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Data Viz Language, Perception, and in Practice 2018-07-28 leoluyi@iii Slides https://leoluyi.pse.is/iiiviz © leoluyi, 2018 1

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We'll discuss about... 4 What's a good viz? 4 A brief history of data viz. 4 Real world implementation 4 Get better with a simple framework © leoluyi, 2018 2

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橕ෝ౯ 4 㸎瓽 Leo Lu 4 Management + Psychology 4 CRM for Financial Service 4 Build data products 4 ETL 4 Models 4 Text mining 4 Viz 4 ... © leoluyi, 2018 3

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It's all about data Charts, graphs, maps, diagrams, ... © leoluyi, 2018 4

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Speak the language © leoluyi, 2018 5

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Trends driving the need of visual thinking 1. Massive increase of visualization 2. Data 3. Everybody’s doing it © leoluyi, 2018 6

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Past and Present © leoluyi, 2018 7

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Brief history of dataviz 4 (1960) Bertin: Visual variables 4 (1970) Tukey: Exploratory Viz 4 (1980) Tufte: Design principles for information (Chartjunk) 4 (1980) Cleveland & McGill: Graphic perceptions 4 (2000) Computer-driven, Design-driven 4 (2010) Easy-to-use apps 4 (Now) Interactivity, dynamic update © leoluyi, 2018 8

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Perceptions in psychology © leoluyi, 2018 9

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Perceptual tasks1 1 In several experiments, Cleveland and McGill (1984) identified “elementary perceptual tasks”: the most basic tasks they believe viewers perform when evaluating a visualization. © leoluyi, 2018 10

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Color © leoluyi, 2018 11

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Color over shape © leoluyi, 2018 12

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Reading texts © leoluyi, 2018 13

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Reading charts - We don’t go in order © leoluyi, 2018 14

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And more other else 4 People see first what stands out. 4 People see only a few things at once. 4 People seek meaning and make connections. 4 People rely on conventions and metaphors. 4 ... © leoluyi, 2018 15

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A good chart? © leoluyi, 2018 16

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© leoluyi, 2018 17

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Viz works in the real world ܉虋苭玕瞤犋螂聲樿ጱӞݙ扖 © leoluyi, 2018 18

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Data Management Will you change your data? (eg. changing one or all values or adding rows or columns) © leoluyi, 2018 19

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ETL "You can't do viz without those data skills!" ➔ Autonomy? DataOps © leoluyi, 2018 20

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ፓጱ究ਧಋྦྷ 4 Analysis vs. Presentation 4 R, Python <-> D3.js, Illustrator 4 Chart typologies vs. innovative outside-of-the-box charts 4 Excel <-> D3.js 4 Interactivity vs. static 4 PowerBI <-> PowerPoint © leoluyi, 2018 21

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There Are No Perfect Tools Just Good Tools for People with Certain Mindsets © leoluyi, 2018 22

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Get better with a simple framework © leoluyi, 2018 23

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Viz Quadrant 1. Conceptual (Idea-Driven) vs. Data-Driven 4 Do I have ideas or data? 2. Declarative vs. Exploratory 4 Show what vs. Show why Berinato (2016). Good Charts 24

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Conceptual © leoluyi, 2018 25

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Data-Driven © leoluyi, 2018 26

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Berinato (2016). Good Charts 27

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Other Tips © leoluyi, 2018 28

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Ask and Listen 4 Talk to your stakeholders 4 Keep records of words, phrases, and statements © leoluyi, 2018 29

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Prototypes © leoluyi, 2018 30

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Recap - Make dataviz smoother 4 Sharpen your viz thinking 4 Principles 4 Process 4 Data management 4 Availability 4 Cooperate with data engineer, data scientist 4 Familiar with your tools © leoluyi, 2018 31

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൉㺔膏Ի窕 㸎瓽 leoluyi@github https://leoluyi.github.io © leoluyi, 2018 32