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E-raamat: JavaScript and jQuery for Data Analysis and Visualization [Wiley Online]

(Jon Raasch Web Design), (New York, NY, author and trainer), ,
  • Formaat: 480 pages
  • Ilmumisaeg: 20-Jan-2015
  • Kirjastus: Wrox Press
  • ISBN-10: 1119209382
  • ISBN-13: 9781119209386
Teised raamatud teemal:
  • Wiley Online
  • Hind: 47,57 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
JavaScript and jQuery for Data Analysis and VisualizationSuurem pilt
  • Formaat: 480 pages
  • Ilmumisaeg: 20-Jan-2015
  • Kirjastus: Wrox Press
  • ISBN-10: 1119209382
  • ISBN-13: 9781119209386
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119209386
Go beyond design concepts—build dynamic data visualizations using JavaScript

JavaScript and jQuery for Data Analysis and Visualization goes beyond design concepts to show readers how to build dynamic, best-of-breed visualizations using JavaScript—the most popular language for web programming.

The authors show data analysts, developers, and web designers how they can put the power and flexibility of modern JavaScript libraries to work to analyze data and then present it using best-of-breed visualizations. They also demonstrate the use of each technique with real-world use cases, showing how to apply the appropriate JavaScript and jQuery libraries to achieve the desired visualization.

All of the key techniques and tools are explained in this full-color, step-by-step guide. The companion website includes all sample codes used to generate the visualizations in the book, data sets, and links to the libraries and other resources covered.

  • Go beyond basic design concepts and get a firm grasp of visualization approaches and techniques using JavaScript and jQuery
  • Discover detailed, step-by-step directions for building specific types of data visualizations in this full-color guide
  • Learn more about the core JavaScript and jQuery libraries that enable analysis and visualization
  • Find compelling stories in complex data, and create amazing visualizations cost-effectively

Let JavaScript and jQuery for Data Analysis and Visualization be the resource that guides you through the myriad strategies and solutions for combining analysis and visualization with stunning results.

