350102: GenICT II 37 Visualization and Computer Graphics Lab Jacobs University Information visualization examples
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350102: GenICT II 37
Visualization and Computer Graphics LabJacobs University
Information visualization examples
350102: GenICT II 38
Visualization and Computer Graphics LabJacobs University
Information visualization examples
350102: GenICT II 39
Visualization and Computer Graphics LabJacobs University
Information visualization examples
350102: GenICT II 40
Visualization and Computer Graphics LabJacobs University
Information visualization examples
350102: GenICT II 41
Visualization and Computer Graphics LabJacobs University
Information visualization examples
350102: GenICT II 42
Visualization and Computer Graphics LabJacobs University
Information visualization examples
Visualization and Computer Graphics LabJacobs University
2.3 Visual encoding in Python
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Visualization and Computer Graphics LabJacobs University
Pygal
• Dynamic charting library for Python• http://pygal.org
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Visualization and Computer Graphics LabJacobs University
Line Charts
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Visualization and Computer Graphics LabJacobs University
Line Charts
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Visualization and Computer Graphics LabJacobs University
Stacked Line Chart
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Visualization and Computer Graphics LabJacobs University
Bar Charts
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Visualization and Computer Graphics LabJacobs University
Pyramid Charts
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Visualization and Computer Graphics LabJacobs University
Pyramid Charts
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Visualization and Computer Graphics LabJacobs University
Dot Charts
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Visualization and Computer Graphics LabJacobs University
Boxplots
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Visualization and Computer Graphics LabJacobs University
Pie Charts
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Visualization and Computer Graphics LabJacobs University
Scatterplots
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Visualization and Computer Graphics LabJacobs University
Radar Charts
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Visualization and Computer Graphics LabJacobs University
World Maps
Visualization and Computer Graphics LabJacobs University
3. Visualization Principles and Best Practices
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Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
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Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
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Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 61
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
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Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
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Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 64
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 65
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 66
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 67
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 68
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 69
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 70
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 71
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
350102: GenICT II 72
Visualization and Computer Graphics LabJacobs University
Good and bad visualizations
Visualization and Computer Graphics LabJacobs University
4. Visual encoding
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Visualization and Computer Graphics LabJacobs University
Visual encoding
• We have seen that attributes may have different characteristics (numerical, ordered, categorical).
• Special attributes are time (temporal dimension) and geographical location (spatial dimensions) in case of spatiotemporal data.
• Entities are typically visually encoded by some kind of glyph.
• Glyphs vary with respect to position, size, shape, orientation, color, and texture.
• Visual encoding is the mapping of attributes of the entity to specifics of the glyph.
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Visualization and Computer Graphics LabJacobs University
Visual encoding
• The exact visual encoding of a data set depends on the number and characteristics of the available attributes and on the analysis tasks of the given application.
• Interaction mechanisms allow for switching between different attributes to allow for different views on the attributes and to fulfill different tasks.
• Still, there are guidelines for mapping attributes to visual cues.
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Visualization and Computer Graphics LabJacobs University
Visual cues
color
shapetexture
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Visualization and Computer Graphics LabJacobs University
Guidelines• location
• size
• color
• orientation
• texture
• shape
• geospatial
• time
• numerical (continuous)
• numerical (discrete)
• ordered
• categorical
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Visualization and Computer Graphics LabJacobs University
Perception
• One needs to consider that certain visual cues are more perceptionally relevant than others.
• Color is a pre-attentive feature that can be seen immediately.
• Location and size are also easy to perceive.• Shape is more difficult to distinguish.• Orientation and texture do not allow for detecting
subtle changes easily.
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