R: Intro to ggplot()

ggplot() is a powerful graphing tool in R. While it is more complex to use than qplot(), its added complexity comes with advantages.

Don’t worry about the complexity, we are going to step into it slowly.

Let’s start by getting a data set. I am going to choose airquality from the R data sets package. You can find a list of data sets from that package here: Link

We are going to manipulate some of…

chapter3

Table of Contents

1 Chapter 3

1.1 Figure 3.4 - simple bar chart

1.2 Figure 3.5 - simple bar chart

1.3 Figure 3.7

1 Chapter 3

Graphics out of the book Graphics for Statistics and Data Analysis with R by Kevin Keen (book home page)

here are the data

item<-c("Canada", "Mexico", "Saudi Arabia", "Venezuela", "Nigeria") amount<-c(2460,1538,1394,1273,1120) amount<-amount/1000 df <- data.frame(item=factor(1:5,labels=item),amount=amount) barrel <- read.jpeg("barrel.jpg")

1.1 Figure 3.4 - simple bar chart

we use geom_bar to create the bar chart

customizing the y-axis by using scale_y_continuous: limits set the limits, expand defines the multiplicative and additive expansion constants

coord_flip rotates it (so we get a horizontal bar chart)

than we set the background to white

set the colour of the axis lines to black (we have to do this to axis.line not just axis.line.x because of inheritance)

get rid of the vertical axis

set colour of the ticks of the x-axis to black

get rid of the ticks of the y-axis

set the colour of the axis labels to black

change the adjustment of the labels of vertical axis

get rid of the grid lines (they are still visible if one looks carefully)

ggplot(df,aes(y=amount,x=reorder(item,-as.numeric(item)))) + geom_bar(stat="identity",fill="white",colour="black") + scale_y_continuous("Millions of Barrels per Day",limits=c(0,2.5),expand=c(0,0)) + xlab("") + coord_flip() + theme(panel.background=element_rect(fill="white"), axis.line=element_line(colour="black"), axis.line.y=element_blank(), axis.ticks.x=element_line(colour="black"), axis.ticks.y=element_blank(), axis.text=element_text(colour="black",size=11), axis.text.y=element_text(hjust=0), panel.grid=element_blank()) ggsave("fig3_4.png")

Saving 7 x 6.99 in image

1.2 Figure 3.5 - simple bar chart

we use geom_point to create the chart with dots (set the size of the dots to 3)

via geom_segment we add the dotted lines (linetype=3)

customizing the x-axis by using scale_x_continuous: limits set the limits, expand defines the multiplicative and additive expansion constants

set the colour of the axis lines to black (we have to do this to axis.line not just axis.line.x because of inheritance)

get rid of the vertical axis

set colour of the ticks of the x-axis to black

get rid of the ticks of the y-axis

set the colour of the axis labels to black

than we set the background to transparent and the colour of the frame to black (panel.background=element_rect)

get rid of the grid lines (they are still visible if one looks carefully)

get rid of of the title of the y-axis

set the colour and the size of the title of the x-axis to black and 11 respectively

ggplot(df,aes(x=amount,y=item)) + geom_point(size=3) + geom_segment(aes(yend=as.numeric(item)),xend=0,linetype=3) + scale_x_continuous("Millions of Barrels per Day",limits=c(0,2.5),expand=c(0,0)) + theme(axis.line=element_line(colour="black"), axis.line.y=element_blank(), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), axis.text=element_text(colour="black",size=11), panel.background=element_rect(fill="transparent",colour="black"), panel.grid=element_blank(), axis.title.y=element_blank(), axis.title.x=element_text(colour="black",size=11) ) ggsave("fig3_5.png")

