Python Data Visualization Transcripts
Lecture: Pandas conclusion
0:00 So let's summarize where pandas fits in the data visualization ecosystem. From a pro's perspective it is your core data analysis tool,
0:09 so you'll be using it anyway and it's helpful to have one place to go and quickly analyze, manipulate your data and then visualize it.
0:18 It is also very customizable with matplot lib. So pretty much anything you can do with matplot lib you can do with pandas
0:26 And there are some specialized plotting types that are only available in pandas that can be useful for certain data analysis problems.
0:36 From a cons perspective, there are some concerns.
0:40 The visualizations that are created by default pandas are not interactive and there are better statistical
0:47 plotting tools out there, which we will cover. So where does that leave us with? How you should use pandas? Well,
0:54 my recommendation is use pandas for your basic exploratory analysis and then when you need to you can customize it with your underlying
1:02 matplot lib API only when it's needed. Finally, I recommend evaluating some of the other tools we're going to talk about for
1:09 more interactive or complex statistical analysis.