字符串操作一般分割、拼接、替换、提取等等

拆分

strsplit

strsplit默认输出格式为列表

strsplit(x, split, fixed = FALSE, perl = FALSE, useBytes = FALSE)

• x：字符串向量，向量中的每个字符串元素都会被分割
• split：位置的字串向量，即在哪个字串处开始拆分；该参数默认是正则表达式匹配；若设置fixed= T则表示是用普通文本匹配或者正则表达式的精确匹配。用普通文本来匹配的运算速度要快些。

x <- c(as = "asfef", qu = "qwerty", "yuiop[", "b", "stuff.blah.yech")
strsplit(x, "e")

运行结果：

$`as`                                $qu                                    [[3]]                            [[4]]                            [[5]]
[1] "asf" "f"                        [1] "qw"  "rty"                                 [1] "yuiop["                             [1] "b"                                    [1] "stuff.blah.y" "ch"

str_split

stringr包中的str_split函数与标准库中的strsplit一样

str_split(string, pattern, n = Inf, simplify = FALSE)

• string：字符串向量，向量中的每个字符串元素都会被分割
• pattern：分割位置的字符串向量，即在哪个字符串处开始

library(stringr)
fruits <- c( "apples and oranges and pears and bananas","pineapples and mangos and guavas")
str_split(fruits, " and ")

运行结果：

[[1]]                                                                                                            [[2]]
[1] "apples"  "oranges" "pears"   "bananas"                                              [1] "pineapples" "mangos"     "guavas"

拼接

paste和paste0

paste和paste0之间的区别是拼接的字符之间是否带有空格

paste (..., sep = " ", collapse = NULL)
paste0(..., collapse = NULL)

• ...：一个或者多个R对象，该对象需转换为字符向量.如果是字符串，则所有字符串拼接在一起，如果是字符串向量，则匹配。具体看实例
• sep：分割字符串

paste0(1:12, c("st", "nd", "rd", rep("th", 9)))
# 结果
[1] "1st"  "2nd"  "3rd"  "4th"  "5th"  "6th"  "7th"  "8th"  "9th"  "10th" "11th" "12th"
paste(1:12, c("st", "nd", "rd", rep("th", 9)))
# 结果
"1 st"  "2 nd"  "3 rd"  "4 th"  "5 th"  "6 th"  "7 th"  "8 th"  "9 th"  "10 th" "11 th" "12 th"

paste(1:12, c("st", "nd"))
# 结果
[1] "1 st"  "2 nd"  "3 st"  "4 nd"  "5 st"  "6 nd"  "7 st"  "8 nd"  "9 st"  "10 nd" "11 st" "12 nd"
paste0(1:12, c("st", "nd"))
# 结果
[1] "1st"  "2nd"  "3st"  "4nd"  "5st"  "6nd"  "7st"  "8nd"  "9st"  "10nd" "11st" "12nd"

paste("I","love","you")
# 结果
[1] "I love you"
paste0("I","love","you")
# 结果
[1] "Iloveyou"

str_c

str_c(..., sep = "", collapse = NULL)

str_c和paste0函数一样

str_c(1:12, c("st", "nd", "rd", rep("th", 9)))
# 结果
[1] "1st"  "2nd"  "3rd"  "4th"  "5th"  "6th"  "7th"  "8th"  "9th"  "10th" "11th" "12th"
str_c(1:12, c("st", "nd"))
# 结果
[1] "1st"  "2nd"  "3st"  "4nd"  "5st"  "6nd"  "7st"  "8nd"  "9st"  "10nd" "11st" "12nd"
str_c("I","love","you")
# 结果
[1] "Iloveyou"

替换

chartr

chartr(old, new, x)