Saving 7 x 6.99 in image

1.3 Figure 3.7

the clipart can be downloaded here

we need the ReadImages package for reading this jpeg

we need the grid graphics package to divide the plot and insert to several parts

first we load two additional packages (ReadImages for reading the jpeg and grid for the grid graphics functions)

the next part (definition of the dot chart) is exactly the same as in figure 3.5

load the jpeg with the barrel (barrel <- read.jpeg("barrel.jpg"))

the next commands are part of the grid package, which is the underlying graphics system of ggplot2

grid.newpage moves to a new page

pushViewport adds a new viewport (plotting region) to the page (via x and y one can set the position), beginning in the top left corner, setting the width to 0.6 relative to the page and the height to 0.95; just sets the adjustment

print(p,newpage=F) prints the dot chart in this viewport

popViewport() closes the viewport

create another viewport next to the other one with width 0.4 and the same height

grid.raster inserts the picture of the barrel

grid.text inserts the text

library(grid) library(ReadImages) p <- ggplot(df,aes(x=amount,y=reorder(item,amount))) + geom_point(size=3) + geom_segment(aes(yend=reorder(item,amount)),xend=0,linetype=3) + scale_x_continuous("Millions of Barrels per Day",limits=c(0,2.5),expand=c(0,0)) + theme(axis.line=element_line(colour="black"), axis.line.y=element_blank(), axis.ticks.y=element_blank(), axis.text=element_text(colour="black",size=12), panel.background=element_rect(fill="white",colour="black"), panel.grid=element_blank(), axis.title.y=element_blank(), axis.title.x=element_text(colour="black",size=11) ) barrel <- read.jpeg("barrel.jpg") grid.newpage() pushViewport(viewport(x=unit(0,"line"),y=unit(1,"npc")-unit(2,"mm"),width=0.6,height=0.95,name="vp1",just=c("left","top"))) print(p,newpage=F) popViewport() pushViewport(viewport(x=unit(0.7,"npc"),y=unit(0,"npc"),width=0.4,height=0.95,name="vp1",just=c("left","bottom"))) grid.raster(barrel,width=unit(1,"npc"),just=c("centre","bottom"),x=unit(0.2,"npc"),y=unit(3,"line")) grid.text("Top Five Importing\nCountries of Crude Oil\nand Petrolium\nProducts in 2007\nfor the united States",x=unit(0.2,"npc"),y=unit(1,"npc")-unit(2,"line"),just=c("center","top")) savePlot("fig3_7.png")

Date: 2012-09-12 21:56:59 CEST

Author: mandy

Org version 7.8.02 with Emacs version 23

Graphics for Statistics - Chapter 2 - Pie Charts: Figures 2.11-2.12

Graphics out of the book Graphics for Statistics and Data Analysis with R by Kevin Keen (book home page)

Pie charts of the United Nations budget for 2008-2009

in the first two lines we define a vector of grays - using the definition out of the book

using geom_bar() with width 1

mapping x to "", y to amount1 and fill to item1

to put the labels on the plot we use geom_text mapping y to the mid of each block

and we use scale_fill_manual to set the colours to our predefined grays

Maybe now it is time to look what we have done so far:

grays1<-gray(((2*length(df$amount1)-1):0)/(2*length(df$amount1)-1)) grays<-grays1[1:length(amount)] ggplot(df,aes(x="",y=amount1,fill=item1)) + geom_bar(width=1,colour="black") + geom_text(aes(y=c(0,cumsum(df$amount1)[-nrow(df)]) + df$amount/2,label=df$item1),x=1.5,size=4) + scale_fill_manual(values=grays) ggsave("fig2_11a.png")

Saving 7 x 6.99 in image

now we transform our coordinate system via coord_polar using the y-axis to define the angle within the pie chart

we get rid of the legend, background, axis ticks, text etc

grays1<-gray(((2*length(df$amount1)-1):0)/(2*length(df$amount1)-1)) grays<-grays1[1:length(amount)] ggplot(df,aes(x="",y=amount1,fill=item1)) + geom_bar(width=1,colour="black") + geom_text(aes(y=c(0,cumsum(df$amount1)[-nrow(df)]) + df$amount/2,label=df$item1),x=1.5,size=4) + scale_fill_manual(values=grays) + coord_polar(theta="y") + theme(panel.background=element_rect(fill="white"), axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank(), axis.title.x=element_blank(), axis.title.y=element_blank(), legend.position="none" ) ggsave("fig2_11.png")

Saving 7 x 6.99 in image

this is one of the cases one should consider using classical graphics

here is the code used by K. Keen:

pie(df$amount1,labels=df$item1, radius = 0.85, clockwise=TRUE, col=grays, angle=120) savePlot("fig2_11b.png")

