Creating graphs

“No design works unless it embodies ideas that are held common by the people for whom the object is intended.” - Adrian Forty

The use of R offers many advantages not only in the analysis of data, R is also a useful tool for creating scientific graphs. R makes it possible

  • to produce high quality graphs that are also suitable for professional printing.
  • to create graphics completely in R syntax and thus make them reproducible. reproducible.
  • to flexibly combine different types of graphics or develop your own forms of presentation.
  • to easily create uniformly designed graphics.

Do not wait until the very final analysis stage to produce some publication quality graphics but produce fast (not necessarily nice) visualizations all the way through your data analysis. Otherwise you will not utilize the best neural network infrastructure you have available: your brain and it’s ability to identify patterns.

Basic plots in R

plot(x,y) is the universal function for generating scatter plots and line plots from the vectors x and y. plot can be optionally adjusted with various parameters:

Parameter Description Example
type sets the diagram type:
“l” -> lines
“p” -> dots
“b” -> both points and lines
“c”-> empty points joined by lines
“h” -> bars, histogram-like vertical lines
“s” -> step diagram
“n” -> no representation, does not produce any points or lines
type=”b”
main name of title main=”Population growth (annual %)”
col set colour for lines, dots, bars etc.
show available colour words: colours()		 col=”blue”
col=”#112233” (RGB value)
col=”#11223344” (RGB and transparency value)
sub subtitle, caption sub=”Figure 1”
xlab labelling of the x-axis xlab=”Years 2000 to 2020”
ylab labelling of the y-axis ylab=”Population Growth in %”
pch The graphic symbol used to represent data points. Either a character as a string or a number representing the following characters;
pch=1
lty Stroke type of lines
lty=1
lwd Line width lwd=3
cex Symbol size cex=2
xlim Sets start and end values of the X-axis scale xlim=c(0,20)
ylim Sets start and end values of the y-axis scale ylim=c(100,160)
bty Outline of the complete character area. Options are: “n”, “o”, “c”, “l”, “7” bty=”n”
xaxt Labelling of the X-axis scale OFF xaxt=”n”
yaxt Labelling of the Y-axis scale OFF yaxt=”n”
font Selection of the font format, 1=plain, 2=bold, 3=italic, 5=Greek symbols font=5
  “Pointcharacters as used in GNU R” by Marc Schwenzer on Wikimedia
“Line-Styles of GNU R” by Europol on Wikimedia		  

Let’s have some fun

The following is an introduction for producing simple graphs.

Define 2 vectors for two different datasets:

sport_cars <- c(1, 2, 4, 2, 6, 7, 10)
family_cars <- c(3, 6, 6, 8, 6, 5, 2)

Then calculate the range from 0 to max value of sport cars and family cars:

max_range <- range(0, sport_cars, family_cars)

We graph the cars using the y axis that ranges from 0 to max value in sports or family cars and turning off axes and annotations (axis labels) so we can specify them ourself.

plot(sport_cars, type="o", col="blue", ylim=max_range,
     axes=FALSE, ann=FALSE)
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Make x axis using Mon-Fri labels

axis(1, at=1:7, lab=c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))
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Make y axis with horizontal labels that display ticks at every 4 marks. 4*0:g_range[2] is equivalent to c(0,4,8,12).

axis(2, las=1, at=4*0:max_range[2])
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Create box around plot

box()
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Graph trucks with red dashed line and square points

lines(family_cars, type="o", pch=22, lty=2, col="red")
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Create a title with a red, bold/italic font

title(main="Car Types on Streets", col.main="red", font.main=4)
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Label the x and y axes with dark green text

title(xlab="Days", col.lab=rgb(0,0.5,0))
title(ylab="Total", col.lab=rgb(0,0.5,0))
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Create a legend at (1, g_range[2]) that is slightly smaller (cex) and uses the same line colors and points used by the actual plots

legend(1, max_range[2], c("Sport","Family"), cex=0.8,
       col=c("blue","red"), pch=21:22, lty=1:2);
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In total this is the code and the output in the plot-window will look like this with each line:

sport_cars <- c(1, 2, 4, 2, 6, 7, 10)
family_cars <- c(3, 6, 6, 8, 6, 5, 2)
max_range <- range(0, sport_cars, family_cars)
plot(sport_cars, type="o", col="blue", ylim=max_range,
     axes=FALSE, ann=FALSE)
axis(1, at=1:7, lab=c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))
axis(2, las=1, at=4*0:max_range[2])
box()
lines(family_cars, type="o", pch=22, lty=2, col="red")
title(main="Car Types on Streets", col.main="red", font.main=4)
title(xlab="Days", col.lab=rgb(0,0.5,0))
title(ylab="Total", col.lab=rgb(0,0.5,0))
legend(1, max_range[2], c("Sport","Family"), cex=0.8,
       col=c("blue","red"), pch=21:22, lty=1:2);
Animation of the plot process

Visualizations 101

No matter if you produce publication quality graphics or quick and dirty visualizations, remember some guiding principles and traps illustrated in the upcoming figures.

For further reading, have a look at e.g. Kelleher & Wagner 2011. To get some inspiration, the R Graph Gallery is also a good place to start (but it relies on the ggplot2 library, not on the basic R plotting functions).

Test your knowledge!

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