5.13 Review of Basic Visualization

In this chapter, we have introduced the most commonly used plots for visualization. It is helpful to review what we have learned so far.

5.13.1 Summary of geoms

Names	Funs	Section
One continuous variable (e.g. cholesterol or sale_price)
Histogram	geom_histogram(aes(x = cholesterol))	5.9
Density Plot	geom_density(aes(x = cholesterol))	5.10
Boxplot	geom_boxplot(aes(x = "", y = sale_price))	5.11
One discrete variable (e.g. kit_qual)
Bar Chart	geom_bar(mapping = aes(x = kit_qual))	5.8.1
Pie Chart	geom_bar(aes(x = kit_qual), stat = "identity") + coord_polar("y")	5.8.4
Two continuous variables (e.g. sugar and cholesterol)
Scatterplot	geom_point(mapping = aes(x = sugar, y = cholesterol))	5.1
Line Plot	geom_line(mapping = aes(x = dt_sold, y = sale_price))	5.5
Smoothline	geom_smooth(mapping = aes(x = sugar, y = cholesterol))	5.6
Two discrete variables (e.g. kit_qual and central_air):
Bar Chart	geom_bar(mapping = aes(x = kit_qual, fill = central_air))	5.8.3
One continuous variable and one discrete variable (e.g. kit_qual and sale_price):
Boxplot	geom_boxplot(aes(x = kit_qual, y = sale_price))	5.11.3

5.13.2 The grammatical structure of ggplot()

Next, we review the grammatical structure of ggplot().

Code	Info
ggplot(data = <DATA>) +	data to be used
<GEOM_FUNCTION>(	geom for generating the desirable plot
mapping = aes(<MAPPINGS>),	aesthetic mappings, this may include the x and y axes and other features like color, shape, fill, linetype, size, etc.
stat = <STAT>,	statistical transformation, for example, when we create the errorbar
position = <POSITION>) +	position, like stack, dodge, fill
<COORDINATE_FUNCTION> +	such as flipping the x and y axes
<FACET_FUNCTION> +	facet_wrap() and facet_grid(), create multiple plots for different subsets of the data
<SCALE_FUNCTION> +	customize the x and y breaks
<THEME_FUNCTION>	customize labels, title, and fonts

5.13.3 A complex ggplot() example

To conclude this chapter, let’s look at an example with all components.

library(r02pro)
library(tidyverse)
ggplot(data = na.omit(sahp)) +
  geom_bar(
    mapping = aes(x = kit_qual, fill = oa_qual > 5),
    stat = "count", #Default stat for geom_bar, can be removed
    position = "fill") +
  coord_flip() +
  facet_wrap(vars(house_style)) +
  scale_y_continuous(breaks = seq(from = 0, to = 1, by = 0.2)) +
  theme(plot.title = element_text(size = 24, color = "magenta")) +
        xlab("Kitchen quality") +
  ylab("Proportion") +
  ggtitle('A bar chart in proportion of kitchen quality')

This plot shows a bar chart using the data sahp for the variable kit_qual, map the variable oa_qual > 5 to the fill aesthetic and with fill position, with the x and y coordinates flipped, faceted using the variable house_style, and with the breaks on the y axis, the title and its font, the label on the y axis being customized.