02_lmplot_Anscombe_quartet.ipynb

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   "source": [
    "# Anscombe's quartet \n",
    "> \"numerical calculations are exact, but graphs are rough.\"\n",
    "\n",
    "* [Anscombe’s quartet — seaborn documentation](https://seaborn.pydata.org/examples/anscombes_quartet.html)\n",
    "* [앤스컴 콰르텟 - 위키백과, 우리 모두의 백과사전](https://ko.wikipedia.org/wiki/%EC%95%A4%EC%8A%A4%EC%BB%B4_%EC%BD%B0%EB%A5%B4%ED%85%9F)\n",
    "* [Anscombe's quartet - Wikipedia](https://en.wikipedia.org/wiki/Anscombe%27s_quartet)\n",
    "* [The Datasaurus Dozen - Same Stats, Different Graphs | Autodesk Research](https://www.autodeskresearch.com/publications/samestats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "# 주피터 노트북 안에서 그래프를 표시합니다.\n",
    "%matplotlib inline\n",
    "# 그래프의 스타일을 지정합니다.\n",
    "sns.set(style=\"ticks\")\n",
    "\n",
    "# Load the example dataset for Anscombe's quartet\n",
    "# 내장되어 있는 데이터셋을 가져옵니다. 이 데이터셋에 대한 설명은 위에 있는 위키백과의 링크를 참고해 주세요.\n",
    "df = sns.load_dataset(\"anscombe\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44, 3)"
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     "execution_count": 2,
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   "source": [
    "df.shape"
   ]
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       "      <td>7.500682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
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       "      <th>25%</th>\n",
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       "               x          y\n",
       "count  44.000000  44.000000\n",
       "mean    9.000000   7.500682\n",
       "std     3.198837   1.958925\n",
       "min     4.000000   3.100000\n",
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     "execution_count": 3,
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   "source": [
    "# 데이터의 요약을 보면 평균, 표준편차가 같습니다.\n",
    "df.describe()"
   ]
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       "               x          y\n",
       "count  11.000000  11.000000\n",
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     "execution_count": 4,
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    "# 데이터의 요약을 보면 평균, 표준편차가 같습니다.\n",
    "df[df[\"dataset\"] == \"I\"].describe()"
   ]
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   "cell_type": "code",
   "execution_count": 5,
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       "               x          y\n",
