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The Glamour of Graphics
The shape of data
- Chart types
- How to choose a chart
- Visual metaphor
- Memorability vs. speed of comprehension
- Identifying your audience
- Data encoding process
- Grids, borders, lines
- Grids, borders, lines, and axes examples and exercises
- White space
- Charts in larger layouts
- Alignment, white space, and layout of multiple plots examples and exercises
- What is typography and why does it matter?
- Typographic hierarchy
- Font styles
- Good fonts and where to find them
- Using custom fonts in R examples and exercises
- ggtext examples and exercises
- Pairing fonts
- Typography beyond charts
- Color palettes
- Color examples and exercises
- Color models
- HCL color palettes in ggplot examples and exercises
- The color wheel
- Color and emotion
- The eyedropper tool and color inspiration
- Combining ggplot with a vector editor
- Resizing plots for export
- Finding inspiration
Data encoding process
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This lesson is called Data encoding process, part of the The Glamour of Graphics course. This lesson is called Data encoding process, part of the The Glamour of Graphics course.
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There's no right answer, just a chance to learn and practice!
Using the plastic pollution dataset, follow the data encoding process to design one or multiple charts. Try to think outside the box a bit and go beyond just a line or bar chart.