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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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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 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

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 JPype1 package offers a solution, and can be downloaded from http://pypi.python.org/pypi/JPype1 or http://github.com/originell/jpype. You can install JPype1 with the following command:

$ pip3 install JPype1 

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

jpype.startJVM(jpype.getDefaultJVMPath()) 

Create a JPype array JArray with some random values:

values = np.random.randn(7) 
java_array = jpype.JArray(jpype.JDouble,...
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