jan 2000" "Jan 2001" "Jan 2002" "Jan 2003"
 [2,] "Feb 1999" "Feb 2000" "Feb 2001" "Feb 2002" "Feb 2003"
 [3,] "Mar 1999" "Mar 2000" "Mar 2001" "Mar 2002" "Mar 2003"
 [4,] "Apr 1999" "Apr 2000" "Apr 2001" "Apr 2002" "Apr 2003"
 [5,] "May 1999" "May 2000" "May 2001" "May 2002" "May 2003"
 [6,] "Jun 1999" "Jun 2000" "Jun 2001" "Jun 2002" "Jun 2003"
 [7,] "Jul 1999" "Jul 2000" "Jul 2001" "Jul 2002" "Jul 2003"
 [8,] "Aug 1999" "Aug 2000" "Aug 2001" "Aug 2002" "Aug 2003"
 [9,] "Sep 1999" "Sep 2000" "Sep 2001" "Sep 2002" "Sep 2003"
[10,] "Oct 1999" "Oct 2000" "Oct 2001" "Oct 2002" "Oct 2003"
[11,] "Nov 1999" "Nov 2000" "Nov 2001" "Nov 2002" "Nov 2003"
[12,] "Dec 1999" "Dec 2000" "Dec 2001" "Dec 2002" "Dec 2003"
#例如用其生成九九乘法表
f<-function(x,y){
    left<-paste0(x,"*",y,"=")
    right<-x*y
    re<-paste0(left,right)
    return(re)
}
vec1<-vec2<-vec
outer(vec1,vec2,FUN=f)
#結果
    [,1]    [,2]     [,3]     [,4]     [,5]     [,6]     [,7]     [,8]     [,9]    
 [1,] "1*1=1" "1*2=2"  "1*3=3"  "1*4=4"  "1*5=5"  "1*6=6"  "1*7=7"  "1*8=8"  "1*9=9" 
 [2,] "2*1=2" "2*2=4"  "2*3=6"  "2*4=8"  "2*5=10" "2*6=12" "2*7=14" "2*8=16" "2*9=18"
 [3,] "3*1=3" "3*2=6"  "3*3=9"  "3*4=12" "3*5=15" "3*6=18" "3*7=21" "3*8=24" "3*9=27"
 [4,] "4*1=4" "4*2=8"  "4*3=12" "4*4=16" "4*5=20" "4*6=24" "4*7=28" "4*8=32" "4*9=36"
 [5,] "5*1=5" "5*2=10" "5*3=15" "5*4=20" "5*5=25" "5*6=30" "5*7=35" "5*8=40" "5*9=45"
 [6,] "6*1=6" "6*2=12" "6*3=18" "6*4=24" "6*5=30" "6*6=36" "6*7=42" "6*8=48" "6*9=54"
 [7,] "7*1=7" "7*2=14" "7*3=21" "7*4=28" "7*5=35" "7*6=42" "7*7=49" "7*8=56" "7*9=63"
 [8,] "8*1=8" "8*2=16" "8*3=24" "8*4=32" "8*5=40" "8*6=48" "8*7=56" "8*8=64" "8*9=72"
 [9,] "9*1=9" "9*2=18" "9*3=27" "9*4=36" "9*5=45" "9*6=54" "9*7=63" "9*8=72" "9*9=81"

outer()在3d作圖中的應用。

f<-function(x,y,z) x^2-10*cos(2*pi*x)+y^2+10*cos(2*pi*y)+20
x<-y<-seq(-5,5,0.01)
z<-outer(x,y,f)
image(x,y,z)
Z<-rank(z)
library(rgl)
bg3d("slategray")#設定背景色
persp3d(x,y,z,col=rainbow(as.integer(max(Z)))[Z])
play3d(spin3d())