head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

Functions create graphics, example with Fisher's Iris:

hist(iris$Petal.Length, col = "grey", border = "white",
     main = "Example of a histogram", xlab = "Fisher's Iris: petal length")

Functions create a graphical object:

my_plot <- ggplot(iris) + geom_histogram(aes(Petal.Length)) +
  labs(title = "Example of a histogram",
       x = "Fisher's Iris: petal length")
my_plot

ggplot2 builds graphics one component at a time. The grammar includes:

• ggplot(): to provide the data
• geom_...: to define the type of graph
• aes(): to map features of data into aesthetic properties (e.g. shapes, colors)

my_plot <- ggplot(iris) + # use 'iris' data.frame
  geom_histogram(aes(Petal.Length)) + # hist using petal length
  labs(title = "Example of a histogram", # add title
       x = "Fisher's Iris: petal length") # add x label

For instance, to color histograms by species:

my_plot + aes(fill = Species)

my_plot <- ggplot(iris, aes(x = Petal.Length, y = Sepal.Length)) +
  geom_point(aes(color = Species, shape = Species),
             size = 5, alpha = .75) +
  geom_smooth() +
  labs(title = "Example of a scatterplot")
my_plot

Learn more about ggplot2:

• check the package's website
• a list of all available geoms_ (types of plot)
• a list of aes() specifications (colors / shapes / etc.)
• a gallery of extensions to ggplot2

• select your favourite colors, e.g. using a color picker
• make a named vector storing these colors as character
• specify your colors using e.g.:

col <- c(setosa = "#666699", versicolor = "#99cc00", virginica = "#b30059")
my_plot + scale_color_manual(values = col)

Note that you will need to use scale_fill_manual for colors specified through fill = ....

You can use facet_grid(rows ~ columns) to specify panels:

new_plot <- ggplot(iris) +
  geom_histogram(aes(x = Petal.Length, fill = Species)) +
  scale_fill_manual(values = col) + facet_grid(Species ~  .)
new_plot

Use theme(legend.position = c(x_coord, y_coord)) to move the legend:

new_plot + theme(legend.position = c(.9, .8))

Other themes are available and can be customised:

new_plot + theme_light(base_family = "Times", base_size = 20)