Section 3.2 Learning Objectives
By the end of this chapter, you will be able to:
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Explain why visualizing data is a critical step alongside summary statistics
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Describe the core grammar of graphics used by
ggplot2(data, aesthetics, geometry) -
Create common plot types using
ggplot2, including scatterplots, bar charts, column charts, histograms, density plots, boxplots, and line graphs -
Map and customize aesthetics such as color, shape, size, fill, and transparency
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Enhance visual clarity using labels, themes, facets, coordinate transformations, and reference lines
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Add contextual information to plots using trend lines, error bars, and text labels
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Interpret visual patterns to identify relationships, distributions, outliers, and trends in data
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Create visualizations that are interpretable and reproducible when viewed independently of accompanying text
With that being said, let’s get right to it.
