Four data visualization books recommended for reading in the big data age

Source: Internet
Author: User

1. Data Visualization (full color)

In the face of complex big data, visualization provides a good interpretation angle and method, and is a powerful tool for big data analysis and application.

For the first time, this book comprehensively and meticulously combs the history, theories, tools, and application cases of visualization, as well as illustrations and texts. The book is informative, professional, and rigorous. It is the best choice to understand visualization knowledge, it is also worth keeping relevant practitioners as reference books of the case.

This book was selected as the "Big Data Series" of the national key book publishing planning project in the 12th Five-Year Plan, and won the sort recommendation from Professor ma Kuang-6 and Professor shi jiao-ying, one of the famous academic leaders in this field.




2. Turing programming series · data visualization practice: Use D3 to design interactive charts

(Mike Bostock, creator of D3, the most promising web data visualization library, recommends it! The first domestic book explores how to achieve dynamic data visualization in browsers)

You have some data on hand and want to make beautiful charts and put them on the website? Good idea. It is the right option to achieve data visualization across platforms through a browser. What else do you want a chart to respond to user operations? No problem. interactive charts are more attractive than static images to explore the source. Well, to generate a dynamic chart displayed through a browser, the most popular Web data visualization library-D3 is the first choice.

The Turing programming series-data visualization practice: Using D3 to design interactive charts is interesting and less demanding for readers. You do not need to know what data visualization is or understand it without having to have too many web development backgrounds. Believe it? I will know that this is a fun and practical hands-on guide! What will you do after reading this book?



Have basic knowledge of HTML, CSS, JavaScript, and SVG;

Learn how to generate elements in webpages based on data and set styles for them;

Generate bar chart, scatter chart, pie chart, stacked bar chart, and force-directed chart;

Use a smooth transition animation to show data changes;

The dynamic interaction capability of charts is provided to respond to users' requests to explore data from different perspectives;

Collect data and create custom maps;

In addition, Turing programming series · data visualization practices: Using D3 to design interactive charts more than 100 code examples can be viewed online!


3. Fresh guide to data visualization

Nathan Yau's "fresh data (data visualization guide)" is a book that systematically introduces data visualization. The book mainly describes how to convert cold and boring data into easy-to-understand, interesting, and clear-theme charts. Based on the general sequence of data visualization, the author describes how to obtain data, format the data, generate charts using visual tools (such as R), and finally use graphic processing software (such as 11 lustrator) to achieve the best visualization effect. This book describes in detail how to draw charts such as bar chart, pie chart, line chart, and scatter chart, as well as their respective advantages and disadvantages. It also uses a special chapter to introduce data visualization techniques related to maps.

The examples of fresh data (data visualization guide) are rich and illustrated. It is suitable for data analysts, visual designers, and developers interested in data to learn and improve.





4. IDL program design-data visualization and envi Secondary Development

Data visualization is an effective method for extracting information. IDL programming: data visualization and envi secondary development is a programming guide dedicated to Interactive Data Language-IDL visualization applications. The book introduces the syntax basics of IDL programming from a simple perspective, focuses on comparing the three data visualization methods: direct graphics, object image, and quick visualization, and describes their usage and features, finally, hybrid programming of IDL and other programming languages, such as C ++, C #, and Java, as well as ENVI Function Extension and secondary development are introduced. abundant sample code and comments are listed, various functions in IDL are summarized. The accompanying CD contains all the sample code and experiment data in the book for your convenience.

The content of this book is comprehensive and can be used as teaching books and Tutorial Courses for remote sensing, geographic information systems, computers, image processing and related undergraduates and graduate students, it can also be used as a tool book for computer software developers.

Four data visualization books recommended for reading in the big data age

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