Introduction xix
Part I: The Beauty Of Numbers Made Visible
Chapter 1 The World Of Data Visualization
3(14)
Bringing Numbers to Life
4(3)
Acquiring the Data
4(1)
Visualizing the Data
4(3)
Simultaneous Acquisition and Visualization
7(1)
Applications of Data Visualization
7(2)
Uses in the Public Sector
7(1)
Business-to-Business and Intrabusiness Uses
8(1)
Business-to-Consumer Uses
8(1)
Web Professionals: In the Thick of It
9(2)
Control of Presentation
9(2)
What Tech Brings to the Table
11(6)
Faster and Better JavaScript Processing
12(1)
Rise of HTML5
12(1)
Lowering the Implementation Bar
13(1)
Summary
14(3)
Chapter 2 Working With The Essentials Of Analysis
17(10)
Key Analytic Concepts
18(2)
Mean Versus Median
18(1)
Standard Deviation
19(1)
Working with Sampled Data
20(2)
Standard Deviation Variation
20(1)
Per Capita Calculations
21(1)
Margin of Error
21(1)
Detecting Patterns with Data Mining
22(1)
Projecting Future Trends
23(2)
Summary
25(2)
Chapter 3 Building A Visualization Foundation
27(30)
Exploring the Visual Data Spectrum
28(21)
Charting Primitives
28(12)
Exploring Advanced Visualizations
40(2)
Candlestick Chart
42(1)
Bubble Chart
42(2)
Surface Charts
44(2)
Map Charts
46(1)
Infographics
46(3)
Making Use of the HTML5 Canvas
49(3)
Integrating SVG
52(2)
Summary
54(3)
Part II: Working With Javascript For Analysis
Chapter 4 Integrating Existing Data
57(16)
Reading Data from Standard Text Files
58(3)
Working Asynchronously
58(1)
Reading CSV Files
59(2)
Incorporating XML Data
61(5)
Understanding the XML Format
61(1)
Getting XML Data
62(1)
Styling with XSLT
63(3)
Displaying JSON Content
66(5)
Understanding JSON Syntax
66(1)
Reading JSON Data
67(1)
Asynchronous JSON
68(3)
Summary
71(2)
Chapter 5 Acquiring Data Interactively
73(6)
Using HTML5 Form Controls
73(2)
Introducing HTML5 Input Types
74(1)
Form Widgets and Data Formatting
74(1)
Maximizing Mobile Forms
75(2)
Using Contextual Keyboards
76(1)
Styling Mobile Forms for Usability
77(1)
Form Widgets for Mobile
77(1)
Summary
77(2)
Chapter 6 Validating Your Data
79(14)
Server-Side Versus Client-Side Validation
80(1)
Native HTML5 Validation
81(4)
Native Versus JavaScript Validation
81(1)
Getting Started with HTML5 Validation
82(1)
HTML5 Validation for Numbers
82(1)
Required Fields and Max Length
82(1)
Custom HTML5 Validation Rules
83(1)
Custom HTML5 Validation Messages
83(1)
h5Validate Polyfill
84(1)
jQuery Validation Engine
85(6)
Getting Started with jQuery Validation Engine
85(1)
Validators
86(4)
Error Messages
90(1)
Summary
91(2)
Chapter 7 Examining And Sorting Data Tables
93(52)
Outputting Basic Table Data
94(11)
Building a Table
94(2)
Using Semantic Table Markup
96(5)
Labeling Your Table
101(1)
Configuring the Columns
102(3)
Assuring Maximum Readability
105(11)
Styling Your Table
106(2)
Increasing Readability
108(6)
Adding Dynamic Highlighting
114(2)
Including Computations
116(9)
Using JavaScript for Calculations
120(3)
Populating the Table
123(2)
Using the DataTables Library
125(8)
Making Pretty Tables with DataTables
126(2)
Sorting with DataTables
128(2)
Using Calculated Columns with DataTables
130(3)
Relating a Data Table to a Chart
133(11)
Mashing Visualizations Together
133(11)
Summary
144(1)
Chapter 8 Statistical Analysis On The Client Side
145(12)
Statistical Analysis with jStat
146(3)
Getting Started with jStat
146(1)
Stat 101
147(2)
Rendering Probability Distributions with Flot
149(4)
Getting Started with Flot
149(2)
Rendering the Normal Curve
151(2)
Summary
153(4)
Part III: Visualizing Data Programmatically
Chapter 9 Exploring Charting Tools
157(46)
Creating HTML5 Canvas Charts
158(36)
HTML5 Canvas Basics
158(1)
Linear Interpolation
159(1)
A Simple Column Chart
160(16)
Implementing Axes
176(7)
Adding Animation
183(11)
Starting with Google Charts
194(9)
Google Charts API Basics
195(1)
A Basic Bar Chart
195(2)
A Basic Pie Chart
197(1)
Working with Chart Animations
198(3)
Summary
201(2)
Chapter 10 Building Custom Charts With Raphael
203(30)
Introducing Raphael
204(5)
SVG Versus Canvas Charts
204(1)
Getting Started with Raphael
204(1)
Drawing Paths
205(1)
Importing Custom Shapes into Raphael
206(2)
Animating Raphael Graphics
208(1)
Handling Mouse Events with Raphael
208(1)
Working with gRaphael
209(7)
