Sonar Submarine - Project 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import model_selection\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.svm import SVC\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 208 entries, 0 to 207\n",
      "Data columns (total 61 columns):\n",
      "0     208 non-null float64\n",
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      "12    208 non-null float64\n",
      "13    208 non-null float64\n",
      "14    208 non-null float64\n",
      "15    208 non-null float64\n",
      "16    208 non-null float64\n",
      "17    208 non-null float64\n",
      "18    208 non-null float64\n",
      "19    208 non-null float64\n",
      "20    208 non-null float64\n",
      "21    208 non-null float64\n",
      "22    208 non-null float64\n",
      "23    208 non-null float64\n",
      "24    208 non-null float64\n",
      "25    208 non-null float64\n",
      "26    208 non-null float64\n",
      "27    208 non-null float64\n",
      "28    208 non-null float64\n",
      "29    208 non-null float64\n",
      "30    208 non-null float64\n",
      "31    208 non-null float64\n",
      "32    208 non-null float64\n",
      "33    208 non-null float64\n",
      "34    208 non-null float64\n",
      "35    208 non-null float64\n",
      "36    208 non-null float64\n",
      "37    208 non-null float64\n",
      "38    208 non-null float64\n",
      "39    208 non-null float64\n",
      "40    208 non-null float64\n",
      "41    208 non-null float64\n",
      "42    208 non-null float64\n",
      "43    208 non-null float64\n",
      "44    208 non-null float64\n",
      "45    208 non-null float64\n",
      "46    208 non-null float64\n",
      "47    208 non-null float64\n",
      "48    208 non-null float64\n",
      "49    208 non-null float64\n",
      "50    208 non-null float64\n",
      "51    208 non-null float64\n",
      "52    208 non-null float64\n",
      "53    208 non-null float64\n",
      "54    208 non-null float64\n",
      "55    208 non-null float64\n",
      "56    208 non-null float64\n",
      "57    208 non-null float64\n",
      "58    208 non-null float64\n",
      "59    208 non-null float64\n",
      "60    208 non-null object\n",
      "dtypes: float64(60), object(1)\n",
      "memory usage: 99.2+ KB\n"
     ]
    }
   ],
   "source": [
    "ds_sonar = pd.read_csv(r'data/sonar/sonar-all-data.csv', header=None)\n",
    "#Check object types.  All are float and last classification is Object.  We have to convert target classification \n",
    "#to Numeric value.\n",
    "ds_sonar.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th>1</th>\n",
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       "      <th>51</th>\n",
       "      <th>52</th>\n",
       "      <th>53</th>\n",
       "      <th>54</th>\n",
       "      <th>55</th>\n",
       "      <th>56</th>\n",
       "      <th>57</th>\n",
       "      <th>58</th>\n",
       "      <th>59</th>\n",
       "      <th>60</th>\n",
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       "      <td>0.0371</td>\n",
       "      <td>0.0428</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0954</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.1601</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>0.2111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0180</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0453</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>0.0843</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>0.1183</td>\n",
       "      <td>0.2583</td>\n",
       "      <td>0.2156</td>\n",
       "      <td>0.3481</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>0.2872</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0094</td>\n",
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       "      <td>0.0140</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0582</td>\n",
       "      <td>0.1099</td>\n",
       "      <td>0.1083</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>0.2431</td>\n",
       "      <td>0.3771</td>\n",
       "      <td>0.5598</td>\n",
       "      <td>0.6194</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0232</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>0.0316</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>R</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>0.0623</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.1098</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>0.0598</td>\n",
       "      <td>0.1264</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>R</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0762</td>\n",
       "      <td>0.0666</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0590</td>\n",
       "      <td>0.0649</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.2467</td>\n",
       "      <td>0.3564</td>\n",
       "      <td>0.4459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>R</td>\n",
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       "1  0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
       "2  0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
       "3  0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
       "4  0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
       "\n",
       "       9   ...      51      52      53      54      55      56      57  \\\n",
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       "2  0.6194  ...  0.0232  0.0166  0.0095  0.0180  0.0244  0.0316  0.0164   \n",
       "3  0.1264  ...  0.0121  0.0036  0.0150  0.0085  0.0073  0.0050  0.0044   \n",
       "4  0.4459  ...  0.0031  0.0054  0.0105  0.0110  0.0015  0.0072  0.0048   \n",
       "\n",
       "       58      59  60  \n",
       "0  0.0090  0.0032   R  \n",
       "1  0.0052  0.0044   R  \n",
       "2  0.0095  0.0078   R  \n",
       "3  0.0040  0.0117   R  \n",
       "4  0.0107  0.0094   R  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_sonar.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>55</th>\n",
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       "      <th>57</th>\n",
       "      <th>58</th>\n",
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       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
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       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.029164</td>\n",
       "      <td>0.038437</td>\n",
       "      <td>0.043832</td>\n",
       "      <td>0.053892</td>\n",
       "      <td>0.075202</td>\n",
       "      <td>0.104570</td>\n",
       "      <td>0.121747</td>\n",
       "      <td>0.134799</td>\n",
       "      <td>0.178003</td>\n",
       "      <td>0.208259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016069</td>\n",
       "      <td>0.013420</td>\n",
       "      <td>0.010709</td>\n",
       "      <td>0.010941</td>\n",
       "      <td>0.009290</td>\n",
       "      <td>0.008222</td>\n",
       "      <td>0.007820</td>\n",
       "      <td>0.007949</td>\n",
       "      <td>0.007941</td>\n",
       "      <td>0.006507</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.022991</td>\n",
       "      <td>0.032960</td>\n",
       "      <td>0.038428</td>\n",
       "      <td>0.046528</td>\n",
       "      <td>0.055552</td>\n",
       "      <td>0.059105</td>\n",
       "      <td>0.061788</td>\n",
       "      <td>0.085152</td>\n",
       "      <td>0.118387</td>\n",
       "      <td>0.134416</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>0.009634</td>\n",
       "      <td>0.007060</td>\n",
       "      <td>0.007301</td>\n",
       "      <td>0.007088</td>\n",
       "      <td>0.005736</td>\n",
       "      <td>0.005785</td>\n",
       "      <td>0.006470</td>\n",
       "      <td>0.006181</td>\n",
       "      <td>0.005031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.005800</td>\n",
       "      <td>0.006700</td>\n",
       "      <td>0.010200</td>\n",
       "      <td>0.003300</td>\n",
       "      <td>0.005500</td>\n",
       "      <td>0.007500</td>\n",
       "      <td>0.011300</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000600</td>\n",
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       "      <th>25%</th>\n",
       "      <td>0.013350</td>\n",
       "      <td>0.016450</td>\n",
       "      <td>0.018950</td>\n",
       "      <td>0.024375</td>\n",
       "      <td>0.038050</td>\n",
       "      <td>0.067025</td>\n",
       "      <td>0.080900</td>\n",
       "      <td>0.080425</td>\n",
       "      <td>0.097025</td>\n",
       "      <td>0.111275</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008425</td>\n",
       "      <td>0.007275</td>\n",
       "      <td>0.005075</td>\n",
       "      <td>0.005375</td>\n",
       "      <td>0.004150</td>\n",
       "      <td>0.004400</td>\n",
       "      <td>0.003700</td>\n",
       "      <td>0.003600</td>\n",
       "      <td>0.003675</td>\n",
       "      <td>0.003100</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.022800</td>\n",
       "      <td>0.030800</td>\n",
       "      <td>0.034300</td>\n",
       "      <td>0.044050</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.092150</td>\n",
       "      <td>0.106950</td>\n",
       "      <td>0.112100</td>\n",
       "      <td>0.152250</td>\n",
       "      <td>0.182400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013900</td>\n",
       "      <td>0.011400</td>\n",
       "      <td>0.009550</td>\n",
       "      <td>0.009300</td>\n",
       "      <td>0.007500</td>\n",
       "      <td>0.006850</td>\n",
       "      <td>0.005950</td>\n",
       "      <td>0.005800</td>\n",
       "      <td>0.006400</td>\n",
       "      <td>0.005300</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.035550</td>\n",
       "      <td>0.047950</td>\n",
       "      <td>0.057950</td>\n",
       "      <td>0.064500</td>\n",
       "      <td>0.100275</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.154000</td>\n",
       "      <td>0.169600</td>\n",
       "      <td>0.233425</td>\n",
       "      <td>0.268700</td>\n",
       "      <td>...</td>\n",
       "      <td>0.020825</td>\n",
       "      <td>0.016725</td>\n",
       "      <td>0.014900</td>\n",
       "      <td>0.014500</td>\n",
       "      <td>0.012100</td>\n",
       "      <td>0.010575</td>\n",
       "      <td>0.010425</td>\n",
       "      <td>0.010350</td>\n",
       "      <td>0.010325</td>\n",
       "      <td>0.008525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.137100</td>\n",
       "      <td>0.233900</td>\n",
       "      <td>0.305900</td>\n",
       "      <td>0.426400</td>\n",
       "      <td>0.401000</td>\n",
       "      <td>0.382300</td>\n",
       "      <td>0.372900</td>\n",
       "      <td>0.459000</td>\n",
       "      <td>0.682800</td>\n",
       "      <td>0.710600</td>\n",
       "      <td>...</td>\n",
       "      <td>0.100400</td>\n",
       "      <td>0.070900</td>\n",
       "      <td>0.039000</td>\n",
       "      <td>0.035200</td>\n",
       "      <td>0.044700</td>\n",
       "      <td>0.039400</td>\n",
       "      <td>0.035500</td>\n",
       "      <td>0.044000</td>\n",
       "      <td>0.036400</td>\n",
       "      <td>0.043900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               0           1           2           3           4           5   \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
       "mean     0.029164    0.038437    0.043832    0.053892    0.075202    0.104570   \n",