• x：字符串向量
• old：需要被替换的字符/字符串，其长度不能长于new。也就是说只会更改下标上的字符，而不能更改下标。而且替换的时候，会old和new根据下标对应替换
• new：替换的字符/字符串

chartr(old = "a",new = "c",c("a123","a15","a23"))
# 结果
[1] "c123" "c15"  "c23"
chartr(old = "a12345",new = "c6789101456",c("a123","a15","a23"))
# 结果
[1] "c678" "c61"  "c78"  # 拿a15说明，a在old中下标为1，便替换为new[1]。1在old中下标为2，所以替换为new[2]。5在old中下标为6，所以替换为new[6]，所以最后a15替换为c61。
chartr(old = "a1",new = "c4",c("a123","a15","a23"))
# 结果
[1] "c423" "c45"  "c23" 

sub

sub可以替换字符串，但是sub()函数不会对原字符串进行操作。所以需要创建一个变量来储存该操作后的字符串。另外，sub函数只会替换匹配到的第一个

sub(pattern, replacement, x, ignore.case = FALSE, perl = FALSE,
    fixed = FALSE, useBytes = FALSE)

• pattern：包含正则表达式的字符串
• replacement：与pattern匹配的部分进行替换的值
• x：字符串向量或者转化为字符的R对象

str <- "Now is the time               "
sub(" +$", " 12:00", str) #正则表达式，即str尾部的空格替换为12:00 
# 结果
"Now is the time 12:00"
# 此时我们只是调用了sub函数，却没有保存这个结果。而且该函数不会对原函数操作的。
print(str)
"Now is the time               "

sub("Now","what",str)
# 结果
[1] "what is the time               "

sub(pattern = "nd",replacement = "ND",c("andbndcnd","sndendfund"))
# 结果，字符串元素中有很多"nd"，但是只会替换第一个"nd"。
[1] "aNDbndcnd"  "sNDendfund"

gsub

gsub(pattern, replacement, x, ignore.case = FALSE, perl = FALSE,
     fixed = FALSE, useBytes = FALSE)

gsub()函数和sub用法一样，不过，gsub()函数可以替换所有匹配字符

gsub(pattern = "nd",replacement = "ND",c("andbndcnd","sndendfund"))
# 结果
[1] "aNDbNDcND"  "sNDeNDfuND"

substr和substring

这两个函数可以提取、替换字符串。而且是对原字符串进行操作

substr(x, start, stop) <- value
substring(text, first, last = 1000000L) <- value

• x, text：字符串向量
• start, first：整型，替换字符的起始下标
• stop,：整型，替换字符的结束下标
• last：字符串长度
• value：替换的字符，如果需要的话（与代替换向量长度不同)，自动循环补齐

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
substr(shopping_list,1,3) <- "AAA"
# 结果
[1] "AAAles x4"    "AAA of flour" "AAA of sugar" "AAAk x2"

substr(shopping_list,1) <- "AAA"
# 结果
[1] "AAAles x4"    "AAA of flour" "AAA of sugar" "AAAk x2"

substr(shopping_list,1,20) <- "yesterday once more"
# 结果
[1] "yesterday"    "yesterday on" "yesterday on" "yesterd"   

substring(shopping_list,1) <- "yesterday once more"
# 结果
[1] "yesterday"    "yesterday on" "yesterday on" "yesterd"  

str_replace和str_replace_all

第三方包中的str_replace和str_replace_all

str_replace(string, pattern, replacement) # 和sub一样，只替换第一个匹配字符
str_replace_all(string, pattern, replacement) # 和gsub一样，替换所有匹配字符

fruits <- c("one apple", "two pears", "three bananas")
str_replace(fruits, "[aeiou]", "-") #正则表达式，即对字符串中的小写字母a或e或i或o或u，替换为-
# 结果
[1] "-ne apple"     "tw- pears"     "thr-e bananas" 
str_replace_all(fruits, "[aeiou]", "-") 
# 结果
[1] "-n- -ppl-"     "tw- p--rs"     "thr-- b-n-n-s"

str_sub

第三方包stringr

str_sub(string, start = 1L, end = -1L, omit_na = FALSE) <- value

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
str_sub(shopping_list,1,3) <- "AAA"
# 结果
[1] "AAAles x4"    "AAA of flour" "AAA of sugar" "AAAk x2"
str_sub(shopping_list,1) <- "AAA"
# 结果
[1] "AAA" "AAA" "AAA" "AAA"