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       "min     4.000000   3.100000\n",
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "# 데이터의 요약을 보면 평균, 표준편차가 같습니다.\n",
    "df[df[\"dataset\"] == \"II\"].describe()"
   ]
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   "execution_count": 6,
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       "               x          y\n",
       "count  11.000000  11.000000\n",
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     "execution_count": 6,
     "metadata": {},
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    "df[df[\"dataset\"] == \"III\"].describe()"
   ]
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   "cell_type": "code",
   "execution_count": 7,
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       "               x          y\n",
       "count  11.000000  11.000000\n",
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     "metadata": {},
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    "df[df[\"dataset\"] == \"IV\"].describe()"
   ]
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       "      <td>4.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
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       "      <td>2.031568</td>\n",
       "      <td>4.26</td>\n",
       "      <td>6.315</td>\n",
       "      <td>7.58</td>\n",
       "      <td>8.57</td>\n",
       "      <td>10.84</td>\n",
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       "    <tr>\n",
       "      <th>II</th>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.316625</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.500909</td>\n",
       "      <td>2.031657</td>\n",
       "      <td>3.10</td>\n",
       "      <td>6.695</td>\n",
       "      <td>8.14</td>\n",
       "      <td>8.95</td>\n",
       "      <td>9.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>III</th>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.316625</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>2.030424</td>\n",
       "      <td>5.39</td>\n",
       "      <td>6.250</td>\n",
       "      <td>7.11</td>\n",
       "      <td>7.98</td>\n",
       "      <td>12.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IV</th>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.316625</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.500909</td>\n",
       "      <td>2.030579</td>\n",
       "      <td>5.25</td>\n",
       "      <td>6.170</td>\n",
