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# Boxplot Demo

Example boxplot code

    import numpy as np
    import matplotlib.pyplot as plt

    # Fixing random state for reproducibility
    np.random.seed(19680801)

    # fake up some data
    spread = np.random.rand(50) * 100
    center = np.ones(25) * 50
    flier_high = np.random.rand(10) * 100 + 100
    flier_low = np.random.rand(10) * -100
    data = np.concatenate((spread, center, flier_high, flier_low), 0)

    fig1, ax1 = plt.subplots()
    ax1.set_title('Basic Plot')
    ax1.boxplot(data)

    fig2, ax2 = plt.subplots()
    ax2.set_title('Notched boxes')
    ax2.boxplot(data, notch=True)

    green_diamond = dict(markerfacecolor='g', marker='D')
    fig3, ax3 = plt.subplots()
    ax3.set_title('Changed Outlier Symbols')
    ax3.boxplot(data, flierprops=green_diamond)

    fig4, ax4 = plt.subplots()
    ax4.set_title('Hide Outlier Points')
    ax4.boxplot(data, showfliers=False)

    red_square = dict(markerfacecolor='r', marker='s')
    fig5, ax5 = plt.subplots()
    ax5.set_title('Horizontal Boxes')
    ax5.boxplot(data, vert=False, flierprops=red_square)

    fig6, ax6 = plt.subplots()
    ax6.set_title('Shorter Whisker Length')
    ax6.boxplot(data, flierprops=red_square, vert=False, whis=0.75)

    # fake up some more data
    spread = np.random.rand(50) * 100
    center = np.ones(25) * 40
    flier_high = np.random.rand(10) * 100 + 100
    flier_low = np.random.rand(10) * -100
    d2 = np.concatenate((spread, center, flier_high, flier_low), 0)
    data.shape = (-1, 1)
    d2.shape = (-1, 1)

    # Making a 2-D array only works if all the columns are the
    # same length.  If they are not, then use a list instead.
    # This is actually more efficient because boxplot converts
    # a 2-D array into a list of vectors internally anyway.
    data = [data, d2, d2[::2,0]]
    fig7, ax7 = plt.subplots()
    ax7.set_title('Multiple Samples with Different sizes')
    ax7.boxplot(data)

    plt.show()

Total running time of the script: ( 0 minutes 0.219 seconds)

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