Graphics for Statistics - Chapter 2 - Bar Charts: Figures 2.3-2.10 + 2.13

Graphics out of the book Graphics for Statistics and Data Analysis with R by Kevin Keen (book home page)

Bar charts of the United Nations budget for 2008-2009

using geom_bar()

mapping x to item1 and y to amount1

set stat="identity" because of presummarised data

and there is the basic plot

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(stat="identity") ggsave("fig2_3.png")

Saving 7 x 6.99 in image

But of course there is a lot to do left: you can not read the labels of the x-axis and the we have to change the axis titles

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(stat="identity") + xlab("") + ylab("Millions of US Dollars") + opts(axis.text.x=theme_text(angle=90,size=12)) ggsave("fig2_3b.png")

Saving 7 x 6.99 in image

and there is the graph in default ggplot style

now we the plot the style of the plot in the book:

add the expand argument to the definition of the y-axis to let the drawn axis end exactly at the limits

the width of the bins is changed through the width argument in geom_bar(); in this case it is a bit tricky, because using the identity stat resets width so we have to put width in to the aes() argument (further information)

we add a hjust argument in the axis.text.x to change the alignment

we set fill and colour of the background to white

we use a simple extension by Rudolf Cardinal (source line), because we want to remove just one axis not the two of them (further information)

and at the end like above, we use again the hack to get rid of the ticks of the x-axis

source("http://egret.psychol.cam.ac.uk/statistics/R/extensions/rnc_ggplot2_border_themes.r") png("fig2_3c.png",height=500, width=500) ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + opts(axis.text.x=theme_text(angle=90,size=12,hjust=1), axis.text.y=theme_text(size=12), panel.background=theme_rect(fill="white",colour="white"), panel.border=theme_left_border() ) g <- grid.gget(gPath("axis-b", "", "", "", "axis.ticks.segments")) grid.remove(g$name) dev.off()

X11cairo 2

ggplot9.2 is out - and everything much easier:

you do not need to manipulate the grid elements directly, axis.ticks.x and axis.ticks.y are now available

there is also no need to use additional functions anymore: axis.line, axis.line.x and axis.line.y do a good job

maybe it this a bit confusing: first you have to set axis.line and then you you the axis blank you do not want to see, this is necessary because of the inheritance

there are also some functions renamed: use theme instead of opts and element instead of theme

## 9.2 version ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + theme(axis.text.x=element_text(angle=90,size=12,hjust=1,colour="black"), axis.text.y=element_text(size=12,colour="black"), axis.line=element_line(colour="black"), axis.line.x=element_blank(), axis.ticks.x=element_blank(), panel.background=element_rect(fill="white",colour="white") ) ggsave("fig2_3n.png")

Saving 7 x 6.99 in image

in figure 2.4 just the angle of the labels is changed, but therefore we have to adjust the alignment (add vjust argument)

also set the size of the labels to 11

savePlot() is a alternative to open and close a device explicitly

source("http://egret.psychol.cam.ac.uk/statistics/R/extensions/rnc_ggplot2_border_themes.r") ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800)) + xlab("") + opts(axis.text.x=theme_text(angle=45,size=12,hjust=1,vjust=1), axis.text.y=theme_text(size=12), panel.background=theme_rect(fill="white",colour="white"), panel.border=theme_left_border() ) g <- grid.gget(gPath("axis-b", "", "", "", "axis.ticks.segments")) grid.remove(g$name) savePlot("fig2_4.png")

and here is also the code for ggplot v9.2

## 9.2 version ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",expand=c(0,0),limits=c(0,800)) + xlab("") + theme(axis.text.x=element_text(angle=45,size=11,hjust=1,vjust=1,colour="black"), axis.text.y=element_text(size=12,colour="black"), axis.line=element_line(colour="black"), axis.line.x=element_blank(), axis.ticks.x=element_blank(), panel.background=element_rect(fill="white",colour="white") ) ggsave("fig2_4n.png")

in figure 2.5 the axes are exchanged - so we can use the final code from figure 2.3

and do some minor changes (alignment, angle of labels)

