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Practical Business Intelligence

You're reading from  Practical Business Intelligence

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781785885433
Pages 352 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Practical Business Intelligence
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Practical Business Intelligence 2. Web Scraping 3. Analysis with Excel and Creating Interactive Maps and Charts with Power BI 4. Creating Bar Charts with D3.js 5. Forecasting with R 6. Creating Histograms and Normal Distribution Plots with Python 7. Creating a Sales Dashboard with Tableau 8. Creating an Inventory Dashboard with QlikSense 9. Data Analysis with Microsoft SQL Server

Blending D3 and data


The ultimate goal with any visualization is to incorporate actual data elements within the components. Earlier examples showed D3 elements with data points set up inside of the attributes. The next example will highlight creating the same visualization of four bar charts while assigning the height to a variable.

Visualizing hardcoded data

We will start with a new blank template for D3, with only a <body> tag and a <script> tag. All coding will now be inside the <script> tag.

First off, we will assign a couple of variables that will come into play as we put together the bar chart:

var svgHeight = 500; 
var svgWidth = 500; 
var barHeight = [100,200,300,400]; 
var barDistance = 25; 

svgHeight and svgWidth are two variables that we will use to create dimensions for the canvas that we will be working with inside of the browser. Similar to previous examples, it will be a 500 x 500 square. The barHeight variable is the data that we will use to assign a specific...

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