# ch05: Print examples of chapter 5 of 'R for Dummies'. In rfordummies: Code Examples to Accompany the Book "R for Dummies"

## Description

To print a listing of all examples of a chapter, use `ch5()`. To run all the examples of `ch5()`, use `example(ch5)`.

## Usage

 ```1 2 3``` ```ch05() ch5() ```

`toc`
Other Chapters: `ch01`, `ch02`, `ch03`, `ch04`, `ch06`, `ch07`, `ch08`, `ch09`, `ch10`, `ch11`, `ch12`, `ch13`, `ch14`, `ch15`, `ch16`, `ch17`, `ch18`, `ch19`, `ch20`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172``` ```# Chapter 5 - Getting Started with Reading and Writing # Using Character Vectors for Text Data ## Assigning a value to a character vector x <- "Hello world!" is.character(x) length(x) nchar(x) ## Creating a character vector with more than one element x <- c("Hello", "world!") length(x) nchar(x) ## Extracting a subset of a vector letters LETTERS letters[10] LETTERS[24:26] tail(LETTERS, 5) head(letters, 10) ## Naming the values in your vectors ### Looking at how named vectors work str(islands) islands[c("Asia", "Africa", "Antarctica")] names(islands)[1:9] names(sort(islands, decreasing=TRUE)[1:6]) ## Creating and assigning named vectors month.days <- c(31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31) names(month.days) <- month.name month.days names(month.days[month.days==31]) # Manipulating Text ## String theory: Combining and splitting strings ### Splitting text pangram <- "The quick brown fox jumps over the lazy dog" pangram strsplit(pangram, " ") words <- strsplit(pangram, " ")[[1]] words ### Changing text case unique(tolower(words)) toupper(words[c(4, 9)]) tolower("Some TEXT in Mixed CASE") ### Concatenating text paste("The", "quick", "brown", "fox") paste(c("The", "quick", "brown", "fox")) paste(words, collapse=" ") paste(words, collapse="_") paste(LETTERS[1:5], 1:5, sep="_", collapse="---") paste("Sample", 1:5) paste(c("A", "B"), c(1, 2, 3, 4), sep="-") paste(c("A"), c(1, 2, 3, 4, 5), sep="-") ## Sorting text sort(letters, decreasing=TRUE) sort(words) ## Finding text inside text ### Searching for individual words head(state.name) ### Searching by position head(substr(state.name, start=3, stop=6)) ### Searching by pattern grep("New", state.name) state.name[29] state.name[grep("New", state.name)] state.name[grep("new", state.name)] ### Searching for multiple words state.name[grep(" ", state.name)] state.name[grep("East", state.name)] ## Substituting text gsub("cheap", "sheep's", "A wolf in cheap clothing") x <- c("file_a.csv", "file_b.csv", "file_c.csv") y <- gsub("file_", "", x) y gsub(".csv", "", y) #### Extending text functionality with stringr ## Not run: install.packages("stringr") ## End(Not run) library(stringr) ## Revving up with regular expressions rwords <- c("bach", "back", "beech", "beach", "black") grep("beach|beech", rwords) rwords[grep("beach|beech", rwords)] rwords[grep("be(a|e)ch", rwords)] rwords[grep("b(e*|a*)ch", rwords)] # Factoring in Factors ## Creating a factor directions <- c("North", "East", "South", "South") factor(directions) factor(directions, levels= c("North", "East", "South", "West")) factor(directions, levels= c("North", "East", "South", "West"), labels=c("N", "E", "S", "W")) ## Converting a factor directions <- c("North", "East", "South", "South") directions.factor <- factor(directions) directions.factor as.character(directions.factor) as.numeric(directions.factor) numbers <- factor(c(9, 8, 10, 8, 9)) as.character(numbers) as.numeric(numbers) as.numeric(as.character(numbers)) ## Looking at levels str(state.region) levels(state.region) levels(state.region) <- c("NE", "S", "NC", "W") head(state.region) nlevels(state.region) length(levels(state.region)) levels(state.region)[2:3] ## Distinguishing data types head(state.region) table(state.region) state.region ## Working with ordered factors status <- c("Lo", "Hi", "Med", "Med", "Hi") ordered.status <- factor(status, levels=c("Lo", "Med", "Hi"), ordered=TRUE) ordered.status table(status) table(ordered.status) ```