The document discusses ggplot2, a grammar of graphics plotting package for R. It introduces key concepts of ggplot2 including the layered grammar of graphics model and its components. These components - data, aesthetic mappings, statistical transformations, geometric objects, scales, coordinates, and faceting - provide flexibility to build complex plots from data. The document provides examples using ggplot2 to visualize birth and death rate data and explore the diamonds dataset.

1. Introduction to ggplot2
Elegant Graphics for Data Analysis
Maik Röder
15.12.2011
RUGBCN and Barcelona Code Meetup
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2. Data Analysis Steps
• Prepare data
• e.g. using the reshape framework for restructuring
data
• Plot data
• e.g. using ggplot2 instead of base graphics and
lattice
• Summarize the data and refine the plots
• Iterative process
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3. ggplot2
grammar of graphics
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4. Grammar
• Oxford English Dictionary:
• The fundamental principles or rules of an art or
science
• A book presenting these in methodical form.
(Now rare; formerly common in the titles of
books.)
• System of rules underlying a given language
• An abstraction which facilitates thinking, reasoning
and communicating
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5. The grammar of graphics
• Move beyond named graphics (e.g. “scatterplot”)
• gain insight into the deep structure that underlies
statistical graphics
• Powerful and flexible system for
• constructing abstract graphs (set of points)
mathematically
• Realizing physical representations as graphics by
mapping aesthetic attributes (size, colour) to graphs
• Lacking openly available implementation
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6. Specification
Concise description of components of a graphic
• DATA - data operations that create variables
from datasets. Reshaping using an Algebra with
operations
• TRANS - variable transformations
• SCALE - scale transformations
• ELEMENT - graphs and their aesthetic attributes
• COORD - a coordinate system
• GUIDE - one or more guides
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7. Birth/Death Rate
Source: http://www.scalloway.org.uk/popu6.htm
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8. Excess birth
(vs. death) rates in selected countries
Source: The grammar of Graphics, p.13
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9. Grammar of Graphics
Specification can be run in GPL implemented in SPSS
DATA: source("demographics")
DATA: longitude,
latitude = map(source("World"))
TRANS: bd = max(birth - death, 0)
COORD: project.mercator()
ELEMENT: point(position(lon * lat),
size(bd),
color(color.red))
ELEMENT: polygon(position(longitude *
latitude))
Source: The grammar of Graphics, p.13
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10. Rearrangement of Components
Grammar of Graphics Layered Grammar of
Graphics
Data Defaults
Trans Data
Mapping
Element Layer
Data
Mapping
Geom
Stat
Scale Position
Guide Scale
Coord
Coord Facet
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11. Layered Grammar of Graphics
Implementation embedded in R using ggplot2
w <- world
d <- demographics
d <- transform(d,
bd = pmax(birth - death, 0))
p <- ggplot(d, aes(lon, lat))
p <- p + geom_polygon(data = w)
p <- p + geom_point(aes(size = bd),
colour = "red")
p <- p + coord_map(projection = "mercator")
p
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12. ggplot2
• Author: Hadley Wickham
• Open Source implementation of the layered
grammar of graphics
• High-level R package for creating publication-
quality statistical graphics
• Carefully chosen defaults following basic
graphical design rules
• Flexible set of components for creating any type of
graphics
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13. ggplot2 installation
• In R console:
install.packages("ggplot2")
library(ggplot2)
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14. qplot
• Quickly plot something with qplot
• for exploring ideas interactively
• Same options as plot converted to ggplot2
qplot(carat, price,
data=diamonds,
main = "Diamonds",
asp = 1)
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16. Exploring with qplot
First try:
qplot(carat, price,
data=diamonds)
Log transform using functions on the variables:
qplot(log(carat),
log(price),
data=diamonds)
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18. from qplot to ggplot
