> str_replace(val,"[ab]","-") [1]"-bc""123""c-a" # 把目标字符串所有出现的a或b,替换为- > str_replace_all(val,"[ab]","-") [1]"--c""123""c--" # 把目标字符串所有出现的a,替换为被转义的字符 > str_replace_all(val,"[a]","\1\1") ...
str_replace_na()函数可以将其替换成字符串"NA",从而方便对缺失值的操作。 na <- NA str_length(na) ## [1] NA txt2 <- str_replace_na(na) str_length(txt2) ## [1] 2 分解 类似Excel的分列操作,str_split()函数可以根据特定字符对字符串进行分解。语法结构如下: str_split(string, pattern, n...
> 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", "a...
str_replace_na()将缺失值转换为"NA";stri_replace()用于底层实现。 例子 fruits <- c("one apple","two pears","three bananas")str_replace(fruits,"[aeiou]","-")#> [1] "-ne apple" "tw- pears" "thr-e bananas"str_replace_all(fruits,"[aeiou]","-")#> [1] "-n- -ppl-" "tw-...
用str_glue函数 代码演示 first<- c("Luke","Han","Jean-Luc") last<- c("Skywalker","Solo","Picard") str_glue("My name is {first}. {first} {last}.") minimum_age <-18 over_minimum <- c(5,17,33) str_glue("{first} {last} is {minimum_age + over_minimum} years old.") ...
str_replace(): 替换字符串 该函数可以用于替换字符串中的特定部分。其语法如下: str_replace(string,pattern,replacement) 其中,string 为需要进行替换的字符串,pattern 为需要替换的部分的模式,replacement 为替换后的内容。示例代码如下: library(stringr)string<-"I love cats and dogs."str_replace(string,"cat...
str_sort(letters, locale = "en") str_replace(),字符串替换函数 str_replace(string, pattern, replacement) str_replace_all(string, pattern, replacement) str_replace_na(string, replacement = "NA") string:需要处理的字符向量 pattern:指定匹配模式, ...
str_replace(string,pattern,replacement) 只替换首次满足条件的子字符串 str_replace_all(string,pattern,replacement) 替换掉所有满足条件的字符串, 如 str_replace_all(commadata,',','' string 字符串向量 pattern 待替换的字符串,试用正则表达式 replacement 用来替换的字符串 ...
str_replace(string, pattern, replacement) #-提取字符串---hw <-"Hadley Wickham"> str_sub(hw,1,6)[1]"Hadley"> str_sub(hw, c(1,8), c(6,14))[1]"Hadley""Wickham"#--替换字符串---> fruits <- c("one apple","two pears","three bananas")> st...
1、字符串拆分利器–str_split 2、字符串替换利器–str_replace_all 3、字符串抽取利器–str_match_all 4、字符串截取利器–str_sub 字符串处理中最为常见的四种手段有“拆、替、抽、取”。强烈推荐stringr包,个人觉得远比R自带的grep、regexp、strsplit、sub等函数好用。