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      "cell_type": "markdown",
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      "source": [
        "\n# Table Demo\n\nDemo of table function to display a table within a plot.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\ndata = [[ 66386, 174296,  75131, 577908,  32015],\n        [ 58230, 381139,  78045,  99308, 160454],\n        [ 89135,  80552, 152558, 497981, 603535],\n        [ 78415,  81858, 150656, 193263,  69638],\n        [139361, 331509, 343164, 781380,  52269]]\n\ncolumns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')\nrows = ['%d year' % x for x in (100, 50, 20, 10, 5)]\n\nvalues = np.arange(0, 2500, 500)\nvalue_increment = 1000\n\n# Get some pastel shades for the colors\ncolors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))\nn_rows = len(data)\n\nindex = np.arange(len(columns)) + 0.3\nbar_width = 0.4\n\n# Initialize the vertical-offset for the stacked bar chart.\ny_offset = np.zeros(len(columns))\n\n# Plot bars and create text labels for the table\ncell_text = []\nfor row in range(n_rows):\n    plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])\n    y_offset = y_offset + data[row]\n    cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset])\n# Reverse colors and text labels to display the last value at the top.\ncolors = colors[::-1]\ncell_text.reverse()\n\n# Add a table at the bottom of the Axes\nthe_table = plt.table(cellText=cell_text,\n                      rowLabels=rows,\n                      rowColours=colors,\n                      colLabels=columns,\n                      loc='bottom')\n\n# Adjust layout to make room for the table:\nplt.subplots_adjust(left=0.2, bottom=0.2)\n\nplt.ylabel(f\"Loss in ${value_increment}'s\")\nplt.yticks(values * value_increment, ['%d' % val for val in values])\nplt.xticks([])\nplt.title('Loss by Disaster')\n\nplt.show()"
      ]
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