qplot(carat, price,
data=diamonds,
main = "Diamonds",
asp = 1)
p <- ggplot(diamonds, aes(carat, price))
p <- p + geom_point()
p <- p + opts(title = "Diamonds",
aspect.ratio = 1)
p
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19. Data and mapping
• If you need to flexibly restructure and
aggregate data beforehand, use Reshape
• data is considered an independent concern
• Need a mapping of what variables are
mapped to what aesthetic
• weight => x, height => y, age => size
• Mappings are defined in scales
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20. Statistical Transformations
• a stat transforms data
• can add new variables to a dataset
• that can be used in aesthetic mappings
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21. stat_smooth
• Fits a smoother to the data
• Displays a smooth and its standard error
ggplot(diamonds, aes(carat, price)) +
geom_point() + geom_smooth()
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23. Geometric Object
• Control the type of plot
• A geom can only display certain aesthetics
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24. geom_histogram
• Distribution of carats shown in a histogram
ggplot(diamonds, aes(carat)) +
geom_histogram()
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26. Position adjustments
• Tweak positioning of geometric objects
• Avoid overlaps
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27. position_jitter
• Avoid overplotting by jittering points
x <- c(0, 0, 0, 0, 0)
y <- c(0, 0, 0, 0, 0)
overplotted <- data.frame(x, y)
ggplot(overplotted, aes(x,y)) +
geom_point(position=position_jitter
(w=0.1, h=0.1))
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29. Scales
• Control mapping from data to aesthetic
attributes
• One scale per aesthetic
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30. scale_x_continuous
scale_y_continuous
x <- c(0, 0, 0, 0, 0)
y <- c(0, 0, 0, 0, 0)
overplotted <- data.frame(x, y)
ggplot(overplotted, aes(x,y)) +
geom_point(position=position_jitter
(w=0.1, h=0.1)) +
scale_x_continuous(limits=c(-1,1)) +
scale_y_continuous(limits=c(-1,1))
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32. Coordinate System
• Maps the position of objects into the plane
• Affect all position variables simultaneously
• Change appearance of geoms (unlike scales)
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33. coord_map
library("maps")
map <- map("nz", plot=FALSE)[c("x","y")]
m <- data.frame(map)
n <- qplot(x, y, data=m, geom="path")
n
d <- data.frame(c(0), c(0))
n + geom_point(data = d, colour = "red")
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35. Faceting
• lay out multiple plots on a page
• split data into subsets
• plot subsets into different panels
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36. Facet Types
2D grid of panels: 1D ribbon of panels
wrapped into 2D:
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37. Faceting
aesthetics <- aes(carat, ..density..)
p <- ggplot(diamonds, aesthetics)
p <- p + geom_histogram(binwidth = 0.2)
p + facet_grid(clarity ~ cut)
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39. Faceting Formula
no faceting .~ .
single row multiple columns .~ a
single column, multiple rows b~.
multiple rows and columns a~b
.~ a + b
multiple variables in rows and/or
a + b ~.
columns
a+b~c+d
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40. Scales in Facets
facet_grid(. ~ cyl, scales="free_x")
scales value free
fixed -
free x, y
free_x x
free_y y
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41. Layers
• Iterativey update a plot
• change a single feature at a time
• Think about the high level aspects of the
plot in isolation
• Instead of choosing a static type of plot,
create new types of plots on the fly
• Cure against immobility
• Developers can easily develop new layers
without affecting other layers
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42. Hierarchy of defaults
Omitted layer Default chosen by layer
Stat Geom
Geom Stat
Mapping Plot default
Coord Cartesian coordinates
Chosen depending on aesthetic and type of
Scale
variable
Linear scaling for continuous variables
Position
Integers for categorical variables
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43. Thanks!
• Visit the ggplot2 homepage:
• http://had.co.nz/ggplot2/
• Get the ggplot2 book:
• http://amzn.com/0387981403
• Get the Grammar of Graphics book from
Leland Wilkinson:
• http://amzn.com/0387245448
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