In the spirit of adapting the established tools to new challenges, the last chapter saw us finding ways to work around the limitations of matplotlib on a single workstation. In this chapter, we will explore ways around some of the other limitations that matplotlib users may run up against when working on problems with very large datasets. Note that this investigation will often cause us to bump up against the topic of clustering. We will be setting these explorations aside for now though. Lest you feel that a critical aspect of the problem domain is being ignored, take heart—this will be the primary focus of the next chapter.

The material in the final two chapters of this book attempt to provide the reader with enough additional context to easily understand the origins of these technologies and their uses and thus apply them to their own computation, analysis, and ultimately their plotting needs.

There are two major areas of the problem domain that we will...