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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

Sending NumPy arrays to Java

Like Python, Java is a very popular programming language. We installed Java in Chapter 8, Working with Databases, as a prerequisite to using Cassandra. To run Java code, we need the Java Runtime Environment (JRE). For development, the Java Development Kit (JDK) is required.

Jython is an implementation of Python written in Java. Jython code can use any Java class. However, Python modules written in C cannot be imported in Jython. This is an issue, because many numerical and data analysis Python libraries have modules written in C. The JPype package offers a solution and can be downloaded from http://pypi.python.org/pypi/JPype1 or http://github.com/originell/jpype. The most current JPype version at the time of writing was 0.5.5.2. Once you have downloaded and unpacked JPype, run the following command:

$ python setup.py install

Start the Java Virtual Machine (JVM) with the following line:

jpype.startJVM(jpype.getDefaultJVMPath())

Create a JPype array JArray with some...

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