[第一部份].R 的基本資料屬性包含以下五種
class("test")
## [1] "character"
class(10.10)
## [1] "numeric"
class(10)
## [1] "numeric"
class(as.integer(3)) # 因為 R 計算上是都是以雙倍精確度來計算，所以必須指定為 integer，不然都會被當成 numeric
## [1] "integer"
class(as.integer(3.1)) # as.integer 可以將不是整數的數值變成整數
## [1] "integer"
class(as.integer(T)) # as.integer(T) = 1
## [1] "integer"
class(as.integer(F)) # as.integer(T) = 0
## [1] "integer"
class(2+2i)
## [1] "complex"
class(TRUE) # 注意都要大寫，不可寫 True，但可以簡化成 T
## [1] "logical"
class(T)
## [1] "logical"
[第二部份].R的基本變數與資料
2-1.一般變數
x = 12.5 # 一般數值
A1= "John" #文字字串
z = FALSE # 邏輯值 TRUE/FALSE 或 T/F
y = 2.4e3 # 2.4 x 10三次方 = 2400
A2 = paste(A1,"Dow",sep="") # A2="JohnDow"
x^2 # 平方, 也可寫成 x**2
## [1] 156.25
x + 3 ; x - 3 ; x * 3 ; x / 3 # 加減乘除
## [1] 15.5
## [1] 9.5
## [1] 37.5
## [1] 4.166667
x %/% 3 # 整除
## [1] 4
x %% 3 # 餘數
## [1] 0.5
2-2.向量 (Vector)
x = c(1, 15.2, 33) # c是combine的意思
y = c("男","女","女") # 文字向量
z = c(TRUE,FALSE, FALSE, TRUE) # 或 c(T,F,F,T)
x2 = x + 1 # x2 = c(2, 16.2, 14)
x[2] # 15.2
## [1] 15.2
x[c(1,3)] # 第一和第三個元素，就是(1, 33)
## [1] 1 33
x[-2] # 去掉第二個元素，也就是(1, 33)
## [1] 1 33
y[3] # "女"
## [1] "女"
y[1:2] # c("男","女")
## [1] "男" "女"
#vector 中所有元素都必須是同一種資料屬性
#c() 也可以被用來結合兩個向量
x <- c(1:5) # 1:5 表示從1到5 . 就是(1,2,3,4,5)
y <- c(2, 4, 8)
z <- c(x, y)
z
## [1] 1 2 3 4 5 2 4 8
2-3.Factor 變數
#其實就是”分類”的意思
#可以把”文字向量”分類，也可以把”數值向量”分類
gender = c("Boy","Girl","Girl","Boy","Girl") # 文字向量
gender = as.factor(gender) ; gender # Factor 變數 # 用分號區隔指令
## [1] Boy Girl Girl Boy Girl
## Levels: Boy Girl
parttime = c(1,0,0,0,1) # 有無打工(數值向量)
parttime = as.factor(parttime) ; parttime # Factor 變數
## [1] 1 0 0 0 1
## Levels: 0 1
parttime[2] # 顯示出第二筆資料(Factor 變數的指標使用跟向量變數一樣)
## [1] 0
## Levels: 0 1
2-4.串列 (List)
#是向量的的擴充，可包含不同屬性的元素
#list 是非常方便好用的資料形態。尤其是需儲存不同類型資料的時候，特別好用。
friend1 = list(fname="John",age=32,child.ages=c(2,5))
friend1
## $fname
## [1] "John"
##
## $age
## [1] 32
##
## $child.ages
## [1] 2 5
friend1$fname # 等於 friend1[[1]] # $是指定變項
## [1] "John"
friend1$age # 等於 friend1[[2]]
## [1] 32
friend1$child.ages # 等於 friend1[[3]]
## [1] 2 5
friend1$child.ages[2] # 等於 friend1[[3]][2]
## [1] 5
2-5.矩陣 (Matrix)
M1 <- matrix(c(1:144), 12, 12)
M1[6, ]
## [1] 6 18 30 42 54 66 78 90 102 114 126 138
M1[, 6]
## [1] 61 62 63 64 65 66 67 68 69 70 71 72
x1 = c(11,12,13)
x2 = c(21,22,23)
M1 = rbind(x1,x2) #row bind; 視為橫列連起來
M2 = cbind(x1,x2) #column bind; 視為直行連起來
2-6.資料框架 (Data Frame)
data(iris)
names(iris) # 查看變數名
