Summary
You have successfully learned the techniques for visualizing multivariate data in 2D and 3D forms. Although most examples in this chapter revolved around the topic of stock trading, the data processing and visualization methods can be applied readily to other fields as well. In particular, the divide-and-conquer approach used to visualize multivariate data in facets is extremely useful in the scientific field.
We didn't go into too much detail of the 3D plotting capability of Matplotlib, as it is yet to be polished. For simple 3D plots, Matplotlib already suffices. The learning curve can be reduced if we use the same package for both 2D and 3D plots. You are advised to take a look at MayaVi2, Plotly, and VisPy if you require more powerful 3D plotting functions.
