ggplot2 tutorial: Grammar of Graphics

Web Reference: A system for declaratively creating graphics, based on "The Grammar of Graphics". You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. ggplot2 is an R package for producing visualizations of data. Unlike many graphics packages, ggplot2 uses a conceptual framework based on the grammar of graphics. This allows you to ‘speak’ a graph from composable elements, instead of being limited to a predefined set of charts. More complete information about how to use ggplot2 can be found in the book, but here you’ll find a brief ... All ggplot2 plots begin with a call to ggplot(), supplying default data and aesthetic mappings, specified by aes(). You then add layers, scales, coords and facets with +. To save a plot to disk, use ggsave().

YouTube Excerpt: Learn more about Grammer of Graphics in ggplot2: https://www.datacamp.com/courses/data-visualization-with-ggplot2-part-1 The first step in thinking creatively about data visualisation is to appreciate that graphics are built upon an underlying grammar. To begin, let's consider one of the most well-known sentences in English The quick brown fox jumps over the lazy dog. Every word in the sentence has a clear grammatical definition and when we write text, we take great care to choose the grammatical elements so that we communicate a very specific message. If we changed any of the grammatical elements of this sentence it would change the meaning, sometimes subtly, sometimes dramatically. The same concept holds true for data visualisation - graphics are build on an underlying grammar. The grammar of graphics is a plotting framework developed by Leland Wilkinson and published in his 1999 book, The Grammar of Graphics. There are two key things to note about the grammar of graphics. First, graphics are made up of distinct layers of grammatical elements, and second. meaningful plots are built around appropriate aesthetic mappings. To continue our analogy to written grammar, the layers are like the adjectives and nouns and the aesthetic mappings are like the grammatical rules for how to assemble that vocabulary. Let's explore grammatical elements first. There are seven grammatical elements in total and three of them are essential: Data, aesthetics, geometries The data is obviously the data which we want to plot. the aesthetics layer refers to the scales onto which we will map our data, and the geom layer refers to the actual shape the data will take in the plot. The remainig elements are optional, and control details of our plots. They are the facets, statistics, coordinates and theme layers. We will explore the optional layers in the next course. This diagram gives an example of some of the terms we'll encounter in each layer. Whenever we make a plot we are choosing from these items, and even more which are not shown. The grammar of graphics established the building blocks for solid, creative and meaningful data visualisations. This means we are not limited to specific, standard, forms of expression. because now we have a framework that allows us to communicate in a way that best suits our goal. By the end of this couse you will be able to generate meaningful exploratory plots using the first three layers. In the next courese we'll go into details of the remaining four optional layers. Let's head over to the exercises and explore one of the datasets that you'll be using throughout the two courses.

Learn more about Grammer of Graphics in ggplot2: https://www.datacamp.com/courses/data-visualization-with-ggplot2-part-1 The first step in...

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