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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Setting up Google App Engine

Cloud computing was briefly mentioned in the introduction to this chapter. Google App Engine (GAE) is one of the offerings in that area. GAE puts each application made by users in separate sandboxes located somewhere in the Google data centers (Google Cloud). GAE automatically scales application resources according to the number of requests. GAE supports several Python web frameworks and numerical software such as NumPy.

To use GAE, we need a Google account, which is free. Download the GAE tools and libraries for various operating systems from https://developers.google.com/appengine/downloads. From this web page, we can download documentation and the GAE Eclipse plugin as well. For developers who use the Eclipse IDE, the plugin is recommended. The GAE Standard Development Kit (SDK) provides a development environment, which mimics the Google Cloud. GAE at the moment supports Python 2.7 only. We can manage GAE apps either with Python scripts or using a GUI, which...

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