## [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width"
## [5] "Species"
dim(iris) # 查看列數與欄數
## [1] 150 5
summary(iris)#基本敘述性統計量
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100
## 1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300
## Median :5.800 Median :3.000 Median :4.350 Median :1.300
## Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
## 3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
## Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
## Species
## setosa :50
## versicolor:50
## virginica :50
##
##
##
iris #把iris資料全部show出來
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginica
head(iris, 12) # 只看前12筆資料
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
tail(iris, 12) # 只看尾巴12筆資料
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginica
iris1 <- iris[1:12, ] # 把iris前12筆資料存成iris1
iris1[6, ] # iris1第6筆是多少(row)
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 6 5.4 3.9 1.7 0.4 setosa
iris1[c(4, 10) , ] #取得第4 及第10 列資料
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 4 4.6 3.1 1.5 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
以下三種寫法都代表同一件事(Column)
iris1[, 2] # iris1第2筆是多少(Column)
## [1] 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4
iris1[, "Sepal.Width"] #和 iris1[, 2] 相同
## [1] 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4
iris1$Sepal.Width
## [1] 3.5 3.0 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 3.7 3.4
subset(iris1, Sepal.Width >= 3.5)#取得Sepal.Width 大於等於3.5 的資料
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 11 5.4 3.7 1.5 0.2 setosa
[第三部份].R的資料匯入與輸出
3-1.如果我的檔案是.csv檔
babies = read.csv("d:/Rdata Practice/babies.csv") #把babies.csv 叫進來
str(babies) #把babies資料的屬性show出來
## 'data.frame': 1236 obs. of 7 variables:
## $ bwt : int 120 113 128 123 108 136 138 132 120 143 ...
## $ gestation: int 284 282 279 NA 282 286 244 245 289 299 ...
## $ parity : int 0 0 0 0 0 0 0 0 0 0 ...
## $ age : int 27 33 28 36 23 25 33 23 25 30 ...
## $ height : int 62 64 64 69 67 62 62 65 62 66 ...
## $ weight : int 100 135 115 190 125 93 178 140 125 136 ...
## $ smoke : int 0 0 1 0 1 0 0 0 0 1 ...
head(babies , 15) # 只看前15筆資料
## bwt gestation parity age height weight smoke
## 1 120 284 0 27 62 100 0
## 2 113 282 0 33 64 135 0
## 3 128 279 0 28 64 115 1
## 4 123 NA 0 36 69 190 0
## 5 108 282 0 23 67 125 1
## 6 136 286 0 25 62 93 0
## 7 138 244 0 33 62 178 0
## 8 132 245 0 23 65 140 0
## 9 120 289 0 25 62 125 0
## 10 143 299 0 30 66 136 1
## 11 140 351 0 27 68 120 0
## 12 144 282 0 32 64 124 1
## 13 141 279 0 23 63 128 1
## 14 110 281 0 36 61 99 1
## 15 114 273 0 30 63 154 0
tail(babies , 15) # 只看尾巴15筆資料
