Learn R – How to Get Started with GGPlot – Code Example

This article represents quick introduction to GGPlot along with key concepts and code examples using R programming language. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.


Following are the key points described later in this article:

  • Quick introduction to GGPlot
  • Installation and loading of GGPlot
  • GGPlot – Key Concepts


Quick Introduction to GGPlot

ggplot is one of statistical package that facilitates the easy creation of different plots. One of the key concept related to ggplot is that ggplot is built up layer by layer. This means that one could start by initializing the ggplot using ggplot(data) command and then, keep adding on plot functions as another layer in order to finally draw the plot/chart. The layers are separated by “+” sign. Following is a sample ggplot command created using diamonds data that gets loaded by default when loading ggplot.

	ggplot(data=diamonds, aes(x=carat, y=price)) + geom_point(aes(color=color)) + xlab("Carat") + ylab("Price") + ggtitle("Carat vs Price")

Following is the plot for above command:



Installation and Loading of ggplot

Before going further, lets quickly see what would it take to install and load ggplot2 package.

  • Install the ggplot2 package. When using R console, you could do that by clicking on Packages > Install packages…. When using RStudio, one could do that by clicking on Tools > Install packages…
  • Load the package using either “library” command or “require” command.


GGPlot – Key Concepts

Following are some key concepts to know when starting with ggplot:

  • ggplot function: ggplot function is the core of ggplot2 package. The basic syntax is ggplot(data=dataFrameName). The data argument (or dataset passed) to ggplot command must be of type, data frame. ggplot could also take additional number of arguments. However, the main argument is the one specified in the example below. When loading ggplot, diamonds data comes by default. Thus, to work with diamonds data, following is how ggplot commands would look like:
  • Different layer functions: Once initialized using ggplot command, one would require to draw the plot. For this, one would need to use one of the many layer functions such as some of the following which takes different arguments, the primary one being another function called as aes (short for aesthetic).
    • geom_point
    • geom_histogram
    • geom_line
  • aes function: In above mentioned layer functions, one of the key parameter is aes function which takes some of the following as arguments:
    • Labels representing points to be plotted on the graph/plot. Following is the syntax:
    • Color of the plot using command such as aes(color=someColor)
    • Shape of the plot using command such as aes(shape=clarity)

    One must note that aes function could either go in ggplot function such as following or in one of the geom functions.

    # aes function within ggplot function
    ggplot(data=diamonds, aes(x=carat, y=price)) + geom_point() + xlab("Carat") + ylab("Price") + ggtitle("Carat vs Price")
    # aes function within geom function
    ggplot(data=diamonds) + geom_point(aes(x=carat, y=price)) + xlab("Carat") + ylab("Price") + ggtitle("Carat vs Price")


Nidhi Rai

Nidhi Rai

Nidhi has been been actively blogging in different technologies such as AI / machine learning and internet technologies. Her field of interest includes AI / ML, Java, mobile technologies, UI programming such as HTML, CSS, Javascript (Angular/ReactJS etc), open-source and other related technologies.
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