Coverart for item
The Resource #MakeoverMonday : Improving How We Visualize and Analyze Data, One Chart at a Time, (electronic book)

#MakeoverMonday : Improving How We Visualize and Analyze Data, One Chart at a Time, (electronic book)

Label
#MakeoverMonday : Improving How We Visualize and Analyze Data, One Chart at a Time
Title
#MakeoverMonday
Title remainder
Improving How We Visualize and Analyze Data, One Chart at a Time
Creator
Contributor
Subject
Language
eng
Member of
Cataloging source
MiAaPQ
http://library.link/vocab/creatorName
Kriebel, Andrew
Dewey number
001.4226
LC call number
QA76.9.I52 .K754 2018
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Murray, Eva
http://library.link/vocab/subjectName
  • Information visualization
  • Statistics as Topic
  • Statistics
Label
#MakeoverMonday : Improving How We Visualize and Analyze Data, One Chart at a Time, (electronic book)
Instantiates
Publication
Copyright
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro -- #MakeoverMonday -- Contents -- Foreword -- Acknowledgments -- From Andy and Eva -- From Andy -- From Eva -- About the Authors -- Andy Kriebel -- Eva Murray -- Part I -- Introduction -- What Is Makeover Monday? -- How Did Makeover Monday Start? -- The Community Project -- The Andys: Makeover Monday 2016 -- The Murray/Cotgreave Swap: Makeover Monday 2017 -- The Next Phase: Makeover Monday 2018 -- Pillars of Makeover Monday -- Developing Technical Skills -- Building a Data Visualization Portfolio -- Learning and Inspiration -- Networking -- Demonstrating Leadership -- Making an Impact -- How to Use this book -- Part II -- Chapter 1 Habits of a Good Data Analyst -- Approaching Unfamiliar Data -- Identify the Challenges -- Gain Insights from Metadata -- Explore the Data -- Analysis versus Visualization -- Take Your Time -- Build Context Through Additional Research -- Read the Available Information -- Seek Additional Information -- Find Insights -- Educating Your Audience -- Communicate Clearly -- Ask Questions -- Summary -- Chapter 2 Data Quality and Accuracy -- Working with Incomplete Data -- Incomplete Data -- Missing Data -- Excluding Data -- Tips for Working with Incomplete or Missing Data -- Overcounting Data -- Sense-Checking Data -- Trump's Tweets -- Is Puerto Rico a State? -- Is the Data Aggregable? -- Adult Obesity in the United States -- Averages of Averages -- Substantiating Claims with Data -- Summary -- Chapter 3 Know and Understand the Data -- Using Appropriate Aggregations -- Can the Data Be Aggregated? -- Basic Aggregation Types -- Explaining Metrics -- Know Your Audience -- Using Appropriate Metrics -- Creating New Metrics to Tell a Different Story -- Identifying and Correcting Mistakes -- Time Series Analysis -- Univariate Time Series -- Visualizing Seasonality -- Using Moving Averages for Smoothing
  • Variance from a Point in Time -- Cycle Plots -- Calendar Heat Map -- Summary -- Chapter 4 Keep It Simple -- What Is Simplicity? -- Simplicity in Design -- Simplicity in Layout and Positioning -- Simplicity in Colors and Icons -- Simplicity in Analysis -- Getting Started with New Data -- Start Simple -- Know When to Stop -- Simplicity in Storytelling -- Finding Insights -- Focusing on a Key Message -- Summary -- Chapter 5 Attention to Detail -- Typos -- Punctuation -- Formatting -- Formatting Charts Effectively -- Universal Formatting -- Crediting Images and Data Sources -- Summary -- Chapter 6 Designing for the Audience -- Creating an Effective Design -- What Is the Purpose? -- Who Is the Audience? -- Sketching -- Planning the Layout -- Designing for Mobile -- Know Your Audience -- Information Displays -- Color Choices -- Use of White Space -- Keep It Simple -- Bringing It All Together -- Using Visual Cues for Additional Information -- Using Icons and Shapes -- Proper Attributions -- Go Easy on the Shapes -- Storytelling -- Finding a Story and Sticking to It -- Long-Form Storytelling -- Think Like a Data Journalist -- Reviewing Your Work to Improve Its Quality -- Take a Step Back -- Ask a Friend -- Viz Review -- Summary -- Chapter 7 Trying New Things -- Developing a Sharing Culture -- Circular Charts -- Images from Dot Plots -- Patterns and Shapes -- Waffle Charts -- Tile Maps -- Borders and Lines -- Summary -- Chapter 8 Iterate to Improve -- Why Iterate? -- Agile Data Visualization -- Examples of Effective Iteration -- Louise Heath: The Price of Oil versus Gold -- Wale Ilori: Air Quality Above America -- Paul Griffith: Le Tour de France -- Rodrigo Calloni: India's Broken Toilets -- Sarah Bartlett: The Timing of Baby Making -- Daniel Caroli: The UK Economy Since the Brexit Vote -- Adolfo Hernandez: Baseball Demographics, 1947-2016