提取

substr 和substring

substr(x, start, stop)
substring(text, first, last = 1000000L)

substr("abcdef", 2, 4)
# 结果
"bcd"
substr("abcdef", 1:6, 1:6)
# 结果
"a","b","c","d","d","e"

str_extract 和str_extract_all

第三方包stringr

str_extract(string, pattern)
str_extract_all(string, pattern, simplify = FALSE)

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
str_extract(shopping_list, "[a-z]+")
# 结果
[1] "apples" "bag"    "bag"    "milk"  
str_extract_all(shopping_list, "[a-z]+")
# 结果
[[1]]                                        [[2]]                                        [[3]]                                        [[4]]
[1] "apples" "x"                           [1] "bag"   "of"    "flour"                  [1] "bag"   "of"    "sugar"                [1] "milk" "x"

str_sub

第三方包stringr

str_sub(string, start = 1L, end = -1L)

str_sub(shopping_list,1,5)
# 结果
[1] "apple" "bag o" "bag o" "milk "

测定字符串长度

nchar

nchar(x, type = "chars", allowNA = FALSE, keepNA = NA) #以字符串为向量，返回向量元素--字符串的长度组成的向量
nzchar(x, keepNA = FALSE) #快速判定字符串向量元素是否为非空值

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
nchar(shopping_list)
# 结果
[1]  9 12 12  7
nzchar(shopping_list)
# 结果
[1] TRUE TRUE TRUE TRUE

str_count

str_count(string, pattern = "")

str_count不仅可以测定元素长度，还以测定某字符在字符串中的下标位置

str_count(shopping_list)
# 结果
[1]  9 12 12  7
str_count(shopping_list, "a")
# 结果，如果不包含则返回0
[1] 1 1 2 0

str_length

第三方包stringr

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
str_length(string)

str_length(shopping_list)
# 结果
[1]  9 12 12  7

字符串匹配

grep

grep(pattern, x, ignore.case = FALSE, perl = FALSE, value = FALSE,
     fixed = FALSE, useBytes = FALSE, invert = FALSE)

• pattern: 包含一个正则表达式的字符串（或者，当fixed = True时，为字符串）
• x: 一个待匹配的字符串向量，或者是一个可强制转换为字符串的R对象
• value:当value = False时，函数返回匹配值的下标。当value = True，函数返回匹配值

shopping_list <- c("apples x4", "bag of flour", "bag of sugar", "milk x2")
grep("apple",shopping_list)
# 结果
[1] 1
grep("apple",shopping_list,value = T)
# 结果
[1] "apples x4"

grepl

grepl(pattern, x, ignore.case = FALSE, perl = FALSE,
      fixed = FALSE, useBytes = FALSE)

grepl和grep的用法差不多，只是grepl返回的是逻辑变量TRUE或FALSE

grepl("apple",shopping_list)
# 结果
[1]  TRUE FALSE FALSE FALSE

str_subset

str_subset(string, pattern, negate = FALSE)

• string: 待匹配的字符串向量
• pattern: 一个包含正则表达式的字符串
• negate: 当negate = False，函数返回匹配值。当negate = True，函数返回与pattern不匹配的字符串

fruit <- c("apple", "banana", "pear", "pinapple")
str_subset(fruit, "a") #匹配所有含有a的字符串
# 结果
[1] "apple"    "banana"   "pear"     "pinapple"
str_subset(fruit, "^p", negate = TRUE) # 返回所有不以p开头的字符串
# 结果
[1] "apple"  "banana"

str_which

str_which(string, pattern, negate = FALSE)

str_which(fruit, "a")
# 结果
[1] 1 2 3 4

排序

str_sort

str_sort(x, decreasing = FALSE, na_last = TRUE, locale = "en",
  numeric = FALSE, ...)

• x:待排序的字符串向量
• decreasing：布尔值，默认FALSE，表示从低到高排序。如果为TRUE，表示从高到低排序
• na_last：NA 应该排在什么位置，TRUE表示放在末端，FALSE表示放在开头，NA向下排。
• numeric：如果为True，则按照数字排序而不是按照字符排序

x <- c("100a10", "100a5", "2b", "2a")
str_sort(x)
# 结果
[1] "100a10" "100a5"  "2a"     "2b" 
str_sort(x, numeric = TRUE)
# 结果
[1] "2a"     "2b"     "100a5"  "100a10"