Congressional.ipynb

{
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   "cell_type": "markdown",
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   "source": [
    "# Assignment 7: Supervised learning\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "### March 19th 2018\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#### Team Members:\n",
    "#### Prashant Wankhede\n",
    "#### Abhishek Shankarnarayanan \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "For the following two data sets, originating from the Irvine Machine Learning Repository (http://archive.ics.uci.edu/ml/):\n",
    "\n",
    "\n",
    " Congressional Voting Records (http://archive.ics.uci.edu/ml/datasets/Congressional+Voting+Records)\n",
    "\n",
    "a) Build classification models based on each of these algorithms:\n",
    "\n",
    "    Logistic Regression or SVM\n",
    "    Random Forest or Boosting (i.e. Adaboost)\n",
    "    CART (i.e. Decision Tree)\n",
    "\n",
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python version: 3.6.3 |Anaconda, Inc.| (default, Oct 15 2017, 03:27:45) [MSC v.1900 64 bit (AMD64)]\n",
      "pandas version: 0.20.3\n",
      "matplotlib version: 2.1.0\n",
      "NumPy version: 1.13.3\n",
      "SciPy version: 0.19.1\n",
      "IPython version: 6.1.0\n",
      "scikit-learn version: 0.19.1\n"
     ]
    }
   ],
   "source": [
    "import sys # access to system parameters\n",
    "print('Python version: {}'.format(sys.version))\n",
    "\n",
    "import pandas as pd # library of functions for data processing\n",
    "print('pandas version: {}'.format(pd.__version__))\n",
    "\n",
    "import matplotlib # functions for visualization\n",
    "print('matplotlib version: {}'.format(matplotlib.__version__))\n",
    "\n",
    "import numpy as np # package for scientific computing\n",
    "print('NumPy version: {}'.format(np.__version__))\n",
    "\n",
    "import scipy as sp # functions for scientific computing and advanced mathematics\n",
    "print('SciPy version: {}'.format(sp.__version__))\n",
    "\n",
    "import IPython.display\n",
    "from IPython import display # printing fancy in Jupyter notebook\n",
    "print('IPython version: {}'.format(IPython.__version__))\n",
    "\n",
    "import sklearn # collection of machine learning algorithms\n",
    "print('scikit-learn version: {}'.format(sklearn.__version__))\n",
    "\n",
    "# Some additional nifty functions\n",
    "import re\n",
    "import random\n",
    "import time\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Model algorithms\n",
    "from sklearn import svm, tree, linear_model, neighbors, naive_bayes, ensemble, discriminant_analysis, gaussian_process, neural_network\n",
    "\n",
    "# Common Model Helpers\n",
    "from sklearn.preprocessing import OneHotEncoder, LabelEncoder\n",
    "from sklearn import feature_selection\n",
    "from sklearn import model_selection\n",
    "from sklearn import metrics\n",
    "\n",
    "# Visualization\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pylab as pylab\n",
    "import seaborn as sns\n",
    "from pandas.tools.plotting import scatter_matrix\n",
    "\n",
    "#Configure visualization defaults\n",
    "%matplotlib inline\n",
    "mpl.style.use('ggplot')\n",
    "sns.set_style('white')\n",
    "pylab.rcParams['figure.figsize'] = 12,8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "column_names = ['party', 'handicap', 'water', 'budget', 'physician', 'elsavador', 'religion', 'satellite', 'nicaraguan',\n",
    "               'missile', 'immigration', 'snyfuels', 'education', 'superfund', 'crime', 'dutyfree', 'export']\n",
    "# Data for visualizations, training and testing\n",
    "data = pd.read_csv('C:/Users/work/Desktop/DA/house-votes-84.data', names=column_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 435 entries, 0 to 434\n",
      "Data columns (total 17 columns):\n",
      "party          435 non-null object\n",
      "handicap       435 non-null object\n",
      "water          435 non-null object\n",
      "budget         435 non-null object\n",
      "physician      435 non-null object\n",
      "elsavador      435 non-null object\n",
      "religion       435 non-null object\n",
      "satellite      435 non-null object\n",
      "nicaraguan     435 non-null object\n",
      "missile        435 non-null object\n",
      "immigration    435 non-null object\n",
      "snyfuels       435 non-null object\n",
      "education      435 non-null object\n",
      "superfund      435 non-null object\n",
      "crime          435 non-null object\n",
      "dutyfree       435 non-null object\n",
      "export         435 non-null object\n",
      "dtypes: object(17)\n",
      "memory usage: 57.9+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "      <th>budget</th>\n",
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       "      <th>superfund</th>\n",
       "      <th>crime</th>\n",
       "      <th>dutyfree</th>\n",
       "      <th>export</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>count</th>\n",
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       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>democrat</td>\n",
       "      <td>n</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>y</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>267</td>\n",
       "      <td>236</td>\n",
       "      <td>195</td>\n",
       "      <td>253</td>\n",
       "      <td>247</td>\n",
       "      <td>212</td>\n",
       "      <td>272</td>\n",
       "      <td>239</td>\n",
       "      <td>242</td>\n",
       "      <td>207</td>\n",
       "      <td>216</td>\n",
       "      <td>264</td>\n",
       "      <td>233</td>\n",
       "      <td>209</td>\n",
       "      <td>248</td>\n",
       "      <td>233</td>\n",
       "      <td>269</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           party handicap water budget physician elsavador religion satellite  \\\n",
       "count        435      435   435    435       435       435      435       435   \n",
       "unique         2        3     3      3         3         3        3         3   \n",
       "top     democrat        n     y      y         n         y        y         y   \n",
       "freq         267      236   195    253       247       212      272       239   \n",
       "\n",
       "       nicaraguan missile immigration snyfuels education superfund crime  \\\n",
       "count         435     435         435      435       435       435   435   \n",
       "unique          3       3           3        3         3         3     3   \n",
       "top             y       y           y        n         n         y     y   \n",
       "freq          242     207         216      264       233       209   248   \n",
       "\n",
       "       dutyfree export  \n",
       "count       435    435  \n",
       "unique        3      3  \n",
       "top           n      y  \n",
       "freq        233    269  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
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    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>party</th>\n",
       "      <th>handicap</th>\n",
       "      <th>water</th>\n",
       "      <th>budget</th>\n",
       "      <th>physician</th>\n",
       "      <th>elsavador</th>\n",
       "      <th>religion</th>\n",
       "      <th>satellite</th>\n",
       "      <th>nicaraguan</th>\n",
       "      <th>missile</th>\n",
       "      <th>immigration</th>\n",
       "      <th>snyfuels</th>\n",
       "      <th>education</th>\n",
       "      <th>superfund</th>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>democrat</td>\n",
       "      <td>?</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>?</td>\n",
       "      <td>y</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>democrat</td>\n",
       "      <td>n</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>?</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>democrat</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>y</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "        party handicap water budget physician elsavador religion satellite  \\\n",
       "0  republican        n     y      n         y         y        y         n   \n",
       "1  republican        n     y      n         y         y        y         n   \n",
       "2    democrat        ?     y      y         ?         y        y         n   \n",
       "3    democrat        n     y      y         n         ?        y         n   \n",
       "4    democrat        y     y      y         n         y        y         n   \n",
       "\n",
       "  nicaraguan missile immigration snyfuels education superfund crime dutyfree  \\\n",
       "0          n       n           y        ?         y         y     y        n   \n",
       "1          n       n           n        n         y         y     y        n   \n",
       "2          n       n           n        y         n         y     y        n   \n",
       "3          n       n           n        y         n         y     n        n   \n",
       "4          n       n           n        y         ?         y     y        y   \n",
       "\n",
       "  export  \n",
       "0      y  \n",
       "1      ?  \n",
       "2      n  \n",
       "3      y  \n",
       "4      y  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Total: 435\n",
    "\n",
    "Republicans: 168\n",
    "\n",
    "Democrats: 267\n",
    "\n",
    "Votes : 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data with null values: \n",
      " party          0\n",
      "handicap       0\n",
      "water          0\n",
      "budget         0\n",
      "physician      0\n",
      "elsavador      0\n",
      "religion       0\n",
      "satellite      0\n",
      "nicaraguan     0\n",
      "missile        0\n",
      "immigration    0\n",
      "snyfuels       0\n",
      "education      0\n",
      "superfund      0\n",
      "crime          0\n",
      "dutyfree       0\n",
      "export         0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print('Training data with null values: \\n',data.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "## Change 'y' and 'n' to 1 and 0.\n",
    "data.replace(to_replace='y', value=1, inplace = True)\n",
    "data.replace(to_replace='n', value=0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "      <th>superfund</th>\n",
       "      <th>crime</th>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.44208</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.417453</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.504762</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.362319</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.641509</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</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",
       "      <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>405</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.362319</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.641509</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.44208</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>0.596698</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.504762</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.567696</td>\n",
       "      <td>0.57619</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>0.504673</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          party  handicap     water    budget  physician  elsavador  religion  \\\n",
       "0    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "1    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "2      democrat   0.44208  1.000000  1.000000   0.417453   1.000000  1.000000   \n",
       "3      democrat   0.00000  1.000000  1.000000   0.000000   0.504762  1.000000   \n",
       "4      democrat   1.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "5      democrat   0.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "6      democrat   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "7    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "8    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "9      democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "10   republican   0.00000  1.000000  0.000000   1.000000   1.000000  0.000000   \n",
       "11   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "12     democrat   0.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "13     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "14   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "15   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "16     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "17     democrat   1.00000  0.503876  1.000000   0.000000   0.000000  0.000000   \n",
       "18   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "19     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "20     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.641509   \n",
       "21     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "22     democrat   1.00000  0.503876  1.000000   0.000000   0.000000  0.000000   \n",
       "23     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "24     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "25     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "26     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "27     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "28   republican   1.00000  0.000000  0.000000   1.000000   1.000000  0.000000   \n",
       "29     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "..          ...       ...       ...       ...        ...        ...       ...   \n",
       "405  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "406    democrat   1.00000  0.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "407    democrat   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "408    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "409  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "410  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "411    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "412  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "413  republican   1.00000  1.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "414    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "415    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "416  republican   1.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "417    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "418    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "419    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "420  republican   1.00000  1.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "421    democrat   0.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "422    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "423    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "424    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  0.641509   \n",
       "425    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "426    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "427  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "428    democrat   0.44208  0.503876  0.596698   0.000000   0.000000  0.000000   \n",
       "429    democrat   1.00000  0.000000  1.000000   0.000000   0.504762  0.000000   \n",
       "430  republican   0.00000  0.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "431    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "432  republican   0.00000  0.503876  0.000000   1.000000   1.000000  1.000000   \n",
       "433  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "434  republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "\n",
       "     satellite  nicaraguan   missile  immigration  snyfuels  education  \\\n",
       "0     0.000000     0.00000  0.000000     1.000000  0.362319   1.000000   \n",
       "1     0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "2     0.000000     0.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "3     0.000000     0.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "4     0.000000     0.00000  0.000000     0.000000  1.000000   0.423267   \n",
       "5     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "6     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "7     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "8     0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "9     1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "10    0.000000     0.00000  0.000000     0.000000  0.362319   0.423267   \n",
       "11    0.000000     0.00000  0.000000     0.000000  1.000000   0.423267   \n",
       "12    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "13    1.000000     1.00000  0.501211     1.000000  1.000000   0.423267   \n",
       "14    0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "15    0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "16    0.000000     1.00000  0.501211     1.000000  1.000000   1.000000   \n",
       "17    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "18    0.000000     0.00000  0.000000     0.000000  0.000000   0.423267   \n",
       "19    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "20    1.000000     1.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "21    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "22    1.000000     1.00000  1.000000     0.000000  0.000000   0.423267   \n",
       "23    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "24    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "25    1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "26    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "27    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "28    1.000000     1.00000  1.000000     0.000000  0.000000   1.000000   \n",
       "29    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "..         ...         ...       ...          ...       ...        ...   \n",
       "405   0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "406   0.000000     0.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "407   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "408   1.000000     1.00000  1.000000     0.000000  0.000000   1.000000   \n",
       "409   0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "410   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "411   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "412   0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "413   1.000000     1.00000  0.000000     1.000000  0.362319   0.423267   \n",
       "414   1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "415   1.000000     1.00000  0.501211     1.000000  0.000000   0.000000   \n",
       "416   0.000000     0.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "417   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "418   1.000000     1.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "419   1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "420   1.000000     1.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "421   1.000000     1.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "422   1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "423   1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "424   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "425   1.000000     1.00000  0.000000     1.000000  1.000000   0.000000   \n",
       "426   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "427   1.000000     1.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "428   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "429   1.000000     1.00000  1.000000     1.000000  0.000000   1.000000   \n",
       "430   0.000000     0.00000  1.000000     1.000000  0.000000   1.000000   \n",
       "431   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "432   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "433   0.567696     0.57619  0.501211     0.504673  0.000000   1.000000   \n",
       "434   0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "\n",
       "     superfund     crime  dutyfree    export  \n",
       "0     1.000000  1.000000  0.000000  1.000000  \n",
       "1     1.000000  1.000000  0.000000  0.812689  \n",
       "2     1.000000  1.000000  0.000000  0.000000  \n",
       "3     1.000000  0.000000  0.000000  1.000000  \n",
       "4     1.000000  1.000000  1.000000  1.000000  \n",
       "5     1.000000  1.000000  1.000000  1.000000  \n",
       "6     0.509756  1.000000  1.000000  1.000000  \n",
       "7     1.000000  1.000000  0.427518  1.000000  \n",
       "8     1.000000  1.000000  0.000000  1.000000  \n",
       "9     0.000000  0.000000  0.427518  0.812689  \n",
       "10    1.000000  1.000000  0.000000  0.000000  \n",
       "11    1.000000  1.000000  0.427518  0.812689  \n",
       "12    1.000000  0.000000  0.427518  0.812689  \n",
       "13    0.000000  0.000000  1.000000  0.812689  \n",
       "14    0.509756  0.593301  0.000000  0.812689  \n",
       "15    1.000000  0.593301  0.000000  0.812689  \n",
       "16    0.509756  0.000000  0.000000  1.000000  \n",
       "17    1.000000  0.000000  1.000000  1.000000  \n",
       "18    1.000000  1.000000  0.000000  0.000000  \n",
       "19    0.000000  0.000000  1.000000  1.000000  \n",
       "20    0.000000  0.000000  1.000000  1.000000  \n",
       "21    0.509756  0.593301  1.000000  1.000000  \n",
       "22    0.000000  0.000000  1.000000  1.000000  \n",
       "23    0.000000  0.000000  1.000000  1.000000  \n",
       "24    0.000000  0.000000  1.000000  0.812689  \n",
       "25    0.000000  0.000000  1.000000  1.000000  \n",
       "26    0.000000  0.000000  1.000000  1.000000  \n",
       "27    0.000000  0.000000  1.000000  1.000000  \n",
       "28    1.000000  1.000000  0.000000  1.000000  \n",
       "29    0.000000  0.000000  1.000000  1.000000  \n",
       "..         ...       ...       ...       ...  \n",
       "405   1.000000  1.000000  0.000000  1.000000  \n",
       "406   1.000000  1.000000  0.000000  1.000000  \n",
       "407   1.000000  1.000000  0.000000  0.000000  \n",
       "408   0.509756  1.000000  1.000000  1.000000  \n",
       "409   1.000000  1.000000  0.000000  0.000000  \n",
       "410   1.000000  1.000000  0.000000  1.000000  \n",
       "411   0.000000  0.000000  0.000000  1.000000  \n",
       "412   1.000000  1.000000  0.000000  1.000000  \n",
       "413   0.509756  1.000000  0.000000  1.000000  \n",
       "414   0.000000  0.000000  0.000000  1.000000  \n",
       "415   0.000000  0.000000  0.000000  1.000000  \n",
       "416   1.000000  1.000000  0.000000  1.000000  \n",
       "417   1.000000  0.000000  0.000000  1.000000  \n",
       "418   0.000000  0.000000  0.000000  1.000000  \n",
       "419   0.000000  0.000000  0.000000  1.000000  \n",
       "420   1.000000  1.000000  0.000000  1.000000  \n",
       "421   1.000000  0.000000  1.000000  1.000000  \n",
       "422   0.000000  0.000000  1.000000  1.000000  \n",
       "423   0.000000  1.000000  1.000000  1.000000  \n",
       "424   0.509756  1.000000  1.000000  1.000000  \n",
       "425   0.000000  0.000000  1.000000  0.812689  \n",
       "426   0.000000  0.000000  1.000000  1.000000  \n",
       "427   1.000000  1.000000  0.000000  1.000000  \n",
       "428   1.000000  0.000000  1.000000  1.000000  \n",
       "429   0.000000  0.593301  1.000000  1.000000  \n",
       "430   1.000000  1.000000  0.000000  1.000000  \n",
       "431   0.000000  0.000000  0.000000  1.000000  \n",
       "432   1.000000  1.000000  0.000000  1.000000  \n",
       "433   1.000000  1.000000  0.000000  1.000000  \n",
       "434   1.000000  1.000000  0.427518  0.000000  \n",
       "\n",
       "[435 rows x 17 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Replace ? with the votes' mean\n",
    "data.replace(to_replace='?', value=np.nan, inplace = True)\n",
    "data.fillna(data.mean(), inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>party</th>\n",
       "      <th>handicap</th>\n",
       "      <th>water</th>\n",
       "      <th>budget</th>\n",
       "      <th>physician</th>\n",
       "      <th>elsavador</th>\n",
       "      <th>religion</th>\n",
       "      <th>satellite</th>\n",
       "      <th>nicaraguan</th>\n",
       "      <th>missile</th>\n",
       "      <th>immigration</th>\n",
       "      <th>snyfuels</th>\n",
       "      <th>education</th>\n",
       "      <th>superfund</th>\n",
       "      <th>crime</th>\n",
       "      <th>dutyfree</th>\n",
       "      <th>export</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.362319</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.44208</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.417453</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.504762</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.362319</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.641509</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</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",
       "      <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>405</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.362319</td>\n",
       "      <td>0.423267</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.641509</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.509756</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.812689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.44208</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>0.596698</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.504762</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.593301</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.503876</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.567696</td>\n",
       "      <td>0.57619</td>\n",
       "      <td>0.501211</td>\n",
       "      <td>0.504673</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.427518</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          party  handicap     water    budget  physician  elsavador  religion  \\\n",
       "0    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "1    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "2      democrat   0.44208  1.000000  1.000000   0.417453   1.000000  1.000000   \n",
       "3      democrat   0.00000  1.000000  1.000000   0.000000   0.504762  1.000000   \n",
       "4      democrat   1.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "5      democrat   0.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "6      democrat   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "7    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "8    republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "9      democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "10   republican   0.00000  1.000000  0.000000   1.000000   1.000000  0.000000   \n",
       "11   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "12     democrat   0.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "13     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "14   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "15   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "16     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "17     democrat   1.00000  0.503876  1.000000   0.000000   0.000000  0.000000   \n",
       "18   republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "19     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "20     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.641509   \n",
       "21     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "22     democrat   1.00000  0.503876  1.000000   0.000000   0.000000  0.000000   \n",
       "23     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "24     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "25     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "26     democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "27     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "28   republican   1.00000  0.000000  0.000000   1.000000   1.000000  0.000000   \n",
       "29     democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "..          ...       ...       ...       ...        ...        ...       ...   \n",
       "405  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "406    democrat   1.00000  0.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "407    democrat   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "408    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "409  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "410  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "411    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "412  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "413  republican   1.00000  1.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "414    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "415    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "416  republican   1.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "417    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "418    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "419    democrat   1.00000  1.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "420  republican   1.00000  1.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "421    democrat   0.00000  1.000000  1.000000   0.000000   1.000000  1.000000   \n",
       "422    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "423    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  1.000000   \n",
       "424    democrat   0.00000  1.000000  1.000000   0.000000   0.000000  0.641509   \n",
       "425    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "426    democrat   1.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "427  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "428    democrat   0.44208  0.503876  0.596698   0.000000   0.000000  0.000000   \n",
       "429    democrat   1.00000  0.000000  1.000000   0.000000   0.504762  0.000000   \n",
       "430  republican   0.00000  0.000000  1.000000   1.000000   1.000000  1.000000   \n",
       "431    democrat   0.00000  0.000000  1.000000   0.000000   0.000000  0.000000   \n",
       "432  republican   0.00000  0.503876  0.000000   1.000000   1.000000  1.000000   \n",
       "433  republican   0.00000  0.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "434  republican   0.00000  1.000000  0.000000   1.000000   1.000000  1.000000   \n",
       "\n",
       "     satellite  nicaraguan   missile  immigration  snyfuels  education  \\\n",
       "0     0.000000     0.00000  0.000000     1.000000  0.362319   1.000000   \n",
       "1     0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "2     0.000000     0.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "3     0.000000     0.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "4     0.000000     0.00000  0.000000     0.000000  1.000000   0.423267   \n",
       "5     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "6     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "7     0.000000     0.00000  0.000000     0.000000  0.000000   0.000000   \n",
       "8     0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "9     1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "10    0.000000     0.00000  0.000000     0.000000  0.362319   0.423267   \n",
       "11    0.000000     0.00000  0.000000     0.000000  1.000000   0.423267   \n",
       "12    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "13    1.000000     1.00000  0.501211     1.000000  1.000000   0.423267   \n",
       "14    0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "15    0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "16    0.000000     1.00000  0.501211     1.000000  1.000000   1.000000   \n",
       "17    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "18    0.000000     0.00000  0.000000     0.000000  0.000000   0.423267   \n",
       "19    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "20    1.000000     1.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "21    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "22    1.000000     1.00000  1.000000     0.000000  0.000000   0.423267   \n",
       "23    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "24    1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "25    1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "26    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "27    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "28    1.000000     1.00000  1.000000     0.000000  0.000000   1.000000   \n",
       "29    1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "..         ...         ...       ...          ...       ...        ...   \n",
       "405   0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "406   0.000000     0.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "407   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "408   1.000000     1.00000  1.000000     0.000000  0.000000   1.000000   \n",
       "409   0.000000     0.00000  0.000000     0.000000  0.000000   1.000000   \n",
       "410   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "411   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "412   0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "413   1.000000     1.00000  0.000000     1.000000  0.362319   0.423267   \n",
       "414   1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "415   1.000000     1.00000  0.501211     1.000000  0.000000   0.000000   \n",
       "416   0.000000     0.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "417   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "418   1.000000     1.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "419   1.000000     1.00000  1.000000     0.000000  0.000000   0.000000   \n",
       "420   1.000000     1.00000  0.000000     1.000000  0.000000   0.000000   \n",
       "421   1.000000     1.00000  0.000000     0.000000  1.000000   0.000000   \n",
       "422   1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "423   1.000000     1.00000  1.000000     0.000000  1.000000   0.000000   \n",
       "424   1.000000     1.00000  1.000000     1.000000  1.000000   0.000000   \n",
       "425   1.000000     1.00000  0.000000     1.000000  1.000000   0.000000   \n",
       "426   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "427   1.000000     1.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "428   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "429   1.000000     1.00000  1.000000     1.000000  0.000000   1.000000   \n",
       "430   0.000000     0.00000  1.000000     1.000000  0.000000   1.000000   \n",
       "431   1.000000     1.00000  1.000000     1.000000  0.000000   0.000000   \n",
       "432   0.000000     0.00000  0.000000     0.000000  1.000000   1.000000   \n",
       "433   0.567696     0.57619  0.501211     0.504673  0.000000   1.000000   \n",
       "434   0.000000     0.00000  0.000000     1.000000  0.000000   1.000000   \n",
       "\n",
       "     superfund     crime  dutyfree    export  \n",
       "0     1.000000  1.000000  0.000000  1.000000  \n",
       "1     1.000000  1.000000  0.000000  0.812689  \n",
       "2     1.000000  1.000000  0.000000  0.000000  \n",
       "3     1.000000  0.000000  0.000000  1.000000  \n",
       "4     1.000000  1.000000  1.000000  1.000000  \n",
       "5     1.000000  1.000000  1.000000  1.000000  \n",
       "6     0.509756  1.000000  1.000000  1.000000  \n",
       "7     1.000000  1.000000  0.427518  1.000000  \n",
       "8     1.000000  1.000000  0.000000  1.000000  \n",
       "9     0.000000  0.000000  0.427518  0.812689  \n",
       "10    1.000000  1.000000  0.000000  0.000000  \n",
       "11    1.000000  1.000000  0.427518  0.812689  \n",
       "12    1.000000  0.000000  0.427518  0.812689  \n",
       "13    0.000000  0.000000  1.000000  0.812689  \n",
       "14    0.509756  0.593301  0.000000  0.812689  \n",
       "15    1.000000  0.593301  0.000000  0.812689  \n",
       "16    0.509756  0.000000  0.000000  1.000000  \n",
       "17    1.000000  0.000000  1.000000  1.000000  \n",
       "18    1.000000  1.000000  0.000000  0.000000  \n",
       "19    0.000000  0.000000  1.000000  1.000000  \n",
       "20    0.000000  0.000000  1.000000  1.000000  \n",
       "21    0.509756  0.593301  1.000000  1.000000  \n",
       "22    0.000000  0.000000  1.000000  1.000000  \n",
       "23    0.000000  0.000000  1.000000  1.000000  \n",
       "24    0.000000  0.000000  1.000000  0.812689  \n",
       "25    0.000000  0.000000  1.000000  1.000000  \n",
       "26    0.000000  0.000000  1.000000  1.000000  \n",
       "27    0.000000  0.000000  1.000000  1.000000  \n",
       "28    1.000000  1.000000  0.000000  1.000000  \n",
       "29    0.000000  0.000000  1.000000  1.000000  \n",
       "..         ...       ...       ...       ...  \n",
       "405   1.000000  1.000000  0.000000  1.000000  \n",
       "406   1.000000  1.000000  0.000000  1.000000  \n",
       "407   1.000000  1.000000  0.000000  0.000000  \n",
       "408   0.509756  1.000000  1.000000  1.000000  \n",
       "409   1.000000  1.000000  0.000000  0.000000  \n",
       "410   1.000000  1.000000  0.000000  1.000000  \n",
       "411   0.000000  0.000000  0.000000  1.000000  \n",
       "412   1.000000  1.000000  0.000000  1.000000  \n",
       "413   0.509756  1.000000  0.000000  1.000000  \n",
       "414   0.000000  0.000000  0.000000  1.000000  \n",
       "415   0.000000  0.000000  0.000000  1.000000  \n",
       "416   1.000000  1.000000  0.000000  1.000000  \n",
       "417   1.000000  0.000000  0.000000  1.000000  \n",
       "418   0.000000  0.000000  0.000000  1.000000  \n",
       "419   0.000000  0.000000  0.000000  1.000000  \n",
       "420   1.000000  1.000000  0.000000  1.000000  \n",
       "421   1.000000  0.000000  1.000000  1.000000  \n",
       "422   0.000000  0.000000  1.000000  1.000000  \n",
       "423   0.000000  1.000000  1.000000  1.000000  \n",
       "424   0.509756  1.000000  1.000000  1.000000  \n",
       "425   0.000000  0.000000  1.000000  0.812689  \n",
       "426   0.000000  0.000000  1.000000  1.000000  \n",
       "427   1.000000  1.000000  0.000000  1.000000  \n",
       "428   1.000000  0.000000  1.000000  1.000000  \n",
       "429   0.000000  0.593301  1.000000  1.000000  \n",
       "430   1.000000  1.000000  0.000000  1.000000  \n",
       "431   0.000000  0.000000  0.000000  1.000000  \n",
       "432   1.000000  1.000000  0.000000  1.000000  \n",
       "433   1.000000  1.000000  0.000000  1.000000  \n",
       "434   1.000000  1.000000  0.427518  0.000000  \n",
       "\n",
       "[435 rows x 17 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.cross_validation import train_test_split\n",
    "\n",
    "\n",
    "X = data.drop(['party'], 1)\n",
    "y = data.party\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=4444)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "logistic regression accuracy:\t 0.939\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "\n",
    "## Make a logistic regression object, fit it on the training set, and test it to find accuracy\n",
    "log_reg = LogisticRegression()\n",
    "log_reg.fit(X_train, y_train)\n",
    "logistic_prediction = log_reg.predict(X_test)\n",
    "log_reg_accuracy = accuracy_score(y_test, logistic_prediction)\n",
    "print ('logistic regression accuracy:\\t %.3f' % log_reg_accuracy)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29fc320e710>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x29fc31ee748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.party.value_counts().plot(kind = 'bar', color='y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.587786259542\n"
     ]
    }
   ],
   "source": [
    "## Here's a predictor that predicts everyone to be a democrat\n",
    "def all_democrat(X):\n",
    "    return ['democrat' for _ in range(len(X))]\n",
    "\n",
    "democrat_prediction = all_democrat(X_test)\n",
    "dem_acc = accuracy_score(y_test, democrat_prediction)\n",
    "print (dem_acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.412213740458\n"
     ]
    }
   ],
   "source": [
    "## Here's a predictor that predicts everyone to be a republican\n",
    "def all_republican(X):\n",
    "    return ['republican' for _ in range(len(X))]\n",
    "\n",
    "republican_prediction = all_republican(X_test)\n",
    "rep_acc = accuracy_score(y_test, republican_prediction)\n",
    "print (rep_acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gaussian Naive Bayes Classifier accuracy: 0.939\n",
      "With Parameters:\t\n",
      "{'priors': None}\n",
      "\n",
      "\n",
      "Support Vector Machine (SVM)accuracy: 0.954\n",
      "With Parameters:\t\n",
      "{'C': 1.0, 'cache_size': 200, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'auto', 'kernel': 'rbf', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}\n",
      "\n",
      "\n",
      "Decision Tree accuracy: 0.931\n",
      "With Parameters:\t\n",
      "{'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': None, 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'presort': False, 'random_state': None, 'splitter': 'best'}\n",
      "\n",
      "\n",
      "Random Forest accuracy: 0.962\n",
      "With Parameters:\t\n",
      "{'bootstrap': True, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 10, 'n_jobs': 1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "gnb = GaussianNB()\n",
    "gnb.fit(X_train, y_train)\n",
    "gnb_predict = gnb.predict(X_test)\n",
    "gnb_accuracy = accuracy_score(y_test, gnb_predict)\n",
    "print ('Gaussian Naive Bayes Classifier accuracy: %.3f' % gnb_accuracy)\n",
    "print('With Parameters:\\t' )\n",
    "print(gnb.get_params())\n",
    "print('\\n')\n",
    "\n",
    "svm = SVC()\n",
    "svm.fit(X_train, y_train)\n",
    "svm_predict = svm.predict(X_test)\n",
    "svm_accuracy = accuracy_score(y_test, svm_predict)\n",
    "print ('Support Vector Machine (SVM)accuracy: %.3f' %svm_accuracy)\n",
    "print('With Parameters:\\t' )\n",
    "print(svm.get_params())\n",
    "print('\\n')\n",
    "\n",
    "\n",
    "tree = DecisionTreeClassifier()\n",
    "tree.fit(X_train, y_train)\n",
    "tree_predict = tree.predict(X_test)\n",
    "tree_accuracy = accuracy_score(y_test, tree_predict)\n",
    "print ('Decision Tree accuracy: %.3f' %tree_accuracy)\n",
    "print('With Parameters:\\t' )\n",
    "print(tree.get_params())\n",
    "print('\\n')\n",
    "\n",
    "\n",
    "forest = RandomForestClassifier()\n",
    "forest.fit(X_train, y_train)\n",
    "forest_predict = forest.predict(X_test)\n",
    "forest_accuracy = accuracy_score(y_test, forest_predict)\n",
    "print ('Random Forest accuracy: %.3f' %forest_accuracy)\n",
    "print('With Parameters:\\t' )\n",
    "print(forest.get_params())\n",
    "print('\\n')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Feature Selection using Recursive Feature Elimination with cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_selection import RFECV\n",
    "m = RFECV(RandomForestClassifier(), scoring = 'accuracy')\n",
    "m.fit(X_train,y_train)\n",
    "m.score(X_train,y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True, False, False, False,  True,  True,\n",
       "       False,  True,  True,  True,  True,  True,  True], dtype=bool)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.support_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 1, 3, 5, 4, 1, 1, 2, 1, 1, 1, 1, 1, 1])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.ranking_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see top 5 features are enough in determining randam forest algorithm's prediction but addition of other features should not harm the prediction, let alone tries to improve it as they are binary yes/no values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Cross Validated Models\n",
      "Gaussian Naive Bayes:\t0.931\n",
      "Support Vector Machine:\t0.954\n",
      "Decision Tree:\t\t0.952\n",
      "Random Forest:\t\t0.961\n"
     ]
    }
   ],
   "source": [
    "from sklearn.cross_validation import cross_val_score\n",
    "\n",
    "\n",
    "gnb_cv = np.mean(cross_val_score(gnb, X, y))\n",
    "svm_cv = np.mean(cross_val_score(svm, X, y))\n",
    "tree_cv = np.mean(cross_val_score(tree, X, y))\n",
    "forest_cv = np.mean(cross_val_score(forest, X, y))\n",
    "\n",
    "print ('Accuracy of Cross Validated Models')\n",
    "print ('Gaussian Naive Bayes:\\t%.3f' %gnb_cv)\n",
    "print ('Support Vector Machine:\\t%.3f' %svm_cv)\n",
    "print ('Decision Tree:\\t\\t%.3f' %tree_cv)\n",
    "print ('Random Forest:\\t\\t%.3f' %forest_cv)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data2 = pd.read_csv(\"C:/Users/work/Desktop/DA/house-votes-84.data\", names=column_names)\n",
    "\n",
    "## Change 'y' and 'n' to 1 and 0. And ? to NaN\n",
    "data2.replace(to_replace='y', value=1, inplace = True)\n",
    "data2.replace(to_replace='n', value=0, inplace = True)\n",
    "data2.replace(to_replace='?', value=np.nan, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>party</th>\n",
       "      <th>handicap</th>\n",
       "      <th>water</th>\n",
       "      <th>budget</th>\n",
       "      <th>physician</th>\n",
       "      <th>elsavador</th>\n",
       "      <th>religion</th>\n",
       "      <th>satellite</th>\n",
       "      <th>nicaraguan</th>\n",
       "      <th>missile</th>\n",
       "      <th>immigration</th>\n",
       "      <th>snyfuels</th>\n",
       "      <th>education</th>\n",
       "      <th>superfund</th>\n",
       "      <th>crime</th>\n",
       "      <th>dutyfree</th>\n",
       "      <th>export</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</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",
       "      <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>405</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>republican</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>democrat</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>democrat</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>republican</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          party  handicap  water  budget  physician  elsavador  religion  \\\n",
       "0    republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "1    republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "2      democrat       0.0    1.0     1.0        0.0        1.0       1.0   \n",
       "3      democrat       0.0    1.0     1.0        0.0        1.0       1.0   \n",
       "4      democrat       1.0    1.0     1.0        0.0        1.0       1.0   \n",
       "5      democrat       0.0    1.0     1.0        0.0        1.0       1.0   \n",
       "6      democrat       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "7    republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "8    republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "9      democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "10   republican       0.0    1.0     0.0        1.0        1.0       0.0   \n",
       "11   republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "12     democrat       0.0    1.0     1.0        0.0        0.0       0.0   \n",
       "13     democrat       1.0    1.0     1.0        0.0        0.0       1.0   \n",
       "14   republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "15   republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "16     democrat       1.0    0.0     1.0        0.0        0.0       1.0   \n",
       "17     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "18   republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "19     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "20     democrat       1.0    1.0     1.0        0.0        0.0       1.0   \n",
       "21     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "22     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "23     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "24     democrat       1.0    0.0     1.0        0.0        0.0       0.0   \n",