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + opts(axis.text.x=theme_text(size=11,vjust=-1), axis.text.y=theme_text(hjust=1,size=12), panel.background=theme_rect(fill="white",colour="white"), panel.border=theme_bottom_border() ) g <- grid.gget(gPath("axis-l", "", "", "", "axis.ticks.segments")) grid.remove(g$name) savePlot("fig2_5.png")

and here is the 9.2 version

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + theme(axis.text.x=element_text(size=11,vjust=-1,colour="black"), axis.text.y=element_text(hjust=1,size=12,colour="black"), axis.line=element_line(colour="black"), axis.line.y=element_blank(), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), panel.background=element_rect(fill="white",colour="white") ) ggsave("fig2_5n.png")

for figure 2.6 we just remove the colour argument from panel.background, the panel.border option and add panel.grid.major=theme_blank() to get rid of the tracks of the grid lines

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + opts(axis.text.x=theme_text(size=11,vjust=-1), axis.text.y=theme_text(hjust=1,size=12), panel.background=theme_rect(fill="white"), panel.grid.major=theme_blank() ) g <- grid.gget(gPath("axis-l", "", "", "", "axis.ticks.segments")) grid.remove(g$name) savePlot("fig2_6.png")

and again the 9.2 version

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + theme(axis.text.x=element_text(size=11,vjust=-1,colour="black"), axis.text.y=element_text(hjust=1,size=12,colour="black"), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), panel.background=element_rect(fill="white",colour="black"), panel.grid.major=element_blank() ) ggsave("fig2_6n.png")

Saving 7 x 6.99 in image

from now all code is for ggplot2 version 9.2

figure 2.8 keep the vertical grid lines, but removes the horizontal ones: this is controlled by panel.grid.major.x and panel.grid.major.y (line elements)

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + theme(axis.text.x=element_text(size=11,vjust=-1,colour="black"), axis.text.y=element_text(hjust=1,size=12,colour="black"), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), panel.background=element_rect(fill="white",colour="black"), panel.grid.major.y=element_blank(), panel.grid.major.x=element_line(colour="black") ) ggsave("fig2_8.png")

Saving 7 x 6.99 in image

for figure 2.9 we change the colour of the borders of the bars to black (colour) and the colour of the filling to grey (fill)

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity",fill="grey",colour="black") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + theme(axis.text.x=element_text(size=12,colour="black"), axis.text.y=element_text(size=12,colour="black"), axis.ticks.x=element_line(colour="black"), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), axis.line=element_line(colour="black"), axis.line.y=element_blank(), panel.background=element_rect(fill="white") ) ggsave("fig2_9.png")

Saving 7 x 6.99 in image

for figure 2.10 just the filling of the bars have to be changed to white

ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity",fill="white",colour="black") + scale_y_continuous("Millions of US Dollars",limits=c(0,800),expand=c(0,0)) + xlab("") + coord_flip() + theme(axis.text.x=element_text(size=12,colour="black"), axis.text.y=element_text(size=12,colour="black"), axis.ticks.x=element_line(colour="black"), axis.ticks.y=element_blank(), axis.ticks.x=element_line(colour="black"), axis.line=element_line(colour="black"), axis.line.y=element_blank(), panel.background=element_rect(fill="white") ) ggsave("fig2_10.png")

Saving 7 x 6.99 in image

for figure 2.13 figure 2.4 is a good beginning

set the colour of the filling of the bars to grey

we set the breaks and labels of the y-axis manually

add horizontal white lines via geom_hline

## 2.13 dollars <- paste("US$",c(200,400,600),"k",sep="") ggplot(df,aes(x=item1,y=amount1)) + geom_bar(aes(width=0.7),stat="identity",fill="grey") + scale_y_continuous(expand=c(0,0),breaks=c(0,200,400,600),labels=c("0",dollars)) + geom_hline(yintercept=c(200,400,600),colour="white") + theme(axis.text=element_text(size=11.5,colour="black"), axis.text.x=element_text(angle=45,hjust=1,vjust=1), axis.ticks=element_blank(), axis.title=element_blank(), axis.line=element_line(colour="grey"), axis.line.y=element_blank(), panel.background=element_rect(fill="white",colour="white") ) ggsave("fig2_13.png")

