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Scatter Plot Matrix in Base R

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2017-07-04 2:09:02
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Statistical Analysis with R Essentials For Dummies
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Base R provides a nice way of visualizing relationships among more than two variables. If you add price into the mix and you want to show all the pairwise relationships among MPG-city, price, and horsepower, you'd need multiple scatter plots. R can plot them all together in a matrix, as the figure shows.

stats-r-plot-matrix Multiple scatter plots for the relationships among MPG-city, price, and horsepower.

The names of the variables are in the cells of the main diagonal. Each off-diagonal cell shows the scatter plot for its row variable (on the y-axis) and its column variable (on the x-axis). For example, the scatter plot in the first row, second column shows MPG-city on the y-axis and price on the x-axis. In the second row, first column, the axes are reversed: MPG city is on the x-axis, and price is on the y-axis.

The R function for plotting this matrix is pairs(). To calculate the coordinates for all scatter plots, this function works with numerical columns from a matrix or a data frame.

For convenience, you create a data frame that's a subset of the Cars93 data frame. This new data frame consists of just the three variables to plot. The function subset() handles that nicely:

cars.subset <- subset(Cars93, select = c(MPG. city,Price,Horsepower)) The second argument to subset creates a vector of exactly what to select out of Cars93. Just to make sure the new data frame is the way you want it, use the head() function to take a look at the first six rows:

> head(cars.subset)

MPG.city Price Horsepower

1 25 15.9 140 2 18 33.9 200 3 20 29.1 172 4 19 37.7 172 5 22 30.0 208 6 22 15.7 110 And now,

> pairs(cars.subset) creates the plot shown.

This capability isn't limited to three variables, nor to continuous ones. To see what happens with a different type of variable, add Cylinders to the vector for select and then use the pairs() function on cars.subset.

Box plots

To draw a box plot, you use a formula to show that Horsepower is the dependent variable and Cylinders is the independent variable:

> boxplot(Cars93$Horsepower ~ Cars93$Cylinders, xlab="Cylinders", ylab="Horsepower")

If you get tired of typing the $-signs, here's another way:

> boxplot(Horsepower ~ Cylinders, data = Cars93, xlab="Cylinders", ylab="Horsepower")

With the arguments laid out as in either of the two preceding code examples, plot() works exactly like boxplot().

About This Article

This article is from the book: 

About the book author:

Joseph Schmuller, PhD, is a cognitive scientist and statistical analyst. He creates online learning tools and writes books on the technology of data science. His books include R All-in-One For Dummies and R Projects For Dummies.