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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

Spectral analysis


In the previous section, we charted the amplitude spectrum of the dataset. The power spectrum of a physical signal visualizes the energy distribution of the signal. We can modify the code easily to plot the power spectrum, just by squaring the values as follows:

plt.plot(transformed ** 2, label="Power Spectrum") 

The phase spectrum visualizes the phase (the initial angle of a sine function) and can be plotted as follows:

plt.plot(np.angle(transformed), label="Phase Spectrum") 

Refer to the following graph for the end result:

Please refer to the ch-07.ipynb file in this book's code bundle for the complete code.

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