We can begin to understand the point of this article by understand my reason to write it. As part of my responsibilities as a data analyst, I was tasked with finding the best Python data visualization library, for my team and other analytical groups. Our goal: to develop quickly and efficiently, utilizing a library that enabled customizations.
With a rein to select visualization libraries of interest, I began to research and document our needs and the requirements we had for libraries, from visualization capabilities, code complexity, and ease of customization, to versioning related issues.
After some introspection, my teammates and…