       "std      0.022991    0.032960    0.038428    0.046528    0.055552    0.059105   \n",
       "min      0.001500    0.000600    0.001500    0.005800    0.006700    0.010200   \n",
       "25%      0.013350    0.016450    0.018950    0.024375    0.038050    0.067025   \n",
       "50%      0.022800    0.030800    0.034300    0.044050    0.062500    0.092150   \n",
       "75%      0.035550    0.047950    0.057950    0.064500    0.100275    0.134125   \n",
       "max      0.137100    0.233900    0.305900    0.426400    0.401000    0.382300   \n",
       "\n",
       "               6           7           8           9   ...          50  \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  ...  208.000000   \n",
       "mean     0.121747    0.134799    0.178003    0.208259  ...    0.016069   \n",
       "std      0.061788    0.085152    0.118387    0.134416  ...    0.012008   \n",
       "min      0.003300    0.005500    0.007500    0.011300  ...    0.000000   \n",
       "25%      0.080900    0.080425    0.097025    0.111275  ...    0.008425   \n",
       "50%      0.106950    0.112100    0.152250    0.182400  ...    0.013900   \n",
       "75%      0.154000    0.169600    0.233425    0.268700  ...    0.020825   \n",
       "max      0.372900    0.459000    0.682800    0.710600  ...    0.100400   \n",
       "\n",
       "               51          52          53          54          55          56  \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
       "mean     0.013420    0.010709    0.010941    0.009290    0.008222    0.007820   \n",
       "std      0.009634    0.007060    0.007301    0.007088    0.005736    0.005785   \n",
       "min      0.000800    0.000500    0.001000    0.000600    0.000400    0.000300   \n",
       "25%      0.007275    0.005075    0.005375    0.004150    0.004400    0.003700   \n",
       "50%      0.011400    0.009550    0.009300    0.007500    0.006850    0.005950   \n",
       "75%      0.016725    0.014900    0.014500    0.012100    0.010575    0.010425   \n",
       "max      0.070900    0.039000    0.035200    0.044700    0.039400    0.035500   \n",
       "\n",
       "               57          58          59  \n",
       "count  208.000000  208.000000  208.000000  \n",
       "mean     0.007949    0.007941    0.006507  \n",
       "std      0.006470    0.006181    0.005031  \n",
       "min      0.000300    0.000100    0.000600  \n",
       "25%      0.003600    0.003675    0.003100  \n",
       "50%      0.005800    0.006400    0.005300  \n",
       "75%      0.010350    0.010325    0.008525  \n",
       "max      0.044000    0.036400    0.043900  \n",
       "\n",
       "[8 rows x 60 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_sonar.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0\n",
       "1     0\n",
       "2     0\n",
       "3     0\n",
       "4     0\n",
       "5     0\n",
       "6     0\n",
       "7     0\n",
       "8     0\n",
       "9     0\n",
       "10    0\n",
       "11    0\n",
       "12    0\n",
       "13    0\n",
       "14    0\n",
       "15    0\n",
       "16    0\n",
       "17    0\n",
       "18    0\n",
       "19    0\n",
       "20    0\n",
       "21    0\n",
       "22    0\n",
       "23    0\n",
       "24    0\n",
       "25    0\n",
       "26    0\n",
       "27    0\n",
       "28    0\n",
       "29    0\n",
       "     ..\n",
       "31    0\n",
       "32    0\n",
       "33    0\n",
       "34    0\n",
       "35    0\n",
       "36    0\n",
       "37    0\n",
       "38    0\n",
       "39    0\n",
       "40    0\n",
       "41    0\n",
       "42    0\n",
       "43    0\n",
       "44    0\n",
       "45    0\n",
       "46    0\n",
       "47    0\n",
       "48    0\n",
       "49    0\n",
       "50    0\n",
       "51    0\n",
       "52    0\n",
       "53    0\n",
       "54    0\n",
       "55    0\n",
       "56    0\n",
       "57    0\n",
       "58    0\n",
       "59    0\n",
       "60    0\n",
       "Length: 61, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_sonar.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QDRJoAMCUgm40UutyuZz6+vrGVIr7+vpOeg40G7QA8UMCDQCYUnGDkeJmI/Vq8eLFam9vH1Mpbm9v1+LFi0/qumzQAsQPCTQAAAGNr8DPREWeDVqA+CGBBgAggMcee0ydnZ1KJpOaP3++ksmkOjs79dhjj53UddmgBYgf5kADABBAU1OTlixZot7e3tFj2Wz2pCvFiURC999/v1atWqXjx4+rsbFRa9euZd40UMWoQAMAEEBUleKenh7t27dP+/fv19DQkPbv3699+/YxhQOoYiTQQAjMagXqVyKR0KWXXqpVq1Zp3rx5WrVqlS699NKTrhQzhQOIH1o4gICKs1q7urrU3NysgwcPqq2tTZJ4q7WOnb/5gJ4+Njz6fNnGfZKk009t0OGbLqlUWIhAaaW49B6wcuXKk7oHMIUDiB8SaCCg0iqRpNEqUTKZJIGuY08fG9aj2y6dcLyYSKN2RHUPKE7hKF5XYgoHUO1o4QACokoE1Leo7gFM4QDihwo0EBBVIqC+RXUPKFavk8mkcrmcmpqalE6neWcLqGJUoIGAqBIB9S3Ke0AikVBvb69GRkbU29tL8gxUOSrQQEBUiYD6xrxmAEVUoIEQqBIB9SvKec1hRmQyThOoPBJoAAACiGpec3FEZiaT0eDgoDKZjFKpVNnEOMy5AKJDCwcAzBJmRsdbVFM4wozHY5wmUB1IoAFgljAzOt6imsIRJjFnnCZQHWjhAAAggKimcBQT81KTJeZhzgUQHSrQADBOuVYL2iwQ1SSeYmLe1dU1Zovwcr3VYc4FEB0SaAAYp1yrBW0WkPJJ9Ez3GodJzBmnCVQHWjgAAIhAmHFzYUZkMk4TqDwSaAAAZlhPT4/Wr1+vgYEBSdLAwIDWr1/PuDmgRpBAAwAQUNCqcnt7u+bOnavu7m4NDg6qu7tbc+fOVXt7+yxHDCAK9EADABBAcROT8Qv4JE1oo+jr69OBAwfGzGvetWuXLrmEhahALaACDQBAAFHtRAggfqhAAwAQQJhNTJYsWaK3vvWtevGLX6yjR49q6dKl+tnPfqYlS5bMVrgAIkQFGgCAAMJsYrJ69Wr19/fr2LFjkqRjx46pv79fq1evnpVYAUSLBBoAgADC7ESYzWZ14403atGiRTIzLVq0SDfeeKOy2WwFIgcw02jhAFAXSncXLG6Kwu6CCCPMJia5XE6HDh3Sli1bRo8NDw9r69atsxYvgOiQQAOIrTBJMbsLYiYE3Ymw2O5RnMIhTd7uASB+SKABxBZJMapVsd1j/Mg7JnYAtYEEGgCAGRam3QNA/JBAAwAQgaDtHgDihykcAAAAQAgk0AAAAEAIJNAAAABACPRAAyGZ2ejH7l7BSAAAQCVQgQZCcnct7bib5BkAgDpFAg0AAACEQAsHAFSh0l0WJbYfB4BqQgINAFWo3C6LEjstAkA1IIEGUDWougIA4oAeaABVo1h1Hf8oTaqBSurp6dGKFSs0Z84crVixQj09PZUOCUAFUIEGACCAnp4epVIpdXV1qbm5WQcPHlRbW5sksWU3UGeoQAMAEEA6nVZXV5daWlrU0NCglpYWdXV1KZ1OVzo0ALOMBBoAgAByuZyam5vHHGtublYul6tQRAAqhQQaAIAAmpqaNG/ePJnZ6OPgwYNqamqqdGgAZhkJNAAAAaRSKZ1zzjm67777dPa79+q+++5TW1ubUqlUpUMDMMtYRAgAQADFhYLJZFI/OpJTcn+T0uk0CwiBOkQCDSBSzHZGLUkkEkokElq2cZ96y2x0A6A+0MIBIFLMdgYqh7nVQDSoQAMAUIOYWw1Ehwo06h4VGgC1iLnVQHSoQKOuUaEBUKuYWw1Ehwo06hoVGgC1qqmpSQcPHhxzjLnVwMwggUZdo0IDoFalUim1tbUpm81qeHhY2WyWudXADKGFA3WtWKFpaWkZPUaFZnqMpgNmVk9Pj9LptHK5nJqampRKpU66jax0bnXxusytBmYGCTTqWrFCM74HmhaOqRVH041XTKQBBBflWozi3GoAM4sEGnWNCg2ASitdiyFpdC1GMpnkXgRUKRJo1D0qNAAqibUYQPyQQAOQVL6vmZ5mIHqsxQDiJ9IE2szeJGmHpDmS7nT3beM+f7akXZJeVDhno7vfE2VMAMor19dMTzMQPdZiAPET2Rg7M5sj6cOSVkk6T1LCzM4bd9p7JH3K3S+U9DZJ/xhVPAAAVKNEIqF0Oq1kMqn58+crmUzO2FoMdloFohFlBfp1kr7v7j+QJDP7pKQ/lXSk5ByX9MLCx6dLeizCeAAAqEpRrMVgp1UgOlFupPIyST8ued5XOFbqfZL+3Mz6JN0jKRlhPAAA1A12WgWiE2UCbWWO+bjnCUl3ufsSSX8s6eNmNiEmM7vWzB4wsweeeOKJCEIFAKC2MN0DiE6UCXSfpLNKni/RxBaNNkmfkiR3/7qk+ZIWjb+Qu9/u7he5+0VnnnlmROECAFA7mpqatHnz5jE90Js3b2a6BzADokygvyVpuZmdY2bzlF8k+IVx5/xI0hslycyalE+gKTEDAHCSWlpa1NnZqdbWVvX396u1tVWdnZ1jxuUBODGRJdDu/pyk6yR9WVJO+WkbD5vZ+83szYXTrpe01swOS+qRdLW7j2/zAAAAIWWzWXV0dKi7u1sLFy5Ud3e3Ojo6lM1mKx0aEHuRzoEuzHS+Z9yx95Z8fETS66OMAQCAepTL5XTo0CFt2bJl9Njw8LC2bt1awaiA2hBlCwcQC8xJBVCLijsclmKHQ2BmkECjrhXnpGYyGQ0ODiqTySiVSpFEA4i94g6H2WxWw8PDymazamtrUyqVqnRoQOxF2sIBVLt0Oq01a9YomUwql8upqalJa9asmbFdwACgUor3sNL7G/c2YGaQQKOuHTlyRAMDA+ru7h7dqau1tVVHjx6tdGgAcNKi2OEQAC0cqHPz5s1TMpkcs1NXMpnUvHnzKh0aAJRVLes2qiUOoBJIoFHXhoaGdNttt43pEbzttts0NDRU6dAAYIIo122ESYhZP4J6RwKNunbeeeeN9kDPnz9fyWRSa9as0XnnnVfp0ABggnQ6ra6urjHvmnV1dSmdTp/UdcMmxFHFAcQFCTTqWiqV0u7du8e8aOzevZtV6gCqUi6XU3Nz85hjzc3NyuVyJ3XdsAlxVHEAccEiQtQ1VqkDiJOmpiZt3rxZe/fuHb1nrV69+qRnO4dNiIszpku3BWfGNOoJFWjUvUQiod7eXo2MjKi3t5fkGcCMMLMxj5nQ0tKizs5Otba2qr+/X62trers7ByTyJ6IsJuuMGMa9Y4EGgCACLi73F1LO+6Wu8/INbPZrDo6OtTd3a2FCxequ7tbHR0dymazJ3XdsAlxIpFQOp0es36Ed+9QT2jhAAAgJnK5nA4dOqQtW7aMHhseHtbWrVtP6ron0s7GjGnUMxJoAABiIsreYxJiIDhaOAAAiAl6j4HqQAUaAICYYHIQUB1IoAEAiBFaLYDKo4UDAACE2sobqHdUoAFgnIVNG/XqXRvHHZOkSysSDxC14lbeXV1dam5u1sGDB9XW1iZJVLuBMkigAWCc/tw2PbptbLK8bOO+CkUDRK90K29Jo1t5J5NJEmigDFo4AACoc2G38gbqHQk0AAB1LuxW3kC9I4EGAKDOMV8aCIceaAA4CeUWHOaPSyw6RFwwXxoIhwQaAE5CuQWHEosOET/MlwaCo4UDFcPMUQAAEEck0KiI4szRTCajwcFBZTIZpVIpkmgAmAbFB6DySKBREaUzRxsaGkZnjqbT6UqHBgBVi+IDUB1IoFERzBwFZtb5mw+M9l0v27hPyzbu0/mbD1Q4Ksy0eig+UGFHHLCIEBVRnDla3PVKYuYoal+UEzuePjbM7ol1oNaLD2wpjrigAo2KYObo7ChWJUsrk1QlK6c/t00Pvf2hCY/+3LZKh4aYCLvhSdyqufVQYUdtoAKNimDm6OygKgnUlmLxYXyFtlyCGcdqbq1X2FE7SKBRMcwcBYBwwhQfSqu5kkaruclksmrvvbT3IS5IoAEAiJGgxYc4VnPDVNiBSiKBBgCgBsWxmkt7H+KCBBpAXSg3AWMmpl8AlWBmox+7e9lz4lrNpb0PcUACjZrU09OjdDo9WsFIpVLckOtcf24bCypRM9xdyzbum/C/6VLFe97FF19c9jiAE8cYO8yoahiZxE5dAJCXSCTk7lracbfcfdJqNYBwSKAxY6olcWWOKAAAiBIJNGZMlIlrmMp22JXn1VA1BwAA8UECjRkT1ciksJXtMDt1VUvVHABqGYUK1BoSaMyYsFvMBhW2sp1KpXTFFVfonHPO0SmnnKJzzjlHV1xxRdltwmn3AIBoUahALSKBxowpjkzKZrMaHh5WNptVW1tb2cQ1jJOpbJeOeprpawPATDKz0UctoVCBWkQCjRmTSCSUTqeVTCY1f/58JZPJGRmAH7aynU6ntWfPHv3whz/UyMiIfvjDH2rPnj1lb9ZRVc0BIKzSaRm1hEIFahEJNGZUIpFQb2+vRkZG1NvbOyPzRsNWtsPcrKOqmgMA8ihUoBaxkQqqXtitXcNsX5tIJLRmzZoxGw3s3r2bjQYqpNxugfnjEjsGAvEU1x0RgamQQCMWwmztWlxEuGDBAh09elRLly7VwMCAduzYUfb84tul0+3qheiV2y1QmnzHQLbnBqpf2CIIEAck0KhptbYYB2OxPTcQD2GKIEAc0AONmhNmESEAAEBYJNCoOaz4BgAAUSKBRs1hxTcAAIgSCTSmFbctWBlNBwAAosQiQkypuAXr+PFDkqp2QQgrvgEAQJRIoDGl0i1YJY1uwZpMJqs6IWXFNwAAiAotHJgSC/IAAADGClSBNrMXS1os6ZikR939+UijQtUIs6sfgJnDrowAUL0mTaDN7HRJfy0pIWmepCckzZf0q2b2DUn/6O7ZWYkSFcMWrNXn/M0H9PSxYUm/3DTk9FMbdPimSyoZFmZY2F0ZAQCzZ6oK9GckfUzS77n7z0s/YWavlfQXZvZyd++KMkBUFgvyqs/Tx4bZfQ8AgAqatAfa3f/Q3T8+PnkufO5Bd/8bkuf6kEgk1Nvbq5GREfX29s5Y8hy38XgAAADS1C0cr5nqC9392zMfDupFHMfjAQAASFO3cHyw8N/5ki6SdFiSSfpNSd+U1DzJ1wHTiut4PAAAgKlaOFrcvUXSUUmvcfeL3P21ki6U9P3ZChDxErQtg/F4AAAgroLMgf51d3+o+MTdeyVdEF1IiKtiW0Ymk9Hg4KAymYxSqVTZJLo4Hq8U4/EAAEAcBEmgc2Z2p5m9wcz+wMzukESZsI4ErSqXtmU0NDSMtmWUG3lXHI+XzWY1PDysbDartrY2pVKpqH8czLL8PONXT3gsbJo44xgAgDgIspHKNZL+UtL6wvOvSfpIZBGhqoRZ7BemLSPseLyenh6l0+nRc1OpFL3SMcE8YwBArZk2gXb3QTPbKeked39kFmJCFQmz2C/sroWJRCJQElzrEztKN0aR2BwFAIBqN20CbWZvlvQB5XcjPMfMLpD0fnd/c9TBofLCVJWj2rWw1id2lNsYRaJCCwBAtQrSwnGTpNdJ+ookuft3zGxZdCGhmoSpKke1ayETOwAAQDUJsojwOXd/OvJIUJXCLvaLYtdCJnYAAIBqEiSB7jWzNZLmmNlyM8tIuj/iuFAlEomE0um0ksmk5s+fr2QyOSNV5TCY2AEA8RZ0mhMQF0FaOJKSUpKOS9ot6cuStkQZFKpL0MV+UX5/aeZbQwAA0av1heCoT0ES6NdKeq+7j5b7zOw1kr4dWVTAOJVO4gEAJ6bWF4KjPgVp4fiypPvM7FdLjt0ZUTwAAKCGsBActShIAv2I8mPsvmJmKwvHLLqQAABArWAhOGpRkBYOd/e7zewRSXvMrFuSRxwXACAipZv3sHEPohbVHgFAJQWpQJskufv3JP2epN+X9JtRBoX6EOWqbFZ8A5Mrbt5T+ijdDROYSdUwzQmYaUG28r6w5OMBSZeb2dmRRoWaF+WqbFZ8A0B1YSE4as2kFWgzay/890PjH5LePWsRoiaVrspuaGgYXZU9E2/pRXltAKhVvHMHBDdVBbq4PPbB2QgE9SXKVdms+AaAcHjnDghn0gTa3b9Y+O+u2QsH9R1utZMAACAASURBVKKpqUmbN2/W3r17RzdHWb169Yysyi6u+C7OHJVY8Q0AU2FWMxDOVC0cXzSzL0z2mM0gUXtaWlrU2dmp1tZW9ff3q7W1VZ2dnWOS3hPF1t8AEA7v3AHhTNXCccusRYG6k81m1dHRoe7ubt1www1qampSR0eH9u7de9LXZutvAAinmt656+npUTqdHr1/p1Ip7t+oOlO1cHx1NgNBbQh648vlcjp06JC2bNkyemx4eFhbt26dkThY8Q0AwVXLrGZ6sREX046xM7PlkrZKOk/S/OJxd395hHEhhsLc+Kqp2gEA9a5a3rmjFxtxEWQjlY9K+oik5yS1SPqYpI9HGRTiKcz4OPqUAaB+BB2RRy824iLIVt6nuvu9ZmbuflTS+8zs3yTdFHFsiJkwN75qqXYAAKpncyvenURcBEmgB83sFEnfM7PrJP1E0q9EGxbiKOyNL8o+ZTMb89zdI/k+9Wph00a9etfGMscl6dJZjwfAyYmydSLMtaulFxuYTpAE+m8knSbpXZL+XtLFkt4eZVCIp2q68RUT5mUb9+nRbSR0M60/t63s73XZxn0ViAbAyaqWza14dxJxMW0C7e7fKnz4C0nXRBsO4owbHwDEU5StE9X07iQwU6ZdRGhmF5nZ583s22b23eJjNoJD/CQSCfX29mpkZES9vb3cBAEgBqJc2M2icdSiIC0cn5B0g6SHJD0fbTgAAGC2RfkOIu9OohYFSaCfcPcT2rrbzN4kaYekOZLudPdtZc65XNL7JLmkw+6+5kS+FwDUs3ILO1nUiTBonQCCC5JA32Rmd0q6V9Lx4kF3/9xUX2RmcyR9WNIfSuqT9C0z+4K7Hyk5Z7mkGyW93t1/ZmZM9wCAE1BuYSeLOlEN2F0QtSjIRirXSLpA0psk/UnhcVmAr3udpO+7+w/cfUjSJyX96bhz1kr6sLv/TJLc/X+CBo7qlEwmNX/+fJmZ5s+fr2QyWemQAAAVFGaTLSAuglSgz3f3V5/AtV8m6cclz/sk/fa4c14lSWb2/yvf5vE+d//SCXwvVIFkMqmdO3eqs7NT69at086dO9XR0SFJymQyFY4OAFAJ7C6IWhSkAv0NMzvvBK5tZY6N381irqTlkt4gKSHpTjN70YQLmV1rZg+Y2QNPPPHECYSC2XDHHXeos7NTGzZs0GmnnaYNGzaos7NTd9xxR6VDAwBUSHGMXSl2F0TcBUmgmyV9x8weKYyweyjgGLs+SWeVPF8i6bEy5/yzuw+7+w8lPaJ8Qj2Gu9/u7he5+0VnnnlmgG+NSjh+/LgeeeSRMS0cjzzyiI4fPz79FwOoK+dvPqBlG/eN9mkXPz5/84EKR4aZlkqldMUVV+icc87RnDlzdM455+iKK66YdIxdT0+PVqxYoTlz5mjFihXq6emZ5YiB6QVp4XjTCV77W5KWm9k5ym///TZJ4yds7FW+8nyXmS1SvqXjByf4/VBhp5xyiu6880594AMfGG3huOGGG3TKKUH+TgNQT54+NsxulnWouEvsZFhwiLiYMoE2s1Mk7XP3FWEv7O7Pmdl1kr6sfH9zt7s/bGbvl/RAYTTelyVdYmZHJI1IusHdnwz9U6AqmFnZm6NZuW4eAAjm/M0H9PSx4dHnxST79FMbdPimSyoVFgJKp9Pas2fPmJ0Is9msksnkhKS4dMGhpNEFh+XOBSppygTa3Z83s8Nmdra7/yjsxd39Hkn3jDv23pKPXdKGwgMxNzIyomuvvVabNm3S9ddfr8bGRr3jHe/Q7bffXunQAMQY1ep4y+Vy6uvr04oVK0Y3Uuno6Ci7iJAFh4iLIO+tv1TSw2Z2r5l9ofiIOjDET2Njo84991wNDg7K3TU4OKhzzz1XjY2NZc+nzw0AqkdU9+TFixcrmUxqYGBA7q6BgQElk0ktXrx4wrksOERcBEmgNys/9/n9kj5Y8gDGWLt2rTo6OnTrrbfq2Wef1a233qqOjg6tXbt2wrnFPrdMJqPBwUFlMhmlUimSaACogCjvyc8++6x+8YtfKJlMjvnvs88+O+HcVCqltrY2ZbNZDQ8PK5vNqq2tbdIFh0ClTJtAu/tXJf2HpIWFR65wDBgjk8lo3bp12rRpkxYsWKBNmzZp3bp1ZWdAM1gfAKpHlPfkp556Su3t7eru7tbChQvV3d2t9vZ2PfXUUxPOTSQSSqfTo5tyJZNJpdNp+p9RdaZNoM3sckn/Lumtki6X9E0ze0vUgSGeVq5cqVe+8pU65ZRT9MpXvlIrV64sex59bgBQPU7knhxm59nxC8ynm8YBVLsgLRwpSb/l7m9396uU36L776INC9UkaF9cmLcA6XMD4qHcvGZmNdeesPfk4s6zN998swYGBnTzzTdr586dZZPoM844Q52dnXryyfyQrSeffFKdnZ0644wzJpxLex/iIkgCfYq7/0/J8ycDfh1qQJibWZi3AOlzA+KhOAGj9FE6Ug61Iew9+UR2nnX30cdkaO9DXATZSOVLZvZlScWM6QqNG02H2hVmJmeYtwCLX5tMJkfHGk3X5zZ+njRvAQLAzAh7Tz5+/LjWrVs35ti6det0/fXXTzj3qaee0saNG/XFL35RTzzxhBYtWqRrrrlG27Ztm3Au7X2IiyCLCG+QdLuk35R0vqTb3b0j6sBQHcLczMK+BZhIJNTb26uRkRH19vZOu0jE3bW04+5pKxgAgPDC3JMbGxu1c+fOMcd27tw56djSiy++eMy1L7744rLnNTU1afPmzWPaBjdv3kx7H6pOoFYMd/+su29w9791989HHRSqR5ibGW0ZAFAf1q5dqxtuuEEvfelLNWfOHL30pS/VDTfcUHZs6ZIlS3TVVVeNeW246qqrtGTJkgnntrS0qLOzU62trerv71dra6s6OzvH7GIIVIMgUzj+zMy+Z2ZPm9kzZtZvZs/MRnCovDA3M8YPAUB9WLlypV7wghfoySef1PPPP68nn3xSL3jBC8pOXtq+fbtGRkbU2tqqxsZGtba2amRkRNu3b59wbjab1WWXXTZmHOpll12mbDY7Gz8WEFiQCvR2SW9299Pd/YXuvtDdXxh1YKgO2WxWHR0dY+Z3dnR0THozC9uWAQCIn3Q6rb1792poaEjurqGhIe3du7fsYr9EIqEdO3ZowYIFMjMtWLBAO3bsKPv6cOTIER0+fFj79+/X0NCQ9u/fr8OHD+vIkSOz8WMBgQVJoP/b3ener1O5XE7nnnvumGPnnnsuCzoAoI5Ftdhv3rx5uu6668ZM4bjuuus0b968k7ouMNOCTOF4wMz2SNor6XjxoLt/LrKoUDUWL16s9vZ27d69W83NzTp48KDWrFmjxYsXVzo0AECFFBeNl7bzTbZovDgOtaura/R1pK2tTZImVKGHhoaUyWR04YUXjp6byWQ0NDQU7Q8EhBSkAv1CSc9KukTSnxQel0UZFKrL+PFx458DAOpLmEXjYWY7n3feebryyivHrKW58sordd55583GjwUENm0F2t2vmY1AUJ0ee+wx3XXXXWNmg3Z2durqq6+udGgAgBkWdN5+mLnRYdo9UqlU2Wo1G6mg2kxagTaz95jZxH02f/n5i82MSnSNa2pq0iOPPDLm2COPPMJMTgCoQWHm7QddNB5mj4Cw05x6enrGjFlly2/Mlqkq0A9J+qKZDUr6tqQnJM2XtFzSBZL+VdLNkUeIiiqOsevs7NS6deu0c+dOdXR0TNiBCgDO33xgzDbfyzbukySdfmqDDt90Sd3EUC96enqUTqdHK9CpVKpsolts95jpqnKY3mpgpk2aQLv7P0v6ZzNbLun1kl4q6RlJ/yTpWnc/NjshopJKx9jdcMMNampqUkdHh/bu3Vvp0ABUmaePDevRbZdOOF5MYuslhnoQJnkN0+4R5rqlvdWSRnurk8kkCTQiF6QH+nuSvjcLsaAK5XI5HTp0SFu2bBk9Njw8rK1bt87I9YP22wEAqkfY5DWRSARKasNcN6pRekAQgbbyRv0K07t2IsL02wEAqkPY5DVor3KY60b9+gRMhQQaUwozqggAUB/CJK/FtoxMJqPBwUFlMhmlUqmySXSY6/L6hEqatoXDzM5w96dmIxhUnzC9awCA+hBmYWCYtoww1+X1CZUUZCfCb5rZdyR9VNJ+5332uhO0d00KviobqHbjF52dfmpDhSIBqk8ikdD999+vVatW6fjx42psbNTatWtPeg502KQ4zOsTMJOCJNCvkvS/JLVKyhS29b7L3f9vpJEhdhgpFG8Lmzbq1bs2jjsmSRMnGtS60ikOyzbuKzvVAahnPT092rdvn/bv3z/mfr9y5coJ9/sw235LJMWIhyBTOFzSv0j6FzNrUX6M3V+Z2WFJG9396xHHiJhgpFC89ee2TUgU4zD6i0oxMPuiassA4iJID/RLJP25pL+Q9N+SkpK+oPxmKp+WdE6UASI+GCmE2VZM+KkSA7MryrYMIA6CtHB8XdLHJa12976S4w+Y2c5owkIchX2brpaxGxqAWsb9HvUuyBi797j735cmz2b2Vkly987IIkPVCDq/k5FCv1TcDW38ozSpRn1atnHfhAdtJ4ibMPf7MGPsiucHec0BKilIBXqjpE+NO3aj8u0bqHFRbdcK1JJyveLlkmIWJ6JWhLnfh+mXZjE64mLSBNrMVkn6Y0kvM7MPlXzqhZKeizowVIeotmsFagVJMTC1MP3SLEZHXExVgX5M0gOS3izpwZLj/ZL+NsqgUD1YGAgAGC9MpbipqUmbN2/W3r17R6vVq1evLtsvzWsO4mLSHmh3P+zuuyS9wt13lTw+5+4/m8UYUUFhtlUFqh29x8DMKK0UNzQ0jFaKy42ma2lpUWdnp1pbW9Xf36/W1lZ1dnaOWYBYxGsO4mLSBNrMin3Ph8zsuyWPh8zsu7MUHyqMhYGoFcWFnKUfMxEFODFhKsXZbFYdHR3q7u7WwoUL1d3drY6ODmWz2Qnn8pqDuJiqhWN94b+XzUYgqE4sDAQAjBdmjF0ul9OhQ4e0ZcuW0WPDw8PaunXrhHN5zUFcTJpAu/vjhQ9/KumYuz9vZq+S9OuS9s9GcKgOLAwEAJQKs7sgW3mjFgWZA/01SfPN7GWS7pV0jaS7ogwKAIDZcP7mA6NjCIu98edvPlDhqKpfIpFQOp1WMpnU/PnzlUwmJ60Uh23LYA404iDIHGhz92fNrE1Sxt23m9mhqAMDACBqxU2PSpWb642JglaKw7RlMAcacRGkAm1m9ruSrpRUvKsESbxRh6gcAABOVJjpHkAlBUmE1yu/8+Dn3f1hM3u5pIlLZ1H3qBwAAMYL89rAHGjExbQVaHf/mru/2d07C89/4O7vij40xA2VAwDAeGFeG5gDjbiYNoE2s1eZ2e1mdsDM7is+ZiM4xAuVAwCoH0Fb9nK5nPr6+sac29fXV/a1gTnQiIsgLRyflrRT0p2SRqINB3EWdlQRACCewrRlLF68WO3t7dq9e/fouWvWrNHixYsnXJc50IiLIIsIn3P3j7j7v7v7g8VH5JGhagStMlA5AID6ELZlz8ymfF4qkUiot7dXIyMj6u3tJXlGVQpSgf6imf2VpM9LOl486O5PRRYVqkaYKkPx+cUXXzx6bPfu3dz8AKDGlLZlFCvFHR0dZdsyHnvsMd11111jqsqdnZ26+uqrZz9wYIYEqUC/XdINku6X9GDh8UCUQaF6hK0yJBIJubuWdtwtdyd5BoAaVGzLyGQyGhwcVCaTUXt7e9m2jKamJi1ZsmRMVXnJkiW09yHWpq1Au/s5sxEIqhMLAwEA5TzzzDP6oz/6Iw0PD6uhoUENDQ0644wzJpwXZttvIC6CTOE4zczeY2a3F54vN7PLog8N1YCRQgCA8fr6+jQ4OKiXvOQlOuWUU/SSl7xEg4OD6uvrm3BuIpHQ8uXL9cY3vlHz5s3TG9/4Ri1fvpx3KBFrQVo4PippSNLKwvM+SVsiiwhVhYWBAIDxzEzvfOc79fjjj2tkZESPP/643vnOd5ZdHJhMJnXffffplltu0cDAgG655Rbdd999SiaTFYgcmBlBFhG+wt2vMLOEJLn7MZtq+SxqCiOFAADjubv279+vbDY72paxf/9+ufuEc++44w51dnZqw4YNkjT6302bNimTycxq3MBMCZJAD5nZqZJckszsFSqZxoHal0gkSJiBGrKwaaNevWvjuGOSdGlF4kH8NDY26vWvf/2Y4srrX/96Pf744xPOPX78uNatWzfm2Lp163T99dfPVrjAjAvSwnGTpC9JOsvMPiHpXkntkUYFAIhMf26bHnr7Q2Me/bltlQ4LMbJ27Vrt2bNHra2t6u/vV2trq/bs2aO1a9dOOLexsVE7d+4cc2znzp1qbGycrXCBGTdtAu3u/yLpzyRdLalH0kXu/pVowwIAANUqk8lo3bp12rRpkxYsWKBNmzZp3bp1ZVsy1q5dq46ODt1666169tlndeutt6qjo6Nssi0F37wLqKRJWzjM7DXjDhXflznbzM52929HFxYAAKhmt9122+jHx48fn7SfuXh806ZNuv7669XY2Dhpsh1m8y6gkqaqQH+w8PiwpG9Kul3SHYWPPxR9aAAAoFq5+5iNs6ZS3HDF3Uc3Xikn7OZdQKVMmkC7e4u7t0g6Kuk17n6Ru79W0oWSvj9bAQIAgPrA5l2IiyCLCH/d3R8qPnH3XkkXRBcSAACoJUH7mtm8C3ERJIHOmdmdZvYGM/sDM7tDEn8KAgCAafX09Gj9+vUaGBiQu2tgYEDr168vm0SzeRfiIkgCfY2khyWtl/Q3ko4UjgEAAEypvb1dc+bMUXd3t44fP67u7m7NmTNH7e0TJ+ImEgml02klk0nNnz9fyWSSzbtQlabdSMXdByX9Q+EBAAAQWF9fnw4cOKCWlhZJUktLiz72sY/pkksuKXs+m3chDoJUoAEAAAAUBNnKGwAA4IQsWbJEl19+uV70ohfpRz/6kc4++2z9/Oc/15IlSyodGnDCqEDXKXZ6AgDMhtWrV+uZZ57RsWPH5O46duyYnnnmGa1evbrSoQEnbKqdCL8oadLJ6O7+5kgiQuSKK6IXLFggSaMroiV2egKqybKN+yYcO/3UhgpEApy4bDarG2+8UXv37tUTTzyhRYsW6R3veIf27t1b6dCAEzZVC8ctsxYFZlV7e7vmzp2r7u7u0a1Sr7zySrW3t5NAA1Xi0W2Xjn68bOO+Mc+BOMnlcjp06JC2bNkyemx4eFhbt26tYFTAyZk0gXb3r85mIJg95VZE79q1a9IV0QAAnKji5ijF1xyJzVEQf9P2QJvZcjP7jJkdMbMfFB+zERwAAIi3sJujsEYHcRBkEeFHJX1E0nOSWiR9TNLHowwK0VqyZImuuuqqMTezq666ihXRAIAZl0gkdOmll2rVqlWaN2+eVq1apUsvvbRsy2BPT49SqZQymYwGBweVyWSUSqVIolF1giTQp7r7vZLM3Y+6+/skXRxtWIjS9u3bNTIyotbWVjU2Nqq1tVUjIyPavn17pUOraudvPqBlG/eNLuwqfnz+5gMVjgwAqldPT4/27dun/fv3a2hoSPv379e+ffvKJsXpdFpdXV1qaWlRQ0ODWlpa1NXVpXQ6XYHIgckFmQM9aGanSPqemV0n6SeSfiXasBCl4l/96XRaZqYFCxbo5ptvZgHhNJ4+Nlx2IVe5SQkAgLzSpFjSaFKcTCYnvO7kcjk1NzePOdbc3KxcLjdr8QJBBEmg/0bSaZLeJenvlW/jeHuUQSF6bJWKasXoNqC2hEmKm5qatHnzZu3du1e5XE5NTU1avXo1Cw5RdaZMoM1sjqTL3f0GSb+QdM2sRAWgLjG6Dag9YZLilpYWdXZ2qrOzU+vWrdPOnTvV0dGhdevWVSByYHJT9kC7+4ik15qZzVI8AACghhST4tbWVvX396u1tVWdnZ1jxtoVZbNZdXR0qLu7WwsXLlR3d7c6OjqUzWYrEDkwuSAtHIck/bOZfVrSQPGgu38usqgAAEBNyGazuuCCC/Tud79b119/vcxMr33ta8smxWy6grgIkkCfIelJjZ284ZJIoAEAdeP8zQf09LHh0efLNu7T6ac26PBNbEI1lYcfflhz587VLbfcMqYt47nnnptwLpuuIC6CjLG7092vKX1I6oo6MAAAqklxEk/pozShRnlmprVr12rDhg067bTTtGHDBq1du1blukPZdAVxESSBzgQ8BgAAMIa76yMf+YjMbPRxzz33yN0nnBt205X169drYCDfXTowMKD169eTRGNWTNrCYWa/K2mlpDPNbEPJp14oaU7UgaG6lFYKyt30UJ0WNm3Uq3dtHHdMkphuAUSpXLuHpLps+WhsbNRb3vIWfec739HDR3L6jfOadMEFF+i//uu/JpxbuulKc3OzDh48qLa2Nq1cuXJCEt3e3q65c+equ7t79Nwrr7xS7e3tjGlF5KaqQM+T9ALlk+yFJY9nJL0l+tDiI45vIYWN2d21tONukueY6c9t00Nvf2jMoz+3rdJhATWvXLtHvbZ8rF27Vnv27FFra6vO+ptPqbW1VXv27NHatWsnnJtOp7VmzRolk0nNnz9fyWRSa9asKbsTYV9fn3bt2jVm18Jdu3apr69vNn4s1LlJK9Du/lVJXzWzu9z96CzGFCs9PT1KpVLq6uoa89eypKr9CziOMQMA4imTyXd9btq0ScePH9emxkatW7du9HipI0eO6Nlnn53w+vToo4/OctTA1AItIjSzFxWfmNmLzezLEcYUK6VblBb/Au7q6ir713K1CPMXPoD6lm8DevWYx8KmjdN/IVAik8locHBQSzvu1uDgYNnkWZLmzZunlStXjnl9WrlypebNmzfh3CVLluiqq64as+Dwqquu0pIlS6L+cYBAY+wWufvPi0/c/Wdm9isRxhQrYbYorRZHjhzRwMDAmL6x1tZWHT3KGw0AxurPbZuwI2S57daBmTA0NKRPfvKT2r59++jIu/b2dj3//PMTzt2+fbvWr18/+vq1dOlSjYyM6NZbb61A5Kg3QSrQz5vZ2cUnZrZU+TnQ0C9nVpaq9pmV8+bNUzKZHFM1TyaTZf/CBwBE6/zNB7Rs477RP0yKH5+/+UCFI5t98+bN09ve9rYxOxG+7W1vK/v6lEgktGPHDi1YsEBmpgULFmjHjh20ImJWBKlApyQdNLOvFp7/vqRrowspXoozK8f3a1VzO8TQ0JBuu+02XXjhhaMx33bbbRoaGqp0aABQd4oLDserx0r/0NCQ7r///gmvqZO9PiUSCRJmVMS0CbS7f8nMXiPpdySZpL91959GHllMFP+Pm0wmlcvl1NTUpHQ6XdX/hz7vvPO0evXqMTGvWbNGe/furXRoAIA6xusT4mLaFg7LDwB+k6TXuPsXJZ1mZq+LPLIYSSQS6u3t1cjIiHp7e6s6eZbyVfPdu3ePLurIZDLavXv3pDs9AQAwG3h9QlwEaeH4R0nPS7pY0vsl9Uv6rKTfijAuRCiRSOj+++/XqlWrdPz4cTU2Nmrt2rVVn/gDAGpbHN/VRX0Ksojwt939ryUNSvkpHMpvsoKYKt3paWhoSPv379e+fftisQEMAKC2xe1dXdSnIAn0sJnNUWHyhpmdqXxFGjEVx9nVAACMF8edgFEbgrRwfEjS5yX9qpmlld/G+z2RRoVIxXF2NYDpjZ/acPqpDRWKBDhxPT09SqfToy0cqVSqbBWaXXVRSUGmcHzCzB6U9MbCodXuHijTMrM3SdohaY6kO9192yTnvUXSpyX9lrs/EChynLDi7OqWlpbRY9U+uxrA1Ipj0JZt3Fd2JBoQB2GS4tJ3UyWNvpuaTCZJoBG5IC0cknSa8knwKZJODfIFhbaPD0taJek8SQkzO6/MeQslvUvSNwPGEmvV8HZTcXZ16fanbW1trHJGZIobQ5Q+qI4CGC9MiyHvpqKSpq1Am9l7Jb1V+ckbJumjZvZpd98yzZe+TtL33f0Hhet8UtKfSjoy7ry/l7Rd0rtDxh471fJ2E6ucMZtKq6FURwFMJUxSzLupqKQgFeiE8q0V73P3m5TfUOXKAF/3Mkk/LnneVzg2yswulHSWu98dMN5Yq6bFe6xyBgBUm2JSXGqypJh3U1FJQRYRPippvgpj7CQ1SvrPAF9nZY756CfNTpH0D5KunvZCZteqsH342WefHeBbVyfebgIAYHLFpHj8O7XlCk28m4pKCpJAH5f0sJn9i/IJ8B9KOmhmH5Ikd3/XJF/XJ+mskudLJD1W8nyhpBWSvpLf7FC/JukLZvbm8QsJ3f12SbdL0kUXXeSKKd5uQi0ZP/FBYuoDgJMTNilOJBIkzKiIIAn05wuPoq8EvPa3JC03s3Mk/UTS2yStKX7S3Z+WtKj43My+IundtTyFI8xf1kA1o68ZQFRIihEHQcbY7Sp+bGYvVr5n+bsBvu45M7tO0peVn+DR7e4Pm9n7JT3g7l84ibhjibebAACYOUFnRgMzLcgUjq9IenPh3O9IesLMvuruG6b7Wne/R9I94469d5Jz3xAg3tjjL2sAAE5etUy2Qn0K0sJxurs/Y2bvkPRRd7/JzKatQAMA6svCpo169a6NZY5LEm0+mFlspIJKCjLGbq6ZvVTS5ZLqYtxctaiGTVcAIKj+3DY99PaHJjz6c2U3oQVOCpOtUElBKtDvV76P+aC7f8vMXi7pe9GGBd6amh3nbz6gp48Njz4vTpY4/dQGHb7pkkqFBQBlcc/6JSZboZKCLCL8tKRPlzz/gaT/HWVQ4K2p2fL0seGyEyTKjWgDgEoLc8+Ka7JdGG07yr389FomW6GSglSgUQFRvzXFymUAqG1xLRAUE+bpRmQy2QqVRAJdpaJ8a4r2EABALWCyFSplykWEZnaKmV0+W8Hgl4pvTWWzWQ0PDyubzaqtrU2pVGrSrwm66LC0PaShoWG0PYS3vQAAAKY3ZQXa3Z8vbIbyqVmKBwVh35oKU1Vm5TIAAMCJCzLG7l/MdV5C7QAAIABJREFU7N1mdpaZnVF8RB4ZlEgk1Nvbq5GREfX29k75NlWYqnKxPaQUK5cBAACCCZJAt0r6a0lfk/Rg4fFAlEEhvDBV5RNpDwEAAEBekDF258xGIDg5YRYdsnIZAADgxE2bQJvZaZI2SDrb3a81s+WSznV3diWsImHnYbJyOb7KbZfMVskAAMyeIGPsPqp828bKwvM+5TdWIYGuIlSV60d/btuE2ajVPtcVAIBaEqQH+hXuvl3SsCS5+zFJNvWXoBLCLDoMOvIOAAAAYwWpQA+Z2amSXJLM7BWSjkcaFSLFRioAAAAnLkgF+n2SviTpLDP7hKR7JbVHGRSixUYqAAAAJy7IFI4DZvagpN9RvnVjvbv/NPLIEBk2UgEAADhx01agzezjkv5M0n+6+90kz/HHRioAgFrAeh5UStApHM2SMmb2cknfkfQ1d98RaWSITCqV0hVXXKEFCxbo6NGjWrp0qQYGBrRjB/+kAIB4YD0PKmnaCrS73ycpLenvJN0p6SJJfxlxXIhYf3+/Hn30Ubm7Hn30UfX391c6JAAAAmM9DyopyEYq90paIOnrkv5N0m+5+/9EHRiic91112l4eFgf/OAHtW7dOu3cuVPt7e267rrrauKv9vM3H9DTx4ZHny/buE+nn9qgwzddUsGo4mH8POnTT22oUCSodeU2BMofl9gUCEGwngeVFKSF47uSXitphaSnJf3czL5emAeNGHrqqae0fft2bdiwQZK0YcMGjYyMqL29NoarPH1smI1GTkDp72zZxn0TfofATCq3IZDE/1cRXHE9T0tLy+gx1vNgtgSZwvG3kmRmL5B0jfI90b8mqTHa0BClFStWTPkcQG3j3QbEXSqVUltb24QeaFo4MBuCtHBcJ+n3lK9CH5XUrXwrB2Jq7ty5uvLKK/XZz3529KZz5ZVXau7cIG9IAIi7YuWXdxoQZ4lEQvfff79WrVql48ePq7GxUWvXrq2JVkRUvyAbqZz6/9q7++imzvxO4N8H25IdY97Cy8SYl5x2JpUxQ2jTySzx2cbZYuq2A2Q7CWOYhqxdwFAU2niwDTozs/SMg+2ZcGZXhDhhrCXpgkpeNi5bjxdnB3VSw04nbZgEg1IyU4JjXgPmxcjIsq1n/7ClSNaV0bV9pXul7+ccHazLw9VjY0k//e7v+T0A9gD4HSnlf5JS7hpeWEgGVVFRgVu3bqG0tBQmkwmlpaW4desWKioqEj01IiKimDidTrS0tKC1tRU+nw+tra1oaWlhKzuKi1i6cPwQgBdAhRBiqxBiifbTIi3Z7XZs2bIFN2/eBADcvHkTW7Zsgd1uT/DMiIiIYqO2Cwd7RtNEimUjlecAHAQwe/j2P4UQVq0nRuqpeXGw2+3wer2QUsLr9TJ4JiIiQ1HThSPQMzrw3me322Gz2RhE05jFUsLxFwAelVJ+T0r5PQxt6b1B22mRWnxxICKiVKJmV132jKaJFsuqMQFgMOT+4PAx0pHQFwcAwRcHq9XKBRVERJR0QnfV7ezsxPz586Puqsue0TTRYt3K+5+FEO8M318NoEm7KdFYJPuLQ+jmKIH2W9wchYiIAEBKOerfs2c0TbRYFhHuwVD/524ANwD8Fynlj7WeGKmj5lKWEQU2Rwm9he42SEREqaW2thYbN25EdnY2hBDIzs7Gxo0bFcsyAj2jXS4X+vv74XK5UF5eDpvNloCZUzKImoEWQmQCqADw2wBOAdgnpRyI18SSldPpRG1tLdxuNywWC2w224SUWLChPBERpZIzZ87A4/HA4XAE3/fKyspw/vz5iLGB91mr1Rp8/62trWWJI43ZaCUcrwHox9CmKSUALAD+Kh6TSlaBhX4jg1wA434S88WBiIhSiclkwmOPPRb2vvfYY4/h0qVLiuNLS0v5nkgTZrQAOl9KuRgAhBBNAH4ZnyklL60X+vHFgYiIxspoa036+vpw+PBh1NfXo6KiAo2NjaiursbAAC+Wk/ZGC6CDBaZSygEh2HhjvJJ9oR8RUaLlWGqw+LUaheMAwG3LRxNYaxIqEEjrkdlsxje/+U04