R語(yǔ)言 Factor類型的變量使用說(shuō)明

更新時(shí)間：2021年03月27日 11:46:40 作者：葑歆

這篇文章主要介紹了R語(yǔ)言 Factor類型的變量使用說(shuō)明，具有很好的參考價(jià)值，希望對(duì)大家有所幫助。一起跟隨小編過(guò)來(lái)看看吧

factor類型的創(chuàng)建

1. factor( )

> credit_rating <- c("BB", "AAA", "AA", "CCC", "AA", "AAA", "B", "BB") #生成名為credit_rating的字符向量
> credit_factor <- factor(credit_rating) # step 2.將credit_rating轉(zhuǎn)化為因子
> credit_factor
[1] BB AAA AA CCC AA AAA B BB 
Levels: AA AAA B BB CCC
> str(credit_rating) #調(diào)用str()函數(shù)，顯示credit_rating結(jié)構(gòu)
 chr [1:8] "BB" "AAA" "AA" "CCC" "AA" "AAA" "B" "BB"
> str(credit_factor) #調(diào)用str()函數(shù)，顯示credit_factor結(jié)構(gòu)
 Factor w/ 5 levels "AA","AAA","B",..: 4 2 1 5 1 2 3 4

2. levels( )

上述代碼中第二個(gè)運(yùn)行后得到了levals，用于顯示不同的因子（不重復(fù)）,上述代碼運(yùn)行一二行

>credit_rating <- c("BB", "AAA", "AA", "CCC", "AA", "AAA", "B", "BB") 
> credit_factor <- factor(credit_rating) # step 2.將credit_rating轉(zhuǎn)化為因子
> credit_factor
[1] BB AAA AA CCC AA AAA B BB 
Levels: AA AAA B BB CCC
> levels(credit_factor)
[1] "AA" "AAA" "B" "BB" "CCC"
>levels(credit_factor) <-c("2A","3A","1B","2B","3C")
> credit_factor
[1] 2B 3A 2A 3C 2A 3A 1B 2B
Levels: 2A 3A 1B 2B 3C

3. Factor 匯總：summary()函數(shù)

> summary(credit_rating)
 Length Class Mode 
 8 character character 
> summary(credit_factor)
 AA AAA B BB CCC 
 2 2 1 2 1

4. factor 可視化:plot()

# 使用plot()將credit_factor可視化
plot(credit_factor)
#> summary(credit_factor)
# AA AAA B BB CCC 
 # 2 2 1 2 1

5. cut( )函數(shù) 對(duì)數(shù)據(jù)進(jìn)行分組

>AAA_rank <- sample(seq(1:100), 50, replace = T)
> AAA_rank
 [1] 90 28 63 57 96 41 93 70 76 36 26 1 86 43 47 15 23 70
[19] 63 1 79 100 20 59 17 23 84 96 21 33 32 19 52 58 81 37
[37] 22 58 42 75 41 64 15 58 63 2 1 65 54 35
> # step 1：使用cut()函數(shù)為AAA_rank創(chuàng)建4個(gè)組
> AAA_factor <- cut(x = AAA_rank , breaks =c(0,25,50,75,100) )
> > AAA_factor 
 [1] (75,100] (25,50] (50,75] (50,75] (75,100] (25,50] (75,100] (50,75] 
 [9] (75,100] (25,50] (25,50] (0,25] (75,100] (25,50] (25,50] (0,25] 
[17] (0,25] (50,75] (50,75] (0,25] (75,100] (75,100] (0,25] (50,75] 
[25] (0,25] (0,25] (75,100] (75,100] (0,25] (25,50] (25,50] (0,25] 
[33] (50,75] (50,75] (75,100] (25,50] (0,25] (50,75] (25,50] (50,75] 
[41] (25,50] (50,75] (0,25] (50,75] (50,75] (0,25] (0,25] (50,75] 
[49] (50,75] (25,50] 
Levels: (0,25] (25,50] (50,75] (75,100]
> # step 2：使用levels()按順序?qū)⒓?jí)別重命名
> levels(AAA_factor) <- c("low","medium","high","very_high")
> 
> # step 3：輸出AAA_factor
> AAA_factor
 [1] medium medium very_high high very_high high high 
 [8] high medium medium very_high high medium very_high
[15] medium low medium low high medium low 
[22] medium high very_high very_high very_high medium very_high
[29] low low low medium very_high low very_high
[36] low very_high low low high medium medium 
[43] medium low low low low medium medium 
[50] medium 
Levels: low medium high very_high
> 
> # step 4：繪制AAA_factor
> plot(AAA_factor)
>

6. 刪除元素：- 表示刪除

（1）-1：刪除第一位的元素，-3：刪除第三位的元素

（2）

> credit_factor
[1] BB AAA AA CCC AA AAA B BB 
Levels: AA AAA B BB CCC
> # 刪除位于`credit_factor`第3和第7位的`A`級(jí)債券，不使用`drop=TRUE`
> keep_level <- credit_factor[c(-3,-7)]
> 
> # 繪制keep_level
> plot(keep_level)
> 
> # 使用相同的數(shù)據(jù)，刪除位于`credit_factor`第3和第7位的`A`級(jí)債券，使用`drop=TRUE`
> drop_level <-credit_factor[c(-3,-7),drop=TRUE]
> 
> # 繪制drop_level
> plot(drop_level)
>

7. 轉(zhuǎn)換Factor為String類型

>cash=data.frame(company = c("A", "A", "B"), cash_flow = c(100, 200, 300), year = c(1, 3, 2)) #創(chuàng)建數(shù)據(jù)框
>str(cash)
'data.frame': 3 obs. of 3 variables:
 $ company : Factor w/ 2 levels "A","B": 1 1 2
 $ cash_flow: num 100 200 300
 $ year : num 1 3 2

注意：創(chuàng)建數(shù)據(jù)框時(shí)，R的默認(rèn)行為是將所有字符轉(zhuǎn)換為因子

那么，如何在創(chuàng)建數(shù)據(jù)框時(shí)，不讓r的默認(rèn)行為執(zhí)行呢？

采用 stringsAsFactors = FALSE

> cash=data.frame(company = c("A", "A", "B"), cash_flow = c(100, 200, 300), year = c(1, 3, 2),stringsAsFactors=FALSE) #創(chuàng)建數(shù)據(jù)框
> str(cash)
'data.frame': 3 obs. of 3 variables:
 $ company : chr "A" "A" "B"
 $ cash_flow: num 100 200 300
 $ year : num 1 3 2

8. 創(chuàng)建有序Factor類型:ordered=TRUE

# 有序Factor類型
credit_rating <- c("AAA", "AA", "A", "BBB", "AA", "BBB", "A")
credit_factor_ordered <- factor(credit_rating, ordered = TRUE, levels = c("AAA", "AA", "A", "BBB"))

>credit_rating <- c("BB", "AAA", "AA", "CCC", "AA", "AAA", "B", "BB") 
> credit_factor <- factor(credit_rating) # step 2.將credit_rating轉(zhuǎn)化為因子
> credit_factor #此時(shí)的credit_factor 無(wú)序
>ordered(credit_factor, levels = c("AAA", "AA", "A", "BBB"))

9. 刪除因子級(jí)別時(shí)，采用drop=TRUE

>credit_factor
[1] AAA AA A BBB AA BBB A 
Levels: BBB < A < AA < AAA
>credit_factor[-1]
[1] AA A BBB AA BBB A 
Levels: BBB < A < AA < AAA #可見(jiàn)，AAA還存在
>credit_factor[-1, drop = TRUE] #完全放棄AAA級(jí)別
[1] AA A BBB AA BBB A 
Levels: BBB < A < AA

以上為個(gè)人經(jīng)驗(yàn)，希望能給大家一個(gè)參考，也希望大家多多支持腳本之家。如有錯(cuò)誤或未考慮完全的地方，望不吝賜教。

您可能感興趣的文章: