R语言 Factor类型的变量使用说明
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2022-11-23 20:51:30
factor类型的创建1. factor( )> credit_rating <- c("bb", "aaa", "aa", "ccc", "aa", "aaa", "b", "bb")...
factor类型的创建
1. factor( )
> credit_rating <- c("bb", "aaa", "aa", "ccc", "aa", "aaa", "b", "bb") #生成名为credit_rating的字符向量 > credit_factor <- factor(credit_rating) # step 2.将credit_rating转化为因子 > credit_factor [1] bb aaa aa ccc aa aaa b bb levels: aa aaa b bb ccc > str(credit_rating) #调用str()函数,显示credit_rating结构 chr [1:8] "bb" "aaa" "aa" "ccc" "aa" "aaa" "b" "bb" > str(credit_factor) #调用str()函数,显示credit_factor结构 factor w/ 5 levels "aa","aaa","b",..: 4 2 1 5 1 2 3 4
2. levels( )
上述代码中第二个运行后得到了levals,用于显示不同的因子(不重复),上述代码运行一二行
>credit_rating <- c("bb", "aaa", "aa", "ccc", "aa", "aaa", "b", "bb") > credit_factor <- factor(credit_rating) # step 2.将credit_rating转化为因子 > 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 汇总:summary()函数
> summary(credit_rating) length class mode 8 character character > summary(credit_factor) aa aaa b bb ccc 2 2 1 2 1
4. factor 可视化:plot()
# 使用plot()将credit_factor可视化 plot(credit_factor) #> summary(credit_factor) # aa aaa b bb ccc # 2 2 1 2 1
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5. cut( )函数 对数据进行分组
>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()函数为aaa_rank创建4个组 > 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()按顺序将级别重命名 > levels(aaa_factor) <- c("low","medium","high","very_high") > > # step 3:输出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:绘制aaa_factor > plot(aaa_factor) >
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6. 删除元素 :- 表示删除
(1)-1:删除第一位的元素,-3:删除第三位的元素
(2)
> credit_factor [1] bb aaa aa ccc aa aaa b bb levels: aa aaa b bb ccc > # 删除位于`credit_factor`第3和第7位的`a`级债券,不使用`drop=true` > keep_level <- credit_factor[c(-3,-7)] > > # 绘制keep_level > plot(keep_level) > > # 使用相同的数据,删除位于`credit_factor`第3和第7位的`a`级债券,使用`drop=true` > drop_level <-credit_factor[c(-3,-7),drop=true] > > # 绘制drop_level > plot(drop_level) >
7. 转换factor为string类型
>cash=data.frame(company = c("a", "a", "b"), cash_flow = c(100, 200, 300), year = c(1, 3, 2)) #创建数据框 >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:创建数据框时,r的默认行为是将所有字符转换为因子
那么,如何在创建数据框时,不让r的默认行为执行呢?
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) #创建数据框 > 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. 创建有序factor类型:ordered=true
# 有序factor类型 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.将credit_rating转化为因子 > credit_factor #此时的credit_factor 无序 >ordered(credit_factor, levels = c("aaa", "aa", "a", "bbb"))
9. 删除因子级别时,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 #可见,aaa还存在 >credit_factor[-1, drop = true] #完全放弃aaa级别 [1] aa a bbb aa bbb a levels: bbb < a < aa
以上为个人经验,希望能给大家一个参考,也希望大家多多支持。如有错误或未考虑完全的地方,望不吝赐教。
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