Forked from fonnesbeck/3. Plotting and Visualization.ipynb
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November 22, 2013 18:23
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{ | |
"metadata": { | |
"name": "3. Plotting and Visualization" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"import pandas as pd\n", | |
"import numpy as np\n", | |
"\n", | |
"# Set some Pandas options\n", | |
"pd.set_option('display.notebook_repr_html', False)\n", | |
"pd.set_option('display.max_columns', 20)\n", | |
"pd.set_option('display.max_rows', 25)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 1 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Plotting and Visualization\n", | |
"\n", | |
"There are a handful of third-party Python packages that are suitable for creating scientific plots and visualizations. These include packages like:\n", | |
"\n", | |
"* matplotlib\n", | |
"* Chaco\n", | |
"* PyX\n", | |
"* Bokeh\n", | |
"\n", | |
"Here, we will focus excelusively on matplotlib and the high-level plotting availabel within pandas. It is currently the most robust and feature-rich package available.\n", | |
"\n", | |
"### Visual representation of data\n", | |
"\n", | |
"We require plots, charts and other statistical graphics for the written communication of quantitative ideas.\n", | |
"\n", | |
"They allow us to more easily convey relationships and reveal deviations from patterns.\n", | |
"\n", | |
"Gelman and Unwin 2011:\n", | |
"\n", | |
"> A well-designed graph can display more information than a table of the same size, and more information than numbers embedded in text. Graphical displays allow and encourage direct visual comparisons." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Matplotlib\n", | |
"\n", | |
"The easiest way to interact with matplotlib is via `pylab` in iPython. By starting iPython (or iPython notebook) in \"pylab mode\", both matplotlib and numpy are pre-loaded into the iPython session:\n", | |
"\n", | |
" ipython notebook --pylab\n", | |
" \n", | |
"You can specify a custom graphical backend (*e.g.* qt, gtk, osx), but iPython generally does a good job of auto-selecting. Now matplotlib is ready to go, and you can access the matplotlib API via `plt`. If you do not start iPython in pylab mode, you can do this manually with the following convention:\n", | |
"\n", | |
" import matplotlib.pyplot as plt" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.plot(np.random.normal(size=100), np.random.normal(size=100), 'ro')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 2, | |
"text": [ | |
"[<matplotlib.lines.Line2D at 0x105e80510>]" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
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umXX//ve/ceTIEQwPDyMjIwN5eXlR5924RZ+ISHHc2UlEpDgGORGR4hjkRESK\nY5ATESmOQU5EpDgGORGR4hjkRESKY5ATESnu/wHtjgZKp/Gb5gAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x105a4cbd0>" | |
] | |
} | |
], | |
"prompt_number": 2 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The above plot simply shows two sets of random numbers taken from a normal distribution plotted against one another. The `'ro'` argument is a shorthand argument telling matplotlib that I wanted the points represented as red circles.\n", | |
"\n", | |
"This plot was expedient. We can exercise a little more control by breaking the plotting into a workflow:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"with mpl.rc_context(rc={'font.family': 'serif', 'font.weight': 'bold', 'font.size': 8}):\n", | |
" fig = plt.figure(figsize=(6,3))\n", | |
" ax1 = fig.add_subplot(121)\n", | |
" ax1.set_xlabel('some random numbers')\n", | |
" ax1.set_ylabel('more random numbers')\n", | |
" ax1.set_title(\"Random scatterplot\")\n", | |
" plt.plot(np.random.normal(size=100), np.random.normal(size=100), 'r.')\n", | |
" ax2 = fig.add_subplot(122)\n", | |
" plt.hist(np.random.normal(size=100), bins=15)\n", | |
" ax2.set_xlabel('sample')\n", | |
" ax2.set_ylabel('cumulative sum')\n", | |
" ax2.set_title(\"Normal distrubution\")\n", | |
" plt.tight_layout()\n", | |
" plt.savefig(\"normalvars.png\", dpi=150)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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HJycnmaH3jDEUFxerMSpCtBuvhKaKDmxCujIfHx+8/fbbzZYfPnxYDdEQoht4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\nG/dvS0vLdh/DysoKVlZW3LOmgIYvppGREe99pKe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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x105e5fdd0>" | |
] | |
} | |
], | |
"prompt_number": 3 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"matplotlib is a relatively low-level plotting package, relative to others. It makes very few assumptions about what constitutes good layout (by design), but has a lot of flexiblility to allow the user to completely customize the look of the output.\n", | |
"\n", | |
"If you want to make your plots look pretty like mine, steal the *matplotlibrc* file from [Huy Nguyen](http://www.huyng.com/posts/sane-color-scheme-for-matplotlib/).\n", | |
"\n", | |
"## Plotting in Pandas\n", | |
"\n", | |
"On the other hand, Pandas includes methods for DataFrame and Series objects that are relatively high-level, and that make reasonable assumptions about how the plot should look." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"normals = pd.Series(np.random.normal(size=10))\n", | |
"normals.plot()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 4, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x105e6ce10>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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yVlOmXiPajttAipMQFF5owTduiu1TZMFinPhCCV8iKkzUIZPwndFxEWi2O2Cx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\nGwAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x10614a350>" | |
] | |
} | |
], | |
"prompt_number": 4 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Notice that by default a line plot is drawn, and a light grid is included. All of this can be changed, however:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"normals.cumsum().plot(grid=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 5, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x1061818d0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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chJAAEzAM8tNUqG0y4Ve5VFokFLhN+OXl5Zc9QFRUFAoKCrBp06Zxz6nVahiN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\nRK5CYII=\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106174bd0>" | |
] | |
} | |
], | |
"prompt_number": 5 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Similarly, for a DataFrame:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"variables = pd.DataFrame({'normal': np.random.normal(size=100), \n", | |
" 'gamma': np.random.gamma(1, size=100), \n", | |
" 'poisson': np.random.poisson(size=100)})\n", | |
"variables.cumsum(0).plot()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 6, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x1061a91d0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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fkf/2p3inJND/9WfwHd7f1s0SfkckfzsiejQWPSEWm7IrGB2tIMzb5Q/3s+dY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\n8SeEEA79FxhQhBO3FkSMAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x1061a9710>" | |
] | |
} | |
], | |
"prompt_number": 6 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"As an illustration of the high-level nature of Pandas plots, we can split multiple series into subplots with a single argument for `plot`:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"variables.cumsum(0).plot(subplots=True)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 7, | |
"text": [ | |
"array([<matplotlib.axes.AxesSubplot object at 0x10632ecd0>,\n", | |
" <matplotlib.axes.AxesSubplot object at 0x1063b4150>,\n", | |
" <matplotlib.axes.AxesSubplot object at 0x1063d6c90>], dtype=object)" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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3exMFBQUcO3aM7777jqdPn/Lpp58yduxYWZAuFBcXR8+ePdm8eXOxVNGNGzey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\nrHoy/wAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x105f9c710>" | |
] | |
} | |
], | |
"prompt_number": 7 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Or, we may want to have some series displayed on the secondary y-axis, which can allow for greater detail and less empty space:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"variables.cumsum(0).plot(secondary_y='normal')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 8, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106423b90>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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9gJ/fNNbRy7E7JouVP28vYWacnCfmjiJRMXyup57Q5JWQ/bu/IvXzIeP5x+2S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\nCLEZhQYhhBCbUWgQQgixGYUGIYQQm/0fop/VnMR1nz0AAAAASUVORK5CYII=\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106323450>" | |
] | |
} | |
], | |
"prompt_number": 8 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"If we would like a little more control, we can use matplotlib's `subplots` function directly, and manually assign plots to its axes:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12, 4))\n", | |
"for i,var in enumerate(['normal','gamma','poisson']):\n", | |
" variables[var].cumsum(0).plot(ax=axes[i], title=var)\n", | |
"axes[0].set_ylabel('cumulative sum')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 9, | |
"text": [ | |
"<matplotlib.text.Text at 0x1064ebbd0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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3nbdYzgb4lq+q2YCF31dgyfQMFCRH+jmZb9frgJxqUGexu5SdAEBUhACtRqvf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\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x1064df4d0>" | |
] | |
} | |
], | |
"prompt_number": 9 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Bar plots\n", | |
"\n", | |
"Bar plots are useful for displaying and comparing measurable quantities, such as counts or volumes. In Pandas, we just use the `plot` method with a `kind='bar'` argument.\n", | |
"\n", | |
"For this series of examples, let's load up the Titanic dataset:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic = pd.read_excel(\"data/titanic.xls\", \"titanic\")\n", | |
"titanic.head()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 10, | |
"text": [ | |
" pclass survived name sex \\\n", | |
"0 1 1 Allen, Miss. Elisabeth Walton female \n", | |
"1 1 1 Allison, Master. Hudson Trevor male \n", | |
"2 1 0 Allison, Miss. Helen Loraine female \n", | |
"3 1 0 Allison, Mr. Hudson Joshua Creighton male \n", | |
"4 1 0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) female \n", | |
"\n", | |
" age sibsp parch ticket fare cabin embarked boat body \\\n", | |
"0 29.0000 0 0 24160 211.3375 B5 S 2 NaN \n", | |
"1 0.9167 1 2 113781 151.5500 C22 C26 S 11 NaN \n", | |
"2 2.0000 1 2 113781 151.5500 C22 C26 S NaN NaN \n", | |
"3 30.0000 1 2 113781 151.5500 C22 C26 S NaN 135 \n", | |
"4 25.0000 1 2 113781 151.5500 C22 C26 S NaN NaN \n", | |
"\n", | |
" home.dest \n", | |
"0 St Louis, MO \n", | |
"1 Montreal, PQ / Chesterville, ON \n", | |
"2 Montreal, PQ / Chesterville, ON \n", | |
"3 Montreal, PQ / Chesterville, ON \n", | |
"4 Montreal, PQ / Chesterville, ON " | |
] | |
} | |
], | |
"prompt_number": 10 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.groupby('pclass').survived.sum().plot(kind='bar')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 11, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106702d90>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x106702150>" | |
] | |
} | |
], | |
"prompt_number": 11 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.groupby(['sex','pclass']).survived.sum().plot(kind='barh')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 12, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106751190>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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l1zxL0GiMnN/I2cF/87duGkzb0Eb1kKhmjP4+PU9uTnf7fXrXP6pLz5SsG0Z+\nOsOu/B+IizXuXxwj5zdydlB+8R63R3pS9ywWC7169fJ2DBERQ6n3x5CJiIjcDlT0pNaMfq+PkfMb\nOTsov7cZPb8nVPRERMRvqKfnRerpiYjUnHp6IiIiblDRk1ozel/AyPmNnB2U39uMnt8Tbt+nJ/Xj\nh6Jz3o5Qa46WnZTfS4ycHXwnv6/cLC4NR0XPy2Z8meftCB464+0AHjJyfiNnB1/InzY0ulZFz8hP\nMwHj5/eEpjdFRMRvqOiJiNSQ0XtiRs/vCRU9ERHxGyp6IiI1ZPSemNHze0JFT0RE/IaKnohIDRm9\nJ2b0/J5Q0RMREb/RYPfpORwOZs+ezZtvvonJZGLLli1kZGTQs2dPEhMT6+WcS5YsoXfv3tx///01\n3vfbb79ly5YtALRr147hw4ff8C3xZ8+e5b333uPcuXNER0czbtw4zGYzGRkZFBcX8/jjj3v8PUTE\ntxi9J2b0/J5osJFeVlYWPXr0wGQyAfD555/z1ltv1VvBAzCZTK7z1VSbNm2YM2cOaWlpxMXF8cc/\n/vGG261evZohQ4awcOFCAgIC2LlzJwB9+/YlIyMDPc9bRMR3NNhIz2KxMHr0aAAWLFhAWVkZr7zy\nCsOGDaNnz54sX76cEydOEBgYyPjx44mOjmb9+vWUlJRQWFiI1WolKSmJAwcOkJmZSffu3UlKSsJk\nMvHpp5+yd+9eAOLj43nyySdd571SdPLz81m5ciXl5eVERETw4osvEhoaWm3emJgY15979erFf/zH\nf1TZxul0kpOTw+TJkwF4+OGH2bBhA48++iiBgYF06tSJ/fv3ExcX5/kPKCI+Y9euXYYeLRk9vyca\nbKRXUFBAVFQUALNmzSI4OJjU1FT69+/P6tWrGTRoEIsXL2bSpEls2LDBtd/hw4dJTk5mwoQJLFq0\niMjISBYuXMjJkyc5evQoAI899hjz589n3rx55OXluQogXB7tVVZWsnTpUqZOncq7775Lnz59+Prr\nr93OvnPnTuLj46t8fu7cOZo0aYLZfPlnDA8Px2q1uta3a9fOlVFERLyvQUZ6FRUVmM1mV3G43v79\n+yksLHQVu/Lyci5duoTJZCI+Pp7GjRsTExODzWZjwIABmEwmoqOjOXToEF26dCE/P5+vvvqKoqIi\nKioqOH78OL179wYuj8aKioo4c+YMCxYsAC73F1u1auVW9r/97W98++23vPXWWzX+3m3atCEzM7PG\n+4mIbzNCRgEGAAAPKklEQVT6KMno+T3RIEXPZDLdsrc1c+ZMIiIiqnweEhICQGBgIEFBQQQFBbmW\nKysrAVi1ahVTp06lQ4cOrFmzBpvNds25AZo2bUpqamqNchcUFPDhhx/yyiuv0KRJkyrrmzVrRnl5\nOQ6HA7PZjNVqJTw83LVe/TwR31ZaWgpRzYC/X8Z/pSBo2beXa6tBil7jxo1xOBzY7XYCAgKqrI+L\ni2Pbtm089dRTBAUFcezYMTp16nTL4zqdTmw2GxcuXKB169ZYrVaysrIYOHDgNdtdmVbdvXs3/fr1\nw263c/LkSdq1a8f27duBy1OkVysuLmbRokVMmjSJyMjIG57fZDLRo0cPdu/eTf/+/UlPT6dPnz6u\n9adOnXKdW0R8T/PmzV1/vv4f05st36gnZqRlo+f3RIP19Dp27EhRUZFr+eqrKseOHUtxcTFTpkxh\n6tSprisgr9/u+isxTSYTQUFBDBs2jJdffpnFixdz3333VTl3YGAgM2bM4IsvvmDy5MnMmjWLQ4cO\nAVBYWHjDC1o+/fRTzp8/z0cffcTMmTN5+eWXXevmz59PSUkJAGPGjGHHjh1MmzYNu93O4MGDXdsV\nFhbSuXNnt38jERGpXyZnA83B7dmzhyNHjjBq1KiGOJ3bUlJSmDFjxg1HoJ6w2Wy89tprpKSkVHvb\nhMViITm7drdUiIjn0oZGE/f/05tiHNnZ2SQkJNRq3wYb6cXHx5Obm+tzfa7k5OQ6L3gAmZmZrotu\nRETENzRY0TObzcydO9dvikD//v31NBaR25TRn11p9Pye0LM3RUTEb6joiYjUkNHvczN6fk+o6ImI\niN9Q0RMRqSGj98SMnt8TKnoiIuI3VPRERGrI6D0xo+f3hIqeiIj4jQZ7n57cWNrQaG9HqLXS0tJr\nnl1oNEbOb+Ts4Dv5WzcNrtV+Rn8fndHze0JFz8uM/AikXfk/EBdr3L84Rs5v5Oxg/PxiXA327E2p\nymKx0KtXL2/HEBExFEM8e1NERMTbVPSk1ox+r4+R8xs5Oyi/txk9vydU9ERExG+op+dF6umJiNSc\nenoiIiJuUNGTWjN6X8DI+Y2cHZTf24ye3xO6T8/Lfig65+0IteZo2Un5vcTI2UH5vc2I+Vs3DaZt\naCOPj6Oi52UzvszzdgQPnfF2AA8ZOb+Rs4Pye5ux8qcNja6ToqfpTRER8RsqeiIi4jdU9ERExG+o\n6ImIiN9Q0RMREb+hoiciIn5DRU9ERPxGgxU9h8PB66+/zpVHfW7ZsoXk5GTWrVtXb+dcsmQJu3fv\nrtW+hYWFvPrqq/z+979n69at1W539uxZ5syZw/Tp01m+fDkOhwOAjIwMtmzZUqtzi4hI/WiwopeV\nlUWPHj0wmUwAfP7557z11lskJibW2zlNJpPrfDXVrFkznnnmGX73u9/ddLvVq1czZMgQFi5cSEBA\nADt37gSgb9++ZGRkoOd5i4j4jgZ7IovFYmH06NEALFiwgLKyMl555RWGDRtGz549Wb58OSdOnCAw\nMJDx48cTHR3N+vXrKSkpobCwEKvVSlJSEgcOHCAzM5Pu3buTlJSEyWTi008/Ze/evQDEx8fz5JNP\nus57pejk5+ezcuVKysvLiYiI4MUXXyQ0NLTavKGhoYSGhpKdnV3tNk6nk5ycHCZPngzAww8/zIYN\nG3j00UcJDAykU6dO7N+/n7i4OI9/PxER8VyDjfQKCgqIiooCYNasWQQHB5Oamkr//v1ZvXo1gwYN\nYvHixUyaNIkNGza49jt8+DDJyclMmDCBRYsWERkZycKFCzl58iRHjx4F4LHHHmP+/PnMmzePvLw8\nVwGEy6O9yspKli5dytSpU3n33Xfp06cPX3/9tcff6dy5czRp0gSz+fLPGB4ejtVqda1v166dK6OI\niHhfg4z0KioqMJvNruJwvf3791NYWOgqduXl5Vy6dAmTyUR8fDyNGzcmJiYGm83GgAEDMJlMREdH\nc+jQIbp06UJ+fj5fffUVRUVFVFRUcPz4cXr37g1cHo0VFRVx5swZFixYAFzuL7Zq1arev3ebNm3I\nzMys9/OIiNzuSktL2ZX/A7/5zW88Ok6DFD2TyXTL3tbMmTOJiIio8nlISAgAgYGBBAUFERQU5Fqu\nrKwEYNWqVUydOpUOHTqwZs0abDbbNecGaNq0KampqXXyfa5o1qwZ5eXlOBwOzGYzVquV8PBw13r1\n80RE6kbz5s2Ji/Ws4EEDTW82btwYh8OB3W6/4fq4uDi2bdvmKlbHjh1z67hOpxObzcaFCxdo3bo1\nVquVrKysKttdmVbdvXs3TqeTyspKjh8/DsD27dvZvn37Tc9RHZPJRI8ePVxXiKanp9OnTx/X+lOn\nTrnOLSIi3tdgPb2OHTtSVFTkWr76qsqxY8dSXFzMlClTmDp1qusKyOu3u/5KTJPJRFBQEMOGDePl\nl19m8eLF3HfffVXOHRgYyIwZM/jiiy+YPHkys2bN4tChQ8DlWxNudEFLSUkJEyZM4IsvvmDjxo1M\nmDCBixcvAjB//nxKSkoAGDNmDDt27GDatGnY7XYGDx7sOkZhYSGdO3eu0e8kIiL1x+RsoDm4PXv2\ncOTIEUaNGtUQp3NbSkoKM2bMICAgoE6Pa7PZeO2110hJSan2tgmLxUJydu1uqRAR8SdpQ6OJi2oG\nQHZ2NgkJCbU6ToON9OLj48nNzfW5PldycnKdFzyAzMxM10U3IiLiGxrsPj2z2czcuXMb6nRe179/\nf29HEBGR6+jZmyIi4jdU9ERExG+o6ImIiN9Q0RMREb+hoiciIn5DRU9ERPyGip6IiPiNBrtPT24s\nbWi0tyPUWmlpKc2bN/d2jFozcn4jZwfl9zYj5m/dNLhOjqOi52VXHqtjRLvyf6iTp557i5HzGzk7\nKL+3GT2/Jxrs2ZtSlcVioVevXt6OISJiKIZ49qaIiIi3qehJre3atcvbETxi5PxGzg7K721Gz+8J\nFT0REfEb6ul5kXp6IiI1p56eiIiIG1T0pNaM3hcwcn4jZwfl9zaj5/eEpje9aO/evZSUlHg7hoiI\noYSFhdG7d+9a7auiJyIifkPTmyIi4jdU9ERExG+o6ImIiN9Q0RMREb+htyx4QW5uLh9//DF2u52E\nhAR++9vfejvSTRUXF7NkyRJKS0sJDQ1l4MCBDBw4kAsXLvD+++9z+vRp2rRpw6RJk7jjjju8Hbda\nDoeD5ORkwsPDSU5ONlT+ixcvsmLFCn766SdsNhvPP/887dq1M0z+nTt3kp6ejs1mIzY2ljFjxvjs\n77906VL27dtHaGgoixYtArhp1i+//JKvv/6agIAAxo4dS/fu3b0Z/4b5165dS3Z2NsHBwcTGxjJy\n5EhCQkIAY+S/YuvWraxbt46VK1fStGlToBb5ndKg7Ha7c+LEic5Tp045bTabc/r06c6ff/7Z27Fu\n6uzZs86jR486nU6ns7S01JmUlOT8+eefnWvXrnX+9a9/dTqdTuemTZuc69at82LKW9u6davzD3/4\ngzMlJcXpdDoNlf/99993WiwWp9PpdFZWVjrLy8sNk//cuXPO559/3nnhwgWn3W53vv322859+/b5\nbP7c3Fxnfn6+c+rUqa7Pqsv6888/O6dPn+602WzOU6dOOSdOnOi02+1eyX3FjfL/8MMPTrvd7rTb\n7c5ly5YZLr/T6XSeOXPG+dZbbzmff/5557lz55xOZ+3ya3qzgeXl5REZGUnr1q0JDAxkwIABZGVl\neTvWTYWFhdGpUycAQkNDueuuu7BarWRlZfHwww8DMHDgQDIzM72Y8uZ++eUX9u3bxyOPPILz/+/S\nMUr+iooKDh48yCOPPAJAQEAAISEhhskfHHz55Z8VFRVcunSJX3/9lSZNmvhs/tjYWJo0aXLNZ9Vl\nzczMZMCAAQQGBtK6dWsiIyPJy8tr8MxXu1H+e++9F7PZjNls5h/+4R/45ZdfAOPkB/jkk09ITEy8\n5rPa5Nf0ZgOzWq20bNnStRweHu71/8hq4uTJkxw/fpyYmBhKS0sJCwsDoHnz5pSWlno5XfU+/vhj\nEhMTuXDhguszo+Q/ffo0oaGhLFmyhPz8fLp27crYsWMNkz84OJikpCReeOEFgoKC+O1vf0vXrl0N\nkx+q/2/l7NmzdO3a1bVdy5YtsVqtXsnoLovF4vo/UEbJn5mZSXh4OB07drzm89rk10hP3Hbx4kXe\nffdd/vVf/7VK78VkMnkp1a3t3buX0NBQOnfu7BrlXc+X89vtdo4cOUK/fv2YP38+lZWV/M///M81\n2/hy/rKyMlasWMHixYtZsmQJhw4dYu/evdds48v5r3errL78XTZu3Mgdd9zBAw88UO02vpb/119/\nZdOmTYwcOdL1WXV/j+HW+TXSa2Dh4eGuqQW4PO0WHh7uxUTuqaysZNGiRTz44IP06dMHuPz/eEtK\nSggLC+Ps2bM0b97cyylv7Mcff2Tv3r3s27cPm83muijBKPlbtmxJ06ZNiY+PB2DAgAF88803hIWF\nGSJ/Xl4eXbt2JTIyEoAHHniAAwcOGOb3h+r/WzfS3+f09HT27dvH66+/7vrMCPlPnTrFmTNnmDFj\nBnB5tiw5OZl58+bVKr9Geg3srrvu4uTJk5w+fZrKykoyMjJc/5j5KqfTyfLly2nXrh3/+I//6Po8\nPj6e9PR0AL755htXMfQ1Tz/9NMuWLWPJkiVMnjyZHj16MGnSJMPkDwsLIzIyksOHD+NwOMjOzuae\ne+6hd+/ehsjfvXt3jhw5wvnz57HZbOzbt4+4uDjD/P5Q/X/r8fHxfPfdd1RWVnL69GlOnjxJdHS0\nF5Pe2Pfff8+WLVuYOXOmq8cKxsjfoUMHPvroI5YsWcKSJUsIDw9nwYIFhIWF1Sq/nr3pBbm5uaxZ\ns8Z1y8LQoUO9HemmDh48yOzZs+nQoYNr6uDpp5+mW7duPnnJ+c3k5uaydetWZs2a5bOXzN9IUVER\nS5YsoaysjA4dOjBp0iScTqdh8qenp/Nf//VfXLp0ibi4OEaOHMmvv/7qk/nfffddDhw4wLlz52je\nvDkjR47k/vvvv+ktCxaLxXXJfGxsrE/kLysrIywsjBEjRvDXv/6VyspK12X+MTExJCUlAb6b/+rf\nf9CgQa71EydOJCUl5ZpbFmqSX0VPRET8hqY3RUTEb6joiYiI31DRExERv6GiJyIifkNFT0RE/IaK\nnoiI+A0VPRER8RsqeiIi4jf+D8EFI4o9s1eBAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x1067666d0>" | |
] | |
} | |
], | |
"prompt_number": 12 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"death_counts = pd.crosstab([titanic.pclass, titanic.sex], titanic.survived.astype(bool))\n", | |
"death_counts.plot(kind='bar', stacked=True, color=['black','gold'], grid=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 13, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x1067d5550>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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S0tIAyM3NZcuWLSxatIg5c+awYsUKnE5nvZyIiIjcwPBLUFAQAOXl5TidTho0aEB2djb9\n+/cHYMCAAWRlZQGQlZVFQkICgYGBhIeHExERQU5OTh2WLyIil7rm8AuA0+kkOTmZ48ePM3HiRFq0\naEFJSQmhoaEA2Gw2SkpKACgqKqJjx47u94aFheFwOOqodBER+anrhnpAQACLFy+moKCAhQsX0rlz\n58u2WyyWa77/ettFRMRzbvjul/DwcHr16sWBAwew2WwUFxcD1VfnNpsNALvdTmFhofs9hYWF2O12\nD5csIiJXc81QLy0t5dy5cwCcOXOGr776inbt2hEXF0dmZiYAW7duJT4+HoC4uDh27NhBZWUlBQUF\n5OfnExMTU7dnICIibtccfikuLnbfwRIaGsrIkSOJjY0lJiaG1NRU5s6d676lESAyMpKBAweSnJyM\n1Wpl2rRpGn4REalH1wz1du3a8dJLL13xeqNGjUhKSqrxPSNGjGDEiBGeqU5ERG6KZpSKiBhEoS4i\nYhCFuoiIQRTqIiIGUaiLiBhEoS4iYhCFuoiIQRTqIiIGUaiLiBhEoS4iYhCFuoiIQRTqIiIGUaiL\niBhEoS4iYhCFuoiIQRTqIiIGUaiLiBhEoS4iYhCFuoiIQRTqIiIGUaiLiBhEoS4iYhCFuoiIQRTq\nIiIGUaiLiBhEoS4iYhCFuoiIQRTqIiIGUaiLiBhEoS4iYhCFuoiIQRTqIiIGUaiLiBhEoS4iYpBA\nbxcgIr4hoPIYFmduvRzLFRCJMzCqXo51u1GoiwgAFmcuzYpG1cuxSptvBKLq5Vi3m+uG+unTp1mx\nYgUlJSU0a9aMAQMGMGDAAMrKykhNTaWgoICWLVsyc+ZMgoODAdi0aRMZGRlYrVYmTZpEly5d6vxE\nRETkBkI9MDCQxx9/nKioKEpLS5kzZw4xMTFkZmbSuXNnkpKSSE9PJy0tjXHjxpGbm8uWLVtYtGgR\nDoeDBQsWsHTpUgICNHwvIlLXrpu0oaGhREVFAdCsWTM6dOiAw+EgOzub/v37AzBgwACysrIAyMrK\nIiEhgcDAQMLDw4mIiCAnJ6fuzkBERNxu6vI5Pz+f3NxcOnXqRElJCaGhoQDYbDZKSkoAKCoqIiws\nzP2esLAwHA6HB0sWEZGrueFQLy8v59VXX+Xxxx93j53/yGKxXPO919suIiKecUOhXllZycsvv8wv\nfvEL4uPjgeqr8+LiYqD66txmswFgt9spLCx0v7ewsBC73e7pukVEpAbXDXWXy8Xrr79OZGQkDzzw\ngPv1uLg4MjMzAdi6das77OPi4tixYweVlZUUFBSQn59PTExM3VQvIiKXue7dL4cOHeKzzz6jXbt2\nJCUlAfDYY48xZswYUlNTmTt3rvuWRoDIyEgGDhxIcnIyVquVadOmafhFRKSeXDfUu3Tpwvvvv1/j\nth9D/qdGjBjBiBEjaleZiIjcNN08LiJiEIW6iIhBFOoiIgZRqIuIGEShLiJiEC296yO0lrWIeIJC\n3UdoLWsR8QQNv4iIGEShLiJiEA2/iNwkff4hvkyhLnKT9PmH+DINv4iIGEShLiJiEIW6iIhBFOoi\nIgZRqIuIGEShLiJiEIW6iIhBFOoiIgZRqIuIGEQzSkVuUul5G6UBa+rnYOdtNGlYP4cSM/hlqNfX\n2htad0NqsuebEkaNmlAvx9q4cSP33FMvhxJD+GWo19faG1p3Q0T8jcbURUQMolAXETGIQl1ExCAK\ndRERgyjURUQMolAXETGIQl1ExCAKdRERgyjURUQM4pczSk2k9URExBMU6j5C64mIiCdo+EVExCAK\ndRERg1x3+OW1115jz549NGvWjJdffhmAsrIyUlNTKSgooGXLlsycOZPg4GAANm3aREZGBlarlUmT\nJtGlS5e6PQMR8Qh9rmOG64b6wIEDuf/++1m+fLn7tbS0NDp37kxSUhLp6emkpaUxbtw4cnNz2bJl\nC4sWLcLhcLBgwQKWLl1KQID+IBDxdfpcxwzXDfWuXbtSUFBw2WvZ2dmkpKQAMGDAAFJSUhg3bhxZ\nWVkkJCQQGBhIeHg4ERER5OTk0KlTpzopXnyfHmgiUr9u6e6XkpISQkNDAbDZbJSUlABQVFREx44d\n3fuFhYXhcDg8UKb4Kz3QRKR+1XpcxGKx1Gq7iIh4zi2Fus1mo7i4GKi+OrfZbADY7XYKCwvd+xUW\nFmK32z1QpoiI3IhbCvW4uDgyMzMB2Lp1K/Hx8e7Xd+zYQWVlJQUFBeTn5xMTE+OxYkVE5NquO6b+\n6quv8u2333LmzBmmTp3Kww8/zJgxY0hNTWXu3LnuWxoBIiMjGThwIMnJyVitVqZNm6bhFxGRenTd\nUJ89e3aNryclJdX4+ogRIxgxYkTtqhIRkVuiG8hFRAyiUBcRMYhCXUTEIAp1ERGDKNRFRAyiUBcR\nMYhCXUTEIAp1ERGDKNRFRAyiUBcRMYhCXUTEIAp1ERGDKNRFRAyiUBcRMYhCXUTEIAp1ERGDKNRF\nRAyiUBcRMYhCXUTEIAp1ERGDKNRFRAyiUBcRMYhCXUTEIAp1ERGDKNRFRAyiUBcRMYhCXUTEIAp1\nERGDKNRFRAyiUBcRMYhCXUTEIAp1ERGDKNRFRAyiUBcRMYhCXUTEIIF18U0PHDjA6tWrqaqqYvDg\nwdx///11cRjxA6XnbZQGrKn7A5230aRh3R9GxNd5PNSdTicrV67kueeew2638/vf/57Y2FgiIyM9\nfSjxA3u+KWHUqAl1fpyNGzdyzz11fhgRn+fx4ZecnBwiIiIIDw8nMDCQhIQEsrOzPX0YERGpgcev\n1B0OB2FhYe6v7XY7OTk5Hj2G/qQXEalZnYyp1zX9SS8iUjOLy+VyefIbHj58mPXr1zNv3jwANmzY\ngMViYfTo0Vfs++WXX1JcXOzJw4uIGC80NJQ+ffrUuM3jV+odOnQgPz+fgoIC7HY7O3fuZNasWTXu\ne7WiRETk1nj8Sh2qb2lctWqV+5bGESNGePoQIiJSgzoJdRER8Q7NKBURMYhCXUTEIAp1ERGD+OV9\n6tfjcrnYt28fR48e5cSJEwC0bt2a6OhoevTogcVi8XKFN+/kyZNs3rzZfU4Wi4VWrVoRHR3NoEGD\niIiI8HaJt8TEXoGZ/VKv/INxH5Ru3LiRnTt3EhUVRWRkJC1btsTlcnHy5Eny8vI4evQoCQkJjBo1\nytul3rA//elPOJ1OEhISaNOmjfucCgoKyM3NZefOnQQEBJCUlOTtUm+Kib0CM/ulXvlPr4wL9Z07\nd9K3b18CA2v+I6SiooKsrCzuvvvueq7s1jkcDux2e6338TUm9grM7Jd65T+9Mi7Uf+rixYs0bGjO\nAi6VlZUcPnyYbt26ceHCBZxOJ40aNfJ2WR5hWq/A3H6pV77L2A9Kc3JyWLhwIU899RQAx44d4623\n3vJyVbWTkZHBvHnzWLlyJQCFhYUsXrzYy1XVnom9AjP7pV75PmND/Y033mDcuHE0adIEgKioKA4c\nOODlqmpnw4YNvPDCC+6rh9atW1NSUuLlqmrPxF6Bmf1Sr3yfsaFeWVlJu3bt3F9XVFRw8eJFL1ZU\ne4GBgQQFBbm/Li0tpby83IsVeYaJvQIz+6Ve+T4jb2kEaNWqFVlZWQCcPn2av/3tb3To0MHLVdVO\n7969WbNmDRcuXGDr1q1s3bqVewxYG9jEXoGZ/VKvfJ+xH5SWlpbyzjvvsG/fPgB69uzJpEmTaNq0\nqZcru3VOp5OMjAz27t0LVJ/T4MGD/fb+4B+Z2Csws1/qle8zNtRFRG5Hxg2/vP3229fc/pvf/Kae\nKvGcOXPmXHWbxWJhyZIl9ViN55jYKzCzX+qV/zAu1H/+8597uwSPS05O9nYJdcLEXoGZ/VKv/IeG\nX0REDGLclfqPSkpK+Oijj8jLy7vslqvnn3/ei1XVzpEjR3jzzTfJy8ujoqICl8tFcHAwq1ev9nZp\ntWJir8DMfqlXvs/Y+9TXr1+PzWbj5MmT3H///TRu3Jhu3bp5u6xa2bBhA7/97W9p1aoVf/7zn3n0\n0Ud58MEHvV1WrZnYKzCzX+qV7zM21A8fPswvf/lLrFYrcXFxPPnkk2RnZ3u7rFopKCigY8eOBAQE\nEBQUxC9/+Us+//xzb5dVayb2Cszsl3rl+4wdfmnQoAEAHTt2JDMz0+/WRK5JcHAwFRUVdO/enf/5\nn//hZz/7Gc2bN/d2WbVmYq/AzH6pV77P2A9Ks7Oz6dq1K6WlpXz44Yc4HA4SExPp3r27t0u7ZQUF\nBYSGhgLVS6E6HA769+9PWFiYlyurHRN7BWb2S73yfcaGuojI7cjY4ZfCwkJ27tzJ4cOHqaioAKon\nE/jzfakHDhxg48aN/Otf/7rsnPzxE/pLmdgrMLNf6pXvMzbU33jjDTp27Mh9992H1WoF8Mt1HC61\nevVqHn/8cTp16nTVJ9D4IxN7BWb2S73yff5d/TWUlpYyZswYAgLMucGncePGREdH+/1/up8ysVdg\nZr/UK99n7Jj6F198wf79+4mPj6dx48bu1/15unNeXh6vv/463bt3d5+TxWJh5MiRXq6sdkzsFZjZ\nL/XK9/n/r6WrOHHiBNu2bePIkSOX/fb155lv7733Hg0bNsTpdPrtAv41MbFXYGa/1CvfZ2yob968\nmZUrVxIcHOztUjzmhx9+4NVXXzViDPNSJvYKzOyXeuX7zBoYu0T79u0pLi72dhkeddddd7F161b3\np/OmMLFXYGa/1CvfZ+yY+osvvsjBgweJiYm5bIzMn2+9mjBhAhcvXiQgIMA9s89fb7u6lIm9AjP7\npV75PmNDff/+/Ve8ZrFYjFh8yDTqlf9Qr3yfsaEO1U8+P3z4MN26dePChQtUVVVd9om9+A71yn+o\nV77N2DH1jIwM5s2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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x1067da410>" | |
] | |
} | |
], | |
"prompt_number": 13 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Another way of comparing the groups is to look at the survival *rate*, by adjusting for the number of people in each group." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"death_counts.div(death_counts.sum(1).astype(float), axis=0).plot(kind='barh', stacked=True, color=['black','gold'])" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 14, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x1067968d0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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5MGEubMMVVBxIoVBwgg8RkZVUKpV9VlDJycnBzZs3AQDl5eVITU3Fhg0bUF5e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\nyMzdXcdeAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106798890>" | |
] | |
} | |
], | |
"prompt_number": 14 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Histograms\n", | |
"\n", | |
"Frequenfly it is useful to look at the *distribution* of data before you analyze it. Histograms are a sort of bar graph that displays relative frequencies of data values; hence, the y-axis is always some measure of frequency. This can either be raw counts of values or scaled proportions.\n", | |
"\n", | |
"For example, we might want to see how the fares were distributed aboard the titanic:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.fare.hist(grid=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 19, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106d045d0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x106d06690>" | |
] | |
} | |
], | |
"prompt_number": 19 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The `hist` method puts the continuous fare values into **bins**, trying to make a sensible d\u00e9cision about how many bins to use (or equivalently, how wide the bins are). We can override the default value (10):" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.fare.hist(bins=30)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 20, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106c52ad0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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lWdbc3Jx1/vz5mOVblfHOP9+qITk5efFWDU6ybds2Nm7ceNlj/f39FBcXA+Dz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\nqPRFRBLI/wP0nNt0pERXwwAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106c55850>" | |
] | |
} | |
], | |
"prompt_number": 20 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"There are algorithms for determining an \"optimal\" number of bins, each of which varies somehow with the number of observations in the data series." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"sturges = lambda n: int(log2(n) + 1)\n", | |
"square_root = lambda n: int(sqrt(n))\n", | |
"from scipy.stats import kurtosis\n", | |
"doanes = lambda data: int(1 + log(len(data)) + log(1 + kurtosis(data) * (len(data) / 6.) ** 0.5))\n", | |
"\n", | |
"n = len(titanic)\n", | |
"sturges(n), square_root(n), doanes(titanic.fare.dropna())" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 21, | |
"text": [ | |
"(11, 36, 14)" | |
] | |
} | |
], | |
"prompt_number": 21 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.fare.hist(bins=doanes(titanic.fare.dropna()))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 22, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106c5bf90>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x106c58d10>" | |
] | |
} | |
], | |
"prompt_number": 22 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"A **density plot** is similar to a histogram in that it describes the distribution of the underlying data, but rather than being a pure empirical representation, it is an *estimate* of the underlying \"true\" distribution. As a result, it is smoothed into a continuous line plot. We create them in Pandas using the `plot` method with `kind='kde'`, where `kde` stands for **kernel density estimate**." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.fare.dropna().plot(kind='kde', xlim=(0,600))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 23, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106d191d0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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WiRYIgoAvvB3J7goRUVJxdVmcvHPUh1pfAE/dMzUhn0dEFA9cXSZRi2524bPz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\nRERxwyJDRERxwyJDRERxwyJDRERx8/8BKTMId4jEQy4AAAAASUVORK5CYII=\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106d2d350>" | |
] | |
} | |
], | |
"prompt_number": 23 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Often, histograms and density plots are shown together:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.fare.hist(bins=doanes(titanic.fare.dropna()), normed=True, color='lightseagreen')\n", | |
"titanic.fare.dropna().plot(kind='kde', xlim=(0,600), style='r--')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 24, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106d59810>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x106d49cd0>" | |
] | |
} | |
], | |
"prompt_number": 24 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Here, we had to normalize the histogram (`normed=True`), since the kernel density is normalized by definition (it is a probability distribution)." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"We will explore kernel density estimates more in the next section." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Boxplots\n", | |
"\n", | |
"A different way of visualizing the distribution of data is the boxplot, which is a display of common quantiles; these are typically the quartiles and the lower and upper 5 percent values." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.boxplot(column='fare', by='pclass', grid=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 25, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x106ea0d90>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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+InLVaU5gu1xXb7A3h0b7iIgldehm7Yf0qeUvltFe3s+gdzNcvpa4fjNgOox+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\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106c91d90>" | |
] | |
} | |
], | |
"prompt_number": 25 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"You can think of the box plot as viewing the distribution from above. The blue crosses are \"outlier\" points that occur outside the extreme quantiles." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"One way to add additional information to a boxplot is to overlay the actual data; this is generally most suitable with small- or moderate-sized data series." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"bp = titanic.boxplot(column='age', by='pclass', grid=False)\n", | |
"for i in [1,2,3]:\n", | |
" y = titanic.age[titanic.pclass==i].dropna()\n", | |
" # Add some random \"jitter\" to the x-axis\n", | |
" x = np.random.normal(i, 0.04, size=len(y))\n", | |
