Package: graphics

• basic function for graphics
• Function List

library(help = "graphics")

• 簡單
  
• 可快速觀察資料
• 自由度大，易調整版面

1. Simple Plots
2. Add something to a plot
3. Adjust
   • Graphical Elements
   • Figure Margins
   • Multiple Figure Environment
4. Others
5. Projects

Object Class: data.frame or matrix or vector

Data: iris

練習Formula

##    speed dist
## 1      4    2
## 2      4   10
## 3      7    4
## 4      7   22
## 5      8   16
## 6      9   10
## 7     10   18
## 8     10   26
## 9     10   34
## 10    11   17
## 11    11   28
## 12    12   14
## 13    12   20
## 14    12   24
## 15    12   28
## 16    13   26
## 17    13   34
## 18    13   34
## 19    13   46
## 20    14   26
## 21    14   36
## 22    14   60
## 23    14   80
## 24    15   20
## 25    15   26
## 26    15   54
## 27    16   32
## 28    16   40
## 29    17   32
## 30    17   40
## 31    17   50
## 32    18   42
## 33    18   56
## 34    18   76
## 35    18   84
## 36    19   36
## 37    19   46
## 38    19   68
## 39    20   32
## 40    20   48
## 41    20   52
## 42    20   56
## 43    20   64
## 44    22   66
## 45    23   54
## 46    24   70
## 47    24   92
## 48    24   93
## 49    24  120
## 50    25   85

1. 趨勢

   • Line Chart
   • Bar Plot

2. 比較、組成

   • Bar Plot
   • Pie Chart

3. 分佈

   • Scatter Plot
   • Histgram
   • Box Plot

plot(sin(seq(0,2*pi,1/50)),type='l')

實質薪資倒退十五年？

• 畫出民國69年到102年實質薪資趨勢
• 實質薪資=每人每月平均薪資/消費者物價指數x100
• 每人每月平均薪資：薪資及生產力統計資料查詢系統

• 消費者物價指數：主計總處統計專區

• data(salary,package='DSC2014Tutorial')

  • salary_cpi
  • salary_2013
  • salary_detail

• Data: salary_cpi

平均月薪

plot(salary_cpi[,1:2],type='l')

實質薪資

salary_cpi$real_wage=salary_cpi$salary/salary_cpi$cpi*100
plot(real_wage~year,salary_cpi,type='l')

x=sample(1:150,50) #從1~150中隨機挑選50個數字
plot(iris[x,5])

Data: VADeaths

油電業薪資近9萬，是教服業的4倍?

• 畫出薪資最低與最高的三個行業
• Data: salary_2013

library(xts)
a=order(salary_2013$每人每月薪資)
salary_news=matrix(salary_2013$每人每月薪資[c(head(a,3),tail(a,3))],ncol = 6)
colnames(salary_news)=salary_2013$行業[c(head(a,3),tail(a,3))]
par(family='STKaiti') #Only for Mac!!!
mp=barplot(salary_news,col='dodgerblue4') #x軸座標
text(mp,10000,salary_news,col='gold') #標註薪資

最高薪資與最低薪資

mp=barplot(salary_news,xaxt='n',col='dodgerblue4')
text(mp,-10000,colnames(salary_news),xpd=TRUE,srt=20,cex=1.5)

• 若把行業別劃分更細，可以發現更高的薪水...
• 以'salary_detail'再畫一次

plot(iris[,3:4])
plot(Petal.Width~Petal.Length,data=iris)

plot(iris[,1:3])
plot(~Sepal.Length+Sepal.Width+Petal.Length,data=iris)

plot(factor,number) #Don't Run!
plot(iris[,5],iris[,1])

hist(iris[, 1], breaks = 4)

1. 加上點、線、面、座標軸、文字說明
2. 需要先有圖，才能畫出，無法獨立執行

凸顯實質薪資成長率的沉淪

real_wage=matrix(salary_cpi$real_wage,ncol=34)
colnames(real_wage)=salary_cpi[,1]
mp=barplot(real_wage,ylim=c(-20000,60000),col='dodgerblue4',ylab='TWD',xlab='year')

ratio=diff(salary_cpi$real_wage)/salary_cpi$real_wage[1:33] #實質薪資成長率
lines(mp[2:34],ratio*500000,typ='o',pch=20,lwd=3,col=2) 
#畫上實質薪資成長率，為配合原圖的scale，乘上500000

axis(4,seq(-20000,60000,10000),labels=paste(seq(-4,12,2),'%',sep = ""),col=2)
# 加上右邊Y軸，須考慮比例

legend("bottomleft",c('實質薪資','實質薪資成長率'),bty='n',
   text.col=c('dodgerblue4','red'),
   col=c('dodgerblue4','red'),pch=c(15,20))# 加上圖例說明

mtext(side=3,'成長率',adj=1) # 在plot的周邊加上說明

locator(n=1)