       "      <td>7.04</td>\n",
       "      <td>8.19</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            x                                               y            \\\n",
       "        count mean       std  min  25%  50%   75%   max count      mean   \n",
       "dataset                                                                   \n",
       "I        11.0  9.0  3.316625  4.0  6.5  9.0  11.5  14.0  11.0  7.500909   \n",
       "II       11.0  9.0  3.316625  4.0  6.5  9.0  11.5  14.0  11.0  7.500909   \n",
       "III      11.0  9.0  3.316625  4.0  6.5  9.0  11.5  14.0  11.0  7.500000   \n",
       "IV       11.0  9.0  3.316625  8.0  8.0  8.0   8.0  19.0  11.0  7.500909   \n",
       "\n",
       "                                                   \n",
       "              std   min    25%   50%   75%    max  \n",
       "dataset                                            \n",
       "I        2.031568  4.26  6.315  7.58  8.57  10.84  \n",
       "II       2.031657  3.10  6.695  8.14  8.95   9.26  \n",
       "III      2.030424  5.39  6.250  7.11  7.98  12.74  \n",
       "IV       2.030579  5.25  6.170  7.04  8.19  12.50  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([\"dataset\"]).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 피어슨 상관 계수\n",
    "* 피어슨 상관 계수는 두 변수의 공분산을 표준 편차의 곱으로 나눈 값이다. [출처 : 위키백과]( https://ko.wikipedia.org/wiki/%ED%94%BC%EC%96%B4%EC%8A%A8_%EC%83%81%EA%B4%80_%EA%B3%84%EC%88%98)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.816421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.816421</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "x  1.000000  0.816421\n",
       "y  0.816421  1.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 소수점 3자리까지는 상관계수가 같습니다.\n",
    "df[df[\"dataset\"] == \"I\"].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.816237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.816237</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "x  1.000000  0.816237\n",
       "y  0.816237  1.000000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"dataset\"] == \"II\"].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.816287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.816287</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "x  1.000000  0.816287\n",
       "y  0.816287  1.000000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"dataset\"] == \"III\"].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.816521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.816521</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "x  1.000000  0.816521\n",
