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Hadley Wickham
Stat405Graphical theory & critique
Tuesday, 19 October 2010
Project
• Generally excellent
• Common problems: lack of proof reading, lack of flow
• If you’re going to throw away 85% of the data, I want to know how that differs from the data that you kept
Tuesday, 19 October 2010
Project
• Don’t forget to set up a meeting time with me this week
• (I’ll be travelling from Saturday until when the project is due, so if you can’t meet with me this week, email Garrett to set up a time)
Tuesday, 19 October 2010
Tuesday, 19 October 2010
Exploratory graphics
Are for you (not others). Need to be able to create rapidly because your first attempt will never be the most revealing.
Iteration is crucial for developing the best display of your data.
Gives rise to two key questions:
Tuesday, 19 October 2010
What should I plot?How can I plot it?
Tuesday, 19 October 2010
Two general tools
Plot critique toolkit: “graphics are like pumpkin pie”
Theory behind ggplot2:“A layered grammar of graphics”
plus lots of practice...
Tuesday, 19 October 2010
Graphics are like pumpkin pie
The four C’s of critiquing a graphic
Tuesday, 19 October 2010
Content
Tuesday, 19 October 2010
Construction
Tuesday, 19 October 2010
ContextTuesday, 19 October 2010
ConsumptionTuesday, 19 October 2010
Content
What data (variables) does the graph display?What non-data is present?What is pumpkin (essence of the graphic) vs what is spice (useful additional info)?
Tuesday, 19 October 2010
Your turn
Identify the data and non-data on “Napoleon's march” and “Building an electoral victory”. Which features are the most important? Which are just useful background information?
Tuesday, 19 October 2010
Results
Minard’s march: (top) latitude, longitude, number of troops, direction, branch, city name (bottom) latitude, temperature, dateBuilding an electoral victory: state, number of electoral college votes, winner, margin of victory
Tuesday, 19 October 2010
Construction
How many layers are on the plot?What data does each layer display? What sort of geometric object does it use? Is it a summary of the raw data? How are variables mapped to aesthetics?
Tuesday, 19 October 2010
Perceptual mapping1. Position along a common scale 2. Position along nonaligned scale 3. Length4. Angle/slope5. Area 6. Volume7. Colour
Best
Worst
For continuous
variables only!
Tuesday, 19 October 2010
Your turn
Answer the following questions for “Napoleon's march” and “Flight delays”:How many layers are on the plot?What data does the layer display? How does it display it?
Tuesday, 19 October 2010
ResultsNapoleon’s march: (top) (1) path plot with width mapped to number of troops, colour to direction, separate group for each branch (2) labels giving city names (bottom) (1) line plot with longitude on x-axis and temperature on y-axis (2) text labels giving datesFlight delays: (1) white circles showing 100% cancellation, (2) outline of states, (3) points with size proportional to percent cancellations at each airport.
Tuesday, 19 October 2010
Can the explain composition of a graphic in words, but how do we
create it?
Tuesday, 19 October 2010
“If any number of magnitudes are each the same multiple of the same number of other magnitudes, then the sum is that multiple of the sum.” Euclid, ~300 BC
Tuesday, 19 October 2010
“If any number of magnitudes are each the same multiple of the same number of other magnitudes, then the sum is that multiple of the sum.” Euclid, ~300 BC
m(Σx) = Σ(mx)Tuesday, 19 October 2010
The grammar of graphics
An abstraction which makes thinking about, reasoning about and communicating graphics easier.
Developed by Leland Wilkinson, particularly in “The Grammar of Graphics” 1999/2005
You’ve been using it in ggplot2 without knowing it! But to do more, you need to learn more about the theory.
Tuesday, 19 October 2010
What is a layer?
• Data
• Mappings from variables to aesthetics (aes)
• A geometric object (geom)
• A statistical transformation (stat)
• A position adjustment (position)
Tuesday, 19 October 2010
layer(geom, stat, position, data, mapping, ...)
layer( data = mpg, mapping = aes(x = displ, y = hwy), geom = "point", stat = "identity", position = "identity")
layer( data = diamonds, mapping = aes(x = carat), geom = "bar", stat = "bin", position = "stack")
Tuesday, 19 October 2010
# A lot of typing!
layer( data = mpg, mapping = aes(x = displ, y = hwy), geom = "point", stat = "identity", position = "identity")
# Every geom has an associated default statistic# (and vice versa), and position adjustment.
geom_point(aes(displ, hwy), data = mpg)geom_histogram(aes(displ), data = mpg)
Tuesday, 19 October 2010
# To actually create the plotggplot() + geom_point(aes(displ, hwy), data = mpg) ggplot() + geom_histogram(aes(displ), data = mpg)
Tuesday, 19 October 2010
# Multiple layersggplot() + geom_point(aes(displ, hwy), data = mpg) + geom_smooth(aes(displ, hwy), data = mpg)
# Avoid redundancy:ggplot(mpg, aes(displ, hwy)) + geom_point() + geom_smooth()
Tuesday, 19 October 2010
# Different layers can have different aestheticsggplot(mpg, aes(displ, hwy)) + geom_point(aes(colour = class)) + geom_smooth()
ggplot(mpg, aes(displ, hwy)) + geom_point(aes(colour = class)) + geom_smooth(aes(group = class), method = "lm", se = F)
Tuesday, 19 October 2010
Your turnFor each of the following plots created with qplot, recreate the equivalent ggplot code.
qplot(price, carat, data = diamonds)
qplot(hwy, cty, data = mpg, geom = "jitter")
qplot(reorder(class, hwy), hwy, data = mpg, geom = c("jitter", "boxplot"))
qplot(log10(price), log10(carat), data = diamonds), colour = color) + geom_smooth(method = "lm")
Tuesday, 19 October 2010
ggplot(diamonds, aes(price, data)) + geom_smooth()
gglot(mpg, aes(hwy, cty)) + geom_jitter()
ggplot(mpg, aes(reorder(class, hwy), hwy)) + geom_jitter() + geom_boxplot()
ggplot(diamonds, aes(log10(price), log10(carat), colour = color)) + geom_point() + geom_smooth(method = "lm")
Tuesday, 19 October 2010
More geoms & stats
See http://had.co.nz/ggplot2 for complete list with helpful icons:
Geoms: (0d) point, (1d) line, path, (2d) boxplot, bar, tile, text, polygon
Stats: bin, summary, sum
Tuesday, 19 October 2010
Go back to the descriptions of “Minard’s march” and “Flight delays” that you created before. Start converting your textual description to ggplot2 code.
Your turn
Tuesday, 19 October 2010