factor 因子
在R中數(shù)據(jù)的分類(lèi)是用因子數(shù)據(jù)類(lèi)型（factor）來(lái)表示的。如性別。
> #數(shù)據(jù)框 data.frame
> ID <- c(1:4)
> age <- c(25,34,28,72)
> treatment <- c("type1","type2","type3","type1")
> status <- c("poor","stable","poor","stable")
> pdata <- data.frame(ID,age,treatment,status)
> colnames <- c("ID","age","treatment","status")
> rownames <- pdata[1]
> pdata
ID age treatment status
1 1 25 type1 poor
2 2 34 type2 stable
3 3 28 type3 poor
4 4 72 type1 improve
> summary(pdata)
ID age treatment
Min. :1.00 Min. :25.00 Length:4
1st Qu.:1.75 1st Qu.:27.25 Class :character
Median :2.50 Median :31.00 Mode :character
Mean :2.50 Mean :39.75
3rd Qu.:3.25 3rd Qu.:43.50
Max. :4.00 Max. :72.00
status
Length:4
Class :character
Mode :character
我們想按照status對(duì)患者進(jìn)行分類(lèi)，所以將status由字符串改為factor
> pdata$status <- as.factor(pdata$status)
> class(pdata$status)
[1] "factor"
> summary(pdata)
ID age treatment status
Min. :1.00 Min. :25.00 Length:4 poor :2
1st Qu.:1.75 1st Qu.:27.25 Class :character stable:1
Median :2.50 Median :31.00 Mode :character improve:1
Mean :2.50 Mean :39.75
3rd Qu.:3.25 3rd Qu.:43.50
Max. :4.00 Max. :72.00
status是一個(gè)因子向量，表明了每個(gè)患者的病情是惡化、穩(wěn)定、好轉(zhuǎn)，類(lèi)別總共有三大類(lèi)。
因?yàn)橥ㄟ^(guò)factor對(duì)患者進(jìn)行了分類(lèi)，所以可以對(duì)不同類(lèi)別進(jìn)行作圖：
> library(ggplot2)
> ggplot(data = pdata, aes(x = status)) + geom_bar()
levels()函數(shù)
對(duì)factor進(jìn)行排序、增刪，有利于清洗數(shù)據(jù)、作圖、比較
> levels(pdata$status)
[1] "improve" "poor" "stable"
批量修改其中某一類(lèi)別患者的status，如把improve改為stable
> pdata$status[pdata$status=="improve"] <-"stable"
> pdata
ID age treatment status
1 1 25 type1 poor
2 2 34 type2 stable
3 3 28 type3 poor
4 4 72 type1 stable
此時(shí)檢查還有哪些levels
> levels(pdata$status)
[1] "improve" "poor" "stable"
improve這一類(lèi)還在。如果我們想要?jiǎng)h掉這一類(lèi)別，則droplevels()
> pdata$status <- droplevels(pdata$status)
> levels(pdata$status)
[1] "poor" "stable"
此時(shí)沒(méi)有對(duì)應(yīng)患者的status被刪掉
幾種對(duì)levels的賦值方法
levels(f1)
levels(f2) <- value
attr(x, "levels") <- value
gl()函數(shù)：generate factor levels, 生成因子levels
gl(n,k,labels = c(), ordered = T)
n: 有幾類(lèi)
k: 每類(lèi)重復(fù)幾個(gè)
labels: 每類(lèi)起什么名字
ordered：是否排序
> ## assign individual levels
> x <- gl(2, 4, 8)
> levels(x)[1] <- "low"
> levels(x)[2] <- "high"
> x
[1] low low low low high high high high
Levels: low high
> ## or as a group
> y <- gl(2, 4, 8)
> levels(y) <- c("low", "high")
> y
[1] low low low low high high high high
Levels: low high
將某幾類(lèi)歸為一類(lèi)
> ## combine some levels
> z <- gl(3, 2, 12, labels = c("apple", "salad", "orange"))
> z
[1] apple apple salad salad orange orange apple apple salad
[10] salad orange orange
Levels: apple salad orange
> levels(z) <- c("fruit", "veg", "fruit")
> z
[1] fruit fruit veg veg fruit fruit fruit fruit veg veg fruit fruit
Levels: fruit veg
重復(fù)出現(xiàn)的類(lèi)別歸為一類(lèi)
> ## same, using a named list
> z <- gl(3, 2, 12, labels = c("apple", "salad", "orange"))
> z
[1] apple apple salad salad orange orange apple apple salad
[10] salad orange orange
Levels: apple salad orange
> levels(z) <- list("fruit" = c("apple","orange"), "veg" = "salad")
> z
[1] fruit fruit veg veg fruit fruit fruit fruit veg veg
[11] fruit fruit
Levels: fruit veg
加入data.frame中沒(méi)有出現(xiàn)的組別
> ## we can add levels this way:
> f <- factor(c("a","b"))
> levels(f) <- c("c", "a", "b")
> f
[1] c a
Levels: c a b
對(duì)組別的命名
> f <- factor(c("a","b"))
> levels(f) <- list(C = "C", A = "a", B = "b")
> f
[1] A B
Levels: C A B
將數(shù)值類(lèi)型轉(zhuǎn)換成因子
直接用as.numeric轉(zhuǎn)換會(huì)有問(wèn)題，轉(zhuǎn)換后的內(nèi)容不是你想要的：
> f <- factor(c(3.4,1.2,5))
> f
[1] 3.4 1.2 5
Levels: 1.2 3.4 5
> as.numeric(f)
[1] 2 1 3
正確的方式是
> f <- factor(c(3.4,1.2,5))
> f <- levels(f)[f]
> f <- as.numeric(f)
> f
[1] 3.4 1.2 5.0
