1 Graphics HRP223 – 2011 November 28, 2011 Copyright © 1999-2011 Leland Stanford Junior...

1

Graphics

HRP223 – 2011November 28, 2011

Copyright © 1999-2011 Leland Stanford Junior University. All rights reserved.Warning: This presentation is protected by copyright law and international treaties. Unauthorized reproduction of this presentation, or any portion of it, may result in severe civil and criminal penalties and will be prosecuted to maximum extent possible under the law.

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

How I do graphics

• Exploratory stuff– Use the quick and dirty graphics built into EG

• Production quality graphics– Write SAS or R code to make better looking

graphics– Edit in Adobe Illustrator

4

Visualization Tools

• This is a excellent book that covers how to visualize stuff using many tools (including R). It has a great introduction to Adobe Illustrator.

5

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 information.

• 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

6

Fisher’s Plot Data Reported in Cleveland

Based on code written by Robert Allison at SAS Institute

Year 1 Year 2

7

0

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10

15

0 5 10 15 200

5

10

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0 5 10 15 20

0

5

10

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0 5 10 15 200

5

10

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0 5 10 15 20

Scatter Plot for Correlations

All have r2 = .67Anscombe 1973, Graphs in Statistical Analysis

8

Bad Things

• First, I want to talk about bad graphics that I frequently see.– 3d– Pie– Donuts– Stacked graphics

9

General

• 3D graphics

– Don’t, Don’t, Don’tWhile 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.

10

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….

11

Example Bar ChartSerum Samples in Each Trimester

You can remove ink rather than adding .

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Ink-to-Information Ratio

• How much ink for seven numbers?

Based on Soukup & Davidson, 2002 Visual Data Mining

13

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.

14

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.

15

Don’t Explode!

• This exploded 3D pie (brought to you by Excel) is nearly useless for judging amounts.

Total

tweakedtwistedwrecked

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Forbidden Donut….

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

17

Stacking is Bad

• Cleveland also quantified the fact that people are bad at judging the relative height of stacked data.

18

Wow, a cinnamon roll plot!

• Good luck making rapid judgments using this stacked 3D pie.

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What is a good graphic?

• Don’t make your audience think unnecessarily!– The point of the graphic should stand out instantly.– Plot the quantity (inference) that you want people to

notice.• Show the central tendency and the variability.• Minimize the amount of ink on the page.• Be sure colorblind people can understand it.

– Use a black and white photocopier and make sure you can distinguish all groups.

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What is wrong with this?

Female Male125

130

135

140

145

150

155

160

165

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Weight in Framingham Dataset

What is the point that the reader should learn from this?

How is the variability represented?What are the error bars?Can you interpret a 1 SD error bars?

How many people are included?Ink to information … How many numbers are depicted?

Never contrast black on blue.

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What is the point of this graphic?

How are the two sexes represented?

What data is this?

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Lovely white space

What is the point?

How are the sexes represented?

How many people?

Where is the mean?

What data is this?

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Easy But Awful Boxplots

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How are the two sexes represented?

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Code for a Good Boxplot

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SAS's Framingham Heart Data


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When you test for the difference in the mean SAS gives you a great plot.

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Avoid Thinking

• Put 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.

31

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.

Based on: Robbins Creating More Effective Graphs, 2005

The distance between the two curves is the same at all points.

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Plot Types

• Univariate (one variable)– Categorical variables

• Bar charts• Dot plots• Waffle plots

– Continuous variables• Histogram• Box plot• Violin plots

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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?

34

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.

35

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.

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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.

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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.

38

.PNG format

ActiveX image format

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Saving the Graphic for Publication

• The easiest way to get publication quality graphics is to set the output type to be RTF.

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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.

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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

• RTF graphics are done at 300 dpi by default

43

What is ODS?

• The Output Delivery System (ODS) controls the type and appearance (aka the style) of SAS output.

Different appearance templates

Different output destinations/types.

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

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I Typically Use HTML

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.)

This is the appearance template. For optimal results use:Analysis: colorDefault : overdistinguishes symbols for color or B&WJournal or journal2, etc: black and whiteStatistical or statistical2, etc: color

Include image_dpi = 300 to set the resolution to be higher than the default 100 dots per inch. Try 300 for final images pasting into MS Office.

