Python Data Visualization Transcripts
Chapter: Course Conclusion
Lecture: Data vis concepts
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Next we started talking about core data visualization concepts such as aesthetics,
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Aesthetics are the different ways that you can present information in a visualization using the position shape, size, different colors,
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different line widths and line types. We also talked about the main types of data.
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So we have quantitative data or numerical data which shows us quantities of things.
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We also have qualitative data which is categorical data and shows things like observed qualities in this example hair color of red.
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Then we talked about how you can combine all these to do exploratory versus explanatory analysis
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Exploratory analysis is the quick iterative analysis you need to do when you're trying to
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understand a problem and then explanatory analysis is where you need to refine that visualization and
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present it to others to tell a story or explain a situation.