       "25     democrat       1.0    0.0     1.0        0.0        0.0       0.0   \n",
       "26     democrat       1.0    0.0     1.0        0.0        0.0       0.0   \n",
       "27     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "28   republican       1.0    0.0     0.0        1.0        1.0       0.0   \n",
       "29     democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "..          ...       ...    ...     ...        ...        ...       ...   \n",
       "405  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "406    democrat       1.0    0.0     1.0        0.0        1.0       1.0   \n",
       "407    democrat       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "408    democrat       1.0    0.0     1.0        0.0        0.0       1.0   \n",
       "409  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "410  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "411    democrat       1.0    0.0     1.0        0.0        0.0       1.0   \n",
       "412  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "413  republican       1.0    1.0     1.0        1.0        1.0       1.0   \n",
       "414    democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "415    democrat       0.0    1.0     1.0        0.0        0.0       1.0   \n",
       "416  republican       1.0    1.0     0.0        1.0        1.0       1.0   \n",
       "417    democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "418    democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "419    democrat       1.0    1.0     1.0        0.0        0.0       0.0   \n",
       "420  republican       1.0    1.0     1.0        1.0        1.0       1.0   \n",
       "421    democrat       0.0    1.0     1.0        0.0        1.0       1.0   \n",
       "422    democrat       0.0    0.0     1.0        0.0        0.0       1.0   \n",
       "423    democrat       0.0    1.0     1.0        0.0        0.0       1.0   \n",
       "424    democrat       0.0    1.0     1.0        0.0        0.0       1.0   \n",
       "425    democrat       0.0    0.0     1.0        0.0        0.0       0.0   \n",
       "426    democrat       1.0    0.0     1.0        0.0        0.0       0.0   \n",
       "427  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "428    democrat       0.0    1.0     1.0        0.0        0.0       0.0   \n",
       "429    democrat       1.0    0.0     1.0        0.0        1.0       0.0   \n",
       "430  republican       0.0    0.0     1.0        1.0        1.0       1.0   \n",
       "431    democrat       0.0    0.0     1.0        0.0        0.0       0.0   \n",
       "432  republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "433  republican       0.0    0.0     0.0        1.0        1.0       1.0   \n",
       "434  republican       0.0    1.0     0.0        1.0        1.0       1.0   \n",
       "\n",
       "     satellite  nicaraguan  missile  immigration  snyfuels  education  \\\n",
       "0          0.0         0.0      0.0          1.0       0.0        1.0   \n",
       "1          0.0         0.0      0.0          0.0       0.0        1.0   \n",
       "2          0.0         0.0      0.0          0.0       1.0        0.0   \n",
       "3          0.0         0.0      0.0          0.0       1.0        0.0   \n",
       "4          0.0         0.0      0.0          0.0       1.0        0.0   \n",
       "5          0.0         0.0      0.0          0.0       0.0        0.0   \n",
       "6          0.0         0.0      0.0          0.0       0.0        0.0   \n",
       "7          0.0         0.0      0.0          0.0       0.0        0.0   \n",
       "8          0.0         0.0      0.0          0.0       0.0        1.0   \n",
       "9          1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "10         0.0         0.0      0.0          0.0       0.0        0.0   \n",
       "11         0.0         0.0      0.0          0.0       1.0        0.0   \n",
       "12         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "13         1.0         1.0      1.0          1.0       1.0        0.0   \n",
       "14         0.0         0.0      0.0          0.0       0.0        1.0   \n",
       "15         0.0         0.0      0.0          1.0       0.0        1.0   \n",
       "16         0.0         1.0      1.0          1.0       1.0        1.0   \n",
       "17         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "18         0.0         0.0      0.0          0.0       0.0        0.0   \n",
       "19         1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "20         1.0         1.0      0.0          0.0       1.0        0.0   \n",
       "21         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "22         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "23         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "24         1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "25         1.0         1.0      1.0          1.0       0.0        0.0   \n",
       "26         1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "27         1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "28         1.0         1.0      1.0          0.0       0.0        1.0   \n",
       "29         1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "..         ...         ...      ...          ...       ...        ...   \n",
       "405        0.0         0.0      0.0          0.0       0.0        1.0   \n",
       "406        0.0         0.0      1.0          1.0       0.0        0.0   \n",
       "407        0.0         0.0      0.0          0.0       1.0        1.0   \n",
       "408        1.0         1.0      1.0          0.0       0.0        1.0   \n",
       "409        0.0         0.0      0.0          0.0       0.0        1.0   \n",
       "410        0.0         0.0      0.0          0.0       1.0        1.0   \n",
       "411        1.0         1.0      1.0          1.0       1.0        0.0   \n",
       "412        0.0         0.0      0.0          1.0       0.0        1.0   \n",
       "413        1.0         1.0      0.0          1.0       0.0        0.0   \n",
       "414        1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "415        1.0         1.0      1.0          1.0       0.0        0.0   \n",
       "416        0.0         0.0      0.0          1.0       0.0        0.0   \n",
       "417        1.0         1.0      1.0          1.0       1.0        0.0   \n",
       "418        1.0         1.0      0.0          1.0       0.0        0.0   \n",
       "419        1.0         1.0      1.0          0.0       0.0        0.0   \n",
       "420        1.0         1.0      0.0          1.0       0.0        0.0   \n",
       "421        1.0         1.0      0.0          0.0       1.0        0.0   \n",
       "422        1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "423        1.0         1.0      1.0          0.0       1.0        0.0   \n",
       "424        1.0         1.0      1.0          1.0       1.0        0.0   \n",
       "425        1.0         1.0      0.0          1.0       1.0        0.0   \n",
       "426        1.0         1.0      1.0          1.0       0.0        0.0   \n",
       "427        1.0         1.0      0.0          1.0       0.0        1.0   \n",
       "428        1.0         1.0      1.0          1.0       0.0        0.0   \n",
       "429        1.0         1.0      1.0          1.0       0.0        1.0   \n",
       "430        0.0         0.0      1.0          1.0       0.0        1.0   \n",
       "431        1.0         1.0      1.0          1.0       0.0        0.0   \n",
       "432        0.0         0.0      0.0          0.0       1.0        1.0   \n",
       "433        1.0         1.0      1.0          1.0       0.0        1.0   \n",
       "434        0.0         0.0      0.0          1.0       0.0        1.0   \n",
       "\n",
       "     superfund  crime  dutyfree  export  \n",
       "0          1.0    1.0       0.0     1.0  \n",
       "1          1.0    1.0       0.0     1.0  \n",
       "2          1.0    1.0       0.0     0.0  \n",
       "3          1.0    0.0       0.0     1.0  \n",
       "4          1.0    1.0       1.0     1.0  \n",
       "5          1.0    1.0       1.0     1.0  \n",
       "6          1.0    1.0       1.0     1.0  \n",
       "7          1.0    1.0       0.0     1.0  \n",
       "8          1.0    1.0       0.0     1.0  \n",
       "9          0.0    0.0       0.0     1.0  \n",
       "10         1.0    1.0       0.0     0.0  \n",
       "11         1.0    1.0       0.0     1.0  \n",
       "12         1.0    0.0       0.0     1.0  \n",
       "13         0.0    0.0       1.0     1.0  \n",
       "14         1.0    1.0       0.0     1.0  \n",
       "15         1.0    1.0       0.0     1.0  \n",
       "16         1.0    0.0       0.0     1.0  \n",
       "17         1.0    0.0       1.0     1.0  \n",
       "18         1.0    1.0       0.0     0.0  \n",
       "19         0.0    0.0       1.0     1.0  \n",
       "20         0.0    0.0       1.0     1.0  \n",
       "21         1.0    1.0       1.0     1.0  \n",
       "22         0.0    0.0       1.0     1.0  \n",
       "23         0.0    0.0       1.0     1.0  \n",
       "24         0.0    0.0       1.0     1.0  \n",
       "25         0.0    0.0       1.0     1.0  \n",
       "26         0.0    0.0       1.0     1.0  \n",
       "27         0.0    0.0       1.0     1.0  \n",
       "28         1.0    1.0       0.0     1.0  \n",
       "29         0.0    0.0       1.0     1.0  \n",
       "..         ...    ...       ...     ...  \n",
       "405        1.0    1.0       0.0     1.0  \n",
       "406        1.0    1.0       0.0     1.0  \n",
       "407        1.0    1.0       0.0     0.0  \n",
       "408        1.0    1.0       1.0     1.0  \n",
       "409        1.0    1.0       0.0     0.0  \n",
       "410        1.0    1.0       0.0     1.0  \n",
       "411        0.0    0.0       0.0     1.0  \n",
       "412        1.0    1.0       0.0     1.0  \n",
       "413        1.0    1.0       0.0     1.0  \n",
       "414        0.0    0.0       0.0     1.0  \n",
       "415        0.0    0.0       0.0     1.0  \n",
       "416        1.0    1.0       0.0     1.0  \n",
       "417        1.0    0.0       0.0     1.0  \n",
       "418        0.0    0.0       0.0     1.0  \n",
       "419        0.0    0.0       0.0     1.0  \n",
       "420        1.0    1.0       0.0     1.0  \n",
       "421        1.0    0.0       1.0     1.0  \n",
       "422        0.0    0.0       1.0     1.0  \n",
       "423        0.0    1.0       1.0     1.0  \n",
       "424        1.0    1.0       1.0     1.0  \n",
       "425        0.0    0.0       1.0     1.0  \n",
       "426        0.0    0.0       1.0     1.0  \n",
       "427        1.0    1.0       0.0     1.0  \n",
       "428        1.0    0.0       1.0     1.0  \n",
       "429        0.0    1.0       1.0     1.0  \n",
       "430        1.0    1.0       0.0     1.0  \n",
       "431        0.0    0.0       0.0     1.0  \n",
       "432        1.0    1.0       0.0     1.0  \n",
       "433        1.0    1.0       0.0     1.0  \n",
       "434        1.0    1.0       0.0     0.0  \n",
       "\n",
       "[435 rows x 17 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Replace Nan with the votes' mode\n",
    "data2.fillna(data2.mode().iloc[0], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of predicting Immigration bill votes with Logistic Regression:\t0.524\n",
      "\n",
      "\n",
      "Accuracy of predicting Immigration bill votes with Logistic Regression:\t0.474\n",
      "With Parameters:\t\n",
      "{'C': 1.0, 'cache_size': 200, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'auto', 'kernel': 'rbf', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "y2 = data2.immigration\n",
    "X2 = data2.drop(['party', 'immigration'], 1)\n",
    "\n",
    "\n",
    "\n",
    "logistic2 = LogisticRegression()\n",
    "logistic2.fit(X2, y2)\n",
    "logistic_cv = np.mean(cross_val_score(logistic2, X2, y2))\n",
    "\n",
    "\n",
    "\n",
    "print ('Accuracy of predicting Immigration bill votes with Logistic Regression:\\t%.3f' % logistic_cv)\n",
    "print('\\n')\n",
    "\n",
    "svm2 = SVC()\n",
    "svm2.fit(X2, y2)\n",
    "svc_cv = np.mean(cross_val_score(svm2, X2, y2))\n",
    "print ('Accuracy of predicting Immigration bill votes with Logistic Regression:\\t%.3f' % svc_cv)\n",
    "print('With Parameters:\\t' )\n",
    "print(svm2.get_params())\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Creating an Algorithm list w/ elements [model name, estimator, parameter grid]\n",
    "grid_estimators = []\n",
    "\n",
    "# Logistic Regression\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "param_range = [0.0001, 0.001, 0.01, 0.1, 1.0, 10.0, 100.0, 1000.0]\n",
    "param_grid = [{'C': param_range,\n",
    "               'penalty': ['l1', 'l2']}]\n",
    "grid_estimators.append(['Logistic Regression', LogisticRegression(), param_grid])\n",
    "\n",
    "# Support Vector Machines\n",
    "from sklearn.svm import SVC\n",
    "param_range = [0.0001, 0.001, 0.01, 0.1, 1.0, 10.0, 100.0, 1000.0]\n",
    "param_grid = [{'C': param_range,\n",
    "               'kernel': ['linear']},\n",
    "              {'C': param_range,\n",
    "               'gamma': param_range,\n",
    "               'kernel': ['rbf']}]\n",
    "grid_estimators.append(['Support Vector Machines', SVC(), param_grid])\n",
    "\n",
    "# Random Forest\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "param_grid = [{'n_estimators': [10, 100, 1000],\n",
    "               'max_features': [4, 7, 16],\n",
    "               'max_depth': [2, 4, 6, 8],\n",
    "               'criterion': ['entropy']}]\n",
    "grid_estimators.append(['Random Forest', RandomForestClassifier(), param_grid])\n",
    "\n",
    "# K Nearest Neighbors\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "param_grid = [{'min_samples_split' : range(10,500,20),'max_depth': range(1,20,2)}]\n",
    "grid_estimators.append(['Decision Trees', DecisionTreeClassifier(), param_grid])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Logistic Regression; CV Accuracy: 0.967 +/- 0.018\n",
      "Model: Support Vector Machines; CV Accuracy: 0.957 +/- 0.037\n",
      "Model: Random Forest; CV Accuracy: 0.957 +/- 0.037\n",
      "Model: Decision Trees; CV Accuracy: 0.951 +/- 0.033\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "# Performing 5x2 Nested CV for each algorithm\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "for model in grid_estimators:\n",
    "    gs = GridSearchCV(estimator=model[1],\n",
    "                      param_grid=model[2],\n",
    "                      scoring='accuracy',\n",
    "                      cv=2)\n",
    "    scores = cross_val_score(estimator=gs,\n",
    "                                X=X_train,\n",
    "                                y=y_train,\n",
    "                                cv=5)\n",
    "    print('Model: %s; CV Accuracy: %.3f +/- %.3f' \n",
    "          % (model[0], \n",
    "             np.mean(scores), \n",
    "             np.std(scores)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grid Search Best CV Accuracy: 0.967 +/- 0.018\n",
      "Grid Search Best Parameters: {'C': 10.0, 'kernel': 'linear'}\n"
     ]
    }
   ],
   "source": [
    "param_range = [0.0001, 0.001, 0.01, 0.1, 1.0, 10.0, 100.0, 1000.0]\n",
    "param_grid = [{'C': param_range,\n",
    "               'kernel': ['linear']},\n",
    "              {'C': param_range,\n",
    "               'gamma': param_range,\n",
    "               'kernel': ['rbf']}]\n",
    "gs_svm = GridSearchCV(estimator=SVC(random_state=33),\n",
    "                  param_grid=param_grid,\n",
    "                  scoring='accuracy',\n",
    "                  cv=5)\n",
    "gs_svm.fit(X_train, y_train)\n",
    "print('Grid Search Best CV Accuracy: %.3f +/- %.3f' \n",
    "      % (gs_svm.best_score_, \n",