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ods graphics on;

• This turns on the ODS statistical graphics.• Behind the scenes this combines your data

with a pre-specified description of what to plot and the aesthetics of the appearance.

Your data

Graphtemplate

Styletemplate

What Where?

ColorsFonts

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Useful ods graphics options

• ods graphics on /

• ods graphics / reset;

• ods graphics off;

Width = 8inHeight = 11inImagefmt = jpgimagename = thingyimagefmt = staticmap ;

Make a series of graphics

called thingy1,

thingy2, etc.

If you set only width or height, it will use a 4:3 aspect ratio.

Reset the graphic counter back to 1

Use pop-up tooltips with

details.

If you want to disable ods graphics

for a procedure

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ODS SGraphics

• Compared to the competition, for the last 10 years SAS graphics have been between poor and pathetic.– Graphics procedures rendered with 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.

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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.

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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

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Plot Types

• Univariate (one variable)– Categorical variables

• Bar charts• Dot plots• Waffle plots

– Continuous variables• Histogram• Box plot• Violin plots• Quantile and QQ plots

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You can get an okay looking graphic using sgpanel.

Categorical variables

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


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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

http://cran.cnr.berkeley.edu/bin/macosx/



http://cran.cnr.berkeley.edu/bin/windows/base

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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.

www.perl.org/get.html • Tinn-R is a text editor that knows the R

language.sourceforge.net/projects/tinn-r/

http://www.perl.org/get.html

http://sourceforge.net/projects/tinn-r/



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R Help

• R help files are user hostile. To learn about the options for dotchart type:

?dotchart• Use: rseek.org

http://www.rseek.org/

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Browse

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

http://addictedtor.free.fr/graphiques/thumbs.php



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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.

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Waffle Plots (aka pixel plots)

• I have not found software to do them.

Image from: Visual language for Designers by Connie Malamed 2009.


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Continuous Outcomes

• The Distribution Analysis menu option can do basic plots.

Continuous variables

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

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Use sgplot for high resolution plots.


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Violin

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

05

01

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0


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Grouped Categorical Variables

• 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

Grouped categorical variables

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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.


45% male vs. 30% female admission

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More males were admitted than females.

There is clear evidence of sexist policies in admissions!

Row: Male

Co

l: A

dm

itte

d

Row: Female

Co

l: R

eje

cte

d

1198

557

1493

1278


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Department A admitted more females than males and every other department had no bias!

The joy of Simpsons paradox.

Sex: Male

Ad

mit

?:

Ye

s

Sex: Female

Ad

mit

?:

No

Department: A

512

89

313

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Sex: Male

Ad

mit

?:

Ye

s

Sex: Female

Ad

mit

?:

No

Department: B

353

17

207

8

Sex: Male

Ad

mit

?:

Ye

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Sex: Female

Ad

mit

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No

Department: C

120

202

205

391

Sex: Male

Ad

mit

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Ye

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Sex: Female

Ad

mit

?:

No

Department: D

138

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279

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Sex: Male

Ad

mit

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Ye

s

Sex: Female

Ad

mit

?:

No

Department: E

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94

138

299

Sex: Male

Ad

mit

?:

Ye

s

Sex: Female

Ad

mit

?:

No

Department: F

22

24

351

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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?


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Some basic voodoo in R shows which combinations are over (in blue) or under represented (in red).


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I prefer the simpler association plots.

Green Hazel Blue Brown

Blo

nd

Re

dB

row

nB

lack

Relation between hair and eye color


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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.

Grouped continuous variables

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Request distinct graphics by subgroups.


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Actually this took a bit of voodoo.


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1st

2nd


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Double click here.

Put details on the histogram tweaks here.

I use/tweak nrow ncol and endpoints often.endpoints = 2 to 10 by 0.5midpoints = 5.6 5.8 6.0 6.2 6.4


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Side by Side Violin Plots

A B C

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Scatter PlotGrouped continuous variables

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Jittered Plot

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Jitter vs. Sunflowers

In R you can also do sunflower plots.


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Ordinary Least Squares Regression

• People typically plot a regression line to show a relationship between two continuous variables.


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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.

0 1 2 3 4 5 6 7 8

V1

0

5

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15

20

V3

0 1 2 3 4 5 6 7 8

V1

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V3


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Loess and Splines

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

• Splines are curved lines that allow different amounts of stiffness to the curves.