  • Giving and Receiving Feedback -- Giving Effective Feedback -- Receiving Feedback -- Summary -- Chapter 9 Effective Use of Color -- The Significance of Color in Data Visualization -- How Color Is Used to Tell Stories -- Using Color to Evoke Emotions -- Positive Results and Emotions -- Negative Results and Emotions -- Using Color to Create Associations -- Color Associations with Brands -- Color Associations with Topics -- Color Associations Across Multiple Charts -- Using Color to Highlight -- Best Practices for Using Color -- Less Is More -- Considerations for Color Blindness -- Using Background Colors -- Using Text as a Color Legend -- Summary -- Chapter 10 Choosing the Right Chart Type -- Area Charts -- Purpose -- Description -- Examples -- Alternatives -- Stacked Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Diverging Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Filled Maps -- Purpose -- Description -- Examples -- Alternatives -- Donut and Pie Charts -- Purpose -- Description -- Examples -- Alternatives -- Packed Bubble Charts -- Purpose -- Description -- Examples -- Alternatives -- Treemaps -- Purpose -- Description -- Examples -- Alternatives -- Slopegraphs -- Purpose -- Description -- Examples -- Alternatives -- Connected Scatterplots -- Purpose -- Description -- Examples -- Alternatives -- Circular Histograms -- Purpose -- Description -- Examples -- Alternatives -- Radial Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Resources -- Summary -- Chapter 11 Effective Use of Text -- Effective Titles and Subtitles -- Using Questions as Titles -- Making Definitive Statements -- Using Descriptive Titles -- Working with Quirky, Funny, and Poetic Titles -- Delivering on Your Promises -- What Is Your Key Message? -- State Your Message -- Semantics Matter -- Big Ass Numbers -- Call to Action
  • Instructions and Explanations -- Filters -- Hover Interactivity -- Explanations -- Summary -- Chapter 12 Using Context to Inform -- The Importance of Context -- Lack of Context -- Using Simple Metrics -- Big Ass Numbers -- Color Coding -- Reference Lines -- Tooltips -- Subtitles -- Methods for Communicating Context -- Indicators and Arrows -- Comparing Time Periods -- Normalizing the Data -- Supplementing the Data -- Summary -- Part III -- The Community -- Long-Term Contributors -- Educators -- Employers -- Organizations -- Nonprofits -- Social Impact -- Makeover Monday Live Events -- Makeover Monday Enterprise Edition -- Source Lines -- Index -- EULA
Control code
EBC5554190
Dimensions
unknown
Extent
1 online resource (491 pages)
Form of item
online
Isbn
9781119510727
Isbn Type
(ebk)
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Sound
unknown sound
Specific material designation
remote
Label
#MakeoverMonday : Improving How We Visualize and Analyze Data, One Chart at a Time, (electronic book)
Publication
Copyright
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro -- #MakeoverMonday -- Contents -- Foreword -- Acknowledgments -- From Andy and Eva -- From Andy -- From Eva -- About the Authors -- Andy Kriebel -- Eva Murray -- Part I -- Introduction -- What Is Makeover Monday? -- How Did Makeover Monday Start? -- The Community Project -- The Andys: Makeover Monday 2016 -- The Murray/Cotgreave Swap: Makeover Monday 2017 -- The Next Phase: Makeover Monday 2018 -- Pillars of Makeover Monday -- Developing Technical Skills -- Building a Data Visualization Portfolio -- Learning and Inspiration -- Networking -- Demonstrating Leadership -- Making an Impact -- How to Use this book -- Part II -- Chapter 1 Habits of a Good Data Analyst -- Approaching Unfamiliar Data -- Identify the Challenges -- Gain Insights from Metadata -- Explore the Data -- Analysis versus Visualization -- Take Your Time -- Build Context Through Additional Research -- Read the Available Information -- Seek Additional Information -- Find Insights -- Educating Your Audience -- Communicate Clearly -- Ask Questions -- Summary -- Chapter 2 Data Quality and Accuracy -- Working with Incomplete Data -- Incomplete Data -- Missing Data -- Excluding Data -- Tips for Working with Incomplete or Missing Data -- Overcounting Data -- Sense-Checking Data -- Trump's Tweets -- Is Puerto Rico a State? -- Is the Data Aggregable? -- Adult Obesity in the United States -- Averages of Averages -- Substantiating Claims with Data -- Summary -- Chapter 3 Know and Understand the Data -- Using Appropriate Aggregations -- Can the Data Be Aggregated? -- Basic Aggregation Types -- Explaining Metrics -- Know Your Audience -- Using Appropriate Metrics -- Creating New Metrics to Tell a Different Story -- Identifying and Correcting Mistakes -- Time Series Analysis -- Univariate Time Series -- Visualizing Seasonality -- Using Moving Averages for Smoothing
