Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Practical Data Analysis

You're reading from   Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Arrow left icon
Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Length 360 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Arrow right icon
View More author details
Toc

Table of Contents (24) Chapters Close

Practical Data Analysis
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started FREE CHAPTER 2. Working with Data 3. Data 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 Disease with Cellular Automata 10. Working with Social Graphs 11. Sentiment Analysis of Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with IPython and Wakari Setting Up the Infrastructure Index

Grouping and aggregation


In the following example we will perform grouping and aggregation in order to get statistics (sum, max, min, and avg) about NBA players and their number of points scored. First, the map function will send the name of the player and the number of points scored for each game. The map function will look similar to the following code:

function(){emit(this.player, this.points); }

Then, we can perform all the aggregation functions simultaneously using the method sum from the JavaScript Array object and the max/min functions of the JavaScript Math object. The reduce function will look similar to the following code:

function(key, values) {
  var explain = {total:Array.sum(values),
    max:Math.max.apply(Math, values),
    min:Math.min.apply(Math, values),
    avg:Array.sum(values)/values.length}
  return explain
}

For this example we will create synthetic data, randomly mixing the name of the 10 players and we will assign a random score between 0 and 100. Then, we will insert...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image