L2code

1 数据类型

1.1 数值型numeric

# numeric 数值型，str()查看对象的类型
a1 <- c(1,2,3,4,5)
str(a1)
 num [1:5] 1 2 3 4 5
str(pi)
 num 3.14
str(sqrt(2))
 num 1.41

1.2 整数型integer

# integer 整数型
a2 <- 5L #L 表示该值是整数
str(a2)
 int 5
# 1:5生成序列1，2，3，4，5
a3 <- 1:5
str(a3)
 int [1:5] 1 2 3 4 5
a4 <- as.numeric(a3)
str(a4)
 num [1:5] 1 2 3 4 5

1.3 逻辑型logical

answer <- c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE) 
#查看answer的类型
str(answer) 
 logi [1:6] TRUE TRUE TRUE FALSE TRUE FALSE
#逻辑型向量求和，TRUE = 1, FALSE = 0
sum(answer) 
[1] 4
#逻辑型向量求平均，TRUE的比例
mean(answer) 
[1] 0.6666667
#！逻辑值取反
!answer
[1] FALSE FALSE FALSE  TRUE FALSE  TRUE

1.4 字符串character

# data.frame()创建数据框
df <- data.frame(
  id = 1:50,
  age = round(rnorm(50,40,5)),
  edu = c(rep("highschool",20),
          rep("bachelor", 15),
          rep("master",15)),
  sex = ifelse(rbinom(50, 1, 0.6) == 1, 
               "male", "female")
)

head(df) #显示df的前六行
  id age        edu    sex
1  1  26 highschool   male
2  2  39 highschool female
3  3  41 highschool female
4  4  48 highschool female
5  5  43 highschool female
6  6  41 highschool female
df$edu #edu是字符串，有双引号
 [1] "highschool" "highschool" "highschool" "highschool" "highschool"
 [6] "highschool" "highschool" "highschool" "highschool" "highschool"
[11] "highschool" "highschool" "highschool" "highschool" "highschool"
[16] "highschool" "highschool" "highschool" "highschool" "highschool"
[21] "bachelor"   "bachelor"   "bachelor"   "bachelor"   "bachelor"  
[26] "bachelor"   "bachelor"   "bachelor"   "bachelor"   "bachelor"  
[31] "bachelor"   "bachelor"   "bachelor"   "bachelor"   "bachelor"  
[36] "master"     "master"     "master"     "master"     "master"    
[41] "master"     "master"     "master"     "master"     "master"    
[46] "master"     "master"     "master"     "master"     "master"

1.5 因子factor

#factor()将字符串转换为因子，默认level按字母顺序
df$edu <- factor(df$edu) 
#查看因子df$edu的level顺序
levels(df$edu) 
[1] "bachelor"   "highschool" "master"    
#edu是因子，没有双引号
df$edu 
 [1] highschool highschool highschool highschool highschool highschool
 [7] highschool highschool highschool highschool highschool highschool
[13] highschool highschool highschool highschool highschool highschool
[19] highschool highschool bachelor   bachelor   bachelor   bachelor  
[25] bachelor   bachelor   bachelor   bachelor   bachelor   bachelor  
[31] bachelor   bachelor   bachelor   bachelor   bachelor   master    
[37] master     master     master     master     master     master    
[43] master     master     master     master     master     master    
[49] master     master    
Levels: bachelor highschool master
#箱线图的排列按edu的三个组别的字母顺序
boxplot(df$age ~ df$edu) 

# ordinal scale, levels = 自定义逻辑顺序
df$edu <- factor(df$edu, 
                 levels = c("highschool", "bachelor", "master"))
levels(df$edu)
[1] "highschool" "bachelor"   "master"    
boxplot(df$age ~ df$edu)

#将数值型数据转换为因子
df$age_group <- cut(df$age, 4)

#查看因子的水平个数
nlevels(df$age_group)
[1] 4
#呈现age_group和edu的列联表
table(df$age_group, df$edu)
           
            highschool bachelor master
  (26,31.5]          4        0      2
  (31.5,37]          4        3      3
  (37,42.5]          7        7      6
  (42.5,48]          5        5      4

2 数据结构

2.1 向量vector

# 向量
# scalar
age <- 5

name <- "Harry"

# numeric vector
a <- c(1,2,3,4,5) # c() Combine Values into a Vector

a[1:3] #提取向量中的元素[ ]
[1] 1 2 3
a[a > 3] #提取大于3的元素
[1] 4 5
a > 3 # 返回逻辑值
[1] FALSE FALSE FALSE  TRUE  TRUE
# character vector
b <- LETTERS[1:10] 
b[5]
[1] "E"
b[c(2,4,6)]
[1] "B" "D" "F"
b[1:3]
[1] "A" "B" "C"
#logical vector
answer <- c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE)

2.2 矩阵matrix

# matrix()创建矩阵, 默认按列的方向填充
y1<-matrix(1:20, nrow=5, ncol=4)
y1[3, ] #第3行
[1]  3  8 13 18
y1[, 1] #第2列
[1] 1 2 3 4 5
y1[1:3, 2:4] #第1-3行的第2-4列
     [,1] [,2] [,3]
[1,]    6   11   16
[2,]    7   12   17
[3,]    8   13   18
# byrow = TRUE 按行方向填充
y2<-matrix(1:20, nrow=5, ncol=4, byrow = TRUE)
y2[3,2] #第3行第2列
[1] 10
# 矩阵中可以存放字符串
cells <- letters[1:10]
# 定义矩阵的行名、列名
rnames <- c("team1", "team2")
cnames <- c("class1", "class2", "class3", "class4", "class5")
mymatrix <- matrix(cells, nrow=2, ncol=5, byrow=TRUE,
                   dimnames=list(rnames, cnames))
mymatrix["team1", ]
class1 class2 class3 class4 class5 
   "a"    "b"    "c"    "d"    "e" 
mymatrix[, "class1"]
team1 team2 
  "a"   "f"

2.3 数据框dataframe

#创建数据框data.frame()
d <- c(1,2,3,4)
e <- c("red", "white", "green", NA)
f <- c(TRUE,TRUE,TRUE,FALSE)
df <- data.frame(id = d,
                 color = e,
                 pass = f)
df
  id color  pass
1  1   red  TRUE
2  2 white  TRUE
3  3 green  TRUE
4  4  <NA> FALSE
df[1:2] #第1-2列
  id color
1  1   red
2  2 white
3  3 green
4  4  <NA>
df[c("id","pass")] #df中的向量id和pass
  id  pass
1  1  TRUE
2  2  TRUE
3  3  TRUE
4  4 FALSE
df$color
[1] "red"   "white" "green" NA     
View(mtcars) #以表单形式浏览数据框

head(mtcars) #浏览数据框的前六行
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
tail(mtcars) #浏览数据框的后六行
                mpg cyl  disp  hp drat    wt qsec vs am gear carb
Porsche 914-2  26.0   4 120.3  91 4.43 2.140 16.7  0  1    5    2
Lotus Europa   30.4   4  95.1 113 3.77 1.513 16.9  1  1    5    2
Ford Pantera L 15.8   8 351.0 264 4.22 3.170 14.5  0  1    5    4
Ferrari Dino   19.7   6 145.0 175 3.62 2.770 15.5  0  1    5    6
Maserati Bora  15.0   8 301.0 335 3.54 3.570 14.6  0  1    5    8
Volvo 142E     21.4   4 121.0 109 4.11 2.780 18.6  1  1    4    2
dim(mtcars) #查看数据框的行数和列数
[1] 32 11
str(mtcars) #查看数据框的结构
'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

2.4 列表list

# 创建列表list
mylist <- list(myvector = y1, 
               mymatrix = cells, 
               mydata = df)

mylist[[1]][2,3] #第1个对象中的第2行第3列
[1] 12
mylist[[3]][, 2] #第3个对象中的第2列
[1] "red"   "white" "green" NA     
#hist()函数的运行结果被保存为list
x <- runif(100)
p <- hist(x)

p
$breaks
 [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

$counts
 [1] 15 15 11 12 10  4 13  6  7  7

$density
 [1] 1.5 1.5 1.1 1.2 1.0 0.4 1.3 0.6 0.7 0.7

$mids
 [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

$xname
[1] "x"

$equidist
[1] TRUE

attr(,"class")
[1] "histogram"