17 正则表达式

17.1 grep函数

模式查询函数：查找符合某个条件的字符串/文本

ss <- c("1314","abc","a b c","ABC","aB12c","13ab14c")
grep(pattern = "ab",x = ss) #ss向量中包含"ab"的索引
grep(pattern = "ab",x = ss,ignore.case = TRUE) #忽略大小写
grep(pattern = "ab",x = ss,value = TRUE)

17.1.1 函数参数

pattern
x:字符向量
ignore.case：是否忽略大小写
value：是否返回值（而非索引）

17.1.2 模式（pattern）与匹配（match）

模式(pattern)：符合某种条件的“表达式”，如“姓张的同学”、“以数字开头的行”
匹配：用““模式”去比较/查找/筛选的过程称为“匹配”

17.2 元字符

表示自身的字符：字母、数字
1个任意字符：.（点号）
表示位置：^$ ^表示以xx开始，$表示以xx结束
表示数量：*?+ 星号代表任意数量，加号代表至少1个，问号代表0个或1个
括号类 [] 方括号表示含[]中的字符，注意[]与^联用表示否定，不含xx开头 {m,n} 花括号内可填一个数字或两个数字（表示范围） () 圆括号表示组合
转义符\? \*在元字符前加反斜杠（）进行转义。
其他： Tab(制表符) Enter(换行) 软换行文字间隔符任意空格符不是空格键任意文字字符（字母汉字）

例子：任意字符（.点号）与数量符号（*、+、?）的应用

ss <- c("acb","a b","A b","a#b","a##b","ab")
grep(pattern = "ab",x = ss) #匹配ab
grep(pattern = "a.b",x = ss) #匹配ab中间有1个任意字符
grep(pattern = "a..b",x = ss) #匹配ab中间有2个任意字符
grep(pattern = "a.*b",x = ss) #匹配ab中间有任意数量个任意字符，数量可以为0
grep(pattern = "a.+b",x = ss) #匹配ab中间有至少一个数量个任意字符
grep(pattern = "a.?b",x = ss)#匹配ab中间有0个或1个数量个任意字符

## [1] 6
## [1] 1 2 4
## [1] 5
## [1] 1 2 4 5 6
## [1] 1 2 4 5
## [1] 1 2 4 6

例子：任意字符（.点号）与数量符号（{}）的应用

ss <- c("acb","a b","A b","a#b","a##b","ab")
grep(pattern = "a.{1,3}b",x = ss) #{}表示一个数字范围，匹配"ab"之间有1至3个任意字符
grep(pattern = "a.{3}b",x = ss) #{}匹配"ab"之间有3个任意字符

## [1] 1 2 4 5
## integer(0)

例子：位置字符（^、$）的应用

ss <- c("1314","abc","a b c","ABC","aB12c","13ab14c")
grep(pattern = "^1",x = ss) #匹配以1开始的索引
grep(pattern = "4$",x = ss) #匹配以4结束的索引

## [1] 1 6
## [1] 1

例子：方括号（[]）的应用，注意方括号与^连用表否定

ss <- c("a2b","a1cb","ab","a111b","a1b","acb")
grep(pattern = "a[2c]b" ,x = ss) #ab中间有括号里面（2或c）的任意1个字符
grep(pattern = "a[2c]*b" ,x = ss) #ab中间有任意数量的括号里面（2或c）的任意1个字符
grep(pattern = "a[0-9]b",x = ss) #"ab"中间有 “0到9”中的任意1个字符
grep(pattern = "a[a-z]b",x = ss) #"ab"中间有 “a到z”中的任意1个字符

grep(pattern = "a[^c]b",x = ss) ##这里的^表示否定，“非”的意思。"ab"中间没有以 “c”开头的字符

## [1] 1 6
## [1] 1 3 6
## [1] 1 5
## [1] 6
## [1] 1 5

例子：圆括号的应用可结合gsub函数，替换

ss <- c("1314","abc","a b c","ABC","aB12c","13ab14c")

grep(pattern = "(13).4",x = ss) #匹配有13组合+任意1个字符+4的索引
grep(pattern = "(13|13ab).4",x = ss) #匹配13或1314的组合+任意1个字符+4的索引
gsub(pattern = "(13|13ab).4",replacement = "XXXX",x = ss) #替换13或1314的组合+任意1个字符+4为“XXXX”
gsub(pattern = "(13|13ab).4",replacement = "\\1",x = ss)#替换13或1314的组合+任意1个字符+4为第一次匹配的内容，\\1代表反向引用

## [1] 1
## [1] 1 6
## [1] "XXXX"  "abc"   "a b c" "ABC"   "aB12c" "XXXXc"
## [1] "13"    "abc"   "a b c" "ABC"   "aB12c" "13abc"

转义符的应用

ss <- c("acb","a?b","a??b")

grep(pattern = "a\\?b",x = ss) #\\?表示问号本身
grep(pattern = "a\\?+b",x = ss) #\\?+表示至少一个问号
grep(pattern = "^\\w+$",x = ss) #任意个字符开头并结束，及从头到尾全是字符（字母或汉字）
grep(pattern = "\\W+",x = ss) #含有非字符（符合 空格）成分
grep(pattern = "\\d+",x = ss) #含有数字成分
grep(pattern = "\\D+",x = ss) #含有非数字成分