## bwt gestation parity age height weight smoke
## 1222 114 290 1 21 65 120 1
## 1223 124 288 1 21 64 116 1
## 1224 115 262 1 23 64 136 1
## 1225 143 281 0 28 65 135 1
## 1226 113 287 1 29 70 145 1
## 1227 109 244 1 21 63 102 1
## 1228 103 278 0 30 60 87 1
## 1229 118 276 0 34 64 116 0
## 1230 127 290 0 27 65 121 0
## 1231 132 270 0 27 65 126 0
## 1232 113 275 1 27 60 100 0
## 1233 128 265 0 24 67 120 0
## 1234 130 291 0 30 65 150 1
## 1235 125 281 1 21 65 110 0
## 1236 117 297 0 38 65 129 0
3-2.如果我的檔案是.txt檔
xdata = read.table("d:/Rdata Practice/babies.txt",header=TRUE) # header: 表頭
head(xdata) # 只看前6筆資料
## bwt gestation parity age height weight smoke
## 1 120 284 0 27 62 100 0
## 2 113 282 0 33 64 135 0
## 3 128 279 0 28 64 115 1
## 4 123 NA 0 36 69 190 0
## 5 108 282 0 23 67 125 1
## 6 136 286 0 25 62 93 0
3-3.另存新檔(輸出資料)
data <- iris # iris 是 R 內建的資料。
write.table(data, file = "d:/Rdata Practice/R BasicLab/test.CSV", sep = ",")
[第四部份].合併與分割資料
4-1.資料合併
x <- c(1, 2, 3)
y <- c(10, 20, 30)
union(x ,y) # union 如英文名稱就是取聯集
## [1] 1 2 3 10 20 30
rbind(x, y) # 透過 row 合併
## [,1] [,2] [,3]
## x 1 2 3
## y 10 20 30
cbind(x, y) # 透過 column 合併
## x y
## [1,] 1 10
## [2,] 2 20
## [3,] 3 30
x <- cbind(c("Tom", "Joe", "Vicky"), c(27, 29, 28))
y <- cbind(c("Tom", "Joe", "Vicky"), c(178, 186, 168))
colnames(x) <- c("name", "age")
colnames(y) <- c("name", "tall")
merge(x, y, by = "name") # 將 data.frame 透過一個欄位進行合併
## name age tall
## 1 Joe 29 186
## 2 Tom 27 178
## 3 Vicky 28 168
4-2.資料分割
data <- iris
split(data, sample(rep(1:2, 75))) # rep(1:2, 75) 產生 1,2 交錯的向量，但加了前面的 sample 則是隨機抽取
## $`1`
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 102 5.8 2.7 5.1 1.9 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 150 5.9 3.0 5.1 1.8 virginica
##
## $`2`
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 149 6.2 3.4 5.4 2.3 virginica
data <- iris
subset(data, Sepal.Length > 5) # 只會出現 Sepal.Length > 5 的資料
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginica
subset(data, Sepal.Length > 5,select = Sepal.Length) # 只會出現 Sepal.Length > 5 的資料且欄位只有 Sepal
