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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 FREE CHAPTER 2. NumPy Arrays 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

Chapter 11. Environments Outside the Python Ecosystem and Cloud Computing

Outside the Python ecosystem, programming languages such as R, C, Java, and Fortran are fairly popular. In this chapter, we will delve into the particulars of exchanging information with these environments.

Cloud computing aims to deliver computing power as a utility over the Internet. This means that we don't need to have a lot of powerful hardware locally. Instead, we pay as we go—depending on our current needs. We will also talk about how to get our Python code in the Cloud. This is a rapidly evolving industry in a fast-paced world. We have many options available, of which we will cover Google App Engine and PythonAnywhere. Amazon Web Services (AWS) is deliberately not discussed in this book, since other books such as Building Machine Learning Systems with Python, Willi Richert and Luis Pedro Coelho, Packt Publishing, mentioned in the Preface, cover the topic in great detail. We should also...

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