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

N328 Visualizing Information Week 2 | Data Abstractions & Intro to Tableau Khairi Reda | redak@iu.edu School of Informa5cs & Compu5ng, IUPUI Last week Why use vision to analyze information? Seasonally adjusted unemployment rate in the


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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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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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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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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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This week

  • Intro to Tableau
  • Data type and seman;cs
  • Variable types: Categorical, Ordinal,

and Quan5ta5ve variables

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Assignment 1

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

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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

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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

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Terminology

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

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

  • A?ribute (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

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Attribute/Variable Types

✦Categorical (Nominal, Qualita;ve)

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

  • Quan;ta;ve

Meaningful magnitude Can do arithme5c

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Quan;ta;ve Data

Interval vs. Ra5o

✦ Interval

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

✦ Ra;o

  • 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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http://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

Cri;que 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