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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.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Length 360 pages
Edition 1st Edition
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Author (1):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
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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

Sharing your Notebook


One of the most amazing features of Wakari is that we can share our notebooks with other Wakari users and they can import it into their accounts. This feature makes Wakari an excellent choice for teaching a workshop or for a presentation.

The data

When our IPython Notebook is ready, we can share it with other Wakari users just by clicking on the Share button, next to the name of our notebook in the resources tab.

In the following screenshot we can see the Sharing window, where we may change the name and add a description to our notebook. For paid accounts, we can also include a password to keep our notebook private.

Once we are ready, we will click on the Submit button. We will see in the Sharing Status window that the process is complete and we can click on Link to the bundle to see our notebook shared (see the following screenshot):

After clicking on Link to the bundle, we will see our IPython Notebook Intro to Pandas as a read-only file. If we click on the Run/Edit this...

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