Visualization

OSSF X Taiwan R user Group
陳奎銘（Benjamin）
benjamin0901@gmail.com
2013.11.16

What? Report?

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Ha! I have R!

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Basic

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Data

iris

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Plot

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Hist

hist(iris[, 1], cex.axis = 1.5, cex.lab = 1.5, col.lab = "red", main = "hist(iris[,1])", 
    cex.main = 2)

Boxplot

boxplot(Sepal.Length ~ Species, data = iris, main = "boxplot(Sepal.Length~Species,data=iris)", 
    cex.main = 2)

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Barplot

iris.tab = table(iris.sam)
iris.tab

## iris.sam
##     setosa versicolor  virginica 
##         14         17         19

barplot(iris.tab)

Barplot

##    教育學門 藝術學門
## 男    13727     8213
## 女    25955    20027

Barplot

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Pie

##    Asia  Europe Oceania America  Africa 
##   51855    4624     600    6577     902

Image+Contour

Persp

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Add something

Lines

Points

text(x,y,string)

Legend

abline

segments

Arrows

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Adjust

Permanent Changes
- par
Temporary Changes
- plot, boxplot, pie, barplot
Graphical Elements
Figure Margins
Multiple Figure Environment

Graphical Elements

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

Figure Margins

par(mfrow = c(2, 2))
par(mar = c(3, 1, 1, 1))  #mar controls lines of margin
plot(rnorm(100))
par(mar = c(1, 3, 1, 1))
plot(rnorm(100))
par(mai = c(1, 1, 2, 1))  #mai controls margin size in inches
plot(rnorm(100))
par(mai = c(1, 1, 1, 2))
plot(rnorm(100))

Figure Margins

par(mfrow = c(2, 2), omi = c(2, 2, 2, 2))  #omi controls figure margin
par(mar = c(5, 0, 0, 0))  #mar controls lines of margin
plot(rnorm(100))
par(mar = c(0, 8, 0, 0))
plot(rnorm(100))
par(mai = c(0, 0, 1, 0))  #mai controls margin size in inches
plot(rnorm(100))
par(mai = c(0, 0, 0, 1))
plot(rnorm(100))

Figure Margins

Multiple Figure Environment

本圖取自於網路，本簡報無此受權。from: http://booklive.jp/resources/cms/feature/custom/100432/nrscene_02.png

Multiple Figure Environment

nf <- layout(matrix(c(1, 6, 2, 6, 3, 6, 4, 6, 5, 6), 5, 2, byrow = TRUE), c(5, 
    5), c(1, 1, 1, 1, 1), TRUE)
par(cex = 3, oma = c(0, 0, 0, 0))
layout.show(nf)

Multiple Figure Environment

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Example 1

load("/home/ben/qftrader/plot_demo_3.RData")
kmeans_model = kmeans(TWII_20days_close_normal, 5)
x = as.numeric(table(kmeans_model$cluster))
x = round(x/sum(x) * 100)
y = paste(as.character(x), "%", sep = "")
color = c("gray22", "deepskyblue4", "firebrick2", "springgreen4", "orange")
nf <- layout(matrix(c(1, 6, 2, 6, 3, 6, 4, 6, 5, 6), 5, 2, byrow = TRUE), c(5, 
    5), c(1, 1, 1, 1, 1), TRUE)
for (i in seq(5, 1, -1)) {
    par(mar = c(1, 2, 1, 1))
    plot(kmeans_model$centers[i, ], type = "l", col = color[i], cex.axis = 1.25, 
        lwd = 2)
}
par(mar = c(1, 3, 2, 1))
barplot(x, col = color, space = 0, horiz = TRUE, legend.text = y, args.legend = list(x = 35, 
    y = 5, bty = "n", cex = 2))

Example 1

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Example 2

par(mfrow = c(2, 1))
x = rnorm(100)
y = rnorm(100)
all = hist(c(x, y), plot = F)
z = all$breaks
x = hist(x, breaks = z, plot = F)$counts
y = hist(y, breaks = z, plot = F)$counts

par(mar = c(0, 2, 2, 1))
barplot(x, space = c(0, 0))

par(mar = c(2, 2, 0, 1))
barplot(-y, axes = F, space = c(0, 0))
axis(2, seq(-20, 0, 5), labels = c(as.character(seq(20, 5, -5)), ""))
axis(1, 0:(length(z) - 1), labels = as.character(z))

Example 2

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ggplot2

1. data.frame

nice default
Layer
Stack Over
install.packages(“ggplot2”)
library(ggplot2)

Point

qplot(year,total,data=CS_student,geom='point')
ggplot(CS_student,aes(x=year,y=total))+geom_point()

Line

qplot(year,total,data=CS_student,geom=c('point','line'))
ggplot(CS_student,aes(x=year,y=total))+geom_point()+geom_line()

Barplot

qplot(factor(year),total,data=CS_student,geom=c('bar'),stat="identity")
ggplot(CS_student,aes(x=factor(year),y=total))+geom_bar(stat='identity')

