字符串和因子
1.字符串
创建字符串
> c("Hello","World")
[1] "Hello" "World"
paste( ) 函数连接字符串
> c("Hello","World")
[1] "Hello" "World"
> paste(c("Hello","Hi"),"World")
[1] "Hello World" "Hi World"
> paste(c("Hello","Hi"),"World",sep="-")
[1] "Hello-World" "Hi-World"
> paste(c("Hello","Hi"),"World",collapse =",")
[1] "Hello World,Hi World"
> paste0(c("Hello","Hi"),"World") #paste0函数能去掉分隔符
[1] "HelloWorld" "HiWorld"
tostring() 函数打印字符串
> x
[1] 1 4 9 16 25
> toString(x)
[1] "1, 4, 9, 16, 25"
> toString(x,width = 4)
[1] "1,...."
> toString(x,width = 10) #width表示限制字符长度
[1] "1, 4, ...."
2.格式化数字
formatC函数
> pow <- 1:3
> (powers_of_e <- exp(pow))
[1] 2.718282 7.389056 20.085537
> formatC(powers_of_e)
[1] "2.718" "7.389" "20.09"
> formatC(powers_of_e,digits = 3) #指定3个数字
[1] "2.72" "7.39" "20.1"
> formatC(powers_of_e,digits = 3,width = 10) #前面加上一个空格
[1] " 2.72" " 7.39" " 20.1"
> formatC(powers_of_e,digits = 3,format = "e") #科学格式
[1] "2.718e+00" "7.389e+00" "2.009e+01"
> formatC(powers_of_e,digits = 3,flag = "+") #前面加上 +
[1] "+2.72" "+7.39" "+20.1"
sprintf函数
> sprintf("%s %d = %f","Euler's constant to the power",pow,powers_of_e)
[1] "Euler's constant to the power 1 = 2.718282"
[2] "Euler's constant to the power 2 = 7.389056"
[3] "Euler's constant to the power 3 = 20.085537"
还有format（与formatC用法类似）和prettyNum（格式化非常大或非常小的数字）这里两个函数可格式化数字。
更改大小写
> toupper("I am the king of the world")
[1] "I AM THE KING OF THE WORLD"
> tolower("HELLO WORLD")
[1] "hello world"
3.因子 因子：用于存储类别变量的特殊的变量类型。
> (heights <- data.frame(height_cm = c(153,181,150,172,165,149,174,169,198,163),gender = c("female","male","female","male","male","female","female","male","male","female")))
height_cm gender
1 153 female
2 181 male
3 150 female
4 172 male
5 165 male
6 149 female
7 174 female
8 169 male
9 198 male
10 163 female
> class(heights$gender)
[1] "factor" #是一个因子
> heights$gender
[1] female male female male male female female male male
[10] female
Levels: female male
> levels(heights$gender) #female和male被称为因子水平
[1] "female" "male"
factor函数创建因子
> gender_fac <- c("female","male","female","male","male")
> (gender_char <- factor(gender_fac))
[1] female male female male male
Levels: female male