Spis treści: „Making Data Visual: A Practical Guide to Using Visualization for Insight”

Spis treści publikacji pt. „Making Data Visual: A Practical Guide to Using Visualization for Insight”.

Tytuł: „Making Data Visual: A Practical Guide to Using Visualization for Insight”
Autorzy: Danyel Fischer, Miriah Meyer
Wydawca: O′Reilly
Data wydania: 2018-01-12
Język: Angielski
Liczba stron: 250

Spis treści

Spis treści / Table of contents

Preface

1. Who Is This Book For?
2. Who Are We?
3. Overview of Chapters
4. Acknowledgments
5. O’Reilly Safari
6. How to Contact Us
7. Getting to an Effective Visualization
8. Getting to Insight
9. Hotmap: Making Decisions with Data
10. Where Visualization Is Useful
11. Further Reading
12. From Questions to Tasks
13. Example: Identifying Good Movie Directors
14. Making a Question Concrete

2.1. A Concrete Movie Question

3. Breaking Down a Task

3.1 When Tasks Lead to New Questions

4. Returning to the Example: Exploring Different Definitions

5. How Specific Does the Process Get?

6. Making Use of Results

7. Conclusion: A Well-Operationalized Task

8. Further Reading

III. Data Counseling, Exploration, and Prototyping

1. Technique 1: Data Counseling

1.1. Identifying Stakeholders

1.2. Conducting Interviews

1.3. Conducting Contextual Interviews

2. Technique 2: Exploring the Data

3. Technique 3: Rapid Prototyping for Design

3.1.The Range of Prototypes

3.2. Eliciting Feedback

4. And, Repeat

5. Conclusion

6. Components of a Visualization

7. Dimensions and Measures

1.1. Example: International Towing & Ice Cream

1.2. Dimensions

1.3. Types of Data

1.4. Transforming Between Dimension Types

1.5. Dimensionality Reduction and Clustering

2. Examining Actions

3. Single Views

4. Overall Perceptual Concerns

5. Question: How Is a Measure Distributed?

2.1. Histogram (Categorical)

2.2. Histogram (Quantitative)

2.3. Smoothed Histogram

2.4. Box Plot

2.5. Density Plot for Two Dimensions

3. Question: How Do Groups Differ from Each Other?

3.1. Bar Chart

3.2. Pie Chart

3.3. Heatmap

4. Question: Do Individual Items Fall into Groups? Is There a Relationship Between Attributes of Items?

4.1. Scatterplot

5. Question: How Does an Attribute Vary Continuously?

5.1. Line and Area Charts

6. Question: How Are Objects Related to Each Other in a Network or Hierarchy?

6.1. Node-Link View

6.2. Adjacency Matrix

6.3. Tree View

6.4. Treemap and Sunburst

7. Question: Where Are Objects Located?

7.1. Geographical Map

8. Question: What Is in This Text?

8.1. Word Cloud

9. Conclusion

10. Further Reading

10.1. Relevant Articles

10.2. Datasets

1. Multiple and Coordinated Views
2. Small Multiples
3. Scatterplot Matrices
4. Overview+Detail
5. Multiform Views and Dashboards
6. Overlays
7. Axis Alignment and Scale Consistency
8. Interacting with Multiple Linked Views
9. MLVs and the Operationalization Process
10. Conclusion
11. Further Reading
    10.1. Datasets

VII. Case Study 1: Visualizing Telemetry to Improve Software

1. Introduction
2. Project Background
3. The Data
4. Determining How to Compare Builds
5. Comparing Distributions to Understand “Better”
6. Multiple Scenarios
7. Sketching Dashboards

7.1. Turning Back to the Data

8. Final UI for High-Level Goals

8.1. Additional Visualizations

9. Conclusion

9.1. Acknowledgments

10. Further Reading

VIII. Case Study 2: Visualizing Biological Data

1. Background
2. Setting the Context

2.1. Zooming in a Level

3. Improving the Existing Approach
4. Similarity, Not Outliers
5. A Final Version
6. Conclusion
7. Further Reading
8. Conclusions

Index

Kreatywne pozdrowienia,

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