HA5s374dFosFa9aswVtvvZXoqVEKGC2AXiKEuD38tQCQNXxfAJBSyimazy7JcBUwEZG2etx1EUEgoO9AkMbG5/Ph+PHjETXQPp8v0VOjFBC1C4eUMk1KOWX4liOlTA/5msHzGOhpFTC3NCUiIiPLz8/Hww8/jJKSEphMJpSUlODhhx9Gfn5+oqdGKSCWPtA0QfSy0E/LxYxERETxUFRUhH379mHWrFm4cuUKpk2bhiNHjmDLli2JnhqlgFi28qYJVFpaio6ODgwODqKjo2PUgFWrLDG3NCUiIqNrbm5GTk4OsrKyMGnSJGRlZSEnJwfNzc2JnhqlAGago9CqX7Oax9cqS8zFjERkJHpZGKg0Dy5OTJyuri60tbVh+fLlwWPvvvsuiov12TWEkgsDaAV6KHHQsuUdFzMSkZHoZWGg0jy4OJEoNbGEQ4EeShzGkiW2Wq3IzMyEEAKZmZmwWq2K4/S0mJECWa3FEbccS2TGjYiIhuTl5eHpp5/Ggw8+iEmTJuHBBx/E008/jby8vERPjVIAM9AK9FDioDZLbLVa0djYGNFQHgDsdnvYWL0sZqQhesmuEaUilmUY1+rVq7Fv375g4sjr9eL27dv49re/neipUQpgAK1ADyUOgSzxyDKSaFnw/fv3o76+Hs8//zwABP/cuXNnRAANcNdCremlZpOIRseyDONyuVzYsWMHmpubcfXqVdx///0oLy/nIkKKCwbQCtQGr1pQmyXu6+vD9OnTUVBQEBxfWVmJvr6+uM1ZjdAtYwFjbBurBrPKRETacrvdOHnyJH7wgx8Ej/X392P37t0JnBWlCgbQCvRS4qAmS5yeno7Kykq8/fbbwaD/z/7sz5Cers//YqUtYwEGmFoY+TOdmpWRoJkQEU0ctVeLE91di5KLPqMrHTBaicOUKVNw69YtnDx5Eo8++ihOnjyJ27dvY+rUqYmeGiVQ6IeUhTUtih9aiIiMSM3VYj1016LkwgA6Sdy8eRObNm3Czp07UVlZCbPZjI0bN+KVV15J9NSIiIgmnJqrxbW1tVi7dm3Y2LVr13IBPY0ZA+gkYbFY8NRTT2Hfvn3BYy6XC++9914CZ0VERKSdWK8WnzlzBh6PBw6HI5iBLisrw/nz5+MwS0pG7AOdJNjbmYiISJnJZILVag3b38FqtcJkMiV6amRQzEAnCb0sfCQiItIbn8+HvXv3YunSpcEM9N69e+Hz+RI9NTIoBtBJxGgLH4mIiOIhPz8fq1evjqiBZs9oGiuWcBAREVFSs9lsOHToEOx2O7xeL+x2Ow4dOsQyRxozZqB1jD0riYiMibuR6ktpaSlOnDiBkpIS9PX1wWw2Y8OGDXxPpTFjAK1T7FkZH2re5PiGSKmKm/Gox91I9cXpdOLw4cN44IEH0NnZiQceeACHDx/GsmXL+J5KY8IAWqdqa2vR1NQU3GGpqKgITU1NsFqtE/JkF0KE3ZdSjvucRqTmTY5viJSKuBkPJYOqqiqkp6eHtbFbt24dqqqqGEDTmDCA1im3243CwsKwY4WFhXC73RNy/kDAzDdEIqLE4tUt7XV1daGtrS0sKfXaa6+huLg4wTMjo2IArVMWiwXt7e3BJzsAtLe3w2KxJHBWREQ00Xh1i8h42IVDp7gxChER0b0JIYK3aPLy8vDMM8+Evac+88wzyMvLi+NMKZkwA61T3BiFiIj0asmuNty62x+8v7CmBVOzMvDh9+NfEiGlvGc5YkNDA7Zt2xbcvnvBggUYHBzEnj174jhTSiYMoHXMaBujKL2gAkjYiyoREWnj1t3+iIBVzyUngTZ2+/fvh5QSly5dYhs7GheWcEwAp9OJgoICpKWloaCgAE6nU9fn1UrgBXXkLTSoJiIiijen04mWlha0trbC5/OhtbUVLS0tun9fJf1iAD1OgX7Nobsb2Wy2cT8pnU4nKioqcPbsWfj9fpw9exYVFRV8shMREakU2ho2IyMj2Bq2trY20VMjg2IAPU5qn5SxZpW3bt2KO3fuoK6uDh6PB3V1dbhz5w62bt2q5beTFIZaQi0Ou+VYIltEERFRatC6NSylHtZAj5OaJ6Wa3QW7u7tRWloKh8OB7du3w2KxYM2aNcxAx0CpJZSea/OIiEhbFosFu3btQnNzc3Bh/urVq9kalsaMGehxCvRrDhWtX7PabPWxY8fCSkOOHTumyfdARETGoHSFjVfZ7q2oqAj19fUoKytDT08PysrKUF9fH7bXApEazECPU6Bf88isslJQrPYSUm9v76j3iYj0Rulqz9SsjATMJDlx05WxcblcqK6uDruqW11djebm5kRPjQyKAfQ4qenXrPYSksfjwdq1a3H16lXMnj0bHo9n1LmMbCIf2K6biCgeQgO7e/XlJYont9uN6urqsGMPPfQQa6BpzFjCMQFKS0vR0dGBwcFBdHR0RO0rqeYS0qJFi7By5UrcuHEDfr8fN27cwMqVK7Fo0aKo85BSQkqJBdX/wOCZiIhoWG5uLqqrq8PKIqurq5Gbm5voqZFBMYCOo9BLSDk5OXA4HKiurobL5YoYa7PZ8OGHH4b1rPzwww+5lTcREdEY9Pb2oqysDJmZmSgrK2NZJI0LSzjiyO124+TJk/jBD34QPNbf34/du3dHjA3smlRSUoK+vj6YzeaU3jVpaOFMzYhjAMBLxERENLoLFy5g5syZAL4obzSZTLhw4UIip0UGxgx0HKnp2MFdk8L1uOtwav2psFuPuy7R0yIiIgMwmUyoqanBuXPn4Pf7ce7cOdTU1MBkMiV6amRQzEDHkZqOHaEt7wAEW95ZrdaUzUITEVHslK7cDR0HUu3qnc/ng91ux9KlS4Pvv3a7HT6fL9FTI4NiAB1Hajp2cNckGs3IllVsE0ZEI7Hl3Rfy8/OxevXqsPffdevWsY0djRkD6DgrLS2NKYMcKPcI7dARrdyDUkvgDZFtwoiIYmOz2RR3Ao62kRnRvaRUDbTT6URBQQHS0tJQUFCg63riQLmHy+VCf38/XC4XysvL2YWDiIhIpdLSUtTW1sJqtSIzMxNWqzXqFWCiWKRMBtrpdCp++gSgyyeQmnIPIiIiGl2sV4CJYpEyAbQRF+XxyU5ERESkPykTQHNR3tgs2dWGW3f7g/cDi0+mZmXgw+8XJ2paRERERAmTMgG0XhblOZ1O1NbWBssybDabrrPMt+72cxU3ERGNmVIiJlFJGCFE2P3ApipEaqVMAK2mB7NWxlKHzSc7EREZmVIiJlFJGCklOxjRhEiZAFoPi/LGUofNJzsRERGRvqRMAA0kflEe67C/wB2yiIiIyKhSKoBONL3UYesBd8giItIXpcQGkxpEyhhAx5Ee6rCJiIiUKCU2mNQgUsYAOo70UIdNREREROPDADrOEl2HTUSkF0rZzalZGQmYCRGROgygiYgo7kJLBdhpiIiMZlKiJ0BEREREZCQMoImIiIiIVNA0gBZC/JEQ4t+EEL8WQkQ0/RVCPC+EOCOE+EgI8TMhxAIt50NERERENF6a1UALIdIAvARgOYAuAO8LIY5IKc+EDDsJ4BEpZa8QYjOABgBrtJqTGk6nE7W1tcFuGTabjYv/SDNcTEVERGQcWmagvwbg11LKf5dS+gD8HYBVoQOklC4pZe/w3V8AyNNwPjFzOp2w2Wyw2+3wer2w2+2w2WxwOp2JnholoU/r/iR4C73/4feLEzwzIqLU5HQ6UVBQgLS0NBQUFPD9nyJoGUDPBfBZyP2u4WPRlANo1XA+MautrUVTUxOKioqQkZGBoqIiNDU1ccMTIiKiJMckGsVCyzZ2QuGYVBwoxLcBPALgD6L8/UYAGwFg/vz5EzW/qNxuNwoLC8OOFRYWwu12a/7YREREqWrJrjbcutsfvB8ob5ualRG3q3KhSTQAwSSa1WplKScFaRlAdwGYF3I/D8DFkYOEEH8IwAbgD6SUfUonklK+CuBVAHjkkUcUg/CJZLFY0N7eHnzyAEB7ezssFovWD01ERJSybt3tV+wJHs8txZlEo1hoGUC/D+DLQogHAVwA8C0Aa0MHCCGWAngFwB9JKa9qOBdVbDYbysvL0dTUhMLCQrS3t6O8vJwlHKQKFwYSERkPk2gUC80CaCnlgBBiK4CjANIAOKSUp4UQfwPgX6SURwD8EMBkAG8KIQCgU0q5Uqs5xSpwicZqtQa7cNTW1vLSDcWMu6wRERkTk2gUC0238pZS/hTAT0cc+17I13+o5eOPR2lpKQNmIiKiFMMkGsVC0wCalA1n24Ok1Lysm4iIiGLEJBrdC7fyTgApJRZU/wOklAyeiYiIiAyGGWgiIqIE46JjfeFuxHQvDKCJiIgSiIuO9SWwkcrIRYQAGERTEANomjA5lhosfq1G4TgA8A2BiIj0jxupUCwYQE8AXuoZ0uOuS3gDfCJKTixxoHjhRioUCwbQ48RLPURE2mKJg/4oXXFMlquN3EiFYsEuHOMUeqknIyMjeKmHDdeJiChZ9bjrcGr9qbBbj7su0dOaEIGNVFwuF/r7++FyuVBeXg6bzZboqZGOMAM9TrzUY3y8NExEsRr5ejHaawVfW4yJG6lQLBhARxFrXbPFYsGuXbvQ3NwcHLt69Wpe6jEIXhomolipeb3ga4uxcSMVupeUKuFwOp0oKChAWloaCgoK4HQ6o47btm0bPB4PpJTweDzYtm2b4viioiLs3r0b169fBwBcv34du3fvDqud0pslu9qwsKYlmB0JfL1kV1uCZ0ZERESkfykTQAcW+9ntdni9XtjtdthsNsWguKqqCmlpaXA4HOjr64PD4UBaWhqqqqoixjY3N2PKlCnIzMyElBKZmZmYMmUKmpub4/Ftjcmtu/34tO5PIm637vYnempEREREupcyAbSaxX5dXV14/fXXw8a+/vrr6OrqUhz7xhtv4Ny5c/D7/Th37hzeeOMNxbEUP4GseuDGukMiIopVrFesKXWlTA202+1GV1cXCgoKgrXK1dXVXOyXhLSsPeSiICJKNL4OaStQxpmdnQ0AwTJOgO1p6QspE0Dn5uaiuroaBw8eDPZrXrduHXJzcyPG5uXlYf369WFj169fj7y8PMWxzzzzDA4dOhQc+8wzzyiOJWPjoiAiSjS+DmmvqqoK6enpcDgcYfFCVVUVA2gKSpkAGgCklKPeD2hoaMC2bdtQVlaGzs5OzJ8/HwMDA3jxxRdHHXv+/HksWLAAg4OD2LNnjybfAxERTSw1reko+XV1daGtrS1sK+/XXnsNxcXFCZ4Z6UnKBNAXL17EgQMHwvo6NjQ04Nlnn40YW1paihMnTmD//v3w+/24dOkSNmzYoPjJM3CstrYWQghkZ2fjhRde4KdUIiIDCGRwkzWby3IPIm2kTABtsViQl5eHjo6O4DGXy6XYr9npdKKlpQWtra1h23MvW7ZMMTA+cOAAzpw5Ayklzpw5gwMHDjCAJiKihBpLuQez8SzNpNikTAAd2JqzqakpLChW6sIR2rEDQLBjh9VqjQiMV6xYgba2NkyfPh03btzAtGnT0NbWhhUrVuDo0aNx+d6Aod7OoW3oAp0nPvw+LzkRUWph1nVsjJaNV3rfAzDu976GhgZUVFRgxYoV6O/vR0ZGBrKystDY2DjuOVPySJkAWs3WnGq2525ra0NOTg7efvvtYGC+atUqtLXFd1OSQG/nUEpvImrlWGqw+LUaheMAoP8XWCJKLVxklzqU3veAiXnvM5vNmDFjBjo7OzF37lx4PJ5xn5OSS8oE0EDsW3Oq3Z774MGDYdnqgwcPYuXKlRM690Tpcddp9gJFRESkN7W1tTh8+HDYjsIul0vxKjSlrpTZSEWNoqIi1NfXo6ysDD09PSgrK0N9fX3U7bl//OMfhzVc//GPfxznGRMREenT0JXMxWG3HEvklU29CN03IvC+3tXVxX0jKExKZaBj5XK5UF1dDYfDge3btwc3XVHanttsNuPYsWOYPHky/H4/zp8/j9OnT8NsNidg5kRERPqidCVTz1cx1ewbQanL8BloLbbbdLvdeOihh8KOPfTQQ4qfPgM7Fd25cyfsz8BxIiIiMpZY942g1GXoANrpdMJms8Fut8Pr9cJut8Nms407iM7NzUVVVVXYeauqqhQ/fXZ3d2PHjh1YtGgRJk2ahEWLFmHHjh3o7u4e1xyIiIgo/i5evIgnn3wSJSUlMJlMKCkpwZNPPomLFy8memqkI4YOoEPbzWVkZATbzSm1plNLCDHq/VBFRUXo6OjA4OAgOjo6otZKExERkb7l5ubinXfeQWtrK3w+H1pbW/HOO++whIPCGDqA1qrQ/+LFi1i9enXYp8/Vq1crfvrMy8vD+vXr4XK50N/fD5fLhfXr17PhOhERkUF5vV6UlZXBbDajrKwMXq830VMinTF0AK2m1ELteWP99NnQ0ICBgQGUlZUhMzMTZWVlGBgYQENDw7jmQERERPF34cIFZGQMbbwTuPqckZGBCxcuJHJapDOGDqABdaUWahYc3r59GytWrIDJZMKKFStw+/ZtxXGlpaVYs2YNLl26BL/fj0uXLmHNmjUT0ityya624ErlhTUtWFjTgiW74rtBi54EfgaBG3cWIyKiiWYymVBTU4Nz585hcHAQ586dQ01NDUwmU6KnRjpi6DZ2Fy9exIEDB8J2F6yvr8ezzz4bMdbpdGLTpk3wer3w+/04e/YsNm3aBAARwW5XVxcmTZqEWbNm4erVq5gxYwY+//xzdHV1KZ738OHDeOCBB3D+/Hk88MADOHz4MJYtWzbuIFqr3QWNyGhbzBIRkTH5fD7Y7XYsXbo02MbObrfD5/MlemqkI4bOQFssFuTl5YUt4MvLy1PcMXDr1q3o7e1FXV0dPB4P6urq0Nvbi61bt0aMFUJg06ZNuHz5Mvx+Py5fvoxNmzYpZrerqqqQlpYGh8OBvr4+OBwOpKWloaqqSpPvOZmMzCgzq0xERImWn5+PdevW4YknnoDJZMITTzyBTz/9FPn5+YmeGumIoTPQNpsN5eXlaGpqCn5KLC8vV+zC0d3djWXLlmHnzp2orKyE2WzGo48+ihMnTkSMlVLijTfeQGtrKzo7OzF//nz09PQo9oHs6upCW1tb2Fber7/+OoqLiyf+G04ioVlkZpWJiIxn5BXRZEmA2Gw22Gw2HDt2DM/+9DYO/PEUlJeXw2azJXpqpCOGDqADJRKhJRy1tbVRSydOnDiBF198ERUVFWhsbERlZaXiuPT0dHi9XuTk5ASDZq/Xi/R0Q/+4iIiIJkQyJ0FCY4vOM25YW0ePLSg1GbqEAxj6RQ8t4RjtFzwrKwtLly5FRkYGli5diqysLMVxU6ZMgdfrhdVqxZ07d2C1WuH1ejFlypSIsYE2dkKI4K24uJht7IiIiAwqEFssqDpyz9iCUpPhA2g1nTW8Xi+WL18Ok8mE5cuXR+3rePPmTWzcuBE7d+5EdnY2du7ciY0bN+LmzZsRYwNt7BYuXAiISVi4cCFmzZrFNnZEREQq5VhqsPi1xRG3HEtNoqdGFMbQNQmBrbxH1kADkZ01AuUXAwMDAIDBwcGoJRkWiwVPPfUU9u3bFzzmcrnw3nvvRYwNPE6g7jo7OxsvvPACP60SERGp1OOuUywHGW8HqiW72nDrbn/E+aZmZeDD73PNEqln6Ay0mq28zWYzBgYGsHnzZty8eRObN2/GwMAAzGZzxNjA4sTQ3QVHW0DASz1ERET6FWgLO/IWGlQTqWHoAFrNVt4ejwcrV66Ew+HAtGnT4HA4sHLlSng8noixpaWlqK2thdVqRWZmJqxWKxcQEBEREREAgwfQubm5eO655+DxeCClhMfjwXPPPTfurbyBoSD69OnT8Pv9OH36NINnIiIiIgJg8Bro3t5e3L59G9/97neDrem2b9+OSZMiPxdkZ2fjyJEj2Lx5M3bv3o0dO3bg5ZdfRnZ2dtTzSymTrj0PEFikEbkgI8cCAOP7XpXq1JKlNygRERERYPAAuru7GzU1NXA4HNi+fTssFguqqqpQV1cXMbavrw+TJ09Ga2srGhsbsWDBAkyePDlqJ45kptUijWTuC0pEREQUYOgSDgAR22srbbcNDHXfsNvtyM7OhhAC2dnZsNvtwa4cRqfU+odtf4iIiPRFTftd0i9DZ6BnzJiBhoYGNDQ0BEs4qqqqMGPGjIixZrMZ3d3d6OjoCB7bs2ePYhcOI1LKKo83o0xEREQTR037XdI3Q2eg77vvPphMJtTU1CA7Oxs1NTUwmUy47777IsZu2LAB1dXV2LNnD3p7e7Fnzx5UV1djw4YNCZg5ERERpRo17XdJ3wydgb5w4QLuv/9+TJ48GZ2dnZg7dy7u3LmDCxcuRIy12+04e/YsvvOd76CyshJCCCxfvhx2uz0BMyciIqLx0HJBvFbcbjcKCwvDjhUWFiq23yV9M3QG2mQyYceOHTh37hwGBwdx7tw57NixAyaTKWKs0+nEJ598gp/97Gfw+Xz42c9+hk8++STutUdLdrUFSysW1rRgYU0Lluxqi+sciIiIjK7HXYdT609F3HrckY0E9MJisaC9vT3sWHt7OywWS4JmRGNl6Ay0z+fD3r17sXTp0mAt0d69e+Hz+SLGhl42ARC8bGK1WuNadxTYDSmU3muV2ZqOiIho/AI7HY+sgWYJh/EYOoDOz8/H6tWrYbVa4Xa7YbFYsHbtWjQ3N0eMdbvdeOKJJ8KO+Xw+Xja5B7amIyKi8RqZiEnVJEwgYRcat3CnY2MydABts9kUV7MqfZKzWCyw2+0oKioKBoIul4uXTYiIiDTEREy40tJSBsxJwNABdGlpKU6cOIGSkhL09fXBbDZjw4YNir+YoZdN5OAAXC6X7i+bKC2Q0PPiCKJkEtpTXtQP7UxKREQEGHwRodPpREtLC1pbW+Hz+dDa2oqWlhbFhYGlpaWora2F1WpF54tv69EcAAAWoUlEQVT/GVarVfeXTZQWSOh5cQRRMpFSht2IiJRwY5TUZOgAWm0/xdLSUnR0dGBB1RF0dHToOngmIiIifQtsjGK32+H1emG322Gz2RhEpwBDB9ButxtdXV1hn/y6urq4MJCIiIg0N5aNUZixTg6GDqBzc3Px3HPPwePxQEoJj8eD5557Drm5uYmeGhERESU5t9uNN998E5mZmRBCIDMzE2+++WbURB4z1snD0IsIe3t7cfv2bXz3u99FRUUFGhsbsX37dkyaZOjPBWOmpk0QezsTERGNz7Rp0/DKK6/ghz/8YVgcMm3aNMXxetmTgsbP0AF0d3c3fvd3fzdse+6lS5figw8+SPTU4k5NmyC2FCIiolSi1bbft2/fxrRp07B06VJkZGRg6dKlmDZtGm7fvq04nlt5Jw/Dp2o/+OCD4Ap5KWVKBs9EREQUnVbbfg8MDODFF1+E1WpFZmYmrFYrXnzxRQwMDCiOV7uVN+ul9cvwATQArFy5Ep9//jlWrlyZ6KkQERFRijCbzeju7kZHRwcGBwfR0dGB7u5umM1mxfGBPSlcLhf6+/uDe1LYbLaIsayX1jdDl3AAgMlkwkcffYQ5c+Zg/vz5MJlM8Pl8iZ4WERERJbkNGzaguroaAII10NXV1aioqFAcr2Yrb9ZL65vhA+hVq1bhzJkzAIDs7GysWrUKb775ZoJnRURERMnObrcDAHbu3InKykqYzWZUVFQEjyuJdStv1kvrm+ED6Lfeegs/+tGPgp/8vvOd7yR6SkRERDRGeugStWRXG27d7Q+bz9SsDHz4/eK4zSFQLx3IQAOj10tTfBk6gC4uLkZbWxsqKytRWVkZdjxZqGlNR0REZGR66RJ1625/xGMrBfZWqxWNjY2or68PK+EAMGoWOhaBeummpiYUFhaivb0d5eXlo27SQvFj6AD66NGjWLFiBd59911IKSGEwPLly3H06NG4zSH0UyowsZ9UA09etpqjeBFCfPF1PYIdboiI9CjR2er9+/ejvr4ezz//PAAE/9y5c+e4A2g19dIUf4YOoAEEg+VEBZlKn1ID81Gi1ItyvH0oiSYKA2YiMgo9ZKv7+voiFgxWVFSEXRUfj1jrpSn+DB9AG02Puy6my0JERGoFriCI+qH7/EBEpC2z2YzGxsZg5hkAGhsbo7axo+TBAFqBlmUZRERaYcBMFF9q29hR8mAArUBtWQYRTSxmUonICOx2O/7+7/8+rJnBvHnzxl3/TPqXFDsRElFykVKG3YiI9GjFihX47LPPMH36dAghMH36dHz22WdYsWJF1H/D7bmTAwNoIiIiojFoa2sDANy4cQNSSty4cSPs+Ehqt+dmsK1fDKCJaEyEEBBC4Hz9n4a1v0vEPAJzSOQ8iCh1LVu2DBcvXsSyZctGHVdbW4u1a9fCarUiMzMTVqsVa9euVezt7HQ6UVFRgbNnz8Lv9+Ps2bOoqKiIexCtlyBeq3mM9bwpUwPNhYGUqrTq7ayX0go9zMOI/bNZZ040MebMmYPjx48DAI4fP44vfelLuHLliuLYM2fO4OrVq8jOzoaUEh6PB6+++iquXbsWMXbr1q3o6enBnDlzcPXqVdx///24cuUKtm7dGrfWdoGM+cjNXADEtb2eVvMYz3lTJgMdWBg48hYaVBMlI9YTa8+IP2Ot5qyXKxNE8XLlyhVs2bIFt27dwpYtW6IGzwCQlpaGgYEBOBwO9PX1weFwYGBgAGlpaRFju7u7MW3aNBw6dAherxeHDh3CtGnT0N3dreW3E6a2thZNTU0oKipCRkYGioqK0NTUFPfdELWax3jOmzIZaK0obYwydBzg5ihElGqM8gGCUo+aXQvVbHomhMDLL7+Ml19++Z5zGBgYgN/vR1lZGc6fP48FCxbA7/djYGBAcXxxcXHYToTFxcU4fPiw4lin04na2trgWJvNNu4ssdvtRmFhYdixwsJCuN3uuM0hMI+uri4UFBQEz11dXR11HmrOq+b7C8UAepyUNkYB2PKOiIhIL9TuWhjrpmfz5s3DZ599hqysLNz1epGVmYm7d+9i3rx595xTLFdoDh8+jLS0NPj9fnz88cc4ffq04jin04lt27YhOzsbAODxeLBt2zYA4ytxsFgsePrpp9Ha2oq+vj6YzWaUlJTAYrEozkGrco/c3FxUVVXh0KFDwXOvXbsWubm5iuNjDeQtFgva29tRVFQUPNbe3q74/Y2UMiUcREQ0NizLIFLW2dmJefPm4e7du4CUweC5s7NTcXx6ejrS0tLgcDjg9XrhcDiQlpaG9PTIfGbguTY4OBj2p9JzsKqqCunp6WHnTU9PR1VVleI8AosYhRDBxYxK5s6di+bmZpSVleHmzZsoKytDc3Mz5s6dGzF2LOUQahbwjfy+o70Wqel0YrPZUF5eDpfLhf7+frhcLpSXl8Nms0WdRwAz0Akw8lNstEtIRER6wLKMLxhxwShpKxAsx5LZHhwcRHd3N5544ongsZkzZwaD41DRfreUjnd1daGmpias3GP9+vWoq6uLGGu1WrFv3z7Mnj0bV69exfTp07Fv3z4AiNgA5uc//znWrVuH9957DzNmzIDFYsG6devw1ltvRZxXbZlFaNY8sKAyWtb84sWL2LRpE0pKSoKZ8LKyMrzyyisR5w3tdBKYR6DTycjzBu6HjlUap4QBdJwFnlyxPNGIomEHBaLEUPNc0zLYDn0N4PPfOPLz87F69Wo0Nzfj9Bk3FuVbgvejmT59Om7duoWpU6cG+0wrOXDgQESJg5LGxkZkZGTg+vXr8Pv9uH79OjIyMtDY2BgRQPf19eHVV1/FfffdFzzW29uLgwcPRpxXbZlFVVVVMBsfOr6qqioigM3NzUVzczNaW1uDY9etW6d47jNnzsDj8YSdN1BzrqS0tHRMJSaGDqCVWtNNRFs6LgykRFATFPMNk2jiaPWBVMvnKV8DjMlmswXrhJ/96W3Y/3gKysvLo5Y5pKen4+233w4GgsXFxYoLDtPT09HX1xd2rK+vT7E0ZGBgAIODg5g0aaiKN7CIUel3ymw247d+67dw+fLl4LEvfelLMJvNivP1er1hCyS9Xi8mT56sOLarqwttbW3B+uOioiK8/vrrKC5WjuF6e3tRVlaGzs5OzJ8/H729vcjJyYkYZzKZ8Nhjj4VllR977DFcunRJ8bxjZegAOtCaLtRELN7jwkBKBL4hEiUGn3sUL6ElA51n3LC2jl4yMDAwgNLSUly5cgVz5syJ2q1jcHAQ6enpYcFrenq6YmkIMPQ739DQgIqKCjQ2NqKyslJxXHZ2Ni5fvoyMjAz09/cjIyMDly9fxowZMyLGXrhwAffffz+ALz6Upqen48KFC1F/HseOHcNf//VfBwPdb3zjG4rjLly4gJkzZwbnDgwFykrn7uvrg9PpxKxZs+D3+3Ht2jU4nU74/f6o8xiLlFlEOJRVXhxxy7FEZpqJyBhiXQhDRKQXpaWl6OjowIKqI+jo6Lhn+UCgr/Ro/aXz8/OxceNGZGdnQwiB7OxsbNy4Efn5+eOaa3d3N4QQ6O8futrf398PIYRiL2qTyYSHHnoIly5dgt/vx6VLl/DQQw/BZDIpnnvGjBloaGjAtWvXIKXEtWvX0NDQoBicm0wmFBcXh31/xcXFiucOZN1H/tyUsvHjkTIBdI+7DqfWn4q49bgjC+wpfrgNM42V1WpFY2MjXnjhBXg8HrzwwgtobGw0RBDNjhZEdC+BUoZAqUXgT6USB5vNhkOHDuH06dPw+/04ffo0Dh06FLWbhNlsRk1NDbKzs1FTUxO1JAMAZs+ejWPHjsHn8+HYsWOYPXu24ri+vj4cP348rGPH8ePHI0pLQvn9fly5cgVSSly5ciVqltjn8+HgwYP4+OOPgy39Dh48CJ/PFzE20Gt75ONEy96PNRFj6BIOMj49XDrlqnpj2r9/P+rr6/H8888DQPDPnTt3RiyE0Rv+jhHpX6I7Zh09ehQrVqzAu+++C2DodaO4uBhHjx6NGBvIYtfW1gYXJ0brfTxp0iT4fL7g61AguxwI0Ed68MEHw+qUH3zwQcVsuBAC+fn5cDgcePnll2E2m7Fo0SKcOXNG8byBLPbkyZNx586d4J9K2W0hBKSUMbX0U8NqteKll14Kfu8DAwN46aWXAER2JBkpZTLQWlpY0xJxY2u6iadVttqI2zDTULajoqIi7FhFRcWo2Q5e8SCiWHxa9yfBtVCBr6M1KFiyqy0YbAdigCW72iZkHkePHoXf78eC6n+A3+9XDJ4DYi0N2bJlCwAEtw9PS0uDECJ4fKRf/OIXWLVqFa5du4ZVq1bhF7/4heI4KSU+/vjjsKuCH3/88ajvq1//+tfR09MDKSV6enrw9a9/XXFcIKO8efNm3Lx5E5s3bw47rmTkWCX79u2LmJ+UMtjWbzSGzkCr2WpTK2p3N6KxY3BrbBPddstsNqOxsTGYeQaG2jONdimSv0PGxtZtpEdaNTTQSiCzun///uDiww0bNihmXPPy8nDp0iUcOXIEs2bNCjs+khACjz/+OBwOB7Zv3w6LxYLHH38cx44dizqX3/zmN3C5XMEuI7/5zW+iji0qKgrrR11UVASXy6U4dtKkSWhtbcUrr7yC+fPnY9KkSYrBduDYzJkzcfXqVcycOXPUUpJQhg6gY91qk4gSb6IDng0bNqC6uhoAgivJq6urI7LSpG9qgmIGzWR0WrXfVctut8Nut98z8dfQ0BDc7OTTT89j4cIF8Hg8aGhoiBgrpcTPf/7zYK3x6dOno249HvD555+HbSqTkRH96n1osHz69OlRu3v4/X58+umnABD8Mxqz2Qyn0xkM4gObtdyLoQNoLSkF4izLMA7WNSe/QLZk586dqKyshNlsRkVFhe7rnykcn5tkdGquhhstWx1aW43h7hcvvPCCYnnIokWL8OUvfxmtra3B3QJLSkrwySefKJ578eLFOHXqVEQN9OLFiyPGpqWlYXBwEHPmzMGVK1cxZ85sXLlyJViGEipQL610XInP58PJkyfx6KOP4uTJk4oLE5WkVAAda1DMsgzj08ubMi85ayuQRSEiShStroYrZasBxD1jHdipb2FNCzpGiYcCm8S0trbi2Z/exoF7bBLz0Ucf4atf/SpOnToFAMHg+aOPPooYu3nzZrz00ku4du0agKGWd0IIxfrmv/zLv8TevXsVjyuRUqKysjJqL+xoDB9Ax7pKlkExJQKDZhovbttOlDzGm60GlINzNcG2VoG52k1iAASD5XvFZWrqtkPHBjLh0cbOmDED3d3dwQx34E+lXtQjGTqAZlBMRMmOAXPq4BUr44o1macmW60UbA8dB0YG3GqCbTVjgfCA+17BdqzZ6rGItW5bzdi9e/di06ZN8Hq9we3N77vvPsUM9kiGDqBTgRGzT3wTICJSj6+XxhQI0CY6kacUbAceZyQ1wbaasYC6um01wbaaBZVaZdhH9s/+yle+ErV/9kiaBtBCiD8C8N8ApAH4iZSybsTfmwG8DuD3AFwHsEZK+amWczIavbygcqU8ERmJEZMPlBrUbNAS69otNcG2mrGAdoskxzs22nj1pS9TgD+tx4I/Be4A2PEhUHe27Z7lLJoF0EKINAAvAVgOoAvA+0KII1LK0C1pygHckFL+thDiWwDqAazRak5aUvNirYcXdrVdKvjmQ0RGwtesL+jhPYeGqCk91bJMVU2nsfGWnUQLtsc7Ntp4NWP9CyuRE/ltYKgL9CmFv/mClhnorwH4tZTy3wFACPF3AFYBCA2gVwH4r8NfvwVgrxBCSAM+u9VMWatvT01QbMAfMRERjQFf71ODlp3G1NR4xzKHiRgbbbzasWqy8aG0DKDnAvgs5H4XgEejjZFSDgghbgG4H8C1WB9Ey36/RqvlNcIck4HRfi+IiCi5aZmtVlPjPZaxsYzXMnM/1n0/hIbZ0KcArJBS/sXw/T8H8DUppTVkzOnhMV3D938zPOb6iHNtBLARAObPn/9758+fH+ucwu4z+CEiIvqCmvdJPYwdOV7N2Imchx7GjhzPn8XYfhYjxwoh/lVK+cjIf6NlBroLwLyQ+3kALkYZ0yWESAcwFUD3yBNJKV8F8CoAPPLII2OOehkwExERRadVOaKWZY56mIcexuplHnoYq/W5AWCS6n8Ru/cBfFkI8aAQwgTgWwCOjBhzBMD64a+/CeCYEeufiYiIiCh1aJaBHq5p3grgKIba2DmklKeFEH8D4F+klEcANAH4WyHErzGUef6WVvMhIiIiIpoImvaBllL+FMBPRxz7XsjXXgBPaTkHIiIiIqKJpGUJBxERERFR0mEATURERESkAgNoIiIiIiIVGEATEREREanAAJqIiIiISAUG0EREREREKjCAJiIiIiJSgQE0EREREZEKDKCJiIiIiFRgAE1EREREpAIDaCIiIiIiFRhAExERERGpwACaiIiIiEgFBtBERERERCowgCYiIiIiUoEBNBERERGRCgygiYiIiIhUYABNRERERKQCA2giIiIiIhUYQBMRERERqSCklImegypCiM8BnE/0PIiIiIgo6S2QUs4aedBwATQRERERUSKxhIOIiIiISAUG0EREREREKjCAJiLSiBBiUAjxq5DbwkTPaaIIIZ4VQuyN8ncn4j0fIqJ4Sk/0BIiIkthdKeXD0f5SCJEupRyI54TiQUq5LNFzICLSEjPQRERxNJy5fVMI8b8BtA0f2y6EeF8I8ZEQYlfIWJsQ4t+EEP9XCOEUQnxn+Pg/CiEeGf56phDi0+Gv04QQPww516bh448P/5u3hBAfCyEOCiHE8N/9vhDihBDiQyHEL4UQOUKIfxJCPBwyj+NCiK8qfDvzhBD/Z3iO3w8Zf+dej0tEZGTMQBMRaSdLCPGr4a/PSSmfHP76PwD4qpSyWwhRDODLAL4GQAA4IoT4jwA8AL4FYCmGXqs/APCv93i8cgC3pJS/L4QwAzguhGgb/rulABYBuAjgOIDHhBC/BHAYwBop5ftCiCkA7gL4CYBnAfyVEOIrAMxSyo8UHu9rAAoA9AJ4XwjRIqX8lxFjIh4XQPs9vg8iIl1jAE1EpJ1oJRzvSim7h78uHr6dHL4/GUMBdQ6Ad6SUvQAghDgSw+MVA/iqEOKbw/enDp/LB+CXUsqu4XP9CsBCALcAXJJSvg8AUsrbw3//JoDvCiG2AygDcCDK470rpbw+/G/+F4BCACMDaKXHZQBNRIbGAJqIKP48IV8LALullK+EDhBC/BWAaI36B/BFCV7miHNZpZRHR5zrcQB9IYcGMfT6L5QeQ0rZK4R4F8AqAE8DeCTKPEb+W6X5Kj0uEZGhsQaaiCixjgIoE0JMBgAhxFwhxGwA7wF4UgiRJYTIAfCNkH/zKYDfG/76myPOtVkIkTF8rq8IIbJHeeyPAeQKIX5/eHyOECIQ4P4EwH8H8H5Itnyk5UKIGUKILACrMVSiQUSU9JgJICJKICllmxDCAuD/Da+vuwPg21LKD4QQhwH8CsB5AP8U8s9+BOANIcSfAzgWcvwnGCqR+GB4sd7nGApsoz22TwixBoB9OAi+C+APAdyRUv6rEOI2gP8xyvTbAfwtgN8GcEih/pmIKClxK28iIgMQQvxXDAW2P4rT4+UC+EcAvyOl9MfjMYmIjIIlHEREFEYI8QyAfwZgY/BMRBSJGWgiIiIiIhWYgSYiIiIiUoEBNBERERGRCgygiYiIiIhUYABNRERERKQCA2giIiIiIhUYQBMRERERqfD/AZlN1fgvExgnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We can see that, there are outliers in the dataset.  We can also observe that data is already in the range from 0 to 1 \n",
    "# Data also looks in the normalized form\n",
    "ds_sonar.plot.box(figsize=(12,10), xticks=[])\n",
    "plt.title('Boxplots of all frequency bins')\n",
    "plt.xlabel('Frequency bin')\n",
    "plt.ylabel('Power spectral density (normalized)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>51</th>\n",
       "      <th>52</th>\n",
       "      <th>53</th>\n",
       "      <th>54</th>\n",
       "      <th>55</th>\n",
       "      <th>56</th>\n",
       "      <th>57</th>\n",
       "      <th>58</th>\n",
       "      <th>59</th>\n",
       "      <th>60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.0428</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0954</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.1601</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>0.2111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0453</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>0.0843</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>0.1183</td>\n",
       "      <td>0.2583</td>\n",
       "      <td>0.2156</td>\n",
       "      <td>0.3481</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>0.2872</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0582</td>\n",
       "      <td>0.1099</td>\n",
       "      <td>0.1083</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>0.2431</td>\n",
       "      <td>0.3771</td>\n",
       "      <td>0.5598</td>\n",
       "      <td>0.6194</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0232</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>0.0316</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>0.0623</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.1098</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>0.0598</td>\n",
       "      <td>0.1264</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0762</td>\n",
       "      <td>0.0666</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0590</td>\n",
       "      <td>0.0649</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.2467</td>\n",
       "      <td>0.3564</td>\n",
       "      <td>0.4459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.0286</td>\n",
       "      <td>0.0453</td>\n",
       "      <td>0.0277</td>\n",
       "      <td>0.0174</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.1201</td>\n",
       "      <td>0.1833</td>\n",
       "      <td>0.2105</td>\n",
       "      <td>0.3039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.0317</td>\n",
       "      <td>0.0956</td>\n",
       "      <td>0.1321</td>\n",
       "      <td>0.1408</td>\n",
       "      <td>0.1674</td>\n",
       "      <td>0.1710</td>\n",
       "      <td>0.0731</td>\n",
       "      <td>0.1401</td>\n",
       "      <td>0.2083</td>\n",
       "      <td>0.3513</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0201</td>\n",
       "      <td>0.0248</td>\n",
       "      <td>0.0131</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.0519</td>\n",
       "      <td>0.0548</td>\n",
       "      <td>0.0842</td>\n",
       "      <td>0.0319</td>\n",
       "      <td>0.1158</td>\n",
       "      <td>0.0922</td>\n",
       "      <td>0.1027</td>\n",
       "      <td>0.0613</td>\n",
       "      <td>0.1465</td>\n",
       "      <td>0.2838</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0097</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.0223</td>\n",
       "      <td>0.0375</td>\n",
       "      <td>0.0484</td>\n",
       "      <td>0.0475</td>\n",
       "      <td>0.0647</td>\n",
       "      <td>0.0591</td>\n",
       "      <td>0.0753</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0684</td>\n",
       "      <td>0.1487</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0145</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.0145</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0347</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0671</td>\n",
       "      <td>0.1056</td>\n",
       "      <td>0.0697</td>\n",
       "      <td>0.0962</td>\n",
       "      <td>0.0251</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.0223</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0152</td>\n",
       "      <td>0.0336</td>\n",
       "      <td>0.0310</td>\n",
       "      <td>0.0284</td>\n",
       "      <td>0.0396</td>\n",
       "      <td>0.0272</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.0452</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.0123</td>\n",
       "      <td>0.0309</td>\n",
       "      <td>0.0169</td>\n",
       "      <td>0.0313</td>\n",
       "      <td>0.0358</td>\n",
       "      <td>0.0102</td>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.0579</td>\n",
       "      <td>0.1122</td>\n",
       "      <td>0.0835</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0133</td>\n",
       "      <td>0.0265</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0009</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>0.0344</td>\n",
       "      <td>0.0546</td>\n",
       "      <td>0.0528</td>\n",
       "      <td>0.0958</td>\n",
       "      <td>0.1009</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0176</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0253</td>\n",
       "      <td>0.0489</td>\n",
       "      <td>0.1197</td>\n",
       "      <td>0.1589</td>\n",
       "      <td>0.1392</td>\n",
       "      <td>0.0987</td>\n",
       "      <td>0.0955</td>\n",
       "      <td>0.1895</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0194</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.0152</td>\n",
       "      <td>0.0158</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0189</td>\n",
       "      <td>0.0102</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.0124</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>0.0604</td>\n",
       "      <td>0.0449</td>\n",
       "      <td>0.0597</td>\n",
       "      <td>0.0355</td>\n",
       "      <td>0.0531</td>\n",
       "      <td>0.0343</td>\n",
       "      <td>0.1052</td>\n",
       "      <td>0.2120</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0174</td>\n",
       "      <td>0.0188</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0114</td>\n",
       "      <td>0.0196</td>\n",
       "      <td>0.0147</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.0298</td>\n",
       "      <td>0.0615</td>\n",