## Sepal.Length
## 1 5.1
## 6 5.4
## 11 5.4
## 15 5.8
## 16 5.7
## 17 5.4
## 18 5.1
## 19 5.7
## 20 5.1
## 21 5.4
## 22 5.1
## 24 5.1
## 28 5.2
## 29 5.2
## 32 5.4
## 33 5.2
## 34 5.5
## 37 5.5
## 40 5.1
## 45 5.1
## 47 5.1
## 49 5.3
## 51 7.0
## 52 6.4
## 53 6.9
## 54 5.5
## 55 6.5
## 56 5.7
## 57 6.3
## 59 6.6
## 60 5.2
## 62 5.9
## 63 6.0
## 64 6.1
## 65 5.6
## 66 6.7
## 67 5.6
## 68 5.8
## 69 6.2
## 70 5.6
## 71 5.9
## 72 6.1
## 73 6.3
## 74 6.1
## 75 6.4
## 76 6.6
## 77 6.8
## 78 6.7
## 79 6.0
## 80 5.7
## 81 5.5
## 82 5.5
## 83 5.8
## 84 6.0
## 85 5.4
## 86 6.0
## 87 6.7
## 88 6.3
## 89 5.6
## 90 5.5
## 91 5.5
## 92 6.1
## 93 5.8
## 95 5.6
## 96 5.7
## 97 5.7
## 98 6.2
## 99 5.1
## 100 5.7
## 101 6.3
## 102 5.8
## 103 7.1
## 104 6.3
## 105 6.5
## 106 7.6
## 108 7.3
## 109 6.7
## 110 7.2
## 111 6.5
## 112 6.4
## 113 6.8
## 114 5.7
## 115 5.8
## 116 6.4
## 117 6.5
## 118 7.7
## 119 7.7
## 120 6.0
## 121 6.9
## 122 5.6
## 123 7.7
## 124 6.3
## 125 6.7
## 126 7.2
## 127 6.2
## 128 6.1
## 129 6.4
## 130 7.2
## 131 7.4
## 132 7.9
## 133 6.4
## 134 6.3
## 135 6.1
## 136 7.7
## 137 6.3
## 138 6.4
## 139 6.0
## 140 6.9
## 141 6.7
## 142 6.9
## 143 5.8
## 144 6.8
## 145 6.7
## 146 6.7
## 147 6.3
## 148 6.5
## 149 6.2
## 150 5.9
subset(data, Sepal.Length > 5,select = -Sepal.Length) # selct = 負的代表不要出現的欄位。
## Sepal.Width Petal.Length Petal.Width Species
## 1 3.5 1.4 0.2 setosa
## 6 3.9 1.7 0.4 setosa
## 11 3.7 1.5 0.2 setosa
## 15 4.0 1.2 0.2 setosa
## 16 4.4 1.5 0.4 setosa
## 17 3.9 1.3 0.4 setosa
## 18 3.5 1.4 0.3 setosa
## 19 3.8 1.7 0.3 setosa
## 20 3.8 1.5 0.3 setosa
## 21 3.4 1.7 0.2 setosa
## 22 3.7 1.5 0.4 setosa
## 24 3.3 1.7 0.5 setosa
## 28 3.5 1.5 0.2 setosa
## 29 3.4 1.4 0.2 setosa
## 32 3.4 1.5 0.4 setosa
## 33 4.1 1.5 0.1 setosa
## 34 4.2 1.4 0.2 setosa
## 37 3.5 1.3 0.2 setosa
## 40 3.4 1.5 0.2 setosa
## 45 3.8 1.9 0.4 setosa
## 47 3.8 1.6 0.2 setosa
## 49 3.7 1.5 0.2 setosa
## 51 3.2 4.7 1.4 versicolor
## 52 3.2 4.5 1.5 versicolor
## 53 3.1 4.9 1.5 versicolor
## 54 2.3 4.0 1.3 versicolor
## 55 2.8 4.6 1.5 versicolor
## 56 2.8 4.5 1.3 versicolor
## 57 3.3 4.7 1.6 versicolor
## 59 2.9 4.6 1.3 versicolor
## 60 2.7 3.9 1.4 versicolor
## 62 3.0 4.2 1.5 versicolor
## 63 2.2 4.0 1.0 versicolor
## 64 2.9 4.7 1.4 versicolor
## 65 2.9 3.6 1.3 versicolor
## 66 3.1 4.4 1.4 versicolor
## 67 3.0 4.5 1.5 versicolor
## 68 2.7 4.1 1.0 versicolor
## 69 2.2 4.5 1.5 versicolor
## 70 2.5 3.9 1.1 versicolor
## 71 3.2 4.8 1.8 versicolor
## 72 2.8 4.0 1.3 versicolor
## 73 2.5 4.9 1.5 versicolor
## 74 2.8 4.7 1.2 versicolor
## 75 2.9 4.3 1.3 versicolor
## 76 3.0 4.4 1.4 versicolor
## 77 2.8 4.8 1.4 versicolor
## 78 3.0 5.0 1.7 versicolor
## 79 