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Hadley Wickham Stat405 Graphics for large data Thursday, 26 August 2010
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Hadley Wickham

Stat405Graphics for large data

Thursday, 26 August 2010

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Majoring in Stat

• Declare early (even if you’re not sure)

• Weekly lunches

• Summer opportunities (research & internships)

Thursday, 26 August 2010

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1. Leftovers from last lecture

2. The diamonds data

3. Histograms and bar charts

4. More boxplots and scatterplots

5. Homework

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reorder(class, hwy)

hwy

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pickup suv minivan 2seater midsize subcompact compactqplot(reorder(class, hwy), hwy, data = mpg, geom = "jitter")

# Remember: start withlibrary(ggplot2)

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reorder(class, hwy)

hwy

15

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25

30

35

40

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pickup suv minivan 2seater midsize subcompact compactqplot(reorder(class, hwy), hwy, data = mpg, geom = "boxplot")Thursday, 26 August 2010

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reorder(class, hwy)

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pickup suv minivan 2seater midsize subcompact compactqplot(reorder(class, hwy), hwy, data = mpg, geom = c("jitter", "boxplot"))Thursday, 26 August 2010

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Your turn

Read the help for reorder. Redraw the previous plots with class ordered by median hwy.

How would you put the jittered points on top of the boxplots?

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Diamonds

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Diamonds data

~54,000 round diamonds from http://www.diamondse.info/

Carat, colour, clarity, cut

Total depth, table, depth, width, height

Price

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z

table width

x

depth = z / diameter

table = table width / x * 100

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Recall

Write down five ways to inspect the diamonds dataset.

You have one minute!

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Your turn

Inspect the data and familiarise yourself with the variables. If you don’t know what they mean, look them up on wikipedia.

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Histogram & bar charts

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Histograms and barcharts

Used to display the distribution of a variable

Categorical variable → bar chart

Continuous variable → histogram

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Always experiment with the bin width!

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Examples# With only one variable, qplot guesses that# you want a bar chart or histogramqplot(cut, data = diamonds)

qplot(carat, data = diamonds)qplot(carat, data = diamonds, binwidth = 1)qplot(carat, data = diamonds, binwidth = 0.1)qplot(carat, data = diamonds, binwidth = 0.01)resolution(diamonds$carat)

last_plot() + xlim(0, 3)

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Examples# With only one variable, qplot guesses that# you want a bar chart or histogramqplot(cut, data = diamonds)

qplot(carat, data = diamonds)qplot(carat, data = diamonds, binwidth = 1)qplot(carat, data = diamonds, binwidth = 0.1)qplot(carat, data = diamonds, binwidth = 0.01)resolution(diamonds$carat)

last_plot() + xlim(0, 3)

Common ggplot2 technique: adding

together plot components

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qplot(table, data = diamonds, binwidth = 1)

# To zoom in on a plot region use xlim() and ylim()qplot(table, data = diamonds, binwidth = 1) + xlim(50, 70)qplot(table, data = diamonds, binwidth = 0.1) + xlim(50, 70)qplot(table, data = diamonds, binwidth = 0.1) + xlim(50, 70) + ylim(0, 50)

# Note that this type of zooming discards data outside of the plot regions# See coord_cartesian() for an alternative

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Additional variables

As with scatterplots can use aesthetics or faceting. Using aesthetics creates pretty, but ineffective, plots.

The following examples show the difference, when investigation the relationship between cut and depth.

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depth

count

0

1000

2000

3000

4000

56 58 60 62 64 66 68 70

qplot(depth, data = diamonds, binwidth = 0.2)Thursday, 26 August 2010

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depth

coun

t

0

1000

2000

3000

4000

56 58 60 62 64 66 68 70

cutFairGoodVery GoodPremiumIdeal

qplot(depth, data = diamonds, binwidth = 0.2, fill = cut) + xlim(55, 70)Thursday, 26 August 2010

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depth

coun

t

0

1000

2000

3000

4000

56 58 60 62 64 66 68 70

cutFairGoodVery GoodPremiumIdeal

qplot(depth, data = diamonds, binwidth = 0.2, fill = cut) + xlim(55, 70)

Fill is the aesthetic for fill colour

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depth

coun

t 0

500

1000

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2000

2500

0

500

1000

1500

2000

2500

Fair

Premium

56 58 60 62 64 66 68 70

Good

Ideal

56 58 60 62 64 66 68 70

Very Good

56 58 60 62 64 66 68 70qplot(depth, data = diamonds, binwidth = 0.2) + xlim(55, 70) + facet_wrap(~ cut)Thursday, 26 August 2010

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Your turn

Explore the distribution of price.

How does it vary with colour, or cut, and clarity?

Practice zooming in on regions of interest.

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Box and whisker plots

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Boxplots

Less information than a histogram, but take up much less space.

Already seen them used with discrete x values. Can also use with continuous x values, by specifying how we want the data grouped.

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qplot(table, price, data = diamonds)Thursday, 26 August 2010

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table

price

5000

10000

15000

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50 60 70 80 90

qplot(table, price, data = diamonds, geom = "boxplot")Thursday, 26 August 2010

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table

price

5000

10000

15000

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50 60 70 80 90qplot(table, price, data = diamonds, geom = "boxplot", group = round(table))

Thursday, 26 August 2010

Page 30: 02 Large

table

price

5000

10000

15000

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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

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50 60 70 80 90qplot(table, price, data = diamonds, geom = "boxplot", group = round(table))

One boxplot for each unique value of this aesthetic

Thursday, 26 August 2010

Page 31: 02 Large

Scatterplots

Thursday, 26 August 2010

Page 32: 02 Large

• Global patterns

• Local patterns

• Deviations

Interpreting a scatterplot

Thursday, 26 August 2010

Page 33: 02 Large

Thursday, 26 August 2010

Page 34: 02 Large

Strong linear relationship.A number of outliers.

Thursday, 26 August 2010

Page 35: 02 Large

Thursday, 26 August 2010

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Unusual striations. Two groups? Little relationship between table and price?

Thursday, 26 August 2010

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Thursday, 26 August 2010

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Curved (exponential?) relationship. Outliers mostly cheaper than expected.

Thursday, 26 August 2010

Page 39: 02 Large

qplot(carat, price, data = diamonds)

But what’s the problem with

all these plots?

Thursday, 26 August 2010

Page 40: 02 Large

qplot(carat, price, data = diamonds)

But what’s the problem with

all these plots?In pairs, brainstorm

solutions for 2 minutes.

Thursday, 26 August 2010

Page 41: 02 Large

Idea ggplot

Small points shape = I(".")

Transparency alpha = I(1/50)

Jittering geom = "jitter"

Smooth curve geom = "smooth"

2d bins geom = "bin2d" or geom = "hex"

Density contours geom = "density2d"

Thursday, 26 August 2010

Page 42: 02 Large

Practice doing these plots yourself.

Read the online documentation for each plot type: http://had.co.nz/ggplot2

Your turn

Thursday, 26 August 2010

Page 43: 02 Large

Homework

Practice your graphics/data exploration skills with the diamonds or mpg data.

Due in one week.

Make sure to read the grading rubric, and find a colour printer.

Thursday, 26 August 2010

Page 44: 02 Large

Asking questions

You have two minutes to write down as many questions as you can come up with that you might want to answer about the diamonds data.

Write your best question on a piece of paper and turn it in.

Thursday, 26 August 2010


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