1. 1 Graphics HRP223 – 2011 November 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. 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. 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. 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. 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. 6 Fisher’s Plot Data Reported in Cleveland Based on code written by Robert Allison at SAS Institute Year 1Year 2

7. 7 Scatter Plot for Correlations All have r 2 =.67Anscombe 1973, Graphs in Statistical Analysis

8. 8 Bad Things First, I want to talk about bad graphics that I frequently see. – 3d – Pie – Donuts – Stacked graphics

9. 9 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.

10. 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. 11 Example Bar Chart Serum Samples in Each Trimester You can remove ink rather than adding.

12. 12 Ink-to-Information Ratio How much ink for seven numbers? Based on Soukup & Davidson, 2002 Visual Data Mining

13. 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. 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 3 rd 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. 15 Don’t Explode! This exploded 3D pie (brought to you by Excel) is nearly useless for judging amounts.

16. 16 Forbidden Donut…. Donut plots have the same problems as pies (if not worse) ….

17. 17 Stacking is Bad Cleveland also quantified the fact that people are bad at judging the relative height of stacked data.

18. 18 Wow, a cinnamon roll plot! Good luck making rapid judgments using this stacked 3D pie.

19. 19 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.

20. 20 What is wrong with this? 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.

21. 21 What is wrong with this? What is the point of this graphic? How are the two sexes represented? What data is this?

22. 22

23. 23 What is wrong with this? Lovely white space What is the point? How are the sexes represented? How many people? Where is the mean? What data is this?

24. 24 Easy But Awful Boxplots

25. 25 What is the point of this graphic? How are the two sexes represented?

26. 26 Code for a Good Boxplot

27. 27 SAS's Framingham Heart Data What is the point of this graphic?

28. 28

29. 29 When you test for the difference in the mean SAS gives you a great plot.

30. 30 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. 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.

32. 32 Plot Types Categorical variables – Descriptive Bar charts Dot plots – Inferential Continuous variables – Histogram – Box plot – Violin plots – Quantile and QQ plots

33. 33 Frequency Plots EG for frequency plots Custom code

34. 34 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: color Default : overdistinguishes symbols for color or B&W Journal or journal2, etc: black and white Statistical 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.

35. 35 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 Graph template Style template What Where? Colors Fonts

36. 36 Useful ods graphics options ods graphics on / ods graphics / reset; ods graphics off; Width = 8in Height = 11in Imagefmt = jpg imagename = thingy imagefmt = 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

37. 37

38. 38 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.

39. 39 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.

40. 40 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.

41. 41 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.

42. 42

43. 43 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.

44. 44 Right click on things to set properties. – Colors, text details, fonts – Point and click annotation – Symbols, arrows, text, circles

45. 45 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.

46. 46 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?

47. 47 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.

48. 48 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.

49. 49 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.

50. 50 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.

51. 51.PNG format ActiveX image format

52. 52 Saving the Graphic for Publication The easiest way to get publication quality graphics is to set the output type to be RTF.

53. 53 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.

54. 54

55. 55 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

56. 56 You can browse the ODS appearance templates from the Style Manager on the Tools menu.

57. 57 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.

58. 58 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.

59. 59 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

60. 60 Plot Types Categorical variables – Bar charts – Dot plots Continuous variables – Histogram – Box plot – Violin plots – Quantile and QQ plots

61. 61 You can get an okay looking graphic using sgpanel. Categorical variables

62. 62 I was able to get exactly the graphic I wanted using R. Categorical variables

63. 63 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 cran.cnr.berkeley.edu/bin/macosx/ cran.cnr.berkeley.edu/bin/windows/base

64. 64 How to learn R I usually teach R classes in the summer. – www.stanford.edu/~balise/ has links to my slide decks for R classes. www.stanford.edu/~balise/ In 2013 I may return to teaching and do 223 in R.

65. 65 Plots for inference Categorical plots – Confidence limits on odds ratios – Four-fold plots – Expectancy plots – Mosaic plots

66. 66 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

67. 67 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. Grouped categorical variables 45% male vs. 30% female admission

68. 68 More males were admitted than females. There is clear evidence of sexist policies in admissions! Grouped categorical variables

69. 69 Department A admitted more females than males and every other department had no bias! The joy of Simpsons paradox. Grouped categorical variables

70. 70 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? Grouped categorical variables

71. 71 Some basic voodoo in R shows which combinations are over (in blue) or under represented (in red). Grouped categorical variables

72. 72 I prefer the simpler association plots. Grouped categorical variables

73. 73 Continuous Outcomes The Distribution Analysis menu option can do basic plots. Continuous variables

74. 74 The resolution of the histogram is okay but the others are unacceptable.

75. 75 Use sgplot for high resolution plots. Continuous variables

76. 76 Continuous variables

77. 77 Violin A violin plot mirrors the shape of the histogram (density). They can be done in R. Continuous variables

78. 78 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

79. 79 Request distinct graphics by subgroups. Grouped continuous variables

80. 80 Grouped continuous variables

81. 81 Actually this took a bit of voodoo. Grouped continuous variables

82. 82 1 st 2 nd Grouped continuous variables

83. 83 Double click here. Put details on the histogram tweaks here. I use/tweak nrow ncol and endpoints often. endpoints = 2 to 10 by 0.5 midpoints = 5.6 5.8 6.0 6.2 6.4 Grouped continuous variables

84. 84 Grouped continuous variables

85. 85 Grouped continuous variables

86. 86 Side by Side Violin Plots Grouped continuous variables

87. 87 Scatter Plot Grouped continuous variables

88. 88 Jittered Plot

89. 89 Jitter vs. Sunflowers In R you can also do sunflower plots. Grouped continuous variables

90. 90 Ordinary Least Squares Regression People typically plot a regression line to show a relationship between two continuous variables. Grouped continuous variables

91. 91 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. Grouped continuous variables

92. 92 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. Grouped continuous variables

93. 93 Smooth = 25 Smooth = 50 Smooth = 99

94. 94 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.

95. 95 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.

96. 96 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.

97. 97 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.

98. 98 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.

99. 99 plots(GlobalOptionsGoHere). The global options apply to all graphics in this procedure.

100. 100 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.

101. 101 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

102. 102 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 charts From Heath 2007. SAS/Graph procedures for creating statistical graphics

103. 103 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

104. 104 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.

105. 105 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;

106. 106 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.

107. 107 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.

108. 108 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.

109. 109 I want to add in a reference line showing what is normal and put the categories in order.

110. 110

111. 111

112. 112 Grids You can produce lattices full of graphics with proc gpanel.

113. 113

114. 114 Spaghetti Plots Data from Singer and Willett: www.ats.ucla.edu/stat/examples/alda.htm

115. 115 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 Graph template Style template

116. 116 If you do not want to explain what Kernel density estimation is… remove the lines.

117. 117 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

118. 118 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);

119. 119 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.

120. 120 After adding proc template and commenting out the Kernel statements rerun the code.

121. 121 Oops. Unknown key words… You can fix the color coding on the template code easily.

122. 122 Fixed (permanently) All your subsequent plots will have no density line.

123. 123 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 1 st one.

124. 124 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.

125. 125 Note the dynamic variables 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 "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

126. 126 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.

127. 127 entrytitle "Does _Y1 exist? " eval(exists(_Y1)) " It is the value: " _Y1;

128. 128 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;

129. 129 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.

130. 130

131. 131

132. 132 layout gridded = ticks do not have to align layout lattice = ticks must align

133. 133

134. 134

135. 135 Styles You can also tweak the style (aesthetics/ appearance) of your graphics. Your data Style template Graph template

136. 136 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: fontsIndexTitle GraphFontsIndexProcName TableSystemFooter HeaderGraphColors DataGraph ColorGraphBackground GraphGridlines

137. 137 FontsSysTitleAndFooterContainerListItemTwoColorRampGraphMissing GraphFontsTitleAndNoteContainerParagraphTwoColorAltRampGraphControlLImits color_listTitlesAndFootersListThreeColorRampGraphRunText ColorBylineContainerList2ThreeColorAltRampGraphStars GraphColorsSystemTitleList3GraphOutlier HtmlSstemFooterGraphGraphFit—GraphFit2 TextPageNoGraphWallsGraphConfidence—2GraphClipping ContainerExtendedPageGraphAxisLinesGraphPredictionLayoutcontainer IndexBylineGrapGridLinesGraphPredictionLiimits DocumentParskipGraphOutliensGraphError BodyContinuedGraphBox FrameProcTitleGraphBorderLinesGraphBoxMedian ContentsProcTitleFixedGraphReferenceGraphBoxMean PagesOutputGraphTitleTextGraphBoxWhisker DateTableGraphFootnoteTextGraphHistogram BodyDateBatchGraphDataTextGraphEllipse IndexItemNoteGraphLabelTextBraphBand ContentFoldernoteBannerGraphValueTextGraphContour ByContentFolderUserTextGraphUnicodeTextGraphBlock IndexProcNamePrePgeGraphBackground ContentProcLabelNoteContentFixedGraphFloorGraphAltBlock PagesProcLabelWarnBannerGraphLegendBackgrondGraphAnnoLine IndexTitleWarnContentFxedGraphHeaderBackgroundGraphAnnotext ContentsTitleErrorBanerDropShadowStyleGraphAnnoShape PagesTitleErrorContentFixedGraphDataDefaultGraphSelection FatalBanerGraphData1—GraphData12GraphConnectLine There are a LOT of different parts of a template that can be tweaked.

138. 138 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' = (", ", 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.

139. 139 To get a list of known colors proc registry list startat="COLORNAMES"; run;

140. 140 About the colors You can pick colors by names or specifying details 12 th item in grouped data Contrast around 12 th item in grouped data (typically confidence bounds)

141. 141 About those colors The weird color names are colors in RGB hexadecimal format prefixed with "cx" Go play at kuler.adobe.com/#create/fromacolor

142. 142 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;

143. 143 How to set the color for a histogram

144. 144 proc sgplot data = fram; histogram weight / fillattrs = (color = coral); run;

145. 145 You can also tweak the style template

146. 146 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;

147. 147 vbar Version proc sgplot data = fram; vbar weight / group = sex; run;

148. 148 proc sgplot data = fram; vbar weight / group = sex; xaxis fitpolicy = thin ; run;

149. 149 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;

150. 150 What is the Current color? proc template; source styles.default; run; kuler.adobe.com/#

151. 151 Setting Colors … The Hard Way proc 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;

152. 152 Footnotes In the template use: entryfotnote halign=left textattrs=graphvaluetext "TEXT"; or use the %modtmplt macro title; 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

153. 153 proc sgplot data = fram; scatter x = height y = weight; run; proc sgplot data = fram; reg x = height y = weight; run;

154. 154 ods listing sge = on style = statistical; proc sgplot data = fram; reg x = height y = weight / markerattrs = (color = green) lineattrs = graphdata1 (color = lime); run;

155. 155 ods listing style = statistical; proc sgplot data = fram; reg x = height y = weight / group = sex ; run;

156. 156 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;

157. 157

158. 158 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

159. 159 proc template scatter proc template; define statgraph TABLENAME; begingraph; 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 = LABELVARIABLE markerattrs = (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

160. 160 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 = name markerattrs = (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

161. 161 proc sgplot scatter proc 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

162. 162 Using proc sgplot scatter proc 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;

163. 163 Proc template reg proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; scatterplot y = x = ; regressionplot y = x = / degree = 3; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run; keyboard macros

164. 164 Proc sgplot reg proc sgplot data = ; title ""; reg 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

165. 165 Proc template loess proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; scatterplot y = x = ; loessplot y = x =; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run; keyboard macros

166. 166 proc sgplot loess proc sgplot data = ; title ""; loess 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

167. 167 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

168. 168 Proc template bspline proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; scatterplot y = x = ; pbsplineplot y = x =; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run; keyboard macros

169. 169 proc sgplot bspline proc sgplot data = ; title ""; pbspline 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

170. 170 proc transreg For 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

171. 171 Proc template reg group proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; scatterplot y = x = / group =; regressionplot y = x = / group = degree = 3 name ="thingy"; discretelegend = "thingy" / title = ""; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run; keyboard macros

172. 172 Proc sgplot reg group proc 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

173. 173 Proc template barchart proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; barchart y = x = / stat = mean /*freq pct sum */ orient= horizontal; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

174. 174 proc sgplot hbar proc sgplot data = ; title ""; hbar GROUP / response = RESPONSE stat = mean /*freq mean sum */ numstd = 2 limitstat = /* clm stddev stderr */; run;

175. 175 proc template histogram proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; histogram VARIABLE / endlabels = true; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

176. 176 Proc sgplot histogram proc sgplot data = ; title ""; histogram VARIABLE; run;

177. 177 proc template density proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; histogram VARIABLE / endlabels = true; densityplot VARIABLE / kernel(); /* normal() */ endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

178. 178 proc template fringe proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; histogram / endlabels = true; densityplot / kernel(); /* normal() */ fringeplot ; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

179. 179 proc template boxplot proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; vbox y = x = / orient = horizontal; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

180. 180 proc sgplot boxplot proc sgplot data = noautolegend; title ""; boxplot OUTCOME / category = GROUP; run;

181. 181 proc template series proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay ; seriesplot y = OUTCOME x = DATEVAR / group = GROUPVAR name = 'thingy'; discretelegend 'thingy' / title = "SOMETHING"; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

182. 182 proc template dot proc 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;

183. 183 proc template needle proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; needleplot y = x = ; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

184. 184 proc template step proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; stepplot y = x = / display = (markers) markersize = (size = 3px); endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;

185. 185 proc template block proc template; define statgraph TABLENAME; begingraph; entrytitle ''; layout overlay; blockplot x = DATE block = THEBLOCK / filltype=multicolor datatransparency=.3 valuevalign=top labelposition=top display=(fill values label) blockindex = IDNUMBER; endlayout; endgraph; end; run; proc sgrender data = template = TABLENAME; run;