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# Table Demo

Demo of table function to display a table within a plot.

    import numpy as np
    import matplotlib.pyplot as plt

    data = [[  66386,  174296,   75131,  577908,   32015],
            [  58230,  381139,   78045,   99308,  160454],
            [  89135,   80552,  152558,  497981,  603535],
            [  78415,   81858,  150656,  193263,   69638],
            [ 139361,  331509,  343164,  781380,   52269]]

    columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
    rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]

    values = np.arange(0, 2500, 500)
    value_increment = 1000

    # Get some pastel shades for the colors
    colors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))
    n_rows = len(data)

    index = np.arange(len(columns)) + 0.3
    bar_width = 0.4

    # Initialize the vertical-offset for the stacked bar chart.
    y_offset = np.array([0.0] * len(columns))

    # Plot bars and create text labels for the table
    cell_text = []
    for row in range(n_rows):
        plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])
        y_offset = y_offset + data[row]
        cell_text.append(['%1.1f' % (x/1000.0) for x in y_offset])
    # Reverse colors and text labels to display the last value at the top.
    colors = colors[::-1]
    cell_text.reverse()

    # Add a table at the bottom of the axes
    the_table = plt.table(cellText=cell_text,
                          rowLabels=rows,
                          rowColours=colors,
                          colLabels=columns,
                          loc='bottom')

    # Adjust layout to make room for the table:
    plt.subplots_adjust(left=0.2, bottom=0.2)

    plt.ylabel("Loss in ${0}'s".format(value_increment))
    plt.yticks(values * value_increment, ['%d' % val for val in values])
    plt.xticks([])
    plt.title('Loss by Disaster')

    plt.show()

Total running time of the script: ( 0 minutes 0.045 seconds)

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