Creating Pie Charts
209(2)
Creating Line Charts
211(2)
Creating Bar and Column Charts
213(3)
Extending Raphael to Create Custom Charts
216(16)
Setting Up with Common Patterns
216(1)
Drawing an Arc
217(4)
Massaging Data into Usable Values
221(4)
Adding Mouse Interactivity
225(2)
Labeling the Data
227(2)
Wrapping Up
229(3)
Summary
232(1)
Chapter 11 Introducing D3
233(32)
Getting Started
235(22)
DOM and SVG
236(1)
.select
237(1)
.selectAll
238(1)
.data() (Also Known As Data Joining)
239(10)
Key Functions
249(1)
.transition()
250(3)
Object Constancy
253(2)
Nested Selections
255(2)
D3 Helper Functions
257(3)
Drawing Lines
257(1)
Scales
258(2)
D3 Helper Layouts
260(4)
Summary
264(1)
Chapter 12 Incorporating Symbols
265(26)
Working with SVG Symbols with D3
266(10)
Creating a D3 Line Chart
266(5)
Adding Symbols to the Line
271(2)
Making the Symbols Interactive
273(3)
Canvas Symbols with Ignite UI igDataChart
276(13)
Creating a Line Chart with Ignite UI igDataChart
277(4)
Adding Symbols to the Chart
281(3)
Creating a Bubble Chart
284(5)
Summary
289(2)
Chapter 13 Mapping Global, Regional, And Local Data
291(36)
Working with Google Maps
292(5)
The Basics of Mapping Visualizations
292(2)
The Google Maps API v3
294(3)
Customizing Maps with Iconography
297(17)
Displaying a Map Marker
297(2)
Preparing Data to Plot on a Map
299(4)
Plotting Point Data Using Markers
303(4)
Plotting an Additional Statistic Using Marker Area
307(3)
Displaying Data Density with Heat Maps
310(4)
Plotting Data on Choropleth Maps
314(12)
Obtaining Geometry to Plot on a Map
314(1)
Converting Geometry for Display Using Topojson
315(1)
Rendering Map Geometry Using D3
316(3)
Displaying Statistics Using a Choropleth Map
319(7)
Summary
326(1)
Chapter 14 Charting Time Series With Ignite UI IGDATACHART
327(44)
Working with Stocks
328(3)
The Basics of Stock Data
328(1)
Obtaining Some Stock Data
329(1)
Candlesticks and OHLC Visualizations
329(2)
Implementing Ignite UI igDataChart
331(17)
Obtaining Ignite UI
332(1)
Implementing a Stock Chart Using igDataChart
333(9)
Adding a Zoom Bar to the Chart
342(2)
Adding a Synchronized Chart
344(3)
Working with Technical Analysis Tools
347(1)
Plotting Real-Time Data
348(13)
Creating a Node Push Data Service
349(4)
Receiving Updates in the Client
353(6)
Exploring Update Rendering Techniques
359(2)
Plotting Massive Data
361(5)
Summary
366(5)
Part IV: Interactive Analysis And Visualization Projects
Chapter 15 Building An Interconnected Dashboard
371(42)
The U.S. Census API
372(1)
Rendering Charts
373(13)
Sex Chart
373(2)
Race Chart
375(2)
Household Size Chart
377(1)
Household Tenure Chart
378(1)
Age by Sex Chart
379(5)
Population History Chart
384(2)
Creating the Dashboard
386(4)
Basic Markup and Styling
386(3)
Responsive Layer
389(1)
Connecting Components with Backbone
390(20)
Establishing Models and Collections
391(1)
Converting the Chart Markup to a JavaScript Template
392(2)
Creating the State Drop-down Menu
394(2)
Rendering State Changes
396(14)
Next Steps
410(1)
Rerendering on Resize
411(1)
Other Improvements
411(1)
Summary
411(2)
Chapter 16 D3 In Practice
413(22)
Making D3 Look Perfect
414(3)
Inline Styles Versus CSS
414(1)
Margin
414(1)
Ordering
415(1)
Pointer Events
416(1)
Crisp Edges
416(1)
Working with Axes
417(4)
Working with the Voronoi Map
421(6)
A Basic Voronoi Map
421(3)
Voronoi Point Picking
424(3)
Making Reusable Visualizations
427(7)
Summary
434(1)
Index 435
Jon Raasch is a freelance web developer and author of several books. A user-experience junkie, he builds HTML5 and JavaScript apps for desktop and mobile devices.

Graham Murray is a software architect specializing in building UI development tools.

Vadim Ogievetsky is a data flow processor at Metamarkets, where he works with data visualization framework development.

Joseph Lowery is a professional web designer and online trainer with courses on website and app creation as well as data visualization at Lynda.com.

Wrox guides are crafted to make learning programming languages and technologies easier than you think. Written by programmers for programmers, they provide a structured, tutorial format that will guide you through all the techniques involved.
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