Intro to R Graphics Center for Social Science Computation and Research, 2010 Stephanie Lee, Dept of Sociology, University of Washington

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1 Intro to R Graphics Center for Social Science Computation and Research, 2010 Stephanie Lee, Dept of Sociology, University of Washington Class Outline - The R Environment and Graphics Engine - Basic Graphs - Modifying Basic Graphs - More Advanced Graphics - Other Resources This class is an introduction to creating graphics in R. R has a very powerful graphics engine, but this class only covers the more basic high-level traditional graphics. Even using just the high-level function calls can produce some very useful and interesting graphs. Some knowledge of R is expected. The R Environment and Graphics Engine - Traditional Graphics vs. Grid Graphics - High-level and low-level functions The R graphics engine is very powerful. Here are some examples of what can be done. The following plots were created only using traditional graphics. > demo(graphics) Some more complex and interesting graphics created using R: We won t be learning how to create the more exciting graphs in this class, but even just the traditional graphics allow you to do a lot. Basic Graphs > library(datasets) > mtcars >?mtcars Scatterplot A graph of Miles Per Gallon as a function of Weight of car > plot(mpg ~ wt, data = mtcars) Line Graph > uspop > class(uspop) A timeseries is a special type of object that will plot as a line > plot (uspop) 1

2 For a simple vector of (time-)ordered data, plot defaults to points. > plot(as.vector(uspop)) > plot(as.vector(uspop), type="l") > plot(as.vector(uspop), type="o") Histogram A graph of frequency of number of carburetors > hist (mtcars$carb) Boxplot The distribution of gross horsepower of the cars > boxplot(mtcars$hp) A more interesting comparison of boxplots: >?chickwts > chickwts > boxplot(chickwts$weight ~ chickwts$feed) Bar Chart There are six types of feed in the chickwts dataset. How many chickens are in each category? > chickwts$feed > table(chickwts$feed) A barplot of how many chickens are in each feed category: > barplot(table(chickwts$feed)) Pie Chart A pie chart showing how many chickens in each category: > pie(table(chickwts$feed)) Modifying Basic Graphs Now we know how to create the most common types of graphs. How can we modify them to look better and convey more information? Additional Functions After the graph is created by the function call, you can add to it with other functions. Some common ones are points(), lines(), text(), and legend(). These must be called after a plot function has been already called. These are considered "low-level" functions, but are still part of the traditional graphics. There might come a time when you have two sets of data and wish to see them plotted on top of each other. This is an artificial example, but shows how to do it: > plot(mtcars$mpg[1:20] ~ mtcars$wt[1:20]) > points(mtcars$mpg[21:32] ~ mtcars$mpg[21:32]) 2

3 > text(5, 30, "n=32") More likely you will create a scatterplot and then want to show the fitted regression line. abline() is a very useful function that will overlay the fitted equation. > plot(mtcars$mpg ~ mtcars$wt) > abline(lm(mtcars$mpg ~ mtcars$wt)) Changing Graph Parameters The basic graph functions we covered have many of the same modifiable parameters. They can be found in the help page for the function. Some more common things we may want to change: Adding a Main Title to the graph and labeling X and Y axes: main, xlab, ylab Car Weight", xlab="car Weight (lb/1000)", ylab="miles Per Gallon") Changing the Range on the X and Y Axes: xlim, ylim It doesn't make sense on this plot, but we might want to change the range on the x and y axis from the defaults. ylab="miles Per Gallon", xlim=c(0,10), ylim=c(0,40)) Changing the Color of Plotting Symbols: col ylab="miles Per Gallon", col="blue") There are many colors available to use. The easiest is to use them by name. To see colors with names: > colors() You can also use RGB and hexadecimal to create the exact color you want. (Don't worry if you don't know what this means.) Changing Plotting Symbols: pch Perhaps we want the plotting symbols to be triangles instead of open circles: ylab="miles Per Gallon", col="blue", pch=24) The most common plotting symbols are listed in points() >?points 3

