字符串处理中基本函数的使用

R自带函数与stringr包函数对比

> states <- row.names(USArrests)
> # 提取字符串子集
> substr(x = states, start = 1, stop = 4)
[1] "Alab" "Alas" "Ariz" "Arka" "Cali" "Colo" "Conn" "Dela" "Flor" "Geor" "Hawa" "Idah" "Illi" "Indi" "Iowa" "Kans" "Kent"
[18] "Loui" "Main" "Mary" "Mass" "Mich" "Minn" "Miss" "Miss" "Mont" "Nebr" "Neva" "New " "New " "New " "New " "Nort" "Nort"
[35] "Ohio" "Okla" "Oreg" "Penn" "Rhod" "Sout" "Sout" "Tenn" "Texa" "Utah" "Verm" "Virg" "Wash" "West" "Wisc" "Wyom"
> abbreviate(states, minlength = 5)
Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware
"Alabm" "Alask" "Arizn" "Arkns" "Clfrn" "Colrd" "Cnnct" "Delwr"
Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas
"Flord" "Georg" "Hawai" "Idaho" "Illns" "Indin" "Iowa" "Kanss"
Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi
"Kntck" "Lousn" "Maine" "Mryln" "Mssch" "Mchgn" "Mnnst" "Mssss"
Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York
"Missr" "Montn" "Nbrsk" "Nevad" "NwHmp" "NwJrs" "NwMxc" "NwYrk"
North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina
"NrthC" "NrthD" "Ohio" "Oklhm" "Oregn" "Pnnsy" "RhdIs" "SthCr"
South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia
"SthDk" "Tnnss" "Texas" "Utah" "Vrmnt" "Virgn" "Wshng" "WstVr"
Wisconsin Wyoming
"Wscns" "Wymng"
> # 计算字符串长度
> nchar(states)
[1] 7 6 7 8 10 8 11 8 7 7 6 5 8 7 4 6 8 9 5 8 13 8 9 11 8 7 8 6 13 10 10 8 14 12 4 8 6 12 12 14 12
[42] 9 5 4 7 8 10 13 9 7
> str_count(states)
[1] 7 6 7 8 10 8 11 8 7 7 6 5 8 7 4 6 8 9 5 8 13 8 9 11 8 7 8 6 13 10 10 8 14 12 4 8 6 12 12 14 12
[42] 9 5 4 7 8 10 13 9 7
> str_length(states)
[1] 7 6 7 8 10 8 11 8 7 7 6 5 8 7 4 6 8 9 5 8 13 8 9 11 8 7 8 6 13 10 10 8 14 12 4 8 6 12 12 14 12
[42] 9 5 4 7 8 10 13 9 7
> # 大写和小写
> tolower(states) # 变为小写
[1] "alabama" "alaska" "arizona" "arkansas" "california" "colorado" "connecticut"
[8] "delaware" "florida" "georgia" "hawaii" "idaho" "illinois" "indiana"
[15] "iowa" "kansas" "kentucky" "louisiana" "maine" "maryland" "massachusetts"
[22] "michigan" "minnesota" "mississippi" "missouri" "montana" "nebraska" "nevada"
[29] "new hampshire" "new jersey" "new mexico" "new york" "north carolina" "north dakota" "ohio"
[36] "oklahoma" "oregon" "pennsylvania" "rhode island" "south carolina" "south dakota" "tennessee"
[43] "texas" "utah" "vermont" "virginia" "washington" "west virginia" "wisconsin"
[50] "wyoming"
> toupper(states) # 变为大写
[1] "ALABAMA" "ALASKA" "ARIZONA" "ARKANSAS" "CALIFORNIA" "COLORADO" "CONNECTICUT"
[8] "DELAWARE" "FLORIDA" "GEORGIA" "HAWAII" "IDAHO" "ILLINOIS" "INDIANA"
