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Data at Work : best practices for creating effective charts and information graphics in Microsoft Excel / Jorge Camões.

By: Camões, Jorge.
Publisher: San Francisco : New Riders, 2016Description: xxii, 426 p. : col. ill ; 23 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 0134268636 (pbk.) ; 9780134268637 (pbk.) .Subject(s): Microsoft Excel (Computer file) | Business -- Computer programs | Electronic spreadsheetsDDC classification: 650.0285554 CAM Online resources: Table of contents
Contents:
1.The Building Blocks of Data Visualization Spatial Organization of Stimuli Seeing Abstract Concepts Charts Networks Maps Volume: Figurative Visualizations Visualization in Excel Retinal Variables From Concepts to Charts The Proto-Chart Chart Effectiveness Takeaways 2.Visual Perception Perception and Cognition Cognitive Offloading A False Dichotomy Charts and Tables Eye Physiology The Retina Cones The Arc of Visual Acuity Saccades Impact of Eye Physiology on Visualization Pre-Attentive Processing Salience Impact of Pre-Attentive Processing and Salience on Visualization Working Memory Impact of Working Memory on Visualization Gestalt Laws Law of Proximity Law of Similarity Law of Segregation Law of Connectivity Law of Common Fate Law of Closure Law of Figure/​Ground Law of Continuity Impact of Gestalt Laws on Visualization Contents note continued: The Limits of Perception Why We Need Grid Lines and Reference Lines: Weber's Law Being Aware of Distortions: Stevens' Power Law Context and Optical Illusions Impact of the Limits of Perception on Visualization 3.Beyond Visual Perception Social Pragnanz Breaking the Rules The Tragedy of the Commons Color Symbolism Representing Time Axis Folding Don't Make Me Think! Literacy and Experience Graphic Literacy Familiarity with the Subject Information Asymmetry Organizational Contexts Wrong Messages from the Top Impression Management 4.Data Preparation Problems with the Data Structure without Content Content without Structure What Does "Well-Structured Data" Mean, Anyway? A Helping Hand: Pivot Tables Extracting the Data The PDF Plague "Can It Export to Excel?" Cleansing Data Transforming Data Loading the Data Table Data Management in Excel Contents note continued: Organizing the Workbook Links Outside of Excel Formulas Cycles of Production and Analysis 5.Data Visualization From Patterns to Points Shape Visualization Point Visualization Outlier Visualization Data Visualization Tasks The Construction of Knowledge Data Information Knowledge Wisdom Defining Data Visualization Languages, Stories, and Landscapes Graphical Literacy Graphical Landscapes Profiling Dashboards Infographics A Crossroad of Knowledge Statistics Design Applications Content and Context Data Visualization in Excel The Good The Bad The Ugly Beyond the Excel Chart Library Don't Make Excel Charts 6.Data Discovery, Analysis, and Communication Where to Start? The Visual Information-Seeking Mantra Focus plus Context Asking Questions A Classification of Questions Selecting and Collecting the Data Contents note continued: Searching for Patterns Setting Priorities Reporting Results Clarification The Human Dimension The Design Project: Monthly Births Defining the Problem Collecting the Data Assessing Data Availability Assessing Data Quality Adjusting the Data Exploring the Data Embracing Seasonality Communicating Our Findings 7.How to Choose a Chart Task-Based Chart Classification Audience Profile Sharing Visualizations Screens and Projectors Smartphones and Vertical Displays PDF Files Excel Files Sharing Online 8.A Sense of Order The Bar Chart Vertical and Horizontal Bars Color Coding Ordering Chart Size Breaks in the Scale Changing Metrics to Avoid Breaks in the Scale Evolution and Change A Special Bar Chart: The Population Pyramid Dot Plots Slope Charts Strip Plots Speedometers Bullet Charts Alerts Contents note continued: 9.Parts of a Whole: Composition Charts What Is Composition? Composition or Comparison? Pie Charts Critique Damage Control Donut Charts Donuts as Multi-Level Pies Actual Hierarchical Charts: Sunburst Charts and Treemaps Stacked Bar Chart Pareto Chart 10.Scattered Data The Data Distribution Showing Everything: Transparencies and Jittering Quantifying Impressions Mean and Standard Deviation The Median and the Interquartile Range Outliers Box-and-Whisker Plots Z-Scores The Pareto Chart Revisited Excel Maps Histograms Bin Number and Width Histograms and Bar Charts Cumulative Frequency Distribution 11.Change Over Time Focus on the Flow: The Line Chart Scales and Aspect Ratios Focus on the Relationships: Connected Scatter Plots Sudden Changes: The Step Chart Seasonality: The Cycle Plot Sparklines Animation Contents note continued: 12.Relationships Understanding Relationships Curve Fitting The Scatter Plot Scatter Plot Design Clusters and Groupings Multiple Series and Subsets Profiles Bubble Charts 13.Profiling The Need to Solve Panel Charts Bar Charts with Multiple Series Horizon Chart Reorderable Matrix Small Multiples Profiling in Excel 14.Designing for Effectiveness The Aesthetic Dimension A Wrong Model The Design Continuum Tools Are Not Neutral: Defaults Reason and Emotion A.I.D.A. Does Reason Follow Emotion? Emotion and Effectiveness Occam's Razor Designing Chart Components Pseudo-3D Textures Titles Fonts Annotations Grid Lines Clip Art The Secondary Axis Legends Backgrounds Ordering the Data Number of Series Chart Type Grouping Residual Category Context Lying and Deceiving with Charts Contents note continued: Data, Perception, and Cognition Exaggerating Differences Distorting Time Series Aspect Ratio Omitting Points Mistaking Variation for Evolution Double Axes Pseudo 3D When Everything Goes 15.Color: Beyond Aesthetics Quantifying Color The RGB Model The HSL Model Stimuli Intensity The Functional Tasks of Color Categorize Group Emphasize Sequence Diverge Alert The Role of Gray Color Staging Color Harmony General Principles The Classical Rules Complementary Colors Split Complementary Colors Triadic Harmony Analogous Colors Rectangle Warm Colors and Cool Colors Sources for Color Palettes Excel Beyond Excel Color Blindness 16.Conclusion It's All About Pragmatism, Not Aesthetics Say Goodbye to the Old Ways Find Your Own Data Visualization Model Contents note continued: In Business Visualization, Hard Work Is Not Always the Best Work Organizational Literacy Play with Constraints The Tools.
Summary: Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don't need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you'll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created.
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Book Book Indian Institute for Human Settlements, Bangalore
650.0285554 CAM 008568 (Browse shelf) Available 008568

