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Slide1
Graphics
HRP223 – 2013
November 18, 2013
Copyright ©
1999-2013
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.Slide2
RobbinsCreating 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.Slide3
How I do graphicsExploratory stuffUse the quick and dirty graphics built into EGProduction quality graphics
Write SAS or R code to make better looking graphicsEdit in Adobe IllustratorSlide4
Visualization ToolsThis is a excellent book that covers how to visualize stuff using many tools (including R). It has a great introduction to Adobe Illustrator.Slide5
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 BerraSlide6
Fisher’s Plot Data Reported in Cleveland
Based on code written by Robert Allison at SAS
Institute
Year 1
Year 2Slide7
Scatter Plot for Correlations
All have r
2
= .67
Anscombe
1973, Graphs in Statistical AnalysisSlide8
Good Statistical GraphicsShow central tendency and variabilityDo not require the reader to think…Include no extra information
Avoids unnecessary inkHighlights they key pointsDirectly plots the conclusion/inference
Uses mnemonic colorsLabels categoriesIncludes the sample sizeSlide9
Bad ThingsFirst, I want to talk about bad graphics that I frequently see.3dExtra Ink
PieDonutsStacked graphicsSlide10
General3D graphicsDon’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.Slide11
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….Slide12
Ink-to-Information RatioHow much ink for seven numbers?
Based on
Soukup & Davidson, 2002 Visual Data MiningSlide13
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 worseIf you get a glossy handout with a 3D pie, assume someone is lying to you.Don’t use them. Slide14
Don’t Explode!This exploded 3D pie (brought to you by Excel) is nearly useless for judging amounts.Slide15
Forbidden Donut….Donut plots have the same problems as pies (if not worse) ….Slide16
ClevelandIf 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.Slide17
Stacking is BadCleveland also quantified the fact that people are bad at judging the relative height of stacked data.Slide18
Wow, a cinnamon roll plot!Good luck making rapid judgments using this stacked 3D pie.Slide19
Bar Chart ~ DefaultSlide20
How did I know that?Start using the sgplot documentation:
http://support.sas.com/documentation/cdl/en/grstatproc/64978/HTML/default/viewer.htm#n0yjdd910dh59zn1toodgupaj4v9.htm
… and/or get this: http://library.stanford.edu/bks24_id=45422Slide21
sgplot
documentation:
http://support.sas.com/documentation/cdl/en/grstatproc/64978/HTML/default/viewer.htm#n0yjdd910dh59zn1toodgupaj4v9.htmSlide22
Custom Axis
I prefer to have ticks beyond the largest valueSlide23
yaxis
stuff ;
The popular options are not listed first… Slide24
Ticks on Both Y Axes
Ticks on both axes may help guestimate the countsSlide25
Things in < > are optional argumentsSlide26
Data in Jail
The lines are on top so they look prominent. Can I lighten them?Slide27
OR
Things in < > are optional arguments
A variable name
A number
Optionally add other numbers
Optionally add a
/
and options for the reference line(s)Slide28Slide29
Line Attributes I wanted to adjust the line attributes so I will use / lineattrs=()
OR
Give a set of line options in ()
A style element with options
I wish I knew how that works…Slide30
Details in parentheses:Slide31
Gray is here…Slide32
Reference Lines
First draw
reference lines
then draw bars on top.Slide33
Reducing InkIn Tufte’s world less ink is good. I could remove the bar color but that is removing necessary ink for this style of plot. I can remove the black edges to the bars.Slide34
Second axis labels are goneSlide35Slide36
Put White Lines Over the BarsSlide37
Ut
oh…Slide38Slide39
Awful Design….
I specify a title and it does not show up in the plot.Slide40Slide41
I want to draw attention to
this.Slide42
Specify you want a different color group for each bar.
Specify the bar and outline colors.Slide43
Notice the blue.Slide44Slide45
Cleveland made Dot Plots Replace Bar ChartsSlide46
Adding an Offset to the y-axisSlide47
Adding Value LabelsSlide48
Show Frequency CountsSlide49
Label AttributesSlide50Slide51
You can easily specify that each value is its own color group.Slide52Slide53
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.Slide54
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.Slide55
Another WaySlide56
How did I do that?Slide57Slide58
Don’t put a legend on the plot, add a pop-up description tooltip for pages on the web and save the graphics template.Slide59
The Graphic TemplatePremade complex plot designs are stored in a graphic template. You can also save the graphic template for any plot you make.Add tmplout
= to the gplot statement.Slide60
The
Template
I gave it a name
Use the new template on the dataset.Slide61
With the title in the graphicSlide62
Another version of the same dataSlide63
Moderately Awful CodeBubble sizes are set by providing a radius… I force the area by setting the smallest and largest bubble size in centimeters.
I want to use this part of the plot for the legend so I name it.Slide64
9.3 How do I set the blue and pink?For grouped data you can specify the details for each plotted element in a style template:Slide65
What is wrong with this?
What is the point of this graphic?
How are the two sexes represented?What data is this?Slide66Slide67
Easy But Awful BoxplotsSlide68
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?Slide69
What is the point of this graphic?
