1. Graphics in EG and R HRP223 – 2009 November 16th, 2009
Copyright © Leland Stanford Junior University. All rights reserved.
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2. Robbins
Creating More Effective Graphics by Naomi Robbins is a wonderful book showing the right and wrong ways to visualize scientific data. Read it when you have an afternoon off. It is an ideal read on a transcontinental flight.

3. Why Do Data Visualization?
Well designed pictures will show you the details and the whole pattern in your data.
Numeric descriptions can easily hide important patterns.
Some patterns are hard to detect in tables.
Whenever data is reported over time or locations, you need art.
YOU CAN LEARN A LOT BY JUST LOOKING.
-Yogi Berra

4. Fisher’s Plot Data Reported in Cleveland
Year 1
Year 2
Based on code written by Robert Allison at SAS Institute

5. Scatter Plot for Correlations
Anscombe 1973, Graphs in Statistical Analysis
All have r2 = .67

6. Bad Things
First, I want to talk about bad graphics that I frequently see. 3d
Pie
Donuts
Stacked graphics

7. General 3D graphics Don’t, Don’t, Don’t
While the SAS implementation of 3D graphics is relatively good, don’t use 3D effects, unless you are measuring something in 3D. Even then, don’t.

8. Tufte is a God to many.
The empiricist in me is very nervous about the amount of pontificating in his books…
I want to have evidence-based advice.
His best advice is to put no extra ink on the page.
Think about the ink-to-information ratio.
Remove all chart junk.
Note: the irony of the chart junk on this slide….

9. You can remove ink rather than adding .
Example Bar Chart
Serum Samples in Each Trimester
You can remove ink rather than adding .

10. Ink-to-Information Ratio
How much ink for seven numbers?
Based on Soukup & Davidson, 2002 Visual Data Mining

11. Cleveland
If you want to know how to do scientific visualization, you must read William Cleveland’s work.
He attempted to quantify what makes a good graphic good.
His early work on graphics is one of the reasons why R/S-plus is taking over the statistical world.

12. Pie is bad.
Work by Cleveland (and experimental psychologists) suggests that:
people are bad at judging the relative magnitude of angles
if you twist the rotation of the pie you can cause people to systematically misjudge the size of the angles
a 3rd dimension makes judgment worse
If you get a glossy handout with a 3D pie, assume someone is lying to you.
Don’t use them.

13. Don’t Explode!
This exploded 3D pie (brought to you by Excel) is nearly useless for judging amounts.

14. Forbidden Donut….
Donut plots have the same problems as pies (if not worse) ….

15. Stacking is Bad
Cleveland also quantified the fact that people are bad at judging the relative height of stacked data.

16. Wow, a cinnamon roll plot!
Good luck making rapid judgments using this stacked 3D pie.

17. What is a good graphic? Don’t make your audience think unnecessarily!
Minimize the amount of ink on the page.
This needs to be studied.
Show the central tendency and the variability.
Plot the quantity (inference) that you want people to notice.
Be sure colorblind people can understand it.
Use a black and white photocopier and make sure you can distinguish all groups.

18. Avoid Thinking
But labels on the graphic directly instead of using a key.
If you want people to compare the difference between two lines, plot the difference, not the two lines.

19. Bivariate Comparisons with Lines
People are extremely bad at judging the distance between two curves. Never ask people to judge up and down (vertical) distances between curves.
The distance between the two curves is the same at all points.
Based on: Robbins Creating More Effective Graphs, 2005

20. Plot Types Univariate (one variable) Categorical variables
Bar charts
Dot plots
Waffle plots
Continuous variables
Histogram
Box plot
Violin plots

21. Bar Charts The ink-to-information ratio is lousy.
A one dimensional quantity is being “expanded” into two dimensions.
Doubling of the amount corresponds to how much of an increase in area?

22. SAS Bar Charts
SAS makes the reader do extra work by rotating the axis labels in ActiveX images.
They pointlessly include variable labels by default.