Includes index.

1.The Building Blocks of Data Visualization
Spatial Organization of Stimuli
Seeing Abstract Concepts
Charts
Networks
Maps
Volume: Figurative Visualizations
Visualization in Excel
Retinal Variables
From Concepts to Charts
The Proto-Chart
Chart Effectiveness
Takeaways
2.Visual Perception
Perception and Cognition
Cognitive Offloading
A False Dichotomy
Charts and Tables
Eye Physiology
The Retina
Cones
The Arc of Visual Acuity
Saccades
Impact of Eye Physiology on Visualization
Pre-Attentive Processing
Salience
Impact of Pre-Attentive Processing and Salience on Visualization
Working Memory
Impact of Working Memory on Visualization
Gestalt Laws
Law of Proximity
Law of Similarity
Law of Segregation
Law of Connectivity
Law of Common Fate
Law of Closure
Law of Figure/​Ground
Law of Continuity
Impact of Gestalt Laws on Visualization
Contents note continued: The Limits of Perception
Why We Need Grid Lines and Reference Lines: Weber's Law
Being Aware of Distortions: Stevens' Power Law
Context and Optical Illusions
Impact of the Limits of Perception on Visualization
3.Beyond Visual Perception
Social Pragnanz
Breaking the Rules
The Tragedy of the Commons
Color Symbolism
Representing Time
Axis Folding
Don't Make Me Think!
Literacy and Experience
Graphic Literacy
Familiarity with the Subject
Information Asymmetry
Organizational Contexts
Wrong Messages from the Top
Impression Management
4.Data Preparation
Problems with the Data
Structure without Content
Content without Structure
What Does "Well-Structured Data" Mean, Anyway?
A Helping Hand: Pivot Tables
Extracting the Data
The PDF Plague
"Can It Export to Excel?"
Cleansing Data
Transforming Data
Loading the Data Table
Data Management in Excel
Contents note continued: Organizing the Workbook
Links Outside of Excel
Formulas
Cycles of Production and Analysis
5.Data Visualization
From Patterns to Points
Shape Visualization
Point Visualization
Outlier Visualization
Data Visualization Tasks
The Construction of Knowledge
Data
Information
Knowledge
Wisdom
Defining Data Visualization
Languages, Stories, and Landscapes
Graphical Literacy
Graphical Landscapes
Profiling
Dashboards
Infographics
A Crossroad of Knowledge
Statistics
Design
Applications
Content and Context
Data Visualization in Excel
The Good
The Bad
The Ugly
Beyond the Excel Chart Library
Don't Make Excel Charts
6.Data Discovery, Analysis, and Communication
Where to Start?
The Visual Information-Seeking Mantra
Focus plus Context
Asking Questions
A Classification of Questions
Selecting and Collecting the Data
Contents note continued: Searching for Patterns
Setting Priorities
Reporting Results
Clarification
The Human Dimension
The Design
Project: Monthly Births
Defining the Problem
Collecting the Data
Assessing Data Availability
Assessing Data Quality
Adjusting the Data
Exploring the Data
Embracing Seasonality
Communicating Our Findings
7.How to Choose a Chart
Task-Based Chart Classification
Audience Profile
Sharing Visualizations
Screens and Projectors
Smartphones and Vertical Displays
PDF Files
Excel Files
Sharing Online
