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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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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 (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 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

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 nineties, 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/. MPI 2.0.2 was installed and used 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=/usr/local
...
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