23. Notice you can Edit the data and apply filters.
How to do it?
Notice you can Edit the data and apply filters.
You can right click on variables and apply user-defined formats off the Properties dialog.

24. First create the format.
In the Data windowpane of the Bar Chart GUI, right click on the variable and change the format to the User Defined format you had created.

25. The GUI is Solid
My only complaints are that the rotate grouping values text does not work (position in this example) and the summary statistics do not show up when you request ActiveX images.

26. Saving the Graphic for Publication
The easiest way to get publication quality graphics is to set the output type to be RTF.

27. .PNG format
ActiveX image format

28. Default Output and Graphics
The default graphic format in EG is ActiveX. These images can be edited (even on the web) but they only display with Internet Explorer. I have set my graphics to display as ActiveX images. Tweak this with Tools> Options… > Graph.

29. Types of Images
The default formats of the images are determined by the ODS destinations you are using:
LISTING: pgn visible in the Windows Image Fax Viewer
HTML: png, gif, jpg contained in web pages and visible in Internet Explorer, Firefox or Opera
LATEX: PostScrpt, epsi, gif, jpeg, pgn are visible in GhostView
PCL or PS: contained in Postscript file are visible in GhostView
PDF: contained in pdf, which is visible with Adobe Reader
RTF: visible in MS Word

30. I Typically Use HTML
This is the appearance template. For optimal results use:
Analysis: color
Default : overdistinguishes symbols for color or B&W
Journal or journal2, etc: black and white
Statistical or statistical2, etc: color
Include image_dpi = 200 to set the resolution to be higher than the default 100 dots per inch. Try 200 for final images pasting into MS Office.
This says the images should show tooltips with extra statistical details when you hover the mouse over parts of the graphic. (I can’t image these.)

31. Useful ods graphics Options
After the ods graphics on statement, type a / then:
imagename = “fileName”
reset
resets the counter of images back to 0.
imagefmt = jpg
width = 4.5 in
height = 4.5 in
If you set only width or height, it will use a 4:3 aspect ratio.

32. Different appearance templates
What is ODS?
The Output Delivery System (ODS) controls the type and appearance of SAS output.
Different appearance templates
Different output destinations/types.

33. You can browse the ODS appearance templates from the Style Manager on the Tools menu.

34. ODS Graphics
Compared to the competition, for the last 10 years SAS graphics have been between poor and pathetic.
Graphics procedures that rendered okay quality, at best .
No “what you see is what you get” editing.
Many plots were nearly impossible to render.
Custom graphics required extensive programming.
SAS 9.x has attempted to solve this problem.

35. Old vs. New Procedures
The old (commonly used) graphics procedures were gchart, gplot.
Now most analysis procedures have built in high quality graphics that can be invoked with an ODS graphics on statement.
Early on in the class I told you to tweak the EG options to include “ODS graphics on” with every run.
There are also new “easy to use” statistical graphics (sg) procedures.

37. New Graphics Statistical Graphics Procs
proc sgPlot
general plotting procedure that replaces gplot
proc sgScatter
lots of tools for scatterplots and scatter matrices
proc sgPanel
quick and easy trellis/lattice/matrix/panel of plots
Proc sgRender
used with proc template to make totally custom plots
It replaces proc greplay

38. Plot Types Univariate (one variable) Categorical variables
Bar charts
Dot plots
Waffle plots
Continuous variables
Histogram
Box plot
Violin plots
Quantile and QQ plots

39. You can get an okay looking graphic using sgpanel.

40. I was able to get exactly the graphic I wanted using R.

41. If you want to use R
Download R for Mac or PC cran.cnr.berkeley.edu/bin/macosx/ cran.cnr.berkeley.edu/bin/windows/base

42. If you use a PC, also get PERL and Tinn-R
PERL is a text manipulation language that is used by a couple of key R packages. It ships with Mac OS X. PC users can get ActivePerl (what I use) or Strawberry Perl for Windows.
Tinn-R is a text editor that knows the R language.
sourceforge.net/projects/tinn-r/

43. R Help
R help files are user hostile. To learn about the options for dotchart type:
?dotchart
Use: rseek.org

44. Browse To see why people use R for graphics look here:
addictedtor.free.fr/graphiques/thumbs.php

45. Additional Libraries
If you see sample code that includes require() or library(), you will need to do a onetime download of the additional package. If you are using Vista, run R as the administrator (by right clicking on the R icon instead of just double clicking ) to install and update packages.

46. Waffle Plots
I have not found software to do them. I need to find their real name…
Image from: Visual language for Designers by Connie Malamed 2009.

47. Continuous Outcomes
The Distribution Analysis menu option can do basic plots.

48. The resolution of the histogram is okay but the others are unacceptable.

49. Use sgplot for high resolution plots.

51. Violin
A violin plot mirrors the shape of the histogram (density). They can be done in R.

52. Grouped Categorical Data
To graph categorical data in SAS you need to get Michael Friendly’s Visualizing Categorical Data. Unfortunately, his macros are copyrighted with the book… So I will show you the R versions.
Fourfold plots
Mosaic plots
Association plots

53. Fourfold Plots
They draw 4 slices of pie with the area corresponding to the number of people in each cell of a 2x2 table and they have confidence bands such that if the confidence bounds overlap on adjacent pie pieces, they are not statistically significantly different.

54. More males were admitted than females.
There is clear evidence of sexist policies in admissions!

55. Department A admitted more females than males and every other department had no bias!
The joy of Simpsons paradox.

56. Mosaic Plots
So you have an contingency table and you want to know if there is as an association. You do a chi-square test and it says there are associations between the rows and columns. What next?

57. Some basic voodoo in R shows which combinations are over (in blue) or under represented (in red).
values = c(5, 29, 14, 16, 15, 54, 14, 10, 20, 84, 17, 94, 68, 119, 26, 7);
values = matrix(values, nrow = 4, byrow=TRUE)
rownames(values) = c("Green", "Hazel", "Blue", "Brown")
colnames(values) = c("Black", "Brown", "Red", "Blond")
mosaicplot(values, shade = TRUE)

58. I prefer the simpler association plots.
values = c(5, 29, 14, 16, 15, 54, 14, 10, 20, 84, 17, 94, 68, 119, 26, 7);
values = matrix(values, nrow = 4, byrow=TRUE)
rownames(values) = c("Green", "Hazel", "Blue", "Brown")
colnames(values) = c("Black", "Brown", "Red", "Blond")
marg <- margin.table(values, c(1, 2))
assocplot(marg, main = "Relation between hair and eye color")

59. Grouped Continuous Variables
You can use the Distribution Analysis to get basic grouped plots.
For better looking plots you need to write sgplot and/or sgpanel code.

60. Request distinct graphics by subgroups.

62. Actually this took a bit of voodoo.

63. 2nd
1st

64. Put details on the histogram tweaks here.
Double click here.
I use/tweak nrow ncol and endpoints often.
endpoints = 2 to 10 by 0.5
midpoints =

67. Side by Side Violin Plots

68. Scatter Plot
# People in
household

69. Jittered Plot Notice the family is gone.
Take the values and add randuni()
Jittered Plot
# People in
household
Notice the family is gone.
They jittered off of the graphic.
Why bother

70. Jitter vs. Sunflowers
In R you can also do sunflower plots.

71. Ordinary Least Squares Regression
People typically plot a regression line to show a relationship between two continuous variables.

72. Bisquare
Figure out what is an odd value and then put a weight on it to devalue it. There are many robust regression algorithms around. R and S-Plus software have them well implemented.

73. Loess
This technique essentially creates a rolling window and gets a weighted average across the values visible inside the window.

78. Specialized Plots
Most analysis procedures now have customized high resolution graphics. Some are automatically produced if you type ods graphics on.
Proc Freq
I wanted a deviation plot for a 2x2 (or really any sized table) showing which cell is driving a significant chi-square. They only give you a plot for a one-way table.
The ORPlot is very nice.

79. Turn on editable graphics.
proc freq data = sashelp.heart;
tables smoking_status;
run;
proc format;
value $amount
"Non-smoker" = " Non-smoker"
"Light (1-5)" = " Light (1-5)"
"Moderate (6-15)" = " Moderate (6-15)"
"Heavy (16-25)" = " Heavy (16-25)"
"Very Heavy (> 25)" = "Very Heavy (> 25)" ;
ods listing sge = on;
ods graphics on;
proc freq data = sashelp.heart order = formatted;
format smoking_status $amount.;
tables smoking_status /chisq plots = deviationPlot;
ods graphics off;
Specifying the plot name is optional in proc freq.

80. Deviance Plot

81. ODS Graphics Editor
If you want to do extensive tweaking to a graphic, you can use the WYSIWYG ODS Graphics editor. Unfortunately it only works with ODS graphics procedures and you need to rerun the code in SAS to invoke it.
Right click on the graphic node and choose Open… Open Last Submitted Code.
Copy the code beginning with the SQL that makes the data.
Start SAS and paste the code into the program editor.

83. WYSIWYG Editing
Right click and/or double click to set properties for objects in the plot.
The tool is optimized for some of the ODS style templates but you can use custom colors.

84. Right click on things to set properties.
Colors, text details, fonts
Point and click annotation
Symbols, arrows, text, circles

87. Too Many Graphics
If the ods graphics on statement gives you too many graphics, you can specify which graphics you want by including code designed for the procedure. Typically it looks like this: plot(only) = (table names). This design is poorly implemented because you need to know where to put the plot statement and what the table names are. Does it go on the proc line (like phreg), the tables line (like proc freq), or some other line? Also the table names specified with a plot statement do not always match the ODS table names.

88. Usually you can use an ODS exclude statement or an ODS select statement to pick the correct things to print.

89. Proc phreg has a lot of new features but nothing major in the graphics
Proc phreg has a lot of new features but nothing major in the graphics. With phreg, if you specify ods graphics on you do not automatically get any plots. Here I request survival and cumulative hazard plots including the global confidence limits option (cl).
Once again the option names are not consistent with the table names.

90. Proc lifetest can show the number at risk but
the implementation is weak. It labels the groups with numbers even if the strata are character strings. You have to manually edit them and this affords ample opportunity for mistakes.
I don’t see a way to change the censoring symbol in the legend.

91. Splitting a Grid
Some procedures produce a grid of plots. You can get access to the individual plots by specifying plots(unpack). Then you can use plots(only)=tableName to get just the right parts.
ODS select or exclude statements will not work.

93. Beyond the Basic Univariate plots
There are 4 SG procedures that allow you to build up complex univariate plots and do multivariate (trellis/lattice) plots.

94. New Graphics Statistical Graphics Procs
proc sgPlot
general plotting procedure that replaces gplot
proc sgScatter
lots of tools for scatterplots and scatter matrices
proc sgPanel
quick and easy trellis/lattice/matrix/panel of plots
Proc sgRender
used with proc template to make totally custom plots
It replaces proc greplay

95. proc sgPlot Basic plots Fits curves and generates confidence bounds
scatter, series, band, needle
Fits curves and generates confidence bounds
loess, regression, penalized b-splines, ellipse
Distributions
boxplots, histograms, normal curves, kernel density
Categorization
dot plots, bar charts, line charts
From Heath SAS/Graph procedures for creating statistical graphics

96. As you add more requests to the plot, it resizes and shifts things to make room. It draws them in the order you request them. It reads the requests from the first listed to the bottom. Change the order if you want to have an item appear layered on top of, or behind, another thing.
Some colors are not set yet in the enhanced editor. Use the menu Tools>Options>Enhanced Editor… then click User Defined Keywords to add the coloring.

97. I want to add in a reference line showing what is normal and put the categories in order.

100. Grids
You can produce lattices full of graphics with proc gpanel.

102. Spaghetti Plots
Data from Singer and Willett: