Python Data Visualization Transcripts
Lecture: Seaborn summary
0:00 We'll wrap up the chapter on seaborn by talking about the pros and cons and where it fits into your data analysis stack.
0:07 From a pro's perspective, Seaborn has some really sophisticated analysis tools and it's very customizable
0:14 with a lot of different API's to suit your own needs. I find it very fast for exploratory analysis and at the end of the day it
0:23 does create some very visually appealing plots from a cons perspective plots are not interactive so
0:30 you can't click and drag and explore the individual output. Some of the customization can be difficult.
0:38 It can take some time to figure out how to do what you want to do when you start to stray outside of the Standard API
0:44 Where does that leave us for how Seaborn fits into our analysis
0:49 stack? Well, my recommendation is it is a great tool for sophisticated exploratory analysis I think you should take some time to master the API.
0:58 Use themes and some of the matplot lib concepts to customize your visualization when needed. And if you do need something that is truly interactive.
1:07 We'll talk about some of the other tools that you may want to jump into once you are done with initial analysis in seaborn.