6.R语言【频数、频率统计函数】一维、二维、三维

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b站课程视频链接
https://www.bilibili.com/video/BV19x411X7C6?p=1
腾讯课堂(最新但是要花钱我花99😢😢元买了感觉讲的没问题就是知识点结构有点乱有点废话
https://ke.qq.com/course/3707827#term_id=103855009

本笔记前面的笔记参照b站视频【后面的画图】参考了付费视频
笔记顺序做了些调整【个人感觉逻辑顺畅】并删掉一些不重要的内容以及补充了个人理解
系列笔记目录【持续更新】https://blog.csdn.net/weixin_42214698/category_11393896.html

1. 一维的数据框进行频数统计

因子是专门用来进行分组的有因子才能分组【as.factor】分组之后才能进行频数统计。

> mtcars$cyl <- as.factor(mtcars$cyl)

> table(mtcars$cyl)     #频数统计
 4  6  8 
11  7 14 
# seq(from=to=by=组距)
> table(cut(mtcars$mpg,c(seq(10,50,10))))       #频数统计,数据不一样

(10,20] (20,30] (30,40] (40,50] 
     18      10       4       0

查看每个因子具体的行数-

> split(mtcars,mtcars$cyl)      #结果按照cyl分类
$`4`
                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Datsun 710     22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
Merc 240D      24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230       22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Fiat 128       32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
还有7列..
$`6`
                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Mazda RX4      21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
还有5列..
$`8`
                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
还有12列..

2. 二维的数据框进行频数统计

# vcd包中的风湿病数据集arthritis进行示范
> library(vcd)
># 统计两个量的频数返回的结果是一个二维的列联表
> table(Arthritis$Treatment,Arthritis$Improved)     
         
          None Some Marked
  Placebo   29    7      7
  Treated   13    7     21

或者

> with(data = Arthritis,table(Treatment,Improved))
         Improved
Treatment None Some Marked
  Placebo   29    7      7
  Treated   13    7     21

或者

> xtabs(~Treatment+Improved,data = Arthritis)
         Improved
Treatment None Some Marked
  Placebo   29    7      7
  Treated   13    7     21

3. 三维的数据框进行频数统计

> y <- xtabs(~Treatment+Improved+Sex,data = Arthritis)
> y 
, , Sex = Female

         Improved
Treatment None Some Marked
  Placebo   19    7      6
  Treated    6    5     16

, , Sex = Male

         Improved
Treatment None Some Marked
  Placebo   10    0      1
  Treated    7    2      5
  
---------------------------------将结果转换为一个评估式的列联表
> ftable(y)  
                   Sex Female Male
Treatment Improved                
Placebo   None             19   10
          Some              7    0
          Marked            6    1
Treated   None              6    7
          Some              5    2
          Marked           16    5

4. 对列联表进【行和列】边际频数统计

1️⃣边际频数统计 margin.table( )

> x <- xtabs(~Treatment+Improved,data = Arthritis)
> x
         Improved
Treatment None Some Marked
  Placebo   29    7      7
  Treated   13    7     21
  
  --------------------- 按行进行边际频数统计-----------------------
> margin.table(x,1)     
Treatment
Placebo Treated 
     43      41 
  ---------------------  按列进行边际频数统计-----------------------
> margin.table(x,2)     
Improved
  None   Some Marked 
    42     14     28

2️⃣将边际频数的和添加到频数表中addmargins( )

> addmargins(x)
         Improved
Treatment None Some Marked Sum
  Placebo   29    7      7  43
  Treated   13    7     21  41
  Sum       42   14     28  84
  ------------------------多了最后一行------------------------
> addmargins(x,1)   
         Improved
Treatment None Some Marked
  Placebo   29    7      7
  Treated   13    7     21
  Sum       42   14     28
  ------------------------多了最后一列------------------------
> addmargins(x,2)    
         Improved
Treatment None Some Marked Sum
  Placebo   29    7      7  43
  Treated   13    7     21  41