My last blog post described three ways to add a smoothing spline to a scatter plot in SAS. I ended the post with a cautionary note: From a statistical point of view, the smoothing spline is less than ideal because the smoothing parameter must be chosen manually by the user.
Like many SAS programmers, I use the Statistical Graphics (SG) procedures to graph my data in SAS. To me, the SGPLOT and SGRENDER procedures are powerful, easy to use, and produce fabulous ODS graphics. I was therefore surprised when a SAS customer told me that he continues to use the
O Christmas tree, O Christmas tree, Last year a fractal made thee! O Christmas tree, O Christmas tree, A heat map can display thee! O tree of green, adorned with lights! A trunk of brown, the rest is white. O Christmas tree, O Christmas tree, A heat map can display
A heat map is a graphical representation of a matrix that uses colors to represent values in the matrix cells. Heat maps often reveal the structure of a matrix. There are three common applications of visualizing matrices with heat maps: Visualizing a correlation or covariance matrix reveals relationships between variables.
The mosaic plot is a graphical visualization of a frequency table. In a previous post, I showed how to use the FREQ procedure to create a mosaic plot. This article shows how to create a mosaic plot by using the MOSAICPARM statement in the graph template language (GTL). (The MOSAICPARM
Mosaic plots (Hartigan and Kleiner, 1981; Friendly, 1994, JASA) are used for exploratory data analysis of categorical data. Mosaic plots have been available for decades in SAS products such as JMP, SAS/INSIGHT, and SAS/IML Studio. However, not all SAS customers have access to these specialized products, so I am pleased
On Kaiser Fung's Junk Charts blog, he showed a bar chart that was "published by Teach for America, touting its diversity." Kaiser objected to the chart because the bar lengths did not accurately depict the proportions of the Teach for America corps members. The chart bothers me for another reason:
A common visualization is to compare characteristics of two groups. This article emphasizes two tips that will help make the comparison clear. First, consider graphing the differences between the groups. Second, in any plot that has a categorical axis, sort the categories by a meaningful quantity. This article is motivated
How old is your version of SAS software? The graph on the left shows the release dates for various releases of SAS software, beginning with SAS 8.0. The graph is based on a graph on Jiangtang Hu's blog that shows the major SAS releases. As this graph demonstrates, SAS software
The CLUSTER procedure in SAS/STAT software creates a dendrogram automatically. The black-and-white dendrogram is nice, but plain. A SAS customer wanted to know whether it is possible to add color to the dendrogram to emphasize certain clusters. For example, the plot at the left emphasizes a four-cluster scenario for clustering
Suppose that you have several data distributions that you want to compare. Questions you might ask include "Which variable has the largest spread?" and "Which variables exhibit skewness?" More generally, you might be interested in visualizing how the distribution of one variable differs from the distribution of other variables. The
At a recent conference, I talked with a SAS customer who told me that he was using an R package to create a three-panel visualization of a distribution. Unfortunately, he couldn't remember the name of the package, and he has not returned my e-mails, so the purpose of today's article
I've previously described how to overlay two or more density curves on a single plot. I've also written about how to use PROC SGPLOT to overlay custom curves on a graph. This article describes how to overlay a density curve on a histogram. For common distributions, you can overlay a
I recently showed someone a trick to create a graph, and he was extremely pleased to learn it. The trick is well known to many SAS users, but I hope that this article will introduce it to even more SAS users. At issue is how to use the SGPLOT procedure
Did you know that your ODS style might result in changing the color ramp for contour plots and heat maps? For example, the default style in SAS 9.3 is HTMLBlue. Let's create a contour plot in the HTML destination by running an example adapted from the documentation for the RSREG
It is easy to use the SGPLOT procedure in SAS to plot the graph of a well-behaved continuous function: just create a data set of the (x,y) values on some domain and use the SERIES statement to connect the points. However, to plot the graph of a discontinuous function correctly
A SAS user asked an interesting question on the SAS/GRAPH and ODS Graphics Support Forum. The question is: Does PROC SGPLOT support a way to display the slope of the regression line that is computed by the REG statement? Recall that the REG statement in PROC SGPLOT fits and displays
When a categorical variable has dozens or hundreds of categories, it is often impractical and undesirable to create a bar chart that shows the counts for all categories. Two alternatives are popular: Display only the Top 10 or Top 20 categories. As I showed last week, to do this in
Sometimes a categorical variable has many levels, but you are only interested in displaying the levels that occur most frequently. For example, if you are interested in the number of times that a song was purchased on iTunes during the past week, you probably don't want a bar chart with
It seemed like an easy task. A SAS user asked me how to use the SGPLOT procedure to create a bar chart where the vertical axis shows percentages instead of counts. I assumed that there was some simple option that would change the scale of the vertical axis from counts
What's in a name? As Shakespeare's Juliet said, "That which we call a rose / By any other name would smell as sweet." A similar statement holds true for the names of colors in SAS: "Rose" by any other name would look as red! SAS enables you to specify a
Sometimes a graph is more interpretable if you assign specific colors to categories. For example, if you are graphing the number of Olympic medals won by various countries at the 2012 London Olympics, you might want to assign the colors gold, silver, and bronze to represent first-, second-, and third-place
The New York Times has an excellent staff that produces visually interesting graphics for the general public. However, because their graphs need to be understood by all Times readers, the staff sometimes creates a complicated infographic when a simpler statistical graph would show the data in a clearer manner. A
With the US presidential election looming, all eyes are on the Electoral College. In the presidential election, each state gets as many votes in the Electoral College as it has representatives in both congressional houses. (The District of Columbia also gets three electors.) Because every state has two senators, it
Robert Allison posted a map that shows the average commute times for major US cities, along with the proportion of the commute that is attributed to traffic jams and other congestion. The data are from a CEOs for Cities report (Driven Apart, 2010, p. 45). Robert use SAS/GRAPH software to
The other day I was using PROC SGPLOT to create a box plot and I ran a program that was similar to the following: proc sgplot data=sashelp.cars; title "Box Plot: Category = Origin"; vbox Horsepower / category=origin; run; An hour or so later I had a need for another box
A comment to last week's article on "How to get data values out of ODS graphics" indicated that the technique would be useful for changing the title on an ODS graph "without messing around with GTL." You can certainly use the technique for that purpose, but if you want to
Many SAS procedures can produce ODS statistical graphics as naturally as they produce tables. Did you know that it is possible to obtain the numbers underlying an ODS statistical graph? This post shows how. Suppose that a SAS procedure creates a graph that displays a curve and that you want
When you are working with probability distributions (normal, Poisson, exponential, and so forth), there are four essential functions that a statistical programmer needs. As I've written before, for common univariate distributions, SAS provides the following functions: the PDF function, which returns the probability density at a given point the CDF
I've been working on a new book about Simulating Data with SAS. In researching the chapter on simulation of multivariate data, I've noticed that the probability density function (PDF) of multivariate distributions is often specified in a matrix form. Consequently, the multivariate density can usually be computed by using the
