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Pro Data Visualization Using R and JavaScript: Analyze and Visualize Key Data on the Web 2nd ed. [Pehme köide]

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  • Formaat: Paperback / softback, 274 pages, kõrgus x laius: 254x178 mm, kaal: 559 g, 112 Illustrations, black and white; XV, 274 p. 112 illus., 1 Paperback / softback
  • Ilmumisaeg: 08-Oct-2021
  • Kirjastus: APress
  • ISBN-10: 1484272013
  • ISBN-13: 9781484272015
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  • Pehme köide
  • Hind: 57,96 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 68,19 €
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  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
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Pro Data Visualization Using R and JavaScript: Analyze and Visualize Key Data on the Web 2nd ed.Suurem pilt
  • Formaat: Paperback / softback, 274 pages, kõrgus x laius: 254x178 mm, kaal: 559 g, 112 Illustrations, black and white; XV, 274 p. 112 illus., 1 Paperback / softback
  • Ilmumisaeg: 08-Oct-2021
  • Kirjastus: APress
  • ISBN-10: 1484272013
  • ISBN-13: 9781484272015
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781484272015.html
Märksõnad:
Use R 4, RStudio, Tidyverse, and Shiny to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually.





With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization Using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations.





Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells. This book makes the R language approachable, and promotes the idea of data gathering and analysis mostly using web interfaces.





What You Will Learn









Carry out data visualization using R and JavaScript Use RStudio for data visualization  Harness Tidyverse data pipelines Apply D3 and R Notebooks towards your data Work with the R Plumber API generator, Shiny, and more

Who This Book Is For





Programmers and data scientists/analysts who have some prior experience with R and JavaScript.

Arvustused

This book offers a gradual introduction to data visualization by using R to analyse data and R and D3 Javascript libraries to format and make data visually interesting. this book is a practical tool to implement data visualization solution for standard charts in R and D3 JS with programs allowing the reader to test and implement these solutions, and also to improve them their own use. (Sébastien Bailly, ISCB News, iscb.info, June, 2022)

1. Exploring Data Visualization
2. RStudio
3. Tidyverse Data Pipelines
4. Data Visualization with D3
5. Comparing Groups with Bar Charts
6. Correlation Analysis with Scatter Plots
7. Datetime Trend Data with Line Charts
8. Visual Presentations with D3 and R Notebooks
9. Interactive Dashboards with D3 and Shiny
10. Visualization on the Web with D3 and R Plumber API Generator
Tom Barker is an engineer, a professor and an author. Currently he is Sr Manager of Web Development at Comcast, and an instructor at Philadelphia University. He has authored several books on web development including Pro JavaScript Performance: Monitoring and Visualization, and Pro Data Visualization with JavaScript and R. Matthew Campbell has worked on data visualization and dashboards with a data science team using RStudio. He got his start with technology after college when he learned SAS to do statistical programming at the Educational Testing Service (ETS). Learning this programming language kicked off a lifelong obsession with technology.