OverviewPythonStatistics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ΕΠΙΣΚΟΠΗΣΗ ΣΤΑΤΙΣΤΙΚΗΣ ΜΕ PYTHON"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n",
      "/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py:8: FutureWarning: The pandas.rpy module is deprecated and will be removed in a future version. We refer to external packages like rpy2. \n",
      "See here for a guide on how to port your code to rpy2: http://pandas.pydata.org/pandas-docs/stable/r_interface.html\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from numpy import *\n",
    "import scipy as sp\n",
    "from pandas import *\n",
    "from rpy2.robjects.packages import importr\n",
    "import rpy2.robjects as ro\n",
    "from ggplot import *\n",
    "import pandas.rpy.common as com\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "# pd.options.display.mpl_style = 'default'\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plots(data,var):\n",
    "    fig=plt.figure(figsize=(7,42))\n",
    "\n",
    "    fig.add_subplot(6,1,1)\n",
    "    plt.title('Plot')\n",
    "    data[var].plot()\n",
    "\n",
    "    fig.add_subplot(6,1,2)\n",
    "    plt.title('Bar Plot')\n",
    "    data[var].plot.bar()\n",
    "\n",
    "    fig.add_subplot(6,1,3)\n",
    "    plt.title('Pie Plot')\n",
    "    data[var].plot.pie()\n",
    "\n",
    "    fig.add_subplot(6,1,4)\n",
    "    plt.title('Kernel Density Estimate Plot')\n",
    "    data[var].plot.density()\n",
    "\n",
    "    fig.add_subplot(6,1,5)\n",
    "    plt.title('Histogram')\n",
    "    data[var].plot.hist()\n",
    "    \n",
    "    fig.add_subplot(6,1,6)\n",
    "    plt.title('Box Plot')\n",
    "    data[var].plot.box()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ΠΡΩΤΟ ΠΑΡΑΔΕΙΓΜΑ: Τα δεδομένα mtcars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "RDatasets from https://vincentarelbundock.github.io/Rdatasets/datasets.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([u'Unnamed: 0', u'mpg', u'cyl', u'disp', u'hp', u'drat', u'wt', u'qsec',\n",
      "       u'vs', u'am', u'gear', u'carb'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(32, 12)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtcars = pd.read_csv(\"https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv\")\n",
    "print mtcars.columns\n",
    "mtcars.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mazda RX4</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.620</td>\n",
       "      <td>16.46</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mazda RX4 Wag</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>160.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.875</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Datsun 710</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>108.0</td>\n",
       "      <td>93</td>\n",
       "      <td>3.85</td>\n",
       "      <td>2.320</td>\n",
       "      <td>18.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hornet 4 Drive</td>\n",
       "      <td>21.4</td>\n",
       "      <td>6</td>\n",
       "      <td>258.0</td>\n",
       "      <td>110</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.215</td>\n",
       "      <td>19.44</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hornet Sportabout</td>\n",
       "      <td>18.7</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.440</td>\n",
       "      <td>17.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Valiant</td>\n",
       "      <td>18.1</td>\n",
       "      <td>6</td>\n",
       "      <td>225.0</td>\n",
       "      <td>105</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.460</td>\n",
       "      <td>20.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Duster 360</td>\n",
       "      <td>14.3</td>\n",
       "      <td>8</td>\n",
       "      <td>360.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.570</td>\n",
       "      <td>15.84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Merc 240D</td>\n",
       "      <td>24.4</td>\n",
       "      <td>4</td>\n",
       "      <td>146.7</td>\n",
       "      <td>62</td>\n",
       "      <td>3.69</td>\n",
       "      <td>3.190</td>\n",
       "      <td>20.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Merc 230</td>\n",
       "      <td>22.8</td>\n",
       "      <td>4</td>\n",
       "      <td>140.8</td>\n",
       "      <td>95</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.150</td>\n",
       "      <td>22.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Merc 280</td>\n",
       "      <td>19.2</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Merc 280C</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6</td>\n",
       "      <td>167.6</td>\n",
       "      <td>123</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Merc 450SE</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>4.070</td>\n",
       "      <td>17.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Merc 450SL</td>\n",
       "      <td>17.3</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.730</td>\n",
       "      <td>17.60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Merc 450SLC</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>275.8</td>\n",
       "      <td>180</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.780</td>\n",
       "      <td>18.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cadillac Fleetwood</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>472.0</td>\n",
       "      <td>205</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.250</td>\n",
       "      <td>17.98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lincoln Continental</td>\n",
       "      <td>10.4</td>\n",
       "      <td>8</td>\n",
       "      <td>460.0</td>\n",
       "      <td>215</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.424</td>\n",
       "      <td>17.82</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Chrysler Imperial</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>440.0</td>\n",
       "      <td>230</td>\n",
       "      <td>3.23</td>\n",
       "      <td>5.345</td>\n",
       "      <td>17.42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fiat 128</td>\n",
       "      <td>32.4</td>\n",
       "      <td>4</td>\n",
       "      <td>78.7</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>2.200</td>\n",
       "      <td>19.47</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Honda Civic</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>75.7</td>\n",
       "      <td>52</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1.615</td>\n",
       "      <td>18.52</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Toyota Corolla</td>\n",
       "      <td>33.9</td>\n",
       "      <td>4</td>\n",
       "      <td>71.1</td>\n",
       "      <td>65</td>\n",
       "      <td>4.22</td>\n",
       "      <td>1.835</td>\n",
       "      <td>19.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Toyota Corona</td>\n",
       "      <td>21.5</td>\n",
       "      <td>4</td>\n",
       "      <td>120.1</td>\n",
       "      <td>97</td>\n",
       "      <td>3.70</td>\n",
       "      <td>2.465</td>\n",
       "      <td>20.01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Dodge Challenger</td>\n",
       "      <td>15.5</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>2.76</td>\n",
       "      <td>3.520</td>\n",
       "      <td>16.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>AMC Javelin</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3.15</td>\n",
       "      <td>3.435</td>\n",
       "      <td>17.30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Camaro Z28</td>\n",
       "      <td>13.3</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>245</td>\n",
       "      <td>3.73</td>\n",
       "      <td>3.840</td>\n",
       "      <td>15.41</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pontiac Firebird</td>\n",
       "      <td>19.2</td>\n",
       "      <td>8</td>\n",
       "      <td>400.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.845</td>\n",
       "      <td>17.05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Fiat X1-9</td>\n",
       "      <td>27.3</td>\n",
       "      <td>4</td>\n",
       "      <td>79.0</td>\n",
       "      <td>66</td>\n",
       "      <td>4.08</td>\n",
       "      <td>1.935</td>\n",
       "      <td>18.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Porsche 914-2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>120.3</td>\n",
       "      <td>91</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.140</td>\n",
       "      <td>16.70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Lotus Europa</td>\n",
       "      <td>30.4</td>\n",
       "      <td>4</td>\n",
       "      <td>95.1</td>\n",
       "      <td>113</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1.513</td>\n",
       "      <td>16.90</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ford Pantera L</td>\n",
       "      <td>15.8</td>\n",
       "      <td>8</td>\n",
       "      <td>351.0</td>\n",
       "      <td>264</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.170</td>\n",
       "      <td>14.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Ferrari Dino</td>\n",
       "      <td>19.7</td>\n",
       "      <td>6</td>\n",
       "      <td>145.0</td>\n",
       "      <td>175</td>\n",
       "      <td>3.62</td>\n",
       "      <td>2.770</td>\n",
       "      <td>15.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Maserati Bora</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>301.0</td>\n",
       "      <td>335</td>\n",
       "      <td>3.54</td>\n",
       "      <td>3.570</td>\n",
       "      <td>14.60</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Volvo 142E</td>\n",
       "      <td>21.4</td>\n",
       "      <td>4</td>\n",
       "      <td>121.0</td>\n",
       "      <td>109</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.780</td>\n",
       "      <td>18.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Unnamed: 0   mpg  cyl   disp   hp  drat     wt   qsec  vs  am  \\\n",
       "0             Mazda RX4  21.0    6  160.0  110  3.90  2.620  16.46   0   1   \n",
       "1         Mazda RX4 Wag  21.0    6  160.0  110  3.90  2.875  17.02   0   1   \n",
       "2            Datsun 710  22.8    4  108.0   93  3.85  2.320  18.61   1   1   \n",
       "3        Hornet 4 Drive  21.4    6  258.0  110  3.08  3.215  19.44   1   0   \n",
       "4     Hornet Sportabout  18.7    8  360.0  175  3.15  3.440  17.02   0   0   \n",
       "5               Valiant  18.1    6  225.0  105  2.76  3.460  20.22   1   0   \n",
       "6            Duster 360  14.3    8  360.0  245  3.21  3.570  15.84   0   0   \n",
       "7             Merc 240D  24.4    4  146.7   62  3.69  3.190  20.00   1   0   \n",
       "8              Merc 230  22.8    4  140.8   95  3.92  3.150  22.90   1   0   \n",
       "9              Merc 280  19.2    6  167.6  123  3.92  3.440  18.30   1   0   \n",
       "10            Merc 280C  17.8    6  167.6  123  3.92  3.440  18.90   1   0   \n",
       "11           Merc 450SE  16.4    8  275.8  180  3.07  4.070  17.40   0   0   \n",
       "12           Merc 450SL  17.3    8  275.8  180  3.07  3.730  17.60   0   0   \n",
       "13          Merc 450SLC  15.2    8  275.8  180  3.07  3.780  18.00   0   0   \n",
       "14   Cadillac Fleetwood  10.4    8  472.0  205  2.93  5.250  17.98   0   0   \n",
       "15  Lincoln Continental  10.4    8  460.0  215  3.00  5.424  17.82   0   0   \n",
       "16    Chrysler Imperial  14.7    8  440.0  230  3.23  5.345  17.42   0   0   \n",
       "17             Fiat 128  32.4    4   78.7   66  4.08  2.200  19.47   1   1   \n",
       "18          Honda Civic  30.4    4   75.7   52  4.93  1.615  18.52   1   1   \n",
       "19       Toyota Corolla  33.9    4   71.1   65  4.22  1.835  19.90   1   1   \n",
       "20        Toyota Corona  21.5    4  120.1   97  3.70  2.465  20.01   1   0   \n",
       "21     Dodge Challenger  15.5    8  318.0  150  2.76  3.520  16.87   0   0   \n",
       "22          AMC Javelin  15.2    8  304.0  150  3.15  3.435  17.30   0   0   \n",
       "23           Camaro Z28  13.3    8  350.0  245  3.73  3.840  15.41   0   0   \n",
       "24     Pontiac Firebird  19.2    8  400.0  175  3.08  3.845  17.05   0   0   \n",
       "25            Fiat X1-9  27.3    4   79.0   66  4.08  1.935  18.90   1   1   \n",
       "26        Porsche 914-2  26.0    4  120.3   91  4.43  2.140  16.70   0   1   \n",
       "27         Lotus Europa  30.4    4   95.1  113  3.77  1.513  16.90   1   1   \n",
       "28       Ford Pantera L  15.8    8  351.0  264  4.22  3.170  14.50   0   1   \n",
       "29         Ferrari Dino  19.7    6  145.0  175  3.62  2.770  15.50   0   1   \n",
       "30        Maserati Bora  15.0    8  301.0  335  3.54  3.570  14.60   0   1   \n",
       "31           Volvo 142E  21.4    4  121.0  109  4.11  2.780  18.60   1   1   \n",
       "\n",
       "    gear  carb  \n",
       "0      4     4  \n",
       "1      4     4  \n",
       "2      4     1  \n",
       "3      3     1  \n",
       "4      3     2  \n",
       "5      3     1  \n",
       "6      3     4  \n",
       "7      4     2  \n",
       "8      4     2  \n",
       "9      4     4  \n",
       "10     4     4  \n",
       "11     3     3  \n",
       "12     3     3  \n",
       "13     3     3  \n",
       "14     3     4  \n",
       "15     3     4  \n",
       "16     3     4  \n",
       "17     4     1  \n",
       "18     4     2  \n",
       "19     4     1  \n",
       "20     3     1  \n",
       "21     3     2  \n",
       "22     3     2  \n",
       "23     3     4  \n",
       "24     3     2  \n",
       "25     4     1  \n",
       "26     5     2  \n",
       "27     5     2  \n",
       "28     5     4  \n",
       "29     5     6  \n",
       "30     5     8  \n",
       "31     4     2  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtcars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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jR48yMTHB6Ogof/Inf0IsFiOVSs38v7XV/vJpb28nHo/PHJ9IJGhvb59z3r6+Pvr6+mZ+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ciyLNXV1cldWirr8GHp4EHp8GHZ/vMf2T/5RPbCQoX85z+yHz3a4mXbjhxR/87xrVJnJ3Xx1YMq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\nHCbTJUp8PyTmIyfPb0VQ7Cujk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URR5OJFKC+Xt5AdoaBAybPPBhEW1o5Zs/4gISGZ2bNH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XHVQ7qeTy7e5kZxf94aO4Y0HwoBj90qW/M3Kkj80VozeXV4bc57mhp/jz7o/MP/4FyVnmSYSj\nlJT8+vKvNA9ubpb2HhViZvuIs69WjYzPP7f2MCzqxkcfsfngQTpmZBQbaD928mbjWW/iu1w0Gmg9\n3nTCY8UZLl97rpBAq0aj2cqrr04qNtBKksQ33xxj2DAvswdaMOBeO6rMgTZAF4AqvmCB9tIKTCt5\nqsiSMAAvaa7hOycg/xPZEN0BKvuuJd+N3UKYMsONjY2lV6/qzJnzL+3aVdydykVZs8KZnk+2YP9H\nk1n71EG+CF+En86vzO2ObTq2TLPa2NhY2rZtS926dQkNDWX+/PkAREZG0qJFCxo0aECPHj1IrmBZ\n8kSwfcQpFArsWrZE/8QT1h6K2emrVuXYiROM7taNF65d42YRWYw0wEHHqnRfrOf6kCvI6YUv6Pgv\nc0I5YjtXrg1GlvO/yUqSI2r1VgYMGMPJkyeLHd+GDb8xaVIQCQnm/2/21ph7rL+woszthHmHoTr7\njxlG9IDvuXMEWLhe6fH0dPY3zcalm0u+x/XX9dx804sA36KPXoFpATc9PZ3u3evx8ss/8+qrlv0Q\nYU1//K6mV3gYs/sPZ1aN/ax+ZgNhXqULlo4qR/rU6YO9yr7U41EqlcyZM4fTp0/z+++/s3jxYs6e\nPcuwYcP47LPPiIyM5LnnnuOzzwovu2irRLB9DKh9fcn8+ONHYI/lAwbg2qJFfLtrF+3v32f93Ydn\nn/k1cXAgMjsEu5diubPS+Mw3eL8jaU3nEJ/wUYHnJMkVSfqOvn1f47wJRdbnzfuWTZsa8vffllmC\nbNvnFNvOby1zO03dQrH7918zjOgB/xUr6GTB+7Y5Xk+6jt0ED+zc8s9ik3anot/yJB7uw4ttw5SA\nC7ZfjN5crl6146XuNRnRrjcD7bbzXeed9Kz+HIoijlY9bMpTU2jgX7YdyD4+PjRs2BAAnU5HrVq1\nuHbtGufPn6dly5YAtG/fvthNibZGBNvHgEKhQNWsGVkvvmjtoZSZPjSUP0+dYnjz5rxy7Rr3iklJ\n+ZmTD+tOeBDX9RKZ5ws/3iK5SlSLtCfB8U3uJH5bwK9KNgAAIABJREFU4Hml0htZ/pYXXhjClSuF\nl3jL64033iE+vjvff1/6T/dFebpVJr/d/g+yGT4+NXaohnSt5PmUjVHu2cPT9pb5uh/W1RCDz5cF\na77Gv5eELm4ojo7F3zM0NeBOnTqav/9+kzVr7qLRPLoBFyA1VWLU8AB6P/EMQX+tYEvnnxnVaDT2\ndkX/u3o6eNK1elfs7My36So6OpoTJ07QvHlz6taty/btD2o1b9q0idjYWLP1Ux5EsH1MqFxc0I8c\niay2flaZ0jAA0evWsey772h3+zb/uV904nytJPGbtiod52Vy/bWryBmFv0Ha17In+EgWMUm9SU0t\neA9WqQwgM3MFzz/fnzgTNv60adOeunXfY+ZMyx15GPPRKRafWGiWtgIkVxQ3b5qlLXjwhhJopmLy\nxYnV61kekoL7cI8Cz0U/k4yPZg5KpVex7ZgacCtSMXrzkJg/x43nnmjNv1/NZEP4r3zy9Cw8HAp+\nvwG+aP8FdXzrmK335ORkIiIimDdvHjqdjhUrVrBo0SKaNm1KSkoK6gr2XiaC7WPEvnFjMqZMsfYw\nSiyjVSsOnz3LgBo1GBEXR6qRurA5WjpoOZERjPxiLIlfF16bFsDpOS1+O65xOb4HWVkFZ3dqdQip\nqYvo1eslbhez8QqgcuXKjBixnpEjnSkqq1FZ+PoaiFX8SUpWwVJ/peGYpkdh5gMJvgkJuJhxdlOU\nz5JvkjTYGVVgwfvE0W30VPZeg0JR/D1kUwNuZOQJhg4NZc2aK9Svb95KR7Zs104Nzz3dlNVvjGZR\ng19Y1mENNSr9Lzd1y4CWtKnaxmyVffR6PREREfTv358ePXoAULNmTXbv3s3Ro0d58cUXCQkJMUtf\n5UUEWxsxZMgQvL29qV8//1nBBQsWULt2bUJDQ5kwYUKZ+rBTqyEiAkNAQPEX2wCDUsmF7dtZsGQJ\n7RMS+NWE3YfznfxYfsyd610vkXnZeFYk74+ccJn5O5dj+2AwFAxcGk09EhNn8fzzL3HPSPm9vLRa\nLYsXH2LIkEro9ZarIvPJwkvMOjbDbO05lKFovDFB69bR2gJ5ko3pnB6N11eBBd7Nsm9nEzfIjUBf\n06oZmRpwb968Sffu1Zk69SQ9elSMYvTm8s8/Svp0qsvbXV9mXKVdrO+0jQ5VOjCt1TR8XHzM1s/g\nwYOpU6cOo0aNyn3s5n9XYAwGA9OmTeO114r+d7I1ItjaiEGDBrF79+58j/3yyy/s2LGDqKgooqKi\nGD9+fJn7sa9Rg/QFC8rcjqWl9ujBL6dPE+Hlxdvx8WQWM/tyliSOOITw9Kw04t68ipxl/PqgzTrk\n59YSGzeaBwvU+Wk0TUlImELv3i+ZfLxgw4ajvPmmD/fvW+6/lFJpwM7vJFeTzHdmWm2mhBZ5ab7/\nnk7a8sscdN9gYJLnbbwnFXyzTz2cRtqqBnh5mpa61NSAq9fr6dWrMZ06/YexY22niHt5uXtXYvjL\nwbzU4lne8l5D06CmZpvVHj58mHXr1rF//37CwsJo1KgRu3btYv369dSsWZM6derg7+/PwIEDzdJf\neRFJLWxITEwM3bp1yz1W0qdPH4YPH07btm3N2k/mrVsohg5FtW2bWds1B4NWy7kdO9jg68u0hARM\nKX7WzsGRL+/6cGPYFbKuFnEmUg1Vf9VyS/kh9+/vLPQSB4dwrlwZxssvDyLTxHzBa9bsZdWq1vzy\ni2WPvEydmcDPXn04cPWAWdpTSkpuuc3G5a1RxV9cQj+eOkUXM94LNsV/dFVwfzWBtL8LHtOp/IOO\nOwHvkpS836S2TEl8kWPcuA+oXHkMo0c7YzBUzNq4peXvb2Dv3gxq1zZvGtJHkZjZ2rBz585x8OBB\nmjdvTps2bTh27FjxLzKByt2drAkTbG6z1P3Bg9lz4gTdNBo+NDHQfuXkz6Lf3bj27MUiA63SV0m1\nE3ZcN7xiNNBqtV25cGEg/fq9YnKg/eijBRw82NLigRagfttTZgu0AKEeoaguR5utvbz879/H3kwz\nHVP1SI7G9XM/FPYF+415Lhkvu+moVP4mtWXqDBdg9uwP2bnzZb799g463eM1d1m4MJ1atSyTD/tR\nI4KtDdPr9SQmJvLHH3/w2Wef8cILL5ilXYVCgX2TJqTPKlsCe3MxuLkRdfgwU8eMocu1a1wwIdC5\nShLHHEJoNj2FuDGxGC3pAzg8qSHo4H0u3+pBenrhCRwcHftw6lQPBgwYjL6I5Bh59e07EKXyFVas\nsPybTa+IVHZd/86sbdb3qI+yjEXjjQn6z39oXI5LyfDgR2Cg9jo+nxceUC+HZxLkuRqFwrR/r5IE\n3EehGH1JvfhiJq1aqcy2fPyoE8HWhgUGBtKrVy8AmjZtiiRJJu2KNYWdUokUEUFWly5maa+0br/9\nNjuOHKGzLDP31i2TTo521TpxNKUKab1iuPdD0Qkt3F/X4bXm3/+mXiw8Z65ON5ijR59i6NDhGIrZ\n6ZwjLKwRnTrN4b33ymcj0IAxUaw+tcqsbT7pXBe76GiztpnDedUqujsZL+xuKX+kp/FbC3DqVDCx\nhuG+gdgXHAnyW25yeyUJuI9KMXpTODsbGD9eT6VKll/ReVSIYGtDZFkm7y30nj17sn//g3tM586d\nIysrC3d3d7P1p/b1JWvaNAxmbNNU2f7+/H3sGO++/DI9r13jWpZpb06rnAL4/KAzsd0uob9e9AzU\n/0sn1G/tJObaQGS58NmyTvcWBw7U5I03RmLq9gVPT0+mTt3Jq6+6YqkjPnnVrKnnbPpBMrPNu3O4\nrn2gWRNa5CVdv05NK20HGXw/FvX7XkjOBd/eMiIzSP6iJj5ek01uryQB93/F6P98BIrRGyOzcmU6\nYWFi+bgkRLC1Ef369aNFixacO3eOoKAgVq1axeDBg7l06RKhoaH069ePtWvXmrVPhUKBQ8OGpK9c\nWa6pHOM//ZTvfv6ZDqmprLhj/BxsXu52dvxtH0L9D+4T//Y1iruhG/yTjrQn5xGX8IHRa5ycJrJr\nlwfjx79r8tiVSiWrV//J0KGeZGSUz/LZR/POMfuY+fPAuuvVKCyYzN0/NbUcPooUrod0Bd/FBbNL\nAdxenIzqeA9cXLqb3F5JAi5A374tH6li9HmNGpVJhw4qJEmEj5IQu5EF9ElJZE+fjv2nn1q2nxo1\nOP7998zKzub7YvIZ59XL0ZlPEzyIH3IF/Y2iZ7OSs0TVgyriMseRkvK70eucnD5my5ZUZsyYafI4\nADZvPsaHHzbg5MnyKbum0xmYt2c9Q/YUXRy9NKIbbaRy9z5mbzdH3OLFtAsL42y6dWZ4U528eG5R\nNndWFX7rJeSIlqv6l8jMvGBymyXZpQwwbNgomjadyhtvuJCVVfHvbdatm80PP2RRvbqY1ZaU+Ggi\noHRyQh42DH2DsiUQN8YAXF22jK937KB9YmKJAu23ukCm7dUR2+NSsYFWXV1N8FE9Mcm9iwm0s/n6\n65slDrSLFn3P11/XK7dACzB9zjXm/22ZjWz2qZZNyOC5bBndyqEogTFTk26QPtwVlX/h9xUvtk4l\nyH0ZkmT6ffeSznCXLZv3yBSjt7eX+eqrDKpVK5/c148aEWwFAOyrViVz0SJkB/Oel8tq1Ig/Tp9m\naFgYg69fJ8nEDUjeSiWR6mrUeO8uCe9fLyz3RD5OzzrivzPeaOrFHDrdIpYsOcu8efNL8mUwduwU\nLl7szNat5flGY8CvwSkib0ZapHX7ZMuWjVP+/Tdh5ZS20ZhOGZfx/jKw8Fvr6XClm5rKfqsoyb33\nkgbcQ4cOMmpUI9avv061ahU3xeOCBek8+aRG7D4uJRFsBeDB/VtN8+Zmyy5lkCQub9rEV99+S/ub\nN9mTlGTya/s5uvLr7SDudb9M0t7iX+c1RYfL50e4HNsbg8H4PUidbgVffPEby5aZvhsVoFOnZ6lS\nZSxz5pTvUZZXRySx6dJqi7TtrnFHedu0++VlEWilJeQciQYDH3nfwevdwlMJZp7PJPGDyvj5lCwF\nZkkDbkUvRt+nTyY9ethhZydCRmmJ75yQS7Kzw65bNzL79i1TO+nt2vHrmTP0rVKFkXFxpJVgW8B3\nTkFM2unAtecukX27+POKgZt08MK3xMa9RVHTX53uG2bO/D/WrVtn8lgAQkJCGDhwNaNHl/9yaJcB\nUWw+971F2g7zDkP1b/F1ecvK7/x5/C1cTL44X6feJfZ5DZp6hd9nvPttCooDHXBzLVkJypIG3Jxi\n9P37/1KhitH7+RmYNCkbLy/bSoJT0YhgK+Sj9vIi+733MPiblmknL4NazbmdO/li4UI6xMdzJMX0\nyjT+SiVRqhCqjL9DwtS44jdwKiHkdy33Qj7kxs25RV7q6LiJSZO+ZsuWH0weDzwoXD1v3kGGDq1U\n7mn4nmieyZHEXRhky9zna1ipHnZnLJPQIi//lSvpaIXztg/rlhxNpbn+KFSF/zteey0Jt+SxaDT1\nStRuSQMuwMCBHfHzW8rMmbZfjF6SZFatSqduXbEhqqxEsBUK0NStS/qKFcgluN+W3Ls3+0+dopeb\nGxPj48kqwWx2sM6NX24EktgtmuRfij+KovRWUi1SyTUGcf/+/xV5rVb7A+PHLyxQ5MEUGzb8xWuv\neZOcXP73qN6ZcYaFf5fsvnJJNNfWxO6q+QoaGKPcvZvWGuu/UWcCw3Rx+Hxq/EPkpTYpBLgsxs7O\npURtlybgTp06mhMnbL8Y/dy56bRqZS/u05qBCLZCAQqFAvs2bUj/8stiJ5gGJyfO/PILM6dO5Zlr\n1zhdwnt025wqM26bPbHPXyY7sfhlY4dmGoJ+TeLy7Z6kpxc1M1Pi4LCdN9+cwcGDB0s0JoB16w4w\nY0YwsbHlv8HHy8tAvPIoSZmm3+cuqapKLxTx8RZrP4dkMJRbMfniHExP5VgrBbq2RmbaeojuqKCy\n7xpK+tZYmoCbU4x+0ybbLEY/YkQG/frZodFYd5Pbo0IEW6FQdmo1yogIMidONHrN3ddf58e//qKr\nSsWMGzeK2zCcT2W1mlN2IfiOvMWNaaa96bsN1eH1zQUuX+9JdnZRaSvtsbffyrBh73P06NESjOqB\nTz5Zyu7dzfjtN+vca5y54DKf/1WyY0klpcuQUWSXTw5f35s3cbaRBAgvJ13FYaoXklPh49HH6rk5\n2o8A3zklbrs0ATcy8gRDhtheMfrWrfWMHy/j4SHu05qLbfwPEGySys0NRowgs0/+xAcGT08ijxxh\n8ogRPHvtGtEmVsjJ8brOnb2xftx+9jIpv5l2X9dvoRMOY3cTc62/0dSLAJKkQ63+gQEDRhMVFVWi\ncQG88spwMjL6snatdZY+JcmAQ+UoLt+7bNF+LFE03pigDRt4uhyLyRenlzIW34WFZ5cCSPpPCvrt\nLfGoNLTEbZcm4NpaMfqgoGzmz8+kShVxntacRLAVimQfEED2Rx+hb9IEgFuTJ7P18GE6ZWay8Nat\nErUlATt1VXjjOyXX+kRjuG/aXLjKbh3pTy/kesKkotuX3FAoNtG372tcuGB6VqAcTzzxJK1azeSD\nDxxL/FpzmTDlDivPLrJ4P/YWKBpvjMP69XRxtN739GHnMjL4vm4Gbi9VMnpN/DtJ6G4OR6ttVuL2\nSxNwbaUYvbOzgW+/zSA01EHcpzUzka5RKJYsy6RGRvIPsECSWGNiPuO8qqvVbNMHkTT+OqlHTXsz\nkXQSwb+qic8aT0rK4SKvVSq9yc5eSZ8+g0lISCjx+Hx9fVm8+AR9+niSmWm9N5ktR36m149tLd5P\novciXF9/w+L95Nh5+jRdb9wot/5McUwTQlrPGPQJRpZvJagWqSb6bg/0+pJ9sISSp3bMYa1i9CqV\nzPbtaXTsqBF5jy1AfEeFYikUChzq1yfN15cfSpBqMccYnQc7Y/y4+ewlkwOtOkRN1b+yuZLSp9hA\nq1IFkpGxnOefH1CqQKtWq1mx4g+GDPGwaqDt2jWdffFbLN5PDbcaqGItU+3HGP9791Db2Eypsz4G\n7yVBxi8wQHQ7A0E+a1EoSn7/vjQzXHhQjH7XrgHlXIxeZtWqNNq3txeB1kLEd1UwiSRJtPD0ZFP1\n6tib+KapBPboqjBknURsv2gMSaYtGzt11uK/K4FL8T3IyrpS5LVqdXWSkxfSq9dLpa71u3Hjn4wZ\n48edO9b97zBsYhTLTy6zeD8NPBugOnPW4v3kFbR7N43KuZh8cW7q9czyT8RznJfRa/Q39MQPrUSA\n78JS9VHagLtz5/ZyLUb/+ecZ9OypRqks/c7j2NhY2rZtS926dQkNDWX+/AdH1/7880+aNWtGWFgY\nzZo149ixY+YadoUigq1gMkmSaO/lxYaQEIpLxV/L3p4oRQjOwxK4+YXpy4de7zvh+sVf/029WPTR\nF3v7UBITPyUi4iXu379vch95LVu2gyVLavPvv+VXXKAwISF6zmceIiPb8htknnCth3Te8tmj8nJe\nuZLuNrRJKsey5ERu9HFEU9P4hrjUA2lkrG2Ml8eoUvVR2oCbU4x+6VLLFqOfNCmdV16xw9GxbP8H\nlEolc+bM4fTp0/z+++8sXryYs2fP8u677zJt2jT+/vtvPvzwQ95++20zjbxiEcFWKBE7Ozu6+viw\ntmpVo6nb33PyYvsFH250vUzaCdPT0gWud4K+67l6fQTFFazVaJ4gIWESERH9SC5lTdaJE2cSGdmO\nXbusf7xh2vwLfH7MsiUOczTUBCPFxpZLXznsrl6llo0tI+foknIZ9wX+FPUJ8sb0JBwuv4xOF16q\nPkobcO/fv0/XrpYrRv/+++mMGiXh4VH2Y24+Pj40bNgQeJB9rVatWly/fh1fX1/u/vf20927d/Ev\nRXa6R4HYICWUSnpWFuuvX2fw5f8dUVECexyD8VidxO3FJdhQooSqB7Xc1szg3r1txV7u4NCGmJgh\n9O8/mMwSHjvK0a1bL9q0WcXYsdYrAZdDozHw5f6NDNrTr1z6i2q1hbpte5V7Yfejx47xRFKSTZZS\n76jVMe+AC/HvFH0vO+SEPVeSexdZWaoopd00BfD556u4fz+Cjz5ypCRViox5//0MRo1S4Olp/g+b\n0dHRhIeHc+rUKe7cucNTTz2FQqFAlmV+++03AgONH716VImZrVAqGpWKF3x9WVq5MgD17e05JYfg\nMCiuRIFW6amkWqSK64qhJgVarfZZzp8fQL9+r5Q60NaqVYu+fZcxfrz1c/YCTPs8joWRs8utP21q\nVrkHWgD/v/6ihr1tnt3ck5pMVFs7HFsWfUTpcngWQV6rUChK93WUdoYLMH78IOLiJrF06T1UqrJ9\nZJk40XKBNjk5mYiICObNm4dOp2PIkCEsWLCAK1euMHfuXAYPHmz2PisCMbMVyiQlM5Oj0TfwP5zJ\n9TeuIqeZ/uOkaaTBf8M9YhJeNulohVb7IlFR4bz66ggMJtbFfZirqytff32GPn18SE21hWVNme+O\n7KH3j53Krcfrdb7G94X+5dZfDn3jxkxYs4bZN2+We9+mOi2FcKvLZQwpxn++NI00eG84R8y1V0rd\nT1lmuC1btmLMmO8ZPNide/dKPl+aODGD0aMVFqnio9frefbZZ+ncuTOjRj24x+3s7JxvT4WLiwv3\n7t0ze9+2TsxsH2FDhgzB29ub+vXr5z724osv0qhRIxo1akRwcDCNGjUqUx+OajVP+nmikiXkdNMD\nrdsgR3w2XuLSddPOMOp0Qzl69EmGDn2t1IFWkiTWrTvK8OFeNhJoYeCQJLbGfFOufarLMaFFXsq/\n/qKJ0rob0YrzgvoaPvMDirwm/Xg6KQvr4OP1Xqn7KcsMtyzF6N9913KBFmDw4MHUqVMnN9ACVK9e\nnQMHDgCwb98+atSoYZG+bZ2Y2T7CDh06hE6nY8CAAZw8ebLA8+PHj8fV1ZVJk4rOzGSKrLQs4jbH\ncWngpeL2NuH3hRM8s5fr8cbzLufl5DSKn3/24+233y3TGDdu/I3PP2/C0aPWra+a19bff+P5Pa3I\nlssnT7FWqSXO8WOcx4wrl/4e9uuJE7RKTLRK36aa6+xL+Mw07n5f9JnywA1O3Kv+Affv/6fUfZVl\nhqvRaNi06Rjz5tVg377if6bfeSeDceMsF2gPHz5Mq1atCA0NRaFQoFAomDFjBp6enowYMYLMzEw0\nGg2LFy8mLCzMImOwZbb9MVMok5YtWxITE2P0+U2bNvHzzz+bpS+VgwrfF3xROCi41O8Scmbhn+Gq\n7NKR5Pslt+NXmNSuTvceO3eqmTKlbIF2zpy1/PBDmE0F2kaN9By//1O5BVqA+l71UUVeLLf+HuZ/\n6RK+np7E6W0n6f7DxtyP4/jYEJS/JKO/ZXycV19MIuToZNLVZ8nMvFSqvh7McOcAr5U44OYUo1+9\nejchIU+zdKmD0WvffTeDsWMtF2gBnnrqKbKNFLc4cuSIxfqtKMQy8mPq119/xcfHh5CQELO1qVKr\n8OvhR/Wt1ZF0+X+0JK1EyHENt9zHc/uOaYHWyWk6mzfrmTJlapnGNXz4WG7f7sWGDdavq5rXxM/O\nMO94yavLlEVD9wbYnbZ80XhjAlaupIMNFJMvTpfsGHy+Kn7H7OXWGQR5LEeSSp/7uSxLygADBz5T\nRDF6mdmz0xk/XrJooBWKJ4LtY2r9+vX07dvX7O3aKe3wecaHGv9XA6Xng4UTdbCaqscNXE3rS3Ly\nAZPacXKaw9q1cXzyyWdlGs/TT4cTFjaZ6dNtK3tRpUoGbtsf415G+W4UaaGrjd2VorNyWZJy507C\nbaCYfHHi9XrmV0nCY6RnkdcZUg1c7aEhyG9lmfora8AtrBi9SiXzzTdpDB+uNMs5WqFsRLB9DGVn\nZ7Nlyxb6PFQ6z1wkScK7lTc1/1MT92GuBOy5yaWE7mRmRpv0ep3uS5YsOc38+aVLkZcjICCA0aO/\n4803XTDHuURz+nRBDHOOl08Si7xq2PsjXb9e7v3mkAwGArMslw3JnBYk3eLOyzrUIUXPCDP+yeDu\nx8H4eU8rU39lDbg5xeg3brxBcHA2W7em8cIL9mXODCWYhwi2jzhZlnl4D9zevXupXbs2fn5+FutX\noVDg0cQD348duHX/y2JTL+bQ6VYyd+5Bli0zbanZGI1Gw5IlvzF4cCX0etsKtAqFAV1IFOcSz5V7\n3y6ZChTp1tmNnMPv5k2cKkiy+85pMXguCoRiUgbfXZuC4rdOuLr2LlN/ZQ24kZEnmDLlGb777gad\nOmlQqUqf61gwr4rxEy+USr9+/WjRogXnzp0jKCiIVatWAbBx40aysrIKHAs6evSoWROGKxQK3L1q\nEBLyJZ6erxd7vU63junTt/Ptt+vL1C/Axo3HGDXKt1TnEC1t3IREvj63xCp9a1OtP6sM2rSJljaY\nJ7kwqQYDYyvdwPvD4j+YXhuaRKXU8Wg0dcrUZ1kCbrNmzVi9ejWNGvmI6j02Rhz9eUwVdiyoTZs2\nTJw4kY4dO/Ljjz/y2WefmW23cmrqLeLj13Plymig4DlZR8fvmDRpGXv27ClzX6tX7+abb9rw00+2\neZ/qhyO/8NyPbazSd0KN1Xj1G2iVvnMYnJ1Z/OefvBUXZ9VxlMRWp8r4vXGLlCMpRV+ohpBIics3\numEwlK44Ro6SHgt65ZVXeP/996lWrZoo/G6DxEefx1TLli1xc3PL95ivr29uZhdzJwzXaj0IDBxG\n9erbkKS8+YgltNofGDt2nlkC7QcfzOX335+22UDbvkMGB25st1r/qmTTC0NYinT/PsFGjojYql5J\nMTh96oPCoZgglglXn1FS2W8NZX17NXWGK0kSc+bM4bPPPqN69eoi0NooEWyFXJ988gljx44lKCiI\nd955h5kzZ5q1fZVKg69vF2rV2oNGUx9Q4uCwlTfemM6hQ4fK3H7v3i+h1Q5hyRLj5w2t7Y3JUSyJ\nLHkCA3Pw0/mhTDC93KEl+ScloapAQcEA9FXH4vtF0dmlADKvZHLrbT8CfGeVud/iAq6rqyvbt2/n\n9ddfx8vLeF1ewfpEsBVylUfCcEmS8PRsRq1a3+HouIshQyaapZh0/foN6NZtARMm2O69wMDAbC5n\n/06a3jqzyzDvMNRn/7VK3w8L3LOHhg62+6GoMCcyMvipcTYuPV2LvTZpayrZP7amUqWBZe7XWMBt\n3Lgxe/bsoXPnzmgqwHGqx50ItkKuI0eO0LNnTwAiIiL4888/LdKPQqHA1bUGwcENGDduXJnfKNzd\n3Zk2bTevvuqKLNvubGnmwot8/tcnVuu/iVt97P61jWDrsnIlPSpAcouHvZF0Heltd+zcit/lGzcm\nCZfbI3BwKFv+cSgYcMeNG8fGjRtp0qSJ2AhVQYh/pcfYw8eCyjthuIeHBwMGDGDPnj1Ur169VG1I\nksTXXx9l6FBP0tNtN9Cq1QYMXpFcT7beGdcmmpByLxpvjDI6mtoVaBk5r2cNMfh8aVo91svtU/DX\nzcfOzr3M/T4IuPX46ac9TJkyhZCQEHF/tgIRwfYxVdixoKVLl/LOO+/g7u5O586duXv3f4nYT548\nSYsWLWjQoAE9evQgOTnZLOOws7OjZcuW7Nixg5EjR5b49Rs3/sHEiYHcuGHbP8pTP0lgcVT5pmZ8\nWJBdJRQ3bOOeLUBAaqq1h1AqsXo9y0NScH/No/iLDRDdXqay7xrKmopep2tFUFAz2rRph7Ozc/Ev\nEGyKOPojFFDYsaBmzZoxZ84cWrZsyerVq7l06RIfffSRWfu9d+8e+/fvZ8iQISSaUBlmwYKN/Pxz\nD7Zssc2C5Hl9f2QvET92tOoYzjfbRLUuL1h1DHnFLl9O2zp1OJ+RYe2hlMphbVXkF66SFVP82WXH\ntg5U+vJvrl4v/rx5QXb4+0/Dx6cfOl1gmWezsbGxDBgwgISEBCRJ4tVXX+Wtt97ixRdf5Ny5B4lW\nEhMTcXNz4/jx42XqS/gf254OCFZR2LGg8+fP07JlSwDat2/P5s2bzd6vi4sLPXv2ZN++fURERBR5\n7ciR73HlyrMVItD265/MjitlT9RRVg42kND9JtS5AAAgAElEQVQiL+9ly+haAe/b5uiUHo3X4kCT\n3kVT9qeRsaEJnu5vlqgPjaYWtWrtpUqV0Tg5BZll2VipVDJnzhxOnz7N77//zsKFC/nnn3/YsGED\nx48f5/jx4zz//PP06tWrzH0J/yOCrWCSunXrsn37g/OhmzZtItZC9/4UCgVhYWEsWrSINWvW4FTI\nm3G7ds9Qs+Y7zJpVMXazvvB6FOvOfm3tYWBvpaLxxtgdOUIzlW2ehzZFksHARM/beE/2Men6Gx8k\n4xg7EEfHliZcLeHnN4XatXfg7R2OSmW+3cY+Pj40bNgQAJ1OR+3atbl27Vq+azZt2mSRQiWPMxFs\nBZOsXLmSRYsW0bRpU1JSUlCrLVuuy8vLi5dffpn9+/fn7pAGCA4OZvjwbxg50hlbKy5QmNBQPSdT\nfkFvsG79VqWkRJVUTPajciYBAVbO01xWm1PucflZDQ6NTPvgF90lCV/7z1AqjQdojaYutWrtJTh4\nAi4uls0GFR0dzYkTJ3jiiSdyH7NE+U1BBFvBRDVq1GD37t0cPXqUF198sVz+I0qSRJMmTVi2bBmb\nNm2icuXKLFhwiCFD3MnOtv1ACzB59lnm/lX25AZlVde9LqrL0dYeRgG+MTF4Kyt2VZruydG4zvJD\nYW/az+Sl8Cwqe69BoXj4FogSf/+Z1K69HW/vNqhUll25SU5OJiIignnz5qHLk6vaUuU3H3ci2AqF\nevhY0M2bNwEwGAxMmzaN114rXVWS0vDw8CAiIoIff/yFU6fcMNNGaItzcTFwV/s3ienFb/aytAZe\nDVCe/cfawyggYNUq2lfg+7YA2cAAx+v4zC4+uxSAIdHA9X4uBPn9L5OYk1N7atf+heDgsbi4VLX4\nkR69Xk9ERAT9+/enR48euY9buvzm40wEW6GAwo4FrV+/npo1a1KnTh38/f0ZOHBguY5JoVBQu3YV\n3npLxU8/pdGkiXWXZU0xc95V5h63XhKLvJrr6mB36ZK1h1GA+v/+j7aPQPajP9PSOPykjFNn047k\npB1LI+XLevj6fEzVquupVesbvLxaoFRa9vZMjsGDB1OnTh1GjRqV7/HyKL/5uBJHf4QyefgYwbBh\nwxg5ciSJiYn06dOHmJgYqlSpwqZNm3BxcTFLn7IsExubye7dBsaNs+f+fVv8zGhg45Gd9Pmxm7UH\nAsDB1utp2f1VFEmm1RUuTz9FRdHh1i1rD8MsTipDuPtsNNn3iim0oATfib54DnDBLcS7XJNTHD58\nmFatWhEaGopCoUChUDBjxgw6derEoEGDePLJJ3n11VfLbTyPCxFshTKJj48nPj6ehg0bkpycTOPG\njdm2bRurVq3C3d2dd955h08//ZTExEQ++cS8szyDwcCpUxls2aLgk0/syciwnfu4I8cmEt1oENsv\nbLP2UAA43XILddrb5lGOM7/8whMKBcmGgqUXK5rKajV7o/249lK00Wtce7niN84Pt8ZuqOwr7m5s\noWRscUogVCCFHSOIjY1l27ZtvPLKK8CDOptbt241e9+SJFG/vgPvv6/i4ME0Xn89A0myjc+ObV6I\nYscF65XSe5g2zbbO2OYV+P33tKggxeSLE5OZydc1U6k0uGB6RodGDtT4sQY1l9fEq4WX2QJtbGws\nbdu2pW7duoSGhjJ//vzc5xYsWEDt2rUJDQ1lwoQJZulPKJ2KvQ1QsCk5xwiaN29OQkIC3t7ewIOA\nfMOCaQJVKjuaNdNSr56evn3T+OILFVu2KLHW0aCnW2Xy2+2dyNhG4AfQpNhulibHdevo+uab7Llf\ntmLrtuLjpBt0fTUE1e77ZF3LQl1ZTeCngbi2dEXnpzP7knFOkoq8q0sdO3YkPj6eHTt2EBUVhVKp\n5NYjslRfUYlgK5jFw8cIHn5DKY97UlqtkpYt7QgN1fPaa2l89JGaQ4fK/0d8zMen6H9oYbn3WxR1\nivWLxhsjJSZStYIVky9Op4zLHF1SBdVNGddWrjgHO1vs/4CPjw8+Pg/O7eZNUrF06VImTJiA8r9H\nqzw8TMjlLFiMWEYWyqywYwTe3t4kJCQAD+7rlldh6wfl+1S0b+/A998b2Lo1lXr1yu+N3M/PwFWO\nkJJlOwkk3DRuqG5b//hRUfyTkx+ZT/5+KhWzg4JQtHAicEAgLlVdym0DVN4kFefOnePgwYM0b96c\nNm3amKVutFB6ItgKZVbYMYLu3buzevVqANasWZPvLF95UCgUeHur6d7dgV279GzfnkqLFpY/LjRz\nwSVmHZth8X5KIswzDNW5C9YeRpEC9++nQQUrJv8wf5WKVcHBHKhbl0GVKxPi5lautWYfXl3S6/Uk\nJibyxx9/8Nlnn/HCC7ZThOJxJIKtUCaHDx9m3bp17N+/n7CwMBo1asSuXbt499132bt3LzVr1mTf\nvn1W25yhUCjw97fn2Wcd2LrVwO7dqXTtmgUWuJ+qVBqQ/CKJTbKNmrE5GrqHYnfmjLWHUSTXFSvo\nUUHLxgWr1awODuaXevV4JSiIaq6u5V5ntrDVpcDAwNxiAk2bNkWSJG7fvl2u4xL+51FZuRGs5Kmn\nniLbyP22n376qZxHY5xCocDTU02HDiqaNdNz8mQaGzbYsXy5mqws87wxTpl+g2Wn5xd/YTlr7lgT\n6Yr5qzSZk/LCBepUoELoEtDD1ZWhXl7Uc3IisJB9CuWpsNWlnj17sn//flq3bs25c+fIysrC3b3s\nReyF0hEzW+GxknNPt1UrLXPn2vHbb+nMmJGOq2vZz3jWDT/NwdiDZhileYWovJHi4609jGIFpNnu\nJq4cbnZ2fOznx+E6dVhbuzadfX0JcnIya6B9+CjPggULAPjwww8JCAigUaNGuStIYHx1adCgQVy6\ndInQ0FD69evH2rVrzTZGoeREUgvhsWcwGDh3LoOoKFiyRMm+fSU/NvR87xQq9R3HspNLLDPIMvj3\nye+p8UzR9YFtQeyqVbSuUYNLmZnWHkoBTbRaxvn60tDJiRrOzha9F2ssUczGjRtxcnJi7NixFutb\nsByxjCw89iRJolYtB2rWlOnYUc/p02kcOiQxd66a+HjT3lT7jz5F730rLTzS0nFItb3gVRjvZcvo\numQJC2zkPKi9QsEgDw96u7sT6uyMh4NDuSwVGzvKAyDmRhWXWEYWhP9SKBS4uKho0ULL+PFqDh/O\nZPv2VHr3zkSpNP4mV6uWnjNpB8gy2GaWJo2NFY03xu6332huA8Xkq6nVLAwK4vd69fiiRg3a+vjg\nqdVa5Z7sw/VmFy5cSMOGDRk6dCj37t0r9/EIpSeWkQWhCLIsk5aWzZkzWRw9CgsWqDl7ViLvMvOG\nXad5MzKcW2m2MSN7WKLPYlxfG2HtYZjkYGQkre/cKfd+/VUqRnh50cLJiRo6HT5abbke2ylMcnIy\n4eHhTJ48mR49enDz5k08PDxQKBRMmjSJuLg4VqxYYdUxCqYTy8iCUASFQoFWq6RJEyWNG8v06pXJ\nuXMG/v4bli5VExOjIMXphM0G2mqu1VD9dwmyIvC9ehVPFxdu6i1/JtpbqWSIpyfhzs7U1OkIcHS0\neoDNUdhRHk9Pz9znhw0bRrdutlFRSjCNbfxkCUIxjCVb//7776lXrx52dnYcP37comN4kCjDnqef\nduCttzTs26fnwK9JOGnVNPVpisJKuZiL0sCrAaozZ609DJMFrlpFOwsWk6+iVjPN3589NWvye2go\nH1evTof/7ii2lUALhR/lic+zo3zLli3Uq1fPGkMTSkksIwsVgrEdmgqFAkmSGD58OJ9//jmNGjUq\n97HJsszdlLtcuH2Bf279w8azG9kfs580vfWPssxqNpXR725GGRVl7aGYxKBWsyoqiqHXr5ulPQmo\n7+DAQE9PGjo6Uk2rxdeGZrCFMVZv9ttvv+XEiRNIkkSVKlVYsmRJbrEPwfaJZWShQjC2Q7Ndu3aA\ndXdpKhQK3HRuNNU1pUlQEyLqRXD5zmWu3L3Cv7f/5bt/vuPPuD+tsoGqoaYqUgVaRpYyMwkqw9Ef\nCajn4ECEmxv1HR0J0mgI0mqppNFYNelESRhLFNOpUycrjEYwFxFshQrn4R2atkShUOBg70Ad3zrU\n8a3DM/IzDG40mOjEaGLuxnDq5ik2nd1E5M1IDLLli6X7oENhhQ1HZeGXmIhWkkg1oZh8YcG1slaL\nq729Tc9ehcePCLZChfJwsnVbp1AocNI6EaoNJdQ/lC6GLgxvMpzoxGiu3LvCpcRL7Lq0iyNxR7iX\nYf6jHNo0vQ3eSS5a0ObNPPnyy+xLTi7wXN7gGuroSGURXIUKQgRbocIobIdmRSNJEm46N9x0boQF\nhiHLMq8/8TrX7l4jPime68nXuZh4kX3R+ziecJw76WWblVaUhBZ5OX7zDc++9hpHUlMJ1Who4+JC\nHQcHvNVqvNVq/B0cRHAVKhwRbIUKo7AdmnlVxL1+CoUCjVpDiFcIIV4hwIOvY3SL0cTdi+NGyg1u\npNzgTtodLt+9zLG4Y5y9fZYrSVfQG4o/HqOuAAktZCcnsqtXJ/vJJzE0aACenjzj4EDX+vXxdXBA\nq1KJwCpUeGI3slAhGNuhmZ6ezltvvcWtW7dwdXWlYcOG/Pjjj9YertnJsowsy2RnZ3M75TZ30u6Q\nmJZIYloid9LuEHM/hpM3ThJ9L5qElARupN5AUkjEO83AedQY641bq8Xg64shIABD7drI1aohe3iA\nszM4OYGzM4pKlZC8vLD77y7hirKRSRBKQgRbQXgEGAwGDAYD6Vnp3Eu/R3JGMmlZaQTHZ6JOvAtp\naZCa+uD3e/dQ3L+PIj0dMjIgPf3Bn9PSHvw5Le3BnzMzUej1kJUFajWyRgM6HbKT04PfXVyQ3dyQ\n3dzAwQHs7R/8cnD4XyDV6VA4OyO5uiIplRUmmMbGxjJgwAASEhKQJIlhw4YxcuTI3Odnz57N22+/\nza1bt6hUqZIVRypUFGIZWRAeAZIkIUkSOqUOnUOejWOBBa/NmSXn/Xve33P/nJ2NrNcjZ2ejUCpB\nrX6wqgC5qws89OdHhVKpZM6cOfnOdXfs2JFatWoRGxvL3r17qVy5srWHKVQg4kaIIDxmchKB5Pyy\ns7PDzs4OpVKZ+0ulUqHSaFDpdKhdXFA5OqJSqXKft7Ozy339oxZo4cG57oYNGwIFK++MGTOGWbNm\nWXN4QgUkgq0gCEIR8p7r3r59O4GBgYSGhlp7WEIFI5aRBUEQjMh7rtvOzo4ZM2awd+/e3OfFlhfB\nVGJmKwiCUIiHz3VfvHiR6OhoGjRoQHBwMLGxsTRu3JgbN25Ye6hCBSB2IwuCmT28k/XVV1/lrbfe\n4p133mHHjh3Y29sTEhLCqlWrcHZ2tvZwBSMGDBiAh4cHc+bMKfT54OBgjh8/jpubWzmPTKiIRLAV\nBDMzVqEop0ygJElMmDABhULBzJkzrT1coRDGznXnLQZQtWpVjh07Jo7+CCYR92wFwcyMVShq3759\n7jXNmzdn8+bN1hqiUAxjlXfyunTpUjmNRngUiHu2gmBBxioUrVy5ks6dO1tpVOaVM2OvW7cuoaGh\nLFiwAIApU6bQoEEDGjZsSPv27YmNjbXySAXBesQysiBYSHJyMuHh4UyePDlf4YTp06dz/PjxR2Zm\na2zZPCAgILcy04IFC4iMjGT58uVWHq0gWIdYRhYECzBWoWj16tXs3LmT/fv3W3F05mVs2bxWrVq5\n16SkpODh4WGtIQqC1YlgKwgWUFiFol27djFr1iwOHjyIvb29FUdnOQ8vm0+aNIm1a9ei1Wo5cuSI\nlUcnCNYjlpEFwcwK28k6ffp0Ro4cSWZmJu7u7sCDTVKLFy+28mjNx9iyOcCnn37KP//8w6pVq6w0\nOkGwLhFsBUEoM71ez7PPPkvnzp0LrTd89epVunTpQlRUlBVGJwjWJ3YjC4JQZoUtm1+4cCH3z1u3\nbs1N7C8IjyMxsxUEoUyMJYBYvnw5//77L0qlkqpVq/Lll1/i5eVl7eEKglWIYCsIgiAIFiaWkQVB\nEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtB\nEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FW\nEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSw\nFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDAR\nbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxM\nBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQL\nE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATB\nwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARB\nsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARB\nECxMBFtBEARBsDARbAVBEATBwkSwFQRBEAQLE8FWEARBECxMBFtBKIEPP/yQ6tWrW3sYJSZJEt9+\n+621h1EiwcHBzJgxw9rDMLvVq1ejUqmsPQyhnIlgK9iEQYMG0bFjx3yPHT9+HF9fX55//nkyMjKs\nNLKCFApFkc+Hh4cjSRKSJKFWq/H29iY8PJy5c+eSnp5eTqPMLz4+noiIiNy/q1Qq1q5dW+Z2Y2Ji\ncr/WvL/s7OyYM2eOSW0MGzaMtm3bFnj82LFjjBkzpsxjLM7hw4eRJIkrV66Ypb283wedTkfDhg1Z\nuXJl7vMKhaLYn6GHGfseCRWHCLaCTdqzZw/h4eFERESwefNm7O3tS9WOLMsYDAYzj65oCoWCl156\niYSEBGJiYvjpp5/o3bs3s2fPplGjRty6datcxwPg5eWFWq22SNsKhYIdO3YQHx+f+ysuLo4RI0aU\nqV13d3ccHBzMNErjZFkucfArzuLFi4mPjycyMpIuXbowdOhQtmzZYtY+hIpFBFvB5nz99dd0796d\n9957jwULFuR77q+//uKZZ57ByckJLy8vnn/++Xwzkpxl3k2bNlG7dm3s7e35559/GDRoEB06dGDZ\nsmVUqVIFFxcXevbsye3bt/O1v3fvXlq2bIlWqyUgIIDBgwdz586dEn8NDg4OeHp64uvrS2hoKG+8\n8QZHjhwhPj6eCRMm5Lt2wYIF1K5dGwcHB2rWrMmMGTPIzs7OfT44OJgPPviA0aNH4+7ujo+PD2+/\n/TayLOdec+jQIVq2bImzszPOzs6EhYWxd+/e3OfzLiMHBwdjMBgYNGhQ7iw0OTkZZ2dnNmzYkG9s\n0dHR2NnZceDAAaNfqyzLuLm54eXlle+XRqMBQK/XM3bsWAIDA9FoNPj5+dGvXz/gwb/XihUrOHDg\nQO5YcmbcDy8jBwcHM2XKFEaMGIGrqys+Pj58+eWXZGRk8Oabb1KpUiUCAgJYtGhRvvHNnz+fsLAw\nnJyc8PX1pW/fvsTHxwMPZuatWrUCoEqVKkiSlG8GuWHDBsLCwnBwcCA4OJhx48aRmppq9HuRw9nZ\nGS8vL0JCQpgxYwbVq1cvMtju3LmTJk2aoNFo8Pb25o033iAtLa3Y75FQgciCYAMGDhwod+jQQf70\n009le3t7ee3atQWuOX36tKzT6eQPP/xQPnfunHzq1Cn5hRdekGvUqCFnZGTIsizLU6dOlbVarRwe\nHi4fOXJEPn/+vJyUlCQPHDhQdnFxkfv16yefPn1a/v333+XKlSvLAwcOzG1/3759slarlRctWiRf\nvHhRPnbsmNy2bVu5devWuddMnTpVrl69epFfS3h4uDxs2LBCn3vzzTdlV1fX3L9/8MEHcpUqVeRt\n27bJ0dHR8o8//ihXrlxZnjJlSu41VapUkStVqiR/+umn8oULF+RNmzbJSqVSXr16tSzLsqzX6+VK\nlSrJ48ePly9evChfuHBB3rp1q3zo0KHcNhQKhbxu3TpZlmX55s2bslKplBcsWCAnJCTICQkJsizL\n8vDhw+W2bdvmG++kSZPkmjVrGv1ao6OjZYVCIR8+fNjoNbNnz5YDAwPlgwcPylevXpWPHTsmz5s3\nT5ZlWU5OTpZfeukl+amnnpJv3LghJyQkyOnp6blf9/Tp0/N9H9zc3OS5c+fKFy9elKdPny5LkiQ/\n88wzuY/NnDlTliRJPnv2bO7r5s+fL+/bt0+Ojo6W//jjD/mpp56Sw8PDZVmW5ezsbHn79u2yJEny\nX3/9JSckJMiJiYmyLMvyqlWr5EqVKsnr1q2To6Oj5V9//VVu0KCBPGDAAKNf68Pf6xz169eXe/fu\nLcuyLK9evVpWqVS5z0VGRspKpVIeN26c/O+//8q7du2Sg4KCcvsp6nskVBwi2Ao2YeDAgbK9vb0s\nSZL8zTffGL2mb9+++R5LT0+XtVqtvG3bNlmWHwRDOzs7OTY2tsBrvb295aysrNzHPvnkE9nPzy/3\n7+Hh4fLEiRPzvS4mJkZWKBRyZGRkbvtlCbZfffWVLEmSfPPmTTk1NVXWarXy7t27812zdu3afAG5\nSpUqco8ePfJd06lTJ7lfv36yLMtyYmKiLEmSfODAAaNjejgAKJVKec2aNfmuOX78uCxJknzhwgVZ\nlh8EooCAAHn27NlG280Jto6OjrJOp8v95eTkJP/xxx+yLMvyqFGj5Hbt2hltY+jQoXKbNm0KPF5Y\nsH3uuedy/24wGGRnZ2e5e/fu+R5zc3OTFy1aZLS/nK/z+vXrsizL8qFDh2RJkuSYmJgC/S9ZsiTf\nYwcPHpQVCoV89+5do+3n/V7r9Xp52bJlsiRJ8tKlS2VZLhhs+/fvLz/xxBP52ti2bZssSZJ85coV\nWZaNf4+EikNp7Zm1IOSoXbs2WVlZzJgxg7Zt2+Lr65vv+aNHj3Lx4kWcnJzyPZ6RkcH58+dz/+7t\n7Y2/v3+B9mvVqoVS+b8feX9/fxISEvK1f+TIkQJL1wqFgvPnz1O/fv0yfX1A7tKvQqHg9OnTpKWl\n8fzzz+e7Jjs7m8zMTG7fvo27uzsADRs2zHeNv78/0dHRALi6ujJkyBA6duxI27Ztad26Nc899xw1\natQo0djCwsJo3Lgxy5cvZ+bMmezcuZObN28yYMCAYl+7evVqGjVqlO+xgIAAgNwl/GrVqtGhQwc6\ndOhAt27dSrUjt0GDBrl/VigUeHp65vt3USgUeHl5cePGjdzHfvnlFz755BPOnDnD3bt3c+/hx8TE\nFPgZy3Hr1i1iYmIYO3Ys48aNy31c/u/93QsXLtC4cWOj4xw6dCjDhw8nPT0drVbLxIkTGTZsWKHX\nnj59mnbt2uV7rHXr1siyzJkzZwgMDCziOyJUFCLYCjbD09OT9evX06FDB1q1asW+ffsICgrKfd5g\nMNC/f38mTpyY734lkBuUABwdHQtt/+ENQgqFIl87BoOBd999l/79+xd4rY+PT6m+podFRUXh6uqK\nu7s7Fy9eBOD7778v9DhRpUqVihx73o1fS5cuZfTo0ezZs4c9e/YwefJkFi1aZPQN3pjXXnuN999/\nn2nTprF8+XJ69uyJh4dHsa/z8/OjatWqhT7XoEEDoqOj2bt3Lz///DOjR49m8uTJHDlyBJ1OV6Lx\nPRygFQpFoY/lfG+uXr1K165deeWVV/jggw/w8PDg6tWrtG/fnszMTKP95Lx+/vz5hIeHF3g+54OE\nMTNmzKB79+7odDq8vLxM+dKER5wItoJNcXd35+eff6Zz5848/fTT7Nu3j2rVqgHQpEkTTp48SXBw\nsEX6btKkCadPnzYaNMoqNjaWb7/99v/Zu/u4Kuv7f+Cvz8VBkDvhKCiIigZmkveYireQlalL275R\nq7a5tPY1tWY336bt22rZypVZrnKb0/n9VWvRllbLNFuihpao4BI1RCVBbkROeBPeANf79wdJotwc\nhXM+5zrn9Xw8fMTB63Od17nmeHHdfS7cfvvtAIDExEQEBgbiwIEDuOmmm1q9/r59+6Jv37745S9/\niZkzZ+LPf/5zk2Xbrl27BhdhnXfHHXfg4Ycfxh//+EesWbMGa9eubXUuAAgKCsKUKVMwZcoUzJs3\nD9HR0di4cSMmTZrUZJa2kJWVhTNnzmDx4sX1V7RnZWU1uPr4/C8yF2aIiopCt27dsG/fPtxzzz2X\n/b5RUVFO/ztKTEzEpk2bGnwvIyMDhmEgMTGxPqOrthG5B69GJo/ToUMHfPLJJ4iPj8eYMWOwZ88e\nAMD8+fOxd+9e3H333cjKykJBQUH9ntL5Q6qt8dvf/hbvvfceHnroIeTk5ODgwYNYu3YtZsyYcdn3\n+Z4+fRplZWUoKSnBl19+iVdeeQXDhw9Ht27d6q+wDQ4Oxvz58zF//ny8+uqryMvLw549e/D2229f\ncsVycw4cOIBf/epXyMzMxOHDh7F161Zs3ry5/gd1Y3r27IkNGzagpKSkwRXZQUFBuOuuu/Dwww+j\nR48eTt/b6XA4UFZW1uDPqVOnAAAvvPAC/va3v2HPnj0oKCjA8uXLYbPZ6g9z9+zZE/v27cOePXtQ\nUVHR7B7n5UpISIBSCi+88AIKCgqwevVqPP300w2W6dGjBwzDqD9sfuLECQDAM888gyVLluCZZ55B\nbm4u8vLysHr1avz3f/93m+UDgEcffRQ7d+7EQw89hK+++gpr167FAw88gLvvvrt+D9qV24jcg2VL\nHikoKAgfffQRhgwZgpSUFOzatQt9+vTBli1b8O2332LChAlITEysPy8WHh7e6vccN24cPv30U+ze\nvRtjx47FgAED8PDDDyMsLOyyzy/+7f1uFVYAACAASURBVG9/Q0xMDOLi4nD99dfjn//8Jx599FFk\nZWU1ODz861//Gi+++CKWL1+OgQMHYvTo0XjppZca7L23dA9ocHAw9u/fjx//+Me4+uqrcdttt2HU\nqFENzj1fvI5FixZhx44d6Nmz5yWHOe+77z6cO3fO6UPQSilMmTIFMTExDf7Mnz8fQN1tMIsXL0Zy\ncjL69++P9957D++++279ofPp06dj6NChSE5ORlRUVP3tRxdnbmw7tPS9fv364Q9/+AP+/Oc/IzEx\nES+++CJefvnlBstHRUXh2WefxXPPPYeYmBhMnToVAHD33XcjPT0da9aswbBhw3Ddddfht7/9bYuH\nkC/3nt1+/frh/fffx+bNmzFw4ED87Gc/ww9+8AMsXbq0fpmmthFZh5KLT365UE5ODlauXAkRQUpK\nSv0/6gutWLECOTk5CAgIwKxZsxAXF9fs2Lfffhvbt28HUPd/6vvvv7/+/N2qVauwYcMG+Pn5Ydq0\naQ0uriCixq1ZswY//OEPcfjwYZ5vJGor7rrsuba2VmbPni1Hjx6V6upqeeSRRy65PWPnzp3yu9/9\nTkRE8vLyZP78+S2OPX36dP34NWvWyNKlS0VEpLCwUB599FGpqamRsrIymT17tpim2WLO3bt3t8nn\ndRcr5bVSVhFr5W2LrFVVVXLo0CEZPny43HPPPW2QqnFW2q4i1sprpawi1srb2qxuO4ycn5+P6Oho\nREZGwmazYeTIkcjKymqwTFZWFsaOHQug7lxLVVUVKisrmx17fpYaoO4WkPO3hWzfvh3Jycnw8/ND\nVFQUoqOjkZ+f32LO3NzctvrIbmGlvFbKClgrb1tk/f3vf4+EhATYbDYsXLiwDVI1zkrbFbBWXitl\nBayVt7VZ3Va2Doejwe0Zdrv9kmnwmlqmpbF///vfMXPmTGRkZODWW2+tX9eFtyw09n5E9L3f/OY3\nqK6uxubNm5263YeInOcVF0jdcccdWLp0KcaNG4eVK1fqjkNERNSA2+6ztdvtDZ524nA4GlyVeX6Z\nC29DqKiogN1uR01NTYtjAWDUqFF49tlnG32/8+u6WG5uboPDA2lpaVfw6fSxUl4rZQWslZdZXcdK\nea2UFbBW3rS0NKSnp9e/TkxMbPb2uou5rWzj4+NRWlqK8vJyREREIDMzEw8++GCDZZKSkrBu3Tok\nJycjLy8PwcHBCA8PR1hYWJNjS0tL62f3ycrKqr96OSkpCUuWLMHkyZPhcDhQWlpaPznChRrbYMXF\nxS7YAq4RGhqKkydP6o7hFCtlBayVl1ldx0p5rZQVsFbemJiYVv1y4LayNQwD06dPx4IFCyAiSE1N\nRWxsLNavXw+lFMaPH4/BgwcjOzsbc+bMQWBgIGbOnNnsWAB48803UVJSAsMwEBUVVX9vYGxsLEaM\nGIG5c+fCZrNhxowZbf7MSiIiIme49T5bq+CerWtYKStgrbzM6jpWymulrIC18sbExLRqvFdcIEVE\nROTJWLZEREQuxrIlIiJyMZYtERGRi/F5tkRtQAr2Q3bvAKq+BaK7QQ0aDhUSpjsWEXkI7tkStYKc\nOoHaV5+BufQ54MxpICwc2LsL5q9nwvzkffBifyICuGdLdMXkmwqYL8yHGjgM6hf/A2X7/pm3UlYM\nc9kLwOEDwLQHoAw/jUmJSDfu2RJdATl7BuZLv4EadQOM2+5pULQAoDrHwHj0WUilA/LGUu7hEvk4\nli3RFZC/L4PqfhWMm/+ryWVUQACM++dDDuyDbPzIjemIyNOwbIkuk+zaBsnbDXXXL1pcVgW2hzFr\nPuS9v0GOfO2GdETkiVi2RJdBqqthvv0XGD/+BVRgkFNjVFQM1A9/CnPlEkhtrYsTEpEnYtkSXQb5\n9AMgpjvUtYMva5wadQMQ2B6SscZFyYjIk7FsiZwkZ89A1q2C8cOfXvZYpRSMO+6FfJgOqTrlgnRE\n5MlYtkROks3rgIREqJjuVzRede0BNeA6yJp/tHEyIvJ0LFsiJ0hNNWTdahgTb2vVetSUOyGfrYc4\njrVRMiKyApYtkRMk+wsgKhqqx1WtWo8K7wiVnApZv7qNkhGRFbBsiZwgGz+CGndzm6xL3TAVsuVT\nyMnjbbI+IvJ8LFuiFkhJEVBSCDVoeJusT0V0hEoaCfnkgzZZHxF5PpYtUQtky7+hRqReMiVja6ib\nfgjZ9BHk7Nk2WycReS6WLVEzxDQh2zZBDR/XputVUdHAVddAtm1s0/USkWdi2RI158A+oH0QVGxc\nm6/aSJkE+fRffEgBkQ9g2RI1Q77IgLpujGtWfs0AoLoa2L/HNesnIo/BsiVqgtRUQ3ZscVnZKsOA\nSpkE2fChS9ZPRJ6DZUvUhJo9u4DILlCdOrvsPVRyKiQ3G3LiG5e9BxHpx7IlakL1ji1tdrtPU1T7\nIKiBwyCfZ7j0fYhIL5YtUSNEBNXbM6EGXOfy91Ijx0M++4QXShF5MZYtUWMKD0HZbEB0N9e/V+9E\noKYaKNjv+vciIi1YtkSNkF3b4J80Ekopl7+XUqp+75aIvBPLlqgRsmsb/Icku+391IhUyPbPOKMU\nkZdi2RJdRE5UAkdL4Nf7Wre9p7J3AnomQLK3uu09ich9WLZEF5G9u4DeiXXnbN1IDU+BbNvk1vck\nIvdg2RJdbG8OVN+Bbn9bNXAYkL+Hj94j8kIsW6ILiAhk7y49ZRvYHuraIZDtmW5/byJyLZYt0YXK\njgACoHNXLW+vho3lk4CIvBDLlugCsicHqu8At9zy06jEQUBpEeRYmZ73JyKXYNkSXUD25ADXuP8Q\n8nnK5g81eCQka7O2DETU9li2RN+R2logLxfqmgFac6hhYyBf8FAykTdh2RKdV3QICLdDhYXrzRHf\nF6j6FlJUoDcHEbUZli3RdyQvF6p3ou4Ydc+5vW40L5Qi8iIsW6LvyP5cIEF/2QKAum4MJOszPgmI\nyEuwbIlQd38t9u+BSuirO0qdbr0Amw04lKc7CRG1AZYtEQCUFgEBgVD2SN1JAHz3JKChozl9I5GX\nYNkSoe4QsvKQQ8jnqaFjINszIWat7ihE1EosWyIA2L8H8JRDyN9R0bFAWIe6bERkaSxbInjOlcgX\nU0PH8FAykRdg2ZLPE8cx4NxZbfMhN0cNHQXZuQVSU6M7ChG1AsuW6NBXQK+r9c2H3AzVqXPdLwF7\nc3RHIaJWcOvTsXNycrBy5UqICFJSUjB16tRLllmxYgVycnIQEBCAWbNmIS4urtmxb7zxBnbs2AGb\nzYbOnTvj/vvvR1BQEMrLyzF37lx07Vq3t5KQkIAZM2a47bOSdcjBPKheV+uO0aS6Q8mbofol6Y5C\nRFfIbWVrmiaWL1+OJ554AhEREZg3bx6GDh1aX4YAkJ2djbKyMixZsgT79+/HsmXL8MwzzzQ7tn//\n/rjzzjthGAbefPNNrF69GnfeeScAoEuXLli4cKG7PiJZlBz8CsYP7tAdo0kqaSTM99+EnDsL1S5A\ndxwiugJuO4ycn5+P6OhoREZGwmazYeTIkcjKymqwTFZWFsaOHQugbk+0qqoKlZWVzY7t378/DMOo\nH1NRUVG/Ps6+Qy2Rmhqg8CAQl6A7SpNUhwigRzzw5Q7dUYjoCrmtbB0OBzp27Fj/2m63w+FwOLWM\nM2MBYMOGDRg0aFD96/Lycjz22GN46qmnsG/fvrb8OOQtjnwN2COhgoJ1J2mWGjoaJq9KJrIst56z\ndaV3330Xfn5+GDVqFAAgIiICr732GkJCQnDw4EE8//zzWLx4MQIDAzUnJU8ih76C6tVbd4wWqcEj\nIO+sgJyugmofpDsOEV0mt5Wt3W7HsWPH6l87HA7Y7fZLlrnwMHBFRQXsdjtqamqaHZuRkYHs7Gw8\n8cQT9d+z2WwICQkBAPTq1QtdunRBcXExevXq1eA9c3NzkZubW/86LS0NoaGhrfy07tOuXTvL5PXE\nrN8WHoLtmv4IaCSXR+UNDcWpawag3Vf/QbvRN1zy1x6VtQVWygpYK6+VsgLWy5uenl7/dWJiIhIT\nnb83321lGx8fj9LSUpSXlyMiIgKZmZl48MEHGyyTlJSEdevWITk5GXl5eQgODkZ4eDjCwsKaHJuT\nk4P3338fTz31FPz9/evXdeLECYSEhMAwDJSVlaG0tBSdO3e+JFdjG+zkyZMu2AKuERoaapm8npi1\nNm83asdNxLlGcnlaXnNwMqo2fYyzA4df8neelrU5VsoKWCuvlbIC1sobGhqKtLS0Kx7vtrI1DAPT\np0/HggULICJITU1FbGws1q9fD6UUxo8fj8GDByM7Oxtz5sxBYGAgZs6c2exYoO5WoZqaGixYsADA\n97f47N27F+np6bDZbFBK4d5770VwsGeflyP3km9PAd84gJjuuqM4RQ24DvLmUsipE1AhYbrjENFl\nUMJLdi9RXFysO4LTrPaboSdlldxsmGvegd+jv2v07z0tLwCYf1wI9B0AY8yEBt/3xKxNsVJWwFp5\nrZQVsFbemJiYVo3nDFLks+TQV1A9Pf/iqAup6+omuCAia2HZks+Srw9AxcXrjnF5+g0BCg9CKita\nXpaIPAbLlnzX4QNA96t0p7gsyr8d1IBhkO2ZuqMQ0WVg2ZJPkpPHgdOngcguuqNcNnXdaD52j8hi\nWLbkm74+AHTv5ZFP+mlRnwHAsTJIeanuJETkJJYt+SQ5fACqh7UOIZ+nbLa6GaW2f6Y7ChE5iWVL\nPkm+tt752gvVXZXMQ8lEVsGyJd9k4T1bAEB8X+DUSUjxYd1JiMgJLFvyOfLtKeDUCSCqdTep66QM\nA2roKEgW77klsgKWLfmewweAbj2hDGv/81dD6ya44CRwRJ7P2j9tiK6AHD4AZeHztfXi4gEx6355\nICKPxrIl32Pxi6POU0rV7d1+sVF3FCJqAcuWfI58fQCqh8WmaWyCGpEC+TwDUlOtOwoRNYNlSz5F\nTlcBlRVAl666o7QJ1aUrEN0N1du36I5CRM1g2ZJvKTwIxMZB+fnpTtJm1Ogbce7Tf+mOQUTNYNmS\nT5HCQ1DdeuqO0abUkGTUHsqDHCvTHYWImsCyJd9SVADEelnZ+reD/8jxkM/W645CRE1g2ZJPkcJD\nULFxumO0uYDUSZDMf0Nqa3VHIaJGsGzJZ4hZC5QUArE9dEdpc37dewERHYEvt+uOQkSNYNmS7ygr\nATpEQAUG6U7iEiplEkxeKEXkkVi25DOkqADwwkPI56mho4DiQkjRId1RiOgiLFvyHUXeeb72PGXz\nh0qZCPnkA91RiOgiLFvyGVJUAOVlVyJfTI2ZAMneCjlRqTsKEV2AZUu+o+iQVx9GBgAVGgaVNAqS\n8ZHuKER0AZYt+QT59hTw7bdAp866o7icGn8LJGMN5OwZ3VGI6DssW/INRQVAbA/LP8PWGSq6G9TV\n/SAZa3RHIaLveP9PHiKcP18bpzuG26jJt0M+Xs29WyIPwbIl3+AD52svpLr2gOp9LfduiTwEy5Z8\ngi9ciXwxNfl2yLpVkKpvdUch8nksW/J6YtYCxYe9cprG5qiuPaD6D4WsSdcdhcjnsWzJ+x317mka\nm6Om3g357BPI0RLdUYh8GsuWvJ4UFgBd43TH0EKF26FumALz7b9ARHTHIfJZLFvyfsVfQ/nYIeQL\nqRtvBcpLIVmbdUch8lksW/J6UnwYiOmuO4Y2yt8fxrQHIG//BXLyuO44RD6JZUver7gQKrqb7hRa\nqV5XQ41IhbniJYhp6o5D5HNsugMQuZLUVAMVR4HOXXVH0U5NvRuy6NeQNelQk+9w2/tKdTVQVgQp\nOQKcqMQZPwOmnw0qoiMQlwAVEua2LES6sGzJu5UVAx0jofz9dSfRTtlsMH7xKMxnHoZEd4cakuyy\n95KTJyBZmyC7dwL7c4GITkB0LFRYBCQoCDheCbPiKFCwH4iKgUq+HmpEClRQsMsyEenEsiWvJsWF\ngI8fQr6QCu8IY87/wnzpSRgBgVDXDm6zdYsIcPArSMZHkF3boPonQY1IhZr+EFRwSP1y7UNDUXPy\nZN2Y2lrgqy8hn62H+eHbUBN+BJU6GcrGH03kXfgvmrxb8WEoH744qjGq+1Uw7p8H89Xfwbjrv6GS\nRrVqfXL2DOSLjXVTQ545DTXuZhi3T3fq8LDy8wP6DoTqOxBy5DDM9OWQbZtgzHgIqktsq3IReRKW\nLXk1KTkMNWiE7hgeR8X3hTH3KZivPANVkA815a7LPtQuRQWQzR9DvtgIJPSF8aNpwDUDrvjJSqpr\ndxi/fBKy8SOYC38FY9qDUAOGXtG6iDwNy5a8W3Eh1OTbdafwSKr7VTB+/SLM11+D/PYBqFvuhBo0\notlDuHLiG0jOF5DPPgG+qYAaNR7GEy9B2SPbJpNSUOMmQrpfBfO1Z6G+SYMxbmKbrJtIJ5YteS2p\nqQaOlfFK5GaosHAY988DcrNhfvg25K0/Q107BOhxFRDaAVAG8O0JoLgQcigPKCuGShwEY9LtwLWD\n6w4DuyJXr6thPPYczEW/hgkFY9zNLnkfIndh2ZL3OloCRHSC8m+nO4lHU0oB1w6G37WDIWXFkL27\ngCMFQP5eiGlChYQCnbvCGDISuOpqKJt7ruxWkV1gPPQ0zEWPwwwMhDE8xS3vS+QKLFvyXj4+c9SV\nUJ1joDrH6I5RT0VFw3jgSZiLHod06gIVf43uSERXhDNIkdeS4kKoGN72Y3Wqa3cYP/8lzD8uhFQc\n1R2H6IqwbMl7cc/Wa6h+Q+qeXvSn30NqanTHIbpsLFvyWlLCOZG9ibphChAcCvngLd1RiC6bW8/Z\n5uTkYOXKlRARpKSkYOrUqZcss2LFCuTk5CAgIACzZs1CXFxcs2PfeOMN7NixAzabDZ07d8b999+P\noKC6h4SvWrUKGzZsgJ+fH6ZNm4YBAwa47bOSXlJTA5SXAl14JbK3UIYB4+cPwnz6l5BrBkD16a87\nEpHT3LZna5omli9fjscffxyLFi1CZmYmjhw50mCZ7OxslJWVYcmSJbjvvvuwbNmyFsf2798fixYt\nwvPPP4/o6GisXr0aAFBUVIStW7di8eLFmDdvHv7yFz4826eUlwARHaHaBehOQm1IhYXD+OkcmCuX\nQM6c1h2HyGluK9v8/HxER0cjMjISNpsNI0eORFZWVoNlsrKyMHbsWABAQkICqqqqUFlZ2ezY/v37\nw/huxpqEhARUVFQAALZv347k5GT4+fkhKioK0dHRyM/Pd9fHJd04J7LXUv2GQCX0hbz3N91RiJzm\ntrJ1OBzo2LFj/Wu73Q6Hw+HUMs6MBYANGzZg0KBB9evq1KlTi2PIOwnnRPZqKm0GZNvGuok2iCzA\nay6Qevfdd+Hn54dRo1o3qTp5iZJCgLf9eC0VGgZ12z0wX38VYtbqjkPUIrddIGW323Hs2LH61w6H\nA3a7/ZJlzh8GBoCKigrY7XbU1NQ0OzYjIwPZ2dl44oknmny/8+u6WG5uLnJzc+tfp6WlITQ09Ao/\npfu1a9fOMnndmfVE2REExf8Etla8H7eta7RVVhk/Gac++xjtdmQiIHVSGyRrnC9uW3exWt709PT6\nrxMTE5GYmOj0WLeVbXx8PEpLS1FeXo6IiAhkZmbiwQcfbLBMUlIS1q1bh+TkZOTl5SE4OBjh4eEI\nCwtrcmxOTg7ef/99PPXUU/C/4KklSUlJWLJkCSZPngyHw4HS0lLEx8dfkquxDXbyu2dtWkFoaKhl\n8rorq9TWwiwpQlVoBFQr3o/b1jXaMqvcdg9O/+FpnE0c4rIHz/vqtnUHK+UNDQ1FWlraFY93W9ka\nhoHp06djwYIFEBGkpqYiNjYW69evh1IK48ePx+DBg5GdnY05c+YgMDAQM2fObHYsUHerUE1NDRYs\nWACg7iKpGTNmIDY2FiNGjMDcuXNhs9kwY8aMujlgyfuVlwDhdqgAXons7VSPeKhrh0A+TIe67ee6\n4xA1SQnvh7lEcXGx7ghOs9pvhm7Zs925BeaWT+E3+9etWg+3rWu0dVY5/g3MJ2fDmPcCVFR0m633\nPF/etq5mpbwxMa2bM9xrLpAiOk+KOXOUL1EdIqBSJkM++LvuKERNYtmS9+GcyD5H3TAFkrsTcuSw\n7ihEjWLZkteREj7tx9eo9kFQN/0Q5vtv6o5C1CiWLXkVqa0FjhYDXWJ1RyE3UykTgYNfQQr2645C\ndAmWLXmX8lIgLAIqIFB3EnIz1S4AalIazNVv6I5CdAmWLXmXEs6J7MvUqBuAkkLIIe7dkmdh2ZJX\n4ZzIvk3Z/KFu/CHMNe/ojkLUAMuWvEsx50T2dWrUDcDBfbwymTwKy5a8ipQchormnq0vUwEBUNf/\nAPIR927Jc7BsyWuIWQuUHQGieSWyr1PjJtbdd1teqjsKEQCWLXmTY2VAaDhUYHvdSUgzFRQMNeZm\nyNp/6o5CBIBlS96EM0fRBdT4H0C2fwapdOiOQsSyJe/BOZHpQiq0A9R1YyAZa3RHIWLZkhcpPswr\nkakBdf0tkE3rIOfO6o5CPo5lS16jbk5kHkam76kuXYFeV0M+36A7Cvk4li15BTFrgVJeiUyXMsbf\nAln/PsQ0dUchH8ayJe9w7CgQEgYVGKQ7CXmaq/sB/v5A7k7dSciHsWzJO5Rw5ihqnFIK6oapMNe/\npzsK+TCWLXkFzolMzVFDR9U9oKDokO4o5KNYtuQdivm0H2qasvnXzSr1yQe6o5CPYtmSV5AS3mNL\nzVNjboJkb4V8e1J3FPJBLFuyPDHN787Z8jAyNU2FdoDqPxSS+YnuKOSDWLZkfRVHgeBQqPa8Epma\np1ImQTI+4m1A5HYsW7I+PsOWnNWzNxAUwtuAyO1YtmR5fIYtOUspBZUyEeYGzpdM7sWyJevjnMh0\nGdTQ0cChPMjREt1RyIewbMnypJhzIpPzVLsAqJHXQzZ+pDsK+RCWLVmamCZQWsQ5kemyqLE3Q7b8\nG3KWTwMi92DZkrU5yoH2wVBBIbqTkIWoyC5Az6sh2zbqjkI+gmVL1sY5kekKGamTIBs+hIjojkI+\ngGVLlibFhzlzFF2ZvoOAM6eBQ3m6k5APYNmStRVz5ii6MsowoEbfBNm4VncU8gFOl21WVhZqa2td\nmYXosklJIRQPI9MVUiOvh2R/Dqk6pTsKeTmnyzY9PR333Xcfli9fjv3797syE5FTROS7p/1wz5au\njAoLh7p2MGRrhu4o5OVszi74/PPPo6CgAJs3b8aiRYsQEBCAMWPGYPTo0YiKinJlRqLGOY4Bge2h\ngnklMl05NeYmmG/9GZI6CUop3XHISzldtgAQFxeHuLg43H333fjyyy/x+uuvIz09HX369MH48eMx\ncuRIGAZPA5ObcOYoagtX9wNqa4H8vUBCX91pyEtdVtkCQGlpKTZv3ozNmzdDKYW0tDRERkZi7dq1\n+OKLL/DII4+4IifRJaTkMGeOolZTStU963bTWiiWLbmI02W7du1abN68GSUlJRgxYgRmz56N3r17\n1//9sGHDMGPGDJeEJGpU8WGg59W6U5AXUMmpMOe/DTl1AiokTHcc8kJOl21OTg4mT56MpKQk+Pv7\nX/L3AQEB3Kslt5LiQhgjb9Adg7yACgmD6p8E2boB6oYpuuOQF3L6BGvfvn0xYsSIS4r2X//6V/3X\nAwYMaLtkRM0QEc4eRW1KjZkA2bSWM0qRSzhdtv/85z8v6/tELvXNMSAgECo4VHcS8hYJfQFlAHm7\ndSchL9TiYeTdu+v+4dXW1tZ/fV5ZWRnat2/vmmREzSkuBDhNI7UhpRTU2AmQjWuhru6nOw55mRbL\ndunSpQCA6urq+q+Bun+Y4eHhuOeee1yXjqgJnBOZXEENT4H53t8gJyqhwsJ1xyEv0mLZvvrqqwCA\nV155BbNnz3Z5ICKnlBQCPeJ1pyAvo4JDoAYOg2z5N9SEH+mOQ17E6XO2LFryJJwTmVxFjZ0A2bQO\nYpq6o5AXaXbPdu7cuVi8eDEAYObMmU0ud+HhZSJXq5sT+TCf9kOu0etqICAQ2PcfoO9A3WnISzRb\ntr/4xS/qv54zZ47LwxA5pdIB2Pw5+QC5RN2MUhNgbloLP5YttZFmy7ZPnz71X/ft2/ppzHJycrBy\n5UqICFJSUjB16tRLllmxYgVycnIQEBCAWbNmIS4urtmxn3/+Od555x0UFRXh2WefRa9evQAA5eXl\nmDt3Lrp27QoASEhI4AxX3oJ7teRiathYyKrXIce/AUJ5exm1ntPnbP/1r3+hoKAAAJCXl4eZM2di\n1qxZyMvLc2q8aZpYvnw5Hn/8cSxatAiZmZk4cuRIg2Wys7NRVlaGJUuW4L777sOyZctaHNu9e3c8\n8sgjjf4y0KVLFyxcuBALFy5k0XqRujmReb6WXEcFBUMljYR8tl53FPISTpfthx9+WP8ovbfeeguT\nJ0/Gj370I6xcudKp8fn5+YiOjkZkZCRsNhtGjhyJrKysBstkZWVh7NixAOr2RKuqqlBZWdns2JiY\nGERHRzf6npwJxkvxGbbkBmrMTZDNH0PMWt1RyAs4XbZVVVUICgrC6dOnUVBQgJtvvhmpqakoLi52\narzD4UDHjh3rX9vtdjgcDqeWcWZsY8rLy/HYY4/hqaeewr59+5zKSZ5Pivm0H3I9FZcAhIShZtd2\n3VHICzj9IIKOHTviq6++QmFhIa655hoYhoGqqiqPfX5tREQEXnvtNYSEhODgwYN4/vnnsXjxYgQG\nBuqORq3AK5HJndSYm3D2k/eBeD56j1rH6bK9++678eKLL8Jms+Hhhx8GAOzcuRPx8c5NLGC323Hs\n2LH61w6HA3a7/ZJlKioq6l9XVFTAbrejpqamxbEXs9lsCAkJAQD06tULXbp0QXFxcf0FVOfl5uYi\nNze3/nVaWhpCLXRBRLt27SyTty2ymhXlONkuAGExXdsoVdN8bdu6i5WyyvWTcGLV/0PouTMwOkbq\njtMiK21bwHp509PT679OTExEYmKi02OdLtvBgwfjT3/6U4PvDR8+HMOHD3dqfHx8PEpLS1FeXo6I\niAhkZmbiwQcfbLBMUlIS1q1bx1LiXgAAIABJREFUh+TkZOTl5SE4OBjh4eEICwtrcezFTpw4gZCQ\nEBiGgbKyMpSWlqJz586XLNfYBjt58qRTn8kThIaGWiZvW2SVvD2QLrFu+cy+tm3dxUpZAcA/ORUn\n174L45Y7dUdpkdW2rZXyhoaGIi0t7YrHO122QN152+LiYpw5c6bB96+99toWxxqGgenTp2PBggUQ\nEaSmpiI2Nhbr16+HUgrjx4/H4MGDkZ2djTlz5iAwMLB+Io2mxgLAtm3b8Ne//hUnTpzAc889h7i4\nOMyfPx979+5Feno6bDYblFK49957ERwcfDkflzwQz9eSuwVc/wOce/YxyKTbofz8dMchi1Li5CW7\nGRkZWL58OQIDA9GuXbvvV6AUXnnlFZcF1MHZi748gdV+M2xtVnPlEiAuAca4m9smVDN8bdu6i5Wy\nAnV5Kx+fCWPCD6EGOnckTxcrblur5I2JiWnVeKf3bN966y089NBDGDRoUKvekKg1pPgwjOTrdccg\nH6PG3ARz4zr4eXjZkudy+lJi0zQxYMAAV2YhapaI1D3thxNakJuppFFAQR6kvFR3FLIop8t2ypQp\n+Oc//wmTT8IgXRzHgHYBnBOZ3E61C4AangLZ/LHuKGRRTh9G/vDDD1FZWYn333+//paa8/jUH3IL\n3l9LGqkxN8F84XHILT+GsvnrjkMW43TZ8qk/pBuvRCadVHQ3oEsskPMFkDRKdxyyGKfLti2e+kPU\nKsWH6541SqSJGnMTzE3r4Meypcvk9Dnb6upqvPXWW5g9ezZ+9rOfAQB27dqFtWvXuiwc0YW4Z0u6\nqcHJQFEBpPRIywsTXcDpsv2///s/FBYW4oEHHoBSCgDQrVs3fPwxLxgg1xPT/O5KZJYt6aP8/aGS\nr4dsXqc7ClmM02W7bds2PPDAA+jdu3d92Tr79B2iVnOUA4FBUMEhLS9L5EJqzI2QLZ9Cqs/pjkIW\n4nTZ2my2S277OXHihKUmkSYLKz7M+2vJI6ioGKB7L8iOLbqjkIU4XbbDhw/HK6+8gqNHjwIAvvnm\nGyxfvhzJyckuC0d0npQU8nwteQxjzATIJl6vQs5zumzvvPNOdO7cGQ8//DCqqqrwwAMPICIiArfd\ndpsr8xHVOcJ7bMmDDLgOOFoKOXJYdxKyCKdv/SktLUVMTAxuvfVWmKaJ6667Dt2784cfuYcUH4Yx\n5ibdMYgAAMpmgxo1HrJ5HdQd9+qOQxbQYtmKCJYuXYqNGzeiY8eOiIiIgMPhwD/+8Q+MGTMGM2fO\nrL9gisgVxDSB0iKesyWPokbfCPPpuZBbfwoVEKA7Dnm4Fsv2k08+wZ49e/DMM88gPj6+/vv5+fl4\n+eWXsX79etx4440uDUk+ruIo0D4YKohXIpPnUB2jgF5XQ7Zvhho5Xncc8nAtnrPdtGkTfv7znzco\nWgCIj4/HtGnTsHnzZpeFIwIAFPP+WvJMxtibIRt5oRS1rMWyLSoqanKqxr59+6KoqKjNQxFdiDNH\nkcfqNxg47oAcPqg7CXm4FsvWNE20b9++0b9r3749H7lHrsd7bMlDKcMPavSNvA2IWtTiOdva2lrs\n3r27yb9n2ZKrSfFhGONu1h2DqFFq1A0wfzMb8l/ToAKDdMchD9Vi2Xbo0KHZ59WGhfFB3uQ631+J\nzMPI5JlUeEegT3/I5xlQ4ybqjkMeqsWyffXVV92Rg6hxx8qAkFCo9txjIM9ljJsI8+/LIGNv5q2Q\n1CinZ5Ai0uLI10DXON0piJrXpz9gmsD+XN1JyEOxbMmjSVEBVNceumMQNUspBTVuImTDGt1RyEOx\nbMmjyZECIDZOdwyiFqkRKZA92ZBKPnaULsWyJc925Gvu2ZIlqKBgqKTRkM0f645CHohlSx5Lzp0F\nKsqBLl11RyFyikqZCNm0DlJTozsKeRiWLXmukkIgKhrK5q87CZFTVGwcENkZ2PWF7ijkYVi25LHq\nLo6K0x2D6LKocRNh8kIpugjLljxX0de8OIosRw0eAZQWQYr5YHn6HsuWPJYcKYCK5cVRZC3K5l83\nX3IG927peyxb8lxFBZzQgixJjb4J8sUmyJkq3VHIQ7BsySPJiUqgtgaI6Kg7CtFlU/ZOQJ9+kM8z\ndEchD8GyJc905Gugaw/OM0uWZXw3o5SI6I5CHoBlSx5JigrqbqMgsqrz8yXncb5kYtmSpzpSwPO1\nZGn18yXzQikCy5Y8lBR9zT1bsry6+ZJzOF8ysWzJ84hZWzd7VFc+MJ6sTQUFQw0dBdm0TncU0oxl\nS57naCkQ2gEqkA+MJ+tT4yZCNnO+ZF/HsiXPw8fqkRepmy+5C+dL9nEsW/I4UvQ150Qmr6JSJnG+\nZB/HsiWPI0UF3LMlr6IGDed8yT6OZUuep/AgVLeeulMQtZn6+ZK5d+uzWLbkUeTbU8Cpk0BUtO4o\nRG1KjZkA2bYJcprzJfsili15lqJDQGwPKIP/NMm7qIiOUH0HQrZ8qjsKacCfaORR5PBBqO69dMcg\ncgmVMgmy4UOIaeqOQm7GsiXPUngQ6MayJS+V0Bfwbwfs3aU7CbkZy5Y8CvdsyZsppaBSJ8Hc8KHu\nKORmNne+WU5ODlauXAkRQUpKCqZOnXrJMitWrEBOTg4CAgIwa9YsxMXFNTv2888/xzvvvIOioiI8\n++yz6NXr+x/Uq1atwoYNG+Dn54dp06ZhwIABbvmcdGWk+hxwtASI4TSN5L3UdWMh7/4fpLwUKrKL\n7jjkJm7bszVNE8uXL8fjjz+ORYsWITMzE0eOHGmwTHZ2NsrKyrBkyRLcd999WLZsWYtju3fvjkce\neQR9+/ZtsK6ioiJs3boVixcvxrx58/CXv/yFz5X0dMWHgahoKP92upMQuYwKCIBKHg/J+Eh3FHIj\nt5Vtfn4+oqOjERkZCZvNhpEjRyIrK6vBMllZWRg7diwAICEhAVVVVaisrGx2bExMDKKjL71NZPv2\n7UhOToafnx+ioqIQHR2N/Px8139QumJy+CAUz9eSD1DjboZs+QRy9qzuKOQmbitbh8OBjh071r+2\n2+1wOBxOLePM2Mber1OnTpc1hjQrPATwfC35ABXZBbjqGsi2jbqjkJvwAinyGMKZo8iHGCmTIJ/+\ni6e3fITbLpCy2+04duxY/WuHwwG73X7JMhUVFfWvKyoqYLfbUVNT0+LYlt7v/Loulpubi9zc3PrX\naWlpCA0Ndf6DadauXTvL5G0uq5gmjh/5GiHX9IMR4hmfx1u2raexUlbAdXnlulE4mf4XBB0pgO2a\n/m2yTm5b10pPT6//OjExEYmJiU6PdVvZxsfHo7S0FOXl5YiIiEBmZiYefPDBBsskJSVh3bp1SE5O\nRl5eHoKDgxEeHo6wsLAWx14sKSkJS5YsweTJk+FwOFBaWor4+PhLlmtsg508ebL1H9hNQkNDLZO3\nuaxSVgwEheBbUYCHfB5v2baexkpZAdfmlTE349sP34ER2zZHdLhtXSc0NBRpaWlXPN5tZWsYBqZP\nn44FCxZARJCamorY2FisX78eSimMHz8egwcPRnZ2NubMmYPAwEDMnDmz2bEAsG3bNvz1r3/FiRMn\n8NxzzyEuLg7z589HbGwsRowYgblz58Jms2HGjBlQSrnr49LlKjwI8BAy+RiVnArz/b9BvqmAiujY\n8gCyLCU8YXCJ4uJi3RGcZrXfDJvKar77/wCbP4xbfuzmVE3zlm3raayUFXB9XvNvfwSCQ2FMuavV\n6+K2dZ2YmJhWjecFUuQRpPAQVHfu2ZLvUSmTIJvWQaqrdUchF2LZknYiAnydD3S/9Jw6kbdT0d2A\nrj0gOzJ1RyEXYtmSft8cA5QCeM6KfJSRWncbEHkvli3pV5AP9IjnBWzku/oPBU5UQg7t152EXIRl\nS9rJ1/lQcTyETL5LGX51Uzhu4N6tt2LZknZSkA/VI0F3DCKt1KgbILu2QU4e1x2FXIBlS1rVXxzF\nPVvycSokDGrQCMjmj3VHIRdg2ZJex8qAdgFQHSJ0JyHSTqVOgmz8CFJbqzsKtTGWLWkl310cRUSA\n6n4VYI8Edn2hOwq1MZYt6fX1fvDiKKLvqZRJMD/9UHcMamMsW9Kq7uIoli3ReWrwCKD0COTI17qj\nUBti2ZI2YprA4QM8jEx0AWXzhxpzE4R7t16FZUv6HC0BgkKgQsN0JyHyKGrsBMj2zZCqU7qjUBth\n2ZI2wlt+iBqlOkRAXTsEkvlv3VGojbBsSZ+C/ZzMgqgJKnUyZMOHdadbyPJYtqSNHPwKqtfVumMQ\neaZeVwPtg4HcbN1JqA2wbEkLqa4Gigp4GJmoCUopqNTJMPk0IK/AsiU9Dh8AunSFCgjUnYTIY6mh\no4Cv8yFHi3VHoVZi2ZIWdYeQ++iOQeTRVLsAqJHjIRvW6I5CrcSyJT0OflV3ToqImqXG3QzZugFy\n5rTuKNQKLFvSQg7ug7qKZUvUEtUxCkhIhHyeoTsKtQLLltxOvqkAzp0DIqN1RyGyBCN1Ut1tQCK6\no9AVYtmS+313CFkppTsJkTX06Q+IAHm7dSehK8SyJbfj/bVEl6fuNqBJvA3Iwli25HZycB/Llugy\nqeEpwFe7IRXluqPQFWDZkltJTTVQeAjoyWkaiS6HCmwPNXwcZONHuqPQFWDZknsVFgCdOkMFBulO\nQmQ5atxEyGfrIdXndEehy8SyJbeSA3uhrrpGdwwiS1JdugLde0GyNuuOQpeJZUtuJftzgd6JumMQ\nWZaROhnyKW8DshqWLbmNiAD790Al9NUdhci6rh0MVJ2qu4WOLINlS25jFhcC7QKg7JG6oxBZljL8\noFImQf79ge4odBlYtuQ2NXt3QSXwEDJRa6lRN0BysyGOY7qjkJNYtuQ2Nfu+5Plaojag2gdBjUiB\nZHyoOwo5iWVLblOz7z/csyVqIyp1MmTzesjZM7qjkBNYtuQWUnEUqD4HdI7RHYXIK6ioaCC+L2Tr\nBt1RyAksW3IL2Z8LW5/+fPgAURsyxt8C+fcHENPUHYVawLIl98jLha1PP90piLxL70TA3x/Izdad\nhFrAsiW3kLxc+F0zQHcMIq+ilIIafwvMT97XHYVawLIllxNHOfDtSfh176U7CpHXUUPHAEcKIEcO\n645CzWDZksvJ3v9A9ekPZfCfG1FbU/7+UGNvhnzKSS48GX/6kevt2wVc0193CiKvpcZOgGz/DOaJ\n47qjUBNYtuRSIvLdni3P1xK5igoLhxo0Auc4haPHYtmSa5UUAjYbENlFdxIir6bG/wBnP34PUlOt\nOwo1gmVLLiV7/wN1zQDeX0vkYiq2J/xiukG2Z+qOQo1g2ZJLyb5dQB+eryVyh4CJt0HWr+azbj0Q\ny5ZcRmprgbzdULw4isgtbIOGAdXVwN5duqPQRWzufLOcnBysXLkSIoKUlBRMnTr1kmVWrFiBnJwc\nBAQEYNasWYiLi2t27KlTp/DSSy+hvLwcUVFRmDt3LoKCglBeXo65c+eia9euAICEhATMmDHDbZ+V\nABTsByI6QYVF6E5C5BOUYUDd9EOY696FX9+BuuPQBdy2Z2uaJpYvX47HH38cixYtQmZmJo4cOdJg\nmezsbJSVlWHJkiW47777sGzZshbHrl69Gv369cPLL7+MxMRErFq1qn59Xbp0wcKFC7Fw4UIWrQay\neyfUtUN0xyDyKWrYGKC4EHL4gO4odAG3lW1+fj6io6MRGRkJm82GkSNHIisrq8EyWVlZGDt2LIC6\nPdGqqipUVlY2O3b79u31Y8aNG9dgnTxvoZd8uR2qX5LuGEQ+Rdn8oW64BbJuVcsLk9u4rWwdDgc6\nduxY/9put8PhcDi1THNjjx8/jvDwcABAeHg4jh///qbu8vJyPPbYY3jqqaewb98+l3wuapwc/wYo\nLwGu6qM7CpHPUaNvguzJhpSX6o5C3/G6C6TO32ISERGB1157DQsXLsRPfvITvPzyyzhzhg9ZdhfZ\nvRPqmoFQNrdeFkBEAFT7IKjRN0LWv6c7Cn3HbT8J7XY7jh07Vv/a4XDAbrdfskxFRUX964qKCtjt\ndtTU1DQ5Njw8HJWVlfX/7dChAwDAZrMhJCQEANCrVy906dIFxcXF6NWr4WT4ubm5yM3NrX+dlpaG\n0NDQNvrUrteuXTuPzPvt3hzYho5CwAXZPDVrU6yUl1ldx0p5L8xq3vJjnHzk5wj+8b0wwjpoTtY4\nK21bAEhPT6//OjExEYmJiU6PdVvZxsfHo7S0FOXl5YiIiEBmZiYefPDBBsskJSVh3bp1SE5ORl5e\nHoKDgxEeHo6wsLAmxw4ZMgQZGRmYOnUqMjIykJRUd47wxIkTCAkJgWEYKCsrQ2lpKTp37nxJrsY2\n2MmTJ120FdpeaGiox+WVmhqYX25Hbdo9OHdBNk/M2hwr5WVW17FS3gZZbe2AwSNw8oO3YdzyY73B\nmmC1bZuWlnbF491WtoZhYPr06ViwYAFEBKmpqYiNjcX69euhlML48eMxePBgZGdnY86cOQgMDMTM\nmTObHQsAU6dOxeLFi7FhwwZERkZi7ty5AIC9e/ciPT0dNpsNSince++9CA4OdtfH9W0H9gGR0bzl\nh0gzdeNUmL+fB7npVqiAQN1xfJoSXrJ7ieLiYt0RnOaJvxma//gr4B8AY8qdDb7viVmbY6W8zOo6\nVsrbWNbapc9CxfeFccMUTamaZqVtGxMT06rxXneBFOklIpDsL6D6D9UdhYgAGJNuh6xbBTl3VncU\nn8aypbZVXAjUnAPi4nUnISIAqnsvIC4e8tl63VF8GsuW2pRkb4EaNIJP+SHyIMak2yFr34VU8/F7\nurBsqU3Jzq1Qg0fojkFEF1A9E4Cu3SFb/q07is9i2VKbkfJSoNIBxF+jOwoRXcSYfAfko3/w4fKa\nsGypzUj251ADh0EZfrqjENFF1FV9gKhoyNYNuqP4JJYttRnZuYWHkIk8mDH59u/2bmt0R/E5LFtq\nE1JeChwtAfoM0B2FiJqgel8LdOoM2fKJ7ig+h2VLbUK2bYIaMpIPHiDycMatP4F88Dbvu3Uzli21\nmohAvtgINWys7ihE1ALVszcQlwDZsEZ3FJ/CsqXWKzwEnDvLZ9cSWYQx9W7IunchVd/qjuIzWLbU\navLFRqjrxnAiCyKLUF27Q107mM+7dSOWLbWK1NbWna8dNk53FCK6DOqWOyEbPoScPK47ik9g2VLr\n7N4JRHSE6tpddxIiugyqU2eoYWMhH/xddxSfwLKlVjE/+xhq9I26YxDRFVCT74BkbYaUFOqO4vVY\ntnTFpNIB5O2GGjpadxQiugIqNAxq0m0w05frjuL1WLZ0xWTLv+vurQ1srzsKEV0hNW4iUF4G+XKH\n7ihejWVLV0RME/LZeh5CJrI4ZfOHcds9MNOXcxpHF2LZ0pX5cgcQFALEJehOQkSt1T8JsHeCZHCi\nC1dh2dIVMf/9PtT4W3hvLZEXUErBuONeyIfpkMoK3XG8EsuWLpsUFQAlhVBJI3VHIaI2oqK7QY2Z\nAPn7X3RH8UosW7ps8sn7UOMmQtn8dUchojakJt0GOXwA8uV23VG8DsuWLotUOiDZW6HG3KQ7ChG1\nMdUuAMZdM2G++UfIWT4VqC2xbOmyyLpVUCNSoUI76I5CRC6gEgdBXdUH8sFbuqN4FZYtOU1OfFN3\nb+2EH+qOQkQupG6fDtn6KeTAPt1RvAbLlpwmH6+GGjYGKryj7ihE5EIqLKLucPKKxZCzZ3TH8Qos\nW3KKnKiEfPYJ1IQf6Y5CRG6gBo+oO5z8j5W6o3gFli05RT54C2r4OCh7pO4oROQm6o57If/Jguze\nqTuK5bFsqUVSUgjZngk1+XbdUYjIjVRQCIx7fglz5cuQbzjZRWuwbKlF5j//D+rmH0GFhOmOQkRu\npq7uBzVuIsw/Pw+prdUdx7JYttQsyc0Gig9DpUzWHYWINFETbwMCAyGrXtcdxbJYttQkOXsW5huv\nwfjxL6D8OVsUka9ShgHjnofqHjS/c4vuOJbEsqUmyQdvQfW6GqrfEN1RiEgzFRoG4/55MF9/DVKw\nX3ccy2HZUqPk6wN1E1jcPl13FCLyEKpHPIyfzob56jMQR7nuOJbCsqVLyJnTMJe9AHX7DKiwCN1x\niMiDqEHDocZPgfmHpyFV3+qOYxksW7qE/H0Z1FV9YAwbqzsKEXkgdeNUqIREmEuegpw5rTuOJbBs\nqQHz8w2Q/Xugfnyf7ihE5KGUUlB33AvVJbbukPI5PiGoJSxbqicH9kHeXg5j5q+gAtvrjkNEHkwZ\nBtRPZ0GFhcN8ZQH3cFvAsiUAgFSUw1z6HIyfPwgVG6c7DhFZgDL8oO6ZC9UxCuaL/wv59qTuSB6L\nZUuQ49/AXPwE1IRbofoP1R2HiCxE+flB/XQ2VO9EmAt/BSkv1R3JI7FsfZycPA5z0a+hho+DMX6K\n7jhEZEFKKRj/9XOosRNgPvc/kK++1B3J49h0ByB9pOIozJefgho0AgYfMkBErWRc/wNIdDeYf/o9\n1IQfQY2/BcrgPh3APVufJYcPwnzuMagxN8K49W7dcYjIS6i+A2HMex6yIxPmy09BKh26I3kElq0P\nMjM/gbn4CRi3T+ehYyJqcyqyC4z/eQ6q19Uwf/sgzM0fQ0xTdyyteBjZh8ipE5C3/wL5+gCMR34H\n1bW77khE5KWUnx/UlDshg4bBfGMpJPMTGHf+N1T3XrqjacE9Wx8gpgnzi40wn5wDBIXAmP8Ci5aI\n3EJ1vwrGr34PlZwKc8lTMP/0e0hJoe5Ybsc9Wy8mIsDeHJjvvg6IwJg5D+qqPrpjEZGPUYYBNWYC\nZNg4yKcfwnx+PtA7ETWT0yBde0IppTuiy7m1bHNycrBy5UqICFJSUjB16tRLllmxYgVycnIQEBCA\nWbNmIS4urtmxp06dwksvvYTy8nJERUVh7ty5CAoKAgCsWrUKGzZsgJ+fH6ZNm4YBAwa47bPqJNXV\nkB2fQf79L+B0FYypdwGDk3lVIBFppQICoW7+ESTlZsiWT1G1bBFMww8q+XqopFFQER11R3QZt5Wt\naZpYvnw5nnjiCURERGDevHkYOnQounbtWr9MdnY2ysrKsGTJEuzfvx/Lli3DM8880+zY1atXo1+/\nfpgyZQpWr16NVatW4a677kJRURG2bt2KxYsXo6KiAk8//TSWLFnitb9BiVkLfLUbsv0zyM6tQLee\nMCbfAfQbDGX46Y5HRFRPBQZBpU5GyA9ux8msTMi2jTD/9TYQ2wNqwDCoxEFATHev+nnttrLNz89H\ndHQ0IiMjAQAjR45EVlZWg7LNysrC2LF1T5pJSEhAVVUVKisrcfTo0SbHbt++HU8++SQAYNy4cXjy\nySdx1113Yfv27UhOToafnx+ioqIQHR2N/Px8JCQkuOsju5RUVwPFh3G28ABqd2UBebuBTl2grhsN\n49cvQnWM0h2RiKhZyjCg+g6E6jsQclc1kLsT8uUOmBs+BKqroXonAnHxUHEJQPerLD1nu9vK1uFw\noGPH7w8R2O125Ofnt7iMw+Foduzx48cRHh4OAAgPD8fx48fr19W7d+9L1mUlUlMDnKgEKo5CjpUB\nFWVAWQmk6BBQVgx06ozaa/pDDR0N9ZP7+exZIrIs5e8PDBwGNXAYAECOlkDy9wIF+2FuzwSOFAAh\nHYDOMVCdu9b9N6ITEG4HOkQAHex16/BQXneBlFUPO5jbNkE+zwBOnfjuz0ng7GkgtAPQqXPdnmqn\nzkDvRBjXT647xNIuAEGhoTh5kpN/E5F3UVHRUFHRQHIqgO9OlVWUA2VHIGXFQNkRmF/tBo47vvtT\nCQQEAkHBQPsgoH3df1X7YKB9e8A/AGjXDrD5A+0CoHonQvWId9vncVvZ2u12HDt2rP61w+GA3W6/\nZJmKior61xUVFbDb7aipqWlybHh4OCorK+v/26FDh0bf7/y6Lpabm4vc3Nz612lpaYiJiWnlp70C\nU++o+3MFQkND2ziM61gpK2CtvMzqOlbKa6WswGXmje0GYLDLsrQkPT29/uvExEQkJiY6PdZtl6fG\nx8ejtLQU5eXlqKmpQWZmJpKSkhosk5SUhI0bNwIA8vLyEBwcjPDw8GbHDhkyBBkZGQCAjIyM+u8n\nJSVhy5YtqKmpwdGjR1FaWor4+Et/i0lMTERaWlr9nws3phVYKa+VsgLWysusrmOlvFbKClgrb3p6\neoOuuJyiBdy4Z2sYBqZPn44FCxZARJCamorY2FisX78eSimMHz8egwcPRnZ2NubMmYPAwEDMnDmz\n2bEAMHXqVCxevBgbNmxAZGQk5s6dCwCIjY3FiBEjMHfuXNhsNsyYMcOyh5iJiMja3HrOduDAgXj5\n5ZcbfO+GG25o8Hr69OlOjwWAkJAQ/O///m+jY2699VbceuutV5iWiIiobfg9ef6+GaoXFWWt22as\nlNdKWQFr5WVW17FSXitlBayVtzVZlYhIG2YhIiKii3D+PiIiIhdj2RIREbmY101qcTneeOMN7Nix\nAzabDZ07d8b999/f4kMMDh48iNdeew3V1dUYNGgQpk2b5pasn3/+Od555x0UFRXh2WefRa9e3z8T\n0tOyNsaZh1C409KlS7Fz50506NABL7zwAgDPfahFRUUFXnnlFRw/fhxKKVx//fWYOHGiR+atrq7G\nb37zG9TU1KCmpgZJSUm48847PTLrhUzTxLx582C32/HYY495bN5Zs2YhKCgISin4+fnh2Wef9dis\nAFBVVYU//vGPKCwshFIKM2fORHR0tMflLS4uxksvvQSlFEQEZWVluP322zFmzJi2yyo+bNeuXVJb\nWysiIm+88Ya8+eabIiJSWFgojz76qNTU1EhZWZnMnj1bTNMUEZF58+bJ/v37RUTkd7/7nWRnZ7sl\n65EjR6S4uFiefPJJOXDgQP33PTHrxWpra2X27Nly9OhRqa6ulkceeUSKioq0ZDlv7969cujQIXn4\n4Yfrv/f666/L6tWrRURk1apV8sYbb4hI89vYHb755hs5dOiQiIicPn1aHnjgASkqKvLYvGfOnBGR\nuv/d58+fL3v37vXYrOfmg6k6AAAgAElEQVR98MEH8vLLL8tzzz0nIp77b2HWrFly8uTJBt/z1Kwi\nIq+88or8f/buPjqq+sD/+GceSMKQISGQWEjEAJFSBwRraJWWJwO1sjnKemgqsGrYcqwKtua0CupW\ntvIgiBiJQepDV6VurfHY0GVL3bYYCihaUlFwYtbGChVpgEyaBwoxD3N/f2SZn5EEE5Jv7p3k/Ton\nh8yduXc+8+Umn9w7d+599dVXLcuyrObmZusf//iHo/NaVut6e8stt1gnTpzo0az9ejfypZdeKvf/\nXXbu4osvjpy9qqOLGNTU1Oj06dORk2NMmzZN+/bt65WsI0aM0PDhw8+a7sSsn/Xpi1B4vd7IhSTs\nNG7cOA0aNKjNtNLS0siFMGbMmBHJ2NEY95bExMTIpSbj4uKUmpqqUCjk2LyxsbGSWrdyw+Gw4uPj\nHZtVat1zsH//fmVlZUWmOTWvZVmt16n+FKdmPXXqlMrLyzVz5kxJksfjkc/nc2zeMw4ePKgLLrhA\nw4YN69Gs/Xo38qeVlJToa1/7mqSOL2Lg8XjaXBBh6NChtl/cIBqyduYiFE4QDRe1OH78uA4fPqyx\nY8c6Nm84HNby5ct17NgxzZ49W2lpaY7NKknPPfecbrzxRp06dSoyzal5XS6XVq1aJbfbrVmzZikr\nK8uxWY8fPy6/36/HH39chw8f1ujRo5Wbm+vYvGe8/vrr+vrXvy6pZ9eDPl+2K1eujAyQ1PqXocvl\n0g033BA5teMvf/lLeTyeyADbpTNZ0XucdsaxhoYGPfLII8rNzVVcXNxZ9zslr9vt1kMPPaRTp05p\n9erVbc49foZTsp553z49Pb3dnGc4Je/KlSs1ZMgQ1dXVadWqVe2ex90pWcPhsD788EN95zvf0Zgx\nY/Tss89q69atZz3OKXklqbm5WaWlpVq4cGG793cna58v247OLnXGzp07tX//ft1///2RaR1dxKCj\nCyX0Vtb22JW1KzpzEQon6O5FLUxqaWnRhg0bNG3aNE2ePNnxeSXJ5/Ppsssu0wcffODYrOXl5Sot\nLdX+/fvV2Nio06dP67HHHnNs3iFDWi+jOXjwYE2ePFkVFRWOzZqUlKShQ4dqzJgxkqQrrrhCW7du\ndWxeqfVAztGjR2vw4MGSevZnrF+/Z/v222/rv/7rv3T33XdrwKeug9jRRQwSExPl8/lUUVEhy7K0\na9euyC8+u0RD1s5chMIOn33/q7sXtTBp8+bNSktL05w5cxydt66uLrI7trGxUQcPHtSoUaMcmVWS\nFixYoM2bN6uwsFB33nmnxo8frzvuuMOReT/55BM1NDRIat3LceDAAY0cOdKRWaXWoho6dKiOHj0q\nqfW90LS0NMfmlaQ9e/ZE3k6UevZnrF+fQep73/uempubI5d4uvjii7V48WJJrYd1v/rqq/J6vWd9\nnGbTpk2Rj9MsWrSoV7L+8Y9/1DPPPKO6ujoNGjRI6enpuvfeex2ZtT1vv/22nnnmmciFJOz+6M/G\njRtVVlam+vp6JSQkKCcnR5MnT1Z+fr6qqqoiF7U4cxBVR2PcG8rLy7VixQqNHDlSLpdLLpdL8+fP\nV0ZGhuPy/vWvf9WmTZsif8hMnTpV1157rU6ePOm4rJ9VVlambdu2RT7647S8x48f1/r16+VyudTS\n0qKpU6dq7ty5jsx6xqFDh/TEE0+oubk58vHKcDjsyLyffPKJbr/9dhUWFmrgwIGS1KNj26/LFgCA\n3tCvdyMDANAbKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyj\nbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADD\nKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDA\nMMoWAADDKFsAAAyjbIEoNGrUKK1Zs8buGAA6ibIFHGTRokX6xje+0e59brdbP//5zyVJpaWlysvL\n69QyX3vtNbndbv31r3/tsZwAusZrdwAAXTd06NBOP9ayLLlcLoNp2mpqatKAAQN67fmAaMCWLRCF\nPrsb+Ve/+pW+/OUva9CgQRoyZIiuuOIKvfPOOzp8+LCmTZsmSUpPT5fb7dZVV10Vme/hhx/WmDFj\nFBsbq4yMDG3cuLHN81RXV+tb3/qW4uPjNWLECD3wwANatGiRZs+eHXnMzJkztXjxYt1///0aMWKE\n0tLSJEkvvPCCrrjiCiUmJio5OVnZ2dn685//HJnv8OHDcrvdeuGFF/TNb35TgwYN0iWXXKI9e/bo\no48+0jXXXKP4+HgFAgHt2bPHyDgCvYWyBaLcsWPHlJOTo4ULF6qsrExvvPGG7rzzTnm9Xo0cOVK/\n+tWvJLXueq6srNQvf/lLSdKmTZu0YsUK3XvvvSorK9Pdd9+t5cuX65lnnoksOzc3VwcPHtT27du1\nY8cOHTp0SFu3bj1rS/mll15SVVWVXn31Vb366quSpMbGRt1///3av3+/fv/738vr9eqf/umf1Nzc\n3Gbe+++/X0uWLNE777yjcePG6YYbbtDNN9+sW2+9VW+//ba+9KUvaeHChWppaTE5jIBZFgDHyM3N\ntbxerxUfH3/Wl9vttv7zP//TsizLSk9Pt1avXm1ZlmXt37/fcrvd1uHDh9td5p49e9q9/8ILL7SW\nL1/eZlpeXp41ZswYy7Is6/3337dcLpdVUlISub+pqcm68MILrdmzZ0emzZgxw/riF7/4ua8tFApZ\nLpfLev311y3LsqxDhw5ZLpfLKigoiDxm3759lsvlsvLz8yPTzry+YDD4uc8BOBVbtoDDXHHFFTpw\n4IDeeeedNl+WZbX7+EsvvVTf+MY3FAgEdP3116ugoEBHjhw553PU19fryJEjmjp1apvp06dP16FD\nh9TQ0KD33ntPLpdLX/3qVyP3e71eZWZmnrW8yy+//Kxpb7/9tq6//nqNHj1agwcP1kUXXSSXy6XD\nhw+flf+ML3zhC5KkCRMmtJlmWZaOHz9+ztcEOBllCzjMwIEDNWrUKI0ePbrNV0fcbrd+85vfqKSk\nRF/5ylf08ssva+zYsdq+fXuP5OnMwVWDBg1qc/v06dO6+uqr5Xa79eyzz2rfvn0qLS2V1Lp7+dM+\nfTDVmedqb1o4HD6/FwA4AGUL9BGZmZlavny5/vCHP2j69OmR915jYmIkqc17nn6/X2lpadq1a1eb\nZezcuVOjRo1SXFycLrnkEknS3r17I/e3tLToT3/60+dmee+991RVVaXVq1dr2rRp+uIXv6hQKNTh\n1jnQ11G2QJTbu3evVq1apT/+8Y/66KOPtGPHDh04cECBQECSdNFFF8ntdmv79u06ceKE6urqJEn3\n3HOPHnvsMT399NOqqKjQE088oSeeeEL33XefJCkjI0PZ2dlasmSJdu3apffee0/f/e53VVdX97lb\nuxdddJFiY2NVUFCgv/zlL9qxY4fuvPNOud38ykH/xJoPRAmXyxUpuU+XXUJCgvbu3au5c+dq7Nix\nWrx4sW688Ub927/9myQpJSVFDz74oNauXasRI0Zo7ty5kqTbbrtNDzzwgB588EEFAgGtX79e69at\nU25ubmTZzz77rMaPH685c+Zo5syZSk1N1ezZsxUXF9cm12cNHTpUzz//vH7/+99r/Pjxuvvuu7Vh\nw4azyra9eTs7DYgmLquP79c5deqUfvKTn+ijjz6Sy+XSbbfdposvvtjuWEBUCofDGjdunK677jqt\nX7/e7jhA1OjzW7bPPPOMLrvsMuXn52v9+vVKTU095+ODwWAvJesZ0ZQ3mrJK0ZXXVNbdu3fr5Zdf\n1l/+8he9/fbbWrRokQ4fPtxm67eromlcpejKG01ZpejK292sfbpsT506pfLycs2cOVOS5PF45PP5\nzjlPNP3nS9GVN5qyStGV11TWlpYWrVq1SpMmTVJWVpYOHTqknTt3Rt4PPh/RNK5SdOWNpqxSdOXt\nbtY+fW7k48ePy+/36/HHH9fhw4c1evRoLVq0KHJ0JoBzmzFjhvbv3293DCDq9ekt23A4rA8//FBX\nX3211q1bp9jYWG3dutXuWACAfqZPHyBVU1Ojf/u3f1NhYaEkqby8XFu3btXy5csjjwkGg212D+Tk\n5PR6TgCA8xUVFUW+DwQCXXo7pU/vRk5MTNTQoUN19OhRjRgxQgcPHoxckeSM9gbs6NGj3X5uT+UR\nNf7o9m4vpyfE5v1Yn+SvsDuGJClm+Tq1jPmS3TE6xe/3q76+3u4YnUJWc6IpbzRllaIr74gRI7q1\nMdany1ZqvRj3Y489pubmZl1wwQW6/XZnFCAAoP/o82Wbnp6uBx980O4YAIB+rE8fIAUAgBNQtgAA\nGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0A\nAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGUL\nAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZ\nAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZR\ntgAAGEbZAgBgmNfuAKYtWbJEPp9PLpdLHo9HDz74oN2RAAD9TJ8vW5fLpRUrVig+Pt7uKACAfqrP\n70a2LEuWZdkdAwDQj/WLLdtVq1bJ7XYrKytLs2bNsjsSAKCf6fNlu3LlSg0ZMkR1dXVauXKl0tLS\nNG7cOLtjAQD6kT5ftkOGDJEkDR48WF/5yldUUVHRpmyDwaCCwWDkdk5Ojvx+f7eft6nKq8ZuL6Vn\nuFwuuyNEeDxe+XpgfHtDTExMj6wLvaEnszb97YjCVcd7ZFntLt/tUkz489/acQ9L0YDhacZydFZ/\nXQ96Q7TlLSoqinwfCAQUCAQ6PW+fLttPPvlElmUpLi5ODQ0NOnDggObNm9fmMe0NWH19fbef29Pc\n3O1l9BQnvWfd0tLcI+PbG/x+f7/M6jl2VI1rl/XIsrojZvk6NcQn2B2j364HvSGa8vr9fuXk5Jz3\n/H26bGtra7V+/Xq5XC61tLRo6tSpmjhxot2xAAD9TJ8u25SUFK1fv97uGACAfq7Pf/QHAAC7UbYA\nABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQt\nAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhl\nCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG\n2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACG\nUbYAABhG2QIAYFifL9twOKxly5Zp3bp1dkcBAPRTfb5st2/frtTUVLtjAAD6sT5dtqFQSPv371dW\nVpbdUQAA/VifLtvnnntON954o1wul91RAAD9WJ8t27feeksJCQlKT0+XZVmyLMvuSACAfsprdwBT\nysvLVVpaqv3796uxsVGnT59WYWGhli5d2uZxwWBQwWAwcjsnJ0d+v7/bz99U5VVjt5fSM5y0Ze8e\nECPPoT/bHUOS5B6WogHD0zq8PyYmpkfWhd7Qk1k/8Tjj14LH45XPAePfX9eD3hBteYuKiiLfBwIB\nBQKBTs/rjJ8qAxYsWKAFCxZIksrKyrRt27azilZqf8Dq6+u7/fye5uZuL6OnOGmr3qqrUcPGH9sd\nQ5IUs3ydGuITOrzf7/f3yLrQG3oyq6fFGetuS0uzI8a/v64HvSGa8vr9fuXk5Jz3/H12NzIAAE7R\nZ7dsP+2SSy7RJZdcYncMAEA/xZYtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhl\nCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG\n2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYJijy3b79u2qq6uzOwYAAN3itTvAubz77rt64YUXFAgE\nNG3aNE2ePFkDBgywOxYAAF3i6LK9++67VV9fr9dee02//vWv9dRTT+mrX/2qpk2bpksuucTueAAA\ndIqjy1aS/H6/vvnNb+qb3/ymDh8+rMLCQpWUlGjYsGHKysrSnDlzFBcXZ3dMAAA65PiylaSDBw9q\n9+7d2rdvn0aPHq0lS5YoJSVFv/71r7VmzRo98MADdkcEAKBDji7bLVu26PXXX5fP59O0adO0YcMG\nJSUlRe7PyMjQokWLbEwIAMDnc3TZNjU16Yc//KEyMjLavd/r9Wrt2rW9nAoAgK5xdNn+8z//s2Ji\nYtpMO3nypBobGyNbuKmpqXZEAwCg0xz9Odv169erurq6zbTq6mo9/PDDNiUCAKDrHF22R48e1ciR\nI9tMGzlypD7++GObEgEA0HWOLtvBgwersrKyzbTKykr5/X6bEgEA0HWOfs925syZ2rBhg2644QZd\ncMEFqqys1IsvvqirrrrK7mgAAHSao8t27ty58nq9+tnPfqZQKKShQ4fqqquuUnZ2tt3RAADoNEeX\nrdvt1rXXXqtrr73W7igAAJw3R5et1HqQ1KFDh9TQ0NBmOruSAQDRwtFl+8tf/lIvv/yyLrroIsXG\nxra5j7IFAEQLR5ft9u3btWbNGl100UV2RwEA4Lw5+qM/MTExnCEKABD1HF223/72t/Uf//Ef+vvf\n/65wONzmCwCAaOHo3ciPP/64JGnHjh1n3ffiiy/2dhwAAM6Lo8u2sLDQ7ggAAHSbo8s2OTlZkhQO\nh1VbW6shQ4bYnAgAgK5zdNn+4x//0NNPP6033ngjciap0tJSVVRU6IYbbrA7HgAAneLoA6Seeuop\n+Xw+Pf744/J6W/8uGDt2rF5//XWbkwEA0HmO3rI9ePCgnnjiiUjRSq1XAqqtre3U/E1NTVqxYoWa\nm5vV3NyszMxMLViwwFRcAADa5eiy9fl8qq+vb/NebVVVVaffux0wYIBWrFih2NhYhcNh/ehHP1J5\nebnGjRtnKjIAAGdx9G7krKwsbdiwQe+++64sy9L777+vTZs2afbs2Z1expnTPDY1NSkcDis+Pt5U\nXAAA2uXoLdvrrrtOMTEx+ulPf6qWlhZt3rxZs2bN0pw5czq9jHA4rOXLl+vYsWOaPXu20tLSDCYG\nAOBsji5bl8ulOXPmdKlcP8vtduuhhx7SqVOntHr1apWVlemSSy7pwZQAAJybo8v23Xff7fC+8ePH\nd2lZPp9Pl112mT744IM2ZRsMBhUMBiO3c3Jy5Pf7ux72M5qqvGrs9lJ6hsvlsjtChJOyeDxe+c7x\nfx0TE9Mj60Jv6Mmsn3ic8WvBPSBGnkN/tjuGmtwuxSUla8Bw5+8V6+11tulvRxSuOn7+87tdiglb\nPZLFPSzF+P9RUVFR5PtAIKBAINDpeZ3xU9WBzZs3t7ldV1en5uZmDR06tFNnl6qrq5PX65XP51Nj\nY6MOHjyoefPmtXlMewNWX1/f7eye5uZuL6OnWFbPrMw9wUlZWlqaz/l/7ff7e2Rd6A09mdXT4ox1\n16qrUcPGH9sdQ5IUs3ydGuIT7I7xuXp7nfUcO6rGtct67fnOxfT/kd/vV05OznnP7+iy3bRpU5vb\n4XBYL7/8sgYOHNip+WtqarRp0yZZliXLsjR16lRNmDDBRFQAADrk6LL9LLfbreuvv1633nqrsrOz\nP/fxI0eO1Lp163ohGQAAHXP0R3/ac+DAAbndURcbANCPOXrL9rbbbmtzu7GxUY2NjVq8eLFNiQAA\n6DpHl+0dd9zR5nZsbKyGDx8un89nUyIAALrO0WXL52EBAH2Bo8v2scce69TnMpcuXdoLaQAAOD+O\nPtJo0KBB2rdvn8LhsJKSkhQOh7Vv3z75fD5dcMEFkS8AAJzM0Vu2f/vb37R8+XJ96UtfikwrLy/X\nyy+/rH/913+1MRkAAJ3n6C3b999/XxdffHGbaRkZGXr//fdtSgQAQNc5umxHjRqlF154QY2NrWcZ\nbmxs1C9+8Qulp6fbGwwAgC5w9G7k22+/XQUFBbr55psVHx+vkydPasyYMfre975ndzQAADrN0WWb\nkpKiVatWqaqqSn//+981ZMgQDRs2zO5YAAB0iaN3I0utV+ApKytTWVmZhg0bpurqaoVCIbtjAQDQ\naY4u27KyMt15553avXu3Xn75ZUlSZWWlnnrqKZuTAQDQeY4u22effVZ33nmn7rvvPnk8HkmtRyN/\n8MEHNicDAKDzHF22J06cOOv6s16vVy0tLTYlAgCg6xxdtmlpaXr77bfbTDt48KBGjhxpUyIAALrO\n0Ucj33jjjVq3bp0uu+wyNTY26sknn9Sf/vQn3XXXXXZHAwCg0xxdtmPHjtX69eu1e/duxcXFadiw\nYVqzZo2GDh1qdzQAADrNsWUbDof1wAMP6L777tN1111ndxwAAM6bY9+zdbvdOn78uCzLsjsKAADd\n4tiylaR58+bpqaee0okTJxQOh9t8AQAQLRy7G1mSnnjiCUnSrl27zrrvxRdf7O04AACcF0eWbU1N\njRITE1VYWGh3FAAAus2Ru5G///3vS5KSk5OVnJys5557LvL9mS8AAKKFI8v2swdFBYNBm5IAANB9\njixbl8tldwQAAHqMI9+zbWlp0bvvvhu5HQ6H29yWpPHjx/d2LAAAzosjyzYhIUGbN2+O3I6Pj29z\n2+VycfAUACBqOLJsN23aZHcEAAB6jCPfswUAoC+hbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyy\nBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAyjbAEAMIyyBQDAMMoWAADDKFsAAAzz\n2h3ApFAopMLCQtXW1srlcikrK0tz5syxOxYAoJ/p02Xr8Xh08803Kz09XQ0NDVq2bJkmTpyo1NRU\nu6MBAPqRPr0bOTExUenp6ZKkuLg4paamqrq62t5QAIB+p0+X7acdP35chw8f1sUXX2x3FABAP9Mv\nyrahoUGPPPKIcnNzFRcXZ3ccAEA/06ffs5WklpYWbdiwQdOmTdPkyZPPuj8YDCoYDEZu5+TkyO/3\nd/t5m6q8auz2UnqGy+WyO0KEk7J4PF75zvF/HRMT0yPrQm/oyayfeJzxa8FJ64p7QIw8h/5sdwxJ\nkntYigYMT2v3vt5eZ52yrkif//PcE4qKiiLfBwIBBQKBTs/rnJEyZPPmzUpLS+vwKOT2Bqy+vr7b\nz+tpbu72MnqKZVl2R4hwUpaWluZz/l/7/f4eWRd6Q09m9bQ4Y9110rpi1dWoYeOP7Y4hSYpZvk4N\n8Qnt3tfb66xT1hXp83+eu8vv9ysnJ+e85+/TZVteXq7du3dr5MiRuvvuu+VyuTR//nxNmjTJ7mgA\ngH6kT5ftuHHj9OKLL9odAwDQz/WLA6QAALATZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAA\nhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsA\ngGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkC\nAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhlG2\nAAAYRtkCAGAYZQsAgGGULQAAhlG2AAAYRtkCAGAYZQsAgGGULQAAhnntDmDS5s2b9dZbbykhIUEP\nP/yw3XEAAP1Un96ynTlzpu677z67YwAA+rk+Xbbjxo3ToEGD7I4BAOjn+nTZAgDgBJQtAACG9ekD\npDojGAwqGAxGbufk5Mjv93d7uU1VXjV2eyk9w+Vy2R0hwklZ3ANi5Dn05w7vb3K7FBO2eieMb5B0\n6h/nPXtPZrVaWnpkOd3lpHXFSVnOtd726jor56wrkuTxeOXrgd/d51JUVBT5PhAIKBAIdHrePl+2\nlmXJsjpe+dobsPr6+m4/r6e5udvL6Cnnev29zVFZ6mrUsPHHdseQJMV+f4U+cVAWJ3DUuuKkLA5b\nb52ipaW5R353d8Tv9ysnJ+e85+/TZbtx40aVlZWpvr5et912m3JycjRz5ky7YwEA+pk+Xbbf//73\n7Y4AAAAHSAEAYBplCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCA\nYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIA\nYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYA\nABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQt\nAACGUbYAABhG2QIAYBhlCwCAYZQtAACGee0OYNrbb7+tZ599VpZlaebMmZo7d67dkQAA/Uyf3rIN\nh8P66U9/qvvuu08bNmzQa6+9po8//tjuWACAfqZPl21FRYWGDx+u5ORkeb1efe1rX9O+ffvsjgUA\n6Gf6dNlWV1dr6NChkdtJSUmqrq62MREAoD/q8+/Z2sbtknv0F+1OAQBwAJdlWZbdIUx5//339dJL\nL+m+++6TJG3dulWS2hwkFQwGFQwGI7dzcnJ6NyQAICoUFRVFvg8EAgoEAp2et0/vRs7IyFBlZaVO\nnDih5uZmvfbaawciYlUAACAASURBVMrMzGzzmEAgoJycnMjXpwczGkRT3mjKKkVXXrKaE015oymr\nFF15i4qK2nRFV4pW6uO7kd1ut77zne9o1apVsixLV111ldLS0uyOBQDoZ/p02UrSpEmTtHHjRrtj\nAAD6Mc+///u//7vdIZwmJSXF7ghdEk15oymrFF15yWpONOWNpqxSdOXtTtY+fYAUAABO0KcPkAIA\nwAkoWwAADOvzB0h9niVLlsjn88nlcsnj8ejBBx/UyZMn9eijj+rEiRNKSUlRXl6efD5fr2fbvHmz\n3nrrLSUkJOjhhx+WpHNmKy4uVklJiTwej3JzczVx4kTb87700kvasWOHEhISJEnz58/XpEmTbM8b\nCoVUWFio2tpauVwuZWVlac6cOY4c389mnTVrlq655hpHjm1TU5NWrFih5uZmNTc3KzMzUwsWLHDk\nuJ4rrxPH9oxwOKx77rlHSUlJWrZsmWPH9kzW5cuXa+jQoVq2bJmjx7WrXdDlvFY/t2TJEqu+vr7N\ntJ/97GfW1q1bLcuyrOLiYuv555+3I5r13nvvWR9++KH1gx/84HOzffTRR9Zdd91lNTc3W8eOHbOW\nLl1qhcNh2/MWFRVZ27ZtO+uxduf9+9//bn344YeWZVnW6dOnre9973vWkSNHHDm+HWV16tg2NDRY\nlmVZLS0t1r333mu99957jhzXc+V16thalmVt27bN2rhxo7V27VrLspz9O+GzWZ08rl3pgvPJ2+93\nI1uWJeszx4iVlpZq+vTpkqQZM2bYdvGCcePGadCgQW2mdZSttLRUU6ZMkcfjUUpKioYPH66Kigrb\n80o6a3wl+/MmJiYqPT1dkhQXF6fU1FSFQiFHjm97Wc+c49uJYxsbGyupdasxHA4rPj7ekeN6rryS\nM8c2FApp//79ysrKapPJiWPbXlbJmeN6Jldnu+B88vb73cgul0urVq2S2+3WrFmzlJWVpdraWiUm\nJkpq/UVXW1trc8r/r6Ns1dXVGjt2bORxTrrowiuvvKJdu3ZpzJgxuummm+Tz+RyV9/jx4zp8+LDG\njh3r+PE9k/Xiiy9WeXm5I8f2zK7DY8eOafbs2UpLS3P0uLaXV3Lmevvcc8/pxhtv1KlTpyLTnDq2\n7WWVnDmuUte64Hzy9vuyXblypYYMGaK6ujqtWrVKI0aMOOsxLpfLhmSd4+RsknT11Vdr3rx5crlc\n+sUvfqEtW7bo1ltvtTtWRENDgx555BHl5uYqLi7urPudNL6fzerUsXW73XrooYd06tQprV69us25\nx89w0rh+Nm9ZWZkjx/bM8RDp6entjukZThjbjrI6cVzPMN0F/X438pAhQyRJgwcP1uTJk1VRUaHE\nxETV1NRIkmpqaiJv5jtBR9mSkpJUVVUVeVwoFFJSUpItGT9t8ODBkRU0KysrsqvFCXlbWlq0YcMG\nTZs2TZMnT5bk3PFtL6uTx1aSfD6fLrvsMn3wwQeOHdeO8jpxbMvLy1VaWqqlS5dq48aNevfdd/XY\nY485cmzby1pYWOjIcT2jK11wPnn7ddl+8sknamhokNS61XDgwAGNHDlSl19+uXbu3ClJ2rlz51kX\nL+hNn30foaNsmZmZev3119Xc3Kzjx4+rsrJSGRkZtuc9s6JK0ptvvqkLL7zQMXk3b96stLQ0zZkz\nJzLNqePbXlYnjm1dXV1kt2FjY6MOHjyoUaNGOXZc28ubnp7uyLFdsGCBNm/erMLCQt15550aP368\n7rjjDkeObXtZly5d6shxlbreBeeTt1+fQer48eNav369XC6XWlpaNHXqVM2dO1cnT55Ufn6+qqqq\nlJycrLy8vHYP/DFt48aNKisrU319vRISEpSTk6PJkyd3mK24uFivvvqqvF6vLYfOt5c3GAzq0KFD\ncrlcSk5O1i233BJ5D8TOvOXl5VqxYoVGjhwpl8sll8ul+fPnKyMjw3Hj21HWPXv2OG5s//rXv2rT\npk2RP7qmTp2qa6+99pw/U3auBx3lLSwsdNzYflpZWZm2bdsW+eiPE8e2vaxOHdfz6YKu5u3XZQsA\nQG/o17uRAQDoDZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACG\nUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCA\nYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIA\nYBhlCwCAYZQtAACGUbYAesQf/vAHud1uHT161O4ogONQtkCUWLRokdxud+QrMTFRU6ZM0W9+85te\nef709PTIcw8cOFBf+tKXtH79+jaPcblcXVrm6tWrNWrUqJ6MCTgSZQtEkWnTpunYsWOqrKzUm2++\nqS9/+cuaO3euPvzwQ+PP7XK5dM8996iyslLl5eW6/fbbtXz5cm3YsOG8l2lZVpcLGohGlC0QRWJi\nYpScnKyUlBR98Ytf1Nq1a9XU1KQDBw5EHnPy5El997vfVUpKiuLi4jR58mT97ne/i9z/0ksvKTY2\nVqWlpZFpW7Zs0cCBA/XOO++c8/kHDRqklJQUXXTRRbrjjjuUlZWl4uLiDh//xhtvaPr06fL5fEpK\nStLChQt14sQJSdJzzz2n+++/X4cPH5bb7ZbH49EDDzxwvkMDOBplC0SppqYmPfnkk4qLi9OXv/zl\nyPRFixbpd7/7nX7+85/rnXfe0de+9jVlZ2fr/ffflyR961vfUm5urm644QadPHlS77//vpYuXaoN\nGzZo4sSJXcowcOBANTY2tnvfsWPHdPXVV2vkyJEqLS3Vf//3f+vdd9/Vt771LUnSt7/9bS1btkxp\naWk6duyY/va3v+mHP/zheY4G4GxeuwMA6LySkhL5/X5J0qlTpzRo0CBt2bJFF154oSTpgw8+0Msv\nv6zf/OY3mjVrliTp0Ucf1e7du/XQQw/p6aefjkz7yle+ou985zv685//rNmzZ+v222/vdA7LsrR9\n+3b9z//8j37wgx+0+5jCwkIlJCTomWeekdfb+qvmZz/7mSZNmqQ9e/bo61//uuLj4+XxeJScnHze\nYwJEA8oWiCJXXHGFtmzZIsuydPLkSf32t7/VTTfdpISEBM2ePVtlZWVyuVyaOnVqm/mmTZumN954\nI3J74MCB+sUvfqFJkybpC1/4gl599dVOPf/KlSv14IMPqrGxUW63W4sWLdL999/f7mPLysp0xRVX\nRIpWki699FIlJCQoGAzq61//+nmMABCdKFsgigwcOLDN0buXXnqpduzYodWrV2v27NldWtbu3bsl\nSTU1NTp+/LgSExM/d54lS5bo9ttv18CBAzV8+PCuhQf6Md6zBaKc2+3WqVOnJEmBQECStGvXrjaP\n2bVrl8aPHx+5/e677+oHP/iBnnzySV1zzTX69re/raamps99rqSkJI0ePbpTRRsIBPTGG2+oubk5\nMu2dd95RbW2tJkyYIKn1gK+WlpbPf5FAlKNsgSjS2NioY8eO6dixY/rLX/6ixx9/XL/73e90/fXX\nS5JGjx6tefPm6fbbb9dvf/tb/e///q++//3vKxgM6q677pIkNTQ0aP78+Zo7d64WLVqkJ598UjU1\nNR2+99oVlmVFvl+6dKnq6uqUm5urYDCoPXv26KabbtL06dM1ZcoUSdKoUaNUWVmpN954Q6FQSKdP\nn+52BsCRLABRITc313K73ZGvQYMGWePHj7ceeeSRNo+rr6+3br31VislJcWKi4uzJk+ebP3+97+P\n3H/bbbdZGRkZVl1dXWTanj17rJiYGGvbtm0dPv+oUaOs1atXd3j/zp07LbfbbX388ceRaW+++aY1\nffp0y+fzWUOGDLH+5V/+xTpx4kTk/qamJmvhwoVWUlKS5Xa7rR//+MddGhMgWrgs61N/ijrckiVL\n5PP55HK55PF49OCDD+rkyZN69NFHdeLECaWkpCgvL08+n0+SVFxcrJKSEnk8HuXm5nb5Yw0AAPSE\nqDpAyuVyacWKFYqPj49M27p1qyZMmKDrrrtOW7duVXFxsRYuXKgjR45o7969ys/PVygU0sqVK1VQ\nUMDZaoAuCAaDkfeBAZy/qHrP1rIsfXZDvLS0VNOnT5ckzZgxQ/v27YtMnzJlijwej1JSUjR8+HBV\nVFT0emYgmgWDQbsjAH1C1G3Zrlq1Sm63W7NmzVJWVpZqa2sjH1lITExUbW2tJKm6ulpjx46NzJuU\nlKTq6mpbcgMA+reoKtuVK1dqyJAhqqur06pVqzRixIizHsNuYgCA00RV2Q4ZMkSSNHjwYE2ePFkV\nFRVKTExUTU1N5N+EhARJrVuyVVVVkXlDoZCSkpLOWmYwGGyzqywnJ8fwqwCiBz8PwP9XVFQU+T4Q\nCHTpeIaoKdtPPvlElmUpLi5ODQ0NOnDggObNm6fLL79cO3fu1Ny5c7Vz505lZmZKkjIzM1VQUKDs\n7GxVV1ersrJSGRkZZy23vQHj4tdAK7/fr/r6ertjALYbMWJEt/74jJqyra2t1fr16+VyudTS0qKp\nU6dq4sSJGjNmjPLz81VSUqLk5GTl5eVJktLS0nTllVcqLy9PXq9XixcvZhczAMAWUfU5297Cli3Q\nii1boFV7xwh1RVR99AcAgGhE2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYA\nABhG2QIAYBhlCwCAYZQtAACGUbYAABhG2QIAYBhlCwCAYZQtAACGUbYAABjmtTsAALNSU1Nted6P\nP/7YlucFnIiyBfq47pSe3+9XfX19D6YB+id2IwMAYBhlCwCAYZQtAACGUbYAABhG2QLo0Jo1MXZH\nAPoEyhZAh9aujbU7AtAnULYAABhG2QIAYBhlCwCAYVF3BqlwOKzly5dr6NChWrZsmV566SXt2LFD\nCQkJkqT58+dr0qRJkqTi4mKVlJTI4/EoNzdXEydOtDM6AKCfirqy3b59u9LS0nT69OnItOzsbGVn\nZ7d53JEjR7R3717l5+crFApp5cqVKigokMvl6u3IQNRavvwTuyMAfUJU7UYOhULav3+/srKy2ky3\nLOusx5aWlmrKlCnyeDxKSUnR8OHDVVFR0VtRgT7h3nsb7Y4A9AlRtWX73HPP6cYbb9SpU6faTH/l\nlVe0a9cujRkzRjfddJN8Pp+qq6s1duzYyGOSkpJUXV3d25EBAIieLdu33npLCQkJSk9Pb7Mle/XV\nV6uwsFDr169XYmKitmzZYmNKAADOFjVbtuXl5SotLdX+/fvV2Nio06dPq7CwUEuXLo08JisrS+vW\nrZPUuiVbVVUVuS8UCikpKems5QaDQQWDwcjtnJwc+f1+g68EiB4xMTH8PAD/p6ioKPJ9IBBQIBDo\n9LxRU7YLFizQggULJEllZWXatm2bli5dqpqaGiUmJkqS3nzzTV144YWSpMzMTBUUFCg7O1vV1dWq\nrKxURkbGWcttb8C4fifQiuvZAq38fr9ycnLOe/6oKduOPP/88zp06JBcLpeSk5N1yy23SJLS0tJ0\n5ZVXKi8vT16vV4sXL+ZIZKCL1qyJ0R132J0CiH4uq71Defu5o0eP2h0BcITU1BH6+GN+HoARI0Z0\na/6oOUAKAIBoRdkCAGAYZQsAgGGULQAAhlG2ADrEuZGBnsHRyO3gaGSgFZ+zBVpxNDIAAA5H2QIA\nYBhlCwCAYZQtAACGUbYAOrRmTYzdEYA+gbIF0KG1a2PtjgD0CZQtAACGUbYAABhG2QIAYBhlCwCA\nYZQtgA5xbmSgZ3Bu5HZwbmSgFedGBlpxbmQAAByOsgUAwDDKFgAAwyhbAAAMo2wBdIhzIwM9g7IF\n0CHOjQz0DMoWAADDKFsAAAyjbAEAMIyyBQDAMK/dAboqHA7rnnvuUVJSkpYtW6aTJ0/q0Ucf1YkT\nJ5SSkqK8vDz5fD5JUnFxsUpKSuTxeJSbm6uJEyfanB6ILpwbGegZUbdlu337dqWmpkZub926VRMm\nTNDGjRsVCARUXFwsSTpy5Ij27t2r/Px83XPPPXr66afFaaCBrrn33ka7IwB9QlSVbSgU0v79+5WV\nlRWZVlpaqunTp0uSZsyYoX379kWmT5kyRR6PRykpKRo+fLgqKipsyQ0A6N+iqmyfe+453XjjjXK5\nXJFptbW1SkxMlCQlJiaqtrZWklRdXa1hw4ZFHpeUlKTq6ureDQwAgKKobN966y0lJCQoPT39nLuD\nP13EAAA4QdQcIFVeXq7S0lLt379fjY2NOn36tB577DElJiaqpqYm8m9CQoKk1i3ZqqqqyPyhUEhJ\nSUlnLTcYDCoYDEZu5+TkyO/3m39BQBSIiYnh5wH4P0VFRZHvA4GAAoFAp+eNyovHl5WVadu2bVq2\nbJmef/55xcfHa+7cudq6dav+8Y9/aOHChTpy5IgKCgq0Zs0aVVdXa+XKlSooKOjUli8XjwdaPfbY\nUN1xR8juGIDtunvx+KjZsu3I3LlzlZ+fr5KSEiUnJysvL0+SlJaWpiuvvFJ5eXnyer1avHgxu5iB\nLlq7NlZ33GF3CiD6ReWWrWls2QKtUlNH6OOP+XkAurtlGzUHSAEAEK0oWwAADKNsAQAwjLIF0CHO\njQz0DA6QagcHSAGt/H6/6uvr7Y4B2I4DpAAAcDjKFgAAwyhbAAAMo2wBADCMsgXQoTVrYuyOAPQJ\nlC2ADq1dG2t3BKBPoGwBADCMsgUAwDDKFgAAwyhbAAAMo2wBdIhzIwM9g3Mjt4NzIwOtODcy0Ipz\nIwMA4HCULQAAhlG2AAAYRtkCAGAYZQugQ5wbGegZlC2ADnFuZKBnULYAABhG2QIAYBhlCwCAYZQt\nAACGUbYAOsS5kYGewbmR28G5kYFWnBsZaNXdcyN7eyiHcU1NTVqxYoWam5vV3NyszMxMLViwQC+9\n9JJ27NihhIQESdL8+fM1adIkSVJxcbFKSkrk8XiUm5uriRMn2vkSAAD9VNSU7YABA7RixQrFxsYq\nHA7rRz/6kcrLyyVJ2dnZys7ObvP4I0eOaO/evcrPz1coFNLKlStVUFAgl8tlR3wAQD8WVe/Zxsa2\nfsC+qalJ4XBY8fHxkqT29oSXlpZqypQp8ng8SklJ0fDhw1VRUdGreQEAkKJoy1aSwuGwli9frmPH\njmn27NlKS0uTJL3yyivatWuXxowZo5tuukk+n0/V1dUaO3ZsZN6kpCRVV1fbFR0A0I9F1Zat2+3W\nQw89pM2bN+u9995TWVmZrr76ahUWFmr9+vVKTEzUli1b7I4J9BmcGxnoGVG1ZXuGz+fTZZddpg8+\n+ECXXHJJZHpWVpbWrVsnqXVLtqqqKnJfKBRSUlLSWcsKBoMKBoOR2zk5OfL7/QbTA9Fj7dpY3Xsv\nPw+AJBUVFUW+DwQCCgQCnZ43asq2rq5OXq9XPp9PjY2NOnjwoObNm6eamholJiZKkt58801deOGF\nkqTMzEwVFBQoOztb1dXVqqysVEZGxlnLbW/A+KgDcAYf/QGk1o/B5eTknPf8UVO2NTU12rRpkyzL\nkmVZmjp1qiZMmKDCwkIdOnRILpdLycnJuuWWWyRJaWlpuvLKK5WXlyev16vFixdzJDIAwBac1KId\nnNQCaJWaOkIff8zPA9Ddk1pE1QFSAABEI8oWQIc4NzLQM9iN3A52IwOtODcy0IrdyAAAOBxlCwCA\nYZQtAACGUbYAABhG2QLoEOdGBnoGZQugQ2vXxtodAegTKFsAAAyjbAEAMIyyBQDAMMoWAADDouYS\ne0B/Fgh8QTU19vxtnJravdPUdVViYljBYGWvPidgGmULRIGaGrctl7qz49zIvV3uQG9gNzIAAIZR\ntgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBh\nlC0AAIZFzVV/mpqatGLFCjU3N6u5uVmZmZlasGCBTp48qUcffVQnTpxQSkqK8vLy5PP5JEnFxcUq\nKSmRx+NRbm6uJk6caPOrAAD0R1FTtgMGDNCKFSsUGxurcDisH/3oRyovL1dpaakmTJig6667Tlu3\nblVxcbEWLlyoI0eOaO/evcrPz1coFNLKlStVUFAgl8tl90sBAPQzUbUbOTY2VlLrVm44HFZ8fLxK\nS0s1ffp0SdKMGTO0b98+SVJpaammTJkij8ejlJQUDR8+XBUVFbZlBwD0X1GzZStJ4XBYy5cv17Fj\nxzR79mylpaWptrZWiYmJkqTExETV1tZKkqqrqzV27NjIvElJSaqurrYlNwCgf4uqsnW73XrooYd0\n6tQprV69WsFg8KzHsJsYAOA0UVW2Z/h8Pl122WX64IMPlJiYqJqamsi/CQkJklq3ZKuqqiLzhEIh\nJSUlnbWsYDDYprRzcnLk9/vNvwigi+xYL2NiYmx5Xn4G4URFRUWR7wOBgAKBQKfnjZqyraurk9fr\nlc/nU2Njow4ePKh58+aprq5OO3fu1Ny5c7Vz505lZmZKkjIzM1VQUKDs7GxVV1ersrJSGRkZZy23\nvQGrr6/vldcEdJ7flvXS77fjee15rcC5+P1+5eTknPf8UVO2NTU12rRpkyzLkmVZmjp1qiZMmKBR\no0YpPz9fJSUlSk5OVl5eniQpLS1NV155pfLy8uT1erV48WJ2MQMAbOGyLMuyO4TTHD161O4IQBup\nqSP08ce9v17asWVr12sFzmXEiBHdmj+qPvoDAEA0omwBADCMsgUAwDDKFgAAwyhbAAAMo2wBADCM\nsgUAwDDKFgAAwyhbAAAMo2wBADCMsgUAwDDKFgAAwyhbAAAMo2wBADCMsgUAwDDKFgAAwyhbAAAM\no2wBADCMsgUAwDDKFgAAwyhbAAAMo2wBADCMsgUAwDDKFgAAwyhbAAAMo2wBADCMsgUAwDDKFgAA\nw7x2B+isUCikwsJC1dbWyuVyadasWbrmmmv00ksvaceOHUpISJAkzZ8/X5MmTZIkFRcXq6SkRB6P\nR7m5uZo4caKdLwEA0E9FTdl6PB7dfPPNSk9PV0NDg5YtW6ZLL71UkpSdna3s7Ow2jz9y5Ij27t2r\n/Px8hUIhrVy5UgUFBXK5XHbEBwD0Y1GzGzkxMVHp6emSpLi4OKWmpqq6ulqSZFnWWY8vLS3VlClT\n5PF4lJKSouHDh6uioqI3IwMAICmKyvbTjh8/rsOHD+viiy+WJL3yyiu666679JOf/ESnTp2SJFVX\nV2vYsGGReZKSkiLlDABAb4q6sm1oaNAjjzyi3NxcxcXF6eqrr1ZhYaHWr1+vxMREbdmyxe6IAAC0\nETXv2UpSS0uLNmzYoGnTpmny5MmSpMGDB0fuz8rK0rp16yS1bslWVVVF7guFQkpKSjprmcFgUMFg\nMHI7JydHfr/f1EsAzpsd62VMTIwtz8vPIJyoqKgo8n0gEFAgEOj0vFFVtps3b1ZaWprmzJkTmVZT\nU6PExERJ0ptvvqkLL7xQkpSZmamCggJlZ2erurpalZWVysjIOGuZ7Q1YfX29wVcBnA+/Leul32/H\n89rzWoFz8fv9ysnJOe/5o6Zsy8vLtXv3bo0cOVJ33323XC6X5s+frz179ujQoUNyuVxKTk7WLbfc\nIklKS0vTlVdeqby8PHm9Xi1evJgjkQEAtnBZ7R3K288dPXrU7ghAG6mpI/Txx72/XtqxZWvXawXO\nZcSIEd2aP+oOkAIAINpQtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZR\ntgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBh\nlC0AAIZRtgAAGEbZAgBgGGULAIBhlC0AAIZRtgAAGEbZAgBgGGULAIBhXrsDdFYoFFJhYaFqa2vl\ncrmUlZWlOXPm6OTJk3r00Ud14sQJpaSkKC8vTz6fT5JUXFyskpISeTwe5ebmauLEiTa/CgBAfxQ1\nZevxeHTzzTcrPT1dDQ0NWrZsmSZOnKiSkhJNmDBB1113nbZu3ari4mItXLhQR44c0d69e5Wfn69Q\nKKSVK1eqoKBALpfL7pcCAOhnomY3cmJiotLT0yVJcXFxSk1NVSgUUmlpqaZPny5JmjFjhvbt2ydJ\nKi0t1ZQpU+TxeJSSkqLhw4eroqLCrvgAgH4sasr2044fP67Dhw9r7Nixqq2tVWJioqTWQq6trZUk\nVVdXa9iwYZF5kpKSVF1dbUteAED/FnVl29DQoEceeUS5ubmKi4s76352EwMAnCZq3rOVpJaWFm3Y\nsEHTpk3T5MmTJbVuzdbU1ET+TUhIkNS6JVtVVRWZNxQKKSkp6axlBoNBBYPByO2cnBz5/X7DrwTo\nOjvWy5iYGFuel59BOFFRUVHk+0AgoEAg0Ol5o6psN2/erLS0NM2ZMycy7fLLL9fOnTs1d+5c7dy5\nU5mZmZKkzMxMFRQUKDs7W9XV1aqsrFRGRsZZy2xvwOrr682+EKDL/Lasl36/Hc9rz2sFzsXv9ysn\nJ+e854+asi0vL9fu3bs1cuRI3X333XK5XJo/f77mzp2r/Px8lZSUKDk5WXl5eZKktLQ0XXnllcrL\ny5PX69X/a+9+QpvI+ziOf6apXY3GjHlsVxP3sFZEzUplbdm1ICoKIhT0sAQWRXsQQWQPAcE/exBR\n6+5a6B9FPXgSvFQwPXrRqpeqrb0skT0UUTSl2DY0thqL+sxzKE+gayrV+ut0kvfr0mQmk/mmpP3k\nN/PNb/bv388hZgCAKyzHcRy3i5ht+vr63C4BmCAcibhdwozqS6XcLgGYIBwOT2t7z4xsgWJmyVEq\nNfMfAt04jByJhJUSH3hRWDzXjQwAgNcQtgAAGEbYAgBgGGELAIBhhC0AAIYRtgAAGEbYAgBgGGEL\nAIBhhC0AAIYRtgAAGEbYAgBgGGELAIBhhC0AAIYRtgAAGEbYAgBgGGELAIBhhC0AAIYRtgAAGEbY\nAgBgGGEL0ES3NwAACNxJREFUAIBhhC0AAIYRtgAAGEbYAgBgGGELAIBhhC0AAIYRtgAAGEbYAgBg\nWKnbBUzVpUuX1NPTo2AwqMbGRknS9evXdevWLQWDQUnSr7/+qnXr1kmSEomEOjo65PP5VF9fr6qq\nKtdqBwAUN8+E7ZYtW7Rjxw5duHBhwvK6ujrV1dVNWPbixQt1dnaqqalJQ0NDOnXqlFpbW2VZ1kyW\nDACAJA8dRl61apXmz5//0XLHcT5a1t3drdraWvl8PlVUVGjp0qXq7e2diTIBAPiIZ0a2k7l586bu\n3bunyspK7d27V36/X+l0WitXrsw9JhQKKZ1Ou1glAKCYeWZkm8/27dt14cIFnTt3TrZt6+rVq26X\nBADARzw9sl24cGHu9tatW/Xnn39KGh/JDg4O5tYNDQ0pFArlfY5kMqlkMpm7H4vFFAgEDFUMfDk3\n3pdlZWWu7Je/QcxGbW1tudvRaFTRaHTK23oqbB3HmXCOdnh4WLZtS5IePHig7777TpJUXV2t1tZW\n1dXVKZ1Oq7+/XytWrMj7nPl+YSMjI4ZeAfClAq68LwMBN/brzmsFPiUQCCgWi33x9p4J25aWFj1+\n/FgjIyM6ePCgYrGYksmknj59KsuyVF5ergMHDkiSli1bpg0bNigej6u0tFT79++nExkA4BrLydfO\nW+T6+vrcLgGYIBIJK5Wa+felGyNbt14r8CnhcHha23u6QQoAAC8gbAEAMIywBQDAMMIWAADDCFsA\nAAwjbAEAMIywBQDAMMIWAADDCFsAAAwjbAEAMIywBQDAMMIWAADDCFsAAAwjbAEAMIywBQDAMMIW\nAADDCFsAAAwjbAEAMKzU7QIATE0kEnZpz4EZ3Ztt/3dG9wfMBMIW8IBUqs+V/UYiYdf2DRQSDiMD\nAGAYYQsAgGGELQAAhhG2AAAYRtgCmNTRo2NulwAUBMtxHMftImabvj66LwFJCgQCGhkZcbsMwHXh\n8PS+esfIFgAAwwhbAAAMI2wBADDMMzNIXbp0ST09PQoGg2psbJQkjY6Oqrm5WQMDA6qoqFA8Hpff\n75ckJRIJdXR0yOfzqb6+XlVVVW6WDwAoYp4Z2W7ZskW///77hGXt7e1au3atWlpaFI1GlUgkJEkv\nXrxQZ2enmpqadOzYMV25ckX0gQGfr6GhzO0SgILgmbBdtWqV5s+fP2FZd3e3Nm3aJEnavHmzurq6\ncstra2vl8/lUUVGhpUuXqre3d8ZrBrzujz++cbsEoCB4JmzzyWQysm1bkmTbtjKZjCQpnU5r8eLF\nuceFQiGl02lXagQAwNNh+2+WZbldAgAAH/FMg1Q+tm1reHg49zMYDEoaH8kODg7mHjc0NKRQKJT3\nOZLJpJLJZO5+LBZTIDCz1+8EZjP+HoBxbW1tudvRaFTRaHTK23oqbB3HmdDotH79et25c0e7du3S\nnTt3VF1dLUmqrq5Wa2ur6urqlE6n1d/frxUrVuR9zny/MGbMAf6PGaQAafxDZywW++LtPTNdY0tL\nix4/fqyRkREFg0HFYjHV1NSoqalJg4ODKi8vVzwezzVRJRIJ3b59W6WlpZ/91R+mawTGnT//H/32\n25DbZQCum+50jZ4J25lE2ALjmBsZGMfcyAAAzHKELQAAhhG2AAAYRtgCAGAYYQtgUsyNDHwdhC2A\nSTE3MvB1ELYAABhG2AIAYBhhCwCAYYQtAACGEbYAJnX06JjbJQAFgbmR82BuZGAccyMD45gbGQCA\nWY6wBQDAMMIWAADDCFsAAAwjbAFMirmRga+DbuQ86EZGIYlEIq7sN5VKubJfwITpdiOXfqU6AMxS\n0wk9vvoDfB0cRgYAwDDCFgAAwwhbAAAMI2wBADCMsAUAwDDCFgAAwwhbAAAMI2wBADCMsAUAwLCC\nmEHq0KFD8vv9sixLPp9PZ8+e1ejoqJqbmzUwMKCKigrF43H5/X63SwUAFKGCCFvLsnTixAktWLAg\nt6y9vV1r167Vzp071d7erkQiod27d7tYJQCgWBXEYWTHcfTv6yl0d3dr06ZNkqTNmzerq6vLjdIA\nACicke3p06dVUlKibdu2aevWrcpkMrJtW5Jk27YymYzLVQIAilVBhO2pU6e0aNEivXr1SqdPn857\nKSTLslyoDACAAgnbRYsWSZIWLlyompoa9fb2yrZtDQ8P534Gg8G82yaTSSWTydz9WCw27esWAoUk\nEAi4XQIwK7S1teVuR6NRRaPRKW/r+YvHj42NyXEczZ07V2/fvtWZM2f0yy+/6O+//9aCBQu0a9cu\ntbe36/Xr1zRIAZ+pra1NsVjM7TIAz/P8yDaTyejcuXOyLEsfPnzQxo0bVVVVpcrKSjU1Namjo0Pl\n5eWKx+NulwoAKFKeH9kCMIeRLfB1FMRXfwCY8TnnpABMjpEtAACGMbIFAMAwwhYAAMM8340MYPqu\nX7+uuXPnKpvNas2aNfrhhx/cLgkoKIQtAEnjs6zReQyYQYMUUKRu3Lihu3fvyrZthUIhLV++XM+f\nP9f69ev1008/6dq1a+rp6VFJSYmqqqq0Z88eXbx4UXPmzNGTJ0+UzWa1d+9e/fjjj26/FGDWY2QL\nFKEnT56os7NTjY2Nev/+vY4cOaLKysrc+tHRUXV1dam5uVmS9ObNm9y6wcFBnT17Vv39/Tp58qTO\nnz+v0lL+lQCfQoMUUIT++ecf1dTUaM6cOZo3b56qq6snXKbS7/errKxMly9f1sOHD1VWVpZbt2HD\nBknSkiVL9O233yqVSs14/YDXELYAPlJSUqKGhgb9/PPPevTokRoaGvI+znEcrqgFTAFhCxSh1atX\nq6urS+/evVM2m9WjR48mhObY2JjevHmjdevWad++fXr27Flu3f379+U4jvr7+/Xy5UuukgVMASda\ngCL0/fffq7a2VocPH5Zt2xPO10pSNpvVX3/9pXfv3kmS9u3bl1u3ePFiHT9+XNlsVgcOHOB8LTAF\ndCMDmLKLFy/mupUBTB2HkQEAMIyRLQAAhjGyBQDAMMIWAADDCFsAAAwjbAEAMIywBQDAMMIWAADD\n/gcQzu5af1FahAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38e0250fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots(mtcars,'disp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>20.090625</td>\n",
       "      <td>6.187500</td>\n",
       "      <td>230.721875</td>\n",
       "      <td>146.687500</td>\n",
       "      <td>3.596563</td>\n",
       "      <td>3.217250</td>\n",
       "      <td>17.848750</td>\n",
       "      <td>0.437500</td>\n",
       "      <td>0.406250</td>\n",
       "      <td>3.687500</td>\n",
       "      <td>2.8125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.026948</td>\n",
       "      <td>1.785922</td>\n",
       "      <td>123.938694</td>\n",
       "      <td>68.562868</td>\n",
       "      <td>0.534679</td>\n",
       "      <td>0.978457</td>\n",
       "      <td>1.786943</td>\n",
       "      <td>0.504016</td>\n",