Chapter 2 - Dot Charts

Graphics out of the book Graphics for Statistics and Data Analysis with R by Kevin Keen (book home page)

Dot charts of the United Nations budget for 2008-2009

data:

item1<-factor(1:14, labels=c("Overall coordination", "Political affairs", "International law", "International cooperation", "Regional cooperation", "Human rights", "Public information", "Management", "Internal oversight", "Administrative", "Capital", "Safety & security", "Development", "Staff assessment")) amount1<-c(718555600,626069600,87269400,398449400, 477145600,259227500,184000500,540204300,35997700, 108470900,58782600,197169300,18651300,461366000) amount1<-amount1/1000000 df <- data.frame(item1=item1,amount1=amount1) df

item1 amount1 1 Overall coordination 718.5556 2 Political affairs 626.0696 3 International law 87.2694 4 International cooperation 398.4494 5 Regional cooperation 477.1456 6 Human rights 259.2275 7 Public information 184.0005 8 Management 540.2043 9 Internal oversight 35.9977 10 Administrative 108.4709 11 Capital 58.7826 12 Safety & security 197.1693 13 Development 18.6513 14 Staff assessment 461.3660

now we can build the chart using geom_point() and geom_hline()

first we build a ggplot object and map x to amount1 and y to item1

than we add the point layer (geom_point()) setting the shape to 19 (filled circle)

now we need the horizontal lines, therefore we use geom_hline() and map as.numeric(item1) (which gives 1:14) to yintercept

ggplot(df,aes(x=amount1,y=item1)) + geom_point(shape=19) + geom_hline(aes(yintercept=as.numeric(item1)),linetype=3) ggsave("fig2_1.png")

first we reverse the order of the category using reorder() by the negative of the number of the item

then we increase the size of the points a little (size argument in geom_point())

then we change the title of the x-axis and set the limits to c(0,800) (scale_x_continuous())

setting asis.title.y to theme_blank() gets us rid of the title of the y-axis

axis.title.x is managed by theme_text(): we set the text size to 12 and adjust the vertical position (vjust) downwards

last we set the panel background to white using theme_rect() (and because there are some leftovers of the grid lines visible in the frame we set the major grid lines to blank

ggplot(df,aes(x=amount1,y=reorder(item1,-as.numeric(item1)))) + geom_point(shape=19,size=4) + geom_hline(aes(yintercept=as.numeric(item1)),linetype=3) + scale_x_continuous("Millions of US Dollars",limits=c(0,800)) + opts(axis.title.y=theme_blank(), axis.text.y=theme_text(size=12), axis.title.x=theme_text(size=12,vjust=-0.7), axis.text.x=theme_text(size=12), panel.background=theme_rect(fill="white"), panel.grid.major=theme_blank()) ggsave("fig2_1b.png")

remains the ticks of the y-axis, again we must use the hack (as in chapter 1 - have a look there for further information)

png("fig2_1c.png",height=500, width=500) ggplot(df,aes(x=amount1,y=reorder(item1,-as.numeric(item1)))) + geom_point(shape=19,size=4) + geom_hline(aes(yintercept=as.numeric(item1)),linetype=3) + scale_x_continuous("Millions of US Dollars",limits=c(0,800)) + opts(axis.title.y=theme_blank(), axis.text.y=theme_text(size=12), axis.title.x=theme_text(size=12,vjust=-0.7), axis.text.x=theme_text(size=12), panel.background=theme_rect(fill="white"), panel.grid.major=theme_blank()) g <- grid.gget(gPath("axis-l", "", "", "", "axis.ticks.segments")) grid.remove(g$name) dev.off()

