data visualization

Data Visualization

Christian Stade-SchuldtProject-A Ventures

BI Team Knowledge Transfer

Outline

Motivation

Principles of Data Visualization

Types of Visualization

Summary

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Project-A, Data Visualization, 2015 2

Why visualizing data?

É Visualization lets you see things that would rather go unnoticedÉ Visualization gives answers fasterÉ Color pictures are pretty and fun to look atÉ Simple example: Anscombe’s Quartet

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Anscombe’s Quartet

I II III IVx y x y x y x y

10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.588.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76

13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.719.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84

11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.4714.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04

6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.254.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50

12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.567.0 4.82 7.0 7.26 7.0 6.42 8.0 7.915.0 5.68 5.10 4.74 5.0 5.73 8.0 6.89

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Anscombe’s Quartet II

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Edward Tufte

É Professor emeritus at YaleUniversity

É Pioneer in the field of datavisualization

É Notable works: The VisualDisplay of QuantitativeInformation

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Principles of graphical excellence andintegrity

1. Serve a purpose

2. Make large data sets coherent

3. Present many numbers in a small space

4. Don’t lie

5. Use clear labels to defeat ambuigity and graphical distortion

6. Show entire scales

7. Show in context

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Small multiples

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The Lie factor

Lie factor =Size of effect in graphic

Size of effect in data(1)

=5.3− 0.6

0.6/27.5− 18

18= 14.8 (2)

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Scale contorsions

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Scale contorsions and context

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Principle of data graphics

1. Above all else show the data

2. Maximize the data-ink ratio

3. Erase non-data-ink

4. Erase redundant data-ink

5. Revise and edit

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Data-Ink

É Data-ink the non-erasable ink used for the presentation of dataÉ If removed the graphic would lose the contentÉ Non-Data-Ink is accordingly the ink that does not transport the

informationÉ Data-ink ratio = (data ink)/(total ink used to print the graphic)É Chartjunk: unecessary to comprehend the information represented or

distractive

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Data-Ink-Ratio Example

Low Data-Ink-Ratio High Data-Ink-Ratio

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Chart types

The goodÉ Bar chartsÉ Line chartsÉ Scatter plotsÉ Boxplots

The badÉ Pie chartsÉ Area charts

The uglyÉ All 3d charts

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Bar charts

É Go-to graph for comparing accross categories, discrete data orcontinous data

É Proximity: Set white space width separating contiguous bars equal to50%-150% width of bars

É Fills: Avoid pattern lines, use soft but distinct colorsÉ Borders: AvoidÉ Tick marks: Do not overdo

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Bar charts

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Line chart

É Used for continous dataÉ Intervals should be equal in sizeÉ Values should only direct connect values in adjacent intervalsÉ Indicate missing data

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Line chart

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Scatter plots

É Great for correlation between two quantitave dimensions

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Pie chartsPie charts are the Aquaman of data visualization

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Pie charts

The same data represented as a column chart

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3d Pie charts

What is worse than a pie chart? Meet the 3d pie chart

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Maps

É provide specificinformationabout particularlocations

É provide generalinformationabout spatialpatterns

É can be used tocomparepatterns on twoor more maps

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Maps

Relevant xkcd

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Remember Color Blindness

Approximately 10% of males and 1% of females suffer color visiondeficiency

Original colors Perceived colors

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Summary

É Visualize your dataÉ Choose the right type for your visualizationÉ Aim for a high Data-Ink-Ratio

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For Further Reading I

Tufte, Edward RThe Visual Display of Quantitative Information.Graphics Press, 2001.

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data visualization

Data & Analytics

dataink data

discrete data

presentation of data

large data

visualizing data

data inktotal ink

redundant dataink

information dataink