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NumPy Beginner's Guide

You're reading from   NumPy Beginner's Guide An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library.

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Product type Paperback
Published in Apr 2013
Publisher Packt
ISBN-13 9781782166085
Length 310 pages
Edition 2nd 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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Table of Contents (19) Chapters Close

Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Get in Terms with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Move Further with NumPy Modules 7. Peeking into Special Routines 8. Assure Quality with Testing 9. Plotting with Matplotlib 10. When NumPy is Not Enough – SciPy and Beyond 11. Playing with Pygame Pop Quiz Answers Index

Time for action – shading plot regions based on a condition


Imagine that you want to shade the region of a stock chart, where the closing price is below average, with a different color than when it is above the mean. The fill_between function is the best choice for the job. We will again omit the steps of downloading historical data going back 1 year, extracting dates and close prices, and creating locators and date formatter.

  1. Create a Matplotlib figure object.

    fig = plt.figure()
  2. Add a subplot to the figure.

    ax = fig.add_subplot(111)
  3. Plot the closing price.

    ax.plot(dates, close)
  4. Shade the regions of the plot below the closing price using different colors depending whether the values are below or above the average price.

    plt.fill_between(dates, close.min(), close, where=close>close.mean(), facecolor="green", alpha=0.4)
    plt.fill_between(dates, close.min(), close,
      where=close<close.mean(), facecolor="red", alpha=0.4)

    Now we can finish the plot by setting locators and formatting the x-axis values...

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