  • Variance from a Point in Time -- Cycle Plots -- Calendar Heat Map -- Summary -- Chapter 4 Keep It Simple -- What Is Simplicity? -- Simplicity in Design -- Simplicity in Layout and Positioning -- Simplicity in Colors and Icons -- Simplicity in Analysis -- Getting Started with New Data -- Start Simple -- Know When to Stop -- Simplicity in Storytelling -- Finding Insights -- Focusing on a Key Message -- Summary -- Chapter 5 Attention to Detail -- Typos -- Punctuation -- Formatting -- Formatting Charts Effectively -- Universal Formatting -- Crediting Images and Data Sources -- Summary -- Chapter 6 Designing for the Audience -- Creating an Effective Design -- What Is the Purpose? -- Who Is the Audience? -- Sketching -- Planning the Layout -- Designing for Mobile -- Know Your Audience -- Information Displays -- Color Choices -- Use of White Space -- Keep It Simple -- Bringing It All Together -- Using Visual Cues for Additional Information -- Using Icons and Shapes -- Proper Attributions -- Go Easy on the Shapes -- Storytelling -- Finding a Story and Sticking to It -- Long-Form Storytelling -- Think Like a Data Journalist -- Reviewing Your Work to Improve Its Quality -- Take a Step Back -- Ask a Friend -- Viz Review -- Summary -- Chapter 7 Trying New Things -- Developing a Sharing Culture -- Circular Charts -- Images from Dot Plots -- Patterns and Shapes -- Waffle Charts -- Tile Maps -- Borders and Lines -- Summary -- Chapter 8 Iterate to Improve -- Why Iterate? -- Agile Data Visualization -- Examples of Effective Iteration -- Louise Heath: The Price of Oil versus Gold -- Wale Ilori: Air Quality Above America -- Paul Griffith: Le Tour de France -- Rodrigo Calloni: India's Broken Toilets -- Sarah Bartlett: The Timing of Baby Making -- Daniel Caroli: The UK Economy Since the Brexit Vote -- Adolfo Hernandez: Baseball Demographics, 1947-2016
  • Giving and Receiving Feedback -- Giving Effective Feedback -- Receiving Feedback -- Summary -- Chapter 9 Effective Use of Color -- The Significance of Color in Data Visualization -- How Color Is Used to Tell Stories -- Using Color to Evoke Emotions -- Positive Results and Emotions -- Negative Results and Emotions -- Using Color to Create Associations -- Color Associations with Brands -- Color Associations with Topics -- Color Associations Across Multiple Charts -- Using Color to Highlight -- Best Practices for Using Color -- Less Is More -- Considerations for Color Blindness -- Using Background Colors -- Using Text as a Color Legend -- Summary -- Chapter 10 Choosing the Right Chart Type -- Area Charts -- Purpose -- Description -- Examples -- Alternatives -- Stacked Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Diverging Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Filled Maps -- Purpose -- Description -- Examples -- Alternatives -- Donut and Pie Charts -- Purpose -- Description -- Examples -- Alternatives -- Packed Bubble Charts -- Purpose -- Description -- Examples -- Alternatives -- Treemaps -- Purpose -- Description -- Examples -- Alternatives -- Slopegraphs -- Purpose -- Description -- Examples -- Alternatives -- Connected Scatterplots -- Purpose -- Description -- Examples -- Alternatives -- Circular Histograms -- Purpose -- Description -- Examples -- Alternatives -- Radial Bar Charts -- Purpose -- Description -- Examples -- Alternatives -- Resources -- Summary -- Chapter 11 Effective Use of Text -- Effective Titles and Subtitles -- Using Questions as Titles -- Making Definitive Statements -- Using Descriptive Titles -- Working with Quirky, Funny, and Poetic Titles -- Delivering on Your Promises -- What Is Your Key Message? -- State Your Message -- Semantics Matter -- Big Ass Numbers -- Call to Action
  • Instructions and Explanations -- Filters -- Hover Interactivity -- Explanations -- Summary -- Chapter 12 Using Context to Inform -- The Importance of Context -- Lack of Context -- Using Simple Metrics -- Big Ass Numbers -- Color Coding -- Reference Lines -- Tooltips -- Subtitles -- Methods for Communicating Context -- Indicators and Arrows -- Comparing Time Periods -- Normalizing the Data -- Supplementing the Data -- Summary -- Part III -- The Community -- Long-Term Contributors -- Educators -- Employers -- Organizations -- Nonprofits -- Social Impact -- Makeover Monday Live Events -- Makeover Monday Enterprise Edition -- Source Lines -- Index -- EULA
Control code
EBC5554190
Dimensions
unknown
Extent
1 online resource (491 pages)
Form of item
online
Isbn
9781119510727
Isbn Type
(ebk)
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Sound
unknown sound
Specific material designation
remote

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