Python Data Visualization Transcripts
Chapter: Welcome to the course
Lecture: Topic outline
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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
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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.
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And spending time understanding it will help you greatly as you progress in your data visualization
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capabilities. Pandas builds on top of matplotlib for using custom visualization on top
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of the data frame that you're already using to analyze your data.
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Seaborn is a very powerful tool for doing statistical analysis and visualization of your data.
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Then we'll transition to some of the Javascript based frameworks like Altair and Plotly, which produces very visually appealing and interactive charts.
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The final two sections will cover are related to building your own dashboards.
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So, Streamlit is a tool for combining any of the visualization libraries that you've already used to add more interactivity.
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And then at the end we'll talk through Plotly Dash framework,
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which provides a tremendous amount of customization and flexibility for building your own interactive dashboards.