2.9 4.5 1.5 versicolor
## 80 2.6 3.5 1.0 versicolor
## 81 2.4 3.8 1.1 versicolor
## 82 2.4 3.7 1.0 versicolor
## 83 2.7 3.9 1.2 versicolor
## 84 2.7 5.1 1.6 versicolor
## 85 3.0 4.5 1.5 versicolor
## 86 3.4 4.5 1.6 versicolor
## 87 3.1 4.7 1.5 versicolor
## 88 2.3 4.4 1.3 versicolor
## 89 3.0 4.1 1.3 versicolor
## 90 2.5 4.0 1.3 versicolor
## 91 2.6 4.4 1.2 versicolor
## 92 3.0 4.6 1.4 versicolor
## 93 2.6 4.0 1.2 versicolor
## 95 2.7 4.2 1.3 versicolor
## 96 3.0 4.2 1.2 versicolor
## 97 2.9 4.2 1.3 versicolor
## 98 2.9 4.3 1.3 versicolor
## 99 2.5 3.0 1.1 versicolor
## 100 2.8 4.1 1.3 versicolor
## 101 3.3 6.0 2.5 virginica
## 102 2.7 5.1 1.9 virginica
## 103 3.0 5.9 2.1 virginica
## 104 2.9 5.6 1.8 virginica
## 105 3.0 5.8 2.2 virginica
## 106 3.0 6.6 2.1 virginica
## 108 2.9 6.3 1.8 virginica
## 109 2.5 5.8 1.8 virginica
## 110 3.6 6.1 2.5 virginica
## 111 3.2 5.1 2.0 virginica
## 112 2.7 5.3 1.9 virginica
## 113 3.0 5.5 2.1 virginica
## 114 2.5 5.0 2.0 virginica
## 115 2.8 5.1 2.4 virginica
## 116 3.2 5.3 2.3 virginica
## 117 3.0 5.5 1.8 virginica
## 118 3.8 6.7 2.2 virginica
## 119 2.6 6.9 2.3 virginica
## 120 2.2 5.0 1.5 virginica
## 121 3.2 5.7 2.3 virginica
## 122 2.8 4.9 2.0 virginica
## 123 2.8 6.7 2.0 virginica
## 124 2.7 4.9 1.8 virginica
## 125 3.3 5.7 2.1 virginica
## 126 3.2 6.0 1.8 virginica
## 127 2.8 4.8 1.8 virginica
## 128 3.0 4.9 1.8 virginica
## 129 2.8 5.6 2.1 virginica
## 130 3.0 5.8 1.6 virginica
## 131 2.8 6.1 1.9 virginica
## 132 3.8 6.4 2.0 virginica
## 133 2.8 5.6 2.2 virginica
## 134 2.8 5.1 1.5 virginica
## 135 2.6 5.6 1.4 virginica
## 136 3.0 6.1 2.3 virginica
## 137 3.4 5.6 2.4 virginica
## 138 3.1 5.5 1.8 virginica
## 139 3.0 4.8 1.8 virginica
## 140 3.1 5.4 2.1 virginica
## 141 3.1 5.6 2.4 virginica
## 142 3.1 5.1 2.3 virginica
## 143 2.7 5.1 1.9 virginica
## 144 3.2 5.9 2.3 virginica
## 145 3.3 5.7 2.5 virginica
## 146 3.0 5.2 2.3 virginica
## 147 2.5 5.0 1.9 virginica
## 148 3.0 5.2 2.0 virginica
## 149 3.4 5.4 2.3 virginica
## 150 3.0 5.1 1.8 virginica
[補充範圍]4-3.資料比例
#install.packages("dplyr")
library(dplyr)
##
## Attaching package: 'dplyr'
##
## The following object is masked from 'package:stats':
##
## filter
##
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
data(iris)
X = summarise(group_by(iris, Species), tsl = sum(Sepal.Length))
y = X$tsl / sum(X$tsl)
pie(y,label=c("setosa","versicolor","virginica"),density=100,col=2:4)
dev.off()#把圖型清除
## null device
## 1