Data Visualization with d3.js by Swizec Teller

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By Swizec Teller

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

Overview

  • Build blocks of net visualizations
  • Learn visualization with distinct walkthroughs
  • Learn to take advantage of facts extra effectively
  • Animate with d3.js
  • Design solid visualizations

In Detail

d3.js. offers a platform that assist you create your personal appealing visualization and produce information to existence utilizing HTML, SVG and CSS. It emphasis on net criteria that may totally make the most of the functions of your internet browser.

Data Visualization with d3.js walks you thru 20 examples in nice aspect. you could ultimately cease suffering to piece jointly examples you may have chanced on on-line. With this publication in hand, you are going to examine adequate of the center ideas to conceive of and construct your individual visualizations from scratch.

The booklet starts with the fundamentals of placing strains at the reveal, and builds in this starting place all of the solution to developing interactive lively visualizations utilizing d3.js layouts.

You will find out how to use d3.js to control vector portraits with SVG, format with HTML, and styling with CSS. you are going to look at the fundamentals of practical programming and utilizing information buildings successfully – every thing from dealing with time to doing geographic projections. The ebook also will assist in making your visualizations interactive and train you ways automatic layouts fairly work.

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

What you are going to research from this book

  • Draw with SVG shapes and course generators
  • Add types with HTML and CSS
  • Use facts constructions effectively
  • Dynamically replace visualizations as facts changes
  • Animate visualizations
  • Let the consumer discover your data
  • Use layouts to create advanced drawings
  • Learn to spot what makes a superb visualization good

Approach

This ebook is a mini educational with lots of code examples and techniques to offer you several ideas whilst development your individual visualizations.

Who this e-book is written for

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

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Additional info for Data Visualization with d3.js

Sample text

Then we simply return either 'green' or 'red' based on the current index. One thing to keep in mind is that chaining selections can be more efficient than OR selectors when it comes to very large documents. This is because each subsequent selection only searches through the elements matched previously. Manipulating content We can do far more than just playing around with selections and changing the properties of the elements. We can manipulate things. js, we can change the contents of an element, add new elements, or remove elements we don't want.

Without going into too much mathematical detail, it suffices to say that transformations, as used in SVG, are affine transformations of coordinate systems used by shapes in our drawing. The beautiful thing is they can be defined as matrix multiplications, making them very efficient to compute. But, unless your brain is made out of linear algebra, using transformations as matrices can get very tricky. SVG helps out by coming with a set of predefined transformations, namely, translate(), scale(), rotate(), skewX(), and skewY().

Figured out the pattern yet? Read the top row of the table body. remove(). remove() You have to use [0][3] instead of just [3] because selections are arrays of arrays. Joining data to selections We've made it to the fun part of our DOM shenanigans. Remember when I said HTML is data visualization? Joining data to selections is how that happens. data() function. js how to differentiate between various parts of the data. When you join data to a selection, one of the following three things will happen: • There is more data than was already joined (the length of the data is longer than the length of a selection).

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