       "      <td>0.0650</td>\n",
       "      <td>0.0921</td>\n",
       "      <td>0.1615</td>\n",
       "      <td>0.2294</td>\n",
       "      <td>0.2176</td>\n",
       "      <td>0.2033</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0852</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0153</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>0.0212</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.0152</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.0352</td>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0469</td>\n",
       "      <td>0.0737</td>\n",
       "      <td>0.1185</td>\n",
       "      <td>0.1683</td>\n",
       "      <td>0.1541</td>\n",
       "      <td>0.1466</td>\n",
       "      <td>0.2912</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0346</td>\n",
       "      <td>0.0158</td>\n",
       "      <td>0.0154</td>\n",
       "      <td>0.0109</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.0192</td>\n",
       "      <td>0.0607</td>\n",
       "      <td>0.0378</td>\n",
       "      <td>0.0774</td>\n",
       "      <td>0.1388</td>\n",
       "      <td>0.0809</td>\n",
       "      <td>0.0568</td>\n",
       "      <td>0.0219</td>\n",
       "      <td>0.1037</td>\n",
       "      <td>0.1186</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0331</td>\n",
       "      <td>0.0131</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.0270</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0145</td>\n",
       "      <td>0.0278</td>\n",
       "      <td>0.0412</td>\n",
       "      <td>0.0757</td>\n",
       "      <td>0.1026</td>\n",
       "      <td>0.1138</td>\n",
       "      <td>0.0794</td>\n",
       "      <td>0.1520</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.0132</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0149</td>\n",
       "      <td>0.0641</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.2565</td>\n",
       "      <td>0.2559</td>\n",
       "      <td>0.2947</td>\n",
       "      <td>0.4110</td>\n",
       "      <td>0.4983</td>\n",
       "      <td>0.5920</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.0473</td>\n",
       "      <td>0.0509</td>\n",
       "      <td>0.0819</td>\n",
       "      <td>0.1252</td>\n",
       "      <td>0.1783</td>\n",
       "      <td>0.3070</td>\n",
       "      <td>0.3008</td>\n",
       "      <td>0.2362</td>\n",
       "      <td>0.3830</td>\n",
       "      <td>0.3759</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.0664</td>\n",
       "      <td>0.0575</td>\n",
       "      <td>0.0842</td>\n",
       "      <td>0.0372</td>\n",
       "      <td>0.0458</td>\n",
       "      <td>0.0771</td>\n",
       "      <td>0.0771</td>\n",
       "      <td>0.1130</td>\n",
       "      <td>0.2353</td>\n",
       "      <td>0.1838</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0162</td>\n",
       "      <td>0.0109</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.0099</td>\n",
       "      <td>0.0484</td>\n",
       "      <td>0.0299</td>\n",
       "      <td>0.0297</td>\n",
       "      <td>0.0652</td>\n",
       "      <td>0.1077</td>\n",
       "      <td>0.2363</td>\n",
       "      <td>0.2385</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.1882</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0149</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0202</td>\n",
       "      <td>0.0139</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>0.0134</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0136</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.1058</td>\n",
       "      <td>0.1023</td>\n",
       "      <td>0.0440</td>\n",
       "      <td>0.0931</td>\n",
       "      <td>0.0734</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0091</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.0644</td>\n",
       "      <td>0.0390</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0476</td>\n",
       "      <td>0.0816</td>\n",
       "      <td>0.0993</td>\n",
       "      <td>0.0315</td>\n",
       "      <td>0.0736</td>\n",
       "      <td>0.0860</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.0201</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0133</td>\n",
       "      <td>0.0151</td>\n",
       "      <td>0.0541</td>\n",
       "      <td>0.0210</td>\n",
       "      <td>0.0505</td>\n",
       "      <td>0.1097</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0030</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.0151</td>\n",
       "      <td>0.0320</td>\n",
       "      <td>0.0599</td>\n",
       "      <td>0.1050</td>\n",
       "      <td>0.1163</td>\n",
       "      <td>0.1734</td>\n",
       "      <td>0.1679</td>\n",
       "      <td>0.1119</td>\n",
       "      <td>0.0889</td>\n",
       "      <td>0.1205</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.0177</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0288</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0630</td>\n",
       "      <td>0.0526</td>\n",
       "      <td>0.0688</td>\n",
       "      <td>0.0633</td>\n",
       "      <td>0.0624</td>\n",
       "      <td>0.0613</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0102</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0124</td>\n",
       "      <td>0.0099</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0275</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.0201</td>\n",
       "      <td>0.0314</td>\n",
       "      <td>0.0651</td>\n",
       "      <td>0.1896</td>\n",
       "      <td>0.2668</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>0.0104</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>0.0091</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.0189</td>\n",
       "      <td>0.0308</td>\n",
       "      <td>0.0197</td>\n",
       "      <td>0.0622</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.0789</td>\n",
       "      <td>0.1440</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.1789</td>\n",
       "      <td>0.2522</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0142</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0099</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>1</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>0.0197</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.0251</td>\n",
       "      <td>0.0629</td>\n",
       "      <td>0.0747</td>\n",
       "      <td>0.0578</td>\n",
       "      <td>0.1357</td>\n",
       "      <td>0.1695</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0134</td>\n",
       "      <td>0.0097</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0420</td>\n",
       "      <td>0.0446</td>\n",
       "      <td>0.0551</td>\n",
       "      <td>0.0597</td>\n",
       "      <td>0.1416</td>\n",
       "      <td>0.0956</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.1618</td>\n",
       "      <td>0.2558</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0146</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0114</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0087</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.0310</td>\n",
       "      <td>0.0221</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0964</td>\n",
       "      <td>0.1827</td>\n",
       "      <td>0.1106</td>\n",
       "      <td>0.1702</td>\n",
       "      <td>0.2804</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>0.0423</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0709</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.1070</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>0.0961</td>\n",
       "      <td>0.1323</td>\n",
       "      <td>0.2462</td>\n",
       "      <td>0.2696</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0176</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0308</td>\n",
       "      <td>0.0539</td>\n",
       "      <td>0.0411</td>\n",
       "      <td>0.0613</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>0.2592</td>\n",
       "      <td>0.3745</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0102</td>\n",
       "      <td>0.0133</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0030</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0404</td>\n",
       "      <td>0.0682</td>\n",
       "      <td>0.0688</td>\n",
       "      <td>0.0887</td>\n",
       "      <td>0.0932</td>\n",
       "      <td>0.0955</td>\n",
       "      <td>0.2140</td>\n",
       "      <td>0.2546</td>\n",
       "      <td>0.2952</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>0.0170</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.0109</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>0.0269</td>\n",
       "      <td>0.0383</td>\n",
       "      <td>0.0505</td>\n",
       "      <td>0.0707</td>\n",
       "      <td>0.1313</td>\n",
       "      <td>0.2103</td>\n",
       "      <td>0.2263</td>\n",
       "      <td>0.2524</td>\n",
       "      <td>0.3595</td>\n",
       "      <td>0.5915</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0199</td>\n",
       "      <td>0.0145</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>0.0340</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0381</td>\n",
       "      <td>0.0257</td>\n",
       "      <td>0.0441</td>\n",
       "      <td>0.1027</td>\n",
       "      <td>0.1287</td>\n",
       "      <td>0.1850</td>\n",
       "      <td>0.2647</td>\n",
       "      <td>0.4117</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0099</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>0.0209</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0411</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0698</td>\n",
       "      <td>0.1579</td>\n",
       "      <td>0.1438</td>\n",
       "      <td>0.1402</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>0.3914</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>0.0201</td>\n",
       "      <td>0.0104</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0087</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.0279</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>0.0566</td>\n",
       "      <td>0.0759</td>\n",
       "      <td>0.0679</td>\n",
       "      <td>0.0970</td>\n",
       "      <td>0.1473</td>\n",
       "      <td>0.2164</td>\n",
       "      <td>0.2544</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0009</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0274</td>\n",
       "      <td>0.0248</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.1488</td>\n",
       "      <td>0.1224</td>\n",
       "      <td>0.1569</td>\n",
       "      <td>0.2119</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.0069</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>0.0158</td>\n",
       "      <td>0.0239</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0494</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.1463</td>\n",
       "      <td>0.1219</td>\n",
       "      <td>0.1697</td>\n",
       "      <td>0.1923</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0046</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.0156</td>\n",
       "      <td>0.0210</td>\n",
       "      <td>0.0282</td>\n",
       "      <td>0.0596</td>\n",
       "      <td>0.0462</td>\n",
       "      <td>0.0779</td>\n",
       "      <td>0.1365</td>\n",
       "      <td>0.0780</td>\n",
       "      <td>0.1038</td>\n",
       "      <td>0.1567</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>0.0091</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>0.0315</td>\n",