[15] "IOWA" "KANSAS" "KENTUCKY" "LOUISIANA" "MAINE" "MARYLAND" "MASSACHUSETTS"
[22] "MICHIGAN" "MINNESOTA" "MISSISSIPPI" "MISSOURI" "MONTANA" "NEBRASKA" "NEVADA"
[29] "NEW HAMPSHIRE" "NEW JERSEY" "NEW MEXICO" "NEW YORK" "NORTH CAROLINA" "NORTH DAKOTA" "OHIO"
[36] "OKLAHOMA" "OREGON" "PENNSYLVANIA" "RHODE ISLAND" "SOUTH CAROLINA" "SOUTH DAKOTA" "TENNESSEE"
[43] "TEXAS" "UTAH" "VERMONT" "VIRGINIA" "WASHINGTON" "WEST VIRGINIA" "WISCONSIN"
[50] "WYOMING"
> # 符号替换
> chartr("Tt", "Uu", "AgCTcctTagct")
[1] "AgCUccuUagcu"
> str_replace_all("AgCTcctTagct", pattern = "T", replacement = "U")
[1] "AgCUcctUagct"
> # 字符串连接
> paste("control", 1:3, sep = "_")
[1] "control_1" "control_2" "control_3"
> str_c("control", 1:3, sep = "_")
[1] "control_1" "control_2" "control_3"
> x <- c("I love R", "I'm fascinated by Statisitcs", "I")
> # 包含匹配
> grep(pattern = "love", x = x)
[1] 1
> grep(pattern = "love", x = x, value = TRUE)
[1] "I love R"
> grepl(pattern = "love", x = x)
[1] TRUE FALSE FALSE
> str_detect(string = x, pattern = "love")
[1] TRUE FALSE FALSE
> # match返回第一个完全匹配的位置
> match(x = "I",table = x)
[1] 3
> "I" %in% x
[1] TRUE
> # 字符串拆分
> text <- "I love R.\nI'm fascinated by Statisitcs."
> cat(text)
I love R.
I'm fascinated by Statisitcs.
> strsplit(text, split = " ")
[[1]]
[1] "I" "love" "R.\nI'm" "fascinated" "by" "Statisitcs."
> strsplit(text, split = "\\s")
[[1]]
[1] "I" "love" "R." "I'm" "fascinated" "by" "Statisitcs."
> str_split(text, pattern = "\\s")
[[1]]
[1] "I" "love" "R." "I'm" "fascinated" "by" "Statisitcs."
> # 匹配替换
> test_vector3 <- c("Without the vowels,We can still read the word.")
> sub(pattern = "[aeiou]",replacement = "-",x = test_vector3)
[1] "W-thout the vowels,We can still read the word."
> gsub(pattern = "[aeiou]",replacement = "-",x = test_vector3)
[1] "W-th--t th- v-w-ls,W- c-n st-ll r--d th- w-rd."
> str_replace_all(string = test_vector3, pattern = "[aeiou]",
+ replacement = "-")
[1] "W-th--t th- v-w-ls,W- c-n st-ll r--d th- w-rd."
> # 字符串定制输出
> string <- "Each character string in the input is first split into\n paragraphs
+ (or lines containing whitespace)"
> strwrap(x = string, width = 30)
[1] "Each character string in the" "input is first split into" "paragraphs (or lines" "containing whitespace)"
> str_wrap(string = string, width = 30)
[1] "Each character string in\nthe input is first split\ninto paragraphs (or lines\ncontaining whitespace)"
> cat(str_wrap(string = string, width = 30))
Each character string in
the input is first split
into paragraphs (or lines
containing whitespace)

