| Document Type
|
:
|
BL
|
| Record Number
|
:
|
840505
|
| Main Entry
|
:
|
Kriebel, Andrew Michael,1973-
|
| Title & Author
|
:
|
#MakeOverMonday : : improving how we visualize and analyze data, one chart at a time /\ Andy Kriebel, Eva Murray.
|
| Publication Statement
|
:
|
Hoboken, NJ :: John Wiley & Sons, Inc.,, [2018]
|
| Page. NO
|
:
|
1 online resource (xvi, 472 pages) :: illustrations
|
| ISBN
|
:
|
1119510724
|
|
|
:
|
: 1119510791
|
|
|
:
|
: 9781119510727
|
|
|
:
|
: 9781119510796
|
|
|
:
|
1119510775
|
|
|
:
|
9781119510772
|
| Bibliographies/Indexes
|
:
|
Includes bibliographical references and index.
|
| 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 AnalystApproaching 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
|
|
|
:
|
Planning the LayoutDesigning 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
|
| Abstract
|
:
|
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
|
| Subject
|
:
|
Information visualization.
|
| Subject
|
:
|
Statistics.
|
| Subject
|
:
|
Data Collection.
|
| Subject
|
:
|
Statistics as Topic.
|
| Subject
|
:
|
Information visualization.
|
| Subject
|
:
|
REFERENCE-- Questions Answers.
|
| Subject
|
:
|
Statistics.
|
| Dewey Classification
|
:
|
001.4/226
|
| LC Classification
|
:
|
QA76.9.I52K75 2018eb
|
| Added Entry
|
:
|
Murray, Eva Katharina,1985-
|
| Parallel Title
|
:
|
Make Over Monday
|
|
|
:
|
: MakeOver Monday
|
|
|
:
|
: MakeOverMonday
|