How are the two sexes represented?
A Good BoxplotSlide70
What is the point of this graphic?
A Very Good BoxplotSlide71
Code for a Very Good Boxplot 9.4Slide72Slide73
Built in GraphicsMany Enterprise Guide analyses have built in diagnostic graphics. Slide74
When you test for the difference in the mean SAS gives you a great plot.Slide75
Avoid ThinkingPut 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.Slide76
Bivariate Comparisons with LinesPeople 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.Slide77
Plot TypesCategorical variablesDescriptiveBar charts
Dot plotsInferentialContinuous variables
HistogramBox plotViolin plotsQuantile and QQ plotsSlide78
Frequency PlotsEG for frequency plotsCustom codeSlide79
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.Slide80
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
FontsSlide81
Useful ods graphics optionsods 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 procedureSlide82Slide83
ODS Graphics Editor with EGIf 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.Slide84
Move code from EG to SASUse the query builder to put your data in a permanent SAS library (
not the work library).Right click on the graphic node which is run on data in a permanent library 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.Slide85
Move all your code to SASBecause 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.Slide86
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.Slide87Slide88
WYSIWYG EditingRight 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.Slide89
Right click on things to set properties. Colors, text details, fontsPoint and click annotationSymbols, arrows, text, circlesSlide90
WYSIWYG EditingWhile 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.Slide91
Bar ChartsThe 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?Slide92
SAS Bar ChartsSAS makes the reader do extra work by rotating the axis labels in ActiveX images. They pointlessly include variable labels by default.Slide93
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.Slide94
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.Slide95
The GUI is SolidMy 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.Slide96
.PNG formatActiveX image formatSlide97
Saving the Graphic for PublicationThe easiest way to get publication quality graphics is to set the output type to be RTF.Slide98
Default Output and GraphicsThe 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.Slide99Slide100
Types of ImagesThe default formats
of the images are determined by the ODS destinations you are using:LISTING:
pgn visible in the Windows Image Fax ViewerHTML: png, gif, jpg contained in web pages and visible in Internet Explorer, Firefox or OperaLATEX: 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 defaultSlide101
You can browse the ODS appearance templates from the
Style
Manager on the Tools menu.Slide102
ODS SGraphicsCompared 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.Slide103
Old vs. New ProceduresThe 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.Slide104
New Graphics Statistical Graphics Procs
proc
sgPlotgeneral plotting procedure that replaces gplotproc sgScatterlots of tools for scatterplots and scatter matricesproc sgPanel
quick and easy trellis/lattice/matrix/panel of plots
Proc
sgRender
used with proc template to make totally custom plots
It replaces proc
greplaySlide105
Plot TypesCategorical variablesBar chartsDot plots
Continuous variablesHistogramBox plot
Violin plotsQuantile and QQ plotsSlide106
Dot charts
Categorical variablesSlide107
Grouped Categorical VariablesTo 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 plotsMosaic plotsAssociation plots
Grouped categorical variablesSlide108
If you want to use RDownload R for Mac or PC cran.cnr.berkeley.edu/bin/
macosx/
cran.cnr.berkeley.edu/bin/windows/baseSlide109
How to learn RI usually teach R classes in the summer.www.stanford.edu/~balise
/ has links to my slide decks for R classes.Slide110
Plots for inferenceCategorical plotsConfidence limits on odds ratiosFour-fold plots
Expectancy plotsMosaic plotsSlide111
Fourfold PlotsThey 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 Slide112
More males were admitted than females.There is clear evidence of sexist policies in admissions!
Grouped categorical variablesSlide113
Department A admitted more females than males and every other department had no bias!The joy of Simpsons paradox.
Grouped categorical variablesSlide114
Mosaic PlotsSo 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 variablesSlide115
Some basic voodoo in R shows which combinations are over (in blue) or under represented (in red).
Grouped categorical variablesSlide116
I prefer the simpler association plots.
Grouped categorical variablesSlide117
Continuous OutcomesThe Distribution Analysis menu option can do basic plots.
Continuous variablesSlide118
The resolution of the histogram is okay but the others are unacceptable.Slide119
Use sgplot for high resolution plots.
Continuous variablesSlide120
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.Slide121
I want the title!Slide122
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
;Slide123
How is that made?title
"5209 Cholesterol Measures from Framingham Heart Study"
;proc sgplot
data
=
fram
tmplout
=
"c:\blah\
plate.sas
"
;
histogram
cholesterol;
density
cholesterol /
type
=
kernel
;
density
cholesterol /
type
=
normal
;
keylegend
/
location
=
inside
position
=
topright
across
=
1
;
run
;
Make a new graphics templateSlide124
proc template
;define
statgraph sgplotFram;begingraph
/;
EntryTitle
"5209 Cholesterol Measures from Framingham Heart Study"
/;
layout
overlay
;
Histogram
'
Cholesterol'n
/
primary
=true
binaxis
=false
LegendLabel
=
"Cholesterol"
;
DensityPlot
'
Cholesterol'n
/
Lineattrs
=
GraphFit
kernel
()
LegendLabel
=
"Kernel"
NAME
=
"DENSITY"
;
DensityPlot
'
Cholesterol'n
/
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
=
work.fram
template
=
template
=
sgplotFram
;
run
;
This was saved in
plate.sas
.