" plot(x, y, 'r.', alpha=0.2)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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Dmi1SU1WLvM+HqKujMzpeNUG1tWGcOYPMzNSt8+OBQQ00gX8HtGu0FEJ4M3g2\nwFAzARycmwUQen/ofIBIng0wKicvhOAf//EfEUJw6623snLlSrxeL263G4CkpCS8Xu9lXWjYMWib\njzwCUirtcT3uL3LQw7vDmsHOeaiZAJ/97Qk2/8M9YJoD7p8o8gejcvJf+9rXSE5OpqamhmeeeYbs\n7OwB9wshLsviwoWhdOGl04lx6BCG349MTaXL6aRv4UJkQcGAOnqjvBzR24uMilK6N3qMXNgRuoWn\nrg6jpYUbD53C2NaM0dKCaG7G/8AD2mZhyoAUzIwZKpWanAxCYCckcCx7RtB2E7HPYVROPjk5GYCc\nnByWLl3K8ePHSUpKorW1FbfbTUtLC0lJSZd1oZeTu18+RHvP8PrTBaePk19fhbPPT4+jgmPZFUT5\ne5ha10JOYw1+04lrUhb/369PUJ3eq55UfIiC08eZWleF0/KT3N5CTWo2DUmptMccpzp9ypDvlRBl\nsuWBBZfjY2qGITQlY5SVQVoaSV3tON55Bzlnjjp72bVLq4eGKQNSalVV51KpXV1It5v7F4UEpRNw\nGPsFnXxPTw+2bRMTE0NbWxslJSU88sgjLF68mO3bt7Nu3TqKi4tZsmTJlVjvZaG9x+KtR4uGvd8o\ni8I8LJF+P/asWdgLF2KUl2MclhhVEjsjA3vuXOyFCwcKX5VFYRyWqlnKNQM5ZcoFx8jd+lLJJf98\nmgsQmpLJyUF4vfSaTuzCuYj2dt3vEO4MSqmJ8vIBfz84QSL24bigk/d6vXzzm98EICEhgdtvv53C\nwkJmzpzJ5s2beeqpp4IllJGK7fHAmTMYlZUYVVWq69XlQsbEYE+apCLAqiqIisKePTsodwBgzZsH\nhhFM3yCEihYn0Ol+uBO6hbfnzsXYsYOMh5ZjJXdhvvPOhMndjlcC9gOVkwc1klN3Jisu6OTT09OD\nTj6UmJgYNm7ceFkWFXaYJmRkQGur0qY5dgwZFQVTpoDPh9HYiOzuxjh6NDhERFiWErJyu4PbQ1lQ\ngFFaqqs1wo3QLbxpYq9cyacBUVqKXLJEyVVoW4Uv/fYLXlt+PzI6Wjv4frSswWgxTcTZs5inTmGn\npyPj4hDHjiHq6rAnTUJaFtLhQPh8mPv2IaqrET09WNdcQ19entKd9/kwKitVp6zLpas1wojg4Xpv\nL/a0aWpmQG0tRlOTslVh4VgvUXMhRqiEGqk+PtJr57WswSixPR7svDzsyZORGRmIzk5oacGeNQui\no5Xjz82W0fr3AAAgAElEQVRFADI2FtHYCElJGMePY+zYETwckmlpyPZ2nQIIM4TPF/yfceyYitz7\nf8xlTo5KtWnCmpEmQ400ByDSZwRoJz9aTFNJFmRlIYXAzs3Fnj0bHA6sa689p2Lo96vxgNOnI20b\nOztbHdoFdMijorBvukk7+HDDNMG2QUo11nHaNHX2kpWld13jhWEUQn+yv3bkOQARPiNAp2suAtvj\nQRqGSr10dWEeOQK2jREVpSL3vj6MmhqspUuR7e2YJ08qVUomZn3ueCEw2lHGxWHl5yNnzQpu3Qcc\n6EXodj6SGCr18krJWR58ZAFGcTGiqwtHVVWw3yXUzqHXZiSlcHQkfzGYpnIAGRmInh6Ey4Xh82FU\nV2MeOaKcemKiqsLx+ZBzVQmesWOH1iEPY4KjHdPT1W7MNIPRnywoCB6kR+p2PpIYNvVimpCWhtHV\nhejsxDh69Nz9Q1ybkZTC0U7+o9C/tZeGgZ2SgkxPx87JUTlcKbHz8pA5OeeNlNOEKUNs118pOTvi\n/Zow5UJpGds+d42OZMsIsrlO11yAobZt0uUCr1fVyU+Zgj1jhor4+n/xZUEB9vz5mD//OcTH43j9\n9WDFho7kx4aRtt8XSqXpVNv4YSRbBdKtwAV31ZFkcx3JX4Chtm2iqwuRnIywLIyTJzGqq4OpnEA+\nF5cLuXCh2uqHVGxoxoYRt98XSqXpVNv4YQRbiaoq1fNg2x/rdcYbOpK/EINbpisqMHfvxjhwANHZ\niT1vHqKzE/ONN9QwkfR0jEOHEB0diNpaREuL0tBIS1NbRMuKiC/OuGMUapKh0b5hW+fdNpQ+uSZ8\nCO11oKUF4uMhKoonJiVjvv46jj17kG43dlYW0jBUQDYB0JH8BRhceyt8PkhKQsTHQ/8kLHHmDGRl\nBccCGnV1mKdOIVwuaGxEOJ2IuDjMPXt0ND9GjFRDHSA02s9pPHPebXo8YHgT2utgHjmCceYMoqWF\n9U1H1HXb2YlRU4Nx5sxYL/WKoiP5CzFYtc40lYRpRgZy/nzspCTk1KkqegiMBayoQCYmIqVEXn21\nStlIibV48bg/xBm3jEZ9MCTaX77yqvNuIy8PobXlw5fQXoesLEhMVIUP/ZPaZGoq0jTpW7ZsQklU\naCd/kQRr5ZOT1QU/daraxp86hYyJgfp6rBtuwDp7Ftl/gm/s2IHMyTmXr9eEBYMPY0MP2x4YpD8O\n/ZFiWRly/nw93jEMCT1YFdXVON59F7lgAfbMmcioKKy5c5W9HA7Mt94aMB8iku2o0zUXS6BWPjMT\npkxBdHVhHD8OOTmItjaEEEq+oKAAOXcuxMRgr16t/h3BX6TxyHmHsUMdtoXWyoPqjejXIdIpmzAj\npPjB6OhAzpmD6OjA2LVL3T53LnLWLHXN+nzn18tHKNrJf1RC62jz8pScQSBdo7fz44OLqYUOPNbl\nQmZkaBuHO07n8H0qF1MvHwHodM1HINAGT1MT9s03K8XJ/lZpGRU1fAlXBLVKRwLBVIwQF9y+B1M5\nhYXB8Y7afuFF4PoStbXYGRkY9fX03XMPW988wPr8uAFpuUBaJzD3NZKvSR3JfwSCbfApKar2tqsL\nsrPV4atpjqp6I9K3iOOCQCpmNNv3QCrH5YqY+ulII3h9NTdj1NUhFyxA1NTw+wOnzk/L9ad1JoJk\nhY7kLxKjuBjz4EGMhgas2bMR8+cjTp9GtLYiWlqQS5ciysqCUcGAIdFCKMlavx8RHa1r5seYgG3M\nP/4R48QJ6O3FnjoVw+lkx292ceOczFEPX9e7tDCgvxJqcNrUMg5hvPceRnU1dno6VmenmgfR1aXm\nO6SlqR14hKZtdCR/kRhNTZCejujsRHi9qjmmtxfi4pBJSao2N7Q7NiR6lw4H0jRVyWX/ZCjN2BHU\n+I+NVXbJykL09GBWVrK3vBbjyBGMU6dGFeXpXdrYE+iF6PvEJ7BTUoI9EZUZ/WdmSUkY7e2YO3cG\nex5kejqyoyOi5zuMKpK3bZunn36aSZMm8fTTT9PV1cXmzZupr68PzneN7m8MinicTujowJ48Gbuw\nUNVPT52qxvn19p5/8BraaVlQgLTtcw4/QiOHcUMg8ouKUp3LloV0uVTbu+xQg9dHe5A+io5azWUm\npBcitA7eNkxkbi588AFSCKwlSyA2FtHVpQ5mI3y+w6gi+d/97nfk5OQghABgy5YteDwennvuOQoK\nCtiyZctlXWQ40bd6NdbkyfjXrIHmZnA41EFOezvS5cJ4/33o/+8E53dajqbzUnNlsD0eFcVNnYpM\nSMBKS8OePh3p89EZFY1dUDBqW2m7jh2iogKjtFQdoFqWkh55/XUcv/61ut226Fu9mr7Jk7Fmz4bY\nWFU739EBQmCUl4NljfXHuGxc0Mk3NTVRUlLCzTffjJQSgH379rF8+XIAVqxYwd69ey/vKsMJlwt7\n5Uo1MDgnR6VdqqogLQ3R06P05CsqhteqjiDho3GPaUJqKsIwVAqutxdhGIiYGBDmBQ/SB7+WtuvY\nYJSXY5aXYx4+rOYu+3xKOLC8HPPtt/lcSrca9BMfj5BSpdSqqpTtIeJTbBd08j/+8Y/59Kc/jWGc\ne6jX68XtdgOQlJSE1+u9fCsMVwbXWA81Pk4T/gzR7yBdLpoS3Dr1Mk4QPT1qspffr24wzWDVDMnJ\nfHJuarAiTnR0QF3duWs2QjTjR2LEnPz+/ftJTExk6tSpfPDBB0M+RoSkJiYCQaW7ri5obUUuXKh0\nMRwOZHQ0Mi7uvC27rrwIX0Jr5UVHB+KDD7DnzOGTZ44jY2OHrJ8PVTvUcwLGHnvGDIydOxF9fTje\nfhuZloaoqYH2dlUcMWcOoqEB2d2NaGvDuueeYcf+RSIjOvny8nL2799PSUkJfr8/eOCalJREa2sr\nbreblpYWkpKSrtR6x5yg0l1vL8LrhZoaVZVRXw+5uao8sqpqwMFPoPKC/oqaiSSOFPb0p1mM0lLV\n+xAdjVFXx83XFMDx4xhdXdDbi3H0aLDRLfQ7YBw7pn7ctU3HDHv2bERlJXR2YlZWIru7weFAOBzQ\nr/5q5+ZCQgL2tGmImppgam0i2G1EJ3///fdz//33A1BWVsb//M//8OSTT/LKK6+wfft21q1bR3Fx\nMUuWLLkiiw0LQtMyOTnBFnfy8tRp/XBjx3TlRXgzRI01eXlQVnZ++7tOzYUXpqlmPRw+rBRiU1OV\nhlRXV1D9lbg4NddhAl6DF9UMFUjN3H333WzevJmnnnoqWEIZyQwYHNGflqG9HbugALO4GGJiQEpk\ndDRCCMx33kHm5dG3Zk2wkWYibAvHE4NTaNLpRNTVBaUpcDgQHR3Y8fHY+fnIkDTbxYyR01xeBqRP\n29vpmz4d0dqKdc01GKWl2FOmQFSUuj69XkhNxdy2Te24+/omRLpNyEDJzGVk27ZtXHXVVZf7bT4y\nb2ReN+L9SXY3BiCkJFr66TJcJNjdWBgk2N1EYWNhILAxgD5hYklJqxHDWUfCRa/ntrPvfrQPohk1\nRmmpSqH5/dhu97mDumH+ngjb+vGIUVqKWV6uGhLr65HTpyNOnkQYBjI9HTs6mv/1xXL7jCSor1fy\nIx9+iGhogJQUZHQ01vz5496+Bw4c4JZbbhnyPi1rALzw9Rd569GiYe83ysowjh1Tv/7Nzcj4eIzG\nRuzJkzH37YOeHkhNxZoxQ3XTNTdjT55Mz1e+okaQ9TOaA9hbXyrhtsvyKTWhiNpaRHOzSs8UFiKO\nHx845rG8fNgUmz5IDyMCqbP6eoRtIwPzlDs7oa0NUVDA4eYk1hbcgjBNxIcfYtTXq5TOBEm3aVmD\nUWB7PEE5Ahkfj+joUHm+1lb61q3DnjYN/1VX0XfXXaqBJj8fe/ZsjD17BryObn0PH2R6upKiyM5W\nCqKDmpl+3JE4bHOTtmP4YHs89C1YgD19Otb11ysBucREkBLhdIJlkdzRhoyPVzpEcXFYixZhp6TQ\nt2gRdlFRxP9I60h+NAQOdnw+1QI/bZqqtLjmGkRXF9b11wedgZw6VW3vh9Ox1gew4YHLhczMHNDn\nELplf/lQAw8Mt7vTdgwfAoqS/XIh9tSpYBiIXbuQvb3IOXM46HKqqqjy8qDN7WuuiXjnHkA7+VEy\nlJ64qKhAVFZiNDZi7t4NUipdjIAehss15GsAEa9hHe58HFvog/TwI9Qm9ty52LGxYNsYp06R1dyI\nceQI0uFA1NWpqqkJhE7XjJYh9MRFdzfk5GDW12OcOoXR2oq5d6+6+Ac5+NDXmAga1mHPELYwduwI\naqAY9ghaJlrCIPwItYnLhX3rreqQNTmZmD7V5xAc0zlIAXaw9k2koZ38x6G/LdqOilJ5QCGwFi8e\n/Sg5vd0fe0JsQXJy0OHnNJ4Z65VpPi79h7LX5iapPoeAbMWg6y7Sz1h0uuYiMYqLMZqaMI4exc7L\nQ7S303fjjThefx0aGnD+5jfws58h4+KQ6elYy5djz5s3IOrT2/2xYXBVjKiqQpw8iVFSApMmYdTV\nYcfHI/PzEbZLRXcHDqhGmqgo+lavHnqHphlzgvXyPT2qj8WylBxFTAzX3LVCSUh3dCDKyhB+P86t\nW1VQNm+eqrDKyIjYwSHayV8kRlMToq8PUVuL0dmJnDEDc98+5MyZmI2NcOaMKs1zuZBdXbBzpxpK\nEVqHO0HaqceCu18+RHvP0FvugtPHMaWNafXRHnOcKH8PU+uqyGlsJKnjBAKJ33RSVinIdUTxxJZu\nrvnwIH7TSVtsAg3bz7Bn9tJRryUhymTLAwsu1UfTjIDw+TB8PujtVRIHpgkpKepOp1N1vwJERam6\n+q4ujOZm8PuxioqU5PSSJREZdGknfxGIigo1+enUKUR7u/qinD6tpssIofTlbRsSE5GJiUgAy8L5\ngx8gDAM7Lw//I4+oDlnNZaG9xxq258EoiwoObLEXLMDctg2zVCDinMhJMxGtreB2Y83IU93M772H\nWdOmtOYX5dP3qU9dVCR/60sll+pjaS5Ef2pGlJdjdHVhg1KmzM7GOHECY98+DK9XVeBER2M0NSGT\nk5HJyeqazcgY609w2dBO/iIQPh/W1Vdj1tVh3XYbjm3bVLQQG4uoraVv0SKwbezp08/Jnfr9mAcO\ngBCY3d3Yr72G9eCDY/1RJiSD02QyPR17xgyYMgU7Ph7h9yOkRGZlqS2/34+1fLlSpkxJ0amaMCYg\nNeGoq8NKSVEiZF1dyJkzEUePqkHtoGyYkICVl4c1fbqaApadHTyMjcQdtnbyF0NAu2ThQmRODvbc\nuYiODiRgr1iBzMtT9fH9NfNGWZkSTTJNcDqxMzOVzKlmbBicJnO5kJMnByN7o7wcAqMZCwqQx44h\nWlqwFy7EHqZlXBMmBOrlAzbLzVUNiZWVGLW10NeHTEhAxsRgLVuGjIkJ2tw4dkyleWbPRlpWxKVs\ntJO/CAbXyluPPYaxYwcyJ0eV4/XXzwe+JNLpRMbE4L/9dmhpwbr/fp2qCSMComTC4VBaNrW1auBz\nfw8E9fUYW7bA5MmI+nr6+ieCidpa1THbLz4XaU4hnAkcnofaQLpcSqDMNOlbuRJj1y7ViGiaiFOn\n+INM5qZMG3p68H/mM+q5/dep7fEgTp6EKVNU3j4Co3nt5C+GIQYF26tXB+8e/OUQ3d0wZYoqs5w/\nXzv4MCPQ5yA+/FClajo6kP2StKKyEtPrRbhcGPX1iAMHlPLo7bcjmptVFUdmZkQ6hXAmUO5oNDUh\nu7vVLIeTJyE7W81rqKnBXrky+Hg5bRp7f/MBN92cr6rhamvPL4KYOjV4VhOJ1TW6Tv5youvhw5t+\n+wQ15F2u4HwAmZenDtNBbe1nzsRas2bg47VdrzyBa2qQrYa7zmyPB29snKqTH6ZEMtKHsOtI/mMQ\nqM01qqvBtpEZGdgzZ6pJNYEa7Opq7Lw8DCH09j7MGKwhL6+6CmPnTqU/LgT+W27BSEjAOH0a67bb\nsOfNUym5EGkLbcsrS1COIjFR5dLz8rBnzlR2mzQJc9s2ZHo6or4e8+23EQ0N3FDlQ8wQiKwscDiC\n+vETRU1UO/mPQXAMnNeL0dSE3d0NgIyKQnR3Y3R1IXp7cRQXI3NzsRYt0tv7MCKYruntRcbGqsqL\ntDSlI9/VBR0dGH4/wu1W4/9iY5GzZgHnp+Y0V4iQcY1BiYKqqqDdAqk0fD7E8eMYlkXBmRoc/9eN\ndffdA8Y1TpSxnNrJfxwCWtZCICdNwk5Nxc7LAyEwTpxAHDqE0damlCtjYtRQg4k0KjHMCdWUJyFB\ndbhWVkJNjZrt6nAgjh3DaGnBiInBmjNnrJesCRCIxE+fVvY5fRri45FRUdgeD+axY6rDtbqaSR1+\nRHsi5s9+pn6khcCursbxwQdgWfRdd11Ep920k/8YBGpzrblz1Q2BKKOsDJmbi6yoUOWVeXlIvx/r\nttsidks4HpHp6eoANS0tKF4l09Iw9+9HzpqFqKxE1NcjY2KU7nxtLXKB7mC9UozUvWzYFss+qCam\nt4sFlUdJ9LUihYOGeDdnq6HLFcV0czKL/afxTppEQ52PXrObKquBhpp3iOrpoiYjj/SWespP7Wd3\n6cg9EOO5e3lEJ9/b28umTZvw+/24XC6uvfZa7rjjDrq6uti8eTP19fXBGa/R0dFXas3hQ39t7lC3\n092t5rxefTU0NSkHr5tpwosQTXny8hDd3SoSLCpCeL1qalBcHKKzE3vKFCUfrblijNS9DGCUxWIc\nPoxjbwOyOxGZmYldUIDMzUWcPo3oK8B4z41obEQmJSEcDhYkJ2NNnw4xMYj2dqQrn7716y94bY7n\n7uURnbzL5eIrX/kKUVFR+P1+nn76aRYtWsS2bdvweDxs3LiRrVu3smXLFjZs2HCl1jzmBETKcDqx\nCgow9+zBaGvDzs/HmjVLzZtsaqJv7Vo1HSo3F+P48Yg+3BmP2B4Pxo4dkJystvAJCco+DQ0YBw9i\nLV9O3003Ye7Zoxrfqqowjh9H9PZOiAHQ4U5wJz1rlupwzctTO+lduyAqClFWps5R8vKwJ08Gy8I8\ncEB1nqemImNj6bvnnogPvi5YQhkVFQVAd3c3tm3jdDrZt28fy5cvB2DFihXs3bv38q4yzAiKlLW0\nYL7zDmZzM6KzE6O8HHPHDtU+3d9aTWoqAiJWxnRcY5rn7NPfTCO6uzHb2iA7G+PkSczdu5GLFyN6\ne5XKYf9hu3HsmLbnWBPocl2wAHvtWuTcucphp6ZiVFdjtLaqbtfERIzuboRtI5KSEMeO4Th4EKOm\nRh3aRjgXdPK2bfPFL36Rxx57jNWrV5OamorX68XtdgOQlJSE1+u97AsNK5xOlY5xubCXLEEKgezr\nw87OVkp2oTW7ulY+vBlsH9McaM+lS8/dn5enDtonyADocYtpqu5VKSE2Fikldv95izRNRFSUkjiI\n0GqawVzw4NUwDL75zW9SX1/PM888g8fjGXC/6G8YiTRGqqGVXi+OP/5RbfmcTkR1tUrRzJ4NdXWq\nTKtf28b2eDCKi5VeeXm5TtmEAQNa41NToakJHA6cP/whxocfQk+Pkjvw+TA+/FAJmU2bpjTKGxqU\ng09I0CMcw4ygpnx3NzI2FisxEfPYMcymJmRFBcIwkImJWG43MjcX2tuVjd96C/x+RF9fRKbhRt3x\nmp6eTlFREWVlZSQlJdHa2gpAS0sLSUlJl22BY8VI02LMxkZkfj5GUxOO4mKEEIjYWIyKChzvvqtq\ndr1ele81TfU3OmUTLoS2xhs1NZCSgllerpQKGxowGhpASozjx9W2v7YW4+hRzKoqNT3K71e5+Qie\nJjQeCfatdHUh09JUAJqZiegvaaauTtXQJyZCUhK43RinTyOamzH6f/gjMQ03opNva2vD5/MB0N7e\nzvvvv09ubi6LFy9m+/btABQXF7MkEmu/R0izyKgo1SwTFYW9eDGyP0Kws7OxCwvPpXJuvPGCr6UZ\nA4Zqjc/JQfr94HAgMzMhIQGZkQFuN/bMmcjsbGRqqtr6jzBKTjOGBPpWpMTOz8cuKlIzHaRUNs3K\nwk5JwV6wAHvBAtUUlZERlKmI1DTciOma1tZWXnzxRWzbxu12c8cddzB//nxmzJjB5s2beeqpp4Il\nlJHGSCP6/A8/jPnaa1jr16vD1auuQpw5g71iBcY77+A4eBCyspSyYVMTMiUFGhuVXG0EbQPHI6Ki\nQqXWGhuD1U/G4cOItjbo6sJ//fU4du1CREVhu91Y+fkY7e2QmIgVF4fo61M/7jNnammDMEFUVGAW\nF2OWlKjUW34+1uzZ9K1aBeXl6janU8lIR0dDVBTS61XCZPX1WHPmYO7apb4XTudYf5xLzohOPjc3\nl3/5l3857/aYmBg2btx42RYVFow0oi8mJjj4I9jmPm8eAIbXi5wzB3HiBOb+/Soi7O4GKTF//3vk\n1Kk6h3sZ+cKXP8cbXx7+/iS7GwMQUuIXBgaSLKsDE4klJQ5sHEgcSPow8AMdZgyGbWNIm2ZHXPC5\n7UbUyGsBePTdS/jpNEMhfD6MlhaE1ws+H9TWYuzZg0xIQMTHYxiG2l37fKqjuacHYVnYa9dCSopK\n5bjd0NuLceLE+eM6xzm643WUDDkEetDBrKioQJw5g9HRAR0dyJwcqK+HnByMqioledDeHtE6GWPN\nC19/8QINNGVK2MrvR8bFYVRVYW7fjmhtVambuDiMujro7cWeO1dplvf2qiEUc+cqJ+H3I+PjVQpg\nBNG5W18q4bbL+Fk1/Zgm4uRJxPHjwajdUV2t8u+AOHsW6fMpqW/TRBw+jOlyYfzyl/jXrYO8PIzi\nYiU3PG0a2LbSxomQQ3Xt5Pu5UEfbUEOgQ/+uTp9CwenjuPxu5lXWUueeBHtbaI5PYnrJQdpjE4g5\ncoS2mBrembcMu3jo90uIGt9fqHAnqGKYk4Nx9KhyBNnZ4PWq3gbbVoqUBQXItDTs/Hw4exZr4UKk\nx4M4dSr4XNnbq/TM9Y/2mGJ7PNgFBUoU8PBhZHs7Rl8fYtcu+hYuVI1QQmBddRXGe+9Baqp6ot8P\nLS3Yt9yiJCz6lWSN48fP6dNHgG21k4cRI78Ag4dABxpjAn/f+qND/Ns9c/tvmxucEC8dDnAsUlF/\nfb2WNxhrTBM5bZqyk8sFmZlYvb2YgHS71WHc1VcjbVvlbrOzkVOnIvsjutDnBg9tI+ygbtzRP/hD\ndnYim5qUVHR0NFZhIf7Pfx5efVVJWERH43/iCZy//KWSr5gxA3vFCvX86dODox/Jywteu5FgW+3k\nR0mgBV50duJ8773gKb61bBni5EmWfbAbY1ImtLYiCwvVSX1Iw4WoqFAKlON86xcJSJcLcfKkGuJ9\n9izmiRPIri44eRKuvhqOH0fOmYMM6MwXFJyb7ztoBKQ+eB17RL8QIHV19M2ejVldjS0E0u3G+cor\nyEmTwOvFWrpUSVIkJmLs24ejqgrR1IT/0UeD34mAPn0k2VY7+dHS3wJvlJdjtLZCUxMyM1Md1ERF\nEdfTqfTJ29owzpxRwlfR0efmvY7zLV8kIbq6IDsb0dsLfX2I/ooLISXixAlISFDVULm5Smc+9EIf\nYgSkZmwRPh9GTw8yKwuzsRGysgAwT51CArKzEzs/H3P3bkRSEkZjo5I46O7G3L8fOykJWVSkvhNd\nXcrBR5BttZO/GPrrcG3DgJQUlbPNy1PbQ1mm6nGzs/VouHAnoBLavzWnvBxh26oSavJkZHw89vz5\n2objhdC5Dikp2P03B7rxA3MeDID+SjcALAt7zhyse+7BOHky+J2INJtrJ38RBFTvCNGPxzQRPh8+\nVzRWWpo6vKuvD9bET5QRY+HMYBuE9kCIigqsadOw4+OxMzMxamuVdvwHH2DW10NxMfbUqfStWaPP\nUsKEUFkK/H6MU6fg7FkVZKHKmOnuRqakIGNjcbz9NvKdd9Qhe1QUuN303XgjMjYWe9kyVV3V3Y10\nOrFvvTXirlHt5C+GIfTjjdJSBHDt4gK1/Q8oG/Zv+SbKiLFwZigbBM9KurshP1859ro65NVXYxw5\nosbKNTUhWluVI4mLw165cow/iQYGylKIxkbo6kJ0diIACaqxDWVb2dAA7e0YLhfU1anS19xccDqx\nV6xQdvb51LUrZcSlakA7+QsSFD3q6VGn8bNnD4jQjcpKZFoat83LUOJkR46ow9err0aUlakX0e3v\nY0toeob+H+baWmR6Oua+fcjYWITXq/ROjh7F2LsXWlpUpOjxKG2T1lY4fDhofxhZxE5z+QiMbRQf\nfoiIjYXGRmhrQ3Z3Izo7kTExqtS1uhrR3+lKe7v6X3Q0oqEBceedyJwcddg6grJowMbTaivAWjAu\nbayd/AUQPh+Gz6e64Y4eDVZbBKIJmZ6ObG/HXrIEo7QU2duLkBKjpgaZlaUqbKKjI+akfjwSmp4x\nysqCUaDs7g5OCCIxUenW2Da4XIi0NIiJUba95hqlJx9ifxh6h6C5/ATHNs6Yge3zwdSpqnkpORlx\n6hR2YiJmZyeif/Yyx46pjtb4eIyGBhXxHz+OsWsX9k03qRQsDKiiChCwcUzv+LWxdvIXov9QJyhM\nFfilD0SHLpcaC2eaqhY3Kwuqq8/VUA/xxdFcYUIlKkLsJjMy1C5rxgw1WSgrS5XS1daqH4GUFPpW\nrcI8fhzp9w+0f+hr6V3alaV/bCO9vciZM1W/Q1SUqnRzOMDjQfb2QlsbmCbW2rWYZ84g3n9fFUVM\nnox1441KQHC4EZ4B+m3cZ5jj1sbayQ9DcCsuBH1z555zFIGSyP66WmGamG+8gejrQzociDNnYNIk\ntYV0uXD8+teI5masoiKIidHb+jEmENWL9nY1sDsrC9naiszPx/zDH5S6ZEsL4uBBSEvDsXUrCIEw\nTURrK2b/FLSAxnywF0Lb9IoQFJhrakL6fDh+8xuky4U1Zw7i4EGlG7VnD6KlBU6cQOblIZKSoKEB\nOz0dIYRKu86di7FzJ2Z5OVgW1g03YM+bd54dA9+XY9kzxq2NtZMfhuBW3O9XnZCDtmmBWmvjyBHl\n0FMDOhEAAB9BSURBVFNSMOrr1Y9BTw8IoXRO0tIQDQ2qHreoaNxu+SKG/h9rs7RUHZC3t6uoPSND\naf6fPav05J1OpT7Z0KCqNJKTMXy+c9K1nZ0AWPPnj9uLP9wZSmwus68dFzZSglt2YhlOYu0eJGBj\nIH6zAwd9OLFwAMaHJ7Df3E43DgRgIWh/az++f/slUbYfpwBT2vTwHc46EoYVnfs8wJ+PT7E57eSH\n40Jb8ZBtP2lpvHuimetmZiv9i74+VZdrmkoZz+VSYld6Wx8+OJ1KRM7lwi4sRPT2Klv2n6GQmYlo\nbMTOzkZOngyGoQ7nUPXXMi0tIrXHw4mhxOYcW7eqw1Up1YAPw4C2NqyFCzFOn1bj/QwD49AhjPp6\n7EmTkKmpahSgEFgZGWTk5GDPmYNRU4N55AjStulbuZLpixYN+4M9nsXmtJMfhgG11EMoToa2xkuH\ng5eOH2PpnWsxiosxKiuV6mR+vlK+y8zEPHgwOBJQR35jT9/q1Zi/+AXC58O5ZQtSCKwFCxCNjfjv\nuUdNETp7FtHbq364nU7lLJqbsZOTIToae8H4rLYYz9gzZmAcPYqdl0ffnXdi/vKX2FddhXHyJFZS\nEvb06Rj79iFcLmwpkfHx0NmJlZVF3yc+oQ7aa2uVbU+fRnZ3YxUVYS9cGLG2HPX4vwlHSA5+qFGA\nA1rjXS4qM/NUs0xmJiI5WSniVVYip05V0sOpqYjWVjUSUDP2uFzIwkIMrxfR0YHR0YGjpASyshBS\nqgO9pUtVlU1ysrK90wnx8QiXC9LTEVVVY/0pJhz27NlY8+crpxwfj/XggypKnzIFMjPB6cRsboaC\nAiVVUV6O0dWl5ApaW5Fz50JGBqKrKzgMRlhWRNtSR/KjYYjUTbBWt6UFcnJY/85eHJNOIhobEV4v\noqUFOyMDE5XnJSYGGRNzbiSgZkwRFRWY776rGp+ampAJCcjMTPUj3tWFkZSkfshPnVLDvqdMUXX0\nvb1atmIs6Q++REUF5o4dGG1tcPIkor4eamth2jREdTV0dKhGqfh4hM+HWVaGcfgwPPMMpKSo2nmX\nC5Gaip2RoUoyLSsio3nt5EfBUKMAA7W6WBZGZSVJ3W0YVVXI/i2idDiUdkZ3t5oN2t2NtX69bo2/\nAlxoNgCo+QBTz3rJao8np9VLqz+KamcCuUfKKMuFaH8l3U4XhmXReaqDvTNnMvloHWcm5TC5vI6a\n1MnY+w+N+B56NsDlQ/h8GM3NKp3W0gKnT6u0RGUldk8PRnc3TJ2KfeaM6oGQEqOuTo1vbGvD6j93\nwbYRbW0q0o/QoogLOvnGxkZefPFFvF4viYmJrFixghUrVtDV1cXmzZupr68PznmNjo6+Emu+8gw1\nCjCkVpe0NGxxEjs1VUXsOTmI06dVZY5lYU+fHtE5v3BiNLMBQM0HMA9LpD8bopYpNUrLQro8rM/N\n5Z9/spMvf/papTuuc+/hh2kihVBOOz1dVTxVVakoPTZWVbjZdnAegPHOO2BZatDLtGmqGGL6dIiL\nwy4sjOid2QWdvMPh4KGHHiI/P5+2tjb+5m/+hhkzZrB9+3Y8Hg8bN25k69atbNmyhQ0bNlyJNV9R\nhmtdD9UVd7z4IjfYzZh79uB/4AFVcnnVVcH8va6jDg8G2HLGjHOdjtOmYezYoUpeo6KgoYF35l6L\n+OMfMS0LuWcPfTfeqJQqRxj/qLkyBGrl7enTsRwO7BtvxNixA3PbNiUj/MEHyOZmZZNbbkHs3o3M\nyUEeOqR+EGpqVF7+xAn6PvEJjIMHsa67bqw/1mXjggevbreb/Px8ABITE5k+fTrNzc3s27eP5cuX\nA7BixQr29jeJRBpDHboC56J7lwtDCGbmpiIAxxtvnOt+nTVLddNpBxAWDLBlVdU5+7hckPH/t3fu\nwVXV597//Na+JCEheyeBQEhICBhiQEBNUEC5iBcQ8dgzHi+1pXhmtGfsjIOjyLScM6fOtNO3nULL\nyKD09LUHnVZxHE71aO3YqghKyyuQUCLRQEzIBUhCbjubkJ1k7bXeP1b2JlcCMZC9134+/yTZa63k\nlzx7Pfmt5/J9poDXaz3+d3czta0JzTQtCYRz56zSvT7vg2HfF8JVQ1VWopWW4igttXpYMjKsezAp\nCWPNGszbbkOlp6POn8epaTg7O3EcPIjq6rJi9unpcP48WjCI5vejtbfj2r8fPB60r7+2rR2vqLqm\nvr6euro6Zs+ejc/nw+v1AuDxePD5fFdlgeOOwzGiwJgZFwddXeBwoK9aZdvHvqjnUrYMaZL3ClXV\nTZpm2bWzEzMuzhrb2Pfay3hfCGNLuEGxq8v6Jz3wb+9yWdpDSllyBomJGDfdBF6vFUJ1uSAry9KS\n8noxc3MJ3nrrYMkSm3HZiddAIMC2bdtYv379oNh7SJzfjgyVdB1Iz+OPY+zejVFYaJVoyc49IgkP\n8VYKraysX6jFyM+HM2dQFy5AfDwQQF+2DNd//zfGLbeA04nRZxTg5bwvhLFDVVZau+3uboIzZmAm\nJw8Kg+qrVmE2N6O53ZjFxQRvvhnHiROYKSlWQjYlBeX3W7m0lhZMTcPx3nsElyzBmDPHtna8rJ28\nruts3bqVpUuXsnDhQsDavbe1tQHQ2tqKx+O5eqscTwZo1gxJQgLBf/1XTEnQRTah8rvOzsGhFofD\nCtlkZ6M6O/lBepfVBLVoEUrX0b7+Ojwkpu/3EntfG1RHB2Z2trV7T04eOgzqdmMWFkJhIcH169EM\nA1JTLc14w0C1tloaRD09oBSO5ma0UHnlgQPj84tdA0Z08qZpsnPnTrKysrjvvvvCrxcVFfHJJ58A\nsG/fvrDzF4SIZ7hQS5/X/+n+RcMrkArXHofDGteXm3vpMse+NsvIgKQkq6x56lSYPBkSEzEzM2Hq\nVEs2OjERfckSW/evjBiuKS8v59NPPyU7O5tNmzYB8Nhjj/Hggw+yfft2Nm7cGC6hjBXCg0R69U7M\njAz+t6Kdtf9826CRf6bbbTXVSBVGxBAO2wBxGzbA2bOoCRPofuIJuHAhPLrRdLsx4uOtMjsRIhtX\nRgqPafv24fzsM9T58xhZWQR7ZYTVK6+gKWXN7u3qQtXUWMPaNQ0zMZFgXh66zftXRnTy119/PW++\n+eaQx0JOP9ZQHR3hkWFaVRVGTw8f/cPP/QsqB4/8q6qCzEwZLBFJ9IZatNJSOHsWR08Pqroa96uv\n0vPUUxdHN3Z2QnY29B4PSVzIP+xxYKhelT5ozc3W9K5AAO2LL3CEpCcyMjB9PqvrvKsLTSkUYJw7\nh8rJQSUnox08aOvRjtLxeoWEEkCOffusm7y7G5WaytSWc5Z2dd8E0cyZkJNjOYvGRpTLhSorEwdx\nDRmuz0FVVuL4+9+tUXCdnRhJSQSXL7cabOrqcJSWoh0/jpmYaKlOrlxpdU2ePg1+P6q6mqANhz5H\nG6GnasfevXDihNUcFReHIxi0xjeePGl1tCYmWvIFwSCm349yOjHPnUP76iu0nBwoLbVt8lWc/BUS\nSgCRkBCeSKOqq2n05lgNMoGAdfzUKUveoFdnQ7lcKIDeZJ/s6K8Nw43oUx0d4PFgrF6N+uQTetat\ns+K1SUk4amosZ6FpOKqqCN56qzV1aMIEy8ErhZmSIna8BowkUZF3uoIZjdVkNyjy2xWYLpz+HrSG\nr0nq7mDS+S4SghDs6OZ8bSMVmdfhccD5uGRc/iBtFa2c6vycun11VGRWUZM+fcifE80SFeLkr5Re\nsTIjMxM8HlRzM8FFi+j+S60lS1xebh0PJYhCFR1lZdDRIXXV15rh5gI4HKAURk4Oxve/b3VEhkok\nT57k78frWDIhnuDixeHEqzFvHo6PPsJMSbHOFTteVS5HoiIkT6GqTTAyAVANDajmZjBN1ElF4+lz\nTJmSQuLixUxesMCa1TtxoiVMl56OmZVFsKDAqqmXnbxg5Oej7d9PcPFitNJS9LvvRqupQdcc/Y6T\nkoJWXo7pcqECAcuhyKi4a85wCTsjPx9T01B1dZaU8LlzGCtXhhvaDvzvL7nl+/egGhsxZswIl+wF\n77ln0PcbLiQkXH1CduSGG8A0AdAOH8b55pvWU7fbTUv8RCZfd50VequpQV+0CFVfjzlvHsbMmVYT\nlY3vS9GTv1IcDksb3u3GnD8fraYGsrL455kTrYqN0HF6lfLKy62a7N4KG7u+kSKW4erZQwOcp0xB\nORyQlnZRU9zt5kTWbKtDMj3dqry4RH28SByMI712NOfMwZw7F3PuXNTEiaj4eBxKoXV1WfZLSMBx\n9ixK13FUV1vFENOmQXy87aVHZCc/GvqEAMjJQQUCrL5hirUrGOa4hGkilGHCOUFNu3zZgpFGRQrX\nFpcLlMLUdcxJkyhP9pA/cSKmUtbOPyEBc8qUmLGXOPlR0LfOWjt5Eq2mhuDixeHjpsuFamiAnJyw\nYqG0v0cmw4VzTk3JwfB6rM7Iv/wF1d2NMXPmkBUYInEwPmj79qE1N4PLhb5qlTUEpLISIzMTfeVK\ntKNHUXFxxH9RjxEMYk6ejHboEMbMmZa9cnPR6uoIzp5tTXizabhNwjWjIZRMDQQsrZPk5H4qdioQ\ngKws63hvzbXd3ji2YZhwjqH1kUDo7YvQTp4cOhwjEgfjgtbcjNJ1VGtreKym6uhAaRrmLbdg3ngj\nKiGBmRletM5OtPp6lNOJo7YWR2Wl9XVrK479+20dbhMn/00YoFxo9u4QtK+/tjL4SsXE46Ad+e5N\nUwFrzKNWU4M6fRojK0vsGUm4XFaYzO3GWLZs0L2Hy4U6d468QDMoZW2+mpsxUlII5udbGjhutyVA\nZ2NFUQnXfAPCmX0uDgYJ19H31snL7i46+V5hBmCNeTRmzgRdx0xOFntGEPqqVWj791u6M273oHsv\nWFhodSvX1Vm6NcEgZns7waIijBUr0A4csK7tlSKxa7hNdvLfhFBm//rree1oY/i1yxJSEqIDtxsz\nMxNj1iyxZ6ThdltyBCHdmYH3XkKCtZs3DFRDA0Z6OsFvfQvjnnsgIeHitTYPt4mTHyWhKTVaWRkE\ng/y+pB6wdveG1ytzQaOAgTYcipA9zYkT0crKLnmuMM7U16N9/rlV1hwMWklUXcdYsMAK19TUoH3x\nBc4//hHnu+9a85ljAHHyo2TEsYDi4COey6pvv5QGvRBRaG1tMHkyyuezErEOB+b06VaobdIkjNWr\n0Rob0c6c6ZestTvi5EeLjH+Lfq7EhmLvyGdAIhasuP1fOuLQ777bOicu7mLC1cYa8n0RJz9KRgrL\nXE4oQBhfTJcLGhrAObj+4LUjZ/t9LWG4yEdftYrgtGn99eHdbv6PazbGDTdg+v3oixZhBoPoDzwQ\nrqt3/PnPON95x5KetuG9Kk5+tIwQlpFW98inXz/DABuFcixhJAwX+QxMxPbF4bBCOb1yJKquDugz\nG+JSfRBRjpRQjhGhuuow0uoe+fTaiMZGtMZGS+s/1NUq2IqBcx7MvhIkA3pd7IY4+TEiVFcdQlrd\nI5+QjZTLhVZRYU36OnkSMz5+vJcmjDHD9a8M1etiN0Z08i+99BIlJSUkJyezdetWADo7O9m+fTuN\njY3h+a7xcmP0Z4RxZUIE0Ffrf+Bubt+x8V6dMAqGlX0OzYEY2L8SUiO1MSPG5O+44w42b97c77U9\ne/aQn5/Pli1byMvLY8+ePVdtgZGIJFXthZGfT3D+fPTCQtsOjogV+ubCtH37cPz5z/xn+zHo7sb0\n+UAptPLymLpvR3TyBQUFJCYm9nvt8OHDLF++HIAVK1Zw6NChq7O6CEWSqjajT+dyyMEPyrEI0UGf\nUldSU1EdHdwx1YVWWYnq6grPeYil+3ZU1TU+nw+v1wuAx+PB5/ON6aIiHqmZtj0DcyxCdNCv1NXt\n7h+Gy8mJyfv2GydelVJjsY6oYqik6mtHzopjEIRxIBSHV2fPYqanoxobMTs6wOkkOHduv/xY39Gc\ndtSOH4pR7eQ9Hg9tbW0AtLa24vF4xnRREc8QNdOD6qoFQbgmhMKnWnMzWk1N+KPq7LQE5kJhuAGj\nOWMlZDMqJ19UVMQnn3wCwL59+1i4cOFYrkkQBOHyCYVP3W5rrF/o41BhmRgMtY4Yrtm2bRtffvkl\nfr+fp556iocffpgHH3yQ7du3s3HjxnAJpSAIwnhg5Ofj2L0bnE60jz/GKChAKykBvx/Xnj2crKxn\n5rfuwSgo6DeOU1VXD11uaTNGdPLPPPPMkK9v2rRpzBcjCJGC5FiiCIcDlZCA0nU000SVlGDm56Md\nPowCmk+dYfbevehOJ2Z8fDg+Hwrz0CtrYde+Ful4FWKKoYY/h+ibwPv8QCuPJ8yz9Q7PTqiWFrTG\nRvD5MObPR5km5uTJKL8fp96NOW2aNRkqJ+fiRTEiPSICZWOE1FVHB0MNfw4R7n9oaWFaa31MJeei\nneBNN2GkpaGvXYsxaRJ6YSHd//7v9BQV8f7CVQTnzcPMzkZVV4eviRVlUdnJjxHyaB8luFxw/vzQ\neuIhwTKXi6aJqbbf4dmKhASMm2/GdDoxliwJO+3g449TVbsHMzNzsD1jRHpEdvJCTDGk5ngvRn4+\npt+PMWMGngt+jN4aayHyGW5Xriorceo6NDVhzJ2L9tlnOP/nf2T8nyDYlsvRHHc4aEvy9Hu0FyKc\nYfT+VUcHa69Ps+rjq6svGa6zK+LkBaEvvXXU9xRMkVCNHXA4uO86z8VQzRAjAu2OxOSvEsNKngoR\nTUiyYs1CryVBLPaLOvree6am4di7F+V2Y9TWoq9ciXbwoOXgh3qasyGykx8jBs4EFaXKKCWkMR8I\niP2ilH5ywxUVaE4nKhBAKy+3HPxw4TqbIk5+jBhqJmistU/bigH2kxkCkU/YRqdOQVeXZbucHMy2\nNtSZM6i2NlRHB86330b74ouYsaOEa64SMv4vuhlov1jpjoxmQjYyJ0+2qqTuuAOAYGEh5tmzmElJ\nOGpqMNPS0E6cwIyLiwk7yk7+ajFMtl+IEgbaT57MIp+QjeLiLAffqzz5Tk8KRmEhJCRY/wBMEyMn\nJ2bsKDv5MUBVVpJ3ugKtLE6SdFHIUEnyvto1qrLSqqluasK4806xb4Riut2oqirIyUHbvx9HeTla\neTktZxTaHbPp+e53UXV1qLo6cDhiRlNedvJjgOrowGEakqSLUoZKkvfNsaiODhSEa62FyER1dkJm\nJqqzE0dZGVpHB9q5c8xqqEH5/WgHD1ra8lOmxJSmvDj5scDhYO0sjzzKRysjhWIkVBMd9LVTVhZm\n7+f1qZMxMjMv1sXHmD0lXDMGGPn5rHK5MCTJGpUY+fk43nw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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x106eb4ed0>" | |
] | |
} | |
], | |
"prompt_number": 26 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"When data are dense, a couple of tricks used above help the visualization:\n", | |
"\n", | |
"1. reducing the alpha level to make the points partially transparent\n", | |
"2. adding random \"jitter\" along the x-axis to avoid overstriking" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"A related but inferior cousin of the box plot is the so-called dynamite plot, which is just a bar chart with half of an error bar." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"titanic.groupby('pclass')['fare'].mean().plot(kind='bar', yerr=titanic.groupby('pclass')['fare'].std())" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 27, | |
"text": [ | |
"<matplotlib.axes.AxesSubplot at 0x1071a2790>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x1070e2690>" | |
] | |
} | |
], | |
"prompt_number": 27 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Why is this plot a poor choice?\n", | |
"\n", | |
"- bar charts should be used for measurable quantities (*e.g.* raw data), not estimates. The area of the bar does not represent anything, since these are estimates derived from the data.\n", | |
"- the \"data-ink ratio\" (*sensu* Edward Tufte) is very high. There are only 6 values represented here (3 means and 3 standard deviations).\n", | |
"- the plot hides the underlying data.\n", | |
"\n", | |
"A boxplot is **always** a better choice than a dynamite plot." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"data1 = [150, 155, 175, 200, 245, 255, 395, 300, 305, 320, 375, 400, 420, 430, 440]\n", | |
"data2 = [225, 380]\n", | |
"\n", | |
"fake_data = pd.DataFrame([data1, data2]).transpose()\n", | |
"p = fake_data.mean().plot(kind='bar', yerr=fake_data.std(), grid=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": "iVBORw0KGgoAAAANSUhEUgAAAXUAAAD9CAYAAABDaefJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niDoAGISoA4BB/hfPnfu+Z97RQQAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x1071b7490>" | |
] | |
} | |
], | |
"prompt_number": 28 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"fake_data = pd.DataFrame([data1, data2]).transpose()\n", | |
"p = fake_data.mean().plot(kind='bar', yerr=fake_data.std(), grid=False)\n", | |
"x1, x2 = p.xaxis.get_majorticklocs()\n", | |
"plot(np.random.normal(x1, 0.01, size=len(data1)), data1, 'ro')\n", | |
"plot([x2]*len(data2), data2, 'ro')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 29, | |
"text": [ | |
"[<matplotlib.lines.Line2D at 0x107246450>]" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x1072e5bd0>" | |
] | |
} | |
], | |
"prompt_number": 29 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Exercise\n", | |
"\n", | |
"Using the Titanic data, create kernel density estimate plots of the age distributions of survivors and victims." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Scatterplots\n", | |
"\n", | |
"To look at how Pandas does scatterplots, let's reload the baseball sample dataset." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"baseball = pd.read_csv(\"data/baseball.csv\")\n", | |
"baseball.head()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 30, | |
"text": [ | |
"<class 'pandas.core.frame.DataFrame'>\n", | |
"Int64Index: 5 entries, 0 to 4\n", | |
"Data columns (total 23 columns):\n", | |
"id 5 non-null values\n", | |
"player 5 non-null values\n", | |
"year 5 non-null values\n", | |
"stint 5 non-null values\n", | |
"team 5 non-null values\n", | |
"lg 5 non-null values\n", | |
"g 5 non-null values\n", | |
"ab 5 non-null values\n", | |
"r 5 non-null values\n", | |
"h 5 non-null values\n", | |
"X2b 5 non-null values\n", | |
"X3b 5 non-null values\n", | |
"hr 5 non-null values\n", | |
"rbi 5 non-null values\n", | |
"sb 5 non-null values\n", | |
"cs 5 non-null values\n", | |
"bb 5 non-null values\n", | |
"so 5 non-null values\n", | |
"ibb 5 non-null values\n", | |
"hbp 5 non-null values\n", | |
"sh 5 non-null values\n", | |
"sf 5 non-null values\n", | |
"gidp 5 non-null values\n", | |
"dtypes: float64(9), int64(11), object(3)" | |
] | |
} | |
], | |
"prompt_number": 30 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Scatterplots are useful for data exploration, where we seek to uncover relationships among variables. There are no scatterplot methods for Series or DataFrame objects; we must instead use the matplotlib function `scatter`." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.scatter(baseball.ab, baseball.h)\n", | |
"xlim(0, 700); ylim(0, 200)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 31, | |
"text": [ | |
"(0, 200)" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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LC4/W29qguNjBH/+YyLBhQaZPb2PDhkR69QpxySV++vQJz9C5+OIgF1/sPeZ7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\nLEShLyJiIf8PXIq2sfOZAR0AAAAASUVORK5CYII=\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x10737f850>" | |
] | |
} | |
], | |
"prompt_number": 31 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"We can add additional information to scatterplots by assigning variables to either the size of the symbols or their colors." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.scatter(baseball.ab, baseball.h, s=baseball.hr*10, alpha=0.5)\n", | |
"xlim(0, 700); ylim(0, 200)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 32, | |
"text": [ | |
"(0, 200)" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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19X1/4DTGun44ec+Tt0VFhqKinu/r+dDxrlpaLDo6YOFCF2Pg4EGHvDzD177m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\nRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x107198a90>" | |
] | |
} | |
], | |
"prompt_number": 32 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.scatter(baseball.ab, baseball.h, c=baseball.hr, s=40, cmap='hot')\n", | |
"xlim(0, 700); ylim(0, 200);" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x1073a3f50>" | |
] | |
} | |
], | |
"prompt_number": 33 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"To view scatterplots of a large numbers of variables simultaneously, we can use the `scatter_matrix` function that was recently added to Pandas. It generates a matrix of pair-wise scatterplots, optiorally with histograms or kernel density estimates on the diagonal." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"_ = pd.scatter_matrix(baseball.loc[:,'r':'sb'], figsize=(12,8), diagonal='kde')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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zZgtDh/oGTPiExwMbN1qwWuEb3+i+x3vPHoWGBolZs8K/HgONqGwqtLS0kGFW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mAAAg\nAElEQVQhcMlCN8LAtLdbmZQcDpNAAD79VKamRubyy7UJX4RvpIypwPvIkSOdRXs6iugEK/B2u63S\ntH6/RHy8SXq6QUqKzre/bS2WEUH36DtzxipFW14uUVtrlektK5MAkyuv1MTDUAiI9Tgo8zgoy+ha\nUebXDE40tHOsro2qhnbePVxHVWM755r9xIc7SItydf5Jj3KRFuUkNdKFcwLNH/f5rDR0gYAk8vmP\nssZGicpKhZycAHfd1U5eXvfpDJLEkOZ7C4Pj81mLIjUNFi/2c+SIgzfecPD1r7czc6ZOamrvP+dw\n0KPwlDB0VsEcqTOl4MaNDvbuVZg6VSMjw3pAEvfZ4BpTgXdraytJn7178ng8VFVVBWW7GzfCW285\nKS9XWLmyjfJyBykpJjt3OklP1y65uEMIvk8+geefd1Fbq5CSorNoUYC2Nom1a1WWLtW57DJNrEoP\nUU5VJi/BQ95FpecDusG5Fj+nm3ycavRxusnPrlPNnG7yUd3qZ3JcGHMnRbE0N5aM6PE91KJpsGeP\nA78fVq4UQ96jqblZYd06B4sX+3nySRcZGTqzZompCqOtoQHWr7eqC//v/+3luedUVq70k5mps26d\nkyuv1AY81UcYOmuUW8Xthra2ADk5Oh6Pgcdjra3askXlhhsCpKSIN0DBMqYC75EqohMISOzfL7Fs\nWYDJkw28XoOMDIPqakWUbbaJ3w/btiksWWJw440+Xn9dRZZl/u3f/EyebJCRYXcLhcFyKDIZ0W4r\nqJ7U/d8CusHec618XNnIg68eJicujNtKkpiZHjkuF2/qOiQn6wQCQ0tjJwydqppMm6YDJrNndy9U\nJIweSbKugfBw6/pevjxATo5BICDR0tJ7BVEh+EwTUlN1HA6rL1q6VKO9HeLi4MgRieZmCZ/P7laO\nL2Mq8M7Pz+fdd99l/vz57Nmzh2XLlgVlu1deaRIZ2YbDAbm5MG2aNXd41iy/yFJikzlz4Cc/sd7B\nJyXBl79svQ6OiRGFh8YjhyJTmhZJaVokX5mdxsZjDTz20UniPQ6+PDuNgqTxlfpj8mS4/XYfkgSF\nhXa3ZmKZO1ejsFBj9mzIy2sjSLMVhUFKToabb7augfBwmD3begI1TZPkZJ+4946SggL40pd8GIbV\nLwGd9UhmztSZOlUsuAy2MRV45+Tk4HQ6Wb16NdnZ2UGb3w1WoNehowBCbGzQNi8MwaxZdrdAsINT\nkbkqL45lubG8c7iOH6w7TmFSOF+enUZa1PjJd3XZZXa3YGIqKur6epQLIAsXmTmz52eSJO69o+2z\npXM9qCoi6B4BYyrwBoKaQlAQhNClyBLXTo1nWW4sL+2p5luvHOSqvDjuvCyFKPeY67oEQRAEgYmT\nRkAQhDHJrcrcWZrCn24pwK+ZfOWFcl7cU41fF5OjBUEQhLFFBN6CIIwJsR4H31o4iZ9fP4VPTjfz\n1RfK2XisHtMUq+0FQRCEsSFkA+8PPviAL37xi3zhC1/A+GzZv67rrF69mjvvvJOXX37Z5hYKgmCH\nrNgwfnBNLt9ZmMnfPz3Ht9ce4p1DtbQFREo4QRAEIbSF7ETJ4uJifve73/Htb3+787Pt27fj9XrJ\nzc3lwIEDNDQ0ECOWPgvChFSaHsljN05lc0Uj7xyu5b8+PsX05HBmpkeSn+ghM8ZNpOvSXZxmmLT6\nddoCOj7NoF0z8GkGTkVm2jjLpiIIgiDYK2QD794C6k2bNlFWVsa+ffuYPn06R44coayszIbWCYIQ\nCmRJYmFODAtzYmhs19h1qpldp5tZf7SeyoZ2VFkiyqUS4VJQZQnTBN00aQ8YtPp1Wvw6ft0g3Kng\ncSi4VBmXKuFSZTJj3CLwFgRBEIIqZAPv3lRUVHDbbbexb98+PB4P3j5qLYeHh7Nz585Rbp3QQex/\n+0z0fR8FLAm3/nQV6dH6/oFOWi/f18LOnTWD+v0Tff/bTex/+4h9by+x/+2lKMqAv9f2wLuhoYFf\n//rX3T6Ljo7mO9/5TrfP9u7dS2JiIr7PSih5vV5SUlJ63WZraysze0sQKoyKnTt3iv1vE7Hv7SX2\nv73E/reP2Pf2EvvfXoN56LE98I6JiWH16tWX/L7Kykqampr4zW9+Q1NTE42NjaxZs2YUWigIgiAI\ngiAIwxeyWU0OHz7Mfffdh9fr5f777yc3N5ef/vSn5ObmYhgGy5YtEwsrBUEQBEEQhDEjZAPvvLw8\nHnnkEXJycvD5fOTl5VFbW0ttbS05OTk0NTXZ3URBEARBEARBGLCQDbwBIiIiWLVqFfn5+YC1eODf\n//3f+f73v4+u6xw9etTmFgqCIAiCIAjCwNg+x7s/DocDh8PR+ffw8K7UXhERETQ3N9vRLEEQhD61\n+nXCnQNf4S4IgiBMHCE94t2Xuro69uzZQ0lJid1NsY3XC6+84uCjj8QN3g6mCRs2qLz1lorfb3dr\nxpamJnjhBQe7do3J7ueSHv2wyu4mCEG2aZPCa685+CypljAGHTgg8/e/O6iutrslE8fevTLPPeeg\nrs7uloSWMXfnCwQCPPbYY3zta19Dlsdc84PG54Pjx2VOn564+8BOhgEnTsgcP64QCNjdmrHF65U4\ncULm3Lnxee7uONlEdYt4GhtPKitlKipk8ZA9hjU0SFRVyTQ3j89+JxTV1MhUVsq0tkp2NyWkhPRU\nk9788Y9/ZPny5aSnp9vdFFvFxsKXvuTD6bS7JROTosDNN/vRdQgXxQ0HJSXF5J57fHg8drdkZMzP\niubDigZump5kd1OEIFmxIoDfD5GRdrdEGKqZM3UmTzZITDTtbsqEMW+eRmGhRpLoCrsJ6Uc/Xdf5\nwQ9+QEVFBT/60Y/Yv38/W7du5Y033mDNmjVs3brV7ibaKi4OIiLsbsXEFRkJIqPl0CQkMK4D748r\nRdal8SQiwupvhbHL6YSkJBNJDL6OGrcbEXT3IqRHvBVF4Xvf+163z5588kmbWiMIgnBp05Mj+P82\nnEA3TBRZ3OUFQRCELiEbeNfX1/OTn/yEkydP8tRTTyHLMmvXrmX79u0kJCTwwAMPoChiYaEgCKEl\nyq2SGOHkaG0b+YnjdFhfEARBGJKQnWpycQ7vxsZG9u3bx8MPP0xWVhbbtm2zuYWCIAi9m54czr5z\nLXY3QxAEQQgxIRt4OxyObnm7jx49SlFREQDFxcUcOnTIrqYJgiD0Ky/Bw5HaNrubIQiCIISYkA28\nL+b1egkLCwPA4/HQ2tpqc4sEQRB6NyXew9Far93NEARBEELMmAm8PR4PbW3WCJLX6+02Gi4IghBK\nsmPdnGz04dcNu5siCIIghJAxE3jn5uayf/9+APbs2dM591sQBCHUOFWZtCgXJ+rb7W6KIAiCEEJC\nNvC+OIf3+fPnKSgoYNWqVZw4cYLZs2fb3URBEIQ+TYkPE/O8BUEQhG5CNp1gbzm8p0yZwsqVK21q\nkSAIwsBNjvdwrNYLxNvdFEEQBCFEhGzg3RvTNPnDH/7A2bNnSUlJ4etf/7rdTRIEQejV5Dg3H51o\ntLsZgiAIQggJ2akmvTl48CBRUVF8//vfJyoqigMHDtjdJEEQhF5NjgvjeF0bpmna3RRBEAQhRIyp\nwNvlctHc3IxhGLS0tOB2u+1ukiAIQq9iwhw4FYnzrQG7myIIgiCEiBGZamL+/+ydeXwU15Xvf7X1\nqn3f0I4AgSBgdi+YGGNiY0jGS8bxOnHizMzn48w8e2YyHj9DcGI/J2PsN479MvESO/ZgAnGMMfti\ndswuFiEQEgKBkEBCSEjqRd1dy/vjUlK3ulvqlrpV3dL9fj76SOqu5dSpW+eeuvfccxQFO3fuxP79\n+9Ha2oqkpCTMnj0bc+fOBcsO3NcvKCiA1WrFz372M5SWliI/Pz90QlMoFEqIKUw24kKrHWkxOq1F\noVAoFEoEEJYR7xUrVmDNmjUoKirCo48+iqKiIqxduxYrVqwY1HEPHTqErKwsfPDBB8jMzMThw4dD\nJDGFQqGEnoJEIy7QzCYUCoVCuUVYRrx37dqFN954AykpKQCAWbNmYf78+fjFL36BJ598csDHlSQJ\ncXFxAID4+HiIohgSeSkUCiUcFCQZcegyXWBJoVAoFEJYRrwTExO7y7urGI1GJCUlDeq4U6dORU1N\nDZYtW4aamhqay5tCoUQ0RclG1LbSEW8KhUKhEEI24t3U1NT99wMPPIA333wTd955J/Lz81FXV4d9\n+/bhgQceGNQ5dDod/umf/mmwolIoFMqQkBOvR7PFiS5RhoGPqrXsFAqFQgkDIXO8f/7zn3t9ppZ4\nV6msrMTdd989qPPs3r0bGzduhMlkwvPPPz/oUXQKhUIJFwLHIifegEttdoxJNWstDoVCoVA0JmSO\n96pVq0J1KL+Ioojy8nK89tpr4Pmoqv1DoVBGKIVJBlxo7aKON4VCoVCiK493dXU1XC4Xfv3rX2Pd\nunVai0OhUCj9UphEM5tQKBQKhRBSx9tut2PFihXYtWsXAJLd5NVXX8Urr7yC9evXD7qC2/nz5yHL\nMl5++WU0NDSgtrY2BFJTKBRK+Ci4VcGSQqFQKJSQxmusWrUKZ8+eRWVlJZqbm/Htt99i/vz5cDgc\n2Lx5MyRJwuLFiwd8fIPBgIkTJ0IQBEyZMgXnzp1DUVFRCK+AQqFQQkthkhEX20jpeIZhtBaHQqFQ\nKBoSUsf7zJkz+Jd/+RcAwPPPP49XXnkFEyZMAECqTn788ceDcrxLSkq6Q0xoOkEKhRINJJoE8Cwp\nHU8rWFIoFMrIJqShJk1NTUhLS0NaWhr0en230w0AEyZMQGtr66COn5+fj4SEBLz00ktwuVwoLi4e\nrMgUCoUSdmi4CYVCoVCAEI94x8XFwWKxICYmBs8995zHdzabDQaDYdDnGEzlSwqFQtGCwiQjLrTa\nMSM3XmtRKBQKhaIhIR3xXrBgAaxWKwDgjjvu8PjuyJEjmDx5ckjOs379eixZsiQkx6JQKJRwozre\nFAqFQhnZhNTxTk5ORnp6us/v5syZE5JiNy6XC5cuXaKLlCgUStRAUwpSKBQKBQix4/2nP/0Jy5cv\nR3t7u8fnVVVV+Nd//VdUV1cP+hw7duzAnDlzBp2akEKhUIaKUQl6NFmccIiy1qJQKBQKRUNC6ni/\n9dZbiIuLwwsvvIBdu3bBZrPhgw8+wG9/+1s8+OCDgw4PEUURZ86c8Vi0SaFQKJGOwLHITTDgfItN\na1EoFAqFoiEhXVxpNBrx05/+FLNnz8Zbb72Fjz76CGVlZXjrrbeQkJAw6OPv2bPHK3acQqFQooEJ\nGTGoaLJgfEaM1qJQKBQKRSNCXjK+o6MD27dvB8dxKCkpwZUrV9DY2BiSY1+9ehVbt27F66+/jvr6\nemzevDkkx6VQKJRwU5YRg9PXrFqLQaFQKBQNCemI9759+/DJJ59gypQpePvtt2E2m7Fnzx689dZb\nmD59Op544gmYTKYBH//xxx/v/nvp0qVYsGBBKMQOCYoCSBLA96NRl4ts429tqCgCsgzodGRbQfD8\nXpbJj3oeRSH79N6O4okvXfaFL72635tAUO+Vongfh+P8t4FoIBB9Op0Ay5K2Gqz+JYnoh+01NGC1\nAmZz8PJGAhPSzXh772VIsgKOjeKbPwzw1x5V+yxJns+o+ixznH97qx6zPxtPCR5//ZzLRWyEovTf\n97rjqx91OIht721z/O0zUrDbAaPR+3P3di6KRG8sO3R6CrZPCRR/fU8o4X75y1/+MlQH+81vfoN/\n/Md/xIMPPgjdLe8kLy8Pc+bMwaFDh/D5559j4cKFITnX3Llz/X538eJFZGZmhuQ8gfLNNzz27+dR\nVCRBr/e9zfXrwMqVOsgykJ3tvTjUbgfWrePx6ac6xMbK2LRJAM8ryMjo2XbrVh5HjnAoKpKh0wH7\n93PYsUNAQYHk8+HQgqtXrw65/vuioYHBypV66PUK0tMDW5R78CCHbdsE5OVJMJmAzk7gj3/U4cAB\nHnFxMtLS+j/Gpk08Tp1isWuXAJOJnLujA1i9Woe2NgYFBaFfaDcUuj95ksXatTpkZcmIi/O9TXs7\nsHy5ARUVHPLzJXz+uQ4cpyAzs3/9OxzAmjUCams5jB4tdxvAXbs4vPWWAVlZckDH0YK+9G8UOGyp\nvoGJmTFIMtE35XAQSPs/fpzFunUCsrNlxMb2fH79OvDnP+tgswF79/JoaWFRWEie0c2beRw7xsFi\nAb75RkB+vqe9ra8nNkaSFGzdKkAUgZycyGyj4SKctufoUQ6bNgkYNUrqfvFubQW+/FLAyZMczpzh\nUFgoBzwosmULj6NHe/bZsYPHhx/qwDAKiop837eNGwUcP0763kgc6AqH/jdv5vG73+lRUCAjNbVH\nL+qzIopAcrKCL78UUF/PoaRExpYtnj5KOLhyhcGf/xxcnx4IXV2kTdXVkWsJ5uX56tWrKCwsDGjb\nkL6TLF++3GeRnPj4eLzwwgs4fPjwoI5fU1ODTz/9FDzPY/LkyVi0aNGgjhdKXC7A4WAg9+FLyTID\np5OBy+X7e0UBnE4GNhsLp5Mcz+XyvPNOJwO7nYGa1MXlYvo970hHFMnoa29d9oXLxaCri4Ekkf9l\nGbDbia7Vz/rD4WBu3Ud03/Oe4wR5ERGEKJLrEkX/28gyYLUy0OuVW/r3bst94XSS3+7Ji5xOwGpl\no1p3k7NicexKJ4qSBz7zRxkcokie497tV5YZj2dWbYMAeZa7upjufXvbW0kidl21x/5sPGVgqP2r\nJDEAiFGQJKJvp5OMfAaT6Kyri9zPnn4UsFj82yh1RNx9n5GAy0Vsbu/2rD4rLpeqGwYOh9L9d7j1\nJEnk+Qy0Lw4UWSby8zy5lnDNWjFKFOXlu3nzJmJiYsDzPJYvX45nn33W56LNb775BlOmTBlS2YjR\nBfqLpLFaAYOBTFn6wm4nP4mJZFuTyXPKQ21s6miL6lQOIoIn5JSXlw+5/vvDYvHWZV+IIjG07mEN\nNhvRdVxcYMdR75UkeZ7bZiMdRThGTYZC97JMriGmnzWCN2+Sdh4bG7z+u7qI0XOfPZJloKUFAc02\naEV/+j9c344/n2zCWwtLhlCqkUMg7b+v9qvaZ4fD8xlVn2VB8G9vLRZiL2y2vm38cCWctkeSiE3o\nHWZmtfaEmgTTB/rqRzs7yfH9jdL23ifSCIf+RRFoawNSU72/c/dl7HZyH/T6odNTsH1KoPjqewKh\nvLwc99xzT0DbhjGKJfQkJCSAvxU4ZDQau6tkaoEkeY74CUJgD77Z3PdbmtEIJCWRGx8T492odDrP\nBs3z5LzuozPBQkbaB75/JCLL8HhL96XLvuB5TyMvSUT3CQmBH0enI4apd9ygyeTf6XY6gxu50QKW\n7T/O3ekkulKn8vvSv6+2ZzB4Gz6WHXqnu3c7GiyTMmNx4YYdHV19TBdQwgrLejvdahs0m4kj0fsZ\nVe2uam99ERND7LZ6DJcLPmciyWxQaK5lpMBx3k6300k+MxqDH3jy1Y8mJva8WAWyj/t2ohj60deh\npKvL93XzPBAf73sftZ0DRC+qveb5oYmDD7ZPDxRffU+oiSrHW6Wurg4dHR3Izs7W5PyyDKxfL+CL\nL4Sgp70rKlh8+KEely+Hbg7j0iUGH36ox+nTA7udR49y+OMfdWhqGj6rgXbv5vHZZzr0quU0IBQF\n2LRJwOrVAuxBFh/cv5/Dn/6kQ2tr/9s2NwMff6zD4cORPVR24gRpw1eu+G4vdXUsPvhAjzNn+m+P\nNTUs3n9fj5qayDRFW7fyWLlSgMUSmuPpeRYTM2Nw5EpHaA5IGTSXLxP7WVERujbY2Ql8/rkO27d7\neyCrVwv4j/8woq4uZKcbcZw6RWxQfX1o+6wDBzh88okOLS19b+dut2w2ck83bRIiftDEF1YrsHy5\nHv/1X3ov5/v4caLnhobA9bxlC49VqwT6ctkHkdnb9UFnZyc+/vhj/MM//IOmcohiT5aLYCBxaSRG\nKlSo8YUDfeMm1zK84sRFkcT/hcoQqvGbwd9vEjcYyL1RlMC31RJZ7rvtq7NBgVyHGooTqdcsSWRd\nRig71LsKErGzti10B6QMClkenP30h79julxkan442duhRrUxodYhOW7/dl61WaJIBmZcruiN61fj\nmh0Ob33KMhO0nknc/ciKhQ+WqIrxliQJv/3tb/HII4+guLjY73ZDEeOthgQEOyWhKCQGMNQp0dR4\n8IEsBpBlMtUUqjjxSIjxJo536OLMnE6iJx9rh/tEkki8aKC6tdlImxpofOhQ6D6QNhxMe7RY+o8X\n1wrVeQr0vgeif7tLwuMrK/HBw+OQTLObhJSBtv/B2E9/2O1kyr13WBlZJExCG4YTQ2n3w9WPBmOv\n3e1WV1dgIXjhZDD67+wkv92z/AAD8w2CtZnDhWEb433gwAHU1tZixYoVWLZsGaqrqzWRg7zhesYX\ndXX539Y9HIVhSINUFyD4iqvq6iLHV2PI3Y/hbx+z2bvT6OqCR2iEv31ZNrAHKxyriMMFy3o7r6oO\nHY7+46jVEBX1vqrx2iqKQoyVehx/sdkc19Ne3FFj6rq6PHVqMkX+oiw1jtViIfL7mlJU26N721Vf\nhno/KzExRN+9w3h87avSuy2Ha52CIIS+AzEKHG7Pj8e2mhuhPTAlaNS2qLZXf7bBV3tT26Z6DNV5\nUTEae/J6u68H0ukCd7qtVnJeu91/H9P7WvrDXz8Q6agJDByOHhvkj/76Kkki9stmI/+ruusvQYI6\nAAN4DhYYDORe+7NXKmR0uedYkRKO4Z6lqrdc7np0b2P++jw1n/dA8ac7LQjXsxLSPN7hJjc3F4sW\nLcLdd9+Nu+++G8nJyT63C3ce7xMnWLz9th42G1BYKKOmhsVf/6pDUpKCpCTPlnj0KIcNG3TIzZW7\nH9QNGwSUl3NoaWGwf7+A4mKp+0350iUGn3+ux8WLLC5cILkkKypYfPWVDllZEg4c4HHoEO+xjy9E\nEfjd7/TYsUPAbbeJ0OuB7dtJrvHiYv+5xv1hsQCrVunQ3MyguLjveadIyOO9cyeP3bt5FBZKMBhI\nTOBXX+lgMilYu5YozlcudQDYu5fDb35jhCDI+OYbHdLTZfROnrN3L4flyw2Ij1dgMilYuVIPlwsY\nNcrzmHV1DF57zYD2dgZjx8rgOHKPN2zQYfNmDjU1HFpagNGjQzPxNFS6r60lebpPnWKxfTuPyZN9\n55E/coTDxo06jBolYft2Abt28aiq4pCU1KPT+nrgpZdMqK1lcfvtPVa+vJzDunVk3507BZw4waG4\nmOTQ3bGDx969PXnzDx7ksGWLDnl5kqYFdgLVf3qMDr8/0IBFpSm0mE4ICab9nz3rabebm4GVK/UQ\nRe/neNMmAUePkrzygkD6gK+/1kFRFKxbR3J/v/mmAQYDUFTUYx+dTuCrrwRUVxNbHoxD0tQEvP66\nEXV1LI4eZbFnj4Bp0ySfC9fOnWPxxRc6JCYqSE7u25Zs2RJYHxIs4bQ9am7//ft5nD3LIT1d9hqd\nVbFagb/+VcCVK0Tnvti2jeTtPneOA8Mo2LCB5KTesEEHs1lBWpq3DltbSR0Oux3Iy/P+/tAhDps2\nEXu1bZuAM2dIe3EfSPnmG2K3srMlbNokYMUKPbKy5JDkoh6o/q9eBZYsMWLfPh4zZ4pYtUrAqlV6\nTJwoYt8+Hu+8o0d+vgyLhcHq1TrExioA/Pd5mzYJOHKE2Opg25csA+vWCTh1itw7rYsVbd3K4+DB\nwJ4VzfJ4DwWffPIJLl68iIKCAjzzzDOayEAqM3nGganVmnxv2/NmqCie27p/13sf923U7Xqfty96\nx8HJMvlsIMFFqtzREpjU+3546rDvmDVVT33pWq1Uqh5T/dv3doyX3sk5GMiyEtJ4/6FCvWZJYvqM\nieytd1/tz1/MuPu96ut+qv8PtG1rQVGyCQVJBmytbsXCcSlaizNi6W3T/Nk49XntseOMm51wf549\n91Ofk4HSE0vM9Gl/fT0j/gimD4kk3G1mX885w/Rs1/exPPXWX9+g2nJ/9lpReu6Pet/89e3u1xMJ\nNksUAZ5nwDCkfaiyq+1X/dtdV/76PNU/Guh19bbtWqK2k1ATVTHeFy5cwLZt2/Czn/0MH374IebO\nnYuioiKv7cId462GGej1PTHeNpvvKSp1asl9NFBNM8Vx5Kb2Hn222XpCJdTCAHY7Ob66aC2QEWu7\nnWyvjgwEs68vHA4iU39voZEQ460uYlXDBNx1aLcTHfQ1+tTaSqaD1X16I8tAR0dPTu++jtne7p2i\nSJ3iZBhyj0P1Zj+Uum9vJ3LLsndsoIp7+1enJtW85u60thL9uI9Wu98z9ZlRdagublbvr6/nTAuC\n0X/1dRuWbK3Fhw+PQ4w+6sZAIpJg239vu+3vOe5tO93bpnqMtjaSeq33vupU9UBGlzs7iX1QO/++\nZnP89UG9GWw/4I9w2x73cMv+rtPhIPfBX9pWUezpZ2NienRnsxEb4i/W324n99FXOGBvWwd433P3\nfsnhID+xsaFZWzAY/V+9Sq4pLY2EkzgcpC3LMrHzamiUexsL9FkJlt62XkuCuZZgYryjytqfP38e\nkyZNAgCUlZWhurrap+M9EM6dIw3IYOh5sNV4bKORNATVSWIY8lnvkRKHw3fuYTWnq2oE3I2BL4er\nt1FhmJ7PeL7nbdr94Zdl8rAbDD3xUUYjeYhkmcgx2PyaQ/0gnD/fcy90OnItasytTkd+7HZiuHo/\n/BzXox9VNyYTMSJmc/8xaElJ5Lf7vXA4iP44juzvHn6iOnyKQuR0dwDd86CqI7vqS5QsD03O0764\neJG0MZeLyKq+EAoCMbiq/tRRD7X9+8rvqlb9Ux1xlu3Rhdq5+Oo0VX27497u1TbvL1es+3mihZJU\nE2bmxeP9Q4144a5crcUZMbS3E0dj7FgS5jRmDPksNranDTmdnjakd3tzb5sqBoNvB2ow4Rz+XmhV\n3O2Nu0PkLkt/19IXXV3edQhCyYULPX2rWjQuMZHYIrO5p5BR74GL3nK52+ZAXrzMfokAACAASURB\nVEB4ngyaqKjb97ef0dgT99v7vrrbIH/33H3hpjpwp9pMNQ+8Fths5NxpaZ4x2r1nbNz14y6r+6Dc\nYP2McBSWGyjhykkeVTHep06dQmpqKjIyMtDW1oarV6+itLTUa7tgY7x37gRWrzZg3TodHA4Zp0/z\n2LRJh7NnWezcKaC1lcH582x3nB7QE4c0erSM8+dZLF9uwI0bDAoKZA8D4XSS2LRz5ziMGRNcjJ8v\n2tpInFlnJzmXyoEDHDZvJvFlW7YIqKrikJws+41ZDCehiPU7dgx45x0DKip4XLvGYOdOAfv2Caio\n4FBdzeEvf9F1x7GzLDBmjP+50/37OWzdqgPPK/jNbwxwOIDSUjkoI9fZSfTe0tJ3jHtFBYs1a3RI\nT1eQkOCpc0Uh7ebECdJuduzgceAAj9GjQxdrGazurVbgN78xoLKSw6FDPE6f5lFezuPQIRKbbTTK\nuHqVxV/+osO1ayzWrRNw6BCP227zLfP//I+Azz7TY8IE0cMxlyRg7VoBp08HH7sny8A77+ixbZuA\nKVPEiF4tH6z+yzJi8Omxq+BYBiWpEVR+NkoJRP//8z88fv1rI1JSZLz4ohnx8RLee88Ik0lBUZEc\n8LMO9MSJs6yCr7/WwWBQkJExdLZWjTXPzJQRH09ykq9cqYdeT+To7Ax8bU5vrl8nMe8OB5Cb2/81\nBdv2GxrIOpFt2wTk5Ig4dIjH6tV6HDjA4/p14OhRFtu3E3tTWip1O31NTWQdlCwDOTkKbt4k96uj\ng4GiKFi1So+4OAWpqeG5D1u3DmytVFWVdxx+VxfwySc6bN0qIClJQkbGwOUaaL9bVQX89rdGHD4s\noLRUxFdf6bB6tQ6TJonYtInHa68ZkJ8vefgQzc3A558T3yI5WcEXXwiorye2XauXB60JJsY7qrKa\nmEwm2G+lPrDZbDCHaBVV72kjhhn4m+dIbXThQNWlL50yjOL3u76ONVSo8vW/XZgFCZEMaoYSlXCN\ngI00zDoOy+YXYuWJa1h54hqkPuJSKaGlr3YfCc/lQHGXfbDXEW49MIxvW6LaGn/nHy73J1IgPo9/\n29OfvY/Ea4pkoirG++LFi9i2bRuee+65kMd419SQ3+obrMFAGpte7x1qAvSECaijflYr+c7XKKAa\n+hGqKRT3aTUVX6EmghD+qUJfhCrWT70n6jSjGl+n1/cfauKOWvZbrydx2SbTwKaPek/Z+sNu9x/2\n4N5u1MWvoQzhGYjuL1wg+lPLvLuvPVDj/HyFmviid6iJOy4X2X8go/tq2kUtM5YEwkDbfrPFieV7\nLqHJ4sQd+QlIj9FBAeAQZdhdMrpEGQlGHpMyY1CSYgJDezqfBKL/tjaSMWTsWGJjRo/uCTVR7Uig\nzzrQ87z3DvEYCnyFtvUXahIMaqhHIP3HQG2Pr1ATNQ+0GqLZ20b2FWrSl/0NBWrY20DsmC/ZnE7y\n4yslcDAMpt+trSXnLizskScmhlxnWxuQ4mP9t/s9cDp7wllHKsM2xrugoAA6nQ5Lly5Ffn5+yOK7\nAWJ8g6F3A+vLIQh1zJIvR02NT+99vkielu+PQO5JIMZPfYECPOP6giVQQ9uX0XdvNwPtDENNf7Nj\n7m2rP9QXIl8M5jmI5nYcCGkxOrzxvWKcu27D0YZOnL9hB8cwMAgsDDyLBAOPG1YX/s/OSzAJLH46\nIxuTs/oJAKb4JDGxZ7GYamN6r1cIxqlSn3ct1hj4egnu/f9gwtjCva6nt+3pvdbD3/l72wP37cJ9\nHwZjt33J1pfNHCrcXSl3eTjOt9MNeN4DreWPNqLK8QagWQpBCoVCCScMw2Bsmhlj0/y/xf/9TAV7\nL97EW3suY1pOHJ6bmQ0DT+N+KBQKJVqIeIu9fv16LFmyBACwfPlyPPXUU3juuedw9OhRjSWjUCiU\noYVhGNxVmIj//puxsIsS/nFNFc42R0j5OwqFQqH0S0Q73i6XC5cuXQLDMOjo6IDFYsGnn36K733v\ne/j888+1Fo9CoVA0wazj8Iu78/H0bZn45bYLeP9QA+yuMFR6oFAoFEpIiWjHe8eOHZgzZw4URUFt\nbS0mT54MAJg4cSIsFovG0lEoFIq2zClMxB/+Zixu2l14atUZfHy0ERdb7YiiNfMDRlEU2F0Smi1O\n1N6w4URjp9YiUSgUSr9EbIy3KIo4c+YM7rvvPqxevRpWqxXGWysTysvLkeSr4gaFQqGMMBKMAv7t\n7nzU3+zC+qoWLNl6ARanhLwEAxKMPGL1HAw8C4YhJaE5hgGDngwK3WXQfRxbdeDdv1O8/uj5U/Hx\nZe/vPM7T/Zn/7QGgS5RhdUqwOCRYnBIsDhGdDgksyyBWzyFOzyNGx+FHWT4ugkKhUCKIiEwnePPm\nTfzyl78Ex3GIi4vDxYsXkZeXh9tuuw1jx47FihUrUFhYiKefftrn/gcPHoTVSuMetcJsNlP9awTV\nvbZQ/WsL1b92UN1rC9W/tnAch7vvvjugbSNyxDshIQHTpk1DXV3drVEaBmVlZTh58iSOHTuGCRMm\nYNSoUX73t1qtIckjTRkYocrjTQkeqnttofrXFqp/7aC61xaqf20pLy8PeNuIdLwB4PHHH+/+e+nS\npXj44YfxH//xH7h06RIaGxuRnZ2NKVOmQEcTSFIoFAqFQqFQooCIdbzr6+vx/vvvg2VZlJWVAQAa\nGhpQUlICAHjxxRep002hUCgUCoVCiRoi1vHOysrCr371KwDA22+/jZaWFuTl5WHp0qUaS0ahUCgU\nCoVCoQRPxKYT5G7VZJUkCQ6HAzzPo6GhAcuWLcPWrVs1li56kGhq3yFHFLWWIDKRZfJDIVB9hIc3\nd19Cs8WptRgUSsBo3WdQWzS0RKzjDQBHjx7Fz3/+c6SlpSEhIQHvvPMOXnrpJZw+fRqXL1/WWryI\np6UF+PhjHQ4d4rQWZcRw5gyLDz7Q4fJlRmtRIgpJAtavF/DllwIcDq2l0R5JAtatE7BmjQAn9RFD\nSlqMDv9rXTVarFSxlMinoYHBRx/pcOqUNu6Y0wmsWSNg3TqBDtQNERHteE+dOhW/+93vYLPZUF1d\nDbPZDJ1Oh9mzZ+P06dNaixfxSBIDu52hHfsQ4nAADgcDUaSOtzuKAths5CfyEpgOPbJMdGG3U32E\nmqduy8SCMcl4a+/lEVFIiBLdiCJu9dPa9BmKQuwQtc1DR8TGeIuiCJ7nwbIsjEYjFEWBLMtgWRan\nTp3CvHnztBYx4klPV/B3f+eAwaC1JCOHSZNkFBc7EBurtSSRBc8DP/iBC7IM2h4BCALRh6IAer3W\n0gw/HvtOBv7hyyocudKB6aPitRaHQvFLXp6CZ591wGzW5vx6PfDQQy4wDLHTlPATsWo+ceIE1q9f\nD4ZhUFRUBL1ej5deegkGgwGlpaUoLCzUWsSoICZGawlGFiwL6nT7gTqYntAXkPDBswyemJKBz8qv\nYVpOHBiGzkBRIhet+4xbRcEpQ0TEhpqkp6dDkiTIsgyDwYD8/HzcfvvtUBQFTU1NkGgwEoVCoVD8\ncGdBAiwOCWeaaTU/CoUSOUSs462mE1y2bBnq6+vR0tKCyspKvPrqq8jLy8ORI0e0FpFCoVAoEQrL\nMLh/bDI2VN3QWhQKhULpJmId797pBKuqqjB+/HgAQFlZGaqrq7UUj0KhUCgRzvySZBy41I5OB83x\nSaFQIoOIdbyBnnSCqampAADjrUAkk8kEq5VOH/aFogDbt/PYsIGmK4tE2tqAlSsFHD8e0Y/gkGCz\nAV9+KWDfPpr2UhSBzZt5bN7M09ReISDewGNyViz21bVrLQqF4kFjI4NPPxVQXT28+oA9e3isXSvA\nbtdaksglou+4mk7QbrejubkZ9lt30mazwazVEuAoQZaBq1cZNDSwmifnp3jT1cWgsZFFa2tEP4JD\ngssFNDSwaGqiupAkoLGRRWMjSx3vEHF3YQJ2X2jTWgwKxQOLhUFTE4vOzuG18LexkcGVK9Tv6IuI\nzWrSO53gxIkT8cUXX2DRokWoqKhASUmJ1iJGLGqBEjV9m8mkrTzDha4ukm4pFCmXMjNJqsfh9v4o\nisSRDmaVfHw88NRTjhGXykp9Tt2zvej1wCOPkCkqnU4DoYYh03Pj8dbey7hpdyHBKGgtDiXKcbnI\nC/JgsxKNHi3jmWccSEwMjVxa4nCQjF6CADz4oAuiqH2mlkgmYru63ukEi4uLMW7cOCxZsgQpKSlY\nuHCh1iJGJE4nmbYHSG5O2nmHho4OYNUqHUaNkrFgQWhe5ZOSQnKYiGL3bh41NRwefdQR1PXFj7BU\ny6IIrF0rQBTJc+rufNMOK7QYeBbTRsVhX107Fo5L0VocSpSzbRuPxkYWP/yhc1DPKsMAt6Jooxqr\nFfjiCx3i4xUsXuwadoNJ4SBiHe+pU6di6tSpHp8tXrwYixcv1kii6IBhyFun+jclNKjFBTgahtwn\nPA8IggKWRo30izrCT5/T8HNXQSI2VrVQx5syaDiO9LH0uSUQn0MZcTOWgyFiVVVTU4NPP/0UPM9j\n8uTJWLRoEZ5++unuwjkvvvgiYkZodZjr10n4iK83S0EAvv99FwBahSqUxMYCTzzhDKnj3dlJpuhS\nhpEvcOedImbNCn2YREcHGSUeLrMEPA/MnUtCweisVPiZmhOL5XsuweqUYNbRt2fKwLn3XhGS1DPA\nNVhaW4kzr+WsX1sbcaATEoLf12QCHnnEBZalLyOBErGuWWpqKpYuXQqe57F8+XLcvHkTeXl5WLp0\nqdaiaUpzM/DZZ3qUlMh48EGXz22owx0eQmVoVTZsENDUxOKZZxzDJtSCZUPvSMoysGaNDhYLg6ef\ndgyLaqwkJEwHSWLw5JMOWjkuzBgFDqXpZhy70oG7CodBUC1FM1gWIZvRs9mAVav0MBgUPPmkU5O+\n224HVq/Wg+eJDAOx36HuG4c7ETshnJCQAP5WKzQajbBYLGhoaMCyZcuwdetWjaXTDpMJKC6WkZ0t\nD+l5u7qALVt4HD1KR4uCQZZJeqU9e3jIvW5ZXp6M0aOlEVVK/cIFFmvWCGhuDnwflgUKCmQUF0vD\nZnSY54HCQhmFhZJHp9VXe6EMjlm58Th4maYVpISHs2dZrFsnoD2IJiYIQFGRhMJCWbMwRlWGoiKZ\nDtr14sgRDlu38t0L4UNFxKu5rq4OHR0dyMnJwTvvvANBEPDuu+9i7NixyM3N1Vq8IScmBli82Huk\nu7UVaG1lUVgohyW+1mYDzpzhkJEhY+pUmucsUFwuYpABBtOni2hrY+ByAbm5CmbNGnl6bG5mcO4c\ni9JSFmlpgXuWo0dLcLmGT1gGywIlJRJk2XOGyukEzp7lACiYMQMj6qUs3MzIjcefjl2FJCvgWDon\nTgktjY0szp5lMWkSg/h4xet7mw24fJlFXp7cPcMlCMD8+drm3eN5YN684GSQZTKIkpQkD5vwP1/U\n1JA0t9OniyG1xRHteHd2duLjjz/GCy+8AADdubtnz56N06dPj0jH2x8HD/I4dYrDY485kZfn/dAP\nlqQk4PHHHdQRCBI1PZyiECO7bp0Am43Bs886RmT2ismTJeTkyMjKCryNyvLw05vTCaxdq4MsAz/+\nsaM75afBADz8sAMMQ53uUJMWo0NajA6VTVZMzBwG8UqUiGLGDBHjxknIzPRt286cYbF9uw7z5zsx\nZUp0T2fV1zP44gsBEydKuP/+4Zuw+4EHXHA4Bhb73hcR63hLkoR3330XTz75JOLj4+FwOCAIAliW\nxalTpzBv3jytRYwoxo6VERurICUl9E63Slpa2A49rHEfEZg5U4TDwYzY3Op6PZCTE1wbZdnhpzdB\nAGbNckFRGK/47uRkbWQaCcy8FW5CHW9KqImJAWJi/Nu23FwZM2aIyMmJbqcbAFJSFNx+u4js7PD5\nG5FAuNZeRazjfeDAAdTW1mLFihUAgMceewwfffQRDAYDSktLu7ObUAgkXlRrKSj9MXFi9BtdLRhu\nemMYYPLk4XVN0cDMvHi8vqMOP52eBYamYKAMIWlpQFra8BgdNpuBO+8ceaGSoSJiF1emp6cjMzMT\nADB58mSUlJTg9ttvh6IoaGpqgjTM6ylbLCQxPUCqZLW2aisPxROnE6ivJzHclMHT2UkW8LrjcpE0\nVyONlhbyQwk9o5ONcEoy6m+GeLUUZUTQ3o6QLbTr7CQZRSIBd3/DHVEcmTY43ESs462mE1y6dClq\namrQ0tKCyspKvPrqq8jLy8ORI0e0FjFsdHUBq1fr8NVXpLLd8eMcPv5YjwsXIvZ2jTj27uXwb/9m\nxs6dETtpFDW0twOffqrH5s2eOamOHiXt/vLlkTMy2dkJLF+ux/LlenR2ai3N8INhGMzKjce3l29q\nLQolymhuBj75RI89ewZv8y0WYMUKPdav1z4PX1cX8Je/CFizhvcaSDp2jNjgS5dGjg0eCiLWk+ud\nTrC8vBzjx48HAJSVlaG6ulpL8cIKywLJyQqSkkgFQLNZQUKCAoMhuHiq8nIOBw5wUCcHTp9msXcv\nF/LUOCMRs1lBTo6MuLjgwwVu3CBlhy9dAvbv53DyZMQ+hkMCzwOpqTISEjzbt9msIDHRd7uvrPRs\nyzU1LHbu5GGxDIXE4YPjgFGjgNxcWiU1XMzOi8e3dTStICU4dDogOVn2mbHEHUUhgwaHDnFeKUEr\nK1ns2cNDkoCUFBmJidrHSKvVrnme/K3a1q4udxustZTDi5AP10mShN///vd47rnnoAtB7i81naDJ\nZOqOyTOZTLD6mhcZJuh0nikDx42TMW6cM6hjiCJ5+Lu6GJSVSYiJAU6d4tDYyGLcuJGVOzoczJwp\nY+bMgc0TNjezOHaMg9ms4NAhHsnJCiZNCu7+DifMZuDRR71jdiZOlDFxom+9VFRwqK9nMWaMhLQ0\n4nhXVHAoKpL6XOAU6TidwPHjLBgG+NGPtJZmeDIxMwYNHQ7csLmQbNJ+xJESHSQkAE880X9socsF\nHDlCnOuyMsljQfjp0xwuX2YxdqyIhx+OjDhFSQJu3mTB84Asix62dcIEGRMmjNy+KVyE3PHmOA41\nNTWw2WyDdrzd0wnW1tai9Vags81m604tSPENzxPnXZLQXelv/nwXbDZmWJUoj0aKi2U88ogL6eky\nRo2Sg57JoAD33uuCxcJ0Z9qZPVtEaamMUaOiW5cJCcALL5Bh/OFSzTTSEDgWU3PicOBSOxaOo8aQ\nElp0OuAHPyApZHtnYZo3z9NuRQImE/DQQ87uqsO9bSsl9IRljvuBBx7AypUr0TKIFUK90wkWFRXh\nzJkzAICKigqUlJSEStxhS3q64pEvOSWFFG6haAupFCYjJgYYNUpBaqrWEkUfycnwyFefkADk58sY\nDokqyAwXzXgSTmbnxePAJRpuQgkPGRmKz3zeve1WpJCZqSA9ncgVqTIOJ8KyMuzLL79Ee3s7du3a\nhfj4eHBuwYq///3vAzqGr3SC48aNw5IlS5CSkoKFCxeGQ3QKhUKhDHOm5sTh7b2XYXVKMOtoMD2F\nQhk6wuJ4P//884POkTp+/HgkJyejuroan332GViWxWuvvYbCwkK0tbXBbrcjJoYWQaBQKBRKcJh1\nHErTzTh6pQNzChO1FodCoYwgwuJ4l5SUYNeuXairq0OXW3JehmFQWloa0DFiYmKwZMkSvPnmm92f\n5eXlYenSpSGXl0KhUCgji9l5Cfj2Ujt1vCkUypASlhjv9957D1999RUURUFGRgYyMjKQnp6O9PT0\ngI8hCILXAsqGhgYsW7YMW7duDbXIUc3NmySv9LVrA5tluHSJwbffcj4T6FMGx8WLLA4e5LyKw/jC\nZgO+/ZYbUTlTW1pI243UgjFVVSyOHOEgalxwTpaBzZt5bN9OwyJCxe158ThS3wG7a3gXY6OEHne7\nJctAeTmLM2eiMy2sogAnTrCoqAiN/FVVJGvXMK9xOCjCMuJ98uRJvP76692VJ0PFO++8A0EQ8O67\n72Ls2LHIzc0N6fGjlStXWOzfL4BlXcjICL61V1VxOH6cQ0aGgsJCuqgrlJw6xeHsWRbZ2f1n3Ghu\nJjleJ02SkJc3PEoL98elS6TtmkwKUlIir+0dOsSjuZlBQYGkaTagtjbgz3/WQadTMGuWHTSp0+BJ\nNAkYm2bCwcvtmFuUpLU4lCjC3W7xvIzduwWYzQrGjXNG3QJvmw3Ys0cAzwNjxjgw2CzQ+/fzuHmT\n2Mwk+lj5JCyOd1ZWVljybKsj4LNnz8bp06ep432L4mIZDz7oRE7OwByX224TkZsrIzc38hyfaGf2\nbBfGjmWRnd3/KvGcHBmLF7uQmjpy7sOYMTIMBify8iLzmufPd8Fq1T4FZ3Iy8PzzXbcKamkry3Di\nnuIkfHO+jTrelKAYO7bHbsXEkNS9er0SdU43QOzJ4sXkhSEEpVewYIELXV0Mdbr7IGSOd0VFRfeC\nyjlz5uAPf/gD5syZg/z8fI/tJkyYMKDjOxwOCIIAlmVx6tQpzJs3b7AiRyTNzcC33wqYOFEKePTZ\nYADGjx+445KSgogcbYwWOjqAPXt4FBbKKC311GNqKgJ2pHkewzaNnKKQKp2iyOCOO0TcKkqLmJjB\ntd1wQ1KCDV1qLVkG9u0jyrnjDhGs2+zvbbdFrp6ildl58Xj32ytos7uQaKTFdEYijY0MDh3iMXWq\nGHAdALPZ025F+0xxIOkDr15lcPAgjylTxD63J4NMNB1hX4TM8f7v//5vr882bdrk9dl7770X0PEk\nScLrr7+Ouro6vPbaa3jsscfwwQcfwGAwoLS0FIWFhYOWWQssFqChgUVBgezz7bKtjUVVFYuMDBlR\neonDkmvXGDgcvg1URweDM2c46HTwcrxHIg4HUFdHwmvUxEOiSEKanE4G06f3ON4UT5xO4OxZDoCC\nGTPgUWH2yhUGDIOAZk8ogWEUOMwYFYddtW34wQRaMWQk0tLC4Nw5Fnl5DMxmBa2tLAoLZY+X3uFO\nILblxg2ip9xchub5HiQh6/4CdagDpaOjAxaLBU6nEy+//DJYlsXtt9+Oo0ePoqmpCZIkeeQHjxZO\nnuSwdy+PRYtcPp20oiIZjz/uRGoqbdiRgqIA69YJsFgY/PjHDq+Kgjk5Cp54wom4uMDumSxjWBv1\n6moWGzboMGeOC7NmkTUHgkCqucmydzW3YBjuujMYgIcfJpUr3Z1umw1Ys0YHjgN+8hPPOExZBhgG\nUTnNHQncPzYZ/3dfPb4/PnXQaXAp0UdpqYzERCfS0xVs28bj9GkOP/qR02v0W1HIz3CzP33ZFoCU\nlOc4El4TH+/sLrRDGTgR24TUdIJqhcr29nZUVlbi1VdfRV5eHo4cOaKxhAMjP1/GjBkSMjO9nW67\nHfjrXwVUVnIwGDQQjuIThgFmzBBx++0i/KWOz8pS/H7nTmcnsGKFgN27h++Qb1aWjBkzRK+47eRk\nDKpKZ1UVi/ff1w37rC/JyeTHHYMBmD1bxKxZLghuEREOB/DllwI2bBAg08mWAVGWEQOBZVDe0Km1\nKBQN4HlSQVinI87l7NkikpK8ncstW3j85S8C7HYNhAwj/mwLAJw8yeKjj3S4epXx0BNlcESs4907\nnWBtbS3Gjx8PACgrK0N1dbVWovmkro7FqVNsvyl0srMVzJ0rIjGRpJo7dYrt7jBlGbBYGFgsDBQ/\nL5UXLpC0P+o+9fUMjh9n4XKF7lqGKx0dwJEjHFpb+96urY1s1+5WUXriRBnTp0sIdpLl+nVg7Voe\nNTXkf0kCOjvZqErd2NDAoLychcMR2PbJycDcuSKysgKfATh1isXFi/7NUU0Ni/p6Bi4Xokp3fXHu\nHIuzZ72vec8eDnv2eDY0lgVuu03C5Mmyx8i2LBN9WK3wazMofcMwDBaNT8XaM9e1FoUyAESRpMML\n9oVctfMdHcDlywwOH2Zx8yYwbpzktYBZUQCrlfTNwy1NHssCnZ0KrFbvWTOnk4HNxsDp9Pzc4SAp\nFBsaQj8IUlMTvakZAyVqht1sNhuMRiMAwGQyhSVrymDYt49DYyOLjAwH0nqFCqqiqg+z3U4csD17\nODQ3s8jMdCA1lXz/2GNOcJz/aeNdu3i0tjLIzHQgJQU4fJhHTQ2LtDQnjf3shwsXWGzaJOC73wXu\nuMO/9bxwgUV5OQeelzF58uB0evo0hw8+MOCHP3Rg9GgXEhKAp54afMqmoeTECQ4VFRySk0kIlKKQ\nttreDhiNg18J39oKbNkiIC1NQUGB0+t7WQa2b+dhtzNobWUgigyiffGOwwFs3EhGqXNzHd22oa2N\nfM6ywKRJkldYU29EkaSh1OuJnqIw+i4i+G5RIj49dhUXW+0oSDJqLQ4lCK5fZ7Bli4D8fBm5uS60\ntQEJCf2HhNTUsDh0iIdOJ6O6msfBgxxKSmR0dUlISfHsHxgGWLjQBUkaXKhcJHLjBrBqlR6CoGDy\n5C6Pl44pUySMHSshNtZzn2vXGGzdKqCsTEJ2duhS34oisG2bAKcTGDXK4XXe4ULUON4mkwmtt4Yq\nbTabV3EdrbnzThGdnd5pxxwO4IsvdGBZBT/8IZnKWbdOwM2bDL77XSccDtZjn/4e6nvuIenN1Kno\nmTNFjB7N0LirAMjKkpGWJuP6dTKj0Fc45/nzLKZNG7yDN2mShL//+y6UlvYYp0BCUiKJKVMk5OTI\nSE5W8MUXZC5y7lwRX3yhw+TJEu6+e3CGNzkZuP9+F2JifOuaZYH77hPR0UFeWKM9gwBArikjQ4Yo\nwmOhqckExMcrYFkEFG4WGwssWuQCz8NrmpgSOEaBwyNlafis/BqWzCvQWhxKEKSlKbj/fhcSEhSc\nO8dgwwYd