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The middle bar will have a height of 3 and will appear above [2, 3), but be sure to try it and see for yourself. The histogram will look like a symmetric pyramid.
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You can make a histogram of x3 with qplot(x3, binwidth = 1). To make sure our graphs look the same, use the extra argument binwidth = 1: x <- c( 1, 2, 2, 2, 3, 3)
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The following code makes the left-hand plot in Figure 3.2 (we’ll worry about the right-hand plot in just second).
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qplot will make a histogram whenever you give it only one vector to plot. Let’s take a look at a histogram to see if this makes sense. A histogram visualizes the distribution of a single variable it displays how many data points appear at each value of x. However, we’re going to use a different type of graph, a histogram. Scatterplots are useful for visualizing the relationship between two variables. How did R match up the values in x and y to make these points? With element-wise execution, as we saw in Figure 2.3. Together, the vectors x and y describe a set of 10 points. As you can see in Figure 3.1, a scatterplot is a set of points, each plotted according to its x and y values. I just did that to make the example clear. You don’t need to name your vectors x and y. Give c all of the numbers that you want to appear in the vector, separated by a comma. Until now, we’ve been creating sequences of numbers with the : operator but you can also create vectors of numbers with the c function. The following code will make the plot that appears in Figure 3.1. Look for the plot to appear in the Plots tab of the bottom-right pane in your RStudio window. qplot will use the first vector as a set of x values and the second vector as a set of y values. qplot makes “quick plots.” If you give qplot two vectors of equal lengths, qplot will draw a scatterplot for you. Now that you’ve loaded qplot, let’s take it for a spin. R will unload all of its packages each time you close RStudio.
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The main thing to remember is that you only need to install a package once, but you need to load it with library each time you wish to use it in a new R session. I recommend that you read it if you are unfamiliar with R’s package system. Now if you ask to see qplot, R will show you quite a bit of code ( qplot is a long function): qplotĪppendix 2: R Packages contains many more details about acquiring and using packages. As long as you do not see anything that says “Error,” you are doing fine. Don’t worry if you do see a message either ggplot2 sometimes displays helpful start up messages. No news is fine news when loading a package. Don’t worry if you don’t see any results or messages. If you installed the package with install.packages as instructed, everything should go fine. Now load the ggplot2 package: library( "ggplot2") R won’t be able to find qplot because qplot lives in the ggplot2 package, which you haven’t loaded: qplot First, ask R to show you the qplot function. To see what this does, try an experiment. If you would like to load a different package, replace ggplot2 with your package name in the code. To use an R package, you next have to load it in your R session with the command library("ggplot2"). Installing a package doesn’t place its functions at your fingertips just yet: it simply places them in your hard drive.