       "      <td>0.498991</td>\n",
       "      <td>0.737804</td>\n",
       "      <td>1.6152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10.400000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>71.100000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>2.760000</td>\n",
       "      <td>1.513000</td>\n",
       "      <td>14.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>15.425000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>120.825000</td>\n",
       "      <td>96.500000</td>\n",
       "      <td>3.080000</td>\n",
       "      <td>2.581250</td>\n",
       "      <td>16.892500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>19.200000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>196.300000</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>3.695000</td>\n",
       "      <td>3.325000</td>\n",
       "      <td>17.710000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>22.800000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>326.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>3.920000</td>\n",
       "      <td>3.610000</td>\n",
       "      <td>18.900000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>33.900000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>472.000000</td>\n",
       "      <td>335.000000</td>\n",
       "      <td>4.930000</td>\n",
       "      <td>5.424000</td>\n",
       "      <td>22.900000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>8.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mpg        cyl        disp          hp       drat         wt  \\\n",
       "count  32.000000  32.000000   32.000000   32.000000  32.000000  32.000000   \n",
       "mean   20.090625   6.187500  230.721875  146.687500   3.596563   3.217250   \n",
       "std     6.026948   1.785922  123.938694   68.562868   0.534679   0.978457   \n",
       "min    10.400000   4.000000   71.100000   52.000000   2.760000   1.513000   \n",
       "25%    15.425000   4.000000  120.825000   96.500000   3.080000   2.581250   \n",
       "50%    19.200000   6.000000  196.300000  123.000000   3.695000   3.325000   \n",
       "75%    22.800000   8.000000  326.000000  180.000000   3.920000   3.610000   \n",
       "max    33.900000   8.000000  472.000000  335.000000   4.930000   5.424000   \n",
       "\n",
       "            qsec         vs         am       gear     carb  \n",
       "count  32.000000  32.000000  32.000000  32.000000  32.0000  \n",
       "mean   17.848750   0.437500   0.406250   3.687500   2.8125  \n",
       "std     1.786943   0.504016   0.498991   0.737804   1.6152  \n",
       "min    14.500000   0.000000   0.000000   3.000000   1.0000  \n",
       "25%    16.892500   0.000000   0.000000   3.000000   2.0000  \n",
       "50%    17.710000   0.000000   0.000000   4.000000   2.0000  \n",
       "75%    18.900000   1.000000   1.000000   4.000000   4.0000  \n",
       "max    22.900000   1.000000   1.000000   5.000000   8.0000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtcars.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.852162</td>\n",
       "      <td>-0.847551</td>\n",
       "      <td>-0.776168</td>\n",
       "      <td>0.681172</td>\n",
       "      <td>-0.867659</td>\n",
       "      <td>0.418684</td>\n",
       "      <td>0.664039</td>\n",
       "      <td>0.599832</td>\n",
       "      <td>0.480285</td>\n",
       "      <td>-0.550925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cyl</th>\n",
       "      <td>-0.852162</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.902033</td>\n",
       "      <td>0.832447</td>\n",
       "      <td>-0.699938</td>\n",
       "      <td>0.782496</td>\n",
       "      <td>-0.591242</td>\n",
       "      <td>-0.810812</td>\n",
       "      <td>-0.522607</td>\n",
       "      <td>-0.492687</td>\n",
       "      <td>0.526988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disp</th>\n",
       "      <td>-0.847551</td>\n",
       "      <td>0.902033</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.790949</td>\n",
       "      <td>-0.710214</td>\n",
       "      <td>0.887980</td>\n",
       "      <td>-0.433698</td>\n",
       "      <td>-0.710416</td>\n",
       "      <td>-0.591227</td>\n",
       "      <td>-0.555569</td>\n",
       "      <td>0.394977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hp</th>\n",
       "      <td>-0.776168</td>\n",
       "      <td>0.832447</td>\n",
       "      <td>0.790949</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.448759</td>\n",
       "      <td>0.658748</td>\n",
       "      <td>-0.708223</td>\n",
       "      <td>-0.723097</td>\n",
       "      <td>-0.243204</td>\n",
       "      <td>-0.125704</td>\n",
       "      <td>0.749812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drat</th>\n",
       "      <td>0.681172</td>\n",
       "      <td>-0.699938</td>\n",
       "      <td>-0.710214</td>\n",
       "      <td>-0.448759</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.712441</td>\n",
       "      <td>0.091205</td>\n",
       "      <td>0.440278</td>\n",
       "      <td>0.712711</td>\n",
       "      <td>0.699610</td>\n",
       "      <td>-0.090790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wt</th>\n",
       "      <td>-0.867659</td>\n",
       "      <td>0.782496</td>\n",
       "      <td>0.887980</td>\n",
       "      <td>0.658748</td>\n",
       "      <td>-0.712441</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.174716</td>\n",
       "      <td>-0.554916</td>\n",
       "      <td>-0.692495</td>\n",
       "      <td>-0.583287</td>\n",
       "      <td>0.427606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>qsec</th>\n",
       "      <td>0.418684</td>\n",
       "      <td>-0.591242</td>\n",
       "      <td>-0.433698</td>\n",
       "      <td>-0.708223</td>\n",
       "      <td>0.091205</td>\n",
       "      <td>-0.174716</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.744535</td>\n",
       "      <td>-0.229861</td>\n",
       "      <td>-0.212682</td>\n",
       "      <td>-0.656249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vs</th>\n",
       "      <td>0.664039</td>\n",
       "      <td>-0.810812</td>\n",
       "      <td>-0.710416</td>\n",
       "      <td>-0.723097</td>\n",
       "      <td>0.440278</td>\n",
       "      <td>-0.554916</td>\n",
       "      <td>0.744535</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.168345</td>\n",
       "      <td>0.206023</td>\n",
       "      <td>-0.569607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>am</th>\n",
       "      <td>0.599832</td>\n",
       "      <td>-0.522607</td>\n",
       "      <td>-0.591227</td>\n",
       "      <td>-0.243204</td>\n",
       "      <td>0.712711</td>\n",
       "      <td>-0.692495</td>\n",
       "      <td>-0.229861</td>\n",
       "      <td>0.168345</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.794059</td>\n",
       "      <td>0.057534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gear</th>\n",
       "      <td>0.480285</td>\n",
       "      <td>-0.492687</td>\n",
       "      <td>-0.555569</td>\n",
       "      <td>-0.125704</td>\n",
       "      <td>0.699610</td>\n",
       "      <td>-0.583287</td>\n",
       "      <td>-0.212682</td>\n",
       "      <td>0.206023</td>\n",
       "      <td>0.794059</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.274073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carb</th>\n",
       "      <td>-0.550925</td>\n",
       "      <td>0.526988</td>\n",
       "      <td>0.394977</td>\n",
       "      <td>0.749812</td>\n",
       "      <td>-0.090790</td>\n",
       "      <td>0.427606</td>\n",
       "      <td>-0.656249</td>\n",
       "      <td>-0.569607</td>\n",
       "      <td>0.057534</td>\n",
       "      <td>0.274073</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           mpg       cyl      disp        hp      drat        wt      qsec  \\\n",
       "mpg   1.000000 -0.852162 -0.847551 -0.776168  0.681172 -0.867659  0.418684   \n",
       "cyl  -0.852162  1.000000  0.902033  0.832447 -0.699938  0.782496 -0.591242   \n",
       "disp -0.847551  0.902033  1.000000  0.790949 -0.710214  0.887980 -0.433698   \n",
       "hp   -0.776168  0.832447  0.790949  1.000000 -0.448759  0.658748 -0.708223   \n",
       "drat  0.681172 -0.699938 -0.710214 -0.448759  1.000000 -0.712441  0.091205   \n",
       "wt   -0.867659  0.782496  0.887980  0.658748 -0.712441  1.000000 -0.174716   \n",
       "qsec  0.418684 -0.591242 -0.433698 -0.708223  0.091205 -0.174716  1.000000   \n",
       "vs    0.664039 -0.810812 -0.710416 -0.723097  0.440278 -0.554916  0.744535   \n",
       "am    0.599832 -0.522607 -0.591227 -0.243204  0.712711 -0.692495 -0.229861   \n",
       "gear  0.480285 -0.492687 -0.555569 -0.125704  0.699610 -0.583287 -0.212682   \n",
       "carb -0.550925  0.526988  0.394977  0.749812 -0.090790  0.427606 -0.656249   \n",
       "\n",
       "            vs        am      gear      carb  \n",
       "mpg   0.664039  0.599832  0.480285 -0.550925  \n",
       "cyl  -0.810812 -0.522607 -0.492687  0.526988  \n",
       "disp -0.710416 -0.591227 -0.555569  0.394977  \n",
       "hp   -0.723097 -0.243204 -0.125704  0.749812  \n",
       "drat  0.440278  0.712711  0.699610 -0.090790  \n",
       "wt   -0.554916 -0.692495 -0.583287  0.427606  \n",
       "qsec  0.744535 -0.229861 -0.212682 -0.656249  \n",
       "vs    1.000000  0.168345  0.206023 -0.569607  \n",
       "am    0.168345  1.000000  0.794059  0.057534  \n",
       "gear  0.206023  0.794059  1.000000  0.274073  \n",
       "carb -0.569607  0.057534  0.274073  1.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtcars.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>drat</th>\n",
       "      <th>wt</th>\n",
       "      <th>qsec</th>\n",
       "      <th>vs</th>\n",
       "      <th>am</th>\n",
       "      <th>gear</th>\n",
       "      <th>carb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cyl</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disp</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hp</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drat</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wt</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>qsec</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vs</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>am</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gear</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carb</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        mpg    cyl   disp     hp   drat     wt   qsec     vs     am   gear  \\\n",
       "mpg    True  False  False  False   True  False  False   True   True  False   \n",
       "cyl   False   True   True   True  False   True  False  False  False  False   \n",
       "disp  False   True   True   True  False   True  False  False  False  False   \n",
       "hp    False   True   True   True  False   True  False  False  False  False   \n",
       "drat   True  False  False  False   True  False  False  False   True   True   \n",
       "wt    False   True   True   True  False   True  False  False  False  False   \n",
       "qsec  False  False  False  False  False  False   True   True  False  False   \n",
       "vs     True  False  False  False  False  False   True   True  False  False   \n",
       "am     True  False  False  False   True  False  False  False   True   True   \n",
       "gear  False  False  False  False   True  False  False  False   True   True   \n",
       "carb  False   True  False   True  False  False  False  False  False  False   \n",
       "\n",
       "       carb  \n",
       "mpg   False  \n",
       "cyl    True  \n",
       "disp  False  \n",
       "hp     True  \n",
       "drat  False  \n",
       "wt    False  \n",
       "qsec  False  \n",
       "vs    False  \n",
       "am    False  \n",
       "gear  False  \n",
       "carb   True  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtcars.corr() > 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2b73cf5ad0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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xA9C/XwiCgF2tX8hK4sYmXyvzS9K2V0vsv/vOWknt3ryqXpXzZcKYFXtA2rA7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\nYlVkA8/zGAgH0TrQCz8flvw+BoNRtNU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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b74575550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mtcars.plot(kind='hexbin', x='disp', y='hp', gridsize=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
     ]
    },
    {
     "data": {
      "image/png": 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vV2VlpR5//HFJ0rx583TNNddo7dq1amxsVGlpqerq6iRJlZWVmjJlilasWCGP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\nRqOuOG79ZYvFYqddv5COm9/vl3TsDJB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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b75082910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8739037710981)>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = ggplot(aes(x='disp', y='hp',color=\"carb\"), data=mtcars)\n",
    "p + geom_point()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ΔΕΥΤΕΡΟ ΠΑΡΑΔΕΙΓΜΑ: Τα δεδομένα diamonds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([u'Unnamed: 0', u'carat', u'cut', u'color', u'clarity', u'depth',\n",
      "       u'table', u'price', u'x', u'y', u'z'],\n",
      "      dtype='object')\n",
      "(53940, 11)\n",
      "53940\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 53940 entries, 0 to 53939\n",
      "Data columns (total 11 columns):\n",
      "Unnamed: 0    53940 non-null int64\n",
      "carat         53940 non-null float64\n",
      "cut           53940 non-null object\n",
      "color         53940 non-null object\n",
      "clarity       53940 non-null object\n",
      "depth         53940 non-null float64\n",
      "table         53940 non-null float64\n",
      "price         53940 non-null int64\n",
      "x             53940 non-null float64\n",
      "y             53940 non-null float64\n",
      "z             53940 non-null float64\n",
      "dtypes: float64(6), int64(2), object(3)\n",
      "memory usage: 4.9+ MB\n"
     ]
    }
   ],
   "source": [
    "diamonds = pd.read_csv(\"https://vincentarelbundock.github.io/Rdatasets/csv/ggplot2/diamonds.csv\")\n",
    "print diamonds.columns\n",
    "print diamonds.shape\n",
    "print len(diamonds)\n",
    "diamonds.info() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.24</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>VVS2</td>\n",
       "      <td>62.8</td>\n",
       "      <td>57</td>\n",
       "      <td>336</td>\n",
       "      <td>3.94</td>\n",
       "      <td>3.96</td>\n",
       "      <td>2.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.24</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>I</td>\n",
       "      <td>VVS1</td>\n",
       "      <td>62.3</td>\n",
       "      <td>57</td>\n",
       "      <td>336</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.26</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>H</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.9</td>\n",
       "      <td>55</td>\n",
       "      <td>337</td>\n",
       "      <td>4.07</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.22</td>\n",
       "      <td>Fair</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>65.1</td>\n",
       "      <td>61</td>\n",
       "      <td>337</td>\n",
       "      <td>3.87</td>\n",
       "      <td>3.78</td>\n",
       "      <td>2.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>H</td>\n",
       "      <td>VS1</td>\n",
       "      <td>59.4</td>\n",
       "      <td>61</td>\n",
       "      <td>338</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.05</td>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>64.0</td>\n",
       "      <td>55</td>\n",
       "      <td>339</td>\n",
       "      <td>4.25</td>\n",
       "      <td>4.28</td>\n",
       "      <td>2.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>J</td>\n",
       "      <td>VS1</td>\n",
       "      <td>62.8</td>\n",
       "      <td>56</td>\n",
       "      <td>340</td>\n",
       "      <td>3.93</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.22</td>\n",
       "      <td>Premium</td>\n",
       "      <td>F</td>\n",
       "      <td>SI1</td>\n",
       "      <td>60.4</td>\n",
       "      <td>61</td>\n",
       "      <td>342</td>\n",
       "      <td>3.88</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>54</td>\n",
       "      <td>344</td>\n",
       "      <td>4.35</td>\n",
       "      <td>4.37</td>\n",
       "      <td>2.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.20</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>60.2</td>\n",
       "      <td>62</td>\n",
       "      <td>345</td>\n",
       "      <td>3.79</td>\n",
       "      <td>3.75</td>\n",
       "      <td>2.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.32</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>I1</td>\n",
       "      <td>60.9</td>\n",
       "      <td>58</td>\n",
       "      <td>345</td>\n",
       "      <td>4.38</td>\n",
       "      <td>4.42</td>\n",
       "      <td>2.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>I</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>54</td>\n",
       "      <td>348</td>\n",
       "      <td>4.31</td>\n",
       "      <td>4.34</td>\n",
       "      <td>2.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.4</td>\n",
       "      <td>54</td>\n",
       "      <td>351</td>\n",
       "      <td>4.23</td>\n",
       "      <td>4.29</td>\n",
       "      <td>2.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.8</td>\n",
       "      <td>56</td>\n",
       "      <td>351</td>\n",
       "      <td>4.23</td>\n",
       "      <td>4.26</td>\n",
       "      <td>2.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.7</td>\n",
       "      <td>59</td>\n",
       "      <td>351</td>\n",
       "      <td>4.21</td>\n",
       "      <td>4.27</td>\n",
       "      <td>2.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Good</td>\n",
       "      <td>I</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>56</td>\n",
       "      <td>351</td>\n",
       "      <td>4.26</td>\n",
       "      <td>4.30</td>\n",
       "      <td>2.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>63.8</td>\n",
       "      <td>55</td>\n",
       "      <td>352</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.92</td>\n",
       "      <td>2.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>H</td>\n",
       "      <td>VS1</td>\n",
       "      <td>61.0</td>\n",
       "      <td>57</td>\n",
       "      <td>353</td>\n",
       "      <td>3.94</td>\n",
       "      <td>3.96</td>\n",
       "      <td>2.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.4</td>\n",
       "      <td>62</td>\n",
       "      <td>353</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>58.1</td>\n",
       "      <td>62</td>\n",
       "      <td>353</td>\n",
       "      <td>4.44</td>\n",
       "      <td>4.47</td>\n",
       "      <td>2.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>G</td>\n",
       "      <td>VVS2</td>\n",
       "      <td>60.4</td>\n",
       "      <td>58</td>\n",
       "      <td>354</td>\n",
       "      <td>3.97</td>\n",
       "      <td>4.01</td>\n",
       "      <td>2.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.24</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS1</td>\n",
       "      <td>62.5</td>\n",
       "      <td>57</td>\n",
       "      <td>355</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.94</td>\n",
       "      <td>2.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.30</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>57</td>\n",
       "      <td>357</td>\n",
       "      <td>4.28</td>\n",
       "      <td>4.30</td>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>D</td>\n",
       "      <td>VS2</td>\n",
       "      <td>60.5</td>\n",
       "      <td>61</td>\n",
       "      <td>357</td>\n",
       "      <td>3.96</td>\n",
       "      <td>3.97</td>\n",
       "      <td>2.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>F</td>\n",
       "      <td>VS1</td>\n",
       "      <td>60.9</td>\n",
       "      <td>57</td>\n",
       "      <td>357</td>\n",
       "      <td>3.96</td>\n",
       "      <td>3.99</td>\n",
       "      <td>2.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53910</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>60.5</td>\n",
       "      <td>58</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.74</td>\n",
       "      <td>5.77</td>\n",
       "      <td>3.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53911</th>\n",
       "      <td>0.57</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>IF</td>\n",
       "      <td>59.8</td>\n",
       "      <td>60</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.43</td>\n",
       "      <td>5.38</td>\n",
       "      <td>3.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53912</th>\n",
       "      <td>0.61</td>\n",
       "      <td>Premium</td>\n",
       "      <td>F</td>\n",
       "      <td>VVS1</td>\n",
       "      <td>61.8</td>\n",
       "      <td>59</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.48</td>\n",
       "      <td>5.40</td>\n",