4 Colors and symbols are a great way of conveying more information. Let's distinguish between cars that are automatic transmission and cars that are manual transmission. 0 = automatic and 1 = manual, so we'll make automatics blue and manuals red. ylab="miles Per Gallon", col=c("blue","red")[match(mtcars$am,c(0,1))]) Better yet, let's change the plotting symbol depending on how many cylinders it has. ylab="miles Per Gallon", col=c("blue","red")[match(mtcars$am, c(0,1))], pch=c(21, 24, 19)[match(mtcars$cyl, c(4, 6, 8))]) Now we need to label everything: > legend(3, 34, legend=c("automatic Transmission", "Manual Transmission"), fill=c("blue", "red")) > legend(4.25, 28, legend=c("4", "6", "8"), title="# Cylinders", pch=c(21, 24, 19)) Of course, you have to play around with the X and Y coordinates to get it to look right. But this plot shows how important and useful graphs are. A good graph can illustrate relationships between multiple variables very clearly and in a way that makes sense to people who don't understand statistics. Each type of graph has it's own parameters that you may wish to modify. Among the more common are: Histogram: Changing Break sizes: > hist (mtcars$qsec) > hist (mtcars$qsec, breaks=seq(from=12, to=24, by=0.5)) Boxplot: Multiple boxplots and changing widths to reflect sample size > boxplot(chickwts$weight ~ chickwts$feed) > table(chickwts$feed) > boxplot(chickwts$weight ~ chickwts$feed, width=table(chickwts$feed)) boxplot() has kindly put the multiple boxplots into alphabetical order for us, which is why we can use table(chickwts$feed) to get the vector of feed names. The number of chickens in each feed group is very similar, so it's hard to see the differences in widths of the boxplots. Let's cut off the last 10 rows of the dataset, leaving only 3 chickens in the casein category: > chickwts > boxplot(chickwts$weight[1:63] ~ chickwts$feed[1:63], width=table(chickwts$feed[1:63])) 4

5 The help pages for each function will help you change parameters to change the look of your graph. par() par() can be used to query or set graphical parameters. Many of the parameters you can set using par() can also be set using the high-level function call (e.g. specifying plotting symbols, colors, etc.). There are a couple things that are very useful to set in par(), though. >?par Putting several graphs in one window This can be very useful for comparing graphs. > par(mfrow=c(1,2)) > boxplot(chickwts$weight ~ chickwts$feed, width=table(chickwts$feed)) > boxplot(chickwts$weight[1:63] ~ chickwts$feed[1:63], width=table(chickwts$feed[1:63])) Changing Text Size (axis labels, axis ticks labels), Symbol size The help page for plot() shows that " " means we can give it parameters to pass to par(). The help page for par() tells us some of these parameters, such as cex, cex.axis, cex.lab, and cex.main, which change the sizes of the plotting symbols, the font size of the axis tick labels, the font size of the axis titles, and the font size of the main title, respectively. ylab="miles Per Gallon", cex.axis=0.75, cex.lab=1.5, cex.main=2, cex=4) Graphics Devices There are several graphics devices in R. I find the most useful one to be pdf(). This command starts the graphics device for creating pdf files. > pdf( file="c:\temp\rgraph.pdf", width=5, height=5) ylab="miles Per Gallon", col=c("blue","red")[match(mtcars$am, c(0,1))], pch=c(21, 24, 19)[match(mtcars$cyl, c(4, 6, 8))]) > legend(3, 34, legend=c("automatic Transmission", "Manual Transmission"), fill=c("blue", "red")) > legend(4.25, 28, legend=c("4", "6", "8"), title="# Cylinders", pch=c(21, 24, 19)) > dev.off() 5

6 Remember to type dev.off() at the end! This will close the pdf file properly. Other Resources Online CSSS Courses CSSS 508: Introduction to R CSSS 594: Visualizing Data For more advanced R graphics Murrell, Paul. (2005) R Graphics. Chapman & Hall/CRC Press. 6