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Pro Data Visualization using R and JavaScript

Book Description

Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R 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.

What you'll learn

  • A rich understanding of how to gather, and analyze empirical data

  • How to tell a story with data using data visualizations

  • What types of data visualizations are best to use for the story that you want to tell with your data

  • A comprehensive introduction to the R language, covering all the essentials

  • Exploration of how to construct interactive data visualizations using JavaScript and JavaScript libraries

Who this book is for

Developers at all levels interested in data visualization, beginning to intermediate engineering managers, statisticians, mathematicians, economists and any others interested in data visualization.

Table of Contents

  1. Title Page
  2. Dedication
  3. Contents at a Glance
  4. Contents
  5. About the Author
  6. About the Technical Reviewer
  7. Acknowledgments
  8. CHAPTER 1: Background
    1. What Is Data Visualization?
    2. Why Data Visualization?
    3. Tools
    4. Process Overview
    5. Ethics of Data Visualization
    6. Summary
  9. CHAPTER 2: R Language Primer
    1. Getting to Know the R Console
    2. Importing Data
    3. Data Structures and Data Types
    4. Summary
  10. CHAPTER 3: A Deeper Dive into R
    1. Object-Oriented Programming in R
    2. Statistical Analysis with Descriptive Metrics in R
    3. RStudio IDE
    4. Summary
  11. CHAPTER 4: Data Visualization with D3
    1. Preliminary Concepts
    2. History of D3
    3. Using D3
    4. Creating a Bar Chart
    5. Loading External Data
    6. Summary
  12. CHAPTER 5: Visualizing Spatial Data from Access Logs
    1. What Are Data Maps?
    2. Access Logs
    3. Parsing the Access Log
    4. Summary
  13. CHAPTER 6: Visualizing Data Over Time
    1. Gathering Data
    2. Data Analysis with R
    3. Adding Interactivity with D3
    4. Summary
  14. CHAPTER 7: Bar Charts
    1. Standard Bar Chart
    2. Stacked Bar Chart
    3. Grouped Bar Chart
    4. Visualizing and Analyzing Production Incidents
    5. Plotting Data on a Bar Chart with R
    6. Bar Charts in D3
    7. Summary
  15. CHAPTER 8: Correlation Analysis with Scatter Plots
    1. Finding Relationships in Data
    2. Introductory Concepts of Agile Development
    3. Correlation Analysis
    4. Visualizing Bugs
    5. Visualizing Production Incidents
    6. Interactive Scatter Plots in D3
    7. Summary
  16. CHAPTER 9: Visualizing the Balance of Delivery and Quality with Parallel Coordinates
    1. What Are Parallel Coordinate Charts?
    2. History of Parallel Coordinate Plots
    3. Finding Balance
    4. Brushing Parallel Coordinate Charts with D3
    5. Summary
  17. Index