Python Data Visualization Transcripts
Chapter: Visualization Concepts
0:00 An important concept in data visualization is Aesthetics, Aesthetics describe every aspect of a graphical element on your visualization.
0:10 A few common examples should make this clear. The actual position of an element on an XY. Axis is one aesthetic.
0:19 Another common aesthetic is shape or size. To differentiate different elements. Color is a very important one that we'll talk about in
0:28 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,
0:40 there's really only two types of data. So continuous data is data like time or weights or length or temperature,
0:48 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.
0:59 And in general most aesthetics can be used for continuous and discrete data, but shapes and lines usually work best for discrete data.
1:09 We will use these concepts as we start to dive into each of the libraries that
1:15 we're talking about because each library has a different way of mapping these aesthetics into your code.