       "      <td>0.0252</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0479</td>\n",
       "      <td>0.0902</td>\n",
       "      <td>0.1057</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.1241</td>\n",
       "      <td>0.1533</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0267</td>\n",
       "      <td>0.0221</td>\n",
       "      <td>0.0561</td>\n",
       "      <td>0.0936</td>\n",
       "      <td>0.1146</td>\n",
       "      <td>0.0706</td>\n",
       "      <td>0.0996</td>\n",
       "      <td>0.1673</td>\n",
       "      <td>0.1859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>0.0203</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0380</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.0537</td>\n",
       "      <td>0.0874</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>0.0852</td>\n",
       "      <td>0.1136</td>\n",
       "      <td>0.1747</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0134</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>0.0392</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0267</td>\n",
       "      <td>0.0257</td>\n",
       "      <td>0.0410</td>\n",
       "      <td>0.0491</td>\n",
       "      <td>0.1053</td>\n",
       "      <td>0.1690</td>\n",
       "      <td>0.2105</td>\n",
       "      <td>0.2471</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0309</td>\n",
       "      <td>0.0375</td>\n",
       "      <td>0.0767</td>\n",
       "      <td>0.0787</td>\n",
       "      <td>0.0662</td>\n",
       "      <td>0.1108</td>\n",
       "      <td>0.1777</td>\n",
       "      <td>0.2245</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0124</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.0270</td>\n",
       "      <td>0.0450</td>\n",
       "      <td>0.0958</td>\n",
       "      <td>0.0830</td>\n",
       "      <td>0.0879</td>\n",
       "      <td>0.1220</td>\n",
       "      <td>0.1977</td>\n",
       "      <td>0.2282</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0165</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>0.0366</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.0504</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>0.0596</td>\n",
       "      <td>0.0252</td>\n",
       "      <td>0.0958</td>\n",
       "      <td>0.0991</td>\n",
       "      <td>0.1419</td>\n",
       "      <td>0.1847</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0132</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>0.0238</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0422</td>\n",
       "      <td>0.0399</td>\n",
       "      <td>0.0788</td>\n",
       "      <td>0.0766</td>\n",
       "      <td>0.0881</td>\n",
       "      <td>0.1143</td>\n",
       "      <td>0.1594</td>\n",
       "      <td>0.2048</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0744</td>\n",
       "      <td>0.0367</td>\n",
       "      <td>0.0225</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.0545</td>\n",
       "      <td>0.1110</td>\n",
       "      <td>0.1069</td>\n",
       "      <td>0.1708</td>\n",
       "      <td>0.2271</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.0131</td>\n",
       "      <td>0.0387</td>\n",
       "      <td>0.0329</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>0.0721</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.1626</td>\n",
       "      <td>0.1902</td>\n",
       "      <td>0.2610</td>\n",
       "      <td>0.3193</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0009</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>0.0335</td>\n",
       "      <td>0.0258</td>\n",
       "      <td>0.0398</td>\n",
       "      <td>0.0570</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>0.1091</td>\n",
       "      <td>0.1709</td>\n",
       "      <td>0.1684</td>\n",
       "      <td>0.1865</td>\n",
       "      <td>0.2660</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0046</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>0.0272</td>\n",
       "      <td>0.0378</td>\n",
       "      <td>0.0488</td>\n",
       "      <td>0.0848</td>\n",
       "      <td>0.1127</td>\n",
       "      <td>0.1103</td>\n",
       "      <td>0.1349</td>\n",
       "      <td>0.2337</td>\n",
       "      <td>0.3113</td>\n",
       "      <td>0.3997</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0091</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0043</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0346</td>\n",
       "      <td>0.0168</td>\n",
       "      <td>0.0177</td>\n",
       "      <td>0.0393</td>\n",
       "      <td>0.1630</td>\n",
       "      <td>0.2028</td>\n",
       "      <td>0.1694</td>\n",
       "      <td>0.2328</td>\n",
       "      <td>0.2684</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0199</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0157</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0298</td>\n",
       "      <td>0.0564</td>\n",
       "      <td>0.0760</td>\n",
       "      <td>0.0958</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.1018</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>0.2154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0135</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>0.0522</td>\n",
       "      <td>0.0437</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0292</td>\n",
       "      <td>0.0351</td>\n",
       "      <td>0.1171</td>\n",
       "      <td>0.1257</td>\n",
       "      <td>0.1178</td>\n",
       "      <td>0.1258</td>\n",
       "      <td>0.2529</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0077</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>0.0303</td>\n",
       "      <td>0.0353</td>\n",
       "      <td>0.0490</td>\n",
       "      <td>0.0608</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.1354</td>\n",
       "      <td>0.1465</td>\n",
       "      <td>0.1123</td>\n",
       "      <td>0.1945</td>\n",
       "      <td>0.2354</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.0046</td>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>0.0260</td>\n",
       "      <td>0.0363</td>\n",
       "      <td>0.0136</td>\n",
       "      <td>0.0272</td>\n",
       "      <td>0.0214</td>\n",
       "      <td>0.0338</td>\n",
       "      <td>0.0655</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1843</td>\n",
       "      <td>0.2354</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0146</td>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>208 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0       1       2       3       4       5       6       7       8   \\\n",
       "0    0.0200  0.0371  0.0428  0.0207  0.0954  0.0986  0.1539  0.1601  0.3109   \n",
       "1    0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
       "2    0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
       "3    0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
       "4    0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
       "5    0.0286  0.0453  0.0277  0.0174  0.0384  0.0990  0.1201  0.1833  0.2105   \n",
       "6    0.0317  0.0956  0.1321  0.1408  0.1674  0.1710  0.0731  0.1401  0.2083   \n",
       "7    0.0519  0.0548  0.0842  0.0319  0.1158  0.0922  0.1027  0.0613  0.1465   \n",
       "8    0.0223  0.0375  0.0484  0.0475  0.0647  0.0591  0.0753  0.0098  0.0684   \n",
       "9    0.0164  0.0173  0.0347  0.0070  0.0187  0.0671  0.1056  0.0697  0.0962   \n",
       "10   0.0039  0.0063  0.0152  0.0336  0.0310  0.0284  0.0396  0.0272  0.0323   \n",
       "11   0.0123  0.0309  0.0169  0.0313  0.0358  0.0102  0.0182  0.0579  0.1122   \n",
       "12   0.0079  0.0086  0.0055  0.0250  0.0344  0.0546  0.0528  0.0958  0.1009   \n",
       "13   0.0090  0.0062  0.0253  0.0489  0.1197  0.1589  0.1392  0.0987  0.0955   \n",
       "14   0.0124  0.0433  0.0604  0.0449  0.0597  0.0355  0.0531  0.0343  0.1052   \n",
       "15   0.0298  0.0615  0.0650  0.0921  0.1615  0.2294  0.2176  0.2033  0.1459   \n",
       "16   0.0352  0.0116  0.0191  0.0469  0.0737  0.1185  0.1683  0.1541  0.1466   \n",
       "17   0.0192  0.0607  0.0378  0.0774  0.1388  0.0809  0.0568  0.0219  0.1037   \n",
       "18   0.0270  0.0092  0.0145  0.0278  0.0412  0.0757  0.1026  0.1138  0.0794   \n",
       "19   0.0126  0.0149  0.0641  0.1732  0.2565  0.2559  0.2947  0.4110  0.4983   \n",
       "20   0.0473  0.0509  0.0819  0.1252  0.1783  0.3070  0.3008  0.2362  0.3830   \n",
       "21   0.0664  0.0575  0.0842  0.0372  0.0458  0.0771  0.0771  0.1130  0.2353   \n",
       "22   0.0099  0.0484  0.0299  0.0297  0.0652  0.1077  0.2363  0.2385  0.0075   \n",
       "23   0.0115  0.0150  0.0136  0.0076  0.0211  0.1058  0.1023  0.0440  0.0931   \n",
       "24   0.0293  0.0644  0.0390  0.0173  0.0476  0.0816  0.0993  0.0315  0.0736   \n",
       "25   0.0201  0.0026  0.0138  0.0062  0.0133  0.0151  0.0541  0.0210  0.0505   \n",
       "26   0.0151  0.0320  0.0599  0.1050  0.1163  0.1734  0.1679  0.1119  0.0889   \n",
       "27   0.0177  0.0300  0.0288  0.0394  0.0630  0.0526  0.0688  0.0633  0.0624   \n",
       "28   0.0100  0.0275  0.0190  0.0371  0.0416  0.0201  0.0314  0.0651  0.1896   \n",
       "29   0.0189  0.0308  0.0197  0.0622  0.0080  0.0789  0.1440  0.1451  0.1789   \n",
       "..      ...     ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "178  0.0197  0.0394  0.0384  0.0076  0.0251  0.0629  0.0747  0.0578  0.1357   \n",
       "179  0.0394  0.0420  0.0446  0.0551  0.0597  0.1416  0.0956  0.0802  0.1618   \n",
       "180  0.0310  0.0221  0.0433  0.0191  0.0964  0.1827  0.1106  0.1702  0.2804   \n",
       "181  0.0423  0.0321  0.0709  0.0108  0.1070  0.0973  0.0961  0.1323  0.2462   \n",
       "182  0.0095  0.0308  0.0539  0.0411  0.0613  0.1039  0.1016  0.1394  0.2592   \n",
       "183  0.0096  0.0404  0.0682  0.0688  0.0887  0.0932  0.0955  0.2140  0.2546   \n",
       "184  0.0269  0.0383  0.0505  0.0707  0.1313  0.2103  0.2263  0.2524  0.3595   \n",
       "185  0.0340  0.0625  0.0381  0.0257  0.0441  0.1027  0.1287  0.1850  0.2647   \n",
       "186  0.0209  0.0191  0.0411  0.0321  0.0698  0.1579  0.1438  0.1402  0.3048   \n",
       "187  0.0368  0.0279  0.0103  0.0566  0.0759  0.0679  0.0970  0.1473  0.2164   \n",
       "188  0.0089  0.0274  0.0248  0.0237  0.0224  0.0845  0.1488  0.1224  0.1569   \n",
       "189  0.0158  0.0239  0.0150  0.0494  0.0988  0.1425  0.1463  0.1219  0.1697   \n",
       "190  0.0156  0.0210  0.0282  0.0596  0.0462  0.0779  0.1365  0.0780  0.1038   \n",
       "191  0.0315  0.0252  0.0167  0.0479  0.0902  0.1057  0.1024  0.1209  0.1241   \n",
       "192  0.0056  0.0267  0.0221  0.0561  0.0936  0.1146  0.0706  0.0996  0.1673   \n",
       "193  0.0203  0.0121  0.0380  0.0128  0.0537  0.0874  0.1021  0.0852  0.1136   \n",
       "194  0.0392  0.0108  0.0267  0.0257  0.0410  0.0491  0.1053  0.1690  0.2105   \n",
       "195  0.0129  0.0141  0.0309  0.0375  0.0767  0.0787  0.0662  0.1108  0.1777   \n",
       "196  0.0050  0.0017  0.0270  0.0450  0.0958  0.0830  0.0879  0.1220  0.1977   \n",
       "197  0.0366  0.0421  0.0504  0.0250  0.0596  0.0252  0.0958  0.0991  0.1419   \n",
       "198  0.0238  0.0318  0.0422  0.0399  0.0788  0.0766  0.0881  0.1143  0.1594   \n",
       "199  0.0116  0.0744  0.0367  0.0225  0.0076  0.0545  0.1110  0.1069  0.1708   \n",
       "200  0.0131  0.0387  0.0329  0.0078  0.0721  0.1341  0.1626  0.1902  0.2610   \n",
       "201  0.0335  0.0258  0.0398  0.0570  0.0529  0.1091  0.1709  0.1684  0.1865   \n",