R语言学习笔记(二十二):字符串处理中的函数对比(代码实现)的更多相关文章

  1. R语言学习笔记(十二):零碎知识点(31-35)

    31--round(),floor()和ceiling() round()四舍五入取整 floor()向下取整 ceiling()向上取整 > round(3.5) [1] 4 > flo ...

  2. R语言学习笔记(十五):获取文件和目录信息

    file.info() 参数是表示文件名称的字符串向量,函数会给出每个文件的大小.创建时间.是否为目录等信息. > file.info("z.txt") size isdir ...

  3. R语言学习笔记(十九):字符串处理中预定义字符组(表格介绍)

    R中预定义的字符组 代码 含义说明 [:digit:]或\\d 数字; [0-9] [^[:digit:]]或\\D 非数字; 等价于[^0-9] [:lower:] 小写字母; [a-z] [:up ...

  4. R语言学习笔记(十四):零碎知识点(41-45)

    41--ls( ) ls()可以用来列出现存的所有对象. pattern是一个具名参数,可以列出所有名称中含有字符串"s"的对象. > ls() [1] "s&qu ...

  5. R语言学习笔记(十):零碎知识点(21-25)

    21--assign() assign函数可以通过变量名的字符串来赋值 > assign('a', 1:3) > a [1] 1 2 3 > b <- c('a') > ...

  6. R语言学习笔记(十八):零碎知识点46-50

    seq_along与seq_len函数的使用 在for循环中有用 > seq_along(c(2,3,5)) [1] 1 2 3 > seq_len(3) [1] 1 2 3

  7. R语言学习笔记(十六):构建分割点函数

    选取预测概率的分割点 cutoff<- function(n,p){ pp<-1 i<-0 while (pp>=0.02) { model.predfu<-rep(&q ...

  8. 汇编入门学习笔记 (十二)—— int指令、port

    疯狂的暑假学习之  汇编入门学习笔记 (十二)--  int指令.port 參考: <汇编语言> 王爽 第13.14章 一.int指令 1. int指令引发的中断 int n指令,相当于引 ...

  9. VSTO 学习笔记(十二)自定义公式与Ribbon

    原文:VSTO 学习笔记(十二)自定义公式与Ribbon 这几天工作中在开发一个Excel插件,包含自定义公式,根据条件从数据库中查询结果.这次我们来做一个简单的测试,达到类似的目的. 即在Excel ...

随机推荐

  1. webpack-易混淆部分的解释

    原文链接: https://medium.com/@rajaraodv/webpack-the-confusing-parts-58712f8fcad9 webpack的核心哲学 1. 任何皆模块 正 ...

  2. HDFS pipeline写 -- 客户端

    上一篇说了datanode端如何处理pipeline写请求的,这里主要看DFSClient. 这里以append为例, write差不多. 创建一个pipeline用于append操作的流程: Fil ...

  3. 转 Ubuntu Linux 环境变量PATH设置

    Ubuntu Linux系统环境变量配置文件: /etc/profile : 在登录时,操作系统定制用户环境时使用的第一个文件 ,此文件为系统的每个用户设置环境信息,当用户第一次登录时,该文件被执行. ...

  4. Azure 镜像市场虚拟机映像制作指南

    本指南为 Azure 镜像市场(以下简称 Azure 镜像市场)独立软件供应商介绍制作虚拟机映像并上传到Azure的主要过程. 制作虚拟机映像有两种方式.一种是直接在Azure上申请相应的操作系统虚拟 ...

  5. Vue2学习笔记:过渡效果css

    过渡效果 Vue 提供了 transition 的封装组件,在下列情形中,可以给任何元素和组件添加 entering/leaving 过渡 <!DOCTYPE html> <html ...

  6. 转: 根据屏幕分辨率,浏览器调用不同css

    <link type="text/csss" href="" rel="stylesheet"/> <link type= ...

  7. UIView使用UIMotionEffect效果

    UIView使用UIMotionEffect效果 这个效果在模拟器上看不了,所以无法截图. UIView+MotionEffect.h  +  UIView+MotionEffect.m // // ...

  8. Zeal——好用的离线 API 文档大全!

    介绍 作为一名程序员,工作中学习中免不了是要查询API文档的,毕竟我们能记住的东西有限,而且经常也会碰到某个API一时想不起来的情况,而每次还要打开网页去查询还是挺麻烦的,这时候拥有一个款好用的本地离 ...

  9. jquery环形3D立体旋转特效

      jquery环形3D立体旋转特效 作者/代码整理:站长素材  (转载请附加本文地址,带有“懒人原生”字样的谢绝转载)发布日期:2013-07-20   立体效果比较强的jquery特效,周围小图组 ...

  10. HashMap,LinkedHashMap和Hashtable类的深入剖析与理解

    上一篇文章写了一些关于HashMap以及HashMap的线程安全问题,这篇文章再来说说Map系列中HashMap,LinkedHashMap和Hashtable三者之间的差异以及该注意的地方. Has ...