       "      <td>3.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53913</th>\n",
       "      <td>0.80</td>\n",
       "      <td>Good</td>\n",
       "      <td>G</td>\n",
       "      <td>VS2</td>\n",
       "      <td>64.2</td>\n",
       "      <td>58</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.84</td>\n",
       "      <td>5.81</td>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53914</th>\n",
       "      <td>0.84</td>\n",
       "      <td>Good</td>\n",
       "      <td>I</td>\n",
       "      <td>VS1</td>\n",
       "      <td>63.7</td>\n",
       "      <td>59</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.94</td>\n",
       "      <td>5.90</td>\n",
       "      <td>3.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53915</th>\n",
       "      <td>0.77</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.1</td>\n",
       "      <td>56</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.84</td>\n",
       "      <td>5.86</td>\n",
       "      <td>3.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53916</th>\n",
       "      <td>0.74</td>\n",
       "      <td>Good</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.1</td>\n",
       "      <td>59</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.71</td>\n",
       "      <td>5.74</td>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53917</th>\n",
       "      <td>0.90</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.2</td>\n",
       "      <td>60</td>\n",
       "      <td>2753</td>\n",
       "      <td>6.12</td>\n",
       "      <td>6.09</td>\n",
       "      <td>3.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53918</th>\n",
       "      <td>0.76</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS1</td>\n",
       "      <td>59.3</td>\n",
       "      <td>62</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.93</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53919</th>\n",
       "      <td>0.76</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>I</td>\n",
       "      <td>VVS1</td>\n",
       "      <td>62.2</td>\n",
       "      <td>55</td>\n",
       "      <td>2753</td>\n",
       "      <td>5.89</td>\n",
       "      <td>5.87</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53920</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>60</td>\n",
       "      <td>2755</td>\n",
       "      <td>5.57</td>\n",
       "      <td>5.61</td>\n",
       "      <td>3.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53921</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.8</td>\n",
       "      <td>60</td>\n",
       "      <td>2755</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.65</td>\n",
       "      <td>3.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53922</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>D</td>\n",
       "      <td>VS1</td>\n",
       "      <td>63.1</td>\n",
       "      <td>59</td>\n",
       "      <td>2755</td>\n",
       "      <td>5.67</td>\n",
       "      <td>5.58</td>\n",
       "      <td>3.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53923</th>\n",
       "      <td>0.73</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.3</td>\n",
       "      <td>56</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.80</td>\n",
       "      <td>5.84</td>\n",
       "      <td>3.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53924</th>\n",
       "      <td>0.73</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.6</td>\n",
       "      <td>55</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.82</td>\n",
       "      <td>5.84</td>\n",
       "      <td>3.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53925</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>I</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.6</td>\n",
       "      <td>56</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.95</td>\n",
       "      <td>5.97</td>\n",
       "      <td>3.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53926</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.9</td>\n",
       "      <td>56</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.71</td>\n",
       "      <td>5.73</td>\n",
       "      <td>3.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53927</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Good</td>\n",
       "      <td>F</td>\n",
       "      <td>SI1</td>\n",
       "      <td>58.1</td>\n",
       "      <td>59</td>\n",
       "      <td>2756</td>\n",
       "      <td>6.06</td>\n",
       "      <td>6.13</td>\n",
       "      <td>3.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53928</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.4</td>\n",
       "      <td>58</td>\n",
       "      <td>2756</td>\n",
       "      <td>6.03</td>\n",
       "      <td>5.96</td>\n",
       "      <td>3.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53929</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>VS1</td>\n",
       "      <td>61.4</td>\n",
       "      <td>56</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.76</td>\n",
       "      <td>5.73</td>\n",
       "      <td>3.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53930</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>60.5</td>\n",
       "      <td>55</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.79</td>\n",
       "      <td>5.74</td>\n",
       "      <td>3.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53931</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Premium</td>\n",
       "      <td>F</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>62</td>\n",
       "      <td>2756</td>\n",
       "      <td>5.74</td>\n",
       "      <td>5.73</td>\n",
       "      <td>3.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53932</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>60.5</td>\n",
       "      <td>59</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.71</td>\n",
       "      <td>5.76</td>\n",
       "      <td>3.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53933</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.2</td>\n",
       "      <td>59</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.69</td>\n",
       "      <td>5.72</td>\n",
       "      <td>3.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53934</th>\n",
       "      <td>0.72</td>\n",
       "      <td>Premium</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.7</td>\n",
       "      <td>59</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.69</td>\n",
       "      <td>5.73</td>\n",
       "      <td>3.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53935</th>\n",
       "      <td>0.72</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>60.8</td>\n",
       "      <td>57</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.75</td>\n",
       "      <td>5.76</td>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53936</th>\n",
       "      <td>0.72</td>\n",
       "      <td>Good</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.1</td>\n",
       "      <td>55</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.69</td>\n",
       "      <td>5.75</td>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53937</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.8</td>\n",
       "      <td>60</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.66</td>\n",
       "      <td>5.68</td>\n",
       "      <td>3.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53938</th>\n",
       "      <td>0.86</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.0</td>\n",
       "      <td>58</td>\n",
       "      <td>2757</td>\n",
       "      <td>6.15</td>\n",
       "      <td>6.12</td>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53939</th>\n",
       "      <td>0.75</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>55</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.83</td>\n",
       "      <td>5.87</td>\n",
       "      <td>3.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>53940 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       carat        cut color clarity  depth  table  price     x     y     z\n",
       "0       0.23      Ideal     E     SI2   61.5     55    326  3.95  3.98  2.43\n",
       "1       0.21    Premium     E     SI1   59.8     61    326  3.89  3.84  2.31\n",
       "2       0.23       Good     E     VS1   56.9     65    327  4.05  4.07  2.31\n",
       "3       0.29    Premium     I     VS2   62.4     58    334  4.20  4.23  2.63\n",
       "4       0.31       Good     J     SI2   63.3     58    335  4.34  4.35  2.75\n",
       "5       0.24  Very Good     J    VVS2   62.8     57    336  3.94  3.96  2.48\n",
       "6       0.24  Very Good     I    VVS1   62.3     57    336  3.95  3.98  2.47\n",
       "7       0.26  Very Good     H     SI1   61.9     55    337  4.07  4.11  2.53\n",
       "8       0.22       Fair     E     VS2   65.1     61    337  3.87  3.78  2.49\n",
       "9       0.23  Very Good     H     VS1   59.4     61    338  4.00  4.05  2.39\n",
       "10      0.30       Good     J     SI1   64.0     55    339  4.25  4.28  2.73\n",
       "11      0.23      Ideal     J     VS1   62.8     56    340  3.93  3.90  2.46\n",
       "12      0.22    Premium     F     SI1   60.4     61    342  3.88  3.84  2.33\n",
       "13      0.31      Ideal     J     SI2   62.2     54    344  4.35  4.37  2.71\n",
       "14      0.20    Premium     E     SI2   60.2     62    345  3.79  3.75  2.27\n",
       "15      0.32    Premium     E      I1   60.9     58    345  4.38  4.42  2.68\n",
       "16      0.30      Ideal     I     SI2   62.0     54    348  4.31  4.34  2.68\n",
       "17      0.30       Good     J     SI1   63.4     54    351  4.23  4.29  2.70\n",
       "18      0.30       Good     J     SI1   63.8     56    351  4.23  4.26  2.71\n",
       "19      0.30  Very Good     J     SI1   62.7     59    351  4.21  4.27  2.66\n",
       "20      0.30       Good     I     SI2   63.3     56    351  4.26  4.30  2.71\n",
       "21      0.23  Very Good     E     VS2   63.8     55    352  3.85  3.92  2.48\n",
       "22      0.23  Very Good     H     VS1   61.0     57    353  3.94  3.96  2.41\n",
       "23      0.31  Very Good     J     SI1   59.4     62    353  4.39  4.43  2.62\n",
       "24      0.31  Very Good     J     SI1   58.1     62    353  4.44  4.47  2.59\n",
       "25      0.23  Very Good     G    VVS2   60.4     58    354  3.97  4.01  2.41\n",
       "26      0.24    Premium     I     VS1   62.5     57    355  3.97  3.94  2.47\n",
       "27      0.30  Very Good     J     VS2   62.2     57    357  4.28  4.30  2.67\n",
       "28      0.23  Very Good     D     VS2   60.5     61    357  3.96  3.97  2.40\n",
       "29      0.23  Very Good     F     VS1   60.9     57    357  3.96  3.99  2.42\n",
       "...      ...        ...   ...     ...    ...    ...    ...   ...   ...   ...\n",
       "53910   0.70    Premium     E     SI1   60.5     58   2753  5.74  5.77  3.48\n",
       "53911   0.57    Premium     E      IF   59.8     60   2753  5.43  5.38  3.23\n",
       "53912   0.61    Premium     F    VVS1   61.8     59   2753  5.48  5.40  3.36\n",
       "53913   0.80       Good     G     VS2   64.2     58   2753  5.84  5.81  3.74\n",
       "53914   0.84       Good     I     VS1   63.7     59   2753  5.94  5.90  3.77\n",
       "53915   0.77      Ideal     E     SI2   62.1     56   2753  5.84  5.86  3.63\n",
       "53916   0.74       Good     D     SI1   63.1     59   2753  5.71  5.74  3.61\n",
       "53917   0.90  Very Good     J     SI1   63.2     60   2753  6.12  6.09  3.86\n",
       "53918   0.76    Premium     I     VS1   59.3     62   2753  5.93  5.85  3.49\n",
       "53919   0.76      Ideal     I    VVS1   62.2     55   2753  5.89  5.87  3.66\n",
       "53920   0.70  Very Good     E     VS2   62.4     60   2755  5.57  5.61  3.49\n",
       "53921   0.70  Very Good     E     VS2   62.8     60   2755  5.59  5.65  3.53\n",
       "53922   0.70  Very Good     D     VS1   63.1     59   2755  5.67  5.58  3.55\n",
       "53923   0.73      Ideal     I     VS2   61.3     56   2756  5.80  5.84  3.57\n",
       "53924   0.73      Ideal     I     VS2   61.6     55   2756  5.82  5.84  3.59\n",
       "53925   0.79      Ideal     I     SI1   61.6     56   2756  5.95  5.97  3.67\n",
       "53926   0.71      Ideal     E     SI1   61.9     56   2756  5.71  5.73  3.54\n",
       "53927   0.79       Good     F     SI1   58.1     59   2756  6.06  6.13  3.54\n",
       "53928   0.79    Premium     E     SI2   61.4     58   2756  6.03  5.96  3.68\n",
       "53929   0.71      Ideal     G     VS1   61.4     56   2756  5.76  5.73  3.53\n",
       "53930   0.71    Premium     E     SI1   60.5     55   2756  5.79  5.74  3.49\n",
       "53931   0.71    Premium     F     SI1   59.8     62   2756  5.74  5.73  3.43\n",
       "53932   0.70  Very Good     E     VS2   60.5     59   2757  5.71  5.76  3.47\n",
       "53933   0.70  Very Good     E     VS2   61.2     59   2757  5.69  5.72  3.49\n",
       "53934   0.72    Premium     D     SI1   62.7     59   2757  5.69  5.73  3.58\n",
       "53935   0.72      Ideal     D     SI1   60.8     57   2757  5.75  5.76  3.50\n",
       "53936   0.72       Good     D     SI1   63.1     55   2757  5.69  5.75  3.61\n",
       "53937   0.70  Very Good     D     SI1   62.8     60   2757  5.66  5.68  3.56\n",
       "53938   0.86    Premium     H     SI2   61.0     58   2757  6.15  6.12  3.74\n",
       "53939   0.75      Ideal     D     SI2   62.2     55   2757  5.83  5.87  3.64\n",
       "\n",
       "[53940 rows x 10 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[43044 14017 42996 53531 15133]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py:1: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "rows = np.random.choice(diamonds.index.values, round(0.0001*len(diamonds)))\n",
    "print rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43044</th>\n",
       "      <td>0.51</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>H</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.6</td>\n",
       "      <td>55</td>\n",
       "      <td>1375</td>\n",
       "      <td>5.16</td>\n",
       "      <td>5.19</td>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14017</th>\n",
       "      <td>1.01</td>\n",
       "      <td>Good</td>\n",
       "      <td>G</td>\n",
       "      <td>VS2</td>\n",
       "      <td>57.5</td>\n",
       "      <td>62</td>\n",
       "      <td>5701</td>\n",
       "      <td>6.58</td>\n",
       "      <td>6.53</td>\n",
       "      <td>3.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42996</th>\n",
       "      <td>0.55</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>F</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.0</td>\n",
       "      <td>58</td>\n",
       "      <td>1368</td>\n",
       "      <td>5.25</td>\n",
       "      <td>5.28</td>\n",
       "      <td>3.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53531</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.6</td>\n",
       "      <td>56</td>\n",
       "      <td>2690</td>\n",
       "      <td>5.78</td>\n",
       "      <td>5.82</td>\n",
       "      <td>3.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15133</th>\n",
       "      <td>1.25</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.0</td>\n",
       "      <td>59</td>\n",
       "      <td>6084</td>\n",
       "      <td>6.98</td>\n",
       "      <td>6.89</td>\n",
       "      <td>4.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       carat      cut color clarity  depth  table  price     x     y     z\n",
       "43044   0.51    Ideal     H     VS2   61.6     55   1375  5.16  5.19  3.19\n",
       "14017   1.01     Good     G     VS2   57.5     62   5701  6.58  6.53  3.77\n",
       "42996   0.55    Ideal     F     SI1   61.0     58   1368  5.25  5.28  3.21\n",
       "53531   0.71    Ideal     D     SI2   61.6     56   2690  5.78  5.82  3.57\n",
       "15133   1.25  Premium     I     VS2   61.0     59   6084  6.98  6.89  4.23"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds.ix[rows]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "diamonds = diamonds.dropna(how='any') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# plots(diamonds,'price')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f38a69d5cd0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ngQcewDAM/H4/F154IVOmTGH8+PEsW7aMzZs3M2LECMrLywEYM2YMF1xwAeXl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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38a6912a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diamonds['price'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 25335.,   9328.,   7393.,   3878.,   2364.,   1745.,   1306.,\n",
       "          1002.,    863.,    726.]),\n",
       " array([   326. ,   2175.7,   4025.4,   5875.1,   7724.8,   9574.5,\n",
       "         11424.2,  13273.9,  15123.6,  16973.3,  18823. ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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S+/g248tjY2MMDw//21nKVAMfHBycsGyPpmYzJCNSqVHuPtCfhcTj8Uyqp8yOammW6mmW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\nX/twkDKzqQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38a6909890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(diamonds.price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f38a713ce50>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JkyfV39+vJ554QiUlJVqzZo3KysrU0NCgzMxM+f1+SVJ2drbuuOMO+f1+OZ1OrV+/PnzK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\nALAdwgkAYDuEEwDAdv4/kAHS3/tIXrcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38a71f5810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "diamonds['price'].plot(kind='hist', stacked=True, bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'boxes': [<matplotlib.lines.Line2D at 0x7f38a73f76d0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7f38a7406510>,\n",
       "  <matplotlib.lines.Line2D at 0x7f38a7406b50>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7f38a724d810>],\n",
       " 'means': [],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7f38a724d1d0>],\n",
       " 'whiskers': [<matplotlib.lines.Line2D at 0x7f38a73f77d0>,\n",
       "  <matplotlib.lines.Line2D at 0x7f38a73f7e90>]}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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//n39+eefevXVV7V9+3b19PRIknp6etTQ0CBJamho0JUrVzQ9Pa07d+5oZGRE0WhUgUBA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\ngCEKAABDFAAAhigAAMx/ASWGKmwAmglQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38a7b6b250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(diamonds.price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>26970.500000</td>\n",
       "      <td>0.797940</td>\n",
       "      <td>61.749405</td>\n",
       "      <td>57.457184</td>\n",
       "      <td>3932.799722</td>\n",
       "      <td>5.731157</td>\n",
       "      <td>5.734526</td>\n",
       "      <td>3.538734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15571.281097</td>\n",
       "      <td>0.474011</td>\n",
       "      <td>1.432621</td>\n",
       "      <td>2.234491</td>\n",
       "      <td>3989.439738</td>\n",
       "      <td>1.121761</td>\n",
       "      <td>1.142135</td>\n",
       "      <td>0.705699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>326.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13485.750000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>950.000000</td>\n",
       "      <td>4.710000</td>\n",
       "      <td>4.720000</td>\n",
       "      <td>2.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>26970.500000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>61.800000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>2401.000000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>5.710000</td>\n",
       "      <td>3.530000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>40455.250000</td>\n",
       "      <td>1.040000</td>\n",
       "      <td>62.500000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>5324.250000</td>\n",
       "      <td>6.540000</td>\n",
       "      <td>6.540000</td>\n",
       "      <td>4.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>53940.000000</td>\n",
       "      <td>5.010000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>18823.000000</td>\n",
       "      <td>10.740000</td>\n",
       "      <td>58.900000</td>\n",
       "      <td>31.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0         carat         depth         table         price  \\\n",
       "count  53940.000000  53940.000000  53940.000000  53940.000000  53940.000000   \n",
       "mean   26970.500000      0.797940     61.749405     57.457184   3932.799722   \n",
       "std    15571.281097      0.474011      1.432621      2.234491   3989.439738   \n",
       "min        1.000000      0.200000     43.000000     43.000000    326.000000   \n",
       "25%    13485.750000      0.400000     61.000000     56.000000    950.000000   \n",
       "50%    26970.500000      0.700000     61.800000     57.000000   2401.000000   \n",
       "75%    40455.250000      1.040000     62.500000     59.000000   5324.250000   \n",
       "max    53940.000000      5.010000     79.000000     95.000000  18823.000000   \n",
       "\n",
       "                  x             y             z  \n",
       "count  53940.000000  53940.000000  53940.000000  \n",