       "202  0.0272  0.0378  0.0488  0.0848  0.1127  0.1103  0.1349  0.2337  0.3113   \n",
       "203  0.0187  0.0346  0.0168  0.0177  0.0393  0.1630  0.2028  0.1694  0.2328   \n",
       "204  0.0323  0.0101  0.0298  0.0564  0.0760  0.0958  0.0990  0.1018  0.1030   \n",
       "205  0.0522  0.0437  0.0180  0.0292  0.0351  0.1171  0.1257  0.1178  0.1258   \n",
       "206  0.0303  0.0353  0.0490  0.0608  0.0167  0.1354  0.1465  0.1123  0.1945   \n",
       "207  0.0260  0.0363  0.0136  0.0272  0.0214  0.0338  0.0655  0.1400  0.1843   \n",
       "\n",
       "         9   ...      51      52      53      54      55      56      57  \\\n",
       "0    0.2111  ...  0.0027  0.0065  0.0159  0.0072  0.0167  0.0180  0.0084   \n",
       "1    0.2872  ...  0.0084  0.0089  0.0048  0.0094  0.0191  0.0140  0.0049   \n",
       "2    0.6194  ...  0.0232  0.0166  0.0095  0.0180  0.0244  0.0316  0.0164   \n",
       "3    0.1264  ...  0.0121  0.0036  0.0150  0.0085  0.0073  0.0050  0.0044   \n",
       "4    0.4459  ...  0.0031  0.0054  0.0105  0.0110  0.0015  0.0072  0.0048   \n",
       "5    0.3039  ...  0.0045  0.0014  0.0038  0.0013  0.0089  0.0057  0.0027   \n",
       "6    0.3513  ...  0.0201  0.0248  0.0131  0.0070  0.0138  0.0092  0.0143   \n",
       "7    0.2838  ...  0.0081  0.0120  0.0045  0.0121  0.0097  0.0085  0.0047   \n",
       "8    0.1487  ...  0.0145  0.0128  0.0145  0.0058  0.0049  0.0065  0.0093   \n",
       "9    0.0251  ...  0.0090  0.0223  0.0179  0.0084  0.0068  0.0032  0.0035   \n",
       "10   0.0452  ...  0.0062  0.0120  0.0052  0.0056  0.0093  0.0042  0.0003   \n",
       "11   0.0835  ...  0.0133  0.0265  0.0224  0.0074  0.0118  0.0026  0.0092   \n",
       "12   0.1240  ...  0.0176  0.0127  0.0088  0.0098  0.0019  0.0059  0.0058   \n",
       "13   0.1895  ...  0.0059  0.0095  0.0194  0.0080  0.0152  0.0158  0.0053   \n",
       "14   0.2120  ...  0.0083  0.0057  0.0174  0.0188  0.0054  0.0114  0.0196   \n",
       "15   0.0852  ...  0.0031  0.0153  0.0071  0.0212  0.0076  0.0152  0.0049   \n",
       "16   0.2912  ...  0.0346  0.0158  0.0154  0.0109  0.0048  0.0095  0.0015   \n",
       "17   0.1186  ...  0.0331  0.0131  0.0120  0.0108  0.0024  0.0045  0.0037   \n",
       "18   0.1520  ...  0.0084  0.0010  0.0018  0.0068  0.0039  0.0120  0.0132   \n",
       "19   0.5920  ...  0.0092  0.0035  0.0098  0.0121  0.0006  0.0181  0.0094   \n",
       "20   0.3759  ...  0.0193  0.0118  0.0064  0.0042  0.0054  0.0049  0.0082   \n",
       "21   0.1838  ...  0.0141  0.0190  0.0043  0.0036  0.0026  0.0024  0.0162   \n",
       "22   0.1882  ...  0.0173  0.0149  0.0115  0.0202  0.0139  0.0029  0.0160   \n",
       "23   0.0734  ...  0.0091  0.0016  0.0084  0.0064  0.0026  0.0029  0.0037   \n",
       "24   0.0860  ...  0.0035  0.0052  0.0083  0.0078  0.0075  0.0105  0.0160   \n",
       "25   0.1097  ...  0.0108  0.0070  0.0063  0.0030  0.0011  0.0007  0.0024   \n",
       "26   0.1205  ...  0.0061  0.0015  0.0084  0.0128  0.0054  0.0011  0.0019   \n",
       "27   0.0613  ...  0.0102  0.0122  0.0044  0.0075  0.0124  0.0099  0.0057   \n",
       "28   0.2668  ...  0.0088  0.0104  0.0036  0.0088  0.0047  0.0117  0.0020   \n",
       "29   0.2522  ...  0.0038  0.0096  0.0142  0.0190  0.0140  0.0099  0.0092   \n",
       "..      ...  ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "178  0.1695  ...  0.0134  0.0097  0.0042  0.0058  0.0072  0.0041  0.0045   \n",
       "179  0.2558  ...  0.0146  0.0040  0.0114  0.0032  0.0062  0.0101  0.0068   \n",
       "180  0.4432  ...  0.0204  0.0059  0.0053  0.0079  0.0037  0.0015  0.0056   \n",
       "181  0.2696  ...  0.0176  0.0035  0.0093  0.0121  0.0075  0.0056  0.0021   \n",
       "182  0.3745  ...  0.0181  0.0019  0.0102  0.0133  0.0040  0.0042  0.0030   \n",
       "183  0.2952  ...  0.0237  0.0078  0.0144  0.0170  0.0012  0.0109  0.0036   \n",
       "184  0.5915  ...  0.0167  0.0199  0.0145  0.0081  0.0045  0.0043  0.0027   \n",
       "185  0.4117  ...  0.0141  0.0019  0.0067  0.0099  0.0042  0.0057  0.0051   \n",
       "186  0.3914  ...  0.0078  0.0201  0.0104  0.0039  0.0031  0.0062  0.0087   \n",
       "187  0.2544  ...  0.0105  0.0024  0.0018  0.0057  0.0092  0.0009  0.0086   \n",
       "188  0.2119  ...  0.0096  0.0103  0.0093  0.0025  0.0044  0.0021  0.0069   \n",
       "189  0.1923  ...  0.0121  0.0108  0.0057  0.0028  0.0079  0.0034  0.0046   \n",
       "190  0.1567  ...  0.0150  0.0060  0.0082  0.0091  0.0038  0.0056  0.0056   \n",
       "191  0.1533  ...  0.0108  0.0062  0.0044  0.0072  0.0007  0.0054  0.0035   \n",
       "192  0.1859  ...  0.0072  0.0055  0.0074  0.0068  0.0084  0.0037  0.0024   \n",
       "193  0.1747  ...  0.0134  0.0094  0.0047  0.0045  0.0042  0.0028  0.0036   \n",
       "194  0.2471  ...  0.0083  0.0080  0.0026  0.0079  0.0042  0.0071  0.0044   \n",
       "195  0.2245  ...  0.0124  0.0093  0.0072  0.0019  0.0027  0.0054  0.0017   \n",
       "196  0.2282  ...  0.0165  0.0056  0.0010  0.0027  0.0062  0.0024  0.0063   \n",
       "197  0.1847  ...  0.0132  0.0027  0.0022  0.0059  0.0016  0.0025  0.0017   \n",
       "198  0.2048  ...  0.0096  0.0071  0.0084  0.0038  0.0026  0.0028  0.0013   \n",
       "199  0.2271  ...  0.0141  0.0103  0.0100  0.0034  0.0026  0.0037  0.0044   \n",
       "200  0.3193  ...  0.0150  0.0076  0.0032  0.0037  0.0071  0.0040  0.0009   \n",
       "201  0.2660  ...  0.0120  0.0039  0.0053  0.0062  0.0046  0.0045  0.0022   \n",
       "202  0.3997  ...  0.0091  0.0045  0.0043  0.0043  0.0098  0.0054  0.0051   \n",
       "203  0.2684  ...  0.0116  0.0098  0.0199  0.0033  0.0101  0.0065  0.0115   \n",
       "204  0.2154  ...  0.0061  0.0093  0.0135  0.0063  0.0063  0.0034  0.0032   \n",
       "205  0.2529  ...  0.0160  0.0029  0.0051  0.0062  0.0089  0.0140  0.0138   \n",
       "206  0.2354  ...  0.0086  0.0046  0.0126  0.0036  0.0035  0.0034  0.0079   \n",
       "207  0.2354  ...  0.0146  0.0129  0.0047  0.0039  0.0061  0.0040  0.0036   \n",
       "\n",
       "         58      59  60  \n",
       "0    0.0090  0.0032   1  \n",
       "1    0.0052  0.0044   1  \n",
       "2    0.0095  0.0078   1  \n",
       "3    0.0040  0.0117   1  \n",
       "4    0.0107  0.0094   1  \n",
       "5    0.0051  0.0062   1  \n",
       "6    0.0036  0.0103   1  \n",
       "7    0.0048  0.0053   1  \n",
       "8    0.0059  0.0022   1  \n",
       "9    0.0056  0.0040   1  \n",
       "10   0.0053  0.0036   1  \n",
       "11   0.0009  0.0044   1  \n",
       "12   0.0059  0.0032   1  \n",
       "13   0.0189  0.0102   1  \n",
       "14   0.0147  0.0062   1  \n",
       "15   0.0200  0.0073   1  \n",
       "16   0.0073  0.0067   1  \n",
       "17   0.0112  0.0075   1  \n",
       "18   0.0070  0.0088   1  \n",
       "19   0.0116  0.0063   1  \n",
       "20   0.0028  0.0027   1  \n",
       "21   0.0109  0.0079   1  \n",
       "22   0.0106  0.0134   1  \n",
       "23   0.0070  0.0041   1  \n",
       "24   0.0095  0.0011   1  \n",
       "25   0.0057  0.0044   1  \n",
       "26   0.0023  0.0062   1  \n",
       "27   0.0032  0.0019   1  \n",
       "28   0.0091  0.0058   1  \n",
       "29   0.0052  0.0075   1  \n",
       "..      ...     ...  ..  \n",
       "178  0.0047  0.0054   0  \n",
       "179  0.0053  0.0087   0  \n",
       "180  0.0067  0.0054   0  \n",
       "181  0.0043  0.0017   0  \n",
       "182  0.0031  0.0033   0  \n",
       "183  0.0043  0.0018   0  \n",
       "184  0.0055  0.0057   0  \n",
       "185  0.0033  0.0058   0  \n",
       "186  0.0070  0.0042   0  \n",
       "187  0.0110  0.0052   0  \n",
       "188  0.0060  0.0018   0  \n",
       "189  0.0022  0.0021   0  \n",
       "190  0.0048  0.0024   0  \n",
       "191  0.0001  0.0055   0  \n",
       "192  0.0034  0.0007   0  \n",
       "193  0.0013  0.0016   0  \n",
       "194  0.0022  0.0014   0  \n",
       "195  0.0024  0.0029   0  \n",
       "196  0.0017  0.0028   0  \n",
       "197  0.0027  0.0027   0  \n",
       "198  0.0035  0.0060   0  \n",
       "199  0.0057  0.0035   0  \n",
       "200  0.0015  0.0085   0  \n",
       "201  0.0005  0.0031   0  \n",
       "202  0.0065  0.0103   0  \n",
       "203  0.0193  0.0157   0  \n",
       "204  0.0062  0.0067   0  \n",
       "205  0.0077  0.0031   0  \n",
       "206  0.0036  0.0048   0  \n",
       "207  0.0061  0.0115   0  \n",
       "\n",
       "[208 rows x 61 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ole = LabelEncoder()\n",
    "ds_sonar[60] = ole.fit_transform(ds_sonar[60])\n",
    "ds_sonar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(ds_sonar.iloc[:, 0:59], ds_sonar.iloc[:,60], test_size=.3, random_state=1, stratify=ds_sonar.iloc[:,60])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train distribution:\n",
      "0    77\n",
      "1    68\n",
      "Name: 60, dtype: int64\n",
      "\n",
      "\n",
      "Test distribution:\n",
      "0    34\n",
      "1    29\n",
      "Name: 60, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#Verifying that data is distributed properly into train and test data\n",
    "print('Train distribution:'); print(y_train.value_counts())\n",
    "print('\\n')\n",
    "print('Test distribution:'); print(y_test.value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LR: 0.765238 (0.164076)\n",
      "LDA: 0.751429 (0.098049)\n",
      "KNN: 0.750952 (0.107160)\n",
      "CART: 0.681905 (0.102349)\n",
      "NB: 0.676190 (0.157056)\n",
      "SVM: 0.551905 (0.090362)\n"
     ]
    }
   ],
   "source": [
    "# Spot Check Algorithms\n",
    "models = []\n",
    "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n",
    "models.append(('LDA', LinearDiscriminantAnalysis()))\n",
    "models.append(('KNN', KNeighborsClassifier()))\n",
    "models.append(('CART', DecisionTreeClassifier()))\n",
    "models.append(('NB', GaussianNB()))\n",
    "models.append(('SVM', SVC(gamma='auto')))\n",
    "# evaluate each model in turn\n",
    "kfold=10\n",
    "scoring='accuracy'\n",
    "seed = 1\n",
    "results = []\n",
    "names = []\n",
    "for name, model in models:\n",
    "\tkfold = model_selection.KFold(n_splits=10, random_state=seed)\n",
    "\tcv_results = model_selection.cross_val_score(model, x_train, y_train, cv=kfold, scoring=scoring)\n",
    "\tresults.append(cv_results)\n",
    "\tnames.append(name)\n",
    "\tmsg = \"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std())\n",
    "\tprint(msg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy score:  0.6666666666666666\n",
      "Confusion matrix:\n",
      " [[19 15]\n",
      " [ 6 23]]\n",
      "Classification report:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.76      0.56      0.64        34\n",
      "           1       0.61      0.79      0.69        29\n",
      "\n",
      "    accuracy                           0.67        63\n",
      "   macro avg       0.68      0.68      0.67        63\n",
      "weighted avg       0.69      0.67      0.66        63\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Based on above accuracy, LR is giving more predectivity values. Let's try with test data to check its accuracy.\n",
    "lr_model = LogisticRegression()\n",
    "lr_model.fit(x_train, y_train)\n",
    "lr_model.score(x_train, y_train)\n",
    "y_pred = lr_model.predict(x_test)\n",
    "print('Accuracy score: ',accuracy_score(y_test, y_pred))\n",
    "print('Confusion matrix:\\n',confusion_matrix(y_test, y_pred))\n",
    "print('Classification report:\\n',classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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