Python Data Visualization Transcripts
Chapter: Visualization Concepts
Lecture: Aesthetics
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An important concept in data visualization is Aesthetics, Aesthetics describe every aspect of a graphical element on your visualization.
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A few common examples should make this clear. The actual position of an element on an XY. Axis is one aesthetic.
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Another common aesthetic is shape or size. To differentiate different elements. Color is a very important one that we'll talk about in
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future slide. The line width or line type can be useful in those types of charts where we have lines and as we apply aesthetics to the data,
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there's really only two types of data. So continuous data is data like time or weights or length or temperature,
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where there's a continuous range of values versus discrete data, such as count of, value of our dice, roll a yes or no answer.
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And in general most aesthetics can be used for continuous and discrete data, but shapes and lines usually work best for discrete data.
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We will use these concepts as we start to dive into each of the libraries that
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we're talking about because each library has a different way of mapping these aesthetics into your code.