stringr包是R数据处理神器Tidyverse包中的工具之一，是处理字符串很好用的工具，结合正则表达式，可以发挥巨大作用。
字符串长度
stringr包的操作对象是向量，str_length()函数用于确定字符串长度。
> x <- c("why", "video", "cross", "extra", "deal", "authority")
> str_length(x)
#> [1] 3 5 5 5 4 9
但是如果是下面这种写法，便会出现语法错误，因为输入对象是非向量。
> str_length("why", "video", "cross", "extra", "deal", "authority")
Error in str_length("why", "video", "cross", "extra", "deal", "authority") :
unused arguments ("video", "cross", "extra", "deal", "authority")
字符串拼接
str_c()函数用于进行字符串的拼接，主要参数有待拼接字符串向量，sep=''和collapse=NULL。
> x = c('apple', 'banana','peach')
> y = c('one', 'two', 'three')
> str_c(x, y)
# [1] "appleone" "bananatwo" "peachthree"
> str_c(x, y, sep = '_')
# [1] "apple_one" "banana_two" "peach_three"
> str_c(x, y, collapse = "_")
# [1] "appleone_bananatwo_peachthree"
注意，上述例子中sep和collapse的作用后的不同，sep作用后还是多个字符串，collapse作用后则变为了一个字符串。
> case1 <- str_c(x, y, sep = '_')
> str_length(case1)
# [1] 9 10 11
> case2 <- str_c(x, y, collapse = "_")
> str_length(case2)
# [1] 29
字符串拆分
str_split()是stringr包中进行字符串拆分的函数，根据特定字符或者子集数量进行字符串拆分，选取特定子集。
# 构建一个由'_'分割的字符串向量
> x <- c('aajs_123_dkks', 'ahda_236_akdk', 'ahdj_178_ajdj', 'agsh_109_auqyr', 'qwp_2635_qnjx')
> str_split(x, pattern = '_')
[[1]]
[1] "aajs" "123" "dkks"
[[2]]
[1] "ahda" "236" "akdk"
[[3]]
[1] "ahdj" "178" "ajdj"
[[4]]
[1] "agsh" "109" "auqyr"
[[5]]
[1] "qwp" "2635" "qnjx"
主要参数如下pattern = , n = Inf , simplify = FALSE，默认返回值类型为list，simplify = True则返回值类型为matrix,array。
> class(str_split(x, pattern = '_'))
[1] "list"
> str_split(x, pattern = '_', simplify = TRUE)
[,1] [,2] [,3]
[1,] "aajs" "123" "dkks"
[2,] "ahda" "236" "akdk"
[3,] "ahdj" "178" "ajdj"
[4,] "agsh" "109" "auqyr"
[5,] "qwp" "2635" "qnjx"
> class(str_split(x, pattern = '_', simplify = TRUE))
# [1] "matrix" "array"
字符串向量拆分后选择特定的列，用于后续操作，比如本例中拆分后选取数字列，则可以使用矩阵和数组选取子集的操作。
> str_split(x, pattern = '_', simplify = TRUE)[,2]
[1] "123" "236" "178" "109" "2635"
字符串子集
可以使用str_subset()根据某一特征选取向量中的特定的字符串，也可以结合正则表达式进行选择。参数包括pattern和negate。negate默认是FALSE,如果是TRUE，作用是反选。
> x <- c("why", "video", "cross", "extra", "deal", "authority")
> str_subset(x, pattern = 'o')
[1] "video" "cross" "authority"
> str_subset(x, pattern = 'o', negate = T)
[1] "why" "extra" "deal"
如果使用正则表达式，则和不使用存在不同，如下举例。
> x <- c("why", "video", "cross", "extra", "deal", "authority")
> str_subset(x, pattern = 'oi')
# character(0)
> str_subset(x, pattern = '[oi]')
[1] "video" "cross" "authority"
字符串替换
使用str_replace()进行特定字符的替换，参数包括要替换的模式pattern和替换成的模式replacement。
> x <- c("why", "video", "cross", "extra", "deal", "authority")
> str_replace(x, 'i', '@')
[1] "why" "v@deo" "cross" "extra" "deal" "author@ty"
使用正则表达式后则有所不同：
> str_replace(x, 'ie', '@@')
[1] "why" "video" "cross" "extra" "deal" "authority"
> str_replace(x, '[ie]', '@@')
[1] "why" "v@@deo" "cross" "@@xtra" "d@@al" "author@@ty"
注意，str_replace只替换匹配到的第一个，使用str_replace_all()进行全部替换：
> x <- c('apple', 'happy')
> x
[1] "apple" "happy"
> str_replace(string = x, pattern = 'p', replacement = '%')
[1] "a%ple" "ha%py"
> str_replace_all(string = x, pattern = 'p', replacement = '%')
[1] "a%%le" "ha%%y"
另外，使用str_replace_na()缺失值的替换,
> x <- c('one', NA,'ten', NA, 'eleven',NA)
> x
[1] "one" NA "ten" NA "eleven" NA
> str_replace_na(string = x, replacement = '%')
[1] "one" "%" "ten" "%" "eleven" "%"
字符串填补
使用str_pad(）函数进行字符串的填补，参数包括string, width, side = c("left", "right", "both"), pad = " ")，举例如下：
> str_pad(string = letters[1:7], width = 5, side = 'left', pad = '#')
[1] "####a" "####b" "####c" "####d" "####e" "####f" "####g"
> str_pad(string = letters[1:7], width = 5, side = 'both', pad = '#')
[1] "##a##" "##b##" "##c##" "##d##" "##e##" "##f##" "##g##"
> str_pad(string = letters[1:7], width = 5, side = 'right', pad = '#')
[1] "a####" "b####" "c####" "d####" "e####" "f####" "g####"