       "mean       5.731157      5.734526      3.538734  \n",
       "std        1.121761      1.142135      0.705699  \n",
       "min        0.000000      0.000000      0.000000  \n",
       "25%        4.710000      4.720000      2.910000  \n",
       "50%        5.700000      5.710000      3.530000  \n",
       "75%        6.540000      6.540000      4.040000  \n",
       "max       10.740000     58.900000     31.800000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.377983</td>\n",
       "      <td>-0.034800</td>\n",
       "      <td>-0.100830</td>\n",
       "      <td>-0.306873</td>\n",
       "      <td>-0.405440</td>\n",
       "      <td>-0.395843</td>\n",
       "      <td>-0.399208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carat</th>\n",
       "      <td>-0.377983</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.028224</td>\n",
       "      <td>0.181618</td>\n",
       "      <td>0.921591</td>\n",
       "      <td>0.975094</td>\n",
       "      <td>0.951722</td>\n",
       "      <td>0.953387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>depth</th>\n",
       "      <td>-0.034800</td>\n",
       "      <td>0.028224</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.295779</td>\n",
       "      <td>-0.010647</td>\n",
       "      <td>-0.025289</td>\n",
       "      <td>-0.029341</td>\n",
       "      <td>0.094924</td>\n",
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       "    <tr>\n",
       "      <th>table</th>\n",
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       "      <td>0.181618</td>\n",
       "      <td>-0.295779</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.127134</td>\n",
       "      <td>0.195344</td>\n",
       "      <td>0.183760</td>\n",
       "      <td>0.150929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>-0.306873</td>\n",
       "      <td>0.921591</td>\n",
       "      <td>-0.010647</td>\n",
       "      <td>0.127134</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.884435</td>\n",
       "      <td>0.865421</td>\n",
       "      <td>0.861249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>-0.405440</td>\n",
       "      <td>0.975094</td>\n",
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       "      <td>0.195344</td>\n",
       "      <td>0.884435</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974701</td>\n",
       "      <td>0.970772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>-0.395843</td>\n",
       "      <td>0.951722</td>\n",
       "      <td>-0.029341</td>\n",
       "      <td>0.183760</td>\n",
       "      <td>0.865421</td>\n",
       "      <td>0.974701</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.952006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>z</th>\n",
       "      <td>-0.399208</td>\n",
       "      <td>0.953387</td>\n",
       "      <td>0.094924</td>\n",
       "      <td>0.150929</td>\n",
       "      <td>0.861249</td>\n",
       "      <td>0.970772</td>\n",
       "      <td>0.952006</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Unnamed: 0     carat     depth     table     price         x  \\\n",
       "Unnamed: 0    1.000000 -0.377983 -0.034800 -0.100830 -0.306873 -0.405440   \n",
       "carat        -0.377983  1.000000  0.028224  0.181618  0.921591  0.975094   \n",
       "depth        -0.034800  0.028224  1.000000 -0.295779 -0.010647 -0.025289   \n",
       "table        -0.100830  0.181618 -0.295779  1.000000  0.127134  0.195344   \n",
       "price        -0.306873  0.921591 -0.010647  0.127134  1.000000  0.884435   \n",
       "x            -0.405440  0.975094 -0.025289  0.195344  0.884435  1.000000   \n",
       "y            -0.395843  0.951722 -0.029341  0.183760  0.865421  0.974701   \n",
       "z            -0.399208  0.953387  0.094924  0.150929  0.861249  0.970772   \n",
       "\n",
       "                   y         z  \n",
       "Unnamed: 0 -0.395843 -0.399208  \n",
       "carat       0.951722  0.953387  \n",
       "depth      -0.029341  0.094924  \n",
       "table       0.183760  0.150929  \n",
       "price       0.865421  0.861249  \n",
       "x           0.974701  0.970772  \n",
       "y           1.000000  0.952006  \n",
       "z           0.952006  1.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carat</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>depth</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>table</th>\n",
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       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>z</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Unnamed: 0  carat  depth  table  price      x      y      z\n",
       "Unnamed: 0       True  False  False  False  False  False  False  False\n",
       "carat           False   True  False  False   True   True   True   True\n",
       "depth           False  False   True  False  False  False  False  False\n",
       "table           False  False  False   True  False  False  False  False\n",
       "price           False   True  False  False   True   True   True   True\n",
       "x               False   True  False  False   True   True   True   True\n",
       "y               False   True  False  False   True   True   True   True\n",
       "z               False   True  False  False   True   True   True   True"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds.corr() > 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fcd6b94ec50>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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zwzCMgn8LIZDL5QIxqFIRVBUyxdRKRVBldlQopppXfnEIeE9xeLKhSjHVa97c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\nCIJoIP4/PhB1+HLr1uAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd6ba156d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diamonds.plot(kind='hexbin', x='price', y='carat', gridsize=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kBrXDYWGPh8hR8wg9ltUq7ZvsJZrOJWftT3EwGKS6ulozfZLI5/ORm5tLbW2t2iGJ1A6p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\nr6NaZeowxpBtpVPqVvNq9EPCJkYnO49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TFZUV7QqrVrl8J/04LBoDJKvWP0eNMokioO6K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\nRERExGL/A/35b9R2DoN8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd6147be50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8782504967677)>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = ggplot(aes(x='price', y='carat',color=\"clarity\"), data=diamonds)\n",
    "p + geom_point()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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b7r//fk455RQqKyvp168ft99+O+eff/4BtxcIBJg8eTLPPPMMkydPPnCdSUm8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jyEXl/fKrRYoihujD15VuXV8vIe/dTMTYQxDTuJK8fw9SDWOIM/i6C6Vbp53X8g1sp/ZjGhT7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\nJ4VGEREREfH0/wGa7mEP7v98JgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd614439d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8782504589705)>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = ggplot(aes(x='price', y='carat',color=\"cut\"), data=diamonds)\n",
    "p + geom_point()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ΤΡΙΤΟ ΠΑΡΑΔΕΙΓΜΑ: Τα δεδομενα central.park"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data from R library UsingR \n",
    "\n",
    "* https://cran.r-project.org/web/packages/UsingR/UsingR.pdf \n",
    "* https://cran.r-project.org/doc/contrib/usingR.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: MASS\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: HistData\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: Hmisc\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: grid\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: lattice\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: survival\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: Loading required package: Formula\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: \n",
      "Attaching package: ‘Hmisc’\n",
      "\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: The following objects are masked from ‘package:base’:\n",
      "\n",
      "    format.pval, round.POSIXt, trunc.POSIXt, units\n",
      "\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n",
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: \n",
      "Attaching package: ‘UsingR’\n",
      "\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([u'DY', u'MAX', u'MIN', u'AVG', u'DEP', u'HDD', u'CDD', u'WTR', u'SNW',\n",
      "       u'DPTH', u'SPD', u'SPD1', u'DIR', u'MIN2', u'PSBL', u'S.S', u'WX',\n",
      "       u'SPD3', u'DR'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/rpy2/robjects/functions.py:106: UserWarning: The following object is masked from ‘package:survival’:\n",
      "\n",
      "    cancer\n",
      "\n",
      "\n",
      "  res = super(Function, self).__call__(*new_args, **new_kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(31, 19)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ro.r('library(UsingR)')\n",
    "ro.r('data(central.park)')\n",
    "centralpark = com.load_data('central.park')\n",
    "print centralpark.columns\n",
    "centralpark.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DY</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>AVG</th>\n",
       "      <th>DEP</th>\n",
       "      <th>HDD</th>\n",
       "      <th>CDD</th>\n",
       "      <th>WTR</th>\n",
       "      <th>SNW</th>\n",
       "      <th>DPTH</th>\n",
       "      <th>SPD</th>\n",
       "      <th>SPD1</th>\n",
       "      <th>DIR</th>\n",
       "      <th>MIN2</th>\n",
       "      <th>PSBL</th>\n",
       "      <th>S.S</th>\n",
       "      <th>WX</th>\n",
       "      <th>SPD3</th>\n",
       "      <th>DR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>51</td>\n",
       "      <td>62</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>12</td>\n",
       "      <td>180</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>75</td>\n",
       "      <td>52</td>\n",
       "      <td>64</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17</td>\n",
       "      <td>160</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>65</td>\n",
       "      <td>50</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>16</td>\n",
       "      <td>40</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>63</td>\n",
       "      <td>48</td>\n",
       "      <td>56</td>\n",
       "      <td>-3</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>10</td>\n",
       "      <td>150</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>59</td>\n",
       "      <td>45</td>\n",
       "      <td>52</td>\n",
       "      <td>-7</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>13</td>\n",
       "      <td>160</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>130</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>61</td>\n",
       "      <td>45</td>\n",
       "      <td>53</td>\n",
       "      <td>-7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>4.5</td>\n",
       "      <td>10</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>14</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>79</td>\n",
       "      <td>54</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>5.3</td>\n",
       "      <td>14</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>60</td>\n",
       "      <td>53</td>\n",
       "      <td>57</td>\n",
       "      <td>-3</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>17</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>70</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>51</td>\n",
       "      <td>59</td>\n",
       "      <td>-1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>12</td>\n",
       "      <td>220</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>18</td>\n",
       "      <td>16</td>\n",
       "      <td>230</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>71</td>\n",
       "      <td>50</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>12</td>\n",
       "      <td>220</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>220</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>64</td>\n",
       "      <td>53</td>\n",
       "      <td>59</td>\n",
       "      <td>-2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>15</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>140</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>65</td>\n",
       "      <td>53</td>\n",
       "      <td>59</td>\n",
       "      <td>-2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>21</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>250</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>61</td>\n",
       "      <td>51</td>\n",
       "      <td>56</td>\n",
       "      <td>-6</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>T</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>9.3</td>\n",
       "      <td>17</td>\n",
       "      <td>270</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26</td>\n",
       "      <td>290</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>66</td>\n",
       "      <td>51</td>\n",
       "      <td>59</td>\n",
       "      <td>-3</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>14</td>\n",
       "      <td>290</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18</td>\n",
       "      <td>290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>69</td>\n",
       "      <td>50</td>\n",
       "      <td>60</td>\n",
       "      <td>-2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>14</td>\n",
       "      <td>100</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>61</td>\n",
       "      <td>49</td>\n",
       "      <td>55</td>\n",
       "      <td>-8</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.3</td>\n",
       "      <td>23</td>\n",
       "      <td>60</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>62</td>\n",
       "      <td>47</td>\n",
       "      <td>55</td>\n",
       "      <td>-8</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>18</td>\n",
       "      <td>50</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>64</td>\n",
       "      <td>46</td>\n",
       "      <td>55</td>\n",
       "      <td>-8</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>62</td>\n",
       "      <td>-2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>10</td>\n",
       "      <td>170</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>79</td>\n",
       "      <td>55</td>\n",
       "      <td>67</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>4.1</td>\n",
       "      <td>13</td>\n",
       "      <td>230</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>64</td>\n",
       "      <td>55</td>\n",
       "      <td>60</td>\n",
       "      <td>-4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>12</td>\n",
       "      <td>280</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>56</td>\n",
       "      <td>50</td>\n",
       "      <td>53</td>\n",
       "      <td>-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>10.9</td>\n",
       "      <td>20</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>56</td>\n",
       "      <td>50</td>\n",
       "      <td>53</td>\n",
       "      <td>-12</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>9.7</td>\n",
       "      <td>16</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>56</td>\n",
       "      <td>51</td>\n",
       "      <td>54</td>\n",
       "      <td>-11</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>21</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>62</td>\n",
       "      <td>53</td>\n",
       "      <td>58</td>\n",
       "      <td>-7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>12</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>15</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>56</td>\n",
       "      <td>51</td>\n",
       "      <td>54</td>\n",
       "      <td>-12</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.28</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>8.6</td>\n",
       "      <td>26</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>69</td>\n",
       "      <td>50</td>\n",
       "      <td>60</td>\n",
       "      <td>-6</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>3.9</td>\n",
       "      <td>10</td>\n",
       "      <td>140</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>69</td>\n",
       "      <td>54</td>\n",
       "      <td>62</td>\n",
       "      <td>-4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>17</td>\n",
       "      <td>240</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>18</td>\n",
       "      <td>26</td>\n",
       "      <td>240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>75</td>\n",
       "      <td>54</td>\n",
       "      <td>65</td>\n",
       "      <td>-2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>5.8</td>\n",
       "      <td>13</td>\n",
       "      <td>280</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>79</td>\n",
       "      <td>61</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0</td>\n",
       "      <td>M</td>\n",
       "      <td>4.6</td>\n",
       "      <td>13</td>\n",
       "      <td>240</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>68</td>\n",
       "      <td>59</td>\n",
       "      <td>64</td>\n",
       "      <td>-3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>14</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>21</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    DY  MAX  MIN  AVG  DEP  HDD  CDD   WTR  SNW DPTH   SPD  SPD1  DIR MIN2  \\\n",
       "1    1   72   51   62    4    3    0  0.04    0    0   5.8    12  180    0   \n",
       "2    2   75   52   64    6    1    0  0.29    0    0   7.0    17  160    M   \n",
       "3    3   65   50   58    0    7    0  0.00    0    0   8.5    16   40    M   \n",
       "4    4   63   48   56   -3    9    0  0.00    0    0   2.8    10  150    M   \n",
       "5    5   59   45   52   -7   13    0  0.05    0    0   4.6    13  160    M   \n",
       "6    6   61   45   53   -7   12    0  0.00    0    M   4.5    10   90    0   \n",
       "7    7   79   54   67    7    0    2  0.16    0    M   5.3    14   50    0   \n",
       "8    8   60   53   57   -3    8    0  0.19    0    0   8.0    17   70    0   \n",
       "9    9   66   51   59   -1    6    0  0.02    0    0   4.5    12  220    0   \n",
       "10  10   71   50   61    0    4    0  0.00    0    0   3.7    12  220    0   \n",
       "11  11   64   53   59   -2    6    0  0.02    0    0   5.7    15  130    0   \n",
       "12  12   65   53   59   -2    6    0  0.03    0    0   6.0    21  250    0   \n",
       "13  13   61   51   56   -6    9    0     T    0    M   9.3    17  270    M   \n",
       "14  14   66   51   59   -3    6    0  0.00    0    0   6.5    14  290    M   \n",
       "15  15   69   50   60   -2    5    0  0.00    0    0   6.4    14  100    M   \n",
       "16  16   61   49   55   -8   10    0  0.00    0    0  13.3    23   60    M   \n",
       "17  17   62   47   55   -8   10    0  0.00    0    0   7.8    18   50    M   \n",
       "18  18   64   46   55   -8   10    0  0.00    0    M   5.0    16   60    0   \n",
       "19  19   76   48   62   -2    3    0  0.00    0    0   3.1    10  170    M   \n",
       "20  20   79   55   67    3    0    2  0.00    0    M   4.1    13  230    M   \n",
       "21  21   64   55   60   -4    5    0  0.27    0    0   4.4    12  280    M   \n",
       "22  22   56   50   53  -12   12    0  0.02    0    M  10.9    20   60    0   \n",
       "23  23   56   50   53  -12   12    0  0.14    0    M   9.7    16   70    0   \n",
       "24  24   56   51   54  -11   11    0  0.09    0    0   9.7    21   60    0   \n",
       "25  25   62   53   58   -7    7    0  0.01    0    0   4.3    12  130    0   \n",
       "26  26   56   51   54  -12   11    0  1.28    0    M   8.6    26   60    0   \n",
       "27  27   69   50   60   -6    5    0  0.00    0    M   3.9    10  140    M   \n",
       "28  28   69   54   62   -4    3    0  0.04    0    0   5.1    17  240    M   \n",
       "29  29   75   54   65   -2    0    0  0.00    0    M   5.8    13  280    0   \n",
       "30  30   79   61   70    3    0    5  0.19    0    M   4.6    13  240    0   \n",
       "31  31   68   59   64   -3    1    0  0.59    0    0   5.4    14   80    0   \n",
       "\n",
       "   PSBL  S.S  WX  SPD3   DR  \n",
       "1     0    5  18    17  170  \n",
       "2     M    4   1    22  350  \n",
       "3     M    4 NaN    26   40  \n",
       "4     M    0 NaN    14  190  \n",
       "5     M    4   1    17  130  \n",
       "6     0    7  18    14   70  \n",
       "7     0    1  18    17   60  \n",
       "8     0   10   1    25   70  \n",
       "9     0    6  18    16  230  \n",
       "10    0    2  18    17  220  \n",
       "11    0   10   1    22  140  \n",
       "12    0    7  18    29  250  \n",
       "13    M    8 NaN    26  290  \n",
       "14    M    8 NaN    18  290  \n",
       "15    M    3 NaN    18   70  \n",
       "16    M    7 NaN    32   70  \n",
       "17    M    5 NaN    25   70  \n",
       "18    0    0   1    21   60  \n",
       "19    M    0 NaN    16   80  \n",
       "20    M    0 NaN    18  190  \n",
       "21    M    0   1    15  250  \n",
       "22    0   10   1    26   60  \n",
       "23    0   10   1    22   70  \n",
       "24    0   10   1    25   50  \n",
       "25    0   10  18    15  130  \n",
       "26    0   10   1    37   70  \n",
       "27    M    0 NaN    15  170  \n",
       "28    M    6  18    26  240  \n",
       "29    0    1  18    18  220  \n",
       "30    0    3  18    18  230  \n",
       "31    0    5  18    21  160  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralpark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tXa1tMFNJgdNEYVCeSxmnTs4a24FyVXk1PefBCck4fSc2Y/9ZnHmhpoqqSfAr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38553a5450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots(centralpark,'MAX')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DY</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>AVG</th>\n",
       "      <th>DEP</th>\n",
       "      <th>HDD</th>\n",
       "      <th>CDD</th>\n",
       "      <th>SNW</th>\n",
       "      <th>SPD</th>\n",
       "      <th>SPD1</th>\n",
       "      <th>DIR</th>\n",
       "      <th>S.S</th>\n",
       "      <th>WX</th>\n",
       "      <th>SPD3</th>\n",
       "      <th>DR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.00000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>66.064516</td>\n",
       "      <td>51.290323</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>-3.612903</td>\n",
       "      <td>6.290323</td>\n",
       "      <td>0.290323</td>\n",
       "      <td>0</td>\n",
       "      <td>6.267742</td>\n",
       "      <td>15.096774</td>\n",
       "      <td>148.064516</td>\n",
       "      <td>5.032258</td>\n",
       "      <td>9.904762</td>\n",
       "      <td>20.903226</td>\n",
       "      <td>151.290323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.092121</td>\n",
       "      <td>7.013965</td>\n",
       "      <td>3.551465</td>\n",
       "      <td>4.64758</td>\n",
       "      <td>5.057519</td>\n",
       "      <td>4.100354</td>\n",
       "      <td>1.006431</td>\n",
       "      <td>0</td>\n",
       "      <td>2.474320</td>\n",
       "      <td>3.977896</td>\n",
       "      <td>83.443368</td>\n",
       "      <td>3.692189</td>\n",
       "      <td>8.700027</td>\n",
       "      <td>5.647152</td>\n",
       "      <td>87.739840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>52.00000</td>\n",
       "      <td>-12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8.500000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>55.00000</td>\n",
       "      <td>-7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>70.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>140.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>23.500000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>62.00000</td>\n",
       "      <td>-1.500000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>7.900000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>225.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>70.00000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>13.300000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>350.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              DY        MAX        MIN       AVG        DEP        HDD  \\\n",
       "count  31.000000  31.000000  31.000000  31.00000  31.000000  31.000000   \n",
       "mean   16.000000  66.064516  51.290323  59.00000  -3.612903   6.290323   \n",
       "std     9.092121   7.013965   3.551465   4.64758   5.057519   4.100354   \n",
       "min     1.000000  56.000000  45.000000  52.00000 -12.000000   0.000000   \n",
       "25%     8.500000  61.000000  50.000000  55.00000  -7.000000   3.000000   \n",
       "50%    16.000000  65.000000  51.000000  59.00000  -3.000000   6.000000   \n",
       "75%    23.500000  70.000000  53.000000  62.00000  -1.500000  10.000000   \n",
       "max    31.000000  79.000000  61.000000  70.00000   7.000000  13.000000   \n",
       "\n",
       "             CDD  SNW        SPD       SPD1         DIR        S.S         WX  \\\n",
       "count  31.000000   31  31.000000  31.000000   31.000000  31.000000  21.000000   \n",
       "mean    0.290323    0   6.267742  15.096774  148.064516   5.032258   9.904762   \n",
       "std     1.006431    0   2.474320   3.977896   83.443368   3.692189   8.700027   \n",
       "min     0.000000    0   2.800000  10.000000   40.000000   0.000000   1.000000   \n",
       "25%     0.000000    0   4.500000  12.000000   65.000000   1.500000   1.000000   \n",
       "50%     0.000000    0   5.700000  14.000000  140.000000   5.000000  18.000000   \n",
       "75%     0.000000    0   7.900000  17.000000  225.000000   8.000000  18.000000   \n",
       "max     5.000000    0  13.300000  26.000000  290.000000  10.000000  18.000000   \n",
       "\n",
       "            SPD3          DR  \n",
       "count  31.000000   31.000000  \n",
       "mean   20.903226  151.290323  \n",
       "std     5.647152   87.739840  \n",
       "min    14.000000   40.000000  \n",
       "25%    17.000000   70.000000  \n",
       "50%    18.000000  140.000000  \n",
       "75%    25.000000  225.000000  \n",
       "max    37.000000  350.000000  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralpark.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DY</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>AVG</th>\n",
       "      <th>DEP</th>\n",
       "      <th>HDD</th>\n",
       "      <th>CDD</th>\n",
       "      <th>SNW</th>\n",
       "      <th>SPD</th>\n",
       "      <th>SPD1</th>\n",
       "      <th>DIR</th>\n",
       "      <th>S.S</th>\n",
       "      <th>WX</th>\n",
       "      <th>SPD3</th>\n",
       "      <th>DR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DY</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001568</td>\n",
       "      <td>0.463503</td>\n",
       "      <td>0.175122</td>\n",
       "      <td>-0.403767</td>\n",
       "      <td>-0.144846</td>\n",
       "      <td>0.218565</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.053489</td>\n",
       "      <td>0.162208</td>\n",
       "      <td>0.078646</td>\n",
       "      <td>0.045676</td>\n",
       "      <td>0.055841</td>\n",
       "      <td>0.151915</td>\n",
       "      <td>-0.035099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAX</th>\n",
       "      <td>0.001568</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.460888</td>\n",
       "      <td>0.935641</td>\n",
       "      <td>0.860015</td>\n",
       "      <td>-0.925577</td>\n",
       "      <td>0.549739</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.538248</td>\n",
       "      <td>-0.481699</td>\n",
       "      <td>0.419401</td>\n",
       "      <td>-0.675840</td>\n",
       "      <td>0.599752</td>\n",
       "      <td>-0.445023</td>\n",
       "      <td>0.390390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIN</th>\n",
       "      <td>0.463503</td>\n",
       "      <td>0.460888</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.741157</td>\n",
       "      <td>0.435218</td>\n",
       "      <td>-0.699554</td>\n",
       "      <td>0.572485</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.105490</td>\n",
       "      <td>0.002664</td>\n",
       "      <td>0.345027</td>\n",
       "      <td>-0.005822</td>\n",
       "      <td>0.338373</td>\n",
       "      <td>0.016406</td>\n",
       "      <td>0.396697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVG</th>\n",
       "      <td>0.175122</td>\n",
       "      <td>0.935641</td>\n",
       "      <td>0.741157</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.828185</td>\n",
       "      <td>-0.981281</td>\n",
       "      <td>0.619994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.455378</td>\n",
       "      <td>-0.367814</td>\n",
       "      <td>0.446955</td>\n",
       "      <td>-0.512828</td>\n",
       "      <td>0.572913</td>\n",
       "      <td>-0.335294</td>\n",
       "      <td>0.452861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEP</th>\n",
       "      <td>-0.403767</td>\n",
       "      <td>0.860015</td>\n",
       "      <td>0.435218</td>\n",
       "      <td>0.828185</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.830188</td>\n",
       "      <td>0.442145</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.461121</td>\n",
       "      <td>-0.431053</td>\n",
       "      <td>0.369119</td>\n",
       "      <td>-0.496943</td>\n",
       "      <td>0.483839</td>\n",
       "      <td>-0.395462</td>\n",
       "      <td>0.446541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDD</th>\n",
       "      <td>-0.144846</td>\n",
       "      <td>-0.925577</td>\n",
       "      <td>-0.699554</td>\n",
       "      <td>-0.981281</td>\n",
       "      <td>-0.830188</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.457287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.468152</td>\n",
       "      <td>0.382424</td>\n",
       "      <td>-0.464963</td>\n",
       "      <td>0.518980</td>\n",
       "      <td>-0.575940</td>\n",
       "      <td>0.339549</td>\n",
       "      <td>-0.486579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDD</th>\n",
       "      <td>0.218565</td>\n",
       "      <td>0.549739</td>\n",
       "      <td>0.572485</td>\n",
       "      <td>0.619994</td>\n",
       "      <td>0.442145</td>\n",
       "      <td>-0.457287</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.195560</td>\n",
       "      <td>-0.140469</td>\n",
       "      <td>0.169651</td>\n",
       "      <td>-0.253775</td>\n",
       "      <td>0.282038</td>\n",
       "      <td>-0.164976</td>\n",
       "      <td>0.108861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNW</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPD</th>\n",
       "      <td>0.053489</td>\n",
       "      <td>-0.538248</td>\n",
       "      <td>-0.105490</td>\n",
       "      <td>-0.455378</td>\n",
       "      <td>-0.461121</td>\n",
       "      <td>0.468152</td>\n",
       "      <td>-0.195560</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.795512</td>\n",
       "      <td>-0.433960</td>\n",
       "      <td>0.615655</td>\n",
       "      <td>-0.586482</td>\n",
       "      <td>0.762438</td>\n",
       "      <td>-0.330377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPD1</th>\n",
       "      <td>0.162208</td>\n",
       "      <td>-0.481699</td>\n",
       "      <td>0.002664</td>\n",
       "      <td>-0.367814</td>\n",
       "      <td>-0.431053</td>\n",
       "      <td>0.382424</td>\n",
       "      <td>-0.140469</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.795512</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.353910</td>\n",
       "      <td>0.569440</td>\n",
       "      <td>-0.473980</td>\n",
       "      <td>0.957527</td>\n",
       "      <td>-0.230538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIR</th>\n",
       "      <td>0.078646</td>\n",
       "      <td>0.419401</td>\n",
       "      <td>0.345027</td>\n",
       "      <td>0.446955</td>\n",
       "      <td>0.369119</td>\n",
       "      <td>-0.464963</td>\n",
       "      <td>0.169651</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.433960</td>\n",
       "      <td>-0.353910</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.268112</td>\n",
       "      <td>0.429439</td>\n",
       "      <td>-0.325102</td>\n",
       "      <td>0.858578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S.S</th>\n",
       "      <td>0.045676</td>\n",
       "      <td>-0.675840</td>\n",
       "      <td>-0.005822</td>\n",
       "      <td>-0.512828</td>\n",
       "      <td>-0.496943</td>\n",
       "      <td>0.518980</td>\n",
       "      <td>-0.253775</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.615655</td>\n",
       "      <td>0.569440</td>\n",
       "      <td>-0.268112</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.276135</td>\n",
       "      <td>0.543711</td>\n",
       "      <td>-0.186374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WX</th>\n",
       "      <td>0.055841</td>\n",
       "      <td>0.599752</td>\n",
       "      <td>0.338373</td>\n",
       "      <td>0.572913</td>\n",
       "      <td>0.483839</td>\n",
       "      <td>-0.575940</td>\n",
       "      <td>0.282038</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.586482</td>\n",
       "      <td>-0.473980</td>\n",
       "      <td>0.429439</td>\n",
       "      <td>-0.276135</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.390347</td>\n",
       "      <td>0.323194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPD3</th>\n",
       "      <td>0.151915</td>\n",
       "      <td>-0.445023</td>\n",
       "      <td>0.016406</td>\n",
       "      <td>-0.335294</td>\n",
       "      <td>-0.395462</td>\n",
       "      <td>0.339549</td>\n",
       "      <td>-0.164976</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.762438</td>\n",
       "      <td>0.957527</td>\n",
       "      <td>-0.325102</td>\n",
       "      <td>0.543711</td>\n",
       "      <td>-0.390347</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.213673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DR</th>\n",
       "      <td>-0.035099</td>\n",
       "      <td>0.390390</td>\n",
       "      <td>0.396697</td>\n",
       "      <td>0.452861</td>\n",
       "      <td>0.446541</td>\n",
       "      <td>-0.486579</td>\n",
       "      <td>0.108861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.330377</td>\n",
       "      <td>-0.230538</td>\n",
       "      <td>0.858578</td>\n",
       "      <td>-0.186374</td>\n",
       "      <td>0.323194</td>\n",
       "      <td>-0.213673</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            DY       MAX       MIN       AVG       DEP       HDD       CDD  \\\n",
       "DY    1.000000  0.001568  0.463503  0.175122 -0.403767 -0.144846  0.218565   \n",
       "MAX   0.001568  1.000000  0.460888  0.935641  0.860015 -0.925577  0.549739   \n",
       "MIN   0.463503  0.460888  1.000000  0.741157  0.435218 -0.699554  0.572485   \n",
       "AVG   0.175122  0.935641  0.741157  1.000000  0.828185 -0.981281  0.619994   \n",
       "DEP  -0.403767  0.860015  0.435218  0.828185  1.000000 -0.830188  0.442145   \n",
       "HDD  -0.144846 -0.925577 -0.699554 -0.981281 -0.830188  1.000000 -0.457287   \n",
       "CDD   0.218565  0.549739  0.572485  0.619994  0.442145 -0.457287  1.000000   \n",
       "SNW        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "SPD   0.053489 -0.538248 -0.105490 -0.455378 -0.461121  0.468152 -0.195560   \n",
       "SPD1  0.162208 -0.481699  0.002664 -0.367814 -0.431053  0.382424 -0.140469   \n",
       "DIR   0.078646  0.419401  0.345027  0.446955  0.369119 -0.464963  0.169651   \n",
       "S.S   0.045676 -0.675840 -0.005822 -0.512828 -0.496943  0.518980 -0.253775   \n",
       "WX    0.055841  0.599752  0.338373  0.572913  0.483839 -0.575940  0.282038   \n",
       "SPD3  0.151915 -0.445023  0.016406 -0.335294 -0.395462  0.339549 -0.164976   \n",
       "DR   -0.035099  0.390390  0.396697  0.452861  0.446541 -0.486579  0.108861   \n",
       "\n",
       "      SNW       SPD      SPD1       DIR       S.S        WX      SPD3  \\\n",
       "DY    NaN  0.053489  0.162208  0.078646  0.045676  0.055841  0.151915   \n",
       "MAX   NaN -0.538248 -0.481699  0.419401 -0.675840  0.599752 -0.445023   \n",
       "MIN   NaN -0.105490  0.002664  0.345027 -0.005822  0.338373  0.016406   \n",
       "AVG   NaN -0.455378 -0.367814  0.446955 -0.512828  0.572913 -0.335294   \n",
       "DEP   NaN -0.461121 -0.431053  0.369119 -0.496943  0.483839 -0.395462   \n",
       "HDD   NaN  0.468152  0.382424 -0.464963  0.518980 -0.575940  0.339549   \n",
       "CDD   NaN -0.195560 -0.140469  0.169651 -0.253775  0.282038 -0.164976   \n",
       "SNW   NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "SPD   NaN  1.000000  0.795512 -0.433960  0.615655 -0.586482  0.762438   \n",
       "SPD1  NaN  0.795512  1.000000 -0.353910  0.569440 -0.473980  0.957527   \n",
       "DIR   NaN -0.433960 -0.353910  1.000000 -0.268112  0.429439 -0.325102   \n",
       "S.S   NaN  0.615655  0.569440 -0.268112  1.000000 -0.276135  0.543711   \n",
       "WX    NaN -0.586482 -0.473980  0.429439 -0.276135  1.000000 -0.390347   \n",
       "SPD3  NaN  0.762438  0.957527 -0.325102  0.543711 -0.390347  1.000000   \n",
       "DR    NaN -0.330377 -0.230538  0.858578 -0.186374  0.323194 -0.213673   \n",
       "\n",
       "            DR  \n",
       "DY   -0.035099  \n",
       "MAX   0.390390  \n",
       "MIN   0.396697  \n",
       "AVG   0.452861  \n",
       "DEP   0.446541  \n",
       "HDD  -0.486579  \n",
       "CDD   0.108861  \n",
       "SNW        NaN  \n",
       "SPD  -0.330377  \n",
       "SPD1 -0.230538  \n",
       "DIR   0.858578  \n",
       "S.S  -0.186374  \n",
       "WX    0.323194  \n",
       "SPD3 -0.213673  \n",
       "DR    1.000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralpark.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DY</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>AVG</th>\n",
       "      <th>DEP</th>\n",
       "      <th>HDD</th>\n",
       "      <th>CDD</th>\n",
       "      <th>SNW</th>\n",
       "      <th>SPD</th>\n",
       "      <th>SPD1</th>\n",
       "      <th>DIR</th>\n",
       "      <th>S.S</th>\n",
       "      <th>WX</th>\n",
       "      <th>SPD3</th>\n",
       "      <th>DR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DY</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>MAX</th>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>MIN</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVG</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEP</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDD</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDD</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNW</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPD</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>SPD1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIR</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S.S</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WX</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPD3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DR</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         DY    MAX    MIN    AVG    DEP    HDD    CDD    SNW    SPD   SPD1  \\\n",
       "DY     True  False  False  False  False  False  False  False  False  False   \n",
       "MAX   False   True  False   True   True  False   True  False  False  False   \n",
       "MIN   False  False   True   True  False  False   True  False  False  False   \n",
       "AVG   False   True   True   True   True  False   True  False  False  False   \n",
       "DEP   False   True  False   True   True  False  False  False  False  False   \n",
       "HDD   False  False  False  False  False   True  False  False  False  False   \n",
       "CDD   False   True   True   True  False  False   True  False  False  False   \n",
       "SNW   False  False  False  False  False  False  False  False  False  False   \n",
       "SPD   False  False  False  False  False  False  False  False   True   True   \n",
       "SPD1  False  False  False  False  False  False  False  False   True   True   \n",
       "DIR   False  False  False  False  False  False  False  False  False  False   \n",
       "S.S   False  False  False  False  False   True  False  False   True   True   \n",
       "WX    False   True  False   True  False  False  False  False  False  False   \n",
       "SPD3  False  False  False  False  False  False  False  False   True   True   \n",
       "DR    False  False  False  False  False  False  False  False  False  False   \n",
       "\n",
       "        DIR    S.S     WX   SPD3     DR  \n",
       "DY    False  False  False  False  False  \n",
       "MAX   False  False   True  False  False  \n",
       "MIN   False  False  False  False  False  \n",
       "AVG   False  False   True  False  False  \n",
       "DEP   False  False  False  False  False  \n",
       "HDD   False   True  False  False  False  \n",
       "CDD   False  False  False  False  False  \n",
       "SNW   False  False  False  False  False  \n",
       "SPD   False   True  False   True  False  \n",
       "SPD1  False   True  False   True  False  \n",
       "DIR    True  False  False  False   True  \n",
       "S.S   False   True  False   True  False  \n",
       "WX    False  False   True  False  False  \n",
       "SPD3  False   True  False   True  False  \n",
       "DR     True  False  False  False   True  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralpark.corr() > 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fcd6b4bab10>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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mEkFLRWYMJyIjhsTUYDyMt46/i3W/fAxDsREudhzrfw/Hzx7ULaaKABrdfiya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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd980aa1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "centralpark.plot(kind='hexbin', x='MAX', y='DEP', gridsize=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dzeZyTOCY02t5q62t1dlnny1JOvfcc7V3796cDwXg6Pn9Po0pLez7dj5LI2NB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcd614437d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8782504815489)>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = ggplot(aes(x='MAX', y='DEP',color=\"S.S\"), data=centralpark)\n",
    "p + geom_point()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}