    "         gs_svm.cv_results_['std_test_score'][gs_svm.best_index_]))\n",
    "print('Grid Search Best Parameters: %s' % gs_svm.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x29fc2debd68>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ynShNQ1cu3xvqHpsbIoQQx5AEXSGEGEOp+D6m2MVFHZ4KTGeO1Q+47NdDnFko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Q4XEdHCw9gleWQZoIxZhyCphup6kpZ5BCMKaFUB2bjvJMfL5J5pljbhNYKYFgrIJWzzQTbArG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VxdPsVF1hkeiCyiw51mXDAIEOmWq1nsTLDCHOFFo53b8nvZou8kAN5ROExQ2R1P+CEpolHW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\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r+jQWOcGAVqeToSBUGtwSGj4ZoWMiUZiYjeeq3BJ9lN/Fl3BMqUWvaMJCkoRnR4k3HcR3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5IreMOczCQvwyOx+dyd28K6cBvLK33EpEUVlZ/H5mNKh1uLe2jwSsyxhngiOouF1gArAvlIgic6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0JLKYgKR9UKvhdewZjkw2sVeXf2MFnB0Z1oMlO4sfBicm0JG2Ug4sXkS4k3uDW1hWuze/l6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SVk7jADvVGpqtDGVE7vDPImoV6DCyiLIOho9eOUynmXCFaIIAtk1ncYCUIzAm+pGAEVtE\ncByKlQ1T278Q3b9bmr+BYn7wFSeerfFFMByHbfprQ194cTmOg57pmaItPF1IYfF/i7ZwvPzRWRRS\nh7HtFzzjPxZvpUv1uRt3QaBXifC0FMe2dI5u+zxjR+8CwLFNzOIksabTaF34cXBsRnv+yOrGVVyW\n2839vulsVRs4vdSHDXSUkzzkncaE6GV9sZcrs1vAcdjgaccwQuzpO5/bOAnb9KOqBepjP+Gn1f/O\nJ9pupmne7XS13cX7or/C9OcYG5/HyN4L2D1wFkIxzLjoJegYSNjYuIFPEg4FQeZkvZeV5hhPexq5\ny9/FLeHVPB9bxj1OgFWlQYpI5JC5KbKOmK2z0dPE+zNb+VB2K+1WmhG8rCv1c0COcV7hAGNqnLtC\nSys0MR0QoLCdL+67A49V5Pr0Jt6W24Uk+2hZ8BEaZl3xkpZa/92K1K3GccDnlBmRg3SZkxyxBYbM\nIpq/EdVbS3b8OfzRLupqlnBJbi971FqWGKOMSz6+4p1JPttPuZggUnsCguShrZzkzvE/8CGfS7dT\nHYv5tsmJpX6e0poZVMJcZY9z5uiD2Ih8JLaeBflDhGqWIwgv/dkOj+9GF2QumHUZscaTpjyoj2z+\nJAN7f8R4790UUgfxhjvQMz3kk/uZ7N/AwL4fcWTLpxk68DMcu0xd12W0L70Bb7D1Zc/JqYEY2/Q0\nKct8yd/LaohgfAG17RcjOEX80VmEqhcjq0GqWs6gY/lnObl5HUeUGCnRg1EYwe+U8WCh2zbRhnXU\nTX/ry/7917XRrWpxvWNPGr4H//R3cEHhEALwe/8sqq08B+QYNbaOjoKNQIeZ4HeBOTzmaaOlnOYh\nbzv7lDjNZhobgce1Fn4TmE/D3PdjWyUmBx6hWOEz9ogBflHxJ31/tJG3hOv4z/6tZEQPkmNRL8CP\nG2e/ZJNrODZXDe2nx9D5XsMsZnnc5jjWvJ5yKcGHSDLPE+DakUMkrTI3Nczlk5GTmPBUPEudMqmR\nZ9AzPcQlhSNyhAe8HViODY5NyC5N6QFfbI+23BjkxtQTrO//Hd1ShJ1KDR3lFH1ymFlOnq+EVmEI\nEu/N7WCfXI2DhCQotJdTXJ/exOrSANcnn+IrqcdZYLojmS8lH6PBymIh8LTayI2REzkmhflo9llu\nTDyOx7EQcXhAm0aNXXDtyoD7vR0odpmtnkZWFgdYWxzkptBqFppjROILeHDMtXZa6/Fhl3M8q1Rz\nRPDwJsdDengjdlkn1nTKa34NxWWVSyN13JUZ42ApT4fm472xJu7IjPFkhVcXlmTODsb5qX8uCdFD\nZvBRfPHFAJydP0hJkKk3kthAsLKgTdr2VDIZwK8C8ziz0I2IQ1GQKSMhORYqNmfrh7k1uJhOcxLN\nKfMfSivvq76QHwYXUxBV3pbbzUatmRtST/GLwDxazBRzzHF2anWcrvdwc3QtDqBVuKUXF/aTED1s\n1pqI2CUWF4fY6GnGcSyKleNZWhqh2l/DZwLLOC1YzfcS/eQcizW+CGdarrjy95bGZZF6wtLLq01f\nz/KGO9ACzTTbefyOyVNyNWG7RB6ZUs5Vf2uBMdyIaxEbWFEaxEagzsrxvFrLacWjqHaZ57U6Tike\nxRQkuuXolGMJwLmlbgqIzLASaA6IosEpRj8zjQk2eNvZWVGa19tFBuUgz3hacAQBU5CQcFhVGuD7\nE3fjpzyFxs80J7ndP5OU5KHGzOKU/CiBUUAmKXoIOwbPai6iErMLriemVWRIjVIrq6QEhZDgTCV4\n/Yu68PfLE2h8VVHAy31hFAQ25l/Z619NGfoYlpn7C9pCUJRY9D8k5nw15Y/OwrEN9MwLG3tNFPl6\nfRflF+0Zvhdbiy82D8exMfKDILhcxuPv4Qk0EmteT3b8OSaHNpGseI7f45uO3y6REl3e4+X5PTzk\naWOROcof/fNQHIucqDKoVrPEGOEI9VgIDB05nZH95/LQsbdyU+rDPDh6PiOH1zO4683c2XcDb9M/\nRdEM8gb9EKOij/fEz+MX/vmYiIjAH32z+EjsdEpIvFE/yA3Jx/jRxL28sbCf/XKMrzlhTi32EbcL\neLD4eWA+q40BVGxO0XtZXRygjEhRkDmoxfE7BoflCLaosGL+h7lHdteEpfogqq+Ox7EYNnVunbyf\nJcYoweqldK780t8gla9FecMdnEiBcdFLyXHQsGkvp3gg0YsgCASrF1NIH6FcSnNG9QwEHGYZ42zS\nGglbOju0Oj5edTYlxyEzuhHHctcYBYeT+36DxzaIOxateg9ep8xTnhb+I/ko540/Agj8uu5cTDXE\nTHP8ZSkHQ4ZOTa6biUAbtaFGatovonPF56nvugx/bA6l/CCTxx4EIDP2LMd2/gf9u7/L+NG7KOWG\n8Ien0zj7PbQtvZ5I3UqEv2PtBbA+UIUFPJ77+3SkUM0SHCnKRN99OM4L0xxBlJhfu5iYpPB89YkA\n+GMLyAsyR+Qg3rYL8Udnvuz7vq6Nbqh6GahRGq0sO4c3USdKrNd7eNDbgSI4FEQ3096SfSwwR7km\nvQXLgTorw1eTj1BtF/hG5ESKooJQMXH/pX82Vw4fZsfgRhxLx4OFhcAnoqfiAAskWO2Pcl73M+xV\nYoiOjSVI3NI4xx31/FVZjsO1w4fYXEjz5brprPG/gEgGYnNQfXVkBh/l23UzEID3DO6lTfVyTlU7\n7w6dSDY8E3AQRYlg9WJiLetZ7BQIiDL3eDpwELBetLgLL/pXBJrKaX7ln8eIHOCb4RWYgkiVozPD\nE+GIWkW3FCFm63gxsc0U1e1vRADqrRzXpLcwJvmZZYxNfZFxW+fCwiF2KdUkZD8X5A9yY2QttgON\nTh4Zhye1ZpYZI2hYpNBICyqPe1ooCxIzjAk+kX6ar4VXcrZcRnQsrLLOVqWGpnKaOjMJosZvAvNo\nklXWOSKJgUfwRWbgDbW9HpcR769qJiTK3DTqjlU+WNVMh+rl+pEj5CoOCpeE6xgWNQ6H59Nspdlp\nujvHJjtL1CogACcHYqQro1AR0CqICLhc3U/HTmZlsR9bEPE4ZX4UWsIhOcpF+YOAwI3Rk+g0ExyW\nw1yY3UlW0jhVP0pW1Ig6JoYgEbQNbkk+wgaPG7rxqNrMoBximpmiJMq0mQkWGaPc6+3kgFbNRfoR\ndmp1OMBM84XRzqVSgWPtb2MckcWeID9IDCAjcGvDTPTsUYqihwk5zDv/l9BccGkjscaTCVXUrllg\ndWmAh71tOGUvZjGEFhhlhjnJdrUeEddw/iz9CCVRYbtSR9zW8Tom+5RqVpYGURyLHWpNRdsNIxX6\nkq8yCZEQcGyXT3aq3kNC8tKjxBCAqK3zjckNdDlDyBhTHN7VpX4kh6n3bDTTdJkJ7vLNYFFpmJXG\nMDgyjscVesoV/nZ3hYbRWk5jCzJt5STjSowIbthHqyzTbejEJIWo9Nrw0v9fLc3vaiJeqZ+uT5RY\n7A3ydOG1b3T1tMvP9YY7cI7bivn+523FXkn5I10gSH9BXwCY7Qnw/ph7ToNWkaRt8fnICXSs+Dz+\n2FxwythWERCY7H+IzPh28sn92EDCKnGft5OmcprDcpSDcqxi9wfn6keYXhynIMh0lVNEbR0EgR/7\n5zIkBXhfdjsH5BglQcEoRmlOeLkrv54N2dM4rM/CtjTmFXr4ZHoTY6IfAai1C3w4s4WnvU18M7yS\nrUodFxf2c53Zy4kNy2ie+wGmLbmegCBQ0OLkJI3VxX7WVzyuD8gxLsnvZVVpgLKoYgKhSirqY1oL\n60r93OPtZH2xj61VJ6L5YoxX3G2uKOzi15EVBByda7LPUtJitC+9gcZZVyC+TgmSgiBQ03giu5Ua\nmi03XXFdsY8HJl0HjVDNEsAhM7GD2ZqfbeEFXJ/e5IY8yH4kx+KwHOSi6Jn8oekSZG8tR3zTeNLX\nhWob3Dp5Hx9NPsE7cruYFD3cmHqS6cYYshYlNOdqfu/4WFs4ii/cORVg9dd19/B2YnaRztoX0ktF\nSSNct5KGGZfTvuxGFC2GFmimZcFHaJ73IZrnf5jpq75Mx/IbaZj1ToLxBa+Y7jHPE6BGUnkk/7f0\nhb88dyL4V2AURkgOPv4353W5N8TvpVokJQCUKYpe5htjPDi6++++7+tLXRAEmme8HYC2xHNIgWZm\nGWP4HZPvBZewyBjhiK+DqFNiVApxVK3mi6nHOaN4lLwcoracZURQ+ZF/LgISHxPTfKG2g616mrcU\nPTyn1OIAD3vaKEoqs81x8pKPywb2YDg2EbuILYjMkARWv8RY6niTe092guvi07gwXPNXxy9S1XQa\npfwgsXwP32+czUjZ4OJjO7kwWMMSX4RPyi7JXfHEyY5vZ7znT1jlPCflD3B+8QgTouuPekfN2RiV\nNlf01EIFifZhc1FhP9/IPcvF5TG65SgLjTGu6P81EavIHYFZbNKa6CinMBApZntQPFUo2ORElQv0\nQxyVIxgv+ipVLOqcEppd5n5/Jx/JPEsQN750r1zFitIgVU6Rg1KUKCV+4Z+HLUg0WFk+nNnCbVXr\nOORv47T8QVRfHWMTz7NbrWZFOYGe6WabWs0hJcb7q1qQ9f1YZpZ4y1mv/QVUqaik8PHqaTyrZ7g7\nO4EminyxdjrD5RJfH3e9gpd4g0xXfdzln8tROUZNei+EuhCAd+R20ytHoFyivWLqbwOl499zJaUs\nK6g862kCx0FzTDTb4vvBJQQdg/P1Q7w1t4eAVcIUJCYkH9+fuI8rs9uxgFNL/UTsEp9Ob8TrlHnY\n24bPNhlSwq6YqeTSDi4oHEIXZO7xdhLE4dzcPqK2ztcSG9inxN1xGw7nzL6c+3QdjyDy1YleLOCS\ncC1+SSab7mG3HOMtkTri/8vimVD1YkQlhIlAezlFHIt7vJ2uqXeuBs0/xhxzlI0VFwQbeHN+H31S\nmKIoYyKyyBilICr0yhHiVoH9FQGaCMSdInrlvjlO/3FwN4pnFnsQHIeCoODgsF+K0Bc12C82MbOU\nQHJsFNtibfEYIce9+xKCB1mAe33TKYgqy0pDLDMHEUQDXZDJCip1lpsyNym518o0K0tBjeDBZlLy\nIlTGb4u9YY4aOh3/QnP/YWl+d0P2gpj4H9caf5S9pfwUH/+1qkL6CJISQPXWcKCUZ6Rs/J+kLYDb\nfPhCHeQm9/zN7z4UbyEkCGQlDwrwSD7JpyaGkLquIFS7guMh2oXUQYb2/4T95TLfjq6jytZ5c+EA\nn9L3cU1mC98NLkHEYVT0oeAwqoV5xDONE0v9VBkut3SnUsVtkdXEbdeyMVBxL/E7JjPMCXZodXTL\nQfKCSlM5SZeVotnOckwM4ACnFPu4deI+RkQ/X4it4xf++QRyR5kMzWCzHOfTvZt4V3Q9D8jVzC+N\n8oHMNkwEUmiV6HZosPJItkFZcNHDZ7QOlhgjDEhB1uh9fDW8kn+b9QaeHj9CGZHacpYdWiMXDt3F\nPGOMHwQX0bjgo2ivMPTgn6lw7Qoito4M5ESNFaVBdopBhsaeQ/PVofkbyY5vRxAETog085C3ne8k\nHqS5nHYDcRyHsiDwMxPODq7l34Ir+UpwEddFT+FRbxsBx8CLKwpUJY3G2e+lc8XNPCJGsIC1+UNU\nNZ32kseWtcokJnZhI9Dy/7F33uFy1XX+f50+vd2ZO7eX5Lb0Thq9hd6FVRRRVMq6awP8ievuWtZe\ndi2goIIKLBYEBCIYkBJKAuk9N+X2XqbX035/zORKINGgtH0e3s+TJ/eZU+bMmTPnfL6f77tE5h9x\nnVzyAHphklDtybj8LbiD7bgDbeUC8/VDFARO9YR4Jh3727x7dRqe0GzGuh+hmBs/bNEyl58e00CI\nHEdmchct1UvII5EfePKv0qLedAWLO9gKVaVWsx7fRVxyMa84zE61kj87mqjJ9YLspsbOc3JuPzP0\ncX7mmccN/pP5aHorF2T38pirhV+5Z/Bs9Zn06QUWCgY1epIF+ggC8KSjlEa1TwkxoOdxWDqmIE51\nyP6zeuZrjutQkftQaozPhBuP6sLgq1yMrAWZ6FvDUpef3zTMRQCuGtjBR0K1uF3VxEQHaa2C1hXf\nZFqZVO2vWkEBkduDKxGwiWcHOVhuuev5Merm3DBFY1Bsk+ZcH+fF1zNDHy/TCSzO1Id5WavBaxX4\nmWceKhbJ0ZdQnKWHRtjKscPVTKWZQcUqT8yWUGUk+O/YGqJmlm7ZX7ppCBodxiRauTtWa6b4uWce\nf3S1oNgmn0q+zL9XnM2jcpT/9iiYuREsI88WrRZDkFgh5LERuNfZQY0ocqE3CLnNOP0tr8nGfqNx\nuT/KbM3D18e6SFsGi10+PhCo5lfxITZkkwiCwBWBKFv1LELdabhtnV16qZQ9Id9LURAZSHXz9ehf\njvPQxW8f6uQIAoYgIWKTEJ2kBIVmI85GNcrZuQM86O5gvbMebJsHXO0ErAKabXF9ejPvSW/DaxfZ\npkTYpFYzIblIl/1iT8j1sMlRQ5Me46R8D2sczaQlB0XbpF/2Mksf507PfKTy9/JPoXp0Ssbmedua\nsqn7aEUdpp7Fyo2wVwnz0dCRr9m3EoIoE6o9CQWbucURXnDU0WrE6Zf9FNJRRFlntnyQLWrVlNd1\n0CoQtTLMKI6zRY1yfjl9aaNaxXGFAbarlRgIpAQFGZuY6OKH7kXA4R23cdHFydlS10ewS9/jt5Wz\nODO3jxuT67EQ0AWRCdGBp1wm64KIZFs84GrnhHwvcUGjwUzh8A2SLQRL/FwjxpjoKoWLAB3FcXKW\nRULQGLNsUmXx5jJPlAPF3Lv83GOAJDtRtAryx9jRBaZcUt7Irq5t22QT+3D5WxEEgdWpCUTgVE/o\nDXuPNxqe8FyK2SGKubHDXpcEgSv8VQi2zaGhwAOpMU7r3sjPPPMBgWxwNi9qtTzQ8F4+6TueP6s1\nPONo5H2ZXSxvPofjikPckNrIU44mQlaen3nmMc2I84JSesacYAxNvd9t7avYoNXSYZSeqzYQFzTO\nyB1kTHKTFjUeDSydWrZFqSRkFUmUw1+ctsF3Yk9wdWozj7umcUvoVB7Z/yhf6V3PI1KYeYLOwvwA\n16Y24bWLCNj82dnELGOCfqU0ENkvBQjYRXbLFeQFg6iVYaNaxd3eedSVZ1W+P7CBj6Y3c+vk4xyf\n7yUuOvh8xbkMViyhWfv7YulfL2TVx4m+KrpkP6ZtU21mEIDV/S9QzI3ijSwklzyIno9xtjfM3e7Z\n5D2N/HhyDdPNw/2jTcQyxU5glxLhVu8ibAQGJA+Ks46WZV/FG54LwB+SYzRZGdo0J+7Qa+segN8k\nRliY7wPfNCTlyCLaxPB6REnDGz5yIfz34BxvmIxt8uQRRGmHQRCItl6BIEgM7/vfwwrYFeV7wlZf\n6bMJiIwqARbketiROvq95S2Rare3XsagVkMahcuyezg3s4+O4jg/884nK8jsVYJ4IwvwVy6mpvVK\nlgl+vhZ/ikYjwXjZx/I+z2y+GJ/kZ5MDdOt5rkttQgD6JQ87tUoCZoGA7CRnW+RFhY+nNrNOq8Yv\nwHGvGq3rtnVYkXtDRf1Rj730ID+VXGI/uWQX7Zqb3zbMo1rWuH5gN9WKRqdWTSbeybpsHNVRgTc8\nD+f09zASnMOH4uvYpVRwXu4AJ7achy6oSFg81vsM67RaTEoZ3nZ5ulQQZNZqdeSRWJgfQAQ2a9WM\nSy7uKCvSs7HtHPrq5uoT9Ek+fuBdzFqtHpOSN2JSUKk203w5/gwX5zpRsAnaBRKixvc9i/mVew4f\niZzP/a4OEASuT27gT44mUqLEd6vbqJnYAIKIUYyzQavFZRVpS+1lq3s6e9UwN4SbyI28hGBlCDec\n9UZfMq+BJAj8Z3QaI0aRH02UBEw3RpqokTU+PbSXcaPIZb4obkFijVLFXmcD7bleUu4mHJickTuI\nbtvYgkBHWSE/ZfBv2zit4hRft8rMlCgNosgzjga2KZV4bJ2LMyWbnyojRV5U+IVnLj9yLyCDxP94\nF/O54Cl06OM86mopeb2KIn4rz/XpjRyQAlyb2owuSNznmYXPNvBYRT4RWsWV4QvZqlVhlUUDIUnh\nit7tFGybuZoHw7I401NBneJgMLYXgEiwheojxDW+HQhWr8REIGpleUkOc3y+l1+7OiikS50Tj3uY\nSitDj+wnIWj0Sj5OyPexqDDI81odHcZkiaerVnFObj95UWGvUlGy9gJ8dpEWY5zPB06eGhxagMcq\ncG5+fzntr6RA1y0Hn0hu5N6yRZ9imxQElUL59xKw8vzCOw9dELkyvR0bkGxwBXpwZF10ywFa9Ul2\nKxVg2yi2waLiEF49wXZve+nhXq7Ya1QHk6b+bkf3GKF5ao7ZYgxK050+UeL5N7DQ1fPjGIUYrkAr\ntm3zSGqM5a7A2z4z8tfgrSgVMamJba9ZdrwnhC0ILCkXny5BYqUzwN3pBJ1ykIPpYb4SOIGfFkqF\nkkeUWNhxFaqzgpHOu5FUP+3GJMvK9oqt+iQ3hU5nm7OG57R6zsh3ES4nDz4+tJ1FvloOyIEyDUjA\nbxc4Md+HZhl0KUEWJLZNDUdb9UkcFPGXnzseu8iQWsGF2X3cOf4op+d6uNs7h7yocHq+j0k9wzXp\nrdSbSSRs1qu1rCgO0Ct66TCTZJFpLQdHPavVsyrfxWpnCwnRwXqtlvdX1PP4xu/w78nnOC+7j27Z\njyHImC3vZY/s4lJf5WvO35uJQNVy9slB/HYREZvFhSHWKZX0bPkumquk70mMrGe25qZWdfLT0EnI\nqo9bk8/xWzXF2Zl9VJs5FGwqBIuPpLbyrNXJ5wudNJpJJiQ3TfM/PuVX26/n2ZRPcVJmP6HaU49I\nK8hbJg+P7abRTFJ1FL97yyyQGt+EN7wQUXrjnjHLXH6qZJWHkmN/c11FCxJpvpBsfO9UVDeUtBBR\nWeUZo+xZPLKOWTUrEYCuvj8fdX9vSaErCBKNs67hXs8s1qk1zDXGuSG1gZSg8lv3TDbYGrtrz6Fy\n2iXkkvuZlXqWarvIV/0raS2OczIl/pAEfIwEt40/zHx9GAH4sXcRC/Vx9qkhEqYBgsAF2b10ST5M\nRC70Vx92LJOGztX9O3koNcaNf6PIPYRA9QpE2cVE3xoAahSN3zTM5epgDetyCdYpxWADbwAAIABJ\nREFUYQJWns91v8BJB17mqr7tnHRwA/+qtGGpAXyWTtRM8Z2DTxOY/h4A2hPb6fO2IWFjIbJbCbOp\n6mzal3+dp6rP4Tv+Zcwq9LE4P8AaVxuXZvfxkKuNF9Ta8lGVnraWnmSWMc61qU2kRRWpfE6uD5/D\nH50lsUVSUHjU2cKPvAv5YPgC/uRu4T7PLNr0SbxWgUozw5n5LvaoEX7bMI9VskV6YhvYFpHmy3hZ\nCbNQH0Mw89ytNRPF4BJfhIm+NdhyFFeg/R++Ro4FC5w+LvNVcufkIPsKWdyixA9rOpgwda4b2I0i\nCLwnEOWR5DgzW99DWlBI5cexgCszO+iSAzwR6+VTkZI6NH8oTlgQyAnyFF93UPbQoMfwmzlygsLv\n3TN4Wa3mgtw+Vua6+Xr8KRr1OI87p3F9ZjMPu9v5k6uF07MH2S+H2KDVYFBS5d82/ijfCxzPKYVe\n5uqj/NI9m4To4Hqvn+9N/okaM1nyk576RuGrY110FjOogsAZnhAp2+L6cvf2xZHN6IhcVLOEdwok\nxUPCVTq+aiNNvZHkRa2Ogu7BKLjRPCPMKI6zVqsnaBfYJVfgK0+99Uo+TASajTh71DBRM4PT0tmu\nVBK1MiRR8No6C4qj7NCiPORsnaI1uDCJmhlqjBQOS5+in9zhnsMa5zTOz3by/vR2GswkIiWl9zcD\nK9miVfG+1HaqzEzJc1cwUL2DKHkX46KTgF3gZbUaBIEKM4sTEwcmY742AFJCyT/50BTcu9Zix4ap\nKGDr2KgIkiCw3BXguUz8mN0a/hay8ZIHsyvQxo5Chl49z7ne8Buy7zcLiiOE5q4jPf7aQneR04eM\nTX1hhHPdQTK2yVPZGFWKxpi7gRn6BMGymKlJdfBA4zyW+KLUzfwYlllAEEq+1W5MxkUnJxb6ODfT\nydcm/8wOuQLNNrm87CF+R3yQxsgc+kVvWdRpl8Of3Kws9LJZiTLdSoAgsc7RiBMDCVitNZNEQQQq\n9QSRxnOoCM3kPdld3Dv2ADcmXiSDwKDk4zbvIh5wtfO41sReOYjLKpLSKlDMUtJaEYFH1WYuz+2h\nR/LiM7LUG8lSOti+XxHIDfJr10w+WnEOHcYk09o/wAOWG7ctcJ7vrfUad4dmcrI+yahQCiI6I3eA\njY56DFFlaO8vcXgaiQ0+g23pXOKLsqZQgOmXY+hJXP2ruUlKsXbGqezpOJHVzhwXZ3fjq1xCZaab\nMdHJmbM+hPwKKsEj5QLyFHMCX/TIz4d748O0ZLqBvwygXo3U+BYss4C/aukbej4kQeB8b4RnMrFj\noiMFqlfi9E1n9ODvywlpJTrscpefF7MJAtUnlkSlipNuJcy0bNdR9/WmFrrmK7LNm9yVPOlumyq+\nphtxzs/u41FXK1EzTeWmL7J/3S0kRjdgOxfS3HYlKhZ3eeczO9jKTRUlL84f4eMu9zx0JHolH5OC\ng61yEAWBIjanF/q4IN/L711tIAis8lZMHcOefIaLe7ewKZfk21VtXH8MRS6UeFLBmpNIT2yjUI6x\n9Ekyt1RO4/npx3FydemiWqqP0W8UWJdN0KA4+Gp1G/PmXEeTM0geienxrZydsuiTvMjYLE7sRHaE\n0bQg8/QxOlO9FESZb1a1sdFRz0+8C7k4u5eUIDFRfx4rC318L7CcjPDa7kMwNIfzc/uxgTNzB/jF\n2B84L7cfi5IP8Wm5Lm5IlXLE7x57gG9PPM7SwgApycEp+T5Sgspxwem0Czq9234AQOW0S9lVTDEh\nuVhcGGSnfz67lQo+5g2RHVmPUZgE1+K3LJEL4KZIE15J5p8Hd5MyDeY6vXy3uo3N+RQ3D+/j/f4q\nTGwe0UGvPZ0qM82g7KfCyrOoOMz2WCcnu0MEyirRqSMXRIRDhS8CvUqQSitbtsMR+LWzHbetc2m2\nk4iVo8mIkRcV/jNwIr9yz2GumeLy3B7u8s6b6gxfm3gJDZs9kp9rUpvZJwd5xNmGDJyd2o7TNhmS\nSilQSvlIrvBHWd24ABWBszxhfhUfZoXLz1ynl225FFqqm4SrhkbHkeMa3y7UN18AwFn5A7zsqGeW\nPsY2Rx2FTBTNM8qc4ghry8lp3UqA9WoNLlunxYixTanklHw3uiCxS4nQpk+wWYsiAi9r5YGqIHB+\ndi93euczUva3zSMQsAusyPeRFyRE2wJB4EH3DDx2kUsze5ipj5FGRsHiYWcrL2m1nJ3pZEVxgC7Z\nz3x9FM07RMIIASJlP3Y6ldJ9o8rIYEkOsoKM6SoNMu1y9G/Xu44LrwtTUcCZob+57iEc7w4wZBTo\n1o8e7/l6kE3sQ1K8qM4ojybHkDn8GfFOhTc8l1zyIEaZM3sITlFirqKyQ63kqy4431vit3tFmdVi\nEAmbD1pjfDKxnvsq62gsX6uau5rq9g9gFEoqeAuBQlk38t7sTgpKgH/ObOZPjmZW5Q9SoycZkL24\ngzM4oTjAIZZlyZ3G5szsAW5JPI8N7BACLMz3kxRKYvNzCl1UWjkKiPRLbsZ7Hi1N2yOgI9KqT3Jz\nch33jT/AvyZfJmzmGJG9FEWFB1wdeIqTFBF5Qa1ji1LFCn2IgJWn0Uxxoj7IouIQ27RaOhsv53b3\nIu72ziVs5nCHZlMMzeaPqXFORcP1JonPjgZBkKhrOpPNWhUC0KrHSNk2+1uvQdGC5DN9mHqKwd13\ncgEJZGxu7d84FWaUS+xncPddpCd2MtH7J0TZzdq9v2aaEWeHo56A9y/UNdu2eSA+SEdxnBlVxx0x\ntCljmdw22c8qfRjNXYviODJdJzG8DsURxll2JXkjcbG/EgOb1am/3dUVBJGqtvdhWwb9O2/HMktU\nxOWuAJOmTr+zDoe3iYm+P1FbvRynfXTu75ta6L647/6pv59PDpNG5KR8L3r5B3V1eitziyN8z7eU\nF9VadlYspWHuJ8DOM7r7Dm4pHuAybwU/jA0wZup8Lb8bzTYYl1w4MHnC2UyjuxJTkDCwud4Y5BPx\nF/m6ZyGNFPCIEoucPkzb5n/jw1zWuxXdtrmvfu5rhGd/C8HakxBEhclyV/cQ3KLEFdGZKI4w/6IU\neLRxAXMdXnYVMnx2eD/LenZwnnsFj7haWVoYxGVm2B+cjwA066Mc1KowCxOMS17Ozu7ju73rcQ79\nmZviL7Da2cJmNUqjHueXmSQfc3nICjJr6i6ldeV/g/AXS4/M5FagVLhVmRlSZX6oiYBmG2jlW5MT\nE03x0mikuM89i9lGjH/KdTIpOvjg0EMcWP8FzGICzVNPqO4UnipfkAsLQ/xCrSNi5XhPRQNj3X/A\n6W8B9ejeeW8GwrLKD2ra6S7muGm4E8u2WeUNc3O4iUdT4zyQGuN0T4j7EsMsalrFXm8HdUaCAhIf\nTG9j3JYYNYqc54uU/JdfsW8bYapIXag56Zd8HCqFd2tRXiqbl29SojzjLDlM7FArqbMy/Mf4n3jI\n2cJOtXRdLcv3cX6hi53hlXwgswOfXeRH3sXYosgl3jDp8S084Gqb4oEa2HhEia9WtdJZzJKyLUKS\nwqhZ5LpQPbZt883hPbQaMZorZvFOQ33FDNKCQrs+wYtqFSfme/iFs4NCuhJJybNI3M+g7CUmaCwp\nDPK/7pko2Jyf3cdmNcqp+R6wbdZpNZya72a3EikVl4JEEZGoleXS1C4MRL7qPxRKUupGea08CCJn\nZEs+yAgiaUHle77jmJRcrHfUYgG/9szmI6nNnJ/dS7WZJivISNi4wp0MF0sFtccqltweypSpVn0C\n29JZr9XCKx6UszQ3B4pZVEGgTjl6NOa7+AscnlJjIZfqOeZtDnHynsv84ylptm2TjXfiCrQCsDo1\nzkp3gMD/AccMT8VcwCY98Vp1+UpPhP1ykNH4Qb4cnU61rJGzTO7qOBdBVLlU1jkj34U1eXhH2BdZ\nQKjuNAA0ZyV5oaQS8FpF/MUxErKfkJ6lKEhcndlGXpBJJpNIosSA5GO/HEDGpMFK0W7EaDFi3OOe\nzQxrgiHJw12euXzHexx9khc3BgoW++Qgf9KaKehpFErWWyoWNgIjoouiILKkOMhVme1cl97MhzLb\naDSTqFicUuxlgT5MyM5zUPLziGM6NwZP5ZOBU3nvvOtYbiXYqZUoR2elOqmoP53fJUbQsTnHfnt+\no8Hq4znRzJBDImjnabKy/DaTomHep/BFFiMIMunJ7eR3/YQTcj2scTQRXvBZph/3JUJ1p5KJ76V/\n523YVhELEVMQSQgal7T/02Hvsz6XYL+hc2ahh2DNkUObfhkbRCgmqCuMHJV7W8yNk03swx9d9qY0\nsNo1Nx2aiwePgb4AoLmi1HR8iHyqh/6dd2BZ+tQ94cVcgnDjORiFGI2qiy7f25SM5k4dJDW5G9PI\ncW//OtxWETGyhI+Ez8GQPahYfCG+lhYjxncDy9icT/PYnl9Dfg+hulOYtuAzfK26g6sC1dwVH+Jz\nWjsnZbs4Jd9DQtB40tXKs3pJ/flNKcF5E89yt3c+GVElJ7lZ6fTzQjbBed2b+beR/cx1eHiwcT7z\nnK+/GyYrHgLVK0mMvPwaUQCAO9hONr6PdtXBbxvmsnbaYu6sm8W/RZq5KljD8sYzkbD5l+TL/Eio\nLE/qQCixB0uQCLqrcdoGZ/Tdz3jPalb5KrkpVMOv3bNoMhJ0o7IzPcjxxjj35gscPPAA2K+OoYBf\nuWYTFzRCdoGEoPKQo41hyTflS+povICvOufxR9d0YpKTq7O7Uc0sTWYSJxbesv9spPEc8uk+1ksh\nWvUJukOL2CV6+IhikexZjWXkqWq5fGq6/63EMleAz0WaWZOe5NbJEl/3Y6Fa3uOP8qOJPiwbYqbB\ng8kxzpt7LfuVMBIWdWaKmcY4Dw5t5TxveOqcTaFsNyZgs7mQ4/hcHxdkOzm+0EuDkaBFL3UW2o1J\n3pvaRsRIgyAwuzDM484mfupdBLZNxEjzheQLgMRmQ+fs3H4edrWyT61AAG4S4hQsk9+7Sr5/ajkg\n4f2BkhXM/YkRamSNJ9MTzHV4WOHy82hqHD3VhYhNIPjWUEVeL7rUSGka1UzRqk+WzL0zpS5uyD1A\nxMqyUa1ivj7CqORhhxKmzkohWBZOW6fSyrBeq2VhcRhTENmmVDJXH+URZ0lAKIgCM4qj7FdC7JIr\ncGBiA5fkOnFYOnvU8JTVmS0IbHbU8LXA8dQZKbrlAFekd3BSrocqK4eKRZWZwQDc/kGK+SCjootW\nPcaA5J1SPi8oDiPZJjuczcRMHUf5qlniiXCwmKNRcU6JBd/FX4fiqEBSvORS3ce8TaPioE7Rpjyz\n/xHouVGMYgKXv40t+RQDRuEdT1s4BM1di6yFSpSyV2G5pwJLEFmXHsMryXyrupUePc+3Jvtx+VvI\np3pw+qYRH37hNRSQSPOFyFoIPTdCSnYzIHoZFt20GjG6BAfzzHEec0xnZaGfGfo4X+z+I7alU2Fl\n+bHnLxxPFYuXtGp+7ZnNsOjmP4In0iUHedo1jR97SyleB+QgZ+cPcmahC7ncYrAkJ+b093Nl9fu4\nJXQaP/AuKSdNgqf6RAI1J029x2NaIyCwSY2WLCS1KAlB5bJCFwNbvsVE3+OMiy4EbFZJaVRvM/fG\nh1nm8lPPW9vNPQRBlGlpvYDtaiUCcHFqO89n4/TbAjUdV1Hd8UEAKhrP5brGlWQFiUcNCcURonLa\nRTQvvAVBcqK563nS0USrEWODt52o9/BG3c/GDuKzClzkrz6iM0LSNLh9sp+r7QkE7HJC22uRGFkP\nCPijx73Rp2IKF/kq2ZJP0VXMHdP63vBcqtquJBvfw9CeX1ItKzQpDl7Ixkse0d4mJvoe57T29xx1\nH2+uj65d5OW997F3x495VgpylsvNh5tPpN5dxU2BkwFw2SZfjD1DtZnmQVcHq7U6DgQvp3LaJUiy\nC1EQ+Hywku9NPsmSwiADsp9lxUEedbYQL3c0TxSKxCa285B3Hr9zTudkGUYtk13FDB/u30netvhR\nTQf31M+h8h8QHVTUnYEgSkz0PvaaZa5AB5aZJ5cqmULXKA5OdAf5UKiWWyqbOS3Shjs4k6VWktPs\nBGucTdiAGwNsEynZyS/cc3DYBpOiE7P+TD5W2UKL5uIZRwMOy+ABuYqLE5vIiCq3ZpIc+voS5Ynv\nScHBhdm91Fsp+iUPW9QoW7Qo9VZpuqt21vU8kk1yU+JZfueeyQpForZyMQAHGi+nacFNFDIDqM5K\n3KFZ7O9+nL1KBYsKQ9wuVdJoJLjUX0Vi+AVCdSdPWQa9Hbg6WMOF3gj/Pd7Lk+kJBEHgK9EWrg3V\n8WRmEocgcsdkH7Ios3jWR0iKGkVErkpto3NiF42KY+rWN1WmlAMkmsoJWmvc04iYWf4l8TI/nHwM\nCfhi4ARMBI4vDJAUNXxmnsec07ndtwhbKFlsjSletisRuv0dfCD+Ev2Sj7tdswE4xR1kYGQdXw2s\nJF/uuuulXjIfCdUxqBd4LhtntsNDn1HgulAdBdviG2PdnGzGEAQZp7fpLT3XxwxvqSC9LLubrUoV\n7cYkT2nLMHUHmmeE2cVRHndNRwK8VoGfeEs32+X6IDuVCMvzA4zIXiwEWvRJdqgRqswMG5UqRkUn\nYSvPVemSzdJXAieQR0KAsn3RQXqUIEnJSdDM4TELfD62lg+kttFmTFJvJLgot4/9coCDckmcWmVl\n0dTSb0POeuiV/bQZE+xSImDbuG2dNjNOAQnD38KAXpgqFGY6PBx811rsdUEQBJy+JvLJ7te1zSpP\nBWszcWJHSVU6VmTK/Fx3oJVHUuOogsCZnnc+bQFK58EbnksmtmdqCvcQ5ju8qNhsMAUss8gyV4AP\nB2u5Jz7MOiVCMTeCN7wAPTdGNt75qv2KyFUrAVhc6CdoFwhYpf3P10fYrkZYnOtjQnRwTXoLzymV\nIEi4bIPTcl1lA7PSv2l6HMG2ecbZxIn5Hg7IARbpk/xzdjsmAoarBl3U2KTVckXkYm4PnYxo5kh2\n/Y5zkttwm3kmJCefi7+A5IxS1Xg2qdENmEjsEoMs0keZFB1YNhyUK1iSH+TjqU2ck92LKGv8PngC\ntiAQNPP4KhexNptgwCjw/sDhOp23Gp6KecyQSzSOucURJErOB0ApTdQZITOxnUWBJhY4vPwyNohl\n29i2zejB+7GtArHIcpZm9rBTCfOxWR86bP/dhSxP5TKck++hrumcIx7Dz2MDJC2TUwp9aO7aI1qs\n2bZFcuQlXIG2o9Ia3ghc4CvRax5Kjh7zNoGqZVROu5jU+GYG99zFMoebl3JJTJjq6qbGNh91+ze1\n0N2hRAnpcZ4t6BQEmcsjM1AFke/XtDOqBNjkmoYgKgQVJ1+OPUeVmeYpZzNfkTJ8e/f9bOl7mod2\n/JLbtv6Uu90zeEmr5eOpDZiCzGfnvJ9FDi8eW+cZW+WrgeO53TUDU5D4X0odW7co8W+VzTzevJCz\nvOF/uBUva34C1ccfsavrDrQDApnYnqNuH6g5AcvI8KVII9nQfEQoiZbKy1cIOW4JnoLD1hnY+j+k\nk13cWNFQ6jRKKp1qmM1qFednO/mDq50X1Sp6JB9FUUYAQnYeHzr7tWok2cNJhT5Oy3fhsA0ULcT+\n3jWcNvY0t/mWkBZUbq6ezb7xHaQFjdPrVxAfeo5iboTItIvRc2OsyaWwBQHJGaUfhRvENPG+x5BV\nPxUNR/5BvVUQBIH/qmphpubmhoE9/CI2iATcHGniJ7WlKYwevcCNQ51kHSG80y8nJyg4MDku38uV\nfduneGY2ICNMdXQnRAfYNqJt8UfXdHRRIi2orHE2MSh7+YZ/BfVmks8k1yPZFgI2mmUQNjP8QBim\nwsyyVmugPrGTftnLZ0OnkisrY2/wBviNqbFRqwGBKfrEia4AQUnhwWQpSWxfIUOL6uQMTwW3TvYz\naBQ4wZzE4WuaUtm+0zC7qtS5qTHTDMoeTs128UulgXw6iuYZYVmhn11ymJSgML84wkElRBaZdmOS\nQcnNGflSpPZPPfNYnu+fSiartjM8qTVgAW3GJCuy3SQkBz/3lqbfJgUH+5W/dOaclk5a0vDahfKk\naNmiB3jY2YYpCCQEFRMBh7dkSeNLOYmJGm7bYEd5XwEzh9M2eVmroc0ZpF/PT3lhN6tOeot5pr0r\nRHtdcHqbKeZGMPXMMW9zka8SHZtHk+N/e+W/gmxiH7LqR3JE+GNqnBPdQbxvU6rg3wNPxVxs23hN\neIQmiixQFLYpYfJlWshNkUY+EKjmNuMQn11ElF3Eh58/bNv9hSxfypeG/Hblcly2gQeddDnLc0lx\niDqyPKE1M0OfYFFxmLxtoyNwdqEbYGq2MGpladMneMLRzPvSO5lmJPhJ+1k0ChZubwOzsl1ogsBF\nHZdzVbiFh5Qqrg1fQL/k5f2Z7Xwj/hQ/mHwcLyY1Le8hNrQW08hgYKFLCj6ryH2uWSzWR/DZBc4s\ndNNsxAk3X0rTws/ysFhKtlua78UXWczd8SEqJZXT32brOEEQmN12GROik0ory6pcN79NjFC0rbJX\n/2nk071k451cFayhW8/zbCZGYmQdqfHNRJrOZ9vQ82i2ib/mJBTlcKrNz4a2ImJzdeWRfW7HjSJ3\nxgZ5j6YipHvxHaWbm03sRy9M4I8eOU3tjUJU1ljhCvBQcux1iUxDdacRbjqf1NgWpg38kbRlsjUb\nm+rqxgbXHnXbN7XQTSGhYCFiUyeWTP0BahQH365u40fOmRRtG0ULEZXgB4m13JJcT9DKc5sY5dKs\nzKeVafy3bwk7lQhfij1Ng5mktvUKDpg2lZObuXfsIe6YeAyvlefCzF5udDtpV13MUF082rSQDwVr\n/2Ij9Qagor7U1R3v+eNhr0uKC4e3gWz86IWuJzQLRasg1v8En20+iREtSlJUp7pSzZkuBiQvd/uP\nA8ugf8t3aNrxHb6SfJHPpDbgsYrc757BXjmE1yrwXf8yxkUXLlvHpmSo31t7DictupG7qs5ji1zJ\nyYXS1L5emERMd/NT3xLWOhr4V3+IpGVSmxtA9zYhm0XGe1bjCrThCc1mvPdx1moNVBkpVksVzCmO\ncIKqUEj3UTn9UiT57eclOkWJe+rncJI7yJdGD3LT8D7ylsnpngoeapyPKgg8mBrjjK5N3JyX+d+a\ni+mTfMzVx2hO7sb5ioHP7KmCxSYpOphTGOWEQh/fm1iDYlv8T8Xp3OWZT0rQWKA5OSD5WFno57bJ\nx5hVHKMgyswvjmBNbOWW+HNcm97EATnI54KnkhRL56pKVvnNwMvc65mDs5zodog+8b5gNbZt87vE\nCE2Kgy49z79UNPBiNsGtE31c7vYjZwdx+VvfwjP8+tAenMag6EZHZHFxmDZ9gpjkJJmfhqxmWchB\nEEX2yyFOypceyNvKKWgLiyPUGkncVpG1jkbmFkcYkLyMii7mF0fYoVXRJQVwYHJysY/W4gSPulr5\nuXsen6k4k27ZT9RI4THzXJbdhWYbfMu3nLNypeLZUR7WDMseOvRxnLZBUlARPZNMGAFEw4FYvulu\nUytLXo5mBrB5zlFPq+ZkxChiCyJ+ARKmgYH9bkf3dcLhawJ4XfSFGZqbdtXFg6+jA/RqTPFz/a1s\nzKcYMYqc631rVfj/KFz+6Yiyi9QR3BdWeCrpUoIMxEupb4og8p/R6XysdhGTooMnhzbwTORkXor3\nEcvH2JpLcd3ALlZ1b2IDTizZTRADse0DALixpjq1InBpbjdxQeUT6Q04sFDL1AOB0j0sjcyY6OK8\n3D5GZA+dSgU3pDbw+YNPYRRi5FM9KFqIpoU3Y3oacQmlKOB+ycX/C53GV3wrSQoaLttAsA36tv+Q\niZ7VpUAorZl5+ih3ueewtDiAUY4Q/y//Sh4LLCFcfwqCIDEhldLQriv0MqqFeSYT44pAFOUNfP7/\nvXD6mglpJW7pB5MbEYtx/lz2k/VFlyIp3hJl0ROkUlK5a6Kbkf2/xeVv4w+JUZYVBnjWNZ3TG085\nbL+JYpoH83lONidoqVlxxPf+8uhBirbFNZSi449KWxhehyg58IbnvVEf+6i4yBehV8+zMZd8XduF\nG1bRvPgWlpZryUc6H6B709cx9cxfjRd/U6+AM8PNPOVqZUWhn/PjL5N4xWjyFE+ISypn8GPPPPKp\nLgqR41AkmZW5Lr4ce5avTz7JJZndfDi5mUvTO/ja5JMs1EfQ3DV4QrPp3nUHH09toFOt5ObAyVyb\n2szNXg9XVs9jfzHLKW/SlJSs+gjWnEBy9GWK2ZHDlrkDHeSSPZjGkbkngiBS0XgW+VQPucltzG1a\nRYWVZ0h0kxcUXLbO5dldPKLW8VjdJXzXt5QRTzOzjBiLMge4jAQ5UeEjdUu4OfkSuiDxmGsazjJX\nVwbmSDYfH9rH8/k0oZrjp7rFOUHj+tCZPOJoYpmV5J+rZnL38E6qrAzTw7OZ6HsM08hSOe0S9EKM\nnvFtbFcjRCSJGCLX6v3Eh9biDnbgDR/Zf+/tgFeS+XHtDD5R0cADyVEu7tnKL2KDuESJL1SWUusu\n90WRBYEnTJHPhE5ntxLm08n1fHdsNRfmDhLBon/KIUQgbGb4aGYzNydeJC9IeGydHzQuZk3ARasZ\n5078bHQ2sr3hch5ytbFDi+KxCqzV6jkgB+kwJumS/XwueCoZUZ0SuGVNk9+LQRrLccAAqiAQFGVO\ncgfZmEvSo+cZNgosd/k5zunj00N7ma46udFReuwcEtK8EyEKAgNqCAOBxcUhemU/tWaGp4XSzTns\n7sdhFnnG0UCLEUOwbTar1QhAxMqxRw6ztJwg9yvPHMJWlm1qJfOKI0iWRZWZIi0orCgOUm+UojV/\n7yl17785+SSXZPdyVu4gq/Ld1BpJYqKDgF3ABnpFL2lB4brky8iUOIUAoivOYKGkXq6wsoyLzinv\n7jZjHENUeVmtJigqU4OSFsXBgTK/bJr2bqH7euD0lniWuddJX7jYX8nm18HrezVKXeQUrkAbDyRH\ncQgip72DQyKOBEGQ8IRmk57cgf2qdKmVZa7xi+nDZxr/KViNN9BBe2GIb5gFm66jAAAgAElEQVRe\nbgydxuKenVzSu5X12QQfr6jnqenH4Q+2k413Mj2ygKwg0+VrJx49kT4tyoTkRkBAwsZE4KDkZwKB\nPWKATWqU59U6NAEiVpYDUgC3VeQRVysdxiTXjTwMwGOOZi7wrOCUgW7m71/Htyd6sICwkQbbZpca\nKc2ohOYglwtCgBfUGs4tHGS1YzqDzmqOKw6SEDQ65RAbtWo+2FTi8N7V/TwmAm67SLRmKb+KDyEC\nV/iPHIH7dqC57b0AKJj8v/jz3DNRGuyLokKk+QJyyQOk+p/kff5K1uazHFAq6A3OY3p8K/2Sl/fN\nvuo1+/xlz7NkBYWPVM06om/un9OTPJIa54ZQPUpsB5qnHtX52gGeaeRJjW/BG1n4lswYrvKG8YoS\nd8WOPUDmEDRXFbNnf5QOWWa7sx7FEUJxhFFecd28Gm9qoZseeYlO7wwygsppxUGG991HbOCZqeWf\nDjewato5bNVqMAefZnXdJWyZ9kGeds3Bb+W5Jr2Vi3N7OaEwSKtZqtZTNux+6T+Zlu3mZ5753Bo+\nnU9nd7BKyFM57WKey8YxgZM9b16kY6juDARRYfxVXF13sAOwXsODeiX80eNQXVWMdT2MP7IA1VVF\nSJJx2jpFJE7J95SUlYl96P52rtZmcWDmJ/lc3Qd4Qq0lLMncNbyDhYUBrkxvp8lIIAKyWvq8Y31r\neCkzwTeqWmmPbwFKI24dC0tQCFp5vhVt4eVcEitVGv27nBEmB57BX7UMh6eO4c57eF6rwxJE9gpO\nTsr1MC3Xh6z6qG7/4FtqJ3YsEAWBfw03cEftTCxsvjR6kBMOvsw98SFkBH6THGFXoRTr+sloO7uU\nCiwgYmX4WPIlfjj6AP818iB3jT3E2dl9jEtu1jiaudM9hy8HTwbgpaH1NFct4n+UHKfnDnK3eyZD\nYxu5392ByypydXILHlvnPwIncY9zJjdWnElekMsuAKXzlbRNFhWGkC0Di9KPz7RtLvJXoggiv0uO\nIiOg2zZfiEzjU8OdZCyTH9R0YCYPvrP5uWUoziqcmKQFhRozxZnZTv7HnItpqGjuUZYWB3nW0UBe\nkImYGXYpJYFeFpk6M8XyfD8IAtu0KirMHJvUKry2TlGUOSCHGCt7Un4m9RI/GX+E5uIEQSNLtZHi\nrNwBPpjZxjNaA4Oihw69lHpVQCQrKhQFCREBC0gIKkE7g0ebIJWrLHn56gkSQtkg3baZVxil0z8X\nWXZQPGQ9Z9ssdIemCq5m5d1C9/VAlDQ0dw351NE9L4+EC8ouKX9vV/fQPTnnbebB5CgX+Spxv8V2\nU28EfJGFWEaWdGznYa/PcXhxYbFBt7BeYesJ0BCZg8/K80S0hq8U9/Hh/D7+PdLM2ulL+FS4kQpZ\nwR1oxygmsArjjGhRHLkRlrdfzplLv8DKld+gY+V3cNjwA+8SppkJnna10WbF8VpF8qKMYhvoCKzK\ndzGzOMY6rZZh0Y0CWILEvIoZXOl0YJR/R4utFP8++RTzi6N8M/YkH01tpt5MkZ3cTo+tklICJASV\nlcVBntdq2RY+gVXpnRSRCNh5tqpRlhaGafSWdCI/SydAEJifH8KqWMB98WHO90XeMaE6AE7/NCTV\nR1ZQ6DAmmTn+An3FknjWH12GL7KI8e5HOLHrbgJmjjs9c7F7H8Vl6yQrVxB0HF7TJGN7+XVRYDYF\njqtoe837pS2DL4zsp1V18WG3k3yq56i0hdT4ZmyrSKDqzaUtHIJblHh/oJrH0xN0/52D15XeKDtF\nN+EZH6Fh7j/TMO9TR133TS10bQRWxNbxff9ynGYOSQsycuC3jBy4H6NYim29wF/J6XM+CqJMfd/D\n3Bofpb7YS4OZ4oBazVhkGc3GZJlnBz3FHH9Wa7kxdAazG8/k9sx6FuYOUtNxNaKk8nR6koAoM/9N\n9BmVVS/BmhNJjm6g8ApPSKevGUFU/ypPVxAkIk3nU8yNkBzdQLjxXDQ9ge6uR8IiZOU5IdfLC2o1\nN/b9itvHH2F0z11cntjAzSN/4OLYS+wS3WxSq/inaWdxWbaTdVot34isIo+Eahv83OziLCtGLnkQ\nG/i+dzGfC55GTFT5fHoTVYHp/HCilyX6OKLsZnJwbem4Gs8jPbmbbHwvzzoacdoGom1xdWY72DZ1\ns65DVt9Z/q2vxKmeEI83L2JN80JuDjcRkBTatRIl4WPBWv48bRHXhGrxh+Zwp2ceTttgnxplnVbL\niORmrxKm2kxRZyR52N3O844G9soBRiU32cldpXMz8gL/4dL4f+Ywv3F1INk2km1yh28RE5KLhOTg\nXt9cdFt4jSPFJ/Vurkpv54BW6r6c5anABC7xVZK1TB5OjmFgc02olkdS46zLJvhidDptmptsYt87\nmp97CM3hUjTjNiXCTGOC2YVRsoJCNluL5hnh9FwXBVFhUPQwtzjKoOzFAgqCRMjO02pMItoWimWw\nVw2zRSt1ZGbq4zzhbKLZSvKgowUDgRozzXdjT/K1xNN4MJCx2axW8UPfYmTb4KpMSQTzTd9ymowE\ngmXRYsYQgTHRieqKIQo2ZjbAqOTCT5EhqRQR6rR1Wsw4D7vamKG56TPKAiBBYKbDw/5ilqis/p/i\neL5T4PQ1kUv2TKVBHguissZKV4AHk6NYf0d4RDa+D1kNcF+uiG7bXBN6+4S0/wjcoRlIipfE8PrD\nXpcFgcWqxkY1OiW6O4RDgT7e1AHOjc7h0sRGLiWBR5RfsU6pUMrG92J4GqjSY6T17NTyzOQOFHSe\n02p5Xqvjguw+7nDPw0AsWQMCCjYNZpKPpjYB8CPvolK4i21SPbCai7p/ya3Dv+b+kd/yubHHWKiP\n8anUS8zSxzlFH8L0t7K6/nIe9C/Aq8fx2kU2K1GitRfSYU6yNN/HbiWMBGxVo6zy/KUzOSJ7wLb5\nbLGb+wo6Wdvi2ndARPqr4YssImgXWKvVcXF2L/dsu509XX8klzyIKLsAGy0/wuXWJJ+OPY1imwxW\nn8klrecftp9sfD/37F/NkOzlmsoju/B8e6yHEaPI16payI+Xml5Hm41NDK9DdUZxeJvf0M/713BV\nsAZZEPh57NjTEl+Jle4ARdtmXTbxN9d9UwvdPRVLmF8c4QMeN792z8QsxHD6W4gNPM2B9f/OUOe9\nZBMHcBQmiEaPY4Y+we2TjzFXjxFpuYJzln6OFnRkwBZVinNvYrTjWr7vP45VkZmc3Pc7CvFOqlvf\nh8Nbj2XbPJOJcYI7+KZb/lTUn44oOxg9+Pup1wRRxhVo/auFLpREBQ5vI+Pdj+IOzkDz1OE00kiC\ngimIXJTdy7jo4rbwaSQc1czQx1mU2kVOLBU5ETPDnaETcI6+gIbFE8GlPGXAxyvOokv2E5zYwFDn\n3RSQ+KpvBU+4WkjJLv4t/hyt+QG27fgJ69KTLDHGkWQn2dhOwo3nEh9+gf4dtzIhOtiphMkJMlel\ntlJpZqideQ2a++1Vrx4rpqkurq2o4576OdzfOI8GxcFz2TiRcpH43oZlbFMiPKU10loc4WHvHL4f\nPoOvBVbyc+9C+uWSqGFI9hKxsjypNdKaH6B35x0YzhruVev5gRBiTHJxSW4/s/QJbAFUy8B/qEt0\n6Por/18nijgyA9wYOh0AvyCxv5hjhuZmpsPDA4lR8rZFUJTIWCa3TvZxma+SS/1RTCNHPtX7jubn\nHsLcyHzSgkJWUIgLGl50glaRHfZyFEeK2XaJM75TjTDTGKcgKmxVKgnYBYoIhKw8p+S7EbE5LXuQ\nhOgoqbeLQ/TLfqCUsPMt31IsICsobFSr+K5vKe+vuIB/D5yEx8zz9fgzzNbH6Jb9vOyoJSVqmAh4\nbZ24oJW67e7SLJE74yZTdsDYXvZBDlh5vIqXDSbM1Nx0F7JTFJR2zc3eQoa2d4Vofxcc3mYsM0cx\n9/q6sxf7K+nXC2x4nbw+27bIJvYhBtq5JzHEaZ7Q/1kRoSBI+CqXkJ7cgamnD1t2qr+GYdnDrtjh\nha6iBXB4GkhNbMUTnoekeIgPPXf4Oo4wshYiE+ukwj8dCZs9E395jsWHnkPWQrSYSX7oW0JSVLk4\nt4+fu+bw3sjFfMO3DJtSM0p31dCkutmuRckIMhbQVw7Gcds6jnLSoIKF5K6lfu4naV/5bZbOvYFP\nNi7nyomnsYH9UhBLClDt9aPFdmAhoNoGOiJJUeWyxhJt4ccH12Ii4LGL+GqP5xexIU73hGjT3G/0\n6f+H4Y+W0sZW2HnWavVclO0kNvAkP937IOvGdvKkq42ntHpOi63DQOTzodNY0njqYfvIJvaza+cd\n/NQzj3mai/MCta95nw3ZBHfHh7gqUM0Cp4/k2CYc3kZU52vt9Iq5MXLJA/ijS9/S2dpKWeUiXyW/\nS4wybhT/9gavwjKnH6cg8tQxWA++qYXujwgz4Khh2tCfyYUWsEOpJJfqoW72dfirlpIceYnerd+j\nb/sPiQ8dUszZIAfxh+cTH36R1NhGEEQa53ycZm8NP50cpE1xcE7//eRSPdTM+DD+crt9RyHNuKlz\nsvvNoy0cgqR4CDecTSa2m/TkX6aR3MEO9PwYxfzEUbcVBIFI84UYxTjx4eeJNJ2PUYjhr1yIZFt0\nGP+fvfOOk6su9//7e8rMmV52ZnvfTTa9k5AQWugYmgiKKCAICiKCAuq1CyjXFixXvBf9oVKu9Qoq\nIF0QQgIJ6cmmbJLtfaf3U35/zGZDSCEBAgny/id5nTnnzJnZOd/zfJ/v5/k8w8zPdfGYHOIrnmO4\nr/4Kbq6+jC8GFhGX7JyW2YE9FyE58DK/d4xnhWXnfE+YvOrl+pKzOLf0Ys7znsJHw+ez1FHLeZ4S\n/if+AsdaKUBCi27kF5GnsBfiFLJDuEumEx94haH2RwCLf3qLs77xhWEWZ7YSbjwfd3DSYf5GDw+q\nkLihpJaNuRRPJot/kzLFTpWssMQ3j2FJ49zEOoaMAvVGCp+kjHVNAxiUXdzvmcYnQufwLd+xfNw9\nj7tzJpMLgywZeZKPJtfwtdgLPKYM4VMdlCg2pqCPBUVQLNjoMgzu9B9HZrRjzUJXgC35NJ8IVGJY\nFj8Y2lm8NtXOA9E+PhGo5I7yYmCbiW/nSNfn7sKhqOxQg0zUR/ins5EqI8nliVXcUyj6MvrcPXiM\nLI87GqktFAPNZ7R6BDCEg6xQuCy5joKQ0awCU3IDrLRVMKEwTLfsZp0SZLw+gt/MkkLFa+WYme/n\n2Fw3C/LdfDS1nl+M/IN6I4YAIsKOAH7om0d8tG/7dsVP0MqRcaWIGF5KshbqaHZx+WiL7TIjhVV5\nMmnLZJLmZkMmAkIgAzWqxrZ8hpYj8EF6NODYVZAWPzT5wmnuEpxC4i+HKF/IJjsxCkmedo4jYuhc\nHdg7MDia8JXNA8sgPrByj+2njBbX/TO1d1GOJzSDbKIdI5/AX3E8yeG1pGPbxl4XQuDyt5CObWF8\nsJjdHRgtbMun+0lHt+CvWMAP6xcQFzZu8y7EaRW4KbWC49M7eF6rY5WtDBBUJNvoy0YpCJnfuqbS\nqpRQYSR5wDmJZ+117HQ3UTn1c4yb/z3Gzf4yLn/zmL70D8vvxG/m6JHcYJksnnwxX+hay6nZnUQl\nO16rwCY1xHwrhaIUx+n70wkQgpmZHh6z1xIzda4NHlzX03cau6sKSdaQ88NcPOsGvhw8jW7ZzenZ\nHUzQRzglvYX5uW7alADtaim9ipdv9Rf/ToVclGjvUjrX/ZzfemcRl2zcXj4e6XXBaVsuzbU9m6hR\nNT4friOf7ieX7HxD71zvYfTO3R9XB6vIWyb3RQ++W+Iu7JLEcS4/zyRH3tC94bAGuinLpHz8RwG4\ncuAxHvTMIIVC7+b78YRm0TTv21RNuoba6TfSMOerjJv/PSonXgn6MDtW3En/1t8BUDnxSpy+Rr7R\nu5lhI8fnRp6FTB/Vkz+FN7w7Ff9EYhgZOOEdCHQBApUnoDrCDGz/y1hxgMtfbAKQfoOsrss/Hldg\nIsMd/0B1lOLwNpCKtOIKFvtP35hcjbAsTtUcrMkm2DbaAvP37sn8zjWJTydWMig5sFefymMNs/hh\nZQuPNMzhY8YgH0pt4sxMGydn2/mv0jq+mN2Elh2gatKVPFB3KX2Siyp99ywoObwGPRdBUlyo9iB/\nVostCz8Xe5nSmtMoGe2ec7RyjjdMo83BD4fax7SWi8pmUG4kud23kOOzHQSMDEE9zsmJdURNHRuA\nZaGaOvMznUzP99Mle2gpDLFk5Eluy25iouYHIeEKTKSu6YMsqWxhRz7DeksqNp6wjGLnLiExO9e7\nR/Dbls9Qptg4xxvmcz2txE0Dh5DYlsvwnbJmvlraiDI6gKWjm48Kfe4uCloZVUaCrbKXEUljTq6H\nVflGTEPB7h7grMw2ehUPZUYSzSzQKbuxAE2YtCk+QmaGc9JbecLRRJM+wlKtGhmLeflevhZcxHJb\nJU85Grms9Hy+5j+RF+01NBVGuC6xkktTG2hXfGNFmH93juP4bDsb1DAeq0BKKJQVEsVA1hmjPV+H\nhCA82r1oUCkGr/V6lFZvsQPdJLuLHaNaulrFRm8hR84yx2Qx73No2BylSIrjkANdpyRzpifEo4kh\nkqb+xgeMkhrZgIHEgwWJGZqH2Q7voV7yEYXmrsLuqibWv2yP7ZWqRpMwWSZ5KGT3zHJ5wkUrvsTQ\nGkpqTkOxB+jf9ges17RNdQbGY+oZXHqCfsWLlSxKEqJ9L4KQ8JfNp4osNstgq62E77uPwW9mOS/b\nxsLkdv7P0YIF2DH59dDfmJwf5BWtCqeRYafi56J0K3HJzhkzbsAbGIes7r5/hjMJfr78+8wo9DMs\nNHTTZIavivO7NnJmZisyJi7FSY0RZ5WtjMtrd3f/2iVbuEXN8+v4EPOdPma8iaZQ7wRCiFGZiIUU\n3cLHao7li4FT+GPgOJ52T2ZL5dmMm/8dFk/4MAttcEliNU+mIvz36ntoW/5V+rY+yFZnA4/Yqrgi\nUMkkbU87sZ5Clsu61iMhuLd6Mm5JIdr3EiDhC8/Z63osyyTWvxxXYOIBi7kOF402J6e4g9wf6SVt\n7r+F7/44xRWkR8+xOZc+4H6HNdCd5/Qx2V9PzbTrQc/wjcRy7vDOIyXZR7O4S3GXTMHpa8buLEdW\nnUWxtGM2hh6jaG4iiHQ9zX0bHuTvqSiXJNczUZGpmfrZPbKMlmXxWGKIY51+gso709JRSAqlDReQ\nT/cR7SsuBdmc5Sg23xvKFwDKmi8GoGfjLwnWnIGej2JzBJFkB24jxRmZNkSmj6VNc3m8fha/pJc7\nI//kgtQWmvUIv/TM5HeJEX44uJNzd65i0Y6VBJI7uCy1jk8mV3N9YgX1677PSNczuINT+GdBkB5e\nj8O+a6AXY/8aehZTT/Go8BKT7HwovYmJ7lJC9efs89qPJhQh+I9wA235DPeMFPVAZ/nK8Jk5tthC\nrNFqWZzZxqv2Ck7N7OCi5AYa8kMgBAUhM1cf5Kb4y/xq+BFuKnSyeO5XqJt+I0Y+gmoPUjnhCoSQ\nmO/0M10YgEBYFuNtbgRwj9VJ0MqCAPto8NqaT5EzTU7ZvpLHRjPNQVnltzVT+LB/z0rh5MhGHL7m\nI16fu4vSYHGy5zbz/J9zAgErx/xsL8OZOuzufublejCFRLfiZbw+Qkx2MiwcBKws4wsjbFBLuDy5\nlpbCMA+7JtAleRiUHByX7UBH4o/uyRSEgo7EOlspf3c08T/umVwV/ACfC5xKgx7BolhwttJeyUdT\nG7gh/jJhM8OPvfO4reREvhpcSLWtm2imaJzuxKBD9oxJTSbnh1mdS6IJiQabg6gFwrKY6vCxOV8c\nVN/P6L45hJBweBrIHoLF2C4+7q8gaRr8fLjroI9JjmzgVf90OvQ8nwxWHXHFtG8GX/k8ssnOPWpE\nAE52B9ighukb2bjHdpujFLurisTQaiTZRlnTheRSPUR6nh/bxzWq5U1HtxBzVBHK9qHrOaJ9y/CU\nTEO2eRlo+xN1hSgIQVJ28CPPPEqNFJfktpBHYo1alP640DkvvZl+2U23PQyGTq/s5qzMNu555Qfc\nuepXpFJFL+Uvr7mfJ1YtYVGuHR1BqxygjjT3WT5MPcMH0tuQgM2uon40J2w0+4oZ25+1PYeJwG3m\nWFlyDP16/ojN5u7CX1Hs/BbtX8oF3lJmOrz8zdHIZdOv5tzms3GpLlyBFupm3Mxn6hYy2UjwfW0C\nT1ZfSNWMW7g7cBzlio3PhWr3OO+Qnueyzg2kTINfV0+m3ubAMg1i/ctxl0xBsfv2upZ0dHNxNXlU\nUvFucE2wmqipjzXROBROGnVOeTo1csD9Dmugu6ulqcNTR82063FYeW5JruRL7jlkAlMZav87HWvu\nYnDH34j1Lyc5soEdK+9EZF4GwBWYTLD6ZIaws0QqZwIFbmk5j7oZn8fpa9zjvbbk0+wsZDnT8852\nunGXTMXpG8/QzkcxCuniElBgAqno5j1my/vC5ghTOeET5FI9xAdexls2n0j3cwSqi5qcaxOvsqJg\nMZgZoc7KUTHwAgu8lVyZ3cwGWxkrtToSpsHLmTglio1P203OyG4fNfAu/mnF6DJ8cmQ9jRuXcHVy\nFWEhjfrlzaDxmG+O9lE3GPJP4efeuYSMFJemNlI+7iPviYcCFO3szvaE+NlwBzvzGUoUlaC3gZCR\n5g/OcZxPEpul82f3FK5IreM7kWfxmDkQAsssEFWKGYJvOaaQiLaxc9X3MPQMVZOuRlaLAU93Ictq\ns/i9y5ZBWyHLaU4vK2KdPOloZKbmwbQsalU7NiGoUGz0jBY5fSpQzXONc5jn3HMwymcGyaf7cJdM\neQe/rbfGjIo5pIRKvRFn2BaiW3bzmfjLPG7MxeaIUmsNIiyLhxwtjCsMMyQ7eVbb/XB6wt6ABVyd\nXM2MTBcZSWWpvZqZ+X7slsG3h5/mJ8P/wGHpnJPaykRRYJmjhn7FzcJsJyrFKdxfXBMQQLmR5ORs\n8SFaWkhQQELVYqjCwEz7SI7qczeqxaVf1TKYJXKsyiaYprkZKOSwhMASggl2F625FDLQfJTqPI8E\nHN56cqleDD17SMdNc3j4oLeU/zfSfVBWY3o+QTrRwR+1ZmpV7ajphPZGeMNzQEijy867OcVXgyEk\nno/uPRHwhGaQiW9Hz8Vwl0zHFZjA0M5H0PNFzbNi82J3VZEcXo/mrcdnZmnvfg5TT+OvWEh84BUy\n8R181m6CZdGu+timlbPEewwBM8MdsedpV7xYUlEitEAfplpW+VvpKUx2BUhbNl6yVzE318P5iVU8\nuuq73PHKT/lI7BUm6cVmIFu0Gk73+EnLDu5Tq7g5tgwFE1/ZfDLpPmLCxoerdmcm/zeTBiGYle/n\nV5kcU0dbph/JuAItIGQysTYkIfhGWRMjRoHvDu7YYwleCEEwPIPfTzid0z0h7iqofGxkhNZ8mq+X\nNo4VE5qWxSPxQT7csZZePccvqyYzcTTTW9RyJ/CXz9/ntUR7lyIpTtyhaYf/g++H2Q4vcx1e/mu4\n45C1uqWKjWmam6eTw/zn4M797ndYA91pr3E+cHjqqJ36WYIY/HD4cVanhkmVzkcvJBjufILezffR\ntf5ucqkuLMlL45yvUzP1WuJVZ3KTZx55WeOu+nm43fuulv1HYggB7/hAJoSgtOmDGHqawZ1Fz0BX\ncDKmnj4or0h3cBLhhnNJDL6KTQtic5YT7Xked8lMFEzujD7Lvd0rGOl6GiyTVGQTiqzS2HIpBuAQ\nEgXL5Iu+IKf3PIIQMrLNN5Yttsw8hGZzX/B47nPPwDb9VqomXYlpZHH6W8jEt5OKbCLvruMb7jlY\nWHxv5BnKq0/ZZ5vAo5mvljZgExJf72/DsiwW+8spN5JsVEsYCc3hDGOEF+xVPOicxJ2BE5hD8SH8\nC89sbhntvz4x28132v+FJDuom/EFNPduvd8ndqwoShaAJs2DjkVw6BV+5pmN3TJY5ApSALoKOYKS\nyqZ8GpckEZRVbgjV7HNSsUv/7Q5OPuzfz9tFSHWyTQ0yJT9AhZXhbs9svFYePV6UFAXdPTQVRuhS\nvUwsDGMKiTX2olxGxeLUbDv3eGbQqEe4PL2BhvwIS7UabJjMyfXwgqOOeiNOuZHkYdd4nlDCKJaB\nx8ozO9c32jxF8JjWRF0+ggyjHqASV6bX8oPI03zaeBoAT8JJAQkLeE6rA4od0YLuCjZmU8x0eFka\n2x00THO42ZxL0WBzYJfefSP6oxXNUw9YY528DoVbw/XYJYnbBra/oTYvFdnEn5wT2GDJXF9Sc9iL\nlN8pFJsHd3AysYGX90iozHL68GDwr4Kxl6uFJzQDsEgMr0EIQVnTRZhmgYHtD71mn+lk4tupGR3X\nkn0voGph7K5KBnc8jOap4+zx56NgkhEqd5XUslSr5T/d81hur+SDma10CxUDQdbIc7WSZ10uzZq6\ni5gspTldsfizdx5/dLRQInQuzGxmmxpAxgJHBR+YchmpyCb+T2vi3MxWxukjODwN9AVmMqEwxCY1\nxLyyqWPXO6AUm0SMc5TTpee4NVR/xCdnhJDQXNWYRpZCZpipmpsrA1X8PtbPjb2byb5uCd8hyfyo\nYjzjbU7W51L4JYWlqSj3RXr4Q7SPs3eu4obezShC8MvqScxx7pbmRHtfRLH5ce2jxkbPx0kMr8FX\nNg9JemdWwffHt8qaSJoG3xrYfsjHLnIFWZNN8mhi/50T39GRWvPU0jjrS3irTmaqPoxr4CXy2Qiw\na7ASBKpOhuCl2JylLE/HuKhjDTnL5MHaqYw7gCbuscQwxzi8hJR3fnlXc1cTqDqJaO+/ijrbwARA\nIjWy4Q2PBQhWn4onPIuh9kdxeBsx9AymnkLzNBI2M0wcXEpfz4vFYhjFSe30zzMz0MiSyhYylknG\nNLiyaz1DpgmWQVnjBdi0EkAUu9sMrcReSHDehIto9NWO6YdTkU30bv4tqqeWH5ScRmchw9cjz+OT\nZUpqzzhs39e7RZli55ZQPS+mozwcH+R0d4gdagleM8eSRJxP159EQfQerXkAACAASURBVMggBOPz\nAzwr+ZgkQV5SkC2LnbKPk7I7+ZNrEn+p++geQe5PBztoMy2wLE5xuBgxdOqEyUNaYzHwEjI/He5E\npuhrnLVMPhWsImWaXBGoRNuPp2dqZD02R9k+Tb6PZNL2MDVGgmwhRbfiY6NSwsLhBKYpo7n7mFQY\nokf2oBvFh7FsmXRLLiQspuiDvGiv5neuSYzXI3wr9jxRYScq7MzPd/OUo5EsMqdmd2AJiUojwddy\nz1KuJ2g0i0Voz2u15CSFT6aKtjo5ZIZkBztlLwEzS8GVIGa6Kc1auKwCSaHSrvrBsigxM0QclehY\nzNQ8vJgoFj8JYIrdzZZc+ois6D6a2KU3zxyiny5AWLFxQ0ktz6UiPPMGS5ZLR9q4zz2VxZ4QH/SW\nvplLPWLxlc3DyMdJjexuCawIwQJV5RW1lPTrEi12VwU2ZzmJweI9YXOWUVJ9CvGBlxnpegbLsnCH\npgMWpXqMHDL23Aie8Cw61v4Eo5CirOkihJCo1Yu+td/uW8cdvgA7tBL+7JzAz9yzsFsGMhYODMZ1\n/oXro8vp2fYnXpADbMgluTS+lIsymxmRNJ5wjGOKHsXlqqR5xud4uPWP6AjWqWGuSK5BsfmpnX4j\n93cvJ2hmUV9jf/WjrU+Nyhby/K9wcLq7hAWud15n+mbwlh0DwEj3swB8OVzPLaE6HkkMcUnnOgZe\nk9mMGTpXdW9kSz7NIleAGtXOQ4lBvjmwnS/3b8PC4q6KFh6tn8V85+7PX8hGSEU24Ss/FiH2fr7E\n+paBZeKvOO4wf9o3ZrzdxQ0ltTyaGOIFcod0bOWoV/KUA4zJ73hKQtWC1DR9kMZ53+b+4In8XWvg\nqdCJDLVcQ9OCHxBovIBNwuCnQx1c3rmeUsXGn+um75Edfj1tuTRb82nO9OxtnfFOEa4/B5ujjN4t\nDwACh69xDzeGAyGEoGL8pXjDs4j1vYiQZNKxLah2H6ZkZ6I+jEoB1R6gdsZNYxYhZ3pC3FnWwKfi\nK4kKlW/6jiNTdhzbDYv2Db8gYi/hNt9x6EhcnFhN6ZZf0r3xl8VGF0IiObyWQM1Z3Fv2AV7MJrk2\ntoKQmWH8jC8cNXrQQ+Wj/nJmaB7uGNxOwTKZ5w4xTo+xUS3hmc5/cpIrwN890xFIOM0CvnQHbjNH\nn+Lhb85xNOkRAkaGuyO9XNe9iW/3t7Fo+wp+PLzLS9JkjjvMoFGg3RSUmll0IbPIHSCPhQm02Jz8\nq+kYOvJZnELiUv++u/eYRo50dNtRJVvYRcDXDEBByCw2I/zQNx/ZEkRTVWieXlryQ5hCYqstRNhI\nYQqJZxzFh5gFLM5s44/OiTxnryVo5fhy7EWWacVlTwmLvznHcWa6DcXUyUrQlfNxc/SlsSnzP+21\nlBkpphUGMSm2AA4YWXoULwaCEkcfHblaJAQ2THokF3lJASFoLERYqxUnMTMdHjYV8mBZNKoOhICO\nQpYJ7we6bwlZdWJzlpOObnvjnffBZYEKmm0Obh/YQc7ctx/vsJ7lG1aISmFwe1nzEZ/pO1TcwSko\nNj/DXU/tsf00fzVRWWPlyN6NizyhGaRjW9HzCQBKas/EHZrOwPb/o3fL/ahaGFULkx5ZT062F7Xu\nfS+h56LUTL1+zDHjuxVTwbLYrvhpUBTikoaF4FlHAzYzyx+cE1mnhvBZeRbl2plSGKBST5ARKg86\nJ/G4Wsex3mrOyG7H5qqgavJnuGz7SzSmtvOKrYLbos8hCZnaGTexOdqObBUAOOk1Vlu/KxggBB4r\nj47Fl8PvnAfsW8VXPh8QxIeKnsNCCD5dUsPPKyeyNZfmjB0rWbR9Bce3vcIJ21/h1UycH5SP557q\nyTxUP5PVzceytOkYHqqbwaP1szjHG95rtWJXsaJvH7IFyzKJ9i3FMVofdSRwdbCaKXY3d4sUI3rh\noI5JmcVYUQJ88v6z0u/a2ltQdfKFiedD/Xn81lbL5dE4C3euZsbWZdwixblruINjnT7+UDudalU7\n4Ln+MVrMc8a7qL+SZBsVLR9Hz0UZaPsz7uAUcqnuvapf93+8ncqJn6Bu5i043EWReWJoFZKZGy3J\nAyFpezQhyGcGObbzYc7KbOWL0aW0KQGuMsLoWx9ku+zlOu/x1JXNoWH215BkB9n4DpKRVoxCAllx\n45t8HV+Wq3gw1s+FqU006BFWhxfidLw3dGz7QhKC75Q3kzFNPt29idPdJaxUw0zND3K35efjdpW0\nZbGqZC5pobBMq+WGknoA/uFs5pfumUzVi/Y9jyeH+U20l/ZCdizAGm9z8oOhDgBOyHWREhKfCzdQ\nrmhIgIzgJ5UTWJ6O8VhymGuC1fj3c4OmIq1Ylo7rKJIt7GJa+WzSQqFBjzKbDAOykzW2MqR4CNUR\nY4G1FdUySMp2yvUkXYqPl22VRYN5YHF6G3kk7vLNJS5s1BpxTAucls6CbCdPOxqwYXBeZgv9wkeX\n6qfKSiGAbYqfdsXPNyPFLowpVBJCxYlOrR5ngy1Ik9pOLLNbmrPatvv/C3NdLLU0alWNkGKjh2I2\nZJrDw9bcrkK09/W5bxVXYCKZ2DZM49AyOFC0DfxaaSMdhSyf6t5Id2FPra9hWdzctY6YZOP7Xs97\nsrGHkBSCNaeQiW0jHWsb236SrwLJsnh2PzZjYJEcXgsUn1tVE68iVPcB4v3L6Vz7Y2yOMKlIKx4j\njQWkLUHt9Btx+pvHzjOnpAHN0ikImQf6NiIsiwszbZyUbceHRa/s4qyZt+LwNmDHJGRm6Fd9HFd/\nGtd6fZxp9JIcXo1lGbya11mw42V8mR7cVoFj9WFsmJQ1fQibVsLdXcuYnh+gR/FS5S7ep4lEgmHJ\nibCsYtOEQBW1tgPHCUcSsmzH7q7CyMfJpXcXYZ3uKeEPtdNY5A4yXfMw3+njHE+YB2qmcoFv94qE\nEIIyxc5Uzb1POc6uQNbpbxld3d2TdGQzhewQgYqFe732bqEIwfcqxpHC4hsDbW8oSwL4zsAOuvQc\nJ7uCrDqAv/a7KjILyCq3hOt5oekYflo5gblOH5f6y/kP083yprn8umYKvoMYoB5PDDFT81D+Lrf7\nc3jrKak5jVj/MqTR5g4Hm9UdO4enjpppN1Az7Qb85cUlBQOICI18upu2ZV+hZ/MDdKz9Gdtf+Tap\nSHHZ6oxgAzeIGDFZ48bQWeRaPsmylpP5bvk43K4wjXO+SqDyRBi15em0h7i4v4MX0nGui6/grHw3\nX/efyEerjnn7vpAjlBa7ix9WjGdVNsGzqRHskswEZwhdSNzbt5brQzVsyKUIKzYk4LeJYabYXdix\n+LtzHM/bK8CyEFAMgXa1+RWCDYUcBiYfSm7EL6DUWcrH/eX8OdaPSdE3sEK187X+NsaNNrbYH8mR\n9UiyA6e36Z35Yt5GGhx+NqslTM0PsrWQZV6uh//yzKE3WSwi9Xu6cZl5VtnLCRkpBmQXATPDNsVP\nSij4rRwt+gh5ZH7snYuOxNnZ7RSQOCbbTafiY6m9msXprTgsncuTa8cmG2uVMN+NPkuZmcIE3BTI\nobBJDlJrxNnhkbEJHTPtw0CQQ2a5Vvw7qJbBdDPBqkycmZqHnck+8qNylmmam9Zdga7t/YzuW8Ud\nnIRl6QdsmX4gFroCfKu0iZWZOGfueJXfRHrYmc+wZKidE7ev4PlcjqsTa5gdPjo9wA8Gf/kCZNXN\ncMfjY9sCsspkyWApToxCao/97a4qVC1MfHDV2DYhJEJ1Z1E16WpyqV5SkY2AhUUxQIhVLUJz7z1O\nTdKL3tIrhIPpVopzQ41cnVhFm+LnCUcTx+5YzvOlp+MrX0Bc2JmY6ye+9UHiAyuL8r6yhXyx5Cxu\n9Z9ABBsXJzchJBvCzBGsPhV/xUKe632V59QypuQHSXp2j4NX7XwShECxDEpllU8fYBw9UglWF5sH\n7art2cUkzc0PK1pYUtnC9yrGc3t5M7MO0RIvFWlFz0XwVyzY5+uR3heQVfeoVOXIocXu4hLLwaOJ\nIW7o3UxqP5ZjumXxk6EOfhfr4+pgFZf4y0kfoNPiYQ10swfZ4tEmJM72hPhp5QS+UtrIAuwHrbXt\nyGfZkEu9424L+6Ok7izsrioG2x9BsflJjaw/5HMUzbvHI0blAw5HadGeapR4/0uko62AhaS6UB2l\nRPte5PSBJ/ix2YVqD3DrUCe3DWxnc65oY6XYfZQ0fYjWshO5yzuXzzpnk5Xs/MJpclXzYj7vPZ45\nUo5q19GlBX2znOEJcWuonseTIzTaHDxiyFyqD/CCrZzSyEYm213kLBMD6NHzCAQ5BFfrvXx35BkW\n53biwKLeTI9l2SeM/mY/E1/BQqnAI7Zq7iwfx5PJEdKWSUhW+UxJDUuG2unTc9xR3oxN7PsWtCyT\n5MgGXMGJiP3od49khBDEbCFqjDibsbPYitGvuHnUmo5R0NA8vYzPDTEgu5lWKGpgg2aWf2l1uKzi\nZOzaxKsILJbbqxgUDvJIqJgcn+9ibqaL+11TKDEz/Hj4H7itAgUESaGwONuGZunoFCciAghZGbap\nRSuanKu4bOtPaMhYbFaD7FQDCMvCZ2aRtBIGjQIzHR5eGNldHDFN87A5l8ItyVS9y5Pq9wIOXzNC\nspF8nRXWofCxQAWPNcxitsPLtwe2c8qOlfzXcCfNNgdfz2ziQzYTWXnvZt8l2U6g6mRSkY1kE51j\n2092l7BNDdI2uGaP/YUQeEvnkI5uJp8Z3OM1T2g6zfNuo3rK9QCotiB5JGLxjn2+9/+rPw0si37F\nzdkuH5q7Cg2DFmcFTXqErFD4ZiLGaUYlKx013OeayucDp3JT8AzOlFv4gFXFetlLjSjwkFelwkxi\nmXnCDedR2ng+OaPA94Y6mJQfxI5B6DUrW+uVAFgWBUnhlnD9Hu2Mjxa84VkIoZAa2XBI7bAPhkj3\nM8iqB3fJ1L1eK+SiJIfX4Ss79l0vQtsXF+Pg1lA9/0gMcWH7mr3cVTrzWS7pWMuPhzs4zxPmxpI6\n5jt9uA9QHHxYA91/HURrtrfKP5LFSrt3U5/7WiRJpWrilQghMPUMqehmTPPg9CavJRPfTqT7n/gr\njqdx9lcYqT2fO3zHsck7Dc1Tj8PbiM1VDaaOZeqE6hfTPO92Fk/8CI82zOKqQBW/jxUrMidvXcqJ\n219hfttyPm+FeVGr4yxfBX9rms+i2pP4a6KfuGznsmDtG1/Ye4hrglV8yFvKplyKtGVSVjqHhkKU\nOwsKl6kmadNknM2BCazLJalR7fzaVo3HyvHp2HKuji6nTTgQlkUDBTYXcpyY62JBeCo3OqZxTUkN\nkzU3Px0uPii+U9bM1lya30R6uNRfcUDj+lyyCyMfxx08+vS5u3CN6vkMBPNkk7CR4lWtip3pZjRP\nL9cki1mlXtmNbJlYCJ4ftRnrl5w06xHmZHtACG4pOZWIpKFTdGb4RvwFbo8+R1zYqBzN3NqwcFs6\nG2xhYsJGq1IcEzLIxIWNOiPGDsVHo2MHMcNNIKtgAa1KkJwo/r9GjzPsKDq7zHR4eTFTDIolYKLd\nxZZcinE2517diN7n0JEkFad/PKnIxoNaptwf1arGvdWT+UlFC18K1/N84zHcU1rNvPgaPEeh7OdQ\nCVSegCQ7GO7cndU9p6SY/fxrpHOv/f0Vx4EQe3jo7kJWXcQHlgMSpp6gRyvDmdx3waDH48FnZjER\n7EgNkxhcBULGTHdwsy+MZuapK0QRApa4ZhEy0wzLTiKWxTXxFZyf7+SX0iD3G22o2/8XgNKmiyip\nOQ2A2zf9mVZbiJPzPRSQmFZatMD6v64V5EQxsF3sCXHBUVpkKISE09+CZRb2yLC/VTLxHaQirQSr\nT9lnIBvrWwYcGUVo+0Ig+FRJNb+unsKwkef89tVc07WRG3paubl3C4vbV7Eln2ZJxXh+VNmCXZLQ\nJJl7q/f/rDysge7jif23wX07sCyLv8QGmK6531DH+05ic5ZRPeVaTMvAMgskhw9NvpDPDNK96V4U\nu59ww3kISWZB/akYNh/ftDfjnXgNdTM+T+PsLzFuwfdpnvdtQrVnotiKgZNDkvmP0gaeaJjNkooW\nbiipZZbm5TjNxVei/+Jxl84PKsZTrtoxTIP7kwnqjRQnhN67S3z7QgjBbeXNYy2jfxLt445AGapl\n8q14jLNU2JrPUD/62+os5FCFxG2Bk2hTS/iVdyYCCJoZRgydKivHx6rm8qmCiya7k8+W1PJSKkpH\nIUezzcFcp48v9W0lrNi4OVR3wGtLjqwHxD5tYY4WJpfOIC0UmvUo2w2TMzLbWWcr44ncMchqlhp7\nN42FEZ7T6mnQo/TLLhLCTqsSJD36ILs1sQy3kSUmO/ihZx6d0u7JQcjMELDyY7reHBK/dE/nUa2J\nKiOJPpotd2DwsNbI5MIQy21VzFXXsi3bDAgKSIyI0bFDCGbne1mtVeMQEhPsLlYZxXPUqho2IWjN\npd8vRHsbcQcnUcgOk88cWlvf1yOE4APeMFcHq6lU7WMa1KPJlu/NIisOApUnkBhaQy7dB0Cj3ckk\nofO45RwrPNuFavfjDc0k1vfSXj7GuXQf8YEVeELTscwCmj1AVWGE4ezeel/TNKgsFN0XHjdVksPr\n8IZmYOop5qqwSO+nXfXzFdVg28QT+MiEi/mkQ2NYcbHcUctV0aVU9D1DJrYdLBNPeBbBqhMBeLZn\nBX9WK5id66VZj9ClleMe7aT2veggCIFm6XynfNxRXWQYrCl2HR3pfOJtO+dQxz+QVTeByuP3es0y\nDaK9LxS1u0e4k89xLj8P181gvtNHr55jYzbFS+koMzUPj9TP5NzXTXBKD6ACOKyB7spMnH790AsN\nDpbV2QRb8mku9h0ZVYOvxeGpo2riVQD0t/0RQ39jc3OAXKqH9jVLsIw81ZOvQVZ2B/C3lk8gJVR+\n0rnbJPxAN3mDzcG53jA3hGpZUtnCN+UEC3LdlLwmePpd98u0yW6u9HiR/g19QW1C4p6qSSz2hEhb\nJjdkDL7lCxIyMzya11kgGewsZMc6miVMg36h8XXf8aSEDQEMy05sqpuLQuO4dqiXcsXOr6sn061n\nuaa7uCz7xVA9l3Suoy1fbPH7RsUxyeH1OLz1KKr7gPsdyUz1lLFJDTE1P8AyA07LdiJbJu2Z8QBo\nnl6+Hv0XloBKPcE2NUhLYYjntVoajDgvqZU4LJ2b48vANNmgldEte1inhLCAbXLRGD5ddOHkvz2z\n+ItrIh9Kt/Jt/0LGjXZISyMTkd3IWLQ6XVSp/WRSxaKW9WqYjdruAXN+tosnhZ9pmpvhbIRB2QEU\nZQv9ep6Yqb9fiPY24goUx6LUW5Av7Iv4wCvYnRXYnBVv63mPVALVJyMklaH2R8e2ne8tZbsaYFX/\n6r33rzoZ08iOZm93M7TzEYSkUtp0IZLiJDTqdrBhcO1e53hleDObtHKEZTEiOzEQhBrOQ3PXMNT+\nKF9qXETISPHTbIFVg5tpcYe5uuEEvlzayDJbBU81foL62V/GXTINIRRKGz8IQFbP8/2RbmyWwXUl\nDVQWIli+4piRNw0GR1v+PlA6EddRKOt6LU5fM0Kyk0t1k8/s3wf2YMkk2kmNbCBYtQhJ3lteFR9c\niZ6PEqxetI+jjzwqVY1fVE3ib/UzeapxNi+O1m4damLzsEY2JvDX+OAb7vdm+X2sH6eQWOw9MmQL\nr8cTmordVY2Rj7F9xR17+B3ui0yinfY1dyGA2uk3orn3bGU4I9DIaST5vWGjM3XoGZBUZCOKzY9t\n1E4kWUjz42SKFiPJR6rmHvL53itIQvCDivEEZZW4afCZZBafEIwrRFhqygSMDJapFwvQRgvPYrKG\nJQR1qkaDqjFkGiwZ6eQYp5c/1k4jbhhc3LGWtGWywOHjtsEdtOcz3FM9aaxt4f7IZwbIJjtGO9Yd\nvahCYshWQq0RZ4vsp8rhZ1Guk6eVScRyJWjeXrxmlv8ceYa4sJGRVKqNBC9otZhAt+rFBI7J93FJ\neiOSZfID/wKCo9XgzUaMbUoAJwa/c07icWczF6Y28SvPdDplL26rgAAedE1mVqGPYUnjGKX4wPbE\n3VjAU/Y6dozq/VTLoFyYbMhnmOnw8q/h3dZX85w+WnPFwp73W/++fdgcIWyOMlKRQ1v1OhD5zCCZ\n+A68ZXOP6mzfoaCoboLVp5AYfHVsGfy8kiYky+Sv8b699nd469E8dUS6nx/Th8YHXyUxtIpg9Smo\ndj+ekmmoyQ4yQiG6j5b2D490oFgG5XoChODHnjnYtCDhhvPQcxG06EZucdqISXY+N9DG+pHi/XSF\nv7JYk5PK8HzBIt6/HG/ZXFS7n0g2zpUbH2KzWsLHrQjZdA8ALeVzyJgGJ256umgpZuaYUXLkJbgO\nFSEkvOGZAER6nnvL5xtufwxJceKvPGGv1yzLYqTraWzOirEJ5r8LhzXQnWR38VD8rS1J7Y+EofP3\n+CCLveEjWoi+SwcjCZnO9f9F75YHyWeGxgYXy7LIJNrp2/p7Otb8GFl2UDv989hd+85E3Fo9Awv4\ncscKzP34R+4LyzSKzSyCk8YG/5+0L2VY0vhKuA75KJ8Zv1VUIXF5oIK8ZfGFUB31/iZ01cW5qc1M\nKAwRMpIAOK0Cx2famZgrTuB26Dl2vMZerDuX5e6RLi7pXEt6tGJ0Uy5FwtS5r2YqJ4zKJA5EUUMl\n8JYe/Q4Yiqco0XBZBfKSyoXJ9eSRWZ+ZhN3djxA6NsvgimQxABWWxbDs5BVbJadldrBBCmICH0ut\n53+GHuH07HZe0mqQKPrtNusR/uScwAOeaUzID7JODbNBLeWziRXFbLuw80+tjnm5Hl6013CGuoKM\nacOb1DARZGQbppCQsSgzkhj2YLFRhMPDE8lh5NH7dKbDw+Yxa7H3A923E1dwEunoNkzj0Np/7o/4\nwApgtE3uvxGh2jPRPHX0bf1fCrkIIdXOsbLBk8JLbh82l4HKk8hn+klFWslnhujb8iCap55Q7ZlA\n0X/VMnMkFS++5J4d7AxT5ylT4Vgy3KamwLL4p2P0Xg9MwOlvYbjjcS6oPpav2HSGZCef7d1Ma6Qd\nIQTfLW9mgt3Fdf07eMA5gUD1qbQnerhs69Mst1dySb6Tmyd9CCuygX7Fh8NZwYc71jIgO8Cy+KTt\nvbP6uMvnNtr7wlg75jdDNtlJcmQ9wapFe6wE7yIdaSWX6iZYfcq/zQRwF4f113K6u4TWXJpN2eTb\nfu6/JQbJWCYfPgJlC69lV9Wjt3wewZrTiPW9xPZXvsmWF29m56v/yY6V36F91feJ9S/DE5q+R0OI\nfdHgruCzdnhJ8vKrjhcP+joyiR2YRhZXYCIAnakB7tcVFllxjgtPfGsf8j3CR3zl2IRgQM9zV2UL\nj7Wcyk1TLuVXUz/Msy2LWO63s7xmAndP+wjX2g1ujC3HMzpeTLK7qFM1Oowc/z3SRdw0yI0W2FSq\ndn5XM40Zjv03PdmFZZnE+l/GFZyEaj86uvwciMmhqQxJDmbm+3lVhxojwUJ9gIcKxyFJBh7XIHf6\n5hOwsmM2Y4pl8JRWj9/KscpRiQk8a68lJmtcl1jJhzKbgaKbwl8c47jXMwMsi1ZbmK1qCVMLA8zJ\nF7NYd/iO5/TsTlRMBoWG093P9lwjiiXRJXuICztYFgaCifkh+uxFScMExcZSS0MWxUGyyeZkSz5F\nuWI7KMvD9zl43IG3ZjP2WizLIjbwMk7fOFTtjSeV7yWEJFM54XIsU6d38/1YlskF/moGZRfPD6zZ\na39veCayzUuk+1l6Wu8FBJUTrhhzeXF4G7G7qvGaOcr0GD3J3UmrFwY3MixpnOd0UzX8CiVmGkPI\nfGZ9sZ1wacN5GHqKka6nuaTpNL6kZOmTXVzbvY6ftT4Eep7/rRzHomwnD7incFHPVj7evootapDr\nzH5un3oJ0Vyc6mwPr/inc377arZki1pju6VzffPRsfR+MDi8DciqG8vU92jHfKgMtT+KJDsIjOqc\nX89w11MoNi/e0tlv+j2OVg5roLvIHURF8JfDIF/4fbSfFpuT6dqRrWFU7X4c3kaSQ2sobTiPhjlf\noXzcJfgrjkNWXciqi7Lmj9B87B1UTrj8oIKbT9ct5Bgzzo+yJhtj+7Z+eT1FDZyEK9ACwHc6V2Ii\n+Er1rLfy8d5ThBQbiz1h/hjrp6eQRRKCWpuGXZJQFAeh8rk43JU4JJkzGs7g9Fwnf6Wbr5Y2kDYN\nyhUbnwpWc3WgimM0LwJ4uHY6f62fSfNB6jpTkVb0fBRf2bGH98O+Q8z1VfKqrZyZ+T5WCA+S4uRS\nK8IL+mxMS2D39OIzsnwxcAq1eozNaojmwgiDspPtio9F2XY2KCFOzHWwxDOXH3jn8SdnCzf5T2G7\n4md6YZDxuUGCZhosCxmTL0aXAtAqB9mmBjg7s41XbWV8LLuasL0PJVG8xx7XGmi1hcY8kI/J9/Cy\nvZJaVWPVyBYykkoBiZCsoghBay71fjb3MODwj9qMRd66TjebaKeQGXxPrIa8GWyOUsqaLiQd3Uyk\n+1nOKmnEYen8NbF3q2QhKQQqFpKKbCKbaKd8/Ef3SLIIIQhUnoDdKEp2Wod263T/Gu3GbunMyezE\n1LNcJmeLWd1R3bzmqcUTnsVI1zPouRiXNZ/JrXKapGRniQhx4ral/GH1z7kptpSaQpSNhkW34qVK\nWIjwHB6OD3BT5yquCp3D3XIlbiFQRm0HzzDffNbzSEQIaXS8t4gPvLxH84+DJTbwCsnhdZTUnIqs\nOPZ6PZvsIh3dTKDq5CPSUuxwc1gDXZ+scJI7wF/jA+hvwT7m9WzIJlmfS/Jhf/lRkYL3hGaOis0H\nsDvL8VccR1nThdRMvZ666TcSqFx4SF6PsiTzo9q5OCydG7s3kjmIgr/E8FqcviZkxcmjvat4Qnj4\nqJyn3n1kZ8TfaW4MFS3Wbh/Yt6XOLhSbB094FpmB5VzmCfJ04xwerJ3GreF6PhmsYn0uybmeMFMO\nIov7WmL9y5AU51HZ9ndfOCWZPnsYt1UgImuo9iB1ia205OJ0AqXScwAAIABJREFUZutweHu4MrGK\nPtnFJjVMVNao0eNsV4MkhY0aI0GxzAXOzmzjWUcDL9mq2GIP83dHM416FFVYGEJmSmGQG2IvE7By\ndMlubg8cz/xcFyEzQ5scAE8ESVj448XJ8Up7xR6dBlsKI/zB8nKs08dj8QEcZh4LaLQ5yZkmbbnM\n+44Lh4Gizdg4UiNvzWYMikVoQih4wjPepqs7+vCVL8BdMo2BHX8l0/svTpZNnpP8JF9X7GRZBqZR\nDB5l1Y0ntHdNgLd0DkJ2UEAiOZpxj+eTPGXauVDvI92/nEDViVzfch52SycrFH6y7RkAwvXnYFk6\ng+2PAPCJcWfz3PjjuZUIUwoDTMr1s0YtpdJMc06hn7M1Bx67n7uHO/l87xaW69CkR7izrIlzomvJ\nCBXVMlgy+bzD+fW9KwQqTwAEkmynf9sfsKx9N0rYF/nsMP1bf4/D20iw5tR97jPS9TSSbD9iLcUO\nN4dd6HKBt5RBo8Bzqb1nlG+W38f6sAuJ848S/7xi20WKPoNvE5WuEN/y+WmT3Xy97dkD6nVzqV7y\n6T484Rm8OLiJm2MxxhlJbqr/9/zRH4gqVeMzJTU8nhzmuTfwgQ5UnYhl5on171m5fM9IN1nL5DMl\nNfs5ct8YhTTJobV4S+e8p2bdXk8dBoJaI04/Cqae4nKR5MncAmzOESrVEbxmjsyopdh6NYQhJAqW\nxIikkRYq/+E7kXm5bhxmgUozxTmpzfzTUU9c2LgsuZYrYqu4I/IsMwr9/NQzh+tKziYlqZyb2Uqv\n5OLszBbWBmVMS5BPhRiUHMQkDa+RRbYMNLNAEJM4Fgs0Ny9YGuOk4sNmmuZmcy5FAYupR/gK0tGK\nJzSDQnaITPzQs1m7sEyD+OBK3CVT39NNIt4IIQQV4z+GKzCBgbY/cVViNQomj/Ttfv7kM4N0rLmL\nka4n0LyNGIUkI51P73UuSbYRqFiAgkk4uRPTNLmv6xVSQuXDmW3IqptQ3dkAnKBHQQh+nS/eNzZH\nmGDVycT6lhIffBUAp6LxqZZz+L7Xhd/KcfaES3hw2sXcNeVCflo/h4frZ7Bq3LH8qWYy9w4+zCXm\nMGeZEX7rqAchON44/N787waqFsQTmoFlWeRS3UR7Xjio4yzLoLf1NwBUtFyGEHvX2uQzQ8QHVuIr\nX/Bve18c9kB3kTtItWrn58Ndb3m2DhAzdB6OD3KWp+So0cqpWgDNU0986O0LdAHOqZzNh0WK/8PN\ndVse329mNzG0GhB0qkGuG+olZOb5TcNcPOq/54/+jbgqUEWD6uBb/W3kDjCBcHjq0Dz1RHt2Vy6v\nSMe4N9LNBd5Smg7Rhio+uBLL0vGXzX9L13+kcUygkU1qCXNyvSw3i/fsHM3FxlQxa23zdVOtF/04\nhWXisHSEZbHBXkqX7GF6YYAqPc4S37Gckt3B81otF6Y3sSi9g195ZjClMESnLcBHwh/k6tBinnA0\ncmZmGx+Pr2FyYYh/2Wv4QvB0pthbKaSDWKbKMnsVCVmjIGRMJBr1KAnVhwQY6R5SkopdKQa1C11+\nVo/qA6drh5ahf5+DwxuejaQ49tnE4GBJRVsxCkm8Zf+esoXXIqtOqid/mrKmi3CkOrh76DHM/uV0\nbfwV3Zv+HztWfpdcuo/KCVdQP+PzeEIzGGp/dMyH97X4K4p+rAEzzfZ4Jw9kdS7PtKJk+ihtOG9s\nqfwXUy9AtgxiksZzA0WXhnD9OTi8DfRteWDs3PnMIJGuZ/GWzsUbGLfX+7klhXxsGz4rjz8wgYc2\nP0xcsqNYBvdMueBwfWXvOoGqk7HMPDZHGYM7/04u1fuGxwx3PEEmvp2y5g/vt7ZncOdfEZJMsPqU\nt/uSjxreUqDb1tbG7NmzyeX2v3SuColPB2tYnU3wQnpv0+lD5Z6RLpKmwScDVW/5XO8k3vBMcsmu\nvdouvlVubz6Na5U8TwoPl2x5hqF9GHsnhlZhuaq4aqgfOya/qZ1KmePAFlf/ztgliW+UNdJeyPLL\nSPcB9w1Unkg+M0Aq0sqIXuBzvZupUjW+Xtp4yO8b61+G3VWFfR995Y9m5norWGmroFmP0Kr4UexB\ncqluPjDSTyRXgtPXwfxMx6jG1qJf8RA00qyyl+M08uSQmVvoo1P2kKYYKN/rnslnkis5Mb2DiLDz\nieRqLkptpFqP8YXYMq5IrsVHgSwyf3M2k5AUmu3bSafKEBT9cxVLJyOpWMD0fD+tapDpmodnEoM4\nzcL/b+++4+Qqq8ePf26Z3rbN9pbeO0koCTUQIHRIgiCIWBD5ihIEBEH9ogLiDwsqCChFihSp0r5S\nYgolhJCE9E3dzfbZPjt95t7fHxMikXQ2md3Nef+VzNx758w8r505997nOYfAjivMUxw+VkaD+DUL\nRfvZmlwcGFWz4is4hmDLCpKxzoM6Rkfj++lpP0dY6aQ9URSF7JITqJx4I9hz8KdCtHdsItq9HVf2\ncAZMvAVvfroyRcHgOSiadecits+zOvJQPenvswXVb+NPBbmwey0O7wC8BbuWpRyRaANF4cZAukqD\nouoUj7gSRbVQt/YvGKkYzVteRFE18gfseQpCU2AFMTT8gQ/5vXcSKApHJQ5tA6pMc3gHYPdUYBoJ\nFNVC9YrfENrDAk3TNGmvX0hL9Rt48yfj28PJXaRrC8HAJ+SUzugXi5sP1kEnut3d3fzqV7/Cat33\nF/+FvnyKdBv3ttR8qau6gWScR9vrOdvjZ0Qfu4XoyUvXyuvJ6QsAqqryw0Enc6fLwnrVyblbP+Ln\nG9/i7aaVdMZDvFU9n1ionocUP3FUHi4azAD3kVFE/cuY7srmDHcu97Vup2pH/dTd8fjHo1k8tNcv\n5MbGKtpSCf5QPHyfDSH+WzRURzRYja9gap+Yd34gPJpOiy19tUHHBN1OpGsrY+xutnUPx+FuYiBt\nZBtRkqiEVCsj4wGqLLm4SLLcWsBR8QZub1/AqGQLw+ItLHBU8LG1iInJANlm+kT7uFgtdaqHY2O1\nrNFymR6t4R1HJS5SXGEuQFUNYt3p6U5rrH4qEzsSKkVhVCLAm1oe0x0eFhpWjlWi1CXieFQNi6ry\nabSbcQ5Pvxub3iS7eDqYBh2N+19N5jPR7lq6W1aSXTQNpReXm8wEm6uYcRN/xK05M7jVdywDJv2Y\n0lHf3qUqhW71UjBoNtHgNpo3P/+FtvUlFemSY8OD6/h5+7+x23MoHvENFGXXFOKJyhmopkGL5uTu\nqnS3L4stm+LhVxAPN1G7+s90t35KbtlMdJtvt/EahkFucCPbrLm8FbPQpjlQTYMnx1zQkx9Lr6Mo\nCjklJ5GIteEfcA66zcf2VX+is2npLtslYh3Urr6Ppk3P4soeRsHgObs9nmmaNG1+Ac3qJXcPc3eP\nFAeV6JqmyW233ca8efNwOL64wu+/WRWVq3NK+SQa5P3wwZ2tA/ypdTsJ09y5YKgvsdhzDsn0hc/M\nKZ3KX3PzyTZT/C1l46qOIBO3Lufd1vQZYanLz2vlYxidVXlIXr8/+nH+QDyqxldqVrEyEtztNqpq\nIavoOLrbVrOus4ab/QMYfRAnYS3bXkPV7F+4QtJfFLuKaVftjI4HWJMEzBS61YulLR9FNfB4aylI\nBXcuDrOTXiSzxuonjE6z6sJjxjk6UssvOxZQluzkT96jCCo6rYqNlZZ8SlNBruv6CB0Du2JgoLBE\nK+TK4HLO1T8EoDFczjbdR7vmTPdTM01U02B4vIVPrIXkxNsIqlbGuXJJYDLA6qAzlWRLPCLTFg4x\nq8OPK3sk7Q2L0w1aDsBnpZVySo/sH/Q9sWsa33B7Wa1n8++GT3a7jTf/KLKKptNev4Dq5b8m2l27\n8zlX9ghCqp0cI0pCd1E+7ge7vULo8Xg4PZmeR/twyvq5/YeTW3EG4c6NKKoF914WC65pXUNuKkzS\nMLkvJ32l8sRk/76a+xlP3gR0q4+u5o+pGDcPp3cgDRseY+uyO6n59F7q1v6VrcvuINy5iYLBcykd\n/d3dVlmA9J3caHAb/oqzdtsl7Uiyz1Pf5557jscee2yXx4qLiznzzDMZPnz4XvfdtGkTwWA6QRiD\nSa6icvf29dxl7v5M7jPRaJR163btItZIir8rHZyKjcjmbey9x1gvZRSjhN5n3eoPQdv7Z3AwcoBf\nK5WEUzHWGQHWmxHOjVRj6PmcYQwhWNPCOr58m8HP291Y9Sd34uJWpYtLqldyq+lhPLvewYhg8rLh\n5UJUru9ezfDGCtY1HuDJXLwepfNTTOdUNm7a3oPR/0emx6nSVFlmLWRKrJ6XHUMZShPdwU58CSeJ\nhJ2RrlV0BC+CHXd8VlkLyEpF+Le9gp90LOJR12i+GfqUd+2VfGQrIS8ZYrm9mIv9F3JctIYVtiK+\n37WEabFa4qiMSQR4zT6QG0Mf4TYTGJ5W4hEfroTK+w4/xclOanQfCjA00YamKDgUCx+012HXfTR1\n20CFykiC16rWgArZzW2sa+75muD/LdNjlVGpASjxtaxf+TrYvzh/c7cSTSgdn2I6p1C1qXrf2/eg\nvjRWk00n2Uonf2hvo6hz7S4VR/5jLHi9RLvns/WTu8E2CIwQJNtxmVEAkobGxs21u9k37bvaUBYb\ndXRpds759AV+ZdlRp727GQUwjBRbPv4VuE/YdYzNOERWsy6+hREoPOQeS0LV8aUizNOGf6nPuS+N\nE5YRJDs+pGrdh2A5BZxeoolWiHWB2QxqDviOp7Ezm8bOL3asA8BMQds/QMulod1HQ0cfee8c/Fg1\nNTXt8bl9JrqzZ89m9uzZuzx26qmn8vzzz/P8888TCAS48sorefLJJ7+w7+DBgykt/c98w2va67m9\neQtd5cVMde450Vu3bh0jRuzaxOAvDRvQgyq3DRxLgd43z07i0Xy2fPQ++b4guWWHtk7qJNKT/rcs\n/Rf+gaeQW3pomkLsbqz6kxHAi8k4V2xfze2Jbr6eXcJwm5NBVifb4hHuCGylMakyPHcKE1o/pKxA\nwZWz/5+HaZpUr3iNpNXHwAlzUbVDMwc00+NUlEowb9UmZkS30aC7sdh8KIRIoBIIDqLQW4UaNPGn\nQgQ0F42am+Oj1Sy1lWCgcEqshlccQzgvspEl1iJqrLmcGt7MO44BtGhOkopKZaKDGtVDqZE+uZ4V\n3UIUjUc9I/mx6ylq2sZgJ8UqawFnhTfxoHcSmCZj4000ah6Od1j5F1mcpkSocuRAJMaM4kq2JaLQ\nEmTW0FF4D8MC2EyPVSaZ5jC2LF2CrmymYsQ5+7XP9lXziehOBo2fvcerW4dKXxurr1d38JuonZas\nBNMLxu1hqxGkEtNp2vw8ofb1WB1+OtQB/C1p5Svdq/EZHZT4E7stR/aZ3zUrXNkWYI3VT8hvZ6jR\nQX3gY3wFU8kpm0nDhr8RDf4LNbIY3epFt/qIheqIJbqpUGy8Z69kozUPTJOnikYxPLv4S73vvjRO\nqeQAti6rQo29R+XoH6GqB15qsqX6DVpauigbc83OJlF9xcGOlcez5ztuBzV14a233uLxxx/n8ccf\nx+/38/DDD+/XfnN9BeRrVm5v3kzE2P86cWui3bzcFeDy7KI+m+QCWO25OLwD6Gz8sEcqUOxLutrC\nf8qbiYOTr1v5e/lYpjp8PNRWy3UNVZxTvYJrGzaQo1n4R/lY5o6Yi8Xhp3HTs1+Y37Y3wZYVRIPb\nyKs865Alub1Blmah3ZZHCoUByU5qTY1ErA1Vd9IZGYOqJ5irLqJNc+xs4BBWdCKqhafcoxiY7MBI\nGWzRfXy3ezl5qTAaJk4zwQarnwmxRhKmiYMULaqTGsXFO/YKrsk9nVOtS1DVFJ+G010K61QX0R0L\nzVAUxiaaWa1nEw41YaJwbfFYPt3RzXGwzcnKSJBBVsdhSXKPdIqiklU0jUjXZqLBfTfDCXduJtS+\nltyyUw97ktsXfb3kKHxGjN+21pHcy/QQzeKmePjXGHLMnWSN+g7XWIbwgb2C2qxRmEDDxmdIJaN7\n3P+E/OEM37Ew7dtNm2jY8Dh2TyUFQy7G5synYvx1FAyeizf/KKzOAkwjjsM7gNbSM/GZMf7gSTcy\nOjYR+NJJbl+j6XaKhn6FeKSJlurXD3j/UPt6Wqpfx+uf1OeS3EPlsDaMtqsadxUNYUMszM2Nm/Yr\n2Qsk43ynbh1+Ld11qq/zFR5HPNL0pepF7q9gywrs7nKs9txD/lr9nU/TebRsNKuHHMvrlRP4Y/Fw\nfl80jBcrxjPB4UVVLRQOnksiGqBt+1v7dUzTSBLY+gpWZxG+gqmH+B1k3kiHjxXWAo6PVvO+ll4I\no1uz8HT5MQyNs2wLSaHunL6w3FaEahqssBRQo3k5J76Fl3fc6vxN+9uMjTdjNxLYjTgf2kv5bfY0\nVln9/D/vVK7Pm8lvfMdwbHQ7Y1yriKTsGEE/2zQvVwU/4T17GWCimQYj4i18YCthoerlXDVMSPcQ\nNQ0UoEK3szIaZKzMzz1ssgqPRbN4qFv/CKlEeI/bmaZBy7ZX0SyeHQX3xb44dRvXulys1Lz8YvO7\n+7XPLVsW06TYuDu3iMqiY1CAVKKTxo1P7fWk/rUx52IxknRqDr6RNYPSkd/aWR9cUTSyi6dTOHgO\npSO/RcX46ykddRXBjiquy55BVLXgNmI83s8XoO2JK3sEvsJjaNv+DpHg/k/HSUTbqF/3CFZnIYVD\nLzmEEfYtXzrRfffdd7HZ9v8q6wmubOblVfDPYICH2+v3um3ESPGturW0pxI8VDqSLK3vF9H3+iei\nag46Gg58ZfGBiIUaiAar8filxW9Psqkqw2wuzvDkcZbXj/65eW6u7OF4/JNorfnXfpWRa6v7N4lo\ngPyB531h9XJ/dKyvhPn2CgqMMA26B0Wzg5nCjHYQ6K4k27cNqxlHIZ3oGii4zAQR1cKdWenmJhdF\nNnC/fQzPOYczNVbHX1pf5x+BF5jX+SF1mod7fMewzZLN0bE6fta+gK+HVqD76vkgMpERiXY2WHIZ\nkWxjq56FxTQZmmjDikFSs6NjcF3pZD7YUQaxTLfTZiRoSSV6favx/kSzOCkZ+c30j/b6R75Q7grS\nSW7jxqcJd24kr+LMI36xzYH4WtlUziXE44aTZ2o/2uu2z9Yt402cXKmFmVYwmjG5I2hXHbRacggG\nPqFm5e9JxHZfNjTcuYUHOhejmQYNFi8nbdz7b972lnrusg2lypqHZhrc76882LfYL+QPvADd6qWx\n6sn9WpxpGAnq1v4F00xROvKb8jfxORn5db06p5SZ7lzuCmzl/dDu/0gM02ReQxWro938vnjYQa1k\n741UzYq3YDLBwHJSiUO3sKW9YRGKoh8RVwp7k4KBF6CoOvXrHt5rPdD2+kUEtr6MO2c0riOk7ufR\nnkI+tJWSQKU82UmnaicRS6+m3hSdhG4NczmLmBitB9PERCGo2qjXvViMFI+4x1GWCjKIbh71jOen\n3mn80zmEZ5wjyEmF+GvLq9zZ9g7f6vqYeV1LmBBvxOJqwaZHWBkej9NM4jDifGwtwlBUkiiMiTfx\nqe5nlZ7DHC1BkTOXD8KdWBWFYXYnK3ZMYZCKC4eX0zeIwsFzCLWvI7D15V2eM02Dhqon6Wx8n9yy\nmWQVTctQlH2ToijcOfgkxqa6+Fl3hI/bd9/ufHMowM+7uhiV6uT6gScD6fbzAe9QPIlO8oZeTixU\nz7bldxNq30Ay0Y1ppkglQjRUPUXNyt9QosT4qyVd2aRe9zB99e5vxQeDQc5uXkuD7sVqJHmlYDDH\n+gcfss+gL9B0B4VD5hIL1VO/4XGM1J77FRhGgsaqp4h211A07HKszoLDGGnvl5FJZ4qicHfREC6q\njnB1/Tq+mlXEZVlFFFpsmKbJahLcW7+ef3W3clv+QE5x969b71mFx9JRv5DOpqXklJ7U48c3UjG6\nmj7Ckzce3So/0IeTbvNRNPxr1K97hG3L76Zk1LdxeCp22aZ1+9sEtr6EK2c0xSO/ccTUZs3VLZRp\nCqstfqbFtrPEUsSpifSJrjVxDEbqBc53vsVTTMdtxOjW7OlpDIpCte5jizWHAckOZofTK3KfcY0g\noVnYYM1jVriKCcFPWGPxMzbWhEK6Zm91Xpg8UyfWWQQEOSreyC+z0omRqSiMSQR43j0Ch5nke2VT\niBkGH0e6SJgmg63p+blWRWG43ZWhT+3IlVV0HNHuWtpq38E0DWzOInSbj66mpXQFPiavYhZ5FWdk\nOsw+yaZZ+XPlFM7b9glXN27hf8IdnFMwkmzdRmcyxh+2L+WpWAodk9+VjMb6ufUDhf6J2DpWsjYR\nY+qEH1K75kG2r/rD546evn6WXXIy/spZDNZs/KV5Pd9sa6be4mXQ+kXkGmHO0aAqHmKN5qFTtWNq\ndtypGP8qGUeBb/ddvo407twx+CvP3tEprY6SEd/A5tq1Dn6kaysNG54gHmkir2LWXhcJHqkytrrC\nrer8pXQkdzRv5cG2Wv7SVsdJ7mw2xMLUqFFcIY0f5JZzRT+ciG53l6Zbxza+R3bJiT2e6HQ1L8NI\nRckqnt6jxxX7x5M7horx11O35kFqVvyW/IHno9uySCUjRIPVdDQswuOfSPGwr6GoX+xN3p8d5/Dx\npmMgN3d9QKPuRonrKKqFikSU+q5hlPjWo0aTXNBZxd98E7CZSWKKBY8ZJ2bo/Ms+gGnR7cwNr2Nq\nrJ7/sw9gsGqSbcRIoeA2EoxMtWICmzUfg70bWRIbx/B4F82qE78RZpU1HyuQMg3etVfwia2Iq/QY\nuXYfS8OdRHfcKh9ic/J0RyMjbW6sR8DUkt6oYNBFJGLttNfN3+Vxf+U55JaflqGo+ocCZx735Zfz\ng+at3N4d4o7gEiYpcdaaGkHFwimpdn5YNIqBvl1P1CcUjGPFZhudgWXYyqZTOfFGultXk0qGMZIR\njFQMb/4k7O6ynfuckD+cxxSdec2baNFctGouHgGwpk8gFdNkULyV76oRSXL/S275TOyeSurXP8q2\n5b8mp/QUNIsLRdGIR5por1uAbsuibPQ1B1Tx50iS0WXEpRY795WMoCYe5W8d9bzcFWC4zcnsmM4V\nw8bg7MdJQFbRcTRWPUmkawtO36AeO65pmrQ3LMLmLMLhPfA2tKJn2N0lVEy8gfq1f6Vp83O7POcr\nPJbCIRcfEfNy/9uJ2eU8EeoiFtQpSnUT1ZzYU2ESwWresJ/Ft7Q1XGl5g7WWiehmipiik58I0qy7\nOTq6nSX2MgKqE58ZxW+EuSL0KZti2QxOdhBVNM6MbqJRc/E77xRijjDP64081XUus+PNNKtO3rIP\nIKVo+DAIYfBveyVnGB1cNyDd+emDcCcKYAIDLA5WRbuZ7ZPbgJmiqBplo7+DkYqTTARJxTtRFAt2\nT9m+dxb7NCFvOO9mD2Rp86e83FHHQsPGCCPEvLwyjio4d7cXYSyqTqNvFAPal1Pf3UyxOx/ffjS6\nOdY/mA93TEe4etVLfKS5cBtxzrHaGJpsYGD7R+QcdVuPv8f+wJU9jAETf0T9+sdorXljl+d8hceS\nP/B8qTqyF72iXk651c6t+QO5NT+dmK1bt65fJ7mQXpTWvPl5Ohre69FENxqsJta9Pd27/Ai5Jd5b\n6RY3ZWP/h2hwO4qqo2p2NN2BZjlyb4NPdmajoLDBksvRsTqWWfI5NtmFmUzicMwmHr2fs11vc1/8\nfEbHmlhhLyamaKAodKk2FExecQ7h8tAqFNNknSUPtxnHRoo2xcU23cESWwkOI8kxjnQ3tO6uCiys\no8To5g5nelFbm6lgA27qeI/zjpqHZUfb2AWhdvI1K82pOAYmEdNgvEOm/2SaqlmxarkgFWR6nKZZ\nObroKI4uOgojFUdR9X2ehI+rPJ1g+3KWVb9J8ajLD/g17x9z3s5/d8a62fjRT9jqrGSUM/+Aj3Wk\n0G0+ysZ+DyMVSS/QNFKgqDI9cT8ceZeUeglVs+HNn0ww8AmJWHuPHbejYTGKasWbP7nHjikOnqJo\nOLyV2N2lWB15R3SSC+mqFZN0lfm2MtxmgibtP5/HLDVBVed4CpzbGaluwbKjzFin5iAnFaVTc+Az\noix0VBBBw1AUBiU7cBlxTKDQCDEq0cIV3StZYS3gZPuHfBofxrhQJ0kUYihU61m4zCQoCtd2LqHA\nYsWvp+cfbo9HWRENkq3plFnsrImGAFmIJo4cqmbdrztN5Z5itroGUtS2gu69lIDbH4u3vo7bjFNR\neeaXOs6RQFEUNN2JbnGj23yS5O4nSXQzKKdsBiYmrdVv9sjxUokwXYFl+PIny20M0WtN9xbwjmMg\nYdVKgREmpqTL4OihWp6Ln49pKlzmeJ2ljhKcRjzdQMJMUad78RkxulUbD3sm4DYTOM04hUb6h9YE\nYorOQmspeZY2Rlk3sSgymUnxBjRMnnWNwlQUKu0+dDPF1HgDOXmTdsb1ajBdEi5uGgyyOlgc7qBY\nt1FhsR/2z0iI3q64dAZuM8571ftXj3d3gokw+S1L2OwoZ0yezC8Vh4YkuhlkteeSVXQcHY0fEI80\nf+njtdXNxzQSsghN9Gon+opJKSrbrAVMjdWx1JJefBLurMKZfRyhrlKOd7/HsdHq9LQF06RNc6Ka\nBl4jDsAiRwU3ZZ2ECSjAZj2Lf1V+FSvwZ99kLnG+TNJUCbQPRcfEAF52DgUgkIxxVKwBu5lkcukx\nO+P6Z1eACXYPtckYAy0OPgh3MM2VJVOAhNiN8f5RbLf6sTe/T+oAOp1+3qItb+AxYpTI1VxxCEmi\nm2F55aejqDot2177UsdJxNppq30bj38idnff7yAn+q+hVie5pJhvKcBAQduRSMbDTVyRXcQnnVNx\n6CHOtSzA/9kVXcBEYY3VD0BOKsIaaz6LbOWkUHgmfybnt3/EW7Yy0BJc5Po//i9yPMeEugB41jGc\niGrFCjSnkkyPbSeh2rDtKJtUFQuxIR7mWGcWcdPEpqoEjRTTnFmH/wMSog9QVRW9aDoFyS6WNOy9\n8cTuhBIRcgMfsNVeynj/6EMQoRBpkuhmmG71klNyIl1dtiYvAAAXtUlEQVSBZUS7aw/6OIGtr4Bp\nkj/gvH1vLEQGKYrCMTYHi+1lNHgGMylWT5PqBAwKY838PTWTZNzFJP9CfhFdDaZJthHBVBRSiopq\npHAYCRxmktGJACut+VzSMp/Grmr+5D2K2a7XcakRnu86kxHxJsLovOBK3xYt0G3opsGUWB1Wd/nO\nmF4NtqACZTumKbSlEijAsS5JdIXYk+NKp9OmOen8r/Jv+2Ph1jfxGVEKpBayOMQk0e0FckpnoOoO\nAttePaj9I13b6GpeSk7pyVjsOT0cnRA978SsUrpUGwl7PhomLZoTgGDLSrJyR1HXMJl8ewODrfMZ\nn2yhU3WQl0x3KdMwqbN4ubljMX4jwkfWYt6yFnNl3iwUUlzqeoUPo+O5tqUOBXjFOWTnVeEuI8mY\neBNOM0nhjpJIpmnyz64ARzt9tKTSUyM2xMKMtrvJ7gdtx4U4VKyahQ7/VAZE61lQs2C/92uJtJPd\n/D5b7cVMLBh3CCMUQhLdXkGzOMktnUGobTWh9vUHtK9pmjRveR7N4iGnTAqoi75hmjs9L3dFPMIG\n1yAGJjtIkU50v55TxsPxM4mHc3AXfczXrQkMReE0jx/VNEioOlYzyZBkO3Wam3fslbzsGk5UtTLL\n+W/8WjvO+nKyE23EUSlIBAkr6YS100hxSjTd8tTrTy9EWxXtpiYR5WyPn03xMAWalU+jQZm2IMR+\nmDHoHGqs+birX6ImWL/P7ZNGiqWr/ozTiFE26MLDEKE40kmi20tkl5yI1VFA/fpHiUdb93u/YGAZ\nka6t+CvPRtNldbjoG/y6lSEqLFV9OP1H4TCTNGlukrE2xugWFjiHU18/Fas1xBTbCxSlwqwKNvDT\n7GIwTXJTEdxmnN94jyaiWshLhtDMJF9zv0BNrIzsTi8KEFM0nvOMBkXBqagopsnUWD2qxY26o6zY\nq8EAFhRmevJYGw2Rp1tIAdNk2oIQ+2TVLAwb+Q0UYP3av5Awknvd/o11TzIgWkdz2SxG5w47PEGK\nI5okur2EqtkoHX0Vppmibs2DGKnYPveJdG2lcePfsbnL8BUefRiiFKLnzPAWsMaSR2m8lWW2ErKN\nKACdje9zdnYpz6aOJ9xZisP3Npd7FVbpWQyLVnNdThENuodHXWNZb83DVFTaNQdzLPMZZNlOd/MI\nVM2JAmzSs6m2ZIFpEjYNRifbcJpJPLnjAUiZJq8FWzjelY1FUdgUD6Oi4FBUJti9Gfx0hOg7Krwl\ndJWfQ3msmTfXPb3H7RZuX8iQ1o+o8o1hxoCZhzFCcSSTRLcXsTryKRl+JbFQPQ0bHk93P9mDaLCG\n7avuQ7N4KB111RHZTlb0baf7ijAUlQXBRloKT0Q3DZIotNcvZF5eBa+4htJSNwlFTXKR52l00+Dv\nbds5r+NjBiXaeNE1nCl2L5PsHoZqNVyd+zA1iWLcLX6MVAQDhT96p6Caxs45umdGNgOQV3EWAC91\nNdOYjHOhL5+10RAG0JyKM8Xpw6bK35QQ++vEipOo8o5kUOuHvLb+aTpiXTufi6XizK9+F8+2F6ix\n5nPaqCsyF6g44sg3eS/jyhlB/sDzCLasoHHj30nGu76wTbS7lppVf0TTnZSPvRaLTW6xir5nlM1F\nkQKLtCxmePz80TsZHZNkrBWHmcBp8fKaOpFgYBg29R/8Jvcp3raX0dr4ITfrIVKKyoZ4mN8VZXNP\n3u0YKLxadzmdigMDeNteSaPuxthxEmhBYXK0BkW1YLG5iRkGv22pYYzdzanuXFbFggA0JeNMl/m5\nQhywk0ddwVZnBYOaF7Plo5/wz9WP8uq6v7P8gx9TVP0CnZqLUaOvwq7bMh2qOILomQ5AfFF2yckk\nYp20182nq/ljsoqm4c0/imiwhlDHesLt61E1B2VjvydVFkSfpSgKM735PGGkcLavwVcwlReTHZwf\n3kDd2of5Wsm5PBofzqy6SaiKwYn+v3NzTjOLg1M5jwRT7R4+jTVjRi8mT+vkypY7uK5jPV4zRrPq\n4iHPBCoSHVRbsnAoKscpMRxmErt3MAB/66inIRnj10VDUBWF1dFuPKpG0EhxnMzPFeKAuS1OZh11\nA2tbq6irfpOBbcvQMNnsKMcoPp7pRZPRVC3TYYojjCS6vZCiKBQMuoDs4mm01vwf7XULaN9Rp1C3\nZePJm0hu+UysjrwMRyrEl3OGt4BHO5t5p7OOa8tO47TOcYyPNzKgYx1nuIp4N5lkg57HsNopJBMO\nzil+hzUDm9C6Etxt0WjzBPFQx/fbbmN1fAjNei3+RJSbc07CZ8TQzVR6UZppMLtzCQC5ZTPpTCW5\nv7WW413ZHLPj6u2qaDcORcWpawyxOjP4qQjRt43MHcrI3KHUdTdhkGKWuzjTIYkjmCS6vZjVkU/R\nsMvILT+DSNdmHN4BWOx+aUkq+o2JDi95O6YvXBpt4uKsIm4yTuaxllegbj4/w9yxpUKwaSwrrKOY\nmvM8ljwLxDUCKT+3BK9nYXQyhaluRiZaeNMxkBmx7VwQXM3c/AsAOM/jp7Qp3ZDFlT2Mu1uq6TKS\n3JhXAUAwlWRzPIIGXJJVJH9jQvSAEndBpkMQQubo9gVWRx6+gqlYHfnyAyz6FVVRONWTx8fWYgKB\nT/huXgUpVee3vqloFjevl1zAo64xBHeckxfV2jin8Tkuan0FzbOapW0/443oiZwSreH/tb9LCpWX\nHcM4PryFKksOKUVDReFKM12yT7f6aEjGeay9gXO9fkbY3QCsjYUASAGzffLjLIQQ/YUkukKIjDrd\nW0BU1VnQUUuuZuFSPcl79nLWmhZ8yU6ec4/iz950cwenmeR77QvZEo/w29btVHuHMyrexLeDH5Nt\nRAkpFsK6g59mncBf3emOS3N9BdibFgHQmDeVr2xfhQLM23E1F2BVNL0QbZjVyagdya8QQoi+TxJd\nIURGTXX68CiwSMsm3FHFN3PLyU5F+GXWNJxtqwFYZi8jioahOZgQb+LM8EYe62ojWT+fO9r/Tbtq\np9ZZzpgRX+PWjsW0a3Y2W3JRgKuz8ol117LIVsZ3UjkkTZOnysZQYvlPg5XFoQ4ALs4qzMRHIIQQ\n4hCRRFcIkVEWRWWGO48lthKa697F7xvAHV3vkVQs/M43FY8RY7TVwbuOSlKpCIVDLuF8m4VsI8Ji\nexlhdH6ccypvlpyDicHgeDOViQ5QFEzglG0r+J+c07gr6zhG2N28VDGecQ7PLjGsiAZRgXO8/ox8\nBkIIIQ4NSXSFEBk3y5tPt2rl3VAn8WgLo30V3NH5HjFFJ6ZobIx2MsCMYQEebN7Id7QKvEacJs3N\nT4tnM9iVx6tdAd7Y+g43Zp9ClTVdkeS7WYXMClfhNuPMTtTzZPlY/Dta/36mOREnaKQYanWSpVky\n8O6FEEIcKlJ1QQiRcce7sinWLLzmHMqsuvl4/BOpDCzjd2orV5t+WjQnP/RNQ/emSKEyLN7KvdYI\nq/xjeairhSWRdGOVn3omoZsGAyx2DGBu6wK6u1cAkFdxJtbddBB8vKMBgHO8+Yft/QohhDg85Iqu\nECLjNEXhkuxiVlrzWdWyDrunHFWzMZQoP+1eDsAJDg+nJQNcElrN5Ggd97jHM9NXwj/KxnKWKxeP\nEQXga2qIrYkoF3py6G5ZgaKkz+c9eRN2+9qvBwMAzJFqC0II0e9IoiuE6BXm+AqxAK/aK+lsXII7\nZwyh1tWcWXEyBaluEt01/GboGZwf385FkfVsbN/ExM0fMm7jh+Q1vsvPOhaRRGWRrRgVOC6wCDDR\nbVlYnYXYXEVfeM1PI0G2JaJ4VY1sXaYtCCFEfyOJrhCiV8jVLczy+nnXMYj6+sW4c8eRSobQNCvT\nnVksV9xUr32Q4aO/gw7c1T4fq5HgkvBaZofXMTzRymwtxppYmNFWB/aWj1FUG4loC5688V94vZhh\ncGPjRlTgaKfvsL9fIYQQh54kukKIXuPSrCLCisbbei7JRBeqZqer5RNOzh1MRLWwPNJN06ZncGYN\nw2XGea71VS7u/hTN4kazeDg+bxQAtZE2Yqi4c0cDu5+2cG9rDRvjYQzSHdqEEEL0P5LoCiF6jQl2\nDyNtLt5wjyKw7RWcviEEW1ZyjN2DBlQVn0Y80ky4Yz0ARiqKolpJJbrJLT+dF9s24zTitGkOXiy9\ngFSiG6sjH5ureJfXWRkJ8mBbLVN2JLjHOLMO91sVQghxGEiiK4ToNRRF4atZRWxRnayx+ImFGzGS\nYdTgZiY4vCwxrQw99tcMm/4Hhhz3azSrD9OIA7Bxy8ssSKQ4LbqNC+w2nkxovBhN4sodv0vr7PSU\nhSrydSt+3UKOZmGkzZWptyyEEOIQkkRXCNGrnOP1k6PpPJ57PNFoCygawcBypruyWBML0ZpMoCgK\nmuYgt2wGAO7csbzrGUNS0fj6gBncVjqBsRrc65vMNUoRG2IhWpJx/ty6ndO2LWNTPMIdBYNZEu5i\nmjML9XOJsBBCiP5DEl0hRK/iUDVuzR/Ip0mDdwtngpmiK7CUY63plr3vhdsxTYPW2ncIbHkZZ9Zw\nzCGX8ZRzGNOdWYzOKser6fwmsoLrw2vYlkxx9rblTN+ylF+3VFOi23mwZAR+3UpLKsF0l0xbEEKI\n/koaRgghep1zPH5e7grwYFhlkrOcnHANrrV/JCv7NP7d2cC4LU8S6dqMO3cMBYO/wjebNqOg8MvC\nwQAk40Ei7VVcVHYKXymfxP2ttRiYzPUVMsTmBOCB1loAprmyM/Y+hRBCHFpyRVcI0esoisLPCwYB\n8ED+TCzOYsxYG2Mj1SwMNhMN1VE07DJKRn6bFyNhFoc7uMlfSYklfdW3peYNwMRXMJVszcIt+QO4\nNX/gziQXYFG4neE2J/n/1RJYCCFE/yGJrhCiVyqx2LneX8niSJBPKucACsfoOu2ag8joefgKptKY\njPPLwFamOrx8JasQgFiogY76xWQVTcPmLNztscNGimWRLqY75WquEEL0Z5LoCiF6rcuyiphg93Br\naxNPFJzBsI6VWFB4PRZldbSb7zdsIGma3FE4ZOeCsuYtL6JqNvIqZ+3xuEvCncRNk+kybUEIIfo1\nmaMrhOi1NEXhwZKR3N2yjb93mvwr+yRKifFYewN/ba/HpWjcXjCISqsDgO62NYTa15I/8AJ0i3uP\nx10UaseuqBwljSKEEKJfkyu6QoheLUe3cFfhEJ4vH0eeprEVK0lM5ngLeG/QZC70FQBgGimat7yI\nxeEnu/j4vR5zUbiDqU4fNlW+AoUQoj+Tb3khRJ8w3uHhxcqjuD/0MR4jRmt3Le4diWo80kJD1RPE\nw43kDzwfRd3zzaq6RJQt8QjTpRuaEEL0ezJ1QQjRZ9hsXmaMu5qZG9/ipZSHtasfIlu30RX4BEVR\nySk9BXfOmL0eY353O4DMzxVCiCOAJLpCiD5F1Wx8teIE/lGzkjdjUc7q3EBO6Ylkl5yMxbb3q7Sm\nafJERwMjbC4G7ZjXK4QQov+SRFcI0eeMtrsZanWyOPc4flD6TTSLa7/2ey/cwcZ4mLsLh6BI218h\nhOj3ZI6uEKLPURSFC3z5fBqPUm3uf8L6cHs9eZqFszz+QxidEEKI3kISXSFEn3SuNx8VeKqjcb+2\n3xQLsyDUzleziqTaghBCHCHk214I0Sfl61bO9+bzeHsDG2KhfW7/WHs9VkXZ2UFNCCFE/yeJrhCi\nz/qRfwAeTeO2ps0YprnH7dpTCV7oauY8bz55uvUwRiiEECKTDirRTaVS/OIXv+Diiy/mggsuYP78\n+T0dlxBC7FOObuFH/gEsi3TxbGfTHrd7uqORqGlwRXbxYYxOCCFEph1Uovvyyy+TTCZ5+umnuf/+\n+6muru7puIQQYr9c6M1nisPL3YFttCTjX3h+fncbf2zdznRnFsNs+1edQQghRP9wUOXFFi9ezNCh\nQ/n2t7+NaZrcdtttu91u06ZNBIPBAz5+NBpl3bp1BxOaOMxkrPqG/j5OX0fle0qS729azjWmm+wd\n5/D/JsZvlW4q0fh2t9InPoP+Plb9iYxV3yDj1Hcc7Fg1Ne35jt4+E93nnnuOxx57bJfHsrOzsdls\nPPDAAyxdupSbb76ZJ5988gv7Dh48mNLS0gMOeN26dYwYMeKA9xOHn4xV39Dfx2kEMK+1lrtbtrFU\naeckdw6DrE4eaGtlqsPLAyUj8Wh9o2x4fx+r/kTGqm+Qceo7DnasPB7PHp/b5zf/7NmzmT179i6P\nXXfddZx44okoisKUKVPYtm3bAQclhBA96arcUk715PBcZxMvdDbzdncbM9w53Fs0XMqJCSHEEeqg\nvv0nTZrEggULAFi/fj1FRUU9GpQQQhyMgVYnN/kHsHjQZF4oH8efikdIkiuEEEewg/oFmDNnDqZp\nMmfOHG677Tb+93//t6fjEkKIg2ZRVMY5POjS5lcIIY5oBzVpzWq1cuedd/Z0LEIIIYQQQvQYuacn\nhBBCCCH6JUl0hRBCCCFEvySJrhBCCCGE6Jck0RVCCCGEEP2SJLpCCCGEEKJfkkRXCCGEEEL0S5Lo\nCiGEEEKIfkkSXSGEEEII0S9JoiuEEEIIIfolSXSFEEIIIUS/JImuEEIIIYTolyTRFUIIIYQQ/ZIk\nukIIIYQQol+SRFcIIYQQQvRLkugKIYQQQoh+ST8UB02lUgA0NjYe1P5NTU14PJ6eDEkcIjJWfYOM\nU98hY9V3yFj1DTJOfcfBjtVn+eZn+efnHZJENxAIAHDppZceisMLIYQQQgixi0AgQEVFxS6PKaZp\nmj39QtFolNWrV+P3+9E0racPL4QQQgghBJC+khsIBBg9ejR2u32X5w5JoiuEEEIIIUSmyWI0IYQQ\nQgjRL0miK4QQQggh+qVemeiGw2GuvvpqLrnkEr7xjW/Q1taW6ZDEHgSDQb7zne/w1a9+lblz57J8\n+fJMhyT24q233uL666/PdBhiNwzD4Cc/+Qlz587lsssuo7q6OtMhib1YuXIll112WabDEHuRSCS4\n4YYbuOSSS7jooot45513Mh2S2I1UKsXNN9/MxRdfzKWXXkpNTU2PHr9XJrrPPvsso0aN4qmnnmLW\nrFncd999mQ5J7MEjjzzC0UcfzRNPPMGdd97J7bffnumQxB784he/4J577sEwjEyHInbj7bffJh6P\n88wzz3D99ddz1113ZToksQcPPfQQt956K7FYLNOhiL145ZVXyMrK4qmnnuKhhx7i5z//eaZDErsx\nf/58AJ5++mmuvfZa7rzzzh49/iEpL/ZlXXHFFTtrodXX15OXl5fhiMSeXHHFFVitViB9Vmaz2TIc\nkdiTiRMnMmPGDJ555plMhyJ2Y9myZUyfPh2A8ePHs3r16gxHJPakvLycP/zhD9x4442ZDkXsxemn\nn87MmTN3/l+qQPVOM2bM4MQTTwQOTc6X8UT3ueee47HHHtvlsTvuuIOxY8dy+eWXU1VVxSOPPJKh\n6MTn7W2sAoEAN9xwA7fcckuGohOf2dM4nXnmmSxZsiRDUYl96e7uxu127/y/pmkkk0l0PeNf0+K/\nzJw5k9ra2kyHIfbB5XIB6b+ta6+9lh/84AcZjkjsia7r3HTTTbz11lvce++9PXvsHj3aQZg9ezaz\nZ8/e7XN/+9vf2Lx5M1dddRVvv/32YY5M/Lc9jdWGDRuYN28eN954I1OmTMlAZOLz9vY3JXovt9tN\nKBTa+X/DMCTJFeJLamho4JprruGSSy7h7LPPznQ4Yi9+9atf8cMf/pA5c+bw2muv4XQ6e+S4vXKO\n7gMPPMBLL70EgNPplNsNvdimTZv4/ve/zz333MMJJ5yQ6XCE6LMmTpzIwoULAVixYgVDhw7NcERC\n9G0tLS1ceeWV3HDDDVx00UWZDkfswUsvvcQDDzwAgMPhQFGUHs37euXlggsvvJCbbrqJ559/nlQq\nxR133JHpkMQe3HPPPcTjcX75y18C6atS999/f4ajEqLvOfXUU3nvvfe4+OKLMU1TvveE+JL+/Oc/\n09XVxX333bdzUftDDz30hc5ZIrNOO+00br75Zi699FKSySS33HJLj673kc5oQgghhBCiX+qVUxeE\nEEIIIYT4siTRFUIIIYQQ/ZIkukIIIYQQol+SRFcIIYQQQvRLkugKIYQQQoh+SRJdIYQQQgjRL0mi\nK4QQQggh+qX/D7qVDKlAwBJ4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29fc30dc6a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import andrews_curves\n",
    "andrews_curves(data.drop(\"party\", axis=1), \"immigration\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Observations\n",
    "\n",
    "The RBF kernel with a coefficient of 0.1 and a cost of 1.0 produces the best CV result over the grid search. The resulting accuracy (96.8 $\\pm$ 3.1%) is the same as produced from the nested CV search. The final model is trained using these hyperparameters.\n",
    "\n",
    "\n",
    "Of the algorithms included in this comparison, Support Vector Machines appears to perform the best for this data set. However, it's performance does not significantly improve on any of the other algorithms (within CV error). In fact, all algorithms perform reasonably well, with the possible exception of the non-parametric K-Nearest Neighbors Algorithm.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}