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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
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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Table of Contents (16) Chapters Close

Preface 1. NumPy Quick Start 2. Beginning with NumPy Fundamentals FREE CHAPTER 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

Time for action – shading plot regions based on a condition

Imagine that you want to shade a 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 one 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 on 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 as shown by setting...

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