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R Markdown Cookbook Practical Tips and Tricks for R Markdown

Yihui Xie, Christophe Dervieux, Emily Riederer

Section 11.16 Step-by-step plots with low-level plotting functions

For R graphics, there are two types of plotting functions: high-level plotting functions create new plots, and low-level functions add elements to existing plots. You may see Chapter 12 ("Graphical procedures") of the R manual An Introduction to R for more information.
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By default, knitr does not show the intermediate plots when a series of low-level plotting functions are used to modify a previous plot. Only the last plot on which all low-level plotting changes have been made is shown.
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It can be useful to show the intermediate plots, especially for teaching purposes. You can set the chunk option fig.keep = 'low' to keep low-level plotting changes. For example, Figure 11.16.1 and Figure 11.16.2 are from a single code chunk with the chunk option fig.keep = 'low', although they appear to be from two code chunks. We also assigned different figure captions to them with the chunk option fig.cap = c('A scatterplot ...', 'Adding a regression line...').
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par(mar = c(4, 4, .1, .1))
plot(cars)
fit = lm(dist ~ speed, data = cars)
abline(fit)
A scatterplot showing the relationship between car speed (x-axis) and stopping distance (y-axis) from the cars dataset.
Figure 11.16.1. A scatterplot of the cars data.
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A scatterplot of the cars data with a fitted regression line added, showing the linear relationship between speed and stopping distance.
Figure 11.16.2. Adding a regression line to an existing scatterplot.
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If you want to keep modifying a plot in a different code chunk, please see Section 14.5.
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