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ggplot

Resources:

The basic idea: independently specify plot building blocks and combine them to create just about any kind of graphical display you want. Building blocks of a graph include:

  • data
  • aesthetic mapping
  • geometric object
  • statistical transformations
  • scales
  • coordinate system
  • position adjustments
  • faceting

In ggplot land aesthetic means "something you can see". Each type of geom accepts only a subset of all aesthetics–refer to the geom help pages to see what mappings each geom accepts. Aesthetic mappings are set with the aes() function.

Note that variables are mapped to aesthetics with the aes() function, while fixed aesthetics are set outside the aes() call.

Geometric objects are the actual marks we put on a plot. Examples include:

  • points (geom_point, for scatter plots, dot plots, etc)
  • lines (geom_line, for time series, trend lines, etc)
  • boxplot (geom_boxplot, for, well, boxplots!)
  • geom_line for a smoothed out line (with gray area showing range)

Each geom accepts a particualar set of mappings.

Each geom has a default statistic, but these can be changed. For example, geom_histogram() is stat:

> args(geom_histogram)
function (mapping = NULL, data = NULL, stat = "bin", 
  position = "stack", ..., binwidth = NULL, 
  bins = NULL, na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE)

You can see the argets for the bin stat like this:

> args(stat_bin)
function (mapping = NULL, data = NULL, geom = "bar", position = "stack", 
    ..., binwidth = NULL, bins = NULL, center = NULL, boundary = NULL, 
    closed = c("right", "left"), pad = FALSE, na.rm = FALSE, 
    show.legend = NA, inherit.aes = TRUE)

Arguments to stat_ functions can be passed through geom_ functions. For example, bin has a binwidth argument so we can pass it through to the geom_:

geom_histogram(binwidth = 4000)

The ggplot function

ggplot(
  data = NULL, 
  mapping = aes(), ...,
  environment = parent.frame())
  • Default dataset to use for plot.
  • Default list of aesthetic mappings to use for plot. If not specified, must be suppled in each layer added to the plot.

Typically:

ggplot(df, aes(x, y, <other aesthetics>))

Examples:

> housing <- read.csv("data/landdata-states.csv")
> states <- subset(housing, State %in% c("MA", "TX"))
> g <- ggplot(states, aes(x = Date, y = Home.Value, color = State))
> g <- g + geom_point()

Could have also done this without specifying x and y:

> g <- ggplot(states, aes(Date, Home.Value, color = State))

Instead of geom_point(), we could have used another geometric object like geom_line().

Simple line chart

df <- data.frame(x = seq(1:4),y = c(4.2, 10, 29.5))
> ggplot(data = df, aes(x = x, y = y, group = 1)) + geom_line() + geom_point()

Stacked bar chart

g <- ggplot(data, aes(x = expiry_month, y = quantity, fill = auto_renew))
g <- g + geom_bar(stat = "identity")

Customizing the chart

Adding a title

ggtitle("Sign Ups by Date and Vertical")

Setting the X and Y axis labels

labs(x = "Date", y = "Vertical")

Adding a margin around the chart

theme(plot.margin = unit(c(1, 1, 1, 1), "cm"))

Formatting the y axis values

library(scales)
scale_y_continuous(labels = comma)