X11cairo 2

to change this figure to figure 2.2 we have just to replace geom_hline() by geom_segment() and change therefore some mappings

png("fig2_1d.png",height=500, width=500) ggplot(df,aes(x=amount1,y=reorder(item1,-as.numeric(item1)))) + geom_point(shape=19,size=4) + geom_segment(aes(yend=reorder(item1,-as.numeric(item1))),xend=0,linetype=3) + scale_x_continuous("Millions of US Dollars",limits=c(0,800)) + opts(axis.title.y=theme_blank(), axis.text.y=theme_text(size=12), axis.title.x=theme_text(size=12,vjust=-0.7), axis.text.x=theme_text(size=12), panel.background=theme_rect(fill="white"), panel.grid.major=theme_blank()) g <- grid.gget(gPath("axis-l", "", "", "", "axis.ticks.segments")) grid.remove(g$name) dev.off()

chapter1

Graphics out of the book Graphics for Statistics and Data Analysis with R by Kevin Keen (book home page)

dot chart of prevalence of allergy in endoscopic sinus surgery (figure 1.1)

first create the data frame (which is mandatory)

names<-factor(1:6,labels=c("Epidermals","Dust Mites","Weeds","Grasses","Molds","Trees")) prevs<-c(38.2,37.8,31.1,31.1,29.3,26.7) df <- data.frame(names=names,prevs=prevs) df

names prevs 1 Epidermals 38.2 2 Dust Mites 37.8 3 Weeds 31.1 4 Grasses 31.1 5 Molds 29.3 6 Trees 26.7

now we can create the dot chart using geomsegment() (lines) and geompoint()

we map x to prevs and y to names for all layers

in geom_segment() we map additionally yend to names and set xend to zero and linetype to 3 (dotted)

in geom_point() we set shape to 19 (small filled circle)

than we set the limits of the x axis to c(0,50) accordingly to the book chart, set the title to Percent and get rid of the title of the y axis

ggplot(df,aes(x=prevs,y=names)) + geom_segment(aes(yend=names),xend=0,linetype=3) + geom_point(shape=19) + scale_x_continuous("Percent",limits=c(0,50)) + opts(axis.title.y=theme_blank()) ggsave("fig1_1.png")

Saving 7 x 6.99 in image

bar chart of prevalence of allergy in endoscopic sinus surgery (figure 1.1)

now we map x to names and y to prevs

we use geombar(); we have to change the stat to "identity" because we use presummarised data (the default stat of the geom is "bin")

then we change the appearance of the axes as above

ggplot(df,aes(x=names,y=prevs)) + geom_bar(stat="identity") + scale_y_continuous("Percent",limits=c(0,50)) + opts(axis.title.x=theme_blank()) ggsave("fig1_2.png")

Saving 7 x 6.99 in image

this looks fine for now; but in the book graph the labels are rotated and the bins are looking a bit narrower

the width of the bins is changed through the width argument in geom_bar(); in this case it is a bit tricky, because using the identity stat resets width so we have to put width in to the aes() argument (further information)

rotating the labels is done via opts() and text_theme() (angle)

I also resize the labels (size)

and get rid of the axis ticks (axis.ticks=theme_blank())

ggplot(df,aes(x=names,y=prevs)) + geom_bar(aes(width=0.7),stat="identity") + scale_y_continuous("Percent",limits=c(0,50)) + opts(axis.title.x=theme_blank(), axis.text.x=theme_text(angle=90,size=12), axis.ticks=theme_blank()) ggsave("fig1_2b.png")

Saving 7 x 6.99 in image

unfortunately there are no ticks on the y axis as well, further more: in the current version of ggplot there is no equivalent to axis.ticks.x, so if you want to get rid of the ticks of just one axis you must use this hack (link)

another consequence is that ggsave does not work on the grid.remove edit - so we have to save the chart in the old fashioned way

png("fig1_2c.png",height=500, width=500) ggplot(df,aes(x=names,y=prevs)) + geom_bar(aes(width=0.5),stat="identity") + scale_y_continuous("Percent",limits=c(0,50)) + opts(axis.title.x=theme_blank(), axis.text.x=theme_text(angle=90,size=12)) g <- grid.gget(gPath("axis-b", "", "", "", "axis.ticks.segments")) grid.remove(g$name) dev.off()

X11cairo 2

ggplot9.2 is out - and everything much easier:

you do not need to manipulate the grid elements directly, axis.ticks.x and axis.ticks.y are now available

axis.line does a good job to customize the axes

there are also some functions renamed: use theme instead of opts and element instead of theme

Data are available here

I added the maps for overweight and obesity, download

script available here