       "y  0.816521  1.000000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"dataset\"] == \"IV\"].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952bbbf410>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 메소드의 괄호()안에서 Shift + tab키를 누르시면 문서를 보실 수 있습니다.\n",
    "sns.lmplot(x=\"x\", y=\"y\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952bc43d50>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HejhC9MlAmxv6noubSeI7Vp8Wxh3bRTOiVFfNGuyQxzw3Z3LutZYajXi87XrJiuVU3rSBoiWLMIqK0ILBC9xF9EYe7glRIANtbug5Fm42Ca6L6TukrAyu1/0aie+DaTrkbJeSCf7UxUmlqXvxJepfegk33aFGY+XlVG64kcjsWeixIvRwaGQHOk5IeAhRAANtbtixfiPjmmStbI/rG47rkcs5OP1cQxlvrKYm6rbv4Nxrr+GZ+f/fimEw+erVVNx4A6GpleixGFo4LLUaQ0jCQ4ghNpDmhvn+VGl8K4vte6SsLLbXc/CYlkPWcpnI6+a52lpqtz5P46638N38zEwLh5l83bVU3LAGY1IpejSKHo1KaBSAhIcQQ2ggzQ19z8FJJ8G1yXk2KSuD53e/Ddf3fdJZG8eduKmRPnGS2q3biL+3p22XgF5cTMUNa5ly7SfQohH0WAw9EpFajQKS8BBiiDjpNHZzol/bnlr7U3meR8Y1yVhZeppOWLZLznJaC6EnFN/3SR08SM0ftpHcf6DtemDyZCrXr6P8qlWowQBaNIoRjUpoDAMJDyGGgJVI4qb619zQzeXXN2zfJ2X3vJvK9yFnOph2/woLxwPf82je+z41f9hK5kTHGo3pVG5Yz6RLL0HRdbRIBD0akVqNYSThIcQgDKS5oe97+W24ttnrYyrX9chOwEVxz3Foems3NVufx6ytbbsemz+PypvWU7x0KYqqooZDGLGYhMYIkPAQYoAG0tzQd22cTBLPdUg7ObJ2jgs9psqazoQq/nNNk4bX3qB2+wvYTU1t14uXL2fqTeuJzZsLioIaDOR3UEmtxoiR8BBiAAbS3NCzTNxcAtt1SVoZHK/79/q+TybnYDsTZ3HDSaepf+ll6na8hJtuKahUVSZdfhmV628kUp3vxq0EAhhFMbTQ+KzVWLVqFTt37uz253bv3k00GmXJkiWD/px4PM5LL710wTZRvZHwEKKfBtLc0M2lcXNpMq5Nxuq5qaFju2QtB3eC5IYVj1O3/QXOvdqhRkPXKV99FZXr1xGcPDl/LWDkd1CFJ+5xV7/5zW+46aabhiQ8Dhw4wPbt2yU8hBgu/W1umG+jnsKxTVJOBvMCvalypkPOmhiL4rm6Omq3PU/jm7vaajTUUIgp119Lxdo1GK2NUXUdIxZFi0TGZa1GNpvlwQcfpL6+nurqahzH4fDhwzz88MO4rkt9fT0PPPAAFRUVvPLKK+zbt49Zs2axc+dOfve732HbNpqm8eMf/xiABx54AM/zyGazfPvb3+aSSy7hiSee4Omnn0ZRFFatWsUDDzzAP//zP3Pw4EEef/xx7r333gGNXcJDiD7qb3PD1jbqpmO1tBjpvmjQ8zwy2YmxKJ45+TE1W7cRf/e99hqNoiIqbljDlOuuRWudWegaeiSKHo2M68OY/vM//5Pq6mp+/OMfc/LkSX7/+99z8OBBvvrVr7Js2TJ27drFT37yE/7t3/6Na6+9lptuuonZs2fz7LPP8stf/hJN0/jmN7/Jq6++SnFxMZMmTeL73/8+x48fp6mpicOHD7Nlyxb+4z/+A8Mw+Mu//Etef/11vvzlL/PrX/96wMEBEh5C9GogzQ09K4uTS5K2L9xC3bZdMuN8UTxfo3GopUZjf9v1QHk5lTfeQPnqq9o726rKhCrwO3r0KJ/4xCcAmDlzJpWVlVRWVvKzn/2MYDCI7/s453UqUFWVUCjEAw88QDQa5fDhw1xxxRVcd911nDhxgi9/+cuoqspnP/tZDh06RF1dXdvZSalUipMnTzJnzpxBj13CQ4gL6G9zw9Y26o6ZIWGnsZ0LtBgxW1qMjFNtNRpbnydz/Hjb9dC0aUzdcCOTLr+sPSAUBS0awYjFJkRotJo3bx7vvPMON998M2fOnKGuro6/+7u/Y/PmzSxdupQnnniC3/3udwAoioLneezfv59nn32WZ555Btu2+cxnPoPv+7z55puUlZXx2GOPcezYMR544AG+//3vM3v2bH75y1+iqipPPfUUF110EclkEm+Q1aYSHkL0oLW54d6PzrBt10nOxbNMLg2z/sqZrJg3ucvrW9uo5+zsBR9T+T5kcva43U3luy6Nb+2mdtvz5M7WtF2PzpvL1A3rKV6+rH39QlFQw2GMWHRC1mrcdddd/M3f/A133nkn06ZNY9KkSdx+++187Wtfo7S0lGnTptHQ0ADAxRdfzI9+9CO++93vUlZWxp133gnkD8+rq6tj7dq1/NVf/RVPPfUUjuPwhS98gcWLF3PDDTdw99134zgOs2bN4rbbbqO5uZnDhw/z6KOP8qUvfWlAY5fzPIToRmtzw/cP1PDk1gNoukJAV7EcD9fx+dMNizoFiGdbuLkkaStHxkr3+JiqkOsbJUUlI3qeh2dZnHvtDeq2b8dq7FCjsWwpU2/aQGz+vPYXKwpqKJQPDTmMaUySmYcQ5+nY3HDbrpNoukLQyD9KCRoaJi7bdp1kxbzJ+L6PZ2awc2nSvZz0N17XN5xMhvqXXqZ+x0s4qVT+oqIw6fJLqdywnsh53+ypoaAU+I0DEh5CdHB+c8Nz8SzRUOdn8AFdpSmRa6kWT2E7JkkrjdPDYypoaaFujq/1DSveTN0LOzj3yqt4Zj40FV2n/KpV+RqNKVM6vV4JBFpqNcZngd9EI+EhRIvumhtOLg3TnMq1zTwAFAUWTA3hpONkbIv0BYr+fB+yORtrHK1v5Gs0ttO4cxd+y04gNRRiyrXX5M/RKCnp9HrF0OUwpnFIwkNMeL7nYTUnum1uuP7KmTy59QAmLkFDJaQrBH2LKxeUk7DS5GyLnnpTeZ5PJmuPm/qNzMenqPnD1s41GrEYFTesYfJ116JHIp3fMM4L/CY6CQ8xofXW3HDFvMmwAXa8/TGebTI5ZHPZkkomlasXXN9wbJfMODh7w/d9UocOU7t1G4kPP2q7Higry5+j0bFGo5Wmtp/gN44L/CY6CQ8xYfW1ueHyOZNYUhXAs3JkXZu0lel9fWOMHxHrex7NH+yj9g/bSB871nY9VFVF5Yb1lK28rGs9hqqgRWMY0YlR4DfRSXiICamvzQ09x8LNJnFdt2U3Vc+PqfJHxDo4Y7iroe+6NO5+m9qtz5M7e7btenTOHCpvWk/J8mVdZxMtBX56NIqqy5eU0WzRokUcOHCg9xf2gfxOiwmnr80NXSuLl0tiux4pK4vt9VwtPta74XqWRcMbb1K7bTtWY2Pb9eKlS6jcsJ7Ygvld1y0URQ5jmsB6DY/77ruPu+66i6uvvno4xiNEQfWluWFrixHfzGD6Dkkz3eNJfzC2H1M5mQznXn6Fuh0v5f+/QL5G47JLqdxwI5EZM7q+SVFQg0H0WFRqNQpg90e1bHnxMLWNGSrLImxaM5+VSypHelhd9BoeGzZs4F/+5V/47ne/y6c+9SnuuOMOSktLh2NsQgyZvjY3zLdQT+LZVsvZGz1Xi+cfU9k47thLDbs5Qd2OHdS//CpeLge012hU3LiOUMWUbt+nBAMYRUUSGgWy+6NaHt2yF11XKArrNCWyPLplL2y6aNQFSK/hceutt3Lrrbdy5MgR/vu//5s/+ZM/4ZJLLuHTn/40F1100XCMUYhB8V03vxW3l+aG+aK/BJ7rkupDtXh2DO6mMuvrqX3+BRreeLO9RiMYZPK111Bxw1oCpSXdvk8OYxoeW148jK4rhAL5L82hgE4Ohy0vHh574QH5fjwnTpzg+PHjOI5DeXk53/nOd1i9ejVf+9rXCj1GIQastbmhb/W8XgHg2SZuNoHjeSStDLbb8+vH4qFNmVOnqN26jaa33+1UozFl7fVMuf66rjUarXQdIxZDi0iB33CobcxQFO78ZTloaNQ1dq1BGmm9hscPf/hDtmzZwowZM7j77rv5p3/6JwzDIJPJsHbtWgkPMWq1NjfE6XlbLYBrZvCyKUzfJWWlcb3ug2EsHtqUOnyYmj9sI7Hvw7ZrgbJJVKxbx+RPrO65KaGu5Ws1IuP7MKbRprIsQlMi2zbzADBtl4qyHsJ9BPUaHo2Njfzrv/4rixcv7nQ9Eonwgx/8oNcPSKVS3Hnnnfz0pz+lurqa119/nYcffhjTNPnkJz/JAw88MPDRC9GDjs0Ne5JfGE/hmlky7oUPbTJtl9wYaWro+z6JD/ZRs3Ub6SNH266Hpk6lcsONlF2xsuc6jAl2GNNos2nNfB7dspccTr4Jp+3iOD6b1swf6aF1UdCW7Hv27OHb3/42x44d47nnnmPy5MncfPPN/OpXv6KqqoovfelLfOYzn+H666/v9V7Skl301fnNDbvTujBuWTlSdrbHx1Se55HJOaN6Ufx0fYp9RxsoKy4merqRuTUfwLm6tp+PzJ7F1A3rKbloRc+zCFVBi0YxolEJjRHWutuqrjFDxVjebTUYTz31FA899BAPPvggAHv37mXWrFnMaNn+d+utt/Lcc891CY9EIkEikeh0raamBiF6YyWSuK1bTnvgezZOOknaypK5QFPDsTDbOF2f4q29J5idPcTs95oIZ9sf0RUtWczUDeuJLVzQ83qFoqBFIujRiNRqjBIrl1SOyrA4X0HDY/PmzZ1+XFdXx5QObZorKiqora3t8r7HH3+cRx55pJBDE+NMvrlhM17mwjuqPMfCysRJmmmsHo6IHQuzDYBkUyNNb7zAmtNxwmZ+rD5wpnQGZ2dfwhe/uKHnN8thTGKQhrXCvLsnZN19R3TvvfeycePGTtdqamq45557CjY2MXb11tywlWtlMTMJEmaqxyNix8Jso7G2hoZdLzP1ZIIFdn6grgqnpkeoq1zHOaWYTK7n3WByGJMYCsMaHpWVlZw7d67tx3V1dVRUVHR5XXFxMcXFxcM5NDFGebaN1dSEb/e8o8r3PdxcGiuXIWF1HxxjYbZRc/woqXfepOpUmpktT9psHU5Uxzg1aQFV1UuwkkGs5hzlpV3rMZRAAKMohhaSw5jE4A1reFx88cUcO3aMEydOUF1dzbPPPssdd9wxnEMQ40hfmhvm1zdSmE6ux224o3228fGBfdh736XqTJZJLWPMBhTOzilFX3QlB06YaC0zeNN2cR2f9VfObHt/62FMPdZyCDEAwxoewWCQ73//+9x3332Ypsn111/PzTffPJxDEONEX5obthb+pW2r2zYjo3m24fs+x/a8jf7RPipr29dmUmGV2nmTmXnVWpbE8rPzSFF+t5XtOBRHYtx01Zz8OSRyGJMooIJu1R1KslVXtLKTSZxk6oJbcV0zg51NkXIymN20GbFsl+wonG24jsPR3a8TOXiUyY3t54zEizQa5k9l7qq1hELdtwgpKSqhumpWy2FMMfSoFPiJwpGW7GLM6EtzQ9/3cbMpLDNN0kp3ObRptJ65YVsWx958iZIjHzOzuf3R2rlJOomFM1lwxXVU6hfeSqtqOlpRkRzGJHrU8TyPwZ7tIeEhxoT8jqrmtg6w3b7Gc3EzSTJWmpTZtX7Dsl1yo6yZYS6T4cQbL1B+tJZZ6faB1UwxMJcuZN6KK5neywFLmqajRyPo5ZMIFBcVesiiwNJH3qH5jadx4nXopRWUrL6d6LzLRnpYXUh4iFGvL80NPcfCziRIWRlydo6Oh2v4vk8m52A7oyc1UvE4p9/cQcXxBmbnOtRoVAVh+XLmLuv9i4WqaRiRCH4oiNNjqaMYS9JH3qHhuZ+DpqOEYjippvyPb/78qAsQCQ8xqvWluaFrZshmE6TNro+pRttso7G2hnO7XmHqyWZmd6jROD09QujSy5k7d3EvdwBV1fKt0cMhHCW/FVmMD81vPA2ajmrkt1MrRgiPHM1vPC3hIURf9dbc0Pdc7EySlJkkZ2U77aYabbON2hMnSL7zOlWnUsxqWdKwNTg9q4jSy1ezYPqsXu+hqCp6KIQaCeOqCp7njcnTC0XPnHgdSijW6ZqiB3HidT28Y+RIeIhRqbfmhp5rk0k1ks6lusw2UmeOYR57Dz+bhHARavUK1LJujlMdBqcPfoi55x2qzmQpbfml5AIKZ2aXUHnldSya3HsPI0VR0IMh1GgEV1OwPa/X89fF2KSXVuCkmlCM9kJO3zHRS7sWU480CQ8x6vTW3NDOZUimz5Gzcp1mG57nkzx9FPvAa6BooAchl8E79DosuOn+rOEAACAASURBVHpYA+T43rdR9u1jam37NuFUWKV2bjkzr1rDkqLej3JWFAUtEESLRSU0JoiS1bfT8NzP8cih6EF8xwTXoWT17SM9tC4kPMSo0VtzQ9/3yKSaSWYau7QYaa3bsE/ubQmOlm2tugEOeKfeL3h4uI7DsXfeJHTgMFUN7TUazTGNc/MrmXvVWpaG+lblrQeCaNEIrqFje66ExgQRnXcZ3Px52W0lRF+kj7xD4u3nsRobAYXYxTcQmbms02scO0cy2UDWTJ832zivSjybzM84OtL0/PUB8ho/xjv1fv4e3TwGcyyLo7teovjQx8zoUKPRUKrTvHAGC664jgqjb51rNd1Aj0XxAkZLaIyt427F4EXnXVawsOhY1zGYGg+Q8BAjLH3kHZpe/g2u5ePmsviuRfyV/4JrITJzGb7vY2WTNKcbsM9rod5tlXi4CHKZ9pkHgOvkrw+A1/hx/rFXN4/B7HA5x9/YQfmRmi41GrnF85l/8VVM66VGo5Wm6+jRKF4ggO17Ehpi1JPwECMq8e4O7KwDtoWiKCh6EA+T1J4XCFcvJJOOk8wkOj2m8jyfTM7utieVWr0i/8XdIT/jcB3wXdTqFQMan3fq/S6PwVIZqH39dSpOpZidaw+N01VB/GXLmLf88j7fv7XAzw8GcPDxfQkNMTZIeIgR42Qy5E6dwEfp1LhPDURBUUk215PKpTuVv/XWk0otmwELrr7gY6Z+6fAYrNmEhroMU0+l22s0FDhdHSZ48WXMnb+0z7c9v8BPajXEWCPhIUZEa3NDNRjByTSj6EEUzQA9AAGDtKJg51K0FjL4PmRzNlYf6jbUshlDtzgeLqI+niN1LkPV6WznGo2ZMUouv4oF1XP6fDtVVdHDYZRIGBfwJDTEGCXhMQE0vv0OZ377NLnaOkKVFUzbeDtll4/M7o3zmxvGLllH8xtPowRCoGq4CiTTTQTmXUprcDiOS850cYZ5x9GpQx9hHWxk6uksZR1rNGZEmLJsBYvm9v1RmKKq+VqNSBhXaynwGyJHkqfY2fA+qm5QcqyI/7NwLZdWLR+y+wvRHQmPca7x7Xc4+ujPUXQdLRbDbGzi6KM/hy99fsABsvujWra8eJjaxgyVZRE2rZnPyiW9F7t119wwPH0h/hX/h9SHr5GzTTK6SmjepQQqZuH7YFkOWdsd1krq4++/g/LBB51qNNJhlZoZUaZVRFk095I+z2zyBX5B1GgUV1OHfNvtkeQptta8gYZGRTBKczbBY28/yecuRwJEFJSExzh35rdP54Oj5ehRLRTCzeU489unBxQeuz+qZeuWZ1mvvEepkiTeVMTWLZfAplsuGCCtzQ090wTfwfd8PMvEt7NoZdPQr7oV3c5R3JISlu1iWg7D1TnddRyOv7OT4MFDVJ1rr9FIxDTq+1mjAYCioBuBfIGfrrYU+OWfeXn1R3GPvQWZZoiUoM25AnXK3AGNe2fD+2hoGJqOoigE9QC2Z/PM/m0SHqKLnlqyD6Q9u4THOJerrUOLde6VowaD5GoH1itn59Zt3MwruOjkCBEjy828whtbg6xc8mfdvsezLMzGJtxsCs/MgNu+o8j0XVJWpm03leN65MzhO93PsS2O7nqFokMnqY637+hqLNVpWljN/CuuY4oRvMAdutIDAbRoFFfXsX2Xjl0ZvfqjuPueB0UHPQTZdP7Hy24cUIA020mCahBD1dEUFQ+PgBagLt3Q73sJ0R8SHuNcqLICs7GpbeYB4JkmocqB9cpZktqJi4aj5LeuOhjg+yxJ7QS6hoeby2E2nMNJNYPT/h29B6Rds62hoe/7mKZLzhmeR1RmNsvxN3dQdqSGWan2MKudbJBdNI/5l66mqo81Gq3aC/z0/Eyjm2237rG3WoKjcwW8e+ytfoeHoqhMj07FxUNXdWzXxlZcLNeiIlrer3uJ0ePdsx/wzP5t1KUbqIiWc9vi9aNyFinhMc5N23g7Rx/9OW4uhxoM4pkmvuMwbePAeuWUqSkyXoCOJ2Lb6JSpqS6vtVNJzPo6vFyq03N+y/dIW1lsL1/0N5xt09OJZk69sYMpxxo61WicmRrEXbaUecsv7/d5310L/C7wC8k052ccnW+Qv94HqqKiaTphI0RQM7h+2lX897E/oAABPYiHg+253LZ4fb9+DWJ0ePfsBzz29pMYqkbMiBDPNo/aNSwJj3Gu7PLL4EufH7LdVuHyqVj1dTiegaLkt9DqOITLp7a9xvd9zHO1WA31nR5R+UDGtclY+VP+HNslZw3PLqr4uXpqd77I1BPNzLbyn+cpcHp6GOOiy5izsO81Gq3aazVCOHh9K/CLlEA23bUCPlJy4c/RDEJGkKAeQQ+E8RUdX9VZFKvkdj3IjpMv0WQ2MbVo8qj9TlX07pn92zBUjWBLbVFQD4Jjjso1LAkP0S/V6/4E9ZlHSeRccp5KSPUoDulMW/cnALiWhVl7BicR7/Q+D0g5OXJ2Dt/3yOacPtVsDFbtqZMk3n6dqpNJZrd8bXc0ODUjRvHKq5jfjxqNVqqqYUTC+dBQ+lcVrs25Ir/G0akC3kGbc0X+BS2zHk3TCBhhwuEYhhZB1QL4igI+nP9py6cs4fJpKwiHNMLBC59zLka3unQDMaPzxozRuoYl4THODfVW3ei8y5h225eItnX9nNrW9dNKNGPWnsW3Op8zbvouaSuD7TpYtkPOcnusEB8qpw8dILdnN1WnM23naJiGwpnZxUy54hoWVUzr9z3zhzGFWw5jYkCHMalT5sKyG9t3W0Unoc9dhV61ANUIYxhBgnqAgB5GVfW2J2AetH2WAmiqQiigEwxoBAwNVe3fozYxOlVEy4lnm9tmHsCoXcOS8BjnhnqrLnTt+ulZJrmzp7CaGqFDxbTrQ8bNkbOzmLaLNQyPqE588B7+B3uZWmO2rctkQgpn55RTvXoNi4sn9fueiqK0hEaopVbDY8AHhqsq+vQlGDOWo6gqimpgBMKE9BC6aqAqWluwdlw6URQIaBrBoEbQyAeGGH9uW7yex95+EhyTgBbAcq1Ru4Yl4THODfVWXcifq+FbOTzbxrNN7HgcN5vtdOpf62wjY5oFDw3XcTj23i6C+w8ytWONRlTl5IxyylZ8gqXTp/T7vh0L/Ly2Ar8BpIaqoukGGCF8zUBVVAJ6gKCW32LbMTA6zsgUBYK6TjiUDwxNU/v/2WJMubRqOZ+7nILttuqpJftA2rNLeIxzQ7lV1/d9vGwKz0zli/xcDyeRwDPbW6W3bsHNmBnSWRungFV+jmNzdOcrFB06wYyONRolOiemTaE+tAhPUThxME4gEGb6lNgF7tZBpwI/bWDnaigKqqajBIL4WgBVNQjoBkEtmJ9hoLY98eoYGