Python Data Visualization Transcripts
Chapter: Welcome to the course
Lecture: Topic outline

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0:00 Here, the topics we'll cover in this course first, I'll talk about some basic visualization concepts that will help you get the most out of
0:09 each of the tools we talk about next. The first library will cover is matplotlib, which is the grandfather of many of the plotting libraries in python.
0:20 And spending time understanding it will help you greatly as you progress in your data visualization
0:26 capabilities. Pandas builds on top of matplotlib for using custom visualization on top
0:34 of the data frame that you're already using to analyze your data.
0:38 Seaborn is a very powerful tool for doing statistical analysis and visualization of your data.
0:46 Then we'll transition to some of the Javascript based frameworks like Altair and Plotly, which produces very visually appealing and interactive charts.
0:57 The final two sections will cover are related to building your own dashboards.
1:01 So, Streamlit is a tool for combining any of the visualization libraries that you've already used to add more interactivity.
1:10 And then at the end we'll talk through Plotly Dash framework,
1:13 which provides a tremendous amount of customization and flexibility for building your own interactive dashboards.

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