Microsoft Word - AEL CH12_彩色.doc

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2 R R Exploratory Data Analysis EDA R 12-1 Data Frame nrow() ncol() dim() > nrow(iris) # iris [1] 150 > ncol(iris) # iris [1] 5 > dim(iris) # iris [1] nrow() number of rows ncol() number of columns dim() dimensions head() tail() names() 12-2

12 > head(iris) # iris 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.

3 12 > head(iris) # iris Sepal.Length Sepal.Width Petal.Length Petal.Width Species setosa setosa setosa setosa setosa setosa > tail(iris) # iris Sepal.Length Sepal.Width Petal.Length Petal.Width Species virginica virginica virginica virginica virginica virginica > names(iris) # iris [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species" summary() > summary(iris) # iris 12-1 summary(iris) 12-3

4 R str() str() str() structure > str(iris) 12-2 str(iris) 12-2 Base Plotting System R hist() hist(rnorm(1000)) boxplot() boxplot(sepal.length ~ Species, data = iris) plot(..., type = "l") plot(airpassengers, type = "l") plot() plot(cars) barplot() barplot(table(mtcars$cyl)) curve() curve(sin, from = 0, to = pi * 2) 12-4

5 12 hist() hist() histogram >hist(rnorm(1000)) 12-3 hist(rnorm(1000)) rnorm() boxplot() iris Species Sepal.Length > boxplot(sepal.length ~ Species, data = iris) 12-5

6 R 12-4 boxplot(sepal.length ~ Species, data = iris) plot(..., type = "l") > x <- seq(from = as.date(" "), to = as.date(" "), by = 1) > set.seed(123) # y > y <- sample(1:100, size = 31, replace = TRUE) > plot(x, y, type = "l") 12-5 plot(x, y, type = l ) 12-6

7 12 x y type = "l" line set.seed() sample() y 123 sample() set.seed(123) y R AirPassengers LakeHuron ts time series plot() type = "l" > class(airpassengers) [1] "ts" > class(lakehuron) [1] "ts" > plot(airpassengers) > plot(lakehuron) 12-6 plot(airpassengers) 12-7

8 R 12-7 plot(lakehuron) plot() > plot(cars$speed, cars$dist) 12-8 lot(carsspeed,carsdist) 12-8

$times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } >$

9 12 plot() scatter matrix > plot(iris) 12-9 plot(carsspeed,carsdist) barplot() ice_cream_flavor 100 程式碼 12-1 > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > ice_cream_flavor 12-9

$(i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > table(ice_cream_flavor) ice_cream_flavor chocolate matcha other vanilla 32 20 25 23$

10 輕鬆學習 R 語言圖 ice_cream_flavor 的輸出在這個眼花撩亂的 ice_cream_flavor 向量中該如何很快地得知這 100 個人最愛口味的分佈呢可以使用 table() 函數它的作用就像是樞紐分析可以幫我們把凌亂的資料統整起來程式碼 12-2 > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > table(ice_cream_flavor) ice_cream_flavor chocolate matcha other vanilla 我們可以一目瞭然有 32 個人最喜歡的口味是巧克力 20 個人最喜歡抹茶 25 個人喜歡其他的口味而有 23 個人最喜歡香草這時就可以使用 barplot() 函數將這個清晰的結果繪畫成清楚的長條圖 12-10

$12 程式碼 12-3 > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha",$

11 12 程式碼 12-3 > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > barplot(table(ice_cream_flavor)) barplot(table(ice_cream_flavor)) curve() from to sin() > curve(sin, from = -pi, to = pi) 12-11

12 R curve(sin, from = -pi, to = pi) 2 my_sqr() y f ( x) x -3 3 > my_sqr <- function(x){ + return(x^2) + } > curve(my_sqr, from = -3, to = 3) curve(my_sqr, from = -3, to = 3) 12-12

13 12 自訂標題 X 軸標籤與 Y 軸標籤 main xlab ylab > plot(cars, main = "Car speed vs. braking distance", xlab = "Car speed (mph)", ylab = "Braking distance(ft)") 加入格線 grid() X Y > plot(cars, main = "Car speed vs. braking distance", xlab = "Car speed (mph)", ylab = "Braking distance(ft)") > grid() 12-13

$R 12-15 調整圖形為水平方向 horiz = TRUE > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <-$

14 R 調整圖形為水平方向 horiz = TRUE > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > barplot(table(ice_cream_flavor), horiz = TRUE)

15 12 調整刻度顯示方向 las = 1 > ice_cream_flavor <- rep(na, times = 100) > for (i in 1:100){ + ice_cream_flavor[i] <- sample(c("vanilla", "chocolate", "matcha", "other"), size = 1) + } > barplot(table(ice_cream_flavor), horiz = TRUE, las = 1) 調整刻度文字大小 chocolate cex.name Y > barplot(table(ice_cream_flavor), horiz = TRUE, las = 1, cex.name = 0.8) cex.name 12-15

R X cex.axis > barplot(table(ice_cream_flavor), horiz = TRUE, las = 1, cex.name = 0.8, cex.axis = 1.2) 12-19 cex.

16 R X cex.axis > barplot(table(ice_cream_flavor), horiz = TRUE, las = 1, cex.name = 0.8, cex.axis = 1.2) cex.axis cex character expansion factor 1 在直方圖上加上密度曲線 density() lines() freq = FALSE > norm_dist <- rnorm(1000) > hist(norm_dist, freq = FALSE) > lines(density(norm_dist)) 12-16

17 調整資料點的形狀與顏色 pch col pch plotting character col color > plot(cars, pch = 2, col = "red") #

18 R > iris_pch <- c(1, 2, 3)[as.numeric(iris$Species)] > plot(iris$sepal.length, iris$sepal.width, col = iris$species, pch = iris_pch) pch col Graphical Parameters 繪畫多個圖形 par(mfrow = c(m, n)) mxn mfrow matrix of figures entered row-wise 程式碼 12-4 > par(mfrow = c(2, 2)) > boxplot(iris$sepal.length ~ iris$species, main = "Sepal length by species") > boxplot(iris$sepal.width ~ iris$species, main = "Sepal width by species") > boxplot(iris$petal.length ~ iris$species, main = "Petal length by species") > boxplot(iris$petal.width ~ iris$species, main = "Petal width by species") 12-18

19 RStudio Plots Export

20 R Base Plotting System Google StackOverflow 12-20

21 R Base Plotting System 2X2 Base Plotting System R Graphics Cookbook Graphical Parameters

Microsoft PowerPoint _cp09_繪圖功能與文字.pptx

Microsoft PowerPoint _cp09_繪圖功能與文字.pptx 105-2: EE4052 計算機程式設計 Computer Programming 連豊力臺大電機系 Feb 2017 - Jun 2017 課程主題進度 2 Unit 09: 繪圖功能與文字一張圖的長寬或大小, 主標題, 軸標題, 字體等特性的設定數據點的顏色要有變化數據點的形式要有變化數據加上不同註解 3 大綱繪圖視窗之設定常用的圖形參數座標軸及邊界加入文字多張圖形多張圖形之位置安排