8.A Sense of Order
The Bar Chart
Vertical and Horizontal Bars
Color Coding
Ordering
Chart Size
Breaks in the Scale
Changing Metrics to Avoid Breaks in the Scale
Evolution and Change
A Special Bar Chart: The Population Pyramid
Dot Plots
Slope Charts
Strip Plots
Speedometers
Bullet Charts
Alerts
Contents note continued: 9.Parts of a Whole: Composition Charts
What Is Composition?
Composition or Comparison?
Pie Charts
Critique
Damage Control
Donut Charts
Donuts as Multi-Level Pies
Actual Hierarchical Charts: Sunburst Charts and Treemaps
Stacked Bar Chart
Pareto Chart
10.Scattered Data
The Data
Distribution
Showing Everything: Transparencies and Jittering
Quantifying Impressions
Mean and Standard Deviation
The Median and the Interquartile Range
Outliers
Box-and-Whisker Plots
Z-Scores
The Pareto Chart Revisited
Excel Maps
Histograms
Bin Number and Width
Histograms and Bar Charts
Cumulative Frequency Distribution
11.Change Over Time
Focus on the Flow: The Line Chart
Scales and Aspect Ratios
Focus on the Relationships: Connected Scatter Plots
Sudden Changes: The Step Chart
Seasonality: The Cycle Plot
Sparklines
Animation
Contents note continued: 12.Relationships
Understanding Relationships
Curve Fitting
The Scatter Plot
Scatter Plot Design
Clusters and Groupings
Multiple Series and Subsets
Profiles
Bubble Charts
13.Profiling
The Need to Solve
Panel Charts
Bar Charts with Multiple Series
Horizon Chart
Reorderable Matrix
Small Multiples
Profiling in Excel
14.Designing for Effectiveness
The Aesthetic Dimension
A Wrong Model
The Design Continuum
Tools Are Not Neutral: Defaults
Reason and Emotion
A.I.D.A.
Does Reason Follow Emotion?
Emotion and Effectiveness
Occam's Razor
Designing Chart Components
Pseudo-3D
Textures
Titles
Fonts
Annotations
Grid Lines
Clip Art
The Secondary Axis
Legends
Backgrounds
Ordering the Data
Number of Series
Chart Type
Grouping
Residual Category
Context
Lying and Deceiving with Charts
Contents note continued: Data, Perception, and Cognition
Exaggerating Differences
Distorting Time Series
Aspect Ratio
Omitting Points
Mistaking Variation for Evolution
Double Axes
Pseudo 3D
When Everything Goes
15.Color: Beyond Aesthetics
Quantifying Color
The RGB Model
The HSL Model
Stimuli Intensity
The Functional Tasks of Color
Categorize
Group
Emphasize
Sequence
Diverge
Alert
The Role of Gray
Color Staging
Color Harmony
General Principles
The Classical Rules
Complementary Colors
Split Complementary Colors
Triadic Harmony
Analogous Colors
Rectangle
Warm Colors and Cool Colors
Sources for Color Palettes
Excel
Beyond Excel
Color Blindness
16.Conclusion
It's All About Pragmatism, Not Aesthetics
Say Goodbye to the Old Ways
Find Your Own Data Visualization Model
Contents note continued: In Business Visualization, Hard Work Is Not Always the Best Work
Organizational Literacy
Play with Constraints
The Tools.

Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don't need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you'll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created.

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