Data visualization with R study guide

General structure

Overview The general structure of the code that is used to plot figures is as follows:

ggplot(...) +             # Initialization
  geom_function(...) +    # Main plot(s)
  facet_function(...) +   # Facets (optional)
  labs(...) +             # Legend (optional)
  scale_function(...) +   # Scales (optional)
  theme_function(...)     # Theme (optional)

We note the following points:

The ggplot() layer is mandatory.
When the data argument is specified inside the ggplot() function, it is used as default in the following layers that compose the plot command, unless otherwise specified.
In order for features of a data frame to be used in a plot, they need to be specified inside the aes() function.

Basic plots The main basic plots are summarized in the table below:

Type	Command and parameters	Illustration
Scatter plot	`geom_point(` `x, y, params` `)`
Line plot	`geom_line(` `x, y, params` `)`
Bar chart Histogram	`geom_bar(` `x, y, params` `)`
Box plot	`geom_boxplot(` `x, y, params` `)`
Heatmap	`geom_tile(` `x, y, params` `)`

where the possible parameters are summarized in the table below:

Command	Description	Example
`color`	Color of a line / point / border	`'red'`
`fill`	Color of an area	`'red'`
`size`	Size of a line / point	`4`
`shape`	Shape of a point	`4`
`linetype`	Shape of a line	`'dashed'`
`alpha`	Transparency, between 0 and 1	`0.3`

Remark: this reference provides an extensive list of possible colors.

Maps It is possible to plot maps based on geometrical shapes as follows:

The following table summarizes the main commands used to plot maps:

Category	Action	Command
Map	Draw polygon shapes from the `geometry` column	`geom_sf(data)`
Additional elements	Add and customize geographical directions	`annotation_north_arrow(location)`
Additional elements	Add and customize distance scale	`annotation_scale(location)`
Range	Customize range of coordinates	`coord_sf(xlim, ylim)`

Animations Plotting animations can be made using the gganimate library. The following command gives the general structure of the code:

# Main plot
ggplot() +
  ... +
  transition_states(field, states_length)

# Generate and save animation
animate(plot, duration, fps, width, height, units, res, renderer)
anim_save(filename)

Advanced features

Facets It is possible to represent the data through multiple dimensions with facets using the following commands:

Type	Command	Illustration
Grid (1 or 2D)	`facet_grid(` `row_var ~ column_var` `)`
Wrapped	`facet_wrap(` `vars(x1, ..., xn),` `nrow, ncol` `)`

Text annotation Plots can have text annotations with the following commands:

Command	Illustration
`geom_text(` `x, y, label,` `hjust, vjust` `)`
`geom_label_repel(` `x, y, label,` `nudge_x, nudge_y` `)`

Additional elements We can add objects on the plot with the following commands:

Type	Command	Illustration
Line	`geom_vline(` `xintercept, linetype` `)`
Line	`geom_hline(` `yintercept, linetype` `)`
Curve	`geom_curve(` `x, y, xend, yend` `)`
Rectangle	`geom_rect(` `xmin, xmax, ymin, ymax` `)`

Last touch

Legend The title of legends can be customized to the plot with the following command:

plot + labs(params)

where the params are summarized below:

Element	Command
Title / subtitle of the plot	`title = 'text'` / `subtitle = 'text'`
Title of the $x$ / $y$ axis	`x = 'text'` / `y = 'text'`
Title of the size / color	`size = 'text'` / `color = 'text'`
Caption of the plot	`caption = 'text'`

This results in the following plot:

Plot appearance The appearance of a given plot can be set by adding the following command:

Type	Command	Illustration
Black and white	`theme_bw()`
Classic	`theme_classic()`
Minimal	`theme_minimal()`
None	`theme_void()`

In addition, theme() is able to adjust positions/fonts of elements of the legend.
Remark: in order to fix the same appearance parameters for all plots, the theme_set() function can be used.

Scales and axes Scales and axes can be changed with the following commands:

Category	Action	Command
Range	Specify range of $x$ / $y$ axis	`xlim(xmin, xmax)`
		`ylim(ymin, ymax)`
Nature	Display ticks in a customized manner	`scale_x_continuous()`
		`scale_x_discrete()`
		`scale_x_date()`
Magnitude	Transform axes	`scale_x_log10()`
		`scale_x_reverse()`
		`scale_x_sqrt()`

Remark: the scale_x() functions are for the $x$ axis. The same adjustments are available for the $y$ axis with scale_y() functions.

Double axes A plot can have more than one axis with the sec.axis option within a given scale function scale_function(). It is done as follows:

scale_function(sec.axis = sec_axis(~ .))

Saving figure It is possible to save figures with predefined parameters regarding the scale, width and height of the output image with the following command:

ggsave(plot, filename, scale, width, height)