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Smooth = 25Smooth = 50

Smooth = 99

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Tweaking Specialized Plots

• Most analysis procedures now have customized high resolution graphics. Most 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.


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Specifying the plot name is optional in proc freq.

Turn on editable

graphics with ods listing sge= on.

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Deviance Plot

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ODS Graphics Editor with EG

• 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.

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Move code from EG to SAS

1. Use the query builder to put your data in a permanent SAS library (not the work library).

2. Right click on the graphic node which is run on data in a permanent library and choose Open… Open Last Submitted Code.

3. Copy the code beginning with the SQL that makes the data.

4. Start SAS and paste the code into the program editor.

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Move all your code to SAS• Because the ODS graphics editor is not in EG

(yet), you can export the entire set of code for the project and then rerun it in SAS.

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ODS Graphics Editor with EG(2)

• After exporting all your EG project, open the code in SAS and add these lines at the top of the program:

ods rtf file = "c:\blah\somefile.rtf";ods listing sge = on;

• Then open the graphic of interest.

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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.

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

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WYSIWYG Editing

• While the Statistical graphics editor is a much needed improvement, it is incomplete. You can only use a few, style templates (for setting default colors and such) and you can not use custom style templates. This means that you can not do critical tasks like manually set the color for different values in scatter plots.

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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.

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• Usually you can use an ODS exclude statement or an ODS select statement to pick the correct things to print. Using the plots(only) = syntax is more efficient.

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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.

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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.

This shows the number of people at risk after 20, 40 etc days.

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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.

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plots(GlobalOptionsGoHere). The global options apply to all graphics in this procedure.

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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.

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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

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proc sgPlot

• Basic plots– 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 chartsFrom Heath 2007. SAS/Graph procedures for creating statistical graphics

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onLineDoc helps (some)

• onlineDoc for sgplot needs a LOT more hyperlinks and examples. Find these pages:

• The SGPLOT Procedure: Overview• The SGPLOT Procedure: Examples• The SGPLOT Procedure: Procedure Syntax

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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.

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How is that made?proc format library = work;

value $smoked"Non-smoker" = "None "missing = "Missing"other = "Not none"

;run;

data fram;set sashelp.heart;smokin = put(smoking_Status, $smoked.);

run;

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How is that made?

proc sgplot data = fram;histogram cholesterol;density cholesterol / type = kernal;density cholesterol / type = normal;keylegend /

location=inside position=topright across=1;run;

Layers of features are added to the graphic in the order listed.

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How is that made?

proc sgplot data = fram tmplout= "c:\blah\plate.sas";histogram cholesterol;density cholesterol / type = kernal;density cholesterol / type = normal;keylegend /

location=inside position=topright across=1;run;

The statistical graphics language template can be saved and studied.

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proc template;define statgraph sgplot;begingraph;layout overlay; Histogram Cholesterol / primary=true binaxis=false LegendLabel="Cholesterol"; ; DensityPlot Cholesterol / Lineattrs=GraphFit kernel() LegendLabel="Kernel" NAME="DENSITY"; ; DensityPlot Cholesterol / Lineattrs=GraphFit2 normal() LegendLabel="Normal" NAME="DENSITY1"; ; DiscreteLegend "DENSITY" "DENSITY1" / Location=Inside across=1 halign=right valign=top;endlayout;endgraph;end;run;

proc sgrender data = fram template = sgplot;run;

This was saved in plate.sas.

Render a graphic with the template and dataset specified.

Note the name of this template.

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

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Grids

• You can produce lattices full of graphics with proc gpanel.

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Spaghetti Plots

Data from Singer and Willett: www.ats.ucla.edu/stat/examples/alda.htm

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Customizing graphics

• You can tweak the graphics that ship with SAS by modifying their graph template or you can create truly custom graphics by making your own statistical graph template.

Your data

Graphtemplate

Styletemplate

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If you do not want to explain what Kernel density estimation is…

remove the lines.

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Finding the template

• Add before the procedure that draws the graphic add ods trace on; and include ods trace off; afterwards. This prints the names of all the templates used by the procedure in the log. product.procedure.Graphis.TemplateName

124

Looking at a Template

• You can ask proc template to display the template with the source statement:

proc template;source stat.ttest.graphics.summary2;

run;

• Remember to type this before you start editing:

ods path(prepend) work.template (update);

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Don’t Panic

This is a complete template except for the

proc template statement here and a run statement at the

bottom.

Copy this into an editor window and add proc

template.

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After adding proc template and commenting out the Kernel statements rerun the code.

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Oops. Unknown key words…

• You can fix the color coding on the template code easily.

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Fixed (permanently)

All your subsequent plots will have no density line.

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Details on that new template.

• You can ask SAS to list, into the log, all the locations where the graphics templates are stored by using the command ods path show:

Your new template is stored here.

The untouchable

original is here but it is “masked” by the 1st one.

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Want a temporary template?

• You can request that your templates go into work instead of SASUSER with the command:ods path (prepend) work.template (update);

• When you quit SAS the template will be deleted along with everything else in work.

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Note the dynamic variablesproc template;define statgraph Stat.Ttest.Graphics.Summary2; notes "Comparative histograms with normal/kernel densities and boxplots, (two-sample)"; dynamic _Y1 _Y2 _Y _VARNAME _XLAB _SHORTXLAB _CLASS1 _CLASS2 _CLASSNAME _LOGNORMAL _OBSVAR; BeginGraph; entrytitle "Distribution of " _VARNAME; layout lattice / rows=3 columns=1 columndatarange=unionall rowweights=(.4 .4 .2) shrinkfonts=true; columnaxes; columnaxis / display=(ticks tickvalues label) label=_XLAB shortlabel=_SHORTXLAB griddisplay=auto_on; endcolumnaxes; layout overlay / xaxisopts=(display=none); histogram _Y1 / binaxis=false primary=true; if ((NOT EXISTS(_LOGNORMAL)) AND (NOT(EXISTS(_PAIRED) AND EXISTS(_RATIO)))) densityplot _Y1 / normal () name="Normal" legendlabel="Normal" lineattrs= GRAPHFIT; endif; *densityplot _Y1 / kernel () name="Kernel" legendlabel="Kernel" lineattrs=GRAPHFIT2;

Dynamic variables allow the same template to work with lots of datasets

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dynamic

• You can see what things/variables are being passed to a template by a procedure by printing it in a title:

proc template;define statgraph Stat.Ttest.Graphics.Summary2; notes "Comparative histograms with normal/kernel densities and boxplots, (two-sample)"; dynamic _Y1 _Y2 _Y _VARNAME _XLAB _SHORTXLAB _CLASS1 _CLASS2 _CLASSNAME _LOGNORMAL _OBSVAR; BeginGraph; entrytitle "Does _Y1 exist? " eval(exists(_Y1)) " It is the value: " _Y1; entrytitle2 "Does _VARNAME exist? " eval(exists(_VARNAME)) " It is the value: " _VARNAME; *entrytitle "Distribution of " _VARNAME;

This resolves to 1 or 0 depending on if the variable is used.

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entrytitle "Does _Y1 exist? " eval(exists(_Y1)) " It is the value: " _Y1;

134

Setting dynamic Variables

• You can set the values of dynamic variables when you call them:

proc sgrender data = blah template= thing;dynamic _var1Label= 'Dude';

run;

135

SGPlot vs Template

• You can replicate everything done with proc sgplot using the template language but don’t reinvent the wheel if you don’t need to.

• You will want to use proc template to build custom graphics that use many panels.

• Proc sgplot uses statements that start like reg but template uses names like regressionplot. – Similar but not identical names… boo.

138

layout gridded = ticks do not have to alignlayout lattice = ticks must align

141

Styles

• You can also tweak the style (aesthetics/ appearance) of your graphics.

Your data

Styletemplate

Graphtemplate

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What styles?

You can use the GUI to look at the details of the styles or you can explore them with code:

proc template;source styles.statistical;

run;

• This template includes sections for:fonts IndexTitle

GraphFonts IndexProcNameTable SystemFooter

Header GraphColorsData GraphColor GraphBackground

GraphGridlines

143

Fonts SysTitleAndFooterContainer ListItem TwoColorRamp GraphMissing

GraphFonts TitleAndNoteContainer Paragraph TwoColorAltRamp GraphControlLImits

color_list TitlesAndFooters List ThreeColorRamp GraphRunText

Color BylineContainer List2 ThreeColorAltRamp GraphStars

GraphColors SystemTitle List3 GraphOutlier

Html SstemFooter Graph GraphFit—GraphFit2

Text PageNo GraphWalls GraphConfidence—2 GraphClipping

Container ExtendedPage GraphAxisLines GraphPrediction Layoutcontainer

Index Byline GrapGridLines GraphPredictionLiimits

Document Parskip GraphOutliens GraphError

Body Continued GraphBox

Frame ProcTitle GraphBorderLines GraphBoxMedian

Contents ProcTitleFixed GraphReference GraphBoxMean

Pages Output GraphTitleText GraphBoxWhisker

Date Table GraphFootnoteText GraphHistogram

BodyDate Batch GraphDataText GraphEllipse

IndexItem Note GraphLabelText BraphBand

ContentFolder noteBanner GraphValueText GraphContour

ByContentFolder UserText GraphUnicodeText GraphBlock

IndexProcName PrePge GraphBackground

ContentProcLabel NoteContentFixed GraphFloor GraphAltBlock

PagesProcLabel WarnBanner GraphLegendBackgrond GraphAnnoLine

IndexTitle WarnContentFxed GraphHeaderBackground GraphAnnotext

ContentsTitle ErrorBaner DropShadowStyle GraphAnnoShape

PagesTitle ErrorContentFixed GraphDataDefault GraphSelection

FatalBaner GraphData1—GraphData12 GraphConnectLine

There are a LOT of different parts of a template that can be tweaked.

144

Your Own Style Template

• You can customize a style template based on another:

proc template;define style myStyle;

parent = styles.Statistical;style graphdata1 from graphdata1/ color = colors('docbg'); style graphdata2 from graphdata1/ color = violet; style graphdata3 from graphdata1/ color = turquoise; style GraphFonts from GraphFonts /

'GraphDataFont' = ("<sans-serif>, <MTsans-serif>", 9pt); end;

run;

Make the graphic element match the background of

graphic (invisible camouflage)

Change the appearance of the font used for labeling data elements.

Use everything in the statistical template except

tweaks listed below.

145

To get a list of known colors

proc registry liststartat="COLORNAMES";

run;

146

About the colors

• You can pick colors by names or specifying details

12th item in grouped data

Contrast around 12th item in grouped data (typically

confidence bounds)

147

About those colors

• The weird color names are colors in RGB hexadecimal format prefixed with "cx"

• Go play at kuler.adobe.com/#create/fromacolor

http://kuler.adobe.com/#create/fromacolor

148

Using the style template

• Once the style is created you can apply it to an ODS destination (pipeline) with code like:

ods listing style= myStyle;* stuff goes here;ods listing close;

• or something like this:ods html style= myStyle;ods graphics on / width = 11in height = 11in; proc sgrender data=whatWhen template=blockplot1; run; ods html close;

149

How to set the color for a histogram

150

proc sgplot data = fram;histogram weight / fillattrs = (color = coral);

run;

151

You can also tweak the style template

152

Tweaking the Style Template

proc template;define style myStyle;

parent = styles.Statistical;style GraphDataDefault / color=coral;

end;run;

ods html style = myStyle;proc sgplot data = fram;

histogram weight ;run;ods html close;

153

vbar Version

proc sgplot data = fram;vbar weight / group = sex;

run;

154

proc sgplot data = fram;vbar weight / group = sex;xaxis fitpolicy = thin ;

run;

155

proc template;define style myStyle;parent = styles.Statistical;

style graphdata1 from graphdata1 / contrastColor=pink color = pink;

style graphdata2 from graphdata1 / contrastColor=blue color = blue;

end;run;

ods html style = myStyle;proc sgplot data = fram;

vbar weight / group = sex;xaxis fitpolicy = thin ;

run;ods html close;

156

What is the Current color?

proc template;source styles.default;

run;

kuler.adobe.com/#

157

Setting Colors … The Hard Wayproc template;

define statgraph TABLENAME;begingraph;

entrytitle '';layout overlay ;

histogram v / fillattrs = (color = black) outlineattrs =

(color=orange) ;endlayout;

endgraph;end;

run;proc sgrender data = blah template = TABLENAME; run;

158

Footnotes

• In the template use:entryfotnote halign=left textattrs=graphvaluetext "TEXT";

• or use the %modtmplt macrotitle;footnote "halign=left textattrs=graphvaluetext 'blah' ";%modtmplt(template=NAME, step=t, options titles noquotes)

• Use the template then delete temp version:%modtmplt(template= NAME, step=d)

Search online doc for modtmplt and look at this: http://support.sas.com/rnd/app/papers/modtmplt.pdf.

http://support.sas.com/rnd/app/papers/modtmplt.pdf

http://support.sas.com/rnd/app/papers/modtmplt.pdf

159

proc sgplot data = fram;scatter x = height y = weight;

run;

proc sgplot data = fram;reg x = height y =

weight;run;

160

ods listing sge = on style = statistical;

proc sgplot data = fram;reg x = height y = weight /

markerattrs = (color = green) lineattrs = graphdata1 (color = lime);

run;

161

ods listing style = statistical;

proc sgplot data = fram;reg x = height y = weight / group = sex ;

run;

162

proc template;define style sexE;parent = styles.Statistical;style graphdata1 /

contrastColor=pink markersymbol = "star";

style graphdata2 / contrastColor=blue markersymbol = "plus";

end;run;

ods listing sge = on style = sexE;

proc sgplot data = fram;scatter x = height y = weight / group = sex ;reg x = height y = weight / group = sex ;

run;

164

The syntax for proc template vs. proc sgplot

• The following slides marked with:

show the syntax that I have written into enhanced editor keyboard macros for sgplot and template.

• So, after downloading and installing the keyboard macros use the title on the following slides and it will auto-complete with useful syntax.

keyboard macro

165

proc template scatterproc template;


entrytitle '';layout overlay /

xaxisopts = (offsetmin=.05 offsetmax=.05 label=' ')yaxisopts = (offsetmin=.05 offsetmax=.05 label=' '

linearopts = (tickvaluesequence = (start = end =

increment = ) viewmin = ));scatterplot y = x = /

datalabel = LABELVARIABLEmarkerattrs = (symbol = circlefilled color =

black size = 3px);endlayout;

endgraph;end;

run;

proc sgrender data = template = TABLENAME;run;

Required

Instead of title statement

Based on code in Statistical Graphics in SAS by Warren F. Kuhfeld

For a single panel

keyboard macros

166

proc template;define statgraph classscatter;

begingraph;entrytitle 'Weight by Height';layout overlay /

xaxisopts = (offsetmin=.05 offsetmax=.05 label='Class Height')yaxisopts = (offsetmin=.05 offsetmax=.05 label='Class weight'

linearopts = (tickvaluesequence = (start = 50 end = 150

increment = 25) viewmin = 50));scatterplot y = weight x = height /

datalabel = namemarkerattrs = (symbol = circlefilled

color = black

size = 3px

);endlayout;

endgraph;end;

run;

proc sgrender data = sashelp.class template = classscatter;run;

Edge of plot to fist tick

Force to include the lower tick

Tick range to consider

167

proc sgplot scatterproc sgplot data = ;

title "";scatter y = x = / datalabel =

markerattrs = (symbol = circlefilled color = black size = 3px);xaxis offsetmin = .05 offsetmax = .05 label = "";yaxis offsetmin = .05 offsetmax = .05 label = "" values = ( to by );

run;

keyboard macros

168

Using proc sgplot scatterproc sgplot data = sashelp.class;

title "Weight by Height";scatter y = weight x = height / datalabel = name

markerattrs = (symbol=circlefilled color=black size =3px);regressionplot y = weight x = height xaxis offsetmin = .05 offsetmax = .05 label = "Height";yaxis offsetmin = .05 offsetmax = .05 label = "Weight" values = (50 to 150 by 25);

run;

169

Proc template regproc template;


entrytitle '';layout overlay;

scatterplot y = x = ;regressionplot y = x = / degree =

3;endlayout;

endgraph;end;

run;


keyboard macros

170

Proc sgplot regproc sgplot data = ;

title "";reg y = x = / datalabel =


run;

keyboard macros

171

Proc template loessproc template;



scatterplot y = x = ;loessplot y = x =;

endlayout;endgraph;

end;run;


keyboard macros

172

proc sgplot loessproc sgplot data = ;

title "";loess y = x = / datalabel =


run;

keyboard macros

173

proc loess proc loess global

ods graphics on;

* Locally optimal;proc loess data =;

model = ;run;

* Globally optimal fit;proc loess data= ;

model = / select = AICC(global);run;

keyboard macros

174

Proc template bsplineproc template;



scatterplot y = x = ;pbsplineplot y = x =;

endlayout;endgraph;

end;run;


keyboard macros

175

proc sgplot bsplineproc sgplot data = ;

title "";pbspline y = x = / datalabel =


run;

keyboard macros

176

proc transregFor model informaiton on bsplines

* Global optimum;proc transreg data =; model identity(OUTCOME) = pbspline(PREDICTOR);run;

* Local optimum;proc transreg data = ; model identity(OUTCOME) = pbspline(PREDICTOR / sbc lambda = 2 10000 range);run;

keyboard macros

177

Proc template reg groupproc template;



scatterplot y = x = / group =;regressionplot y = x = / group = degree = 3 name

="thingy";discretelegend = "thingy" / title = "";

endlayout;endgraph;

end;run;


keyboard macros

178

Proc sgplot reg groupproc sgplot data = ;

title "";reg y = x = / group =

datalabel = markerattrs = (symbol =

circlefilled color = black size = 3px);xaxis offsetmin = .05 offsetmax = .05 label = "";yaxis offsetmin = .05 offsetmax = .05 label = "" values = ( to by );

run;

keyboard macros

179

Proc template barchartproc template;



barchart y = x = / stat = mean /*freq pct sum */orient= horizontal;

endlayout;endgraph;

end;run;


180

proc sgplot hbarproc sgplot data = ;

title "";hbar GROUP / response = RESPONSE stat = mean /*freq mean sum */

numstd = 2 limitstat = /* clm stddev stderr */;

run;

181

proc template histogramproc template;



histogram VARIABLE / endlabels = true;

endlayout;endgraph;

end;run;


182

Proc sgplot histogram

proc sgplot data = ;title "";histogram VARIABLE;

run;

183

proc template densityproc template;



histogram VARIABLE / endlabels = true;densityplot VARIABLE / kernel(); /* normal() */

endlayout;endgraph;

end;run;


184

proc template fringeproc template;



histogram / endlabels = true;densityplot / kernel(); /* normal() */fringeplot ;

endlayout;endgraph;

end;run;


185

proc template boxplotproc template;



vbox y = x = / orient = horizontal;endlayout;

endgraph;end;

run;


186

proc sgplot boxplotproc sgplot data = noautolegend;

title "";boxplot OUTCOME / category = GROUP;

run;

187

proc template seriesproc template;



seriesplot y = OUTCOME x = DATEVAR / group = GROUPVAR name = 'thingy';

discretelegend 'thingy' / title = "SOMETHING";endlayout;

endgraph;end;

run;


188

proc template dotproc means data = noprint nway;

var OUTCOME;class THEGROUP;output out = tmp mean = OUTCOME lclm = lower uclm = upper;

run;proc template;

define statgraph dotplot;begingraph;

entrytitle '';layout overlay / yaxisopts = (type = discrete griddisplay = on reverse = true);

scatterplot y = THEGROUP x = OUTCOME / xerrorlower = lower xerrorupper = upper

markerattrs = (symbol = circlefilled) name = 'thingy'

legendlabel = "mean and 95% Confidence Limits";discretelegend 'thingy' / title = "whatever";

endlayout;endgraph;

end;run;

proc sgrender data = tmp template = dotplot; run;

189

proc template needleproc template;



needleplot y = x = ;endlayout;

endgraph;end;

run;


190

proc template stepproc template;



stepplot y = x = / display = (markers) markersize = (size = 3px);

endlayout;endgraph;

end;run;


191

proc template blockproc template;



blockplot x = DATE block = THEBLOCK / filltype=multicolor datatransparency=.3 valuevalign=top labelposition=top display=(fill values label) blockindex = IDNUMBER;

endlayout;endgraph;

end;run;


1 Graphics HRP223 – 2011 November 28, 2011 Copyright © 1999-2011 Leland Stanford Junior...

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Transcript of 1 Graphics HRP223 – 2011 November 28, 2011 Copyright © 1999-2011 Leland Stanford Junior...