Render a graphic with the template and dataset specified.
Note I changed the name of this template.Slide125
How to set the color for a histogramSlide126
proc sgplot
data = fram; histogram
weight /
fillattrs
= (
color
= coral);
run
;Slide127
You can also tweak the style templateSlide128
Tweaking the Style Templateproc
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
;Slide129
vbar Versionproc
sgplot
data = fram;
vbar
weight /
group
= sex;
run
;Slide130
proc sgplot
data
= fram; vbar weight /
group
= sex;
xaxis
fitpolicy
=
thin
;
run
;Slide131
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
;Slide132
Customizing graphicsYou 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
templateSlide133
If you do not want to explain what Kernel density estimation is… remove the lines.Slide134
Finding the templateAdd 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.TemplateNameSlide135
Looking at a TemplateYou 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
);Slide136
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.Slide137
After adding proc template and commenting out the Kernel statements rerun the code.Slide138
Oops. Unknown key words…You can fix the color coding on the template code easily.Slide139
Fixed (permanently)All your subsequent plots will have no density line.Slide140
Continuous variablesSlide141
ViolinA violin plot mirrors the shape of the histogram (density). They can be done in R.
Continuous variablesSlide142
Grouped Continuous VariablesYou 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 variablesSlide143
Request distinct graphics by subgroups.
Grouped continuous variablesSlide144
Grouped continuous variablesSlide145
Actually this took a bit of voodoo.
Grouped continuous variablesSlide146
1
st
2nd
Grouped continuous variablesSlide147
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 variablesSlide148
Grouped continuous variablesSlide149
Grouped continuous variablesSlide150
I want to add in a reference line showing what is normal and put the categories in order.Slide151Slide152
Side by Side Violin Plots
Grouped continuous variablesSlide153
Paired Continuous VariablesPeople typically show paired data with scatterplots.EG generate them:
Grouped continuous variablesSlide154
Scatter Plot
Grouped continuous variablesSlide155
Jittered PlotSlide156
Jitter vs. SunflowersIn R you can also do sunflower plots.
Grouped continuous variablesSlide157
Ordinary Least Squares RegressionPeople typically plot a regression line to show a relationship between two continuous variables.
Grouped continuous variablesSlide158
Regression lineYou can easily add a regression line to the scatter plot.Slide159
proc
sgplot data =
fram
;
scatter
x
= height
y
= weight;
run
;
proc
sgplot
data
=
fram
;
reg
x
= height
y
= weight;
run
;Slide160
ods listing
sge = on style = statistical;
proc
sgplot
data
=
fram
;
reg
x
= height
y
= weight /
markerattrs
= (
color
= green)
lineattrs
= graphdata1 (
color
= lime);
run
;Slide161
ods
listing style
= statistical;
proc
sgplot
data
=
fram
;
reg
x
= height
y
= weight /
group
= sex ;
run
;Slide162
proc template
;
define style sexE;
parent
=
styles.Statistical
;
style
graphdata1 /
contrastColor
=pink
markersymbol
=
"star"
;
style
graphdata2 /
contrastColor
=blue
markersymbol
=
"plus"
;
end
;
run
;
ods
html
body
=
"C:\blah\stuff.html"
gpath
=
"c:\blah"
style
=
sexE
;
proc
sgplot
data
=
fram
;
scatter
x
= height
y
= weight /
group
= sex ;
reg
x
= height
y
= weight /
group
= sex ;
run
;
ods
html
close
;Slide163Slide164
BisquareFigure 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 variablesSlide165
Loess and SplinesLoess 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 variablesSlide166
Smooth = 25
Smooth = 50
Smooth = 99Slide167
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.Slide168
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.Slide169
Too Many GraphicsIf 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.Slide170
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.Slide171
Splitting a GridSome 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. Slide172
plots(
GlobalOptionsGoHere
). The global options apply to all graphics in this procedure.Slide173
Beyond the Basic Univariate plotsThere are 4 SG procedures that allow you to build up complex univariate plots and do multivariate (trellis/lattice) plots.Slide174
Statistical Graphics Procs
proc
sgPlotgeneral plotting procedure that replaces gplotProc sgRenderused with proc template to make totally custom plotsIt replaces proc greplayproc sgScatter
lots of tools for
scatterplots
and scatter matrices
proc
sgPanel
quick and easy trellis/lattice/matrix/panel of plotsSlide175
GridsYou can produce lattices full of graphics with proc gpanel.Slide176Slide177
Spaghetti Plots
Data from Singer and Willett: www.ats.ucla.edu/stat/examples/alda.htmSlide178
SGPlot vs TemplateYou 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.Slide179Slide180Slide181
layout gridded = ticks do not have to align
layout lattice = ticks must alignSlide182Slide183