• R Blogger http://www.r-bloggers.com/batman-equationhappy-halloween-plot-the-batman-logo-in/

f1 <- function(x) {
    y1 <- 3 * sqrt(1 - (x/7)^2)
    y2 <- -3 * sqrt(1 - (x/7)^2)
    y <- c(y1, y2)
    d <- data.frame(x = x, y = y)
    d <- d[d$y > -3 * sqrt(33)/7, ]
    return(d)
}
x1 <- c(seq(3, 7, 0.001), seq(-7, -3, 0.001))
d1 <- f1(x1)
x2 <- seq(-4, 4, 0.001)
y2 <- abs(x2/2) - (3 * sqrt(33) - 7) * x2^2/112 - 3 + sqrt(1 - (abs(abs(x2) - 
    2) - 1)^2)
x3 <- c(seq(0.75, 1, 0.001), seq(-1, -0.75, 0.001))
y3 <- 9 - 8 * abs(x3)
x4 <- c(seq(-0.5, -0.75, -0.001), seq(0.75, 0.5, -0.001))
y4 <- 3 * abs(x4) + 0.75
x5 <- seq(-0.5, 0.5, 0.001)
y5 <- rep(2.25, length(x5))

x6 <- c(seq(-3, -1, 0.001), seq(1, 3, 0.001))
y6 <- 6 * sqrt(10)/7 + (1.5 - 0.5 * abs(x6)) * sqrt(abs(abs(x6) - 1)/(abs(x6) - 
    1)) - 6 * sqrt(10) * sqrt(4 - (abs(x6) - 1)^2)/14
dd = data.frame(x = c(x2, x3, x4, x5, x6), y = c(y2, y3, y4, y5, y6))
d1 = rbind(d1, dd)
plot(d1, asp = 1)  # asp: x軸與y軸的比例
text(0, 0, expression(((over(x, 7))^2 * sqrt(over(abs(abs(x) - 3), abs(x) - 
    3)) + (over(y, 3))^2 * sqrt(over(abs(y^3 - over(sqrt(33), 7)), y^3 - over(sqrt(33), 
    7))) - 1) %.% (abs(over(x, 2)) - over(3 * sqrt(33) - 7, 122) * x^2 - 3 + 
    sqrt(1 - (abs(abs(x) - 2) - 1)^2) - y) %.% (9 * sqrt(over(abs((abs(x) - 
    1) * (abs(x) - over(3, 4))), (1 - abs(x)) * (abs(x) - over(3, 4)))) - 8 * 
    abs(x) - y)))  ## 方程式的上半段
text(0, -0.8, expression((3 * abs(x) + over(3, 4) * sqrt(over(abs((abs(x) - 
    over(3, 4)) * (abs(x) - over(1, 2))), (over(3, 4) - abs(x)) * (abs(x) - 
    over(1, 2)))) - y) %.% (over(9, 4) * sqrt(over((x - over(1, 2)) * (x + over(1, 
    2)), (over(1, 2) - x) * (over(1, 2) + x))) - y) %.% (over(6 * sqrt(10), 
    7) + over(3 - abs(x), 2) * sqrt(over(abs(abs(x) - 1), abs(x) - 1)) - over(6 * 
    sqrt(10), 14) * sqrt(4 - (abs(x) - 1)^2) - y) == 0))  ##方程式的下半段

• Permanent Changes

par(...)

