R語言里面的因子

R語言中的因子確實(shí)不好理解，很多人都這么覺得。在R語言中，因子（factor）表示的是一個(gè)符號(hào)、一個(gè)編號(hào)或者一個(gè)等級(jí)，即，一個(gè)點(diǎn)。例如，人的個(gè)數(shù)可以是1，2，3，4......那么因子就包括，1，2，3，4.....還有統(tǒng)計(jì)量的水平的時(shí)候用到的高、中、低，也是因子，因?yàn)樗且粋€(gè)點(diǎn)。與之區(qū)別的向量，是一個(gè)連續(xù)性的值，例如，數(shù)值中有1，1.1，1.2......可以作為數(shù)值來計(jì)算，而因子則不可以。如果用我自己的理解，簡(jiǎn)單通俗來講：因子是一個(gè)點(diǎn)，向量是一個(gè)有方向的范圍。在R中，如果把數(shù)字作為因子，那么在導(dǎo)入數(shù)據(jù)之后，需要將向量轉(zhuǎn)換為因子（factor），而因子在整個(gè)計(jì)算過程中不再作為數(shù)值，而是一個(gè)"符號(hào)"而已。因子的水平就是因子的所有不相同的符號(hào)的集合。
創(chuàng)建因子的函數(shù)介紹如下：

factor(x, levels = sort(unique(x), na.last = TRUE),
labels = levels, exclude = NA, ordered = is.ordered(x))

levels 用來指定因子可能的水平（缺省值是向量x中互異的值）；labels
用來指定水平的名字；exclude表示從向量x中剔除的水平值；ordered是
一個(gè)邏輯型選項(xiàng)用來指定因子的水平是否有次序?；叵霐?shù)值型或字符型
的x。

> factor(1:3)
[1] 1 2 3
Levels: 1 2 3
> factor(1:3, levels=1:5)
[1] 1 2 3
Levels: 1 2 3 4 5
> factor(1:3, labels=c("A", "B", "C"))
[1] A B C
Levels: A B C
> factor(1:5, exclude=4)
[1] 1 2 3 NA 5
Levels: 1 2 3 5

函數(shù)levels用來提取一個(gè)因子中可能的水平值：

> f <- factor(c(2, 4), levels=2:5) > f
[1] 2 4
Levels: 2 3 4 5
> levels(f)
[1] "2" "3" "4" "5"

因子用來存儲(chǔ)類別變量(categorical variables)和有序變量，這類變量不能用來計(jì)算而只能用來分類或者計(jì)數(shù)。因子表示分類變量，有序因子表示有序變量。生成因子數(shù)據(jù)對(duì)象的函數(shù)是factor(),語法是factor(data, levels, labels, ...)，其中data是數(shù)據(jù)，levels是因子水平向量，labels是因子的標(biāo)簽向量。
1、創(chuàng)建一個(gè)因子。
例1：

>colour <- c('G', 'G', 'R', 'Y', 'G', 'Y', 'Y', 'R', 'Y') 
>col <- factor(colour) 
>col1 <- factor(colour, levels = c('G', 'R', 'Y'), labels = c('Green', 'Red', 'Yellow')) #labels的內(nèi)容替換colour相應(yīng)位置對(duì)應(yīng)levels的內(nèi)容 
>col2 <- factor(colour, levels = c('G', 'R', 'Y'), labels = c('1', '2', '3')) 
>col_vec <- as.vector(col2) #轉(zhuǎn)換成字符向量 
>col_num <- as.numeric(col2) #轉(zhuǎn)換成數(shù)字向量 
>col3 <- factor(colour, levels = c('G', 'R'))

2、創(chuàng)建一個(gè)有序因子。
例1：

>score <- c('A', 'B', 'A', 'C', 'B') 
>score1 <- ordered(score, levels = c('C', 'B', 'A')); 
>score1
[1] A B A C B
Levels: C < B < A

3、用cut()函數(shù)將一般的數(shù)據(jù)轉(zhuǎn)換成因子或有序因子。
例1：

>exam <- c(98, 97, 52, 88, 85, 75, 97, 92, 77, 74, 70, 63, 97, 71, 98, 65, 79, 74, 58, 59, 60, 63, 87, 82, 95, 75, 79, 96, 50, 88) 
>exam1 <- cut(exam, breaks = 3) #切分成3組 >exam1
[1] (82,98] (82,98] (50,66] (82,98] (82,98] (66,82] (82,98] (82,98] (66,82]
[10] (66,82] (66,82] (50,66] (82,98] (66,82] (82,98] (50,66] (66,82] (66,82]
[19] (50,66] (50,66] (50,66] (50,66] (82,98] (66,82] (82,98] (66,82] (66,82]
[28] (82,98] (50,66] (82,98]
Levels: (50,66] (66,82] (82,98]
>exam2 <- cut(exam, breaks = c(0, 59, 69, 79, 89, 100)) #切分成自己設(shè)置的組 
> exam2
[1] (89,100] (89,100] (0,59]   (79,89]  (79,89]  (69,79]  (89,100] (89,100]
[9] (69,79]  (69,79]  (69,79]  (59,69]  (89,100] (69,79]  (89,100] (59,69]
[17] (69,79]  (69,79]  (0,59]   (0,59]   (59,69]  (59,69]  (79,89]  (79,89]
[25] (89,100] (69,79]  (69,79]  (89,100] (0,59]   (79,89]
Levels: (0,59] (59,69] (69,79] (79,89] (89,100]
>attr(exam1, 'levels');
[1] "(50,66]" "(66,82]" "(82,98]"
>attr(exam2, 'levels');
[1] "(0,59]"   "(59,69]"  "(69,79]"  "(79,89]"  "(89,100]"
>attr(exam2, 'class')
[1] "factor"
#一個(gè)有序因子
> x <- factor(rep(1:5,3)) 
> ordered(x,labels = c('a1','a2','a3','a4','a5'))
[1] a1 a2 a3 a4 a5 a1 a2 a3 a4 a5 a1 a2 a3 a4 a5
Levels: a1 < a2 < a3 < a4 < a5

關(guān)于因子就說到這里，實(shí)際用的非常少！對(duì)于邏輯數(shù)據(jù)以后會(huì)遇到再說，就不專門講了。





作者：柯廣的網(wǎng)絡(luò)日志

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