7r3XhYkT/duJlhZg1y7hVhIDBcnJIgoKJLCsgvx833bIfc3FcILngdxcGTzv/bLCcfDp\n/GZmKvje91xISwut38HzwH33ueBy+T7vcCFqHO+ioiJs3boVixYtQkVFRXfsd6RAVvl6N8IrVxhY\nrUBmJrpHshMTSceakwMYDME5Eb3Pk52t0JHuAImLA1JTFZhMfTvdCQlAwpfhZAAAIABJREFUSQm5\nL9u385g8WfSKuQ2UpCRg4cLoLoaTmakgM1OBKJLrURRAr1eQlKT4dZZVamtZXLrEYto00a8hZZj+\nUwoOB2fbHZYl7VEUPTs7lkX3wupAF3GNGTO8dKMVC0tT8cXpSlRft6EkdZgNaw5jOA4oKyPPwKVL\nDOLiFBj7mbS4fJk8XEVFMmJjgdhYBTk5I7Mf5Xl1AaUSsM3R6YBJk8Jjd4qKhr89i1jH21c6wXHj\nxmHJkiVISUnBwoULtRYxIC5e5OByAVOmiN3TwPfeO3BHrLUVcDiYW/mFKcFgMAAPPdR/MHxRkYyi\nIie+/ZbF0aMcsrNlJCfLkCTyIqU67yMNnifTrSpPP+0dFuJOUxODujoGR46wKCxkERs7/A1qoHAc\n8MAD3m1RFHsylEhSYKPYTU0MOE7RvMhPtGPgWfx4ahb+a/9lvLNoDDh2eC/iHQ7U1zOIj1cQF0f+\nz8tT8NOf9m2XAFJROCFBwfjxwyxgewAwDEn6QDMjEZqaGPC8MuDBtkCIWMeb4zi88sorHp/FxcVh\n/fr14DgOb7zxBl5++WWNpAuc6dNFFBayASfm74+NGwVcv87imWccSEwMySEpfpg0SUZ6uqu7oueF\nCwzWrhUwa5aE22+nBrsvOjuBVatIifMf/tCF3Fz6ohgIRiPwwAPEcQgk1MRqBdauFaDXK3j8cRfN\njz5I7h2dhK3VrVhTeR0Pl9G83pFMQwODlSt1mDBBwv33BzeY9cADLjgcZHZzpGMyAd/9LinWFU1r\nj8KBxQKsXq2D2azg6aedYVszE3VmeuLEiXj++ee1FsODixdZ7N/PYc4c78pXcXFAXFzgI31XrzLY\nsYPHtGlSd7iDO6WlMtrbSWnaNWsEpKfLmD2bOoGBcuMGuheFTJjQ930xm3umvaxW4MgRHunpCnJy\nZCgKsHMnj64uYN48ccQarD17eNy8yWD+fJeHo2g0At/5jgSDQUFBgecz0d5OFlMWF8uYMsW77bpc\nwDff8OD5ng5hpCBJwMmTxCynpor9Gn6WJaNUHDe88gv3tBEJU6YM3UwJwzB44a5c/NPX1Rifbsa4\ntMhaS0TpIT5ewaRJUvfAiIrDQWx8XJyCOXN6HPKqKhbHjnG4914XqqqI3UpJcdHUvUDAGahU2trI\n8zl2rIRx42Rs2yYgJkbxWu9TUcHi9GkO8+e7wjqCHCoMBrIuy2BQwrpQPeoc78rKSvz617/GvHnz\nMHPmTK3FAUA6icZGFp2dg1+MZ7EwaGhgfTrdALodlbY2EqdGUohRxztQrFai35yc4Dpzh4Nkj8jL\nk5GXp0CSyIiL1cpCFEeu493QwKC1laSzdO/AeB646y7fo1BdXQzq61nEx/t+VkSRtG29njiiw8mh\n7A9RBK5cYbtDTfoz/qSoBwNZHl7FhdQ2kpCgABjaEKWsOD1euDMXv9p+Ef/5QDGy46lnFonExJBF\n171xOon9SEz0bDft7cT222wMGhsZtLR42y1KYNjtDK5cYZGWpsDlknH5MouEBNkraUFrK9ut8+Tk\nyJ/17KvfCiWMokRP9ldRFCHLMkRRxH/+53/ixRdfRIyPFBHffPMNpkyZMujzSRICejAliYykpqQM\nvuNTFJL7OTGRnNto9B931dZGpoYiLMELysvLQ6L/vhBFoveBrDRvaSErpoPdt7e+LRYig7+Uby4X\nuZ9D6ZSHUvc2W/9ZdiwWci/6m7K12Tzb8o0b5Nj+FkF1dJBto21lezD6V3Pj9m4fnbfquAR67S0t\nxEEfbqFnN26QZy0YxyiU7X9TVQs+O34Nr91XRFMMBsBQ2H0Vu53Yb3/9bXs7eSbc3QOnk3yemurb\nbjkcZJ9oDdcajP792aK+cO9HfekbALq6iK7Dsf6kd5+iNeXl5bjnnnsC2jaqxkd4nodOp4PJZMLk\nyZNRVVUV1vPt3cvjk0/0uHGj7+04DkhLC81oE8OQYzU3M/jjH/UoL/c/5JWYGHlO91CxfTuPzz7T\ndTspwZCSMjCHvbe+Y2L8O90AicdfuVIHmy34c2lNTQ2LDz/U91vIICamf6e7oYG05WPHetpycrJ/\npxsgIVrR5nQHgygCX30l4K9/FbwKE5EsC4Edp6uLTKvv2CEMu8IeycnajkZ+b2wKfjo9C/+28Tw2\nVrVAjp4xqmFNUxOxJ4cO+e8b4+O9nUCdrqdybm+7ZbEAn3+uw+bNIy8np8NBKmavXStADGKw170f\n9aVvgDy/4XC6L11i8NFHepw4EVUubDdRJXVXVxcAQJZlnD17NuwpBVmWpNjx9UZVWcni+HE2qDLN\nNhtw4AAXcIUtEr9Jjb0vyL3x//358ywOH+a8Km4FSl0diwMHuEGVB+Y40n6iEZbt+ekLNW6yt9Mn\ny8Dx46QCGcsq3bHIlB5I+/DUi6KQKp6nTrEBV6JUZ3+ofkPP3KIk/Pb+Ymw+dwP//HU1jl3pQBRN\nEg87rlxhcPIkh5gYuds2VVWR7FPBOI29IeskFLDsyLy3/mx9QwOD/fs5WCyBH8tfnxBKAu2fIpWo\nmlQ5e/YsVq1aBaPRiBkzZiBOzSEUJu64Q8TMmeRNua2NdJJq7t0zZxjIMoPiYjng0anmZha7d/OY\nOFFCXl7fViI7W8Gzz0ZXhcOh5J57REgSefNVlJ50UiqnT7O4fp1Fbq6EjIzgj19RwaKykqQSHGhG\nju99j1Q6i8Z7WFQk4yc/cXSPOCoKmYVROyZZZpCWpmD/frJIqaBAQlJSz/4WCylQYTSS9F60LXvC\n88D06S7Ismf76OoCdu8mo26jRzs8ZgVu3iQOgvssi8sF3LjBQqcbefHwQ0VBkhH/d1EJdpxvw38f\nagDHAItKUzGnMBFmHS0VGi5u3AA6OxlkZyvdaTVrajiUl3NYvNiJxERilw4e5NHSwiA/Xxrw6KrZ\nDPzt37pGZOVXvZ4U5mNZ7zCbujoGly4xSE0FAh3n9NcnhJJRoxT85CfR26dEleM9efJknDx5Ehcv\nXsS1a9fCfj41vY7NRkqqGgwKnnjCCVkGDh0ScOMGi3nzAn/NzsmRsXixC6mpgQ2TD9dKWaGA44CT\nJ1n86ldGPPKIEz/6kWdOZLudwaVL7IAN6YwZIoqL5UEVJ1JHNKMV92n+CxdYrF4tICGBlIxvb2fw\n6KMuLFjghN3OehnYuDhg8WIXBEGJej2EA6sV+PBDYn5feEHsdqaNRmDRIkf33yp2O0lzxfPAE084\nuzuc2NgePdPKleGDZRjMG52Ee4oTceRKBzZV3cAHhxsxOy8e95UkoyzDDIZOOYSM9nZS8fnAAQ7/\n/M9d+M53iB2eNElEerqMtjYWX3/N42/+xon5812w2byrRgdLtDpxg8VuBzZt4sAwwKOPSh56uHyZ\nxWef6W8VMAvMb1mwwAW7nQmb060Szf5RVDneFy5cgMPhwLJly/Dhhx+itrYWRUVFITn2pUsMjhzh\nYTZLOHtWQEqKBLsdiItjUFAgo7hYBM8z4DiybU6OgtGjXTCZSBL/Y8d4zJgh9lnYhueBceNoEZFA\nOXOGRW0ti6tXGeTkyOjsZHDtGotRoyTIMotx41y47TYJ2dneOh09WobRSJyXykoWJ0/ySEiQMXWq\niLQA0vOmpQFpaSPjXn3yCYkPtloZLFjgxMmTPOrqODz5pKN7tiA2VkZBgdxdqbK1lUF1NYO8PBal\npT16OnmSRWMji7vuEoddtclQIstAQgKZHrfbexxvWQYuXyZvKaNGSd0j2IIAFBSQss69R6WonocO\nhmEwfVQ8po+KR5vdhW9qWvG7/fVwyQruK0nCvNFJSDWPUA9uAHR0AOvWCbhwgcUddzhx8KAOJSUS\nYmIUpKRImDULOHNGQEGBEydO8OA4BbffLqGmhkV+voy4OCA93XfVaEpg2O1AUxMPQVAgyxI2buRR\nX8/ihz90IiaG9KU8H7iNIYNV9H70RVQ53ufPn8ekSZMAAGVlZaiurg6J4335MnDyJCAIMhRFhiBI\ncLkYOBwMDhxg4XIxeOqpnmDha9dYyLKCefNEGI3A9esMystZJCayyMwcZiucNKSmhoFOp8DlkiBJ\nDAQBsNlkXL/Ooq6OxcSJLP73/+7yue/UqRKmTiX34uJFFrt3cygrU1BUxI4YhzoQnE4gI0OGoii4\ncYMUCbp+ncW+fQymTyfVJs1m8iLyt39LZhU6Osh2mzcLYFnZw/Guq+NQU8PittskmM3U+PqjvR3I\nzhbBMCSLifqC43QCZ87wABRMny51j+rwvP+Kt/X1DHgetJrtEJNoFPDwxHQ8VJaGqus2bK2+gb//\nsgpjUk24ryQZs/LioeNo7E9f7N/PITZWgdXqQHs7g/R0CRYLgytXGNx9twtGI4PKSg6NjQz27+eR\nkiJj+nRS48Jfyl1KcLS1AWPGkHoJ7e1ARQWHigoO8+c7YbWSGX+nc/Cpkik9RJXjbbVakXZruNJk\nMqG+vj4kx62oYPHnPxtQX89i4UIHDAYGe/ZwmDBBxC9+0eWVOWTKFAl5eXJ30vkJE2ScPy+hooJD\naanUvXKaMnC+/Rb4/e8NYFkS9nHsGInZnjbNhRs3iBNSXByY4S0okDBrFokBHD2aGmt3urqA3/3O\ngJQUBUajDIBBbKyMJ55wYft2HUwmF6ZN83yZPHmSw+HDHO69V8SYMZ76nDvXhRkzSPw3xT8uF/CH\nPxjgcADvvWft/txgAB56yAGGCWwq1WIBvvxSB71ewbPPOmm4iQYwDINxaaTYzs9m5mB/3U1srGrB\nu99ewd2FCZhfkoziZCMNRenF5cvA228b0NbG4P/9Pwu2btXh0CEeqaky7r3XBUlicNddIr7zHQmV\nlQySk2XcccfIrZkQLqxW4LXXDDCZgI8+sqKgQILJpNwacFEwYYIUFcVvoomocrxNJhPst9JM2Gw2\nmEOUSy8tTca8eS7Y7UBysgiGYbBggYzx42VkZ3tvbzQCOTk9joVOB5SVyWhrU/pML0cJnNRU4Pvf\nJy9ByckyCgoYSBIDg0GC0chi9Gg54IVk2dkKmpsVFBYqdPFZL+LigEcfJTHFpPgBg9hYMs17110M\nRo3yflHJy5MhigyKimSvFFKkUit1uvsjPh740Y8ckGV4xUIGE6tqMgGzZ4vgeRrjHQkYeBb3FCfh\nnuIkXOt0YFtNK17dfhFmHYv7SpJxV2Eikk30RgFAbi7w2GMOOJ2kANTo0SKysiQkJZF+NDubpKiL\niVHQ1cVAp5O9qlRSBk9iIvDssw7wPLFLZWVkbVN8PFBcLINlGWRkUJseSqLK8S4pKcG2bdswa9Ys\nVFRUYO7cuSE57rRpwLRp7ovzgq+WRmO3Q8vo0cQQ+yY4XSckAHPnhr8aVbTy9NP+dOP789xcBbm5\nVJ+DISkJePbZweuQZeE1I0GJDDJi9XhySiYen5yBU1ct2Fp9A/9z/BoSDDwmZcaiMNmI3AQ90mJ0\niNXzMAlkVEBWAElW4JBkOEXy2yHKcN767RDV72Q4JAVOUQbHMjDrWJgEDiYdh1g9hySjgFg9F9Ej\n7X/3dz3PwIwZ/ttxYaFM1zKEiVGjgJ/+tOc+JCX16Jna+vAQVY53QUEBdDodli5divz8/JAtrKRQ\nKBQKJRywDIPvZMXiO1mxkGQFF1rtqLhmQfV1G7bXtKLF5oTFIcHukqEAYBmAYxjoeBZ6Tv3NQscz\n0Hf/Tb7T8yx0HAtRVmBzSbA5ZdhcEjq6RLTaRTglGUlGAckmAclmAZmxOmTG6ZEVq0dmnA6pZh04\nNnIdcwplOBIRjndbWxveeOMNXLlyBZ999hlaWlrw3nvvgWEYFBYW4qmnngIAvP/++9i9ezf0ej0K\nCgo0lppCoVAolMDhWAajU0wYnWLy+k6SFbAMQjpC3SXKaLO5cMPmwnWrC1c7HKhqtmLH+TZc7XCg\n3SEizaxDZpwOWXF6ZMXpkRmrR1acDhmxeuh5GptHoYSaiHC8Y2JisGTJErz55psAALPZjH//93+H\n0WjExx9/jNraWuTl5aGyshI//vGPYTQa0dLSorHUFAqFQqGEhnCMPBt4FplxemTG+V6p6xBlXOt0\noLHDiaudDlztcODYlU5c7XSgyeJEvJ4n+8fqkGQSkGjkkWDkkWAUkGDgkWDgEWvgwdNRcwolYCLC\n8RYEAYLbyiD3RZMxMTHo7OzEtWvXkJycjI0bNyItLQ1dXV1YtGiRFuJSKBQKhRL16HkWeYlG5CUa\nvb6TZAUtVhcaOxy42ulAm11EY4cDZ5qsaLOLaLO70N4lwuKUYOBZLCnT4AIolCgkIhxvf7S2tqKi\nogIPPfQQampqkJeXh6effhqNjY14+eWXtRaPQqFQKJRhCccySI/VIT1Wh8mI9budoiiwuWScO31y\nCKWjUKKXiHS8b968ibfffhuXL19GZmYmfvWrX0EQhO4c3nFxcRAEAXa7HUaj95u62WxGeXn5UItN\nuQXVv3ZQ3WsL1b+2UP1rB9W9tlD9awvHcQFvG5GOd0JCAtLS0rBw4UJMmzYNACCKIpYtWwZZlnH0\n6FHo9XqfTjdACu1MmTJlKEWmuFFeXk71rxFU99pC9a8tVP/aQXWvLVT/2hLMS09EON6SJOH1119H\nXV0dXnvtNTz00EM4fPgwWlpasHHjRtx///2YNm0aEhIS8Mwzz0Cn0+FnP/uZ1mJTKBQKhUK5xYrj\n19DY4cC4NDMWjEmmiy4pFB9EhOPNcRxeeeUVj8/+9Kc/eW334osvDpVIFAqFQqFQgqCp04kJ6Wbs\nuXgTW6tv4Nf3FSHOEBFuBoUSMdAknRQKhUKhUAbNC3fl4ntjU/D6giKMSzdj2faLEGVabpxCcSci\nHO+2tjb84he/wOOPPw5ZJuVKv/76ayxZsgTvvPMOJImUkt27dy9eeeUVvPHGG7Db7VqKTKFQKBQK\nxQcMw+C56dnQ8wxWnrimtTgUSkQREY63WkCnpKQEANDe3o7Kykq8+uqryMvLw5EjRyCKIrZv345l\ny5bhrrvuwrZt2zSWmkKhUCgUii84lsE/35GLtZXX0dDepbU4FErEEBGOtyAIHkVzamtrMX78eABA\nWVkZqqurce3aNYwaNQosy2LixImorq7WSlwKhUKhUCj9kBajw6MT0/HRkUatRaFQIoaIcLx7Y7PZ\nulMFmkwmWK1W2Gw2mEwmAIDRaITNZtNSRAqFQqFQKP2waHwqzjRZceEGDQ+lUIAIdbxNJlN3DLfN\nZsP/Z++9o6u6zoTv3ym36Kr3LoEkJIToxRTjho17wD0hjmM8yYydxMnMO+98s768mZixJ5lvsjKZ\nd+Ik45nlxPY4ids4toHYccBxwThgUwwI0SWKAAkJ1KWrW8453x8bCYTalXSlW7R/a2lxuZKOnrvP\nPs9+9rOfEhsbi8vl6jW23W53rxEuGRzThJoalebmUEsyeejshGPHVLzeUEsSftTVKZw5I8uL9VBf\nD3V1oZZCIhkYywrO+uHUVe6bnclvZax32HL2rNBHkokhLA3v4uJiDhw4AEBlZSWlpaVkZ2dTW1uL\naZrs27evNx58stHWBq++auPTT4fvknTmDLzzjs62bbKc00Sxd6/G66/bOHZs+Edr2zaN9et1JsPh\njdcL69fbeOMNO52d/b/v94uN4kBYFrz3ns6GDTY8nvGVc6Jwu+HFFx0895yT9va+3zMM8SWRjJS6\nOoX//m87hw4Nrn9MUzxvw3H6tML//I+NP/957OvHHdNT2XO2nXPt0iMRbrS1wfPPO3nxRQfdQQjF\nD3R+TWbCwvA2DIN/+qd/6m2g09jYSHl5OU888QQnT55k0aJFaJrGjTfeyLp169iyZQsrV64Mtdjj\nysGDKkeP9r89Xi/U1ak0NQ3tOTRN+OwzGx6PQkmJXMWDTXc37NqlUl/f9z7k55ssWmSQmTmIFXmR\n8+fhzTdt1NZq+HzjKWl4YLfDVVcZLF7s58qGs+3t8LOfOXjjDduAv2tZ0NCgUFenRo1C7+kurCgW\nl3ca9vng+eftvPCCfVLMC0lgHDqkcvjw8Mt1V5dCY6NCe/vg68PmzTqvvGIbcAN8OcnJFkuWGJSW\nDq3LAiHGprFyWgobDzaO+VqS4KLrkJhokpBgoQbBIty0SefVV4efX5OZsHCFDtRAp6SkhNWrV/d5\n79prr+Xaa6+dSNFCQkcHbNpkQ9ehsNCD3X7pe2lpsHatB6dz+OuYJqSnm+Tnyzqqwaa2VmXzZjsL\nF/rJyrpkDebnW+TnD28dmibk5FhMn+4nMXE8JQ0f5s8feAPY0iI2moMZmqoKq1f7ME24LAc7orHb\n4Zvf9GBZcHnUnNsNR46oKIp4bRt4LyKZRHR1ifVAUcR6MJTuLy42WbvWQ1LS4D/j9Sp0dyuDnjD1\nEBcH110XvJ3uqhnpfGf9Yb4yPxunHhY+PwnCsdHdTR8HwFjweMT8sqTZMShhYXhL+hIXB7fc4kPT\n6GN09zCQUu3shLY2hexsMdtVFVat8mFZ9Crq/ftVWloUFi0ycDjG8QNMAvLzTW65xUtOzsi0S3Oz\n+KqpUVm92kNBwTgJGEHk5sK3v91NfPzgY+n1ivCL+Hjx/6oqceqzaJER0CY0HBkobCY+Xjz7Pa8l\nkxevFz77TCMpyeLWW72A0m+uu93Q1CT0fo+3Mi1t6OvecosPw6DfydN4k5PgoDwjlg+rm7m1LHVi\n/7hkUGJioKLCRNNGttGvq1NISLD6OUNuuy008yuSCFvD27Is/uu//ov6+nqysrJ47LHH2LBhAzt3\n7iQtLY1vfetbaMHaooUh06eP7Hjvk0909uzR+PKXveTlCQPmSuN63z6Ns2dVpk+XhvdYcTph3ryR\n3SPDgLfeslNbq5KRYeByKUydKsOAVBVmzRrc6DZNMW4dHQqPPOIhLg4qKzVqa1XKyiLT8PZ64Y03\n7BiGwsMPe3oXqe5uOHRIR1Hg6qsj87NJgkNbG2zfrpOdbfLggz6g/zOye7fG1q06997ro6QkMH00\nkDNnori1LJXfVTZIwzuM6O6G6moNTYPrr/cHND9On1Z46SU78+YZrFzZ91QklPMrUghbw/vw4cMk\nJCTw2GOP8dJLL3HgwIHepjrr169nx44dLFmyJNRihg25uSZeLyQkDG7A3Hyzj85OZViPiGR80DQo\nKzPIyzOZOtUgK0uexQWCqopxc7uV3g3jypU+OjoUMjJCK9to0XWYPt3AMJQ+C1VMDNxzj0hAk0b3\n5CYtDR54wEtMzOB6IjPToqzMJClp7HHYE8HigkR+urWW063d5CXKCR4OuFxC56hq4EZzQoLFjBkG\nubmRMe/CjbA1vB0OB+3t7ZimSUdHB4cOHerTVGfr1q3S8L6MigqTioqhH4K0NEhLk8ZeKFm2THq4\nR8OV45aaCqmpkTuXVRWuuWbgudATLiaRFBQMPRdKSsyAPd3hgK4q3FiSzKYjTfzFopxQiyO5yEhD\nJhMS4M47oyTTPQSEbYbD1KlT6ezs5NFHH6Wjo4OMjIx+TXUkQ3PggMrevapMcghTDAN271aHLP0l\nCYyTJxW2b9dwR3iPDsuCykqVyko5JyY7fj/s2qVx5Eh0zYWbS1PZfLQJw5QLUzhy7JjKzp2To9pW\nqAjbJ/rTTz8lJyeHZ599lpwcsTO+sqmOZHD8fvjoIxsffGCjoyPU0kgGorUVPvjAxiefhO3BU8Sw\nf7/Ghx/qNDREdoOe7m748EMbH35oi/hNhGRsNDfD++/rbN8eXblMU1NiSIu1setMW6hFkQzAp59q\nvP++TnNzZOvScCZsV3zDMEhISAAgKSkJ0zQ5cOAAq1at6m2qIxkcXYc77vDi9ytBqY7Q3Q0ff6yT\nkmKxYIEMlwgU04Q//1nDskSy3OV1UlNSROUZl2vyeH6OH1fZt09j6VJfUOOzFy3yU1Rkkpsb2WPp\ncMD06f7e15LJS1qaKKMZGzv8nD59WmHnTp1Fi/wR8QzcUprKH480cVX+JKmlGkGsWOGnrU0hPT38\n59F4s3OnRnOzwrXX+oOqj8PW471w4UKOHj3Kk08+yZEjR1iyZEm/pjqSoSkosCgqGj7+r7JS5eWX\nbVy4MPjPdHWJShLRduw53vh8UFWlc+CAPmAb+WnTLhmLTU3w8ss29u6N3jGur1c4eFClqSm4nzEj\nA8rLTfQguxK2btV46y3bhHUX9XqhpkanpqbvUa/fD+++q7N5sz5s/WVJeLN7t8Zrr9lobR365xQF\nSksD20w2NiocOqRy/nxkeCmvK0pi95l22rplnHCouVK3ZGeLhF0lMqbSuHLkiMr+/VrQ9X/Yerzt\ndjt//dd/3ee91atX92uqIxk7TU0qZ86odHUpgyaspaTAgw96cTjkLngkOBxw772iYPNwVSrcboUz\nZ9SL1U6i07qaN09UdRlpMk+oqK9XOXt28OY+wcbpvDRfLvew+P1w+rSKrovcgGB0mJOEhsZGhdOn\nVbq7FRITg/McVFSYpKV5I6ZSUrxDZ1FePB/WNLNqRnqoxZnUSN0yOLff7sPrVUhODu51w9bwlgRO\nW5uIcS0uNsnMHLniXbzYT0WFf9gyg6O59mTn5EmFc+dUZs8ePjwnN9di7VpPVDdOcTrp00n1wgU4\ndEhj+nSD1DAs7XvbbT68Xia0u+hAz6HDAXPn+lFV2c0y0pk61cTptIJmdIMoAxdpHYpvLk3lv3fV\nScM7xDidomylogRHtxw+rNLZCXPmmEHrhhkqRLPC4D9XYW14f/TRR7zzzju4XC6+/e1vs3Xr1knT\nQGcknDqlsmWLDdP0kZFhsHu3GJf5842AjoucTlkzeDg8HhHvlZxsMWNG4N7oPXt0Dh5Uyc42A1oY\nI73G+uHDKo2NCgsXBtb85cQJlY8/tuF0WqSmhp+XPzZ2fNrUWxZ8/rmKaSrMn28M62Xq6oJPPrGh\n6zBzpkc2qYhgDhzQOHRIpagoMJ0wFrxeobcSE61hy81ONPNy4vnJllOcaHYzJVm2OQwlF9PpRkVP\n9R2n02LOHJOtW3VaWhSmTPGQkhI8GaOJsDW8/X4/u3fv5oc//CERXl05AAAgAElEQVS6rtPa2jop\nGuicPatgs1mkX+YEqKlRqapSWbp0YK90cbHJHXd4yc838XhEtzOAigrZ+S5YtLXBn/+sk5NjMmOG\nyaFDKjU1Kldf7R/SG7pkiZ/SUqVPaEVtrUJsrBWVSmn/fo3qapWSEjOgY++yMhO73cvUqf2NgqNH\nVY4cUVm2zE9ysjA+6+tV8vPNiPf6+nywfbsN04QZMwxcLvF+TzIuiNrlPQZ5bCx84Qu+AZtc1NUp\naJoVsc2EognLglOnFJKTrUGNmSVL/JSVKQGHW/XMCUWBpUuH36RdTnu70FtZWcP3eZhoNFXhpmkp\nbDrSxF8tzg21OJIBOHRI4fBhjWXL/H1sksvp7BRzLC7OYvZsLzff7MPtVqJyfQsWYRvNc+TIEXw+\nHz/4wQ/YuHEj1dXVfRroHDlyJMQSBp+2NnjtNTsbN9r71N6ur1eoqtIGTUiLiYFZs0ySkoTn+q67\nvNx1l1ca3UEkPV0cx918swj2PX1aJF20tAx9pJCZaVFefunIraEBXnnFzubNEW45DsL11/u4/35f\nwGFJcXFi7sbF9f/e2bNijJubxbyvrBRJaYcPh63aChi7He6+28vdd3t7jW4QHsr9+3WqqvR+ceVF\nRSZTpvQ1njo64PXX7bz1ll3W3Q0DamsVXnnFzp//PLhPKyurr04YDo8HKit19u/X8I8wFzE1Fe6/\n/5LeCjdWTkvh/WOypne4smuXzq9+5eDo0cEna2Ii3Hefl1WrfCiKCHkqLQ2vTV64EbYe72PHjmGa\nJt/73vf41a9+hcfjIfGiazFaG+i4XLBwoR+Xiz4hIvPmGeTnB14qLRLKSUUihYWXxnXJEj/Tpxsj\nHuuEBFi0yCAtLToVk+goGZzPtnChn6Iig7w8McY5OSZz5xpkZETH2A3UoXKw5MrBiImBBQv82O0y\n9jsc6Cm3WlAQvDkaEwP33y/mxGhCjC7XW+FGQZKTzHg7O0+3sbhAlhYMNxYuNHA4vEyfPnSOUqTl\nF4SaURnef/M3f8O///u/A/CNb3xj0J975plnRicV4HQ6mT17Njabjfnz53P69Omob6Cj67B8ef8J\nHhMjJ3a4ERcHcXEjvydOJ1x/vSyhFQgivvrSGOfnW+TnR//YDXakOxCaJkJSJOFBXBzcdFPw52ik\n534Mxc2lqWw62iQN7zCkrMykrCw6HB3hxKgM70cffbT39eOPPx40YS6ntLSUjRs3AsL7PXfuXDZs\n2CAb6EgkEolEEiVcNzWJX352lrZuPwnOsD2El0iCxqhmeXl5ee/rnrjrYDNlyhSSkpL47ne/S1lZ\nGdOnT+fo0aM88cQTpKWlceedd47L3x1vTpwQiZJXXSVKg3V3KzI0JMzo7oa6OpWcHLP3uH/HDo2u\nLoVly/zySH8YGhrgs890Zs0yAj7mPnNGuVjZZJyFiwDOnRNxZpfHyRsGbNumoWmwZElg1YokE0dP\nLeT0dJPYWBGXvXWrTkqKybx50mM4FHEOnavyE2RN7xBhGPDeezq6brFihdQtE8GYt5c+n4/f/e53\nfPLJJzQ3N5OSksKyZcu45557sI+x5tVDDz3U5//R0ECnrk6hslKjqMhk926N+nqVRx7pW3bHsuD8\nefjTn2zMnWswffrgiruhAVpbRRUJ+cAEhwMHVDZtsnHrrT7mzjWxLFGto71dYf78gQ1vy6Lf+H/8\nsYbbDTk5FgUF5phKNkUSjY0iKTIjw6Kw0Oidy/Pm+Zk2zeo3Tk1NIuE0K8vkwQcHTwLr6IDaWlGG\nLVrbqXd3wzvv2LAs+PKXLyVIezywb59YHBcsMHpjfX0+2LRJx+GwuPFGuWgGg64u2LzZRmamyZIl\ngYXxHD2q8Kc/6cyf72fZMpOODtizRyMnR2HuXKG/5b0ZnJXTUnhhp6zpHQra2uB3v7Nhs8GSJe4h\ny6f2rHOGAdXVKqmpZkicJefOKbz/vs6CBUZEJnKO2fB+9tlnOXPmDKtXr2bKlCkcP36cDz/8kKam\nJr75zW8GQ8aoYu5cg5wck7w8C49HJEJePtHPnFF4+20bFRUGp06J0mlD8cknNo4cUfnKV7zScx4k\nsrIsZs82ej2OigKrVnnx+5UBm9tcuAAbNtiZOdNg0SKxUIuyYiqdnQrbtyvccIOfa66ZHLG4ZWUm\ncXHe3vHr7FRoaFD48EMbVVUWd9zh65MkFhsrkngSE4ee65WVGh99ZOOOO7zMmhV5yjYQVFUY2ara\nt4OcywX33edBUfom2LW2wuuvO4iLM1m+3C0rGQUBjweOH1cvVhAJ7Jnt6FDYs0e7WBZTGCNf/rIX\nm81i/Xobmia64MnWEwMzLyeef+s6xfEmN1NTZE3viSQxER56yIum0afC0pWcPKnw7rs2brjBj8Nh\n8cYbNmbPNrj99onPu2lvV6itVQcsQxsJjNnw3rVrFz/96U+Ju1gPrKSkhKVLl/Kd73xnzMIB/P73\nv+ezzz7jqaeeYsOGDRHfQCcmBjIyLNxuLnpC+k4cj0ehs1MhJkZ0MbyyRvSxYyodHTB7tomqwqxZ\nBpmZ5qCt3iUjJzvbwun092kTK3b1A4+xz6fQ1qbQ1XXJpSWMdd/FsAtbVN6f1lYxn6882NL1vpUU\nCgstHnjAyx//aKO1VcG8Qlc6HHDddUMr78OHVVTVYulSH7m5kalsA8GywO0e2Ds6UJ3ulBT4+te7\ncTgsaXQHieRk+OpXA2tSZFnQ3Ay5uSY33iiq8PSQnS2cK62tCrpuYZpIw3sQemp6//HIBR5bkhdq\ncSYVqiqa7cHQpzJut7BNehyGy5f7x8XZd+iQis8HM2cOfopfXGyydq2XpKTIXFfHbHhnZWXh9Xr7\nvOf1esnKyhrrpfH5fJw8eRJFUWhra4vIBjonTqjU1irMm2cQFycU9caNNlpaFL78ZW+/+sXJySYL\nFvjJzDQHXGi3bNFpalLIz/eQmgolJSYlJRPzWSYLVVUqf/yjjWXLfHg8KnPm+ImNFd25kpOtfqE/\nWVkWf/EXnn6GT3y8CI04eVKLOmOxvl7UK5471xiySsvl8//++31Y1vBdUk0TPv9cQ9Ms5s41MU34\n4AMdt1vhL/6i/2Y0mujuhgsXVBRFbM4DMf4cDrHZkQSPK5t/VFWJ06v58w10XTTJOX5cw+Uy2bLF\nxvz5/t7nvLz8kvHtcIgax8Fqxx3N3DY9lW+/dZiHF2QTY5M7lImiuxt+/nMHdrvF4497B52n06eb\nZGUJ/asolyqwGQbs3i06V471JNLvhw8+sOHxwJQpngFPmEH8/YyMyDS6YZSGd2VlJcrFrcg111zD\nD37wAxYvXtwbarJjxw5Wrlw5ZuHef/99rrvuOl577bV+DXS2bt0aEYb30aMqu3Zp5OZaxMWJHVxS\nkoWqDrxY1tWp/PnPOqoKubn9jzlXrvTR2Sm7Qo0nMTEQH2/R2amwc6dGRoZJWppohZuTYw4Ycz+Y\ngigqMrntNu+wIUORhs1mkZRkDVtSsWf+5+VZAR8LivboOroOM2YIz+Ntt/nweJSoNrpBeER7xjQQ\nY7pnrBwOi4qKwRdNydjYvl2ntVVh2jSD5GSoqdHYvl3juutM4uMtcnMtbrvNO2D97iisfDsuZMc7\nmJkVx3tHm/iCjPWeMLxeUeTBMBT8/qE3iElJ/d/r6BCJxHFxFjNneseUy6DrQtf7fIOvqdHAqAzv\n//zP/+x9bZomqqqyZcsWtmzZ0vv+xo0bufXWW0ctmN/v58CBA9xyyy289tprdHZ2EhMjYr8iqYHO\nwoV+pkwxKSy8pJBvvnlwD2FJicndd/vIyRnYSBH1vC26ukTCWkaGyeLFkyN2eKIoLjYpKvLS0SHG\ne8oUkcx3770+4uLEfbEscfrQ3Q0rVgxe6cTphDlzosvoBhF68/DDwyvZnvl/uUHS1gbvvWejqMjo\nTTy7nLg40dXx8vboInQlcj0cgRIXJ8IcIDCDrWesdD26PKrDzZGJprjYoKND6Y2BnTfPT3a2SVGR\nyZIlYzM2JJe4uyKdpz+p5Y7yNFQ5qBNCQoIIV1NV4XQaKYmJcM89Xuz2/qEqVVUqBw9qrFjhC9hZ\neGV33mhkVIb3L37xCwAMw2Dt2rX86le/GnMFkyvZsmULy5cv7/2/y+WiqakJiKwGOsnJInwkUOx2\nAipY390t4r09HqThPQ4oithxX34vioouvTZNEUbR1aWwfPnkLDEYyLo40Pzv6lKoqVGJibEGNaom\nc8OonJyR/XxBQfSNVWenmCMul8WVeTCh4OxZlfPnVTwePw6HMDaGSwaWjJzZ2XHYNIXdZ9pZmDdJ\nykCFAbm5Y/v9wcrGNjaqHD+uXjyljz49NVrGFBmoaRqFhYVUV1f3qe0dDOrq6ti2bRubN2+mtraW\nmpoajh07JhvoXCQlBR56qH9csWRi0DThaTQMeZQ8UrKyLL76VY8cN8mgZGeLOXJlDkyo+MIXxPH3\nZCkJGioUReHumRn8z75z0vCOApYs8TNjhhHR8djjwZhTcq655hqeffZZli1bxrRp0/pUGpk5c+ao\nr/vggw/2vl63bh333Xcf69evD8sGOn4/nD+vkJFh9