As you saw in some of the examples in this course, there’s no getting around the fact that matplotlib can be a technical, syntax-heavy library. Creating a production-ready chart sometimes requires a half hour of Googling and combining a hodgepodge of lines in order to fine-tune a plot.
However, understanding how the interfaces interact is an investment that can pay off down the road. Taking the time to dissect code rather than resorting to the Stack Overflow “copy pasta” solution tends to be a smarter long-term solution. Sticking to the object-oriented approach can save hours of frustration when you want to take a plot from plain to a work of art.
Congratulations, you made it to the end of the course! Make it stick: Mentor AI will check what you’ve got down, help you build something with it, and find your #1 takeaway to share in the discussion.
Or go straight to the discussion section and share your #1 takeaway and how you’ll put your new skills to use.
lordchuffnel on Nov. 2, 2019
Thanks for the video.