• ggplot2 was developed by Hadley Wickham and is based on Leland Wilkinson’s Grammar of Graphics.

• ggplot2 emphasizes clarity, flexibility, and the use of the grammar of graphics philosophy.

• Grammar of Graphics: A system for describing and building graphs.

• ggplot2 allows for the creation of complex plots from simple components.

• The emphasis is on layering components to build up to the visualization you need.

• Aesthetics define how your data is mapped to visual properties (e.g., x, y , color).

• Geoms represent geometric shapes that represent data (e.g., points, lines, bars).

• Scales fine-tune how aesthetics relationships arevisually encoded (e.g., color maps).

• Themes control the non-data parts of the plot (e.g., plot background, grid lines, and text elements.)

• Aesthetics define how your data is mapped to visual properties.

• Common aesthetics include x, y, color, fill, size, and shape.

# `aes` used to map `displ` to x coordinates and `hwy` to y
# coordinates
library(ggplot2)
ggplot(mpg, aes(x=displ, y=hwy)) + 
    geom_point()

• Geoms represent geometric shapes that represent data (e.g., points, lines, bars, etc.)

# `geom_smooth()` and `geom_point` used to represent x and y
ggplot(mpg, aes(x=displ, y=hwy)) + 
    geom_point()

• Scales fine-tune how aesthetics relationships arevisually encoded (e.g., color maps, axis transforms, etc).

# `scale_color_manual` used to control how levels of `class`
# are mapped to colors.
ggplot(mpg, aes(x=displ, y=hwy, color=class)) +
  geom_point() +
  scale_color_manual(values=c("compact"="blue", 
                              "suv"="red",
                              "pickup"="green",
                              "midsize"="purple",
                              "minivan"="orange",
                              "2seater"="brown",
                              "subcompact"="pink"))

• Themes control the non-data parts of the plot (e.g., plot background, grid lines, and text elements.)

# `theme_minimal` is used set a minimal appearance to the
# overall plot
ggplot(mpg, aes(x=displ, y=hwy)) +
    geom_point() + 
    theme_minimal()

• Aesthetics define how your data is mapped to visual properties (e.g., x, y , color).

• Geoms represent geometric shapes that represent data (e.g., points, lines, bars).

• Scales fine-tune how aesthetics relationships arevisually encoded (e.g., color maps).

• Themes control the non-data parts of the plot (e.g., plot background, grid lines, and text elements.)

Identify the major components of the following ggplot2 plot.

ggplot(mpg, aes(x=displ, y=hwy, color=class)) +
  geom_point() +
  scale_color_manual(values=c("compact"="blue", 
                              "suv"="red",
                              "pickup"="green",
                              "midsize"="purple",
                              "minivan"="orange",
                              "2seater"="brown",
                              "subcompact"="pink")) +
    theme_minimal()