SkBNt5Ecxvh8aShQSygY920yEUY2ttFLemR\n5hwMlDgsEbS0iNOEaI9nHw45RyYnK4qT+c3uevbXdzAzK0x2XpJ+NDSIU+GhwlOcTnA6pdF9JWM2\nvDds2ADABx98wAcffNDnez0hKWPlySefBMK3gU5lpWi4cuedPioq+h8/NjSIhTRd5ouEnMpKlTff\ntHH99QbXXjvx9UcjncZG8W/PXN640UZTk8rDDw+egS4ZmMZGkStwuYHp8cDrr4uwvYce8kZto6BI\nY7B57vGICj/Z2VZAFWgkw2PTVL48N5Nf767nR7fLkl0TwUhtlDNnFF5+2c68eQY33ijX0ZEyZsM7\nWMZ1JJOcDPn5JgkJ/Xd2brdocKFpFo884pXKOYS0t8POnRqGoZCSIuMzR0p3t5jLAI88IsKcCgpM\nEhOl0TFSvF544w07hqGwdq2nN2lP1y8lF8kSgeHDYPN8/36VzZtt3HabLyqTqEPFTdNSeGnPOSrr\nO5glvd7jSleX0Ou6brF2bWA2isslig6kp8s5Pxqkag8CouqFSWur0q91uMMBs2f7UVVRdcDrFf/K\nhO2JxzRFKcdVqzzMnDn08ZdliRAKaVAKb0hDg0ppqcmcOX4s69K49NRyHQifTzRnkE1D+mOzQUmJ\ngWHQx6utaXDTTSPzIPl8Qp9IQ33sDKafB5vnWVkWM2caJCeb7NsnOg1f3nhLMjpsmsrDC7L5z+2n\n+dnqMlnhZBxxOKCkxI+mBV4ZKTkZ7rvPN+D3DEN8ybVzcCYwInlkHD16lO9///s8+eSTveEsGzZs\n4IknnuDpp5/GMMKrksef/mRjwwZ771F8D6oqlPayZQaNjfDccw4+/XT0lojHAxFSSTHsOH5c5fBh\nHZ9v+Gn/5z9rPP98//vZ2kq/zovRzo4dOr//vY26OoVlywyuvtoYNpfB7YaXXrLx1ls2LBni1w+v\nFw4e1Dl0SJSkHC0eD7zyihjnyTYvg01Dg9DP27cPrp+9XnFy1kNursWdd/ppb1d55x07lZVylxks\nVpQkY1NV/nikKdSiRDXd3UIXHTyo4xvYlh4R775r45VXbBFrp3R1MSadHAhha3inp6ezbt061q1b\nx9GjRzl//nxv58rCwkJ27NgRUvna24UR1sPSpQY33TR0rUrLEu2yx7JA/uEPNn77W0cf5S/pT2cn\nXLjQ970pU0yuu85HScnwmzbLAsPo62U5flzlueccfP755FpcZ88WcXyZmcKC9nqFkTIUPcr82DFV\nGoQD4HDAihU+Vqzw9YaZDEdrK/2ee7cbDh3SOXpUxS9DLUeFZUFDg4LPJ/TzUBvFjz/WeeEFR78N\neUGByfXX+wIqBSsJDFVR+ObSPF7YeZbWbjm5xwuX65IuutJL7fEMr+uvRNg4SkQ6XDo74ZVX7GzY\nML6OjLA9nEy6rEVSTEwMu3fvnvDOlQcPqtTVqSxe7O9T+sww4M03bXR1qXz1qyI+s7h4+LuUmWnx\nyCOeMSVMxcZaxMebE1o9JRzZt0+luVncm4Gqk/zpTzaOHRP3p6f6S1KS2CAFwrJlBgsWGH0ytu12\ni9hYa1JkaZ87p/D55xqzZhnk51vk518at927NbZs0bn3Xt+g897lgmXLfDidE1vpJ1KwLOjoUDAM\n+oWnDYTbDa+9ZkfX4StfudShMiYGli4VC6YMNRkdR4+qvPWWjRtu8PHIIx4sCz76SCc52WT27L7z\n2+WyiI+3+h3Jx8fDkiXhdQobDZSmu1hRnMxPt57i+zdO7e2YLQkePbpI0/rrol27NLZu1bnvPl+f\nPhZDceutPkyTiEwM13XRtTo21hrXcOCwV9UnTpygra0Nl8vV+9BNVOfKo0c1Dh1SKS83iI29ZGz1\nxFMqysi3RKPpDHU5K1f6A1qoo52qKo0zZ1QqKgY2vBXFGtOOe6AuXrm5Fl//undSGJLnzins2aOR\nlmaRm9vXoEhKssjPN4mPN/n0U7EBuuEGfx9F63DAF74gvFSTfa4OhM8Hu3frGAbMmWP0er0NA7Zt\nEycqS5cavfHxNpvwqup635h5hwPuuEOO81gQLd9Fd9p337WRm2uwY4dKbq7Sz/BeutRg8eLhQ60k\nweORhTl8e/1hNh1t4pbS1FCLE3V0d8OuXTq6DnPnGn283oYh2smbI3D/RnIzOYfjUuz6pDW829vb\nef755/nbv/1bqqurJ7xz5bXX+pg7V5SKupwDB1T27xfewB7j7swZhfZ2hbIyc9wXQLnAws03+3C7\nlUFrmVuWqB9qWUKxbNumceiQxurVPnJyRm+RT5YFd/p0k7g4Hzk5/RVuRoZJRYXF22/rqKpCW5vC\nsmX9PRxyng6O3Q733OPBspQ+oSYeD2zdqqMoMH++0afayS23DHzcXl2tYrNZg3aPk/TlwgXRidJu\nF2N9001eHnzQR20tHDtmIz7e4ktf8g7qJJksOiBcsOsq310xhf/n7WPkJzqZkSk7bwUTlwvuu8+L\nqloXnwmN06dV7rzTh6JY5ORMrpOciVi3wlaFGIbBz3/+cx566CESExMpLi7mwIEDABPWuTIpaeB2\nzF1dCrGxFrNmGcTGCiNv+3aVP/xB7xf7JxkfUlMhL29wQ2PFCj/33+8lPR2OH1c4cULlyBEVt1ta\ng4Fgt0NRkTngaUJlpc62bTaqq3WysizWrPH2NhPyeqGjY2JljVQSEuhXglTTIDnZIinJCqgaTHs7\n/P73Nt5+2x6UxKjJwL59Om+/baOuDizL6tUJ+fmidvqyZX7y8oSOkYQHU5Jj+LtrC3jqvRpONY9z\n5tskJCvL6u0n0Nys0tCg4vOBzyccilfmO0nGRth6vLdt20Z1dTW//e1vAVizZg3l5eUh6VxpmrB3\nr4quw6xZJvPnG+TmGr3tjKuqVPbutXHddUMnV0qCS0eH8GQXF5sUFfU1YOLi6L0/tbUaR49qPPKI\nh+Ji6RUcDW1tsHevRna2SUGBgcNhsmqVSUpKX0/3Rx/pHDmi8aUveaThMgQ+HzzzjB2fT+E73/H0\nbnAcDnjwQW/v6+GIixOJUboe2Ue8E0lZmUFMjIjTbmwUm/F331WpqDDJz5f6IVxZXJDI167K4e//\ncJQf3lJMcWqAWcmSIbEs2LNHRdNg9myTlSt9eDyic65hKJw6paEoclcfTMLW8F6+fDnLly/v815p\naem4da7s7obGRhFWouuiDXxdnWgD7/PBli027HaYPt2DqsL779vo7BTJe3Y7ZGcL408mOI0PpilC\nfLKyzN7wkoMHVX72Myf33uulqGhwxRAfb1FSYg7pIZ/MNDWJ+d7j8WhtFac6l4dY1dWpbNmik5Bg\n4XKJBL+BDMOYGIu4OPkcDIfbDcePa3g8Cp2d9DlZiBtBvxBFoV8csmRokpIsDMOkvV1B1y3OnVP4\nxS9ieOghD/n50sAIZ1ZOS8Whq/y/f6jmL6/KYeW0FJlwOUa6umDTJhs2m7BvRJv3S99rblZwu1Vg\ncoWcjCdyebxIZaXGxx9r3H67l8xM2LVLob5eo7zcz4IFsHq1D00TXhLLEol23d0Gug6lpSbFxV7Z\nKGQc2bZNYccOndxcP/ffLwyNggKTL33JS3n50Aph6VKDq64y5P0ZANOE9evtdHXBww97iYuD7dsV\nmpo0pk83KSszcblg6lSTu+7ycfasKA84mGHdU7NexsEOjaLArbd2y0TpEPD55wrHj+sUFPiYNs0g\nPd3g/vs9zJghDYtI4NqpyeQnOvn/PjjBn44181eLc6T3ewwoCsyZI+ybK3E6LYqKjFEVkpAMTsQZ\n3i+88ALHjx9n6tSprF27NmjXzcw0SElRefttB0lJBu+9ZyMvD2bONACrt40ziIm6YkXfRCdp1I0P\nhw+rHDqksmGDHVUVpbz+7//VuPVWg/Jyky9/OTAPlbw/A6OqUF5u0Npq8dZbOkeO6KSmWtTXK+zZ\nIzK8Fy0Sme4VFSYVFcMrYGl0D093N7z2mhOfT2Hu3K5QizOpOHhQ59e/dvC//pfJc885eeyxbr76\nVenpjiSmpsTwH3dPZ+OBRv7hjzVkJ9i5ZkoS83PjyUt0oqlyNxso58/Diy86cTotFi5096lqUlRk\nYlkGubnytDiYRJThXVNTg8fj4cknn+SXv/wl1dXVFBcXj/m6Xi/U1ys0NCh88IHGokVwww1+DAPO\nn1eorlYCqtMtCS61tQoHD6rU1or22jabxZ49Gjk5JocOaeTnmyM6lpcMTEcHnDypsWePRmOjyqJF\nfmbP9hMbq5CXJ+f9eOD3w9SpFn6/hccTamkmF7oOeXmiNOPUqcaAnj5J+KOrCnfPzOALM9LZfqqV\nz0618VZVIxe6fKTH2olzaMTYhBfAb1qYJhiWhWFamJZ4bZoWqqoQa9OIc2jE2TUy4uxkxdvJjLOT\nl+gkI84W1eEshiEMbJtNVFU6eVKhtVWhosKkpMSipEQ2Lwo2EWV4Hzt2jDlz5gCiic6RI0eCYnjv\n2SO8IElJ8K1vdXH6tE5MjEFqqsKePTZqaiyKirzySHgCqaqC7ds1HA6xSLa3mzQ1qSxcaOLzKXz2\nmUZZmcGMGdIwHAsej9h0xsZaLF3qIzUVDh/WOHpU59FHPWRmhlrC6EQYff7eBjqSiSMjw2D+fIiL\nM9i3L4bFi/2A1CORiq4qLJ+SxPIpoumex29yrsNLp9fA7TNQUNBUBU0V3TA15dJrVQHTgk6vQafX\noM3j51yHj4MNnXxQ3czpVg9un0FhspMpyTFMufhvQbKTlBg9agzy4mI/miZOhrdt06iv10hP95Cd\nHWrJopOIMrw7OzvJuJgB5nK5qK2tDcp1z51TeecdG2fOaHz966I1dn4+pKebTJniIyZGxmFONM3N\n8OqrDhQFli3zU1xssH+/jb/6K+EenDPHoLBQLpZjxeOB3/7WQXq6RWKiRVycyaxZJjfd5B+0Rrpk\n7LS0wC9/6aC7W2HBAll/cSLZu9fGj3/s4Be/MFmxwkdZmYztjiYcukpB0gB1UEdJW7efky3dnGhy\nc6K5m49PtFDb4sFnmOQnOclPdJCf5CQv0UlWvJ20WBuJTh01QoyG9nZ45hknLpfFNdf4aWlROX1a\nubipkF6B8SCiDG+Xy4Xb7QaC20SnvNzki1/0YBgKOTkmV199+XelcRcKli+Hv/orN3a7Qny8RV6e\nyYIFJiUlpiybFkQSEuDxx90YhoXLpZCWZpGdDZmZUuGOJ9Omwd/9nRvThNmzQy3N5GLJEg///u8m\ns2cb3H+/ISvwSIYkwakzKyuOWVl94xrbuv3UtnZT2+LhdGs37x1toqHTy/lOH11egxSXjbRYGwlO\nnTj7pVCWOLtGrF3DZdeItWm47Coum/i/y6bi1NUJ9aTPng3/5/90XTyFg7vu8tHWpsg1YByJKJVT\nWlrK5s2bWbp0KZWVldxwww1BuW5JiYghloQX99135aZHboLGgzvu6BlXqWgnklWr5HwOBWLZkMmU\nkrGR4NSpcMZRkdk/0cjjN7nQ5eN8p5c2jwhj6bj479k2L10+8brLZ9DlNS/+a9DpM/EZJi6bMM7j\nHRo5CQ5yEx3kJzopTXeRl+gIujf9rrsu6aKsLIusLLkWjCcRZXhPnToVu93OunXrmDJlSlDiuyUS\niUQikUiChUNXyUlwkJMQQBesKzBMq9cob+32c7bNw+lWD5/WtvLfu+ro8hmUpbu4dmoyt5bJLmWR\nSEQZ3kBQSwhKJBKJRCKRhAuaqpDg1Elw6mTFOyhL7xtS29Tl40BDJ4YpvdKRSsQZ3hKJRCKRSCST\nkRSXrbeCiyQyCVvD+6WXXuLdd99F0zSuuuoqvvGNb/Dwww9jt9vx+XzcfvvtPPDAA6EWUyKRSCQS\niUQiCYiw7TG3ePFinnvuOZ599ll27dpFS0sLKSkp3H777bzwwgvU1NTQ0tISajElEolEIpFIJJKA\nCFuPd0/ipGVZWJZFR0cHjY2NfPrpp8TGxjJz5kyOHTvGwoULQyypRCKRSCQSiUQyPGHr8e7h5Zdf\nJj4+nry8PJYuXcpjjz3G/v37cbvddHV1hVo8iUQikUgkEokkIELu8W5paeGnP/1pn/eSkpL467/+\na/bs2cN7773Hv/3bvwGQmJiI3+9n2bJlfPzxx0ydOnXAa8bGxrJ79+5xl10yMHL8Q4cc+9Aixz+0\nyPEPHXLsQ4sc/9CiaVrAPxtywzspKYl169b1e7+xsZGf/vSn/O3f/i1JSUl4PB5KSkrYv38/DQ0N\ndHR0UFJSMuA1Ozs7mT9//niLLhmE3bt3y/EPEXLsQ4sc/9Aixz90yLEPLXL8Q8tINj0hN7wH45ln\nnsHtdvOTn/wEgL//+7/nzTff5MKFC9hsNm655RaSkmRJHYlEIpFIJBJJZBC2hvcTTzzR770f/ehH\nIZBEIpFIJBKJRCIZO2GfXCkJH9rbwe0OtRSRR2cndHSEWhC7SbcAACAASURBVIrwwDCgqSnUUoQ3\nHR1izkgkgWJZ4rmyZDPDkOH1gqxwLAkEaXhLAqK1FV580cG779pCLUpE4fXC66/b+d3v7Hg8oZYm\n9Hz+ucbzzzs4dkyqnoHweOB3v7Pz+utyvkgCp6pK5bnnHBw4IJ+rULF9u87zzzs4e1YJtSiSMCds\nQ02OHj3Kiy++iK7rzJs3j1WrVrFhwwZ27txJWloa3/rWt0aURRotGIb4stsn9u/qOqSnm6SkTG6X\niscDDkfgP6+qkJYmxmyyTVefT3z+yz93XJxFcrJFTMzknkeDoWkjny8+HyiKeEYl44tpgt8/8fp3\nOFwuSE62cLlCLcnE4vWKea+GwX4jPt4kNVXF4QidbjMtC1WRhn+4E7aqOj09nXXr1qHrOj/5yU84\nf/48VVVVPPXUU6xfv54dO3awZMmSUIs54WzapNPYqHDPPT7i4ibu78bGwgMP+CbuD4Yhp04pbNxo\n55prfMyebQb0O7oOd9wx+cbN7YY337QRGwurVvnoWQumTzeZPt0bWuHCmJHOF48H3njDRkyMGOdw\nMECimU8+0Th0SOPee72kpIRamksUFZkUFU2u5+rCBXE6NGOGwfLlRqjFYd48k3nzQnsP1m2q4cmb\ni6TxHeaErZpOSkpCv+jCiYmJYffu3VRUVAAwa9Ysjhw5EkrxQoZpKvj98qEKBZZ16cRBMjymKcdq\nvLGsS+Ms43vHH9NUMAxFjnUYIOa9vBeX09Lt54Pq5lCLIRmGsPV493DixAna2tpwuVwoF3dxLpeL\nzkmafXTLLT4MY2ThDpLgUFho8fWve4iJCbUk4U9MDNx/v/DASufL+OF0wn33+fqF9EjGh+XL/Vx1\nlV/qgDAgPR3WrvWEXdhPKPnKvCx+vbueG0vC6DhG0o+w9XgDtLe38/zzz/ONb3wDl8uF+2JJja6u\nLmJjY0MsXWjQdWl0hxKXSxqSgeJwgE3m4o47cpwnDk1DGt1hREyM3HBezsK8BBo7vZxplZnZ4UzY\nGt6GYfDzn/+chx56iMTERIqLizlw4AAAlZWVlJaWhlhCiUQikUgkkvBAUxWuLkzikxOyrmE4E7aG\n97Zt26iurua3v/0tTz75JOfOnaO8vJwnnniCkydPsmjRolCLKJFIJBKJRBI2LClM4LPatlCLIRmC\nsI3xXr58OcuXL+/zXmlpKatXrw6RRBKJRCKRSCThy8zMOH5w/gRev4ldD1vf6qRG3hWJRCKRSCSS\nKMBl15iS7ORAw+QsQBEJSMNbIpFIJBKJJEqYkxPP3rqOUIshGQRpeEskEolEIpFECTMyYjkoPd5h\nS9jGeDc3N/Mv//IvnD59ml//+teoqsrDDz9MUVERAP/7f/9v4iaydaNEIpFIJBJJmFOW7uLo+S4s\ny+rtfyIJH8LW8I6Li+OJJ57gX//1X3vfKywsZN26dSGUSiKRSCQSiSR8SXHZiLGpnG3zkJvoDLU4\nkisI21ATm83Wr0nOmTNnePLJJ9m0aVOIpJJIJBKJRCIJb8rSYznU2BVqMSQDELaG90A8/fTTfPe7\n32X//v2cOnUq1OJIJBKJRCKRhB1l6S4OS8M7LIkowzs2Nha73c6yZcvYv39/qMUZd5qbwe8PtRSS\n0dLVBe3toZYiPGhuBp8v1FJEJx0d0CnzqIJKezt0d4daCslE0t4ObneopQge09NdHG6UiiEciRjD\n2+PxYJomAPv27WP69Okhlmh8OXlS4fnnHezcqYVaFMkosCz4/e9tvPyyg45JXtXp1Ckxl3fskHM5\n2HR1wauv2lm/3oZhhFqa6KC1FV580cGmTbZQiyKZINrb4Te/cfD229Fzz6eluahp6sZvWqEWRXIF\nYZtcaRgG//zP/8yJEyf44Q9/yJo1a3j22WdxOp3MmDGjt7pJtOJ0QnKyRWysfGgiEUUR909VTfSw\nfcomBqfTIjnZIj5ezuVgo+uQmmrhdFrI4gXBQdMgNdUkKUnO18mCpkFamklKSvTc8xibRlacnRNN\nbkrSXKEWR3IZYWsSaJrG97///T7v/ehHPwqRNBNPZqbFI494Qy2GZAysXCnjhAAyMpBzeZyw2+Gu\nu2QMTzCJi4MvfUmO6WTC5YL774++e16a7uLI+S5peIcZERNqIpFIJBKJRCIJjNI0mWAZjkjDWyKR\nSCQSiSTKKL3YSEcSXoxbqIlhGBw9epTm5maSk5MpLS1FVaWdL5FIJBKJRDLeFKfEUNvSjddvYtel\n/RUujIvhffLkSX784x/T1NREdnY2dXV1pKSk8Hd/93dMmTIloGsM1DJ+w4YN7Ny5k7S0NL71rW+h\naZOvSsLnn6u0tqosXerH4Qi1NJLhOH8ePvtMZ8YMkylTzFCLE7Hs2KHR3Q1LlxpRnaxqmrB9u4ai\nwOLFBtJXERnI5zzyOHNGYe9ejfnzDbKyoiep8nLsukp+kpPqJjflGbHD/4JkQhgXtf4f//Ef3HTT\nTTz33HP85Cc/4bnnnmPlypU888wzAV+jp2V8aWkpAK2trVRVVfHUU09RWFjIjh07xkP0sGf/fo3d\nuzW65OlRRNDUpLJvn8aZM7LkxGgxTdi3T+Pzz/WoqrM7EF4v7N2rs2ePjlfmo0YM58+L5/zsWfmc\nRwr19Qr79mk0NET3PStNd3FExnmHFePiO2pqamLVqlW9oSVOp5M777yTjRs3BnwNm82GzXappmZ1\ndTUVFRUAzJo1i61bt7JkyZLgCh4B3HGHD49HITk51JJIAqG42GTNGi9padHpUZkIVBVWr/bi9yvE\nx4damvHF6YR77/X0vpZEBtOmiec8PV0+55FCRYVJWpqX7OzovmelaS6qzslGOuHEuHi8Fy5cyKef\nftrnvR07drBw4cJRX7Orq4uYmBgAXC4XnZO0VVtKClGvKKIJTYPCQotYeco3JtLSiNrj4CvJyBBf\nksih5zl3yaptEYPTKe6Z3R5qScaXMunxDjuC5vH+2c9+1vvaMAyefvppfv3rX1NQUMDJkydpaWkZ\nk4fa5XLR1NQECCM8VloyEolEIpFIJINSmBxDfYeXLq+Byz758uLCkaAZ3pmZmSiKgmVZKIrC3Xff\n3fu94uLiMV+/uLiYTZs2sWrVKiorK3tjvyUSiUQikUgk/dFVhaIUJ8cuuJmdHRdqcSQE0fB+4IEH\nel/v37+f9PR0MjMzaWlpYePGjbS3t7NmzZqArzdQy/jy8nKeeOIJ0tLSuPPOO4MlukQikUgkEklU\nUprm4khjpzS8w4RxSa785S9/yT/8wz8A8MILL+Dz+dA0jddee41HH300oGsM1DK+pKSE1atXB11e\niUQikUgkkmikNN3Fjtq2UIshuci4JFc2NzeTlpaG3+9n7969PP744zz66KPs379/PP7cpKWhQaFN\nPksho7kZGhtDLUVkUl+v0NERaikk4Uw4zZGWFmhoCLUUkrHQ3S1qd5uTsMx6WVosR2QHy7BhXAzv\nvLw86urq2LdvH0VFRcTExGC322mTVmLQaGqC3/zGzrvv2ob/YUnQMQx48007r73mCBvjIFKoq1P4\n9a/tbNkSxZ1wJGMi3ObIxo02Xn7ZQWtrqCWRjJbduzV+8xs71dWTrytVbqKDFrefdo8/1KJIGKdQ\nkxtvvJGnnnoKr9fL448/DsDhw4fJzc0d03UbGhr43ve+R15eHrqu873vfS8Y4k4ora3gcoFtjPZy\nTAzMmGH01o1tboaEBFHWqoeuLtF8JE6GdY0YrxfcbkhMHPj7qgplZQbd3cqQHUS9XuFpSUjo/73W\nVnEfo7WcVUeHGKcrS6zFxVmUlxvk55tYlpi7ui7GQdauhs5OUJT+49ZTQfXKgk6DjXMkc/kcmUgG\neyZLS03a2qygzE+PR3wNpBMmgu5u8PmImpr4gX6ejAyLsjKTpKSxz6kevZWcLJ7V0TLQuj0eaKpC\nSaooK7ggL0QTT9LLuBjeK1asYOHChSiKQvzFpyElJYXHHntszNeePXs23/72t8d8nVBQV6fwyit2\nFiwwuPbase08Y2Lg1lvFNY4dU1m/3sYNN/iYP18oFcOAt96y4XYrrFnjjapFeSL45BOdvXs11qzx\nkpnZv360osDVVxvDXufjj3X279dYs8bTpzbzuXMKL71kZ+5cgxtuiD4vRFcXvPKKndhYiy9+0den\n9Xl8PNx5p/jMVVVi7mZkWKSlWdx1ly9EEocHHg+8/rodRRHj1rOp6+6G//kfO7ou3u/ZuHd1wWuv\n2XE6xfvjvYBPFJfPkYmiRz/Pn29w3XV9//bixcM/64Hy8cc6VVX9dcJE8c47Ns6dU/nKVzxRYXz/\n4Q826utVHnzQM+RmpqTEpKQkOBu5gwdV/vAHG7fe6qOiYnTXHGjdHk/KM0QjHWl4h55xO3NJSEjo\nNboBcnJyKCgoGPN1q6qq+MEPfsD27dvHfK2Jxm63SE62iIsbuhHISFtFO50WCQmXmjcYhtiRp6RY\npKRYUbMYTyRxcWLsbLZL98rtBv8IbYH4eIuUFLOfB81ms0hNHX4uRBqmKeavpl2af0N5hFwuSEqy\nSEy0SEq6NBZ+v5jH0Yxh9J9Pl8atrxdM0yA52SI5mT6bGE0T45eUNPQ4S4anRz/Hx/d/Jk1TeFWD\nwWA6Ybzw+egT15yUZJGaakbNupCYOPLPM5b7aZoQE2ORkGBysaffqLhy3R5v5uTEs6eufWL+mGRI\nwiOALkBSUlJ4+umn8fv9/PjHP2bmzJnERVAcRWoqrF07tFV96pTC739v55prfMyaFdguOC/P4i//\nUlzX54P164U7bPVq35hDWiYrixYZLFp0yfI7dw7+9V9jmD7dz9e+FrjGvuoqg6uu6m9BpqTAV786\nwh1WBPDxxzrHjqnce6+Xe+4ZfpymTjX55jf7joPHI+aw3Q5f+EL0eHEvx++HDRtsGIZ4TnuMMF0X\nn/lKbDbxcwOhKNG1eQsVQ+nnd9/VaWpSuPtu35i70C5ebATVgz4UHR3wxhs2MjMtbrlF7PJWrIiu\nE7bRfJ4//lHnwoXR3c/Nm3Xq61XWrPGOKYzz8nV7IqjIjOXYeTdun0GMLQqVagQRUVkGuq5jt9tx\nuVzMmzePQ4cOhVqkoGNZY/P29fy+zydeS4KDafbEEkq34lCIuTf2ygE+n/CcR/McDsZzallinKJ9\nrEKNaYrwskgbYzE/lKg/PRopXq+C16uM6n4aRmSurzE2jZK0GKrOdYZalElPRHm8u7u7cTqdmKbJ\nwYMHuf7660MtEgDHj6t88onGddf5yc8f29NYWGjxta95Aj5+2rVLo6ZGpbjYz5EjOrfc4uPuu4Vn\nLFqT9sbChQuwaZONWbMMZs4M3DrMzoZ/+if3iJOrzp1TeO89nQULDMrKTD78UKerC266yT9kUmak\nsGWLTkuLws03+3A64brr/Cxb5h/TEazDAffd50NRhAcY4IMPdNraoLlZYeVKP7m5EbbqXYGqQnq6\niWn2DSkxDHjvPfGhb7rJP6y3vyep0uHoG4IiCS5xcWJzow+yYtbXK/zpTzqLFhmUlk5cQuihQyq7\ndmmsXOkbMF48Ph6+8hVvVJ4aDYbHI3R8QoLVL1a/h9tv92EYl5K5d+zQOHFC5dZbfcPGva9c6e/z\nu4Fy4oTK1q0a11zjp7AwNPprbnY8e862s1DGeYeUiDK8Dx48yKuvvkpMTAyLFy8mIVRp4VfQ2gpn\nz6q0tyvA2B+okRx9NTQo1NaqpKSonD6t4nYrJCdHtlEynnR2Kpw5o5KXN/LFMSlp5H+vo0P8vZIS\nUcHj9GmFzk4Vvz86DO8zZxSamlR8PrEQ6frgxslIuHxsTFP8nc5OhfPnlaA9Z6HE74cTJzQMQyTp\n9oyZ3y8+q6III3w4g8nvh7o6DafTwjCCM/aS/tTV9Z3nV9LznE+k0Q3Q0qJw9qxKR4dKRsbAf3uy\nVQryeuHUKZXk5MHvhc3Wt7LYhQtQW6vgdg9fHeXK3w2Utrbg2gmjYUFePP++tZavXzW2CnOSsRFR\nanrevHnMmzcv1GL0Y9Ysk5wcD2lpY7/W+fPw2Wc6FRVGQLvi66/3s3ixH5cL5swxgiJDNFNQYLF2\nbXCz+dvbYds2ncJCk7Kyvsq+uNhk7VpPb1Lc3XcLT8tY40TDhS98wYffP/xiZVnw2Wcafj8sWWKM\nyAOnqnDXXT68XmFopqePTeZwwG6H++7zYll9DSObTcwZCMyIdrngi1/0oKrS6B5Phpvnlz/nl2Oa\nsH27hqqK2O5gJ8DOn29QXGxExTMRLISX3xOwjqmvV/B4FO68c+BTg2BRUWGSlRUcO2G0lGfE0t7t\n53RrN3mJk2xHFkZIVR0ENI2gPbCNjSr79mkkJVkUFg4fmBcTQ++x/mTzbIyWYCu+lhaFzz/XME36\nGd7Qd25EUC5wQAT6efx+2LtXw+tVmDfPGHEmf7SNGwxsxHm9cOCAUMuLFxsBPdOD1ZqXBI/h5p+i\nDLwGdHfDnj06mmYxf74R9PA/uz06NqLBZiTPxLlzCgcPahdPQcfPEx1MO2G0qIrCssIkPjnRyhfn\nSIMhVEjDexCamqCqSqOszBjwYdm4Ucfthrvu8tPSAtu22cjIMFm40Bh1JRHTBI/H4rrrfMyZc8mA\nq6tTqK5WmTXLmLSLbGenMNxyc83ek4CODti3TyM/3+wXW79tm0Z9vcrNN/s4dUqlslJjyRIfQaho\nCcDJk+Joec4cg7w8izVrvH3K4Q2Gzwd79oiN1bRp4dG7+MABFY8H5swxh4wTtiyorFRpboazZzVu\nuMFHS4tKZ6fC3LnCi11drXL+vPj/5eEiNhvcfbcX01QCNrpraxVOnRJjHBcnFsgjR1RmzjT6eRYj\nkbfe0jEMoUN6vHN2O5SU+Htf92BZsG+fiqrSp9qRaYqKGw6HxY03ygy6QDhzRuHECZXkZIM9e2zM\nnOmjqspGRYVBZ6dCTo456hhct1s83z3XcLng3nu9KIo1aqO7594rCsyeHR46Yzw5fx4OH1YxDKE3\nFEUhI8Ogvl4jO9vg7FmN7GyTs2eDsyaWl5skJvrIyhp6bCsrVWpqhP4pLo7cULerpyTy/M46vjgn\nM9SiTFqk4T0Ip06pfPKJKGmWkdF3QevqghdftNPcrLF4cTvnzmm89pqdRYt8FBcPbKgHQlsbfPCB\naDqyZMmlMkPHjglZUlIsEhOjX/EOxLlzKlu26Myda1BYKAyT+nrx3sKFBvn5fZNoNm+2sWuXxowZ\nfrZv13njDRspKSYFBcExTg4e1NizRyM722LqVJOCgsAUcVOTwvvv6xQUmGFheJumSJB0uxWKijxD\nLmLd3fDRRza6u0WyY06OybFjGi0tClOnGqSkiLbMNTUq+fkmOTl9x0R45gJfsI4e1fjsM43MTIuS\nEpOaGvEcJCVZQ8ZvRgJNTfD883a8XoWrr/aTlSXeb2+HV14RO5arrurqvR9dXWLsdR3Kyjy9Rlxj\nI7z8soPYWJNly9xjSmqdLBw5ovHppxqFhSovveRgzRoxhvfe6+HcOZXZsy/pmJHS0KDw0Ud6n2sM\n1IBrJLjd4t6rKpSWeqL+ZPPkSZX9+3VOnFCIjxehZrNnK+zbpzF3rsKePRrl5SYHD2pBWRPtdpgy\nZehrWJYoI7htm421a7spLo7cTe7cnHia3KeovtBFcarsrBcKIs7wfuGFFzh+/DhTp05l7dq1Qb32\nyZMigauszETXLZYv9w7YlaqrS9R7jYkxKSyE1FSDxx93k5hojenYLykJVq3y4XD0bYYxa5ZBaqpF\nUdHIFExNjUgGGij8IdKIiTFZsMBPQYFBZaVKeblJYaHJ6tW+AZOKvvhFLytWKEybZhEX5yU/3yA2\n1qSrKzittRcu9FNYaI64pXVGhsXdd/tISLCwLFGVwOWyQpblrqpwxx0+WlsVTpwAw1DJzLQGrBoS\nEwOrVnlpaYEFC3zEx1ssXWpht4uGLwDXXutn9myFrKyxf565c/1kZ5sUFIgxrqgwSEgY+Dmor1do\naFAoLzcjonZ9Sgo8+mg3fr/Sa3SDOCK/5x4PitL3uDw2VuiGKz2nmZnw7W+7cTiQRneATJnix++3\nyMkx8Pth4UIf2dkm06YZdHSopKWNXl/m5lqsXu0b0zV6sCzRITEuzmL1ag+gRJ3RXVOj0toqatFP\nm2YRGyvWK5fLx9VX9+QtKKSkmCQkWBfHwiAtzWLaNGPEa+JoURRRaWnJEn9A3S+rq4XHfqKTbQNB\nUxVuK0vl7UMX+M7V0vAOBRFleNfU1ODxeHjyySf55S9/SXV1NcXFxUG7/vvv27hwQcHh8PDOO3ay\nskyWL+//4FRV6VRW6qxeLbzScXGwdGlwHrCexKrLSUqCpKSRXd/vh3ffteH1Qk5O5LcGrqrS2bVL\no7VV5dgxlaQkL/n5FuXlA49LWZlJWZl4nZsL1dXw0UcOEhIG3kyNlLQ0RrW4KsolZdzUBG+/bSM5\n2eJrXwtdM538fIvTp1X27bNz+LDKkiUGDzwwcLOWwkKLwkI4eRJeftnOzJlGn9bemZnWmD18PaSk\nQErKpTFOSGDQe7drl0ZlpUZiojdkm5iR0N4Ob7zhxO+Hq6/uIjVVvN/cDL/7nQNFEe9fbnwP5pW7\n6qrwW9zDmRMndHbt0mlsVHn1VQfJydZlc3hsY6nrDKqTRsr580I/ZGRYPPywl0iv5HMlPp9Yo44f\nVykuNtB1PzNnmsTFQXn55Z/VoqMDdu3S0XX4y7/0XIxtn9h5X1BgBXSy6fGINvamCbm5nrBMpL+1\nLJXH3jjEwwuySXRGlBkYFWj/+I//+I+hFiJQduzYQWFhIXl5efh8Pk6fPs20adP6/dzx48fJzs4O\n+LqnTsFHHynExEBOjo/z5xVycgzS0gzOnVPQNIXmZujqEkdfMTGi3XdxsdnnyLexUe0X59vSImJo\n/X7hweroELFiXq+F1wvnzysDlqkTZeeUfgazZYm64YYxdKtZVYWEBNGSNi3NIiYGGhoGl/H0aZXE\nRCsotYDr6upGNP6DsX69wvHjGjU1YFlizB0OPwUFJm63gtdr0dSkomnWsJ4gcc9MOjsBrCFDKpqa\nhCGn6xZ1dSrx8RaNjQpNTUrv7/n9wltz5d/u6BD1WuPjrUGz6r1e4RExTeHhmT3bJCVFlIOrqVFR\nFGvU3svRjP3mzSpdXcKbVFzsJyHB5NgxEd7jcll4PFBbq9LUZNHcrOB2K6SlWYAIs+kxGnvweMTn\ncDoturouza1z5xRaWxUGqgK6a5dKZ6fV71o91NcrNDdfGv/GRmhoUHtLZ7pcFpmZJkVFVlCrezQ0\nDP6MDkSg4+9wgK6blJcbzJ176XkU992krMxgzpy+z+m+fSJ+PiMjugywYBLI+J84YaHrCjNn+khO\ntigv99PaquJwXDpNOHFC6OjBjKbWVvFMWJbF7t0adrvF/9/enYc1deV9AP8mNyGQsC8issgmAiOL\nC7iMo6Binalja5fX6VRrO+PSVq211alWqzJtdWZa+2i1tfp0Rtupu1MdHBVFrEVGURGtK4JsoiDK\nJossSW7eP26TEZNA7iUkBn6f5+nz2HDuuScnZ8vJOedeusRAJvvfNSUlIrS26p9gVFXFLZNzddW0\ne8qJgwN3pGRgIAu1WoP6esN151FKJVf37Ow0nT6ulGW5uADT2iO+bQ/DcPU4IEAFT08VlEouD+/f\n59pIsZhb8imTaeDoyPVnISEsPD01bdrJR/tEsfh/bU97a+orKrhfG2Wy//WjLS1cX11VJYKHR/uf\nzeNu3eLaRUdH7suXkxP3y9zjvxw+2m6VlHCnqVRWAkVFDBSKzn1mfPJfYcegoqEVN+4/xGA609ss\nysvLERwcbFJYmxp4X7p0CV5eXujduzdqampQXl6OyMhIvXB8B96ZmWLs2OGA1FQ7uLpqUFbGIDVV\nhrt3GWRlSXH3rgi3bzO4do1BTIwazs7cT4qPVuz9+6U4c0aCsDB1m4Y2K4vBxo0ylJcziI9X4cIF\nBmvW2EOlEqG6Gvjvf6UIC2t7ykNjI7B9uwz5+dz9Hh3AVVSIsGOHHerqxIiMbP8bf2MjN6OgVIrQ\nrx9rNI0nT0qQni6Bv7/GLGeAm2PgfeoUsGaNAufOScCyImRlSZGZKUVDA4OyMgkOHpSCYbj1yTKZ\nCEFB7eeFQsF9mfnrX+VgWWDwYONHe6WlSbBunQMcHDQ4e1YCHx8WR49K8dNPEkRGcidNFBWJsXev\nFAzT9t7Z2QxSU6Xw8tLAy8twXt64Icb+/VLcuiVGcTGje+BMaakIu3fbQa0WmfRzpiF8876uDli0\nSI7CQgkKC8UoKZHgp5+kuHFDglOnpFAouC8f338vRUuLCGlpUpSVMfD2ZpGWZgepFHpr1a9fFyMl\nRQq5nOtQ0tMl8PHR4PBhO1y5wmDAgLanOxQXA8uXy1FaymDsWP21tWo1sGuXHX76iTtmUyYDDhyQ\n4vRpCfr148qyszPQp495B90A8K9/SXHunAT9+5t2Eoup+V9UBCxeLMcPP0gwZIhSt9yktBT405/k\nOHtWgnHjlLqBVnU1kJzsgOxsBmPGqOjhWEaYkv+7d9vh/fcdEBfHYsECBfr3VyMnRwKZjJvVvH8f\n2L7dDvfvi41uZjxzRoKjRyWoqhJj40Z7ODpq8OWXMjg6cptfKyuBbdtkBuNIS5MiI0OCoCC23YF0\nVRVw6JAdHjwQ4eZNCa5e5daOt1fG8/LE2LeP25vU2V9+bt8WYdcubh+CKUsm+LY9t24B778vx5Ej\ndpgwoRUXLthh5057XLokgZMT94X3xAk7yOUa+Plx7amnpwa3bomxe7cULMu1k9o+sbaWmwj5979l\ncHIyvFxO6z//kWLjRnvY2/9vs/KNGyLs2SPDyZNcPpu6afPBA66/Li4WY9Agrl8x1v5r260+fdT4\n/nsZCgvFuHRJgkOHJPD3Z+HnJ/wz45v/oR5yrMu8haEBznB1sIH1eU+4bjvwvnXrFhiGgb+/P4qL\ni6FWq80y4/3gAfeNOjxcDT8/FZydRQgNVSM4mPsvVb9dWAAAHrFJREFUNpaFtze3ntdYZZZKucoW\nHKw/0+niokF0NPe0KrGYW5oSFsbC15dFr14aBAW1vUb7EJKAALVeRZRIuJmCoCD251lH47TxBAVp\n4O7ODUp69dJPIzc7DoSGmue4K3MMvJubAZlMg5gYFkFBavj4sAgP536FCAjQIDRUjZAQFn5+3PIc\nU04UkUo1kMk0+MUv1B08YVQDJycNoqJU8PLi4ndy0sDHR4PAQM3PZyZrdIPuR+8tFnMzVaGhaqOz\nRBIJN+MWEMCdxqL9/LnPVoTgYFbwFyC+eS+TASqVBkFBavj6cmU8LIyFtze3fjI2ltss7O7OwsuL\nRVAQi9BQbn39o2Xr8fcnlYoQEsLCxYUrW2Fhajg4cJ1hQEDb2SSZDLCz0yAqSo2gIP33LRYDDKNB\nnz4aXR1imP/Vt648v9pYnTHG1PzXaLjyGBurRlQUq+vk5XJALNYgJkaN4cNZ3T25h3ZwS6siIliz\nnwfdXZiS/7W1GoSFce2Jry+LgQNb4evL1TtnZy6vtW2ssS/PYjE3s923LwtXVxYDBijh4cE9S8Hb\nW/NI26sfB8MAbm7cjGh7+xG0bX1ICFf3/Py4gVl7n722bQkOZjt92of2PQQG6tdxQ/i2PS4uXNsT\nE6OGkxMLhUKDvn1ZDBighp8fi8BArl8ODWXb/PL7aNvr5qbRfV7BwVxeS6XcNe0dAcmyXHseE6PW\nfT4Mw7U1oaFcHTO1L9TePzCQ7XBvi7bdCg3lJu64NHPjivDwzp3Qwjf/5XYMFDIGW7LLMbafOyRi\nalQ6g8/AW6TRaGzmd8uioiKkpaVh1qxZ+Prrr5GYmGhwjXd6ejoGDRpkhRQSAMjJyaH8txLKe+ui\n/Lcuyn/roby3LiH5r9Fo8MmPJXjQrMYH44JgLzHDWtMeKicnB2PHjjUprE3lclBQEOzs7LBixQow\nDGPWjZWEEEIIIT2FSCTCO6P6wsVBgrdTbuDG/UZrJ6lHsLntrOY+QpAQQgghpCeSiEVYNCoAafnV\nWJFWiDBPOSZGeGKwrzMYWn7SJWxu4E0IIYQQQsxDJBJhfJgHRgW74YeCGnxzvhxrM0uR1M8d4/t5\nwNelk0fkkDZo4E0IIYQQ0sPZS8T4dX8P/Lq/BwqrmnAkvwpvH8hDgKs9ngpzx6+CXOEgNWGXOWkX\nDbwJIYQQQohOsIcD3vDww4y4Pjhzqw5H8qrwVdYdjAx0xcRIT4R50lMvhbKpgfeJEyewf/9+uLm5\nISQkBFOnTrV2kgghhBBCuiUpI8bIIFeMDHJF1UMljuZV4cNjRXCxl+DpCE8kBNMsOF82NfAGgEmT\nJmHMmDHWTgYhhBBCSI/hIZfipdje+L9ob5y/U4cD1yqxKes2on0cMdjXGcEeDvB3kcFJJml3Yyar\n0YDVcOeps+CO12PEIohF3HpzS1CqWVQ9VKKyUYn7ja2obFSiRa0By2ogFgEBbvYYFeTWJfe2uYH3\nwYMHceHCBUyePNnkw8oJIYQQQkjnMWIR4v1dEO/vgrpmFc7fqcfFsnocL6jG7QctaGxVw14ihkgk\n4gbZLDfQVv884AYAsQhgRCKIRNwDxbR/E4sAsUgERqQdjIvAiEVwkIrhIBHDQcrAXvdvMeylDPdv\nO0b3moNUDBFEaFKxaFKq8VDJorZJifuNSlT+PMiub1HDXS6Bp9wOXgopPBRS2EvEEItEULEaNLYK\ne3q0KWzqAToPHz6EXC5HRUUFvvrqK6xYscJguPPnz6O2ttbCqSNaDMNArVZbOxk9EuW9dVH+Wxfl\nv/VQ3lsX5b91ubq6YvDgwSaFfSJnvGtra7Fu3bo2r7m4uODtt98GAHh7e0Mmk6GpqQkOBp7Lbeqb\nJ4QQQgghxFKeyIG3q6urwdls7UD74cOHaGlpMTjoJoQQQggh5En0RA68jTl48CAuXrwIhUKByZMn\nWzs5hBBCCCGEmMym1ngTQgghhBBiq8TWTgAhhBBCCCE9AQ28CSGEEEIIsQCbWuNtTgUFBcjLy0Nj\nYyMUCgXCwsIQEhJi7WT1aPSZWA7ldddpbW2FnZ2dwb/xyffa2lo0NjbC19dX91peXh7CwsJMSkdq\naiomTJhg8G/V1dVwd3fXpenGjRsIDQ1FaGgoxGLD8zG5ubmwt7dHYGAgzp49C5VKhbi4OEilUpPS\n05WMnXClxbe8NzQ0IDc3F2FhYXB2du6KJPdY1PaYR1fkI5V7y+gWa7xra2tx8+ZN3TnfoaGhcHV1\nNRp+69atUKlUiIqKglwux8OHD3H58mUwDIPXXnvN6HVqtRrnzp3TK+xxcXFgGOOPTBVynSXvBXAd\nV1paGvLy8nT5GBYWhqSkJKMdWlNTE1JSUnDp0iXdNdHR0Zg0aRLvE2eEfibGCM0HQ4TkjaXiEpL/\nQvLa0uXRFupMdnY2duzYgfr6eri7uyMiIgL9+/dHamoqVq5cqReeT76npKQgPz8fDg4OqKurwxtv\nvAEXFxckJycbPPFp+fLlEIlEeLQ5Ly0tRUBAAJKTk/XCa+M5cOAA7ty5g0GDBiE/Px9KpRKvvvqq\nXvivvvoKzs7OaGhoQGNjI3x8fODi4oL8/Hy89dZbZsnTgoIC1NfXIzo6Wjf4P3v2LOLj4/XCfvfd\nd5g6dSoKCwvxz3/+EzKZDKWlpZg9ezaio6MF5fvHH3+MpUuXIisrC0eOHMHAgQNx/fp1xMTE6H2B\n4fP+Ghoa4OjoCAC4desWrly5gvDwcL0HwHVFnHzi5RvniRMnkJOTo7tu0KBBSEhIaLfOUNvTltD+\n4Ouvv0ZxcTFYloVKpYJEIoFYLEbfvn0xc+ZMo9cZwqfcd8Sc/S6f8mhr6WJWGuohbMj+/fuRmpoK\nuVwOhmFQU1ODw4cPo7KyEuHh4Qav2bdvH9599134+fnB29sbfn5+GDRoEPbv34/ExESj99qwYQMk\nEgni4uIQHR0NHx8fFBYWIi0tDUOHDjXrdZa8FwCsWbMGERERePrppzFmzBjExsaivr4eu3fvxsiR\nIw1es2jRIty/fx9DhgxBVFQUPDw8cP78eRw5coR3hRX6mRgjNB8MEZI3lohLaP4LyWtLl0dbqDMr\nV67EmDFj8Pzzz0MkEuHGjRuwt7fHxYsXMWnSJL3wfPJ9586dWLJkCeLi4uDn54eNGzfC398fly9f\nRkJCgl7cjY2NUKlUePrppzFlyhQkJibi2rVrWL58ucG0Hz58GImJidi1axfmz5+PgIAAREdHY9eu\nXRg3bpxe+P/85z+YN28eBg4ciC1btuD9999Hv379kJqaajA9fPP022+/RXFxMRoaGrB7927djNvX\nX39tMP6//OUvuHjxIg4dOgQ7OzuwLIvKykpkZWXh2WefFZTvP/zwAxISErB161YsXLgQAwYMwIgR\nI7B9+3a9NPB5f6tXr0ZCQgKOHj2KEydOICwsDKdPn8bNmzcxYMCALo2TT7x84ly8eDFyc3MREhKC\nvn37QiKRICMjA8ePH8f48eP1Pi++n4XQvLbWdZbsd7X3mzJlCl544QVMmDABw4cPh7OzM1JSUvDM\nM88Yvc4QPuW+I+bsd/mUR1tLl80vNcnJycGf//znNq9NnDgRy5cv12uAtYKCgrBp0ybExMTA3t4e\nTU1NuHz5MoKCgtq9V2Vlpd7sTnBwsNHOrTPXWfJeANdxDxs2TDfT5OjoiGHDhuHw4cNGr6mpqcGW\nLVva/DT97LPPCpqhFvqZGCM0HwwRkjeWiEto/gvJa0uXR1uoM83NzXjuuecAACEhIYiJicG2bdvQ\n1NRkMDyffFepVLqZrMDAQCxcuBAbNmxAaWmpwbgnTpwIpVKJ48ePIy0tDSNHjkR7P2b+5je/wfr1\n6yGXy7FmzRpER0ejoKAAkZGRBsP37t0b27dvR319PSIiIrBz5044Ozsb/WWRb54WFhbqfiUYO3Ys\nvvjii3a/PDo5OUGtVkMqleKjjz6CRCLBqlWr8PDhQ72wpub77du3sX79ety+fRsSCdc1isVig5+n\nkDJz+vRpLFmyBHZ2dhg2bJjeLxddEaeQeE2Js6KiAt98802b16ZPn47p06cbTStAbc/jhPYHUqkU\nly5dglgs1uXjlStXBC374lPuO2LOflfLlPJoa+my+YG3l5cX9u3bh+joaN3Dda5cuQJPT0+j17z6\n6qsoLCzEzZs3UV5eDrlcjqSkpA4HeUOGDMHq1avxi1/8Ag4ODmhqasK1a9c6fFKmkOsseS8AGD9+\nPJKTk+Hv76/7CbC0tBRJSUlGrwkICMC8efMQHBwMJycn1NfXo7CwEP7+/u3eyxChn4kxQvPBECF5\nY4m4hOa/kLy2dHm0hToTExOD5ORkDBw4UHcdwzAICAgwGJ5Pvr/yyitoaGjQDWydnJzwpz/9CadP\nnzaaHqlUiqeeegpjx45FRkYGAgMDjYYdPXo0fvnLXyIvLw83b96ERCLBb3/7W6PXzJ49Gzdu3IBM\nJkNQUBDOnDkDtVqNN954w2B4vnmq0Wh067Td3d2xePFibN68GYWFhQbDv/TSSwCAkpISrF27FpGR\nkWhpaUFsbKxeWFPz/eOPP9b9WzsQam5uxpQpUzr1/goLC7F8+XLcuXMHSqVSN0Pf3Nzc5XHyiZdP\nnL1798b8+fMRGxsLR0dH1NfX49KlS/D29tYL+yhqe9oS2h9MnToVBw4cQHl5OUQiEViWRUtLC15+\n+eV2rzOET7nviDn7XT7l0dbSZfNrvNVqNbKzs5Gfn99mjdTgwYN5r90xRWVlJXJyciCXyyGXyxES\nEoKKiooONzzV1dWhoKAAjY2NkMvlKCwsxAsvvGA0fHV1NRiGQUFBAQoLCyEWixEeHo7w8HCjm5+0\nrl27htzcXPTq1QsAwLIshg0bZnTDl5ZKpcLdu3d1+ejj49PhWrgzZ87gp59+Qn19PZycnBAbG4v4\n+PguyXu+Hjx4gMLCQjQ2NsLe3r5TG0b45o0l4jKU/wMHDhS0bs0UDx48QEFBgS7dISEhuH//PkJD\nQ9u9TmidqaysRG5uLgDg3r17iI6O7vBefOvZo++Nb1l5vI5mZWXhD3/4g0l1tCfgU17u3bsHhUIB\nhULR5vVr164ZnYV/VHJyMuLi4hAWFtZhGTEXofUBAFpaWlBaWqoXlk9dqa2tRUNDA/z8/HRxlpSU\nGAxral2qrKyERCKBq6sr8vLyoNFoIJPJ9L6QqdVqZGRk4MKFC2hoaIBCoQDDMJg3b55N97uA8L7X\nUv3u49dp1yz37t1bN2NtTZ2pFx0xVm9MIbQMGcKn7hli82u8xWIx/Pz8EB0djcGDByM6Ohq+vr5Q\nq9VmbwBSUlJw/Phx1NfXIz8/H+PHj4eLiws2bNjQ7lqo5cuX4/Tp07h+/ToKCgqQm5uL7OxsXLhw\nwei6tr/97W946qmnkJ2djYqKCvTv3x/Xrl1DTk6OwVkdra+++go1NTWora1FUVERNBoNGIbBkSNH\n2l3LpP0Ck52djRs3buDOnTtoaWmBj4+P0cZGLBajtbUVvXr1wuTJkzFgwAAEBwfj/PnzbU5isIaP\nP/4YSUlJKCkpQVpaGhwdHXH48GE0NDTwrrRC8sYY7cDO2dkZjY2NuHz5MqRSKdzc3HjFA3CzhOXl\n5aivr4dIJIJCoYCHhwe8vb3N3gCzLAuZTIbevXvD398fvXv3hkwmw5dffonRo0cbvU5ondm7dy9O\nnjyJoqIiNDU1oaamBnfu3MG1a9f0Ns9pCalngPCy8ngdraqqglgs7rCO9gR8y4uDgwOkUik0Gk2b\n/zZt2mQwPMuybcL9+OOP+OMf/9hhebTG+3s8rdo2+fGwfOpKSkoKjh07hsLCQqSnpyMqKgoKhcJg\nWFPrkjbcmTNnkJeXh9zcXJSXl6OsrEyvzq1cuRIlJSVobm7Wzbbm5eUhJycHY8aMMU8mC8iXRwlt\nD4T0vZbsd7WKiopQW1uLyMhIuLi4QCwW49y5c1bte4X2E8biMqXemEJoGTIWl6l1zxjrfz3qpJyc\nHBw4cACtra2Ii4vDM888A5FIhFWrVglaC9SeCxcu6OIsLi7GZ599hmnTpnV4XXx8PEpKSjB69Gjd\n4vtVq1bh/fffN3rNw4cPoVKpcP78eSxduhRSqRTx8fFYsmRJu/e6e/cuXn/9dbAsi9mzZ+Odd94B\nAJw5c6bd67744gv07dsXI0eObLPb/IsvvjB4agEALFmyBGFhYVAqlVi7di0CAwMhEonQ0NCAuLi4\ndu/X1VQqFQDg2LFjWLRoEeRyOSZOnIgPP/yQ98ZPIXljzKeffooVK1bg6NGjuHLlCkaMGIFjx47B\nxcWF9097xtI1b948bN68mVdcHZk2bZrBb/PFxcXtXie0zly+fBnJyclQq9V46623sH79eojFYoMn\ndGgJqWeA8LLyeB1dtWoVfv/733dYR3sCvuWls+GLi4vx4YcfdlgezYVPek0Ny6eu8Alral3iU+f6\n9OmDnJwcKBQKjB49Gs888wxWr14NpVJpMA2dYcl+FxDW91qy3wW4zchqtRqOjo74/vvvMXv2bPj6\n+uLQoUNW7XuF9hNdHZfQMtRVcdn8wPvQoUNYunQpGIbB0aNH8cknn2DOnDldci++G560+G58Avhv\nftLiuwlKS8jmg/LycqxevRpr1qzBkiVLsHv3biQmJuIf//hHu/eyhJ6wYeT8+fOorKzE+fPn27xe\nV1cnOF3G+Pn5YeHChXpLAT788MN2rxNaZ1iWBQDdMWPa2Z/26o2QegYILyuP19GqqiqsX7/epKUR\n3R3f8tLZ8NrjETsqj+bCJ72mhuVTV/iENbUu8alzlZWVWLduHX788Uf88MMPOHv2LOzt7fXCmYMl\n+11AWN9ryX4X4L8Z2VKE9hNdHZfQMtRVcdn8Gu+lS5e22RyQl5eHbdu2oba2FuvWrTPrvfLz8+Hl\n5dWmMqnVapw+fdrko+BUKhUyMjJQXl7e4UYIlUql2/ykXXfa3oYpgGskDW2CGjJkSLtrzVJSUnD1\n6lW9zQcRERFGjyeaOnUqpk6dirS0NKxZswZKpRKbN2/GyZMnsXPnzg7zoivdu3dP9293d3dIJBI0\nNzfj+vXrGDhwIK+4hOSNMdOnT0ffvn1x584dfP7551AoFGBZFkuWLMFf//pXXnHNmDEDQUFBiIqK\napOusrIyfP7557zi6khNTQ0cHR31ds13tKRLaJ0pLS1Fnz592sStUqlw8eJFDBkypMP08qlnnSkr\nj9bR9PR0LFiwoMM62hPwLS+dDa8deHfFEkND+KTX1LB86gqfsKbWJT517tF+V6VSYc+ePcjIyICd\nnZ3N97va8Hz6Xkv2uwCwYsUKLF68WHfWt7bvPXv2rN5pM5YktJ/o6rjMUYbMGZfND7yPHTuGmJgY\neHl56V6rrq7G3r17MWvWLCumzPbw3RSRkpICmUwGmUyG+Ph4yOVyNDU1YcuWLXjzzTctnPqu9SRu\nGLlw4QI8PDyQm5vbZsNITk6OoLPPSefU1tZ2OMNFugblvWVRv2s+QvqWzm5GJtZl81vvx40b16by\nr1u3Du7u7lT5eWJZVncqyYgRIxAbGwsnJyfs2LHD6DUTJ05EUlISRo0aBXt7e6xduxYymQxVVVUW\nTHnXE5I37cX1+H9SqVRQXKWlpdizZw9u3ryJzMxMpKenw8XFBRkZGbzjIp1HAz/roby3LOp3zUNo\n3+Lp6QkHBwe9vuRf//qXhVJOOsPm13g/rra21tpJsElCNjI8fk1RUZFFNzhZiq1sGFm5ciVu3rzJ\nOx5CCOkM6neFEdofmLMfIZbX7QbeRBghGxmsvcHJUmxlw4i/vz/27NkjaMMIIYQQyxLaH5izHyGW\nZ/NrvB+nHfwRfoRsZLD2BidLsZUNI8nJyVi2bJmgDSOEECIU9bvCCO0PzNmPPCl2796NiooKzJs3\nz9pJ6XI2v8abmIebm5teJQbQbiUWco0tMuf7NGdc/fr101vbyjAMDbqJWU2ZMgUVFRXWTka3MmfO\nHFy+fNnaySBWJrQ/6I59r0gksnYSLKbbLTWZP3++tZPQY1HeWxflPzGkubkZ7777Ll566SXdl7Km\npia88847mD59OqqqqpCamoq6ujp4e3sjMjISU6ZM0R1VRrpGdxpoUNtDOqubLb5oV7cbeNPuduuh\nvLcuyn9iiL29PWbNmoX169cjOjoazs7O+O677xAaGophw4ahoqICo0ePhqOjI+7du4c1a9bg+++/\nN+m8Y9K1bGXpALU9hI/jx48jPT0dt2/fhpubG2bMmAGRSAS1Wo1NmzYhOzsb7u7uePPNN9G3b19r\nJ9fsaKkJIYR0czExMRg0aBC2bNmCq1evIisrCzNmzAAAeHt7w9HRUReWYRj4+vq2uf769etYtGgR\nZsyYge+++65HzU51lbKyMixduhSvvfYa1q5dC6VSiatXr+L111/H0aNHMX/+fGzcuNHaySTErOrq\n6rBnzx7MnTsX33zzDZYtWwYvLy9oNBqcOXMG0dHR2LRpE4YPH45PPvkEarXa2kk2u243400IIUTf\n9OnTsWDBAly6dAnTpk2Di4uL7m+ZmZnYvHkzWlpa8PzzzyMhIaHNtT/++CNWrlyJpqYmJCcno0+f\nPhgzZoyF30H3kpaWhtmzZ0OhUOCjjz7CiRMn4Ovrq3ugSnJyMuRyubWTSYhZiUQitLa2ory8HF5e\nXvD09NT9zc3NDcOHDwc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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x107754710>" | |
] | |
} | |
], | |
"prompt_number": 35 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Trellis Plots\n", | |
"\n", | |
"One of the enduring strengths of carrying out statistical analyses in the R language is the quality of its graphics. In particular, the addition of [Hadley Wickham's ggplot2 package](http://ggplot2.org) allows for flexible yet user-friendly generation of publication-quality plots. Its srength is based on its implementation of a powerful model of graphics, called the [Grammar of Graphics](http://vita.had.co.nz/papers/layered-grammar.pdf) (GofG). The GofG is essentially a theory of scientific graphics that allows the components of a graphic to be completely described. ggplot2 uses this description to build the graphic component-wise, by adding various layers.\n", | |
"\n", | |
"Pandas recently added functions for generating graphics using a GofG approach. Chiefly, this allows for the easy creation of **trellis plots**, which are a faceted graphic that shows relationships between two variables, conditioned on particular values of other variables. This allows for the representation of more than two dimensions of information without having to resort to 3-D graphics, etc.\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Let's use the `titanic` dataset to create a trellis plot that represents 4 variables at a time. This consists of 4 steps:\n", | |
"\n", | |
"1. Create a `RPlot` object that merely relates two variables in the dataset\n", | |
"2. Add a grid that will be used to condition the variables by both passenger class and sex\n", | |
"3. Add the actual plot that will be used to visualize each comparison\n", | |
"4. Draw the visualization" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"from pandas.tools.rplot import *\n", | |
"\n", | |
"titanic = titanic[titanic.age.notnull() & titanic.fare.notnull()]\n", | |
"\n", | |
"tp = RPlot(titanic, x='age')\n", | |
"tp.add(TrellisGrid(['pclass', 'sex']))\n", | |
"tp.add(GeomDensity())\n", | |
"_ = tp.render(gcf())" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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yMrCxsSE/P5/U1FT69OnTIickaIe5uTmrV6+mU6dOXLt2jUmTJnH48GGsrOrP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\niB2CIAiCAIgdgiAIgnDF/wfAEziD4b15xAAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106759110>" | |
] | |
} | |
], | |
"prompt_number": 36 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Using the cervical dystonia dataset, we can simultaneously examine the relationship between age and the primary outcome variable as a function of both the treatment received and the week of the treatment by creating a scatterplot of the data, and fitting a polynomial relationship between `age` and `twstrs`:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"cdystonia = pd.read_csv(\"data/cdystonia.csv\", index_col=None)\n", | |
"cdystonia.head()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 37, | |
"text": [ | |
" patient obs week site id treat age sex twstrs\n", | |
"0 1 1 0 1 1 5000U 65 F 32\n", | |
"1 1 2 2 1 1 5000U 65 F 30\n", | |
"2 1 3 4 1 1 5000U 65 F 24\n", | |
"3 1 4 8 1 1 5000U 65 F 37\n", | |
"4 1 5 12 1 1 5000U 65 F 39" | |
] | |
} | |
], | |
"prompt_number": 37 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.figure(figsize=(12,12))\n", | |
"bbp = RPlot(cdystonia, x='age', y='twstrs')\n", | |
"bbp.add(TrellisGrid(['week', 'treat']))\n", | |
"bbp.add(GeomScatter())\n", | |
"bbp.add(GeomPolyFit(degree=2))\n", | |
"_ = bbp.render(gcf())" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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zZs0innX4fTxDuqODqlQLiZbjNDY20tTURDwep7GxkcbGxm7f7/f7qa6uprq6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\nGTNm8MADD6BpGp2dnXzwwQf8+te/5umnn0bXdda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Qb04PG9SXICE+aX2WV+QA5jj5bMaT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\nOZe30gV0DZYkrAHFIg+mG1LOc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5/+lP/4j/8gk8mQTqc5c+ZMvy0iRzLmb7AFS3q7RCSX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\nRK5CYII=\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x107a41850>" | |
] | |
} | |
], | |
"prompt_number": 38 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"We can use the `RPlot` class to represent more than just trellis graphics. It is also useful for displaying multiple variables on the same panel, using combinations of color, size and shapes to do so." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"cdystonia['site'] = cdystonia.site.astype(float)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 39 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.figure(figsize=(6,6))\n", | |
"cp = RPlot(cdystonia, x='age', y='twstrs')\n", | |
"cp.add(GeomPoint(colour=ScaleGradient('site', colour1=(1.0, 1.0, 0.5), colour2=(1.0, 0.0, 0.0)),\n", | |
" size=ScaleSize('week', min_size=10.0, max_size=200.0),\n", | |
" shape=ScaleShape('treat')))\n", | |
"_ = cp.render(gcf())" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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OtW5Bk/1tYzS1KigprUgFJaV1BQKNNgsZI2AvQuBguGtxzcFoXgWWs7hBX8v5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\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x10740f510>" | |
] | |
} | |
], | |
"prompt_number": 40 | |
} | |
], | |
"metadata": {} | |
} | |
] | |
} |
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