Pro Data Visualization Using R and JavaScript: Analyze and Visualize Key Data on the Web
- Length: 289 pages
- Edition: 2
- Language: English
- Publisher: Apress
- Publication Date: 2021-10-26
- ISBN-10: 1484272013
- ISBN-13: 9781484272015
- Sales Rank: #6934197 (See Top 100 Books)
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
- Work with the R Plumber API generator, Shiny, and more
Apply D3 and R Notebooks towards your data
Who This Book Is For
Programmers and data scientists/analysts who have some prior experience with R and JavaScript.
Cover Front Matter 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 Back Matter
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