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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 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

Installing Cython

The Cython programming language acts as glue between Python and C/C++. With the Cython tools, we can generate C code from plain Python code, which can then be compiled into binary, which is closer to the machine level. The cytoolz package contains utilities created by Cythonizing the handy Python toolz package. The following command will install cython and cytoolz:

$ pip3 install cython cytoolz

Just as in cooking shows, we will show the results of Cythonizing before going through the process involved (deferred to the next section). The timeit Python module measures time. We will use this module to measure different functions. Define the following function, which accepts a short code snippet, a function call, and the number of times the code will run as arguments:

def time(code, n): 
    times = min(timeit.Timer(code, setup=setup).repeat(3, n)) 
 
    return round(1000* np.array(times)/n, 3) 

Next, we predefine a large setup string containing all the code. The code is in...

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