## [1] 2
## [1] 2 3
## [1] 1
## [1] 2 3
## integer(0)
## [1] 1 2 3

17.3 常用文本处理函数

length/nchar （向量元素的个数/每个向量元素字符的长度）
模式查询：grep/grepl （索引/返回逻辑值）
模式替换 sub/gsub
截取/修剪：substr/substring/strtrim
合并/拆分：paste/strsplit
转换/翻译：tolwer/toupper/chartr

ss1 <- c(1,12,123,"abcdef")

length(ss1)
nchar(ss1)

## [1] 4
## [1] 1 2 3 6

ss1 <- c(1,12,123,"abcdef")

substr("abcdef", 2, 4) #截取字符第2到4位
substring("abcdef", first = 1:6, last = 1:6)  #
strtrim(ss1,width = 2) #修剪得到每个元素字符前两位

## [1] "bcd"
## [1] "a" "b" "c" "d" "e" "f"
## [1] "1"  "12" "12" "ab"

ss1 <- c(1,12,123,"abcdef")

paste(ss1,"###")

## [1] "1 ###"      "12 ###"     "123 ###"    "abcdef ###"

paste(ss1,"###",sep = "-") #sep 两个字符间的分隔符

## [1] "1-###"      "12-###"     "123-###"    "abcdef-###"

paste(ss1,"###",sep = "-",collapse = ";") #collapse 将多个向量元素融合

## [1] "1-###;12-###;123-###;abcdef-###"

strsplit("abc def",split = "") #每个字符拆分
strsplit("abc def",split = " ") #空格符拆分
strsplit("abc  def",split = " +") #split可跟正则表达式，“空格+”表示一个或多个空格拆分空格符拆分

ss1 <- c(1,12,123,"abcdef")
strsplit(ss1,split = "")

## [[1]]
## [1] "a" "b" "c" " " "d" "e" "f"
## 
## [[1]]
## [1] "abc" "def"
## 
## [[1]]
## [1] "abc" "def"
## 
## [[1]]
## [1] "1"
## 
## [[2]]
## [1] "1" "2"
## 
## [[3]]
## [1] "1" "2" "3"
## 
## [[4]]
## [1] "a" "b" "c" "d" "e" "f"

17.4 案例

17.4.1 查找指定目录下的jpg图像文件（list.files函数）

dic

dirctory="../front_end/fig/"
file_name=list.files(path = dirctory, #文件路径
                     pattern = "\\.jpg$", #正则表达式
                     recursive = TRUE, #是否迭代子目录
                     full.names = TRUE, #是否显示文件全部路径
                     ignore.case = TRUE) #是否忽略大小写
file_name
file.size(file_name) #查看文件大小，单位为KB

##  [1] "../front_end/fig//appendix/100-01.jpg"        
##  [2] "../front_end/fig//appendix/100-02.jpg"        
##  [3] "../front_end/fig//appendix/100-03.jpg"        
##  [4] "../front_end/fig//appendix/ps-copy.jpg"       
##  [5] "../front_end/fig//appendix/切图导出.jpg"      
##  [6] "../front_end/fig//appendix/图层.jpg"          
##  [7] "../front_end/fig//case/80-01.jpg"             
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## [60] "../front_end/fig//CSS/CSS三角.jpg"            
## [61] "../front_end/fig//CSS/h5新增语义标签.jpg"     
## [62] "../front_end/fig//CSS/翻页.jpg"               
## [63] "../front_end/fig//CSS/内马尔.jpg"             
## [64] "../front_end/fig//CSS/品优购整体图.jpg"       
## [65] "../front_end/fig//CSS/三角加强.jpg"           
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##  [1]  13029  11057  49485 153758 361807 338243  58444  19010   7625  28207
## [11]  13162  87024  23939  13528   9028   3909 147563  98126  61088  35949
## [21]  24838  22270  14697  10954  13845  37489  20298  24826  10215  11651
## [31]  22618  17758  14780  25265  22767  28288  36725  18726  15727  69040
## [41]  11881  59069  17018  43281  11027  14447  40416  30519  53498  21247
## [51]  36862  19355  11262  14066   7132  10024   5582   6286  17656   2997
## [61]  31630  16079  41010 128708   5517  68877  62464  30827 363379  67013
## [71]  38112  89882 176514 161340  61809  30913  92362  14271   6913   7374
## [81]  58411  45855   7360   8515  13057  56081  14049  13009  22879  26817
## [91]  50769  71105  99416  51007 144687  58105 936815  10285  23057

tolower(c("aBc","ABCxx")) #全部小写
toupper(c("aBc","ABCxx")) #全部大写

## [1] "abc"   "abcxx"
## [1] "ABC"   "ABCXX"

xseq <- "ATCGCCC"
chartr(old = "ATCG",new = "UAGC",x = xseq) #旧字符翻译成新字符，如A翻译成U，T翻译成A...

## [1] "UAGCGGG"

17.4.2 全宋词

gsub(pattern = ".\\s",replacement = "",x = songci) #去除文本向量中所有空格符
sentence=grep(pattern = "|",x = songci,value = TRUE) #查找含“杨”或“柳”的句子
tail(sentence)

17.4.3 SCI（筛选行）

筛选出杂志名包含NATURE，且19年IF>3的行

grepl函数返回TURE or FALSE，表示向量中每个元素是否满足正则表达式

data
ss1 <- grepl(pattern = "nature",x = data$tittle,ignore.case = TRUE)
ss2 <- data$IF > 3
dt[ss1 & ss2,]