• Temporary Changes (with Simple Plots)
• Graphical Elements
• Figure Margins
• Multiple Figure Environment

http://spark.rstudio.com/kmchen/graphics/

Colors

colors() #內建的顏色
rainbow(144) #產生彩虹色
palette(rainbow(144)) #將彩虹色設定成預設顏色
colorRampPalette(c('red','green'))(10) #紅綠漸層 

想要讓葉子顏色漸層

data("df_brower", package = "DSC2014Tutorial")
a = order(df[, 2])

plot(x = df[a, 2], y = df[a, 1], cex = 0.1, asp = 1,
col=colorRampPalette(c("darkgreen", "lightgreen"))(10000))

plot(iris[, 3:4], bty = "n", axes = FALSE)
## 利用rect將背景顏色換掉 par('usr')：繪圖範圍的座標
rect(par("usr")[1], par("usr")[3], par("usr")[2], par("usr")[4], border = "grey89", 
    col = "grey89")
grid(col = "white", lty = 1)  ## 加上grid
axis(1, col = "lightgrey")  ## 加上X軸
axis(2, col = "lightgrey")  ## 加上Y軸
points(iris[, 3:4], pch = 20)  ## 最後畫上data

par(mar = c(3, 1, 1, 1))#the number of lines of margin
par(mai = c(3, 1, 1, 1))#margin size specified in inches

par(mfrow=c(3,2))

nf=layout(matrix(c(2,1,0,3), 2, 2), widths=c(3,1), heights=c(1,3))
layout.show(nf)

layout(matrix(c(2, 1, 0, 3), 2, 2), widths = c(3, 1), heights = c(1, 3))
xhist = hist(iris[, 3], plot = FALSE)  # get distribution
yhist = hist(iris[, 4], plot = FALSE)  # get distribution
par(mar = c(5, 5, 1, 1))  #調整邊界
plot(iris[, 3:4])
par(mar = c(0, 3, 1, 1))  #調整邊界
barplot(xhist$counts, axes = FALSE, space = 0)
par(mar = c(3, 1, 1, 0))  #調整邊界
barplot(yhist$counts, axes = FALSE, space = 0, horiz = TRUE)

極端的工時與薪資

• 找到工時和薪資太誇張的工作
• 將工時和薪資在同一畫面上呈現
• Data: salary_detail

time_salary=cbind(hours=salary_detail$平均.工時,TWD=salary_detail$每人每月薪資)
rownames(time_salary)=salary_detail$行業

plot(TWD~hours,time_salary)

ind=identify(time_salary,plot=FALSE)

• identify可以偵測圖上選擇的點之index
• 執行上述指令後，在圖上以滑鼠點擊選擇欲觀察的點
• 選完後，在Console按ESC鍵

points(time_salary[ind,],pch=20,col='red')
text(time_salary[ind,],rownames(time_salary)[ind],col='dodgerblue',font=2)

利用layout，將Scatter plot與Bar plot結合

layout(matrix(c(1,1,2,3), 2, 2), widths=c(3,6), heights=c(2,2))
plot(TWD~hours,time_salary,xlim=c(100,260),ylim=c(2e4,1.2e5))
points(time_salary[ind,],pch=20,col='red')
text(time_salary[ind,],rownames(time_salary)[ind],pos=1:4,col='dodgerblue',font=2)
mp1=barplot(time_salary[ind,1],ylab='hours')
text(mp1,50,time_salary[ind,1])
barplot(time_salary[ind,2],ylab='TWD')
text(mp1,10000,time_salary[ind,2])

png(file='test.png')
plot(iris[,3:4])
dev.off()

• png
• pdf
• jpeg
• bmp
• tiff

install.packages("wordcloud")
library("wordcloud")
wordcloud(words=c(letters,LETTERS,0:9),freq=seq(1,1000,len=62))

Browser market

Answer

plot_color=c("gray22", "deepskyblue4", "firebrick2", "springgreen4", "orange",'gray50')
palette(plot_color) 
layout(matrix(c(3,1,2,1), 2, 2), widths=c(2,2), heights=c(2,2))
par(mar=c(4,4,0,2),cex=1.2)
plot(browser_table[,1:2],lwd=2,ylim=c(0,60),pch=20,type='o')
for (i in 3:7){
  lines(browser_table[,c(1,i)],type='o',col=i-1,lwd=2,pch=20)
}
par(mar=c(0,0,0,0.1),cex=1.2)
pie(as.numeric(tail(browser_table,1)[2:7]),col=1:6,labels="")
legend('topleft',legend=colnames(browser_table)[2:7],
  text.col=1:6,col=1:6,pch=20,bty='n')
par(mar=c(0,0,0,0),cex=1)
wordcloud(colnames(browser_table)[2:7],tail(browser_table,1)[,2:7]*10000,scale=c(6,1),
 ordered.colors = TRUE,colors =1:6) #字不見時，可調整scale