Data Modeling Design

Data Visualization with d3.js by Swizec Teller

By Swizec Teller

Inject new existence into your info with this mini-guide that takes you thru all of the necessities of information visualization utilizing d3.js. With a uncomplicated wisdom of JavaScript and this educational, you are ready to create nice visualizations.


  • Build blocks of internet visualizations
  • Learn visualization with certain walkthroughs
  • Learn to exploit information extra effectively
  • Animate with d3.js
  • Design strong visualizations

In Detail

d3.js. presents a platform that assist you create your personal attractive visualization and convey facts to lifestyles utilizing HTML, SVG and CSS. It emphasis on internet criteria that would totally make the most of the features of your net browser.

Data Visualization with d3.js walks you thru 20 examples in nice aspect. you could ultimately cease suffering to piece jointly examples you've gotten came upon on-line. With this publication in hand, you are going to research adequate of the middle ideas to conceive of and construct your personal visualizations from scratch.

The ebook starts off with the fundamentals of placing traces at the reveal, and builds in this beginning all of the approach to developing interactive lively visualizations utilizing d3.js layouts.

You will how to use d3.js to govern vector pix with SVG, structure with HTML, and styling with CSS. you are going to seriously look into the fundamentals of sensible programming and utilizing facts constructions successfully – every little thing from dealing with time to doing geographic projections. The e-book also will help in making your visualizations interactive and train you ways computerized layouts quite work.

Data Visualization with d3.js will unveil the secret in the back of all these attractive examples you have been admiring.

What you'll research from this book

  • Draw with SVG shapes and course generators
  • Add types with HTML and CSS
  • Use information buildings effectively
  • Dynamically replace visualizations as info changes
  • Animate visualizations
  • Let the person discover your data
  • Use layouts to create complicated drawings
  • Learn to spot what makes an exceptional visualization good


This ebook is a mini instructional with lots of code examples and techniques to offer you several strategies whilst construction your personal visualizations.

Who this booklet is written for

This publication is perfect for somebody attracted to info visualization. a few rudimentary wisdom of JavaScript is required.

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Additional resources for Data Visualization with d3.js

Example text

Took me a while to figure out what's going on. js can't use a == b to decide whether two complex objects are the same. Instead, it relies on indexes to identify objects. So when we filtered our data, the first x number of indexes had something in them and were considered unchanged, and the rest were removed. The data already attached to elements doesn't get updated, and we have a bad table on our hands. We can get out of this in two ways. descending(Number(a['Doc. ']), Number(b['Doc. '])); }); As before, we used a comparator to sort; we used a numerical comparison between a['Doc.

Attr('transform', 'translate('+(width/2+margin)+', '+margin+')'); Now we define an area generator and draw an area. area() path generator and told it to get the coordinates through the x and y scales we defined earlier. The basis interpolator will use a B-spline to create a smooth curve from our data. To draw the bottom edge, we defined y0 as the bottom of our graph and produced a colored sine approximation: Areas are often used together with lines that make an important edge stand out. attr({stroke: 'steelblue', 'stroke-width': 2, fill: 'none'}); [ 48 ] Chapter 2 We could re-use the same line generator as before; we just need to make sure that we use the same interpolator as for the area.

They use quadratic Bezier curves to create a closed shape connecting two points on an arc. If you don't have a strong background in computer graphics, that tells you nothing. chord() generator for the d attribute. The data itself plays right into the hands of the default accessors. Source defines where the chord begins and target where it ends. Both are fed to another set of accessors, specifying the arc's radius, startAngle, and endAngle. As with the arc generator, angles are defined using radians.

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