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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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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

Installing MPI for Python

The Message Passing Interface (MPI) (see http://en.wikipedia.org/wiki/Message_Passing_Interface) is a standard protocol developed by experts to work on a broad assortment of distributed machines. Originally, in the '90s, MPI was used to write programs in Fortran and C. MPI is independent of hardware and programming languages. MPI functions include the send and receive operations, MapReduce functionality, and synchronization. MPI has point-to-point functions involving two processors and operations involving all processors. MPI has bindings for several programming languages, including Python. Download MPI from http://www.open-mpi.org/software/ompi/v1.8/ 1.8.1. MPI 1.8.1 was the latest MPI version at the time of writing. We can check on the website whether there is a newer version available. Installing MPI can take a while (nearly 30 minutes). The following are the commands involved, assuming that we install it in the /usr/local directory:

$ ./configure --prefix...
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