Barplot

qplot(factor(year),total,data=CS_student,geom=c('bar'),stat="identity",fill=factor(year))
ggplot(CS_student,aes(x=factor(year),y=total))+geom_bar(stat='identity',aes(fill=factor(year)))

Hist

qplot(Sepal.Length,data=iris,binwidth=0.2)
ggplot(iris,aes(x=Sepal.Length))+geom_histogram(binwidth=0.2)

Boxplot

qplot(Species,Sepal.Length,data=iris,geom='boxplot',cex.lab=2)
ggplot(iris,aes(x=Species,y=Sepal.Length))+geom_boxplot()

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Pie

ggplot(foriegn, aes(x = "", y = foriegn, fill = area)) + geom_bar(width = 1, 
    stat = "identity") + scale_fill_manual(values = c("green", "blue", "cyan", 
    "red", "orange")) + coord_polar("y", start = pi/3) + labs(title = "Foriegn Students")

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Tile+Contour

library(reshape2)
volcano3d <- melt(volcano)
names(volcano3d) <- c("x", "y", "z")
ggplot(volcano3d, aes(x, y, z = z)) + geom_tile(aes(fill = z)) + stat_contour() + 
    scale_fill_gradient2(low = "red", mid = "yellow", high = "white", midpoint = 144.5)

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Save

1. jpeg(filename=‘xxx.jpeg’,width=1252,height=623)
png, bmp, tiff, pdf 2. plot something 3. dev.off()

googleVis

1. R & Google Charts API 2. Visualize data with Google Chart Tools without manually upload data to Google. 3. Output is html code. 4. Need browser and internet connection. 5. Tutorial 6. See also: Using the Google Visualisation API with R, The R Journal, 3(2):40-44, December 2011 and googleVis package manual.

Pie

Pie <- gvisPieChart(foriegn,options=list(width=1000, height=500))
plot(Pie)

GeoChart

Geo=gvisGeoChart(foriegn_student[-1:-2,], locationvar="area", colorvar="number",options=list(width=1000, height=500))
plot(Geo) #大專校院境外學生人數統計

Motion

Motion=gvisMotionChart(area_total, idvar="area", timevar="year")
plot(Motion)

shiny

1. beta version: 2012/11 2. 只要幾行程式碼 3. 幾乎只要會R就行 4. 動態展示 5. Tutorial Install & Run — install.packages(“shiny”) library(shiny) runExample(“01_hello”) Hello shiny! — “r sdir <- paste(system.file("examples", package = "shiny"), "01_hello", sep = "/") sdir ``` ``` ## [1] "/home/ben/R/library/shiny/examples/01_hello" ``` ```r dir(sdir) ``` ``` ## [1] "server.R" "ui.R" ``` runApp("/home/ben/R/library/shiny/examples/01_hello") ui --- ```r library(shiny) # Define UI for application that plots random distributions shinyUI(pageWithSidebar( # Application title headerPanel("Hello Shiny!"), # Sidebar with a slider input for number of observations sidebarPanel( sliderInput("obs", "Number of observations:", min = 0, max = 1000, value = 500) ), # Show a plot of the generated distribution mainPanel( plotOutput("distPlot") ) )) ``` server --- ```r library(shiny) # Define server logic required to generate and plot a random distribution shinyServer(function(input, output) { # Expression that generates a plot of the distribution. The expression is # wrapped in a call to renderPlot to indicate that: # # 1) It is 'reactive' and therefore should be automatically re-executed # when inputs change 2) Its output type is a plot output$distPlot <- renderPlot({ # generate an rnorm distribution and plot it dist <- rnorm(input$obs) hist(dist) }) }) ``` Procedure --- 1. ui.R 中的sidebarPanel提供input 2. input傳至server.R 3. 在server.R的rederPlot處理 4. 傳出output到mainPanel shiny+googlVis ---

shiny+googlVis

遇到問題時…

本圖取自於網路，本簡報無此受權

請愛用!

- help - demo - example - tutorial - google

Visualization

What? Report?

Ha! I have R!

Basic

Data

iris

Plot

Plot

Plot

Plot

Plot

Hist

Boxplot

Barplot

Barplot

Barplot

Barplot

Barplot

Barplot

Pie

Image+Contour

Persp

Add something

Lines

Points

text(x,y,string)

Legend

abline

segments

Arrows

Adjust

Graphical Elements

Figure Margins

Figure Margins

Figure Margins

Figure Margins

Multiple Figure Environment

Multiple Figure Environment

Multiple Figure Environment

Example 1

Example 1

Example 2

Example 2

ggplot2

ggplot2

Point

Line

Barplot

Barplot

Hist

Boxplot

Pie

Pie

Tile+Contour

Tile+Contour

Save

googleVis

googleVis

Pie

GeoChart

Motion

shiny

shiny

遇到問題時…

請愛用!

Taiwan R User Group

Thank you!