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Practical Data Analysis

You're reading from   Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

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Product type Paperback
Published in Sep 2016
Publisher
ISBN-13 9781785289712
Length 338 pages
Edition 2nd Edition
Languages
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Authors (2):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Dr. Sampath Kumar Dr. Sampath Kumar
Author Profile Icon Dr. Sampath Kumar
Dr. Sampath Kumar
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Preprocessing Data 3. Getting to Grips with Visualization 4. Text Classification 5. Similarity-Based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Diseases with Cellular Automata 10. Working with Social Graphs 11. Working with Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with Jupyter and Wakari 15. Understanding Data Processing using Apache Spark

Implementation in D3js


In this chapter, we will create an animation in D3.js of a Brownian motion Random Walk simulation. In the simulation, we will control the delay of the animation, the starting point of the Random Walk, and the tendency of the up-down factor.

First, we need to create an HTML file named Simulation.html, and we will run it from Python http.server. In order to run the animation, we just need to open a Command Terminal and run the following command:

>>python -m http.server 8000

Open a web browser and type the direction http://localhost:8000 and select our HTML file; then, we can see the animation running.

First, we need to import the D3 library either directly from the website or with a local copy of the d3.v3.min.js file:

<script type="text/javascript" src="http://d3js.org/d3.v3.min.js"></script> 

In the CSS, we specified the style for the axis line, the font family and size for the text, and the background color:

<style type="text/css"> 
body...
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