Pro Data Visualization Using R and JavaScript: Analyze and Visualize Key Data on the Web
Autor Tom Barker, Jon Westfallen Limba Engleză Paperback – 8 oct 2021
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
Programmers and data scientists/analysts who have some prior experience with R and JavaScript.
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Specificații
ISBN-13: 9781484272015
ISBN-10: 1484272013
Pagini: 267
Ilustrații: XV, 274 p. 112 illus.
Dimensiuni: 178 x 254 mm
Greutate: 0.51 kg
Ediția:2nd ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
ISBN-10: 1484272013
Pagini: 267
Ilustrații: XV, 274 p. 112 illus.
Dimensiuni: 178 x 254 mm
Greutate: 0.51 kg
Ediția:2nd ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
Cuprins
1. Background.- 2. R Language Primer.- 3. A Deeper Dive into R.- 4. Data Visualization with D3.- 5. Visualizing Spatial Data from Access Logs.- 6. Visualizing Data Over Time.- 7. Bar Charts.- 8. Correlation Analysis with Scatter Plots.- 9. Visualizing the Balance of Delivery and Quality with Parallel Coordinates.
Recenzii
“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)
Notă biografică
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.
Textul de pe ultima copertă
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.
You will:
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.
You will:
- 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
Caracteristici
An updated second edition with emphasis on visualizing data and programming web interfaces Includes information about correlation analysis with scatter plots Covers date/time trend data with line chart and more