How Do I Choose the Best Data Visualization Software?

Nathan Yau is a Ph.D. student in statistics at the University of California, Los Angeles, and a super data enthusiast, focusing on data visualization and personal data collection. He has worked for The New York Times, CNN, Mozilla, and SyFy, and believes that data and infographics are not only suitable for analysis, but also suitable for telling data-related stories. Yau's goal is to make non-professionals understand and use data. He created a design, visualization, and statistics area where you can admire his latest data visualization experiments.

Living Data: A Guide to Data Visualization

Subtitle: Data visualization guide ^[1]

Xiang Yining is an interactive and visual designer and rock musician. He is also passionate about translation and writing. Author of "Flash Components, Games, SWF Encryption and Decryption" and "It's That Simple: Usability and User Experience in Web Development", translated "Wonderful Ideas: 15 Computer Geniuses and Their Great Discoveries", "Instant Beauty: "How Web Interface Design Makes People's Minds", "Deconstruction of Website Design: Effective Interaction Design Frameworks and Patterns", "Search Design for Websites: Website Design Experiences Considering SEO and Usability" and other books. He believes that "a designer who can't play guitar is not a good translator."

Data is almost ubiquitous in life, and we can access it. However, the same data may feel very different: or cold and boring, intimidating and puzzling; or vivid and interesting, clear and cheerful. In order to achieve the latter effect, we need to adopt a special way to display the data to explain, analyze and apply it. This is data visualization technology.

In "Live Data: A Guide to Data Visualization", he introduced how to obtain data, format the data, generate charts with visualization tools (such as R), and graphical editing software (such as Illustrator) to optimize the chart. This book introduces dozens of methods (such as bar charts, pie charts, line charts, scatter charts, etc.), and tells stories about data in a creative and visual way. Open the book, the door of thinking will suddenly open, you will find that there are so many ways to give data a whole new meaning!

The main contents of Living Data: A Guide to Data Visualization include:

Learn how to present data in a visual representation so that readers see different information;

Discover the story behind the data;

Explore different data sources to determine effective display formats;

Experiment and compare different visualization tools;

Find trends and patterns in your data and present them with appropriate charts;

Set clear goals and use them to guide your visualization process.

Chapter 1 Telling stories with data ^[1]

1.1 Not just numbers

1.1.1 News Report

1.1.2 Art

1.1.3 Entertainment

1.1.4 eye-catching

1.2 What are we seeking

1.2.1 Mode

1.2.2 Interrelationships

1.2.3 Problematic data

1.3 Design

1.3.1 Interpret encoding

1.3.2 Annotate coordinate axes

1.3.3 ensuring geometric correctness

1.3.4 Provide data sources

1.3.5 Think about your audience

1.4 Summary

Chapter 2 Working with Data

2.1 Collecting data

2.1.1 Provided by others

2.1.2 Finding the data source

2.1.3 Automatic data collection

2.2 Format the data

2.2.1 Data Format

2.2.2 Formatting Tool

2.2.3 Formatting with code

2.3 summary

Chapter 3 Choosing Visualization Tools

3.1 Out-of-the-box visualization tools

3.1.1 Options

3.1.2 trade-offs

3.2 Programming tools

3.2.1 Options

3.2.2 Choosing

3.3 Drawing software

3.3.1 Options

3.3.2 trade-offs

3.4 Map drawing tools

3.4.1 Options

3.4.2 trade-offs

3.5 Measuring various options

3.6 Summary

Chapter 4 Visualizing Time Trends

4.1 What to seek in time

4.2 Discrete points in time

4.2.1 Cylindrical

4.2.2 cylindrical stack

4.2.3 Dots

4.3 Continuity data

4.3.1 Point-to-point connection

4.3.2 step by step

4.3.3 Smoothing and estimation

4.4 Summary

Chapter 5 Visualization of Scale

5.1 What to look for in proportions

5.2 Parts of the whole

5.2.1 Pie chart

5.2.2 Bagel chart

5.2.3 Stacking in proportion

5.2.4 levels and rectangles

5.3 Proportion with time attribute

5.3.1 Continuation of the stack

5.3.2 Point by point

5.4 Summary

Chapter 6 Visualizing Relationships

6.1 What to look for in a relationship

6.2 Relevance

6.2.1 More dots

6.2.2 Exploring More Variables

6.2.3 Bubbles

6.3 Distribution

6.3.1 Old-fashioned distribution chart

6.3.2 Columns Related to Distribution

6.3.3 Continuity density

6.4 Comparison and comparison

6.5 Summary

Chapter 7 Finding Differences

7.1 What to look for in differences

7.2 Comparing between multiple variables

7.2.1 Warming up

7.2.2 Face to Face

7.2.3 Starlight

7.2.4 Parallel advance

7.3 Reduced Dimensions

7.4 Finding Outliers

7.5 Summary

Chapter 8 Visualization of Spatial Relationships

8.1 What to seek in space

8.2 Specific location

8.2.1 Finding Latitude and Longitude

8.2.2 Pure points

8.2.3 There are big and small points

8.3 Region

8.4 Crossing space and time

8.4.1 Series Group Picture

8.4.2 Seize the difference

8.4.3 Animation

8.5 Summary

Chapter 9 Purposeful Design

9.1 Prepare yourself

9.2 Prepare the reader

9.3 Visual cue

9.4 Good visualization

9.5 summary