一，数学函数
绝对值函数abs(x)
sqrt(x) 开平方根
不小于某个数的最小整数ceiling(x)
不大于某个数的最大整数floor(x)
四舍五入round(x)
sin(x)
cos(x)
log(x)
二，统计函数
求平均值
> x<-c(2,3,4,5,6,7,8,9,10)
> mean(x)求和
> a<-c(2,3,4,5,6)
> sum(a)
[1] 20求标准差
> sd(a)
[1] 1.581139方差
> var(a)
[1] 2.5求最大值
> max(a)
[1] 6求最小值
> min(a)
[1] 2标准化
> scale(a)
[,1]
[1,] -1.2649111
[2,] -0.6324555
[3,] 0.0000000
[4,] 0.6324555
[5,] 1.2649111
attr(,"scaled:center")
[1] 4
attr(,"scaled:scale")
[1] 1.581139
三，概率函数
正态函数：
> x<-pretty(c(-3,3),30)
> x
[1] -3.0 -2.8 -2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0
> y<-dnorm(x)
> plot(x,y)
其他正态函数
> rnorm(50,mean=20,sd=8)
[1] 15.01154288 38.11096393 18.65391796 14.38228071 11.60227115 8.36768099 6.78851143 -0.06757863 15.51745301 22.42118256 23.37286503 20.61214282 5.59927021
[14] 23.69614839 17.71606857 29.69719738 27.25146139 27.97797925 11.75969538 30.84565356 3.13559481 -2.82207130 13.43633698 29.48021201 29.33732577 26.96600429
[27] 24.92109400 18.97664020 14.56857325 11.06500051 10.28361728 25.43226224 3.36034989 24.98450651 28.53060037 23.46619776 29.30594271 14.48793170 8.82698624
[40] 31.50511932 11.04945488 18.97749006 22.50621256 21.05814273 33.22670323 20.52845380 11.46026542 18.06046786 19.08941141 8.54350999
> runif(5)
[1] 0.0575840 0.8907667 0.3178646 0.1195145 0.6993192
>
> runif(5)
[1] 0.1634405 0.3271568 0.7107670 0.8365320 0.909055
//保持生成的随机数不变
> set.seed(12)
> runif(5)
[1] 0.06936092 0.81777520 0.94262173 0.26938188 0.16934812
> set.seed(12)
> runif(5)
[1] 0.06936092 0.81777520 0.94262173 0.26938188 0.16934812四，字符串处理函数
获取长度
> x<-"abced"
> nchar(x)
[1] 5截取字符串
> substr(x,3,5)
[1] "ced"获取某个字符串的索引位置
> grep("a",x)
[1] 1替换字符串
> sub("a","A",x)
[1] "Abced分割字符串
> strsplit(x,"c")
[[1]]
[1] "ab" "ed"拼接字符串
> paste("today",x)
[1] "today abced"转换大小写
> toupper(x)
[1] "ABCED"
> tolower(x)
[1] "abced"五，其他类型函数
获取长度
> length(x)
[1] 1
生成等差数列
> seq(1,10,2)
[1] 1 3 5 7 9
重复某个数
> rep(1:3,2)
[1] 1 2 3 1 2 3打印日志
> cat("Hello","Tom")
Hello Tom六，将函数应用于矩阵和数列
> b<-matrix(runif(12),nrow=3)
> b
[,1] [,2] [,3] [,4]
[1,] 0.03389562 0.022877743 0.8138806 0.2649184
[2,] 0.17878500 0.008324827 0.3762485 0.4393343
[3,] 0.64166537 0.392697197 0.3808122 0.4576072
> log(b)
[,1] [,2] [,3] [,4]
[1,] -3.3844694 -3.7775907 -0.2059417 -1.3283335
[2,] -1.7215713 -4.7885131 -0.9775056 -0.8224946
[3,] -0.4436883 -0.9347165 -0.9654490 -0.7817442
> mean(b)
[1] 0.3342539
//对行求平均值
> apply(b, 1,mean)
[1] 0.2838931 0.2506732 0.4681955
//对列求平均值
> apply(b, 2,mean)
[1] 0.2847820 0.1412999 0.5236471 0.3872866七，重复和循环
for循环
> for (i in 1:5) {
+ print("Hello R")
+ }
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"while循环
> x<-5
> while (x>0) {
+ print("Hello R");x<-x-1
+ }
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"
[1] "Hello R"
八，条件执行
if-else
> if(x!=1)print("male") else print("female")
[1] "femaleifelse
> ifelse(x>1,print("male"),print("female"))
[1] "female"
[1] "female"switch
> a<-c("abb","cdd")
> for (i in a) print(switch(i,abb="11",cdd="2",other="3"))
[1] "11"
[1] "2"九，转置
将数据集的行列转置
> head(mtcars)
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
> cars<-mtcars[1:5,1:4]
> cars
mpg cyl disp hp
Mazda RX4 21.0 6 160 110
Mazda RX4 Wag 21.0 6 160 110
Datsun 710 22.8 4 108 93
Hornet 4 Drive 21.4 6 258 110
Hornet Sportabout 18.7 8 360 175
> t(cars)
Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive Hornet Sportabout
mpg 21 21 22.8 21.4 18.7
cyl 6 6 4.0 6.0 8.0
disp 160 160 108.0 258.0 360.0
hp 110 110 93.0 110.0 175.0
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