Pro Data Visualization Using R and JavaScript - Analyze and Visualize Key Data on the Web (2nd Edition)
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 implementa...
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| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Berkeley, CA
Apress, an imprint of Springer Nature
2021
Apress Apress L. P |
| Edition: | 2 |
| Subjects: | |
| ISBN: | 9781484272015, 1484272013, 9781484272022, 1484272021 |
| Online Access: | Get full text |
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Table of Contents:
- Title Page Table of Contents 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 Index
- Chapter 6: Visualizing Data over Time -- Gathering Data -- Data Analysis with R -- Calculating the Bug Count -- Examining the Severity of the Bugs -- Adding Interactivity with D3 -- Reading in the Data -- Drawing on the Page -- Adding Interactivity -- Summary -- Chapter 7: Bar Charts -- Standard Bar Chart -- Stacked Bar Chart -- Grouped Bar Chart -- Visualizing and Analyzing Production Incidents -- Plotting Data on a Bar Chart with R -- Ordering Results -- Creating a Stacked Bar Chart -- Bar Charts in D3 -- Creating a Vertical Bar Chart -- Creating a Stacked Bar Chart -- Creating an Overlaid Visualization -- Summary -- Chapter 8: Correlation Analysis with Scatter Plots -- Finding Relationships in Data -- Introductory Concepts of Agile Development -- Correlation Analysis -- Creating a Scatter Plot -- Creating a Bubble Chart -- Visualizing Bugs -- Visualizing Production Incidents -- Interactive Scatter Plots in D3 -- Adding the Base HTML and JavaScript -- Loading the Data -- Adding Interactive Functionality -- Adding Form Fields -- Retrieving Form Data -- Using the Visualization -- Summary -- Chapter 9: Visualizing the Balance of Delivery and Quality with Parallel Coordinates -- What Are Parallel Coordinate Charts? -- History of Parallel Coordinate Plots -- Finding Balance -- Creating a Parallel Coordinate Chart -- Adding in Effort -- Brushing Parallel Coordinate Charts with D3 -- Creating the Base Structure -- Creating a Y-Axis for Each Column -- Drawing the Lines -- Fading the Lines -- Creating the Axes -- Summary -- Index
- Intro -- Table of Contents -- About the Authors -- About the Technical Reviewer -- Acknowledgments -- Chapter 1: Background -- What Is Data Visualization? -- Time Series Charts -- Bar Charts -- Histograms -- Data Maps -- Scatter Plots -- History -- Modern Landscape -- Why Data Visualization? -- Tools -- Languages, Environments, and Libraries -- Analysis Tools -- Process Overview -- Identify a Problem -- Gather Data -- Analyze Data -- Visualize Data -- Ethics of Data Visualization -- Cite Sources -- Be Aware of Visual Cues -- Summary -- Chapter 2: R Language Primer -- Getting to Know the R Console -- The Command Line -- Command History -- Accessing Documentation -- Packages -- Importing Data -- Using Headers -- Specifying a String Delimiter -- Specifying Row Identifiers -- Using Custom Column Names -- Data Structures and Data Types -- Data Frames -- Matrices -- Adding Lists -- Looping Through Lists -- Applying Functions to Lists -- Functions -- Summary -- Chapter 3: A Deeper Dive into R -- Object-Oriented Programming in R -- S3 Classes -- S4 Classes -- Statistical Analysis with Descriptive Metrics in R -- Median and Mean -- Quartiles -- Standard Deviation -- RStudio IDE -- R Markdown -- RPubs -- Summary -- Chapter 4: Data Visualization with D3 -- Preliminary Concepts -- HTML -- CSS -- SVG -- JavaScript -- History of D3 -- Using D3 -- Setting Up a Project -- Using D3 -- Binding Data -- Creating a Bar Chart -- Loading External Data -- Summary -- Chapter 5: Visualizing Spatial Data from Access Logs -- What Are Data Maps? -- Access Logs -- Parsing the Access Log -- Read in the Access Log -- Parse the Log File -- Geolocation by IP -- Output the Fields -- Adding Control Logic -- Creating a Data Map in R -- Mapping Geographic Data -- Adding Latitude and Longitude -- Displaying Regional Data -- Distributing the Visualization -- Summary