N328 Visualizing Information Week 2 | Data Abstractions & Intro - - PowerPoint PPT Presentation

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N328 Visualizing Information Week 2 | Data Abstractions & Intro - - PowerPoint PPT Presentation

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N328 Visualizing Information Week 2 | Data Abstractions & Intro to Tableau Khairi Reda | redak@iu.edu School of Informa5cs & Compu5ng, IUPUI Assignment 1 Due Monday 11:59pm in Canvas Submit a PDF file: Visualiza5on (picture) + Writeup

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N328 Visualizing Information

Khairi Reda | redak@iu.edu School of Informa5cs & Compu5ng, IUPUI

Week 2 | Data Abstractions & Intro to Tableau

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Assignment 1

Due Monday 11:59pm in Canvas Submit a PDF file: Visualiza5on (picture) + Writeup

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Last week

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Seasonally adjusted unemployment rate in the US Bureau of Labor Statistics

Why use vision to analyze information?

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Why use vision to analyze information?

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Use visualization for confirmation

  • Confirm an exis5ng hypotheses
  • A horse will have all of its 4

feet off the ground at some point while galloping Eadweard Muybridge

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Visualization can also do harm, though, if not done correctly

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Space Shuttle Challenger Disaster

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By E. Tufte

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0" 5" 10" 15" 20" 25" 30" 1978" 1979" 1980" 1981" 1982" 1983" 1984" 1985"

Miles"per"gallon"

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Based on reporting by the Guardian (https://www.theguardian.com/technology/blog/2008/jan/21/liesdamnliesandstevejobs) Via Miriah Meyer

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US smart phone marketshare

Slide by Miriah Meyer

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US smart phone marketshare

Slide by Miriah Meyer

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Via Andy Johnson (https://www.evl.uic.edu/aej/424/)

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Last week

Principles of Visual Integrity “The representa5on of numbers, as physically measured on the surface of the graphic itself, should be directly propor5onal to the numerical quan55es represented” Avoid chartjunk* and 3D charts

* Visual embellishment can in some cases improve memorability and engagement with the visualization

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Via Stephen Few https://www.perceptualedge.com/articles/visual_business_intelligence/the_chartjunk_debate.pdf

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This week

  • Modern visualizaEon tools
  • Tableau
  • Data type and semanEcs
  • Variable types: Categorical, Ordinal,

and Quan5ta5ve variables

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Quiz

Access code: vis02 Two ques5ons about this week’s reading materials Will be used to mark a\endance 10 minutes

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Data abstraction

semanEcs: the meaning behind the informa5on type: the fundamental informa5on type (e.g., number, date, string, etc…)

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Basil 7 S Pear

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Amy Basil Clara Desmond Fanny George Hector 1 2 3 4 5 6 7 8 7 6 8 7 6 10 M S M S L S M Apple Pear Peach Lychee Orange Pear Apple

ID Name Age Shirt Size Favorite Fruit

semantics (meta data)

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Terminology

  • Items: are individual units of informa5on. For example:

a rows in a table represen5ng one order out of many.

  • AGribute (variables, dimension): a property rela5ng to
  • items. E.g., the shipping cost of a par5cular order
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Via Miriah Meyer

Flat Tables

Key: Order ID

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Attribute/Variable Types

✦Categorical (Nominal, QualitaEve)

A finite set of categories No implicit ordering between categories

✦Ordered

  • Ordinal

Implicit ordering between categories/levels, but no clear magnitude difference. Can compare and determine greater/less than

  • QuanEtaEve

Meaningful magnitude Can do arithme5c

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QuanEtaEve Data

Interval vs. Ordinal

✦ Interval

  • Zero does not indicate an absence of detectable measurement
  • We can determine distance between measurement, but not propor5ons
  • Example: temperature, dates

✦ RaEo

  • The posi5on of zero indicates there is nothing of the measured en5ty
  • Can determine ra5o and propor5ons
  • Example: weight, age
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Quiz

What a\ribute/variable type (Categorical, Ordinal, Interval, or Ra5o) best fit the following measurements?

  • Speed
  • Facebook reac5ons (Like, Angry, Sad, etc…)
  • Car configura5ons (Compact, Mid-Sedan, SUV)
  • Product Name
  • IQ scores
  • College Majors
  • 50-meter race 5me

Based on a slide by Alex Lex

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Introduction to Tableau

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research.vis.ninja

Download IMDB Movies dataset:

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Design critique

http://tinyurl.com/6mu8h63

  • What is the visualiza5on

about?

  • What data is represented in

the visualiza5on? And how?

  • What are the interac5ons

used?

  • What ques5ons can we

answer with the visualiza5on?

  • Do you like the visualiza5on?
  • Are there any improvements

that can be made to the design?

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Next week

Visual Percep5on

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Required reading

in Canvas: files/Visual thinking for design

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Critiques

CriEque thread posted (each week by Tuesday 11:59pm)

  • URL to the visualiza5on
  • What the visualiza5on is about
  • Visual encoding: describe how the data is depict in the visualiza5on
  • What insights did you discover from looking at the visualiza5on?
  • Do you like the visualiza5on? Why? What would you do to improve it?

Comments due Sunday 11:59pm

  • Good comments: add addi5onal insights or cri5que points, answer

ques5ons, provide a relevant example, etc…

  • Saying “I agree” is not enough; you should explain why