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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 2. Preprocessing Data FREE CHAPTER 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

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 them 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:

The data

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 Link to the bundle to see our notebook being shared, as shown in the following screenshot:

The data

After clicking on Link to the bundle, we will see our IPython notebook Intro to Pandas as read-only. If we click on the...

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