Long category values occur frequently in real world use cases.  This can happen with graphs for analysis of clinical research data, and also for graphs showing survey data where the question asked may be long (even a paragraph).  Managing such long categories on the x or y axis is always

A few days ago, I posted an article on displaying first N bars from a data set.  This is useful when the data is sorted by descending response, and only the first few values are significant.  There were a few interesting comments, including one that was regarding the treatment of

Often we have  a graph with many bars (or categories) on the x or y axis.  These categories may be sorted by descending response such as frequency of a % value.  An example with simulated data is shown below. title 'Actual Values by Name'; proc sgplot data=bars2 noborder; vbar name /

Recently, while reading up on Wilkinson and Cleveland Dot plots, I saw this excellent article by Xan Gregg on the topic.  I also saw some interesting examples of Lollipop Charts, kind of a dot plot with statistics along with a drop line, maybe more suitable for sparse data.  I thought

As many of the regular readers of this blog know, SGPLOT and GTL, provide extensive tools to build complex graphs by layering plot statements together.  These plots work with axes, legends and attribute maps to create graphs that can scale easily to different data. There are, however, many instances where

A Stem and Leaf plot is a visual that can help quickly visualize the distribution of the data.  This graph was particularly useful before the advent of modern statistical graphs including the Histogram and Box Plot.  One nice feature of the plot is it shows the actual values in the

A frequently requested statistical graph is the scatter plot by with discrete categories along with mean value for each category.  Searching for a "Scatter with Mean" will return a lot of requests for such a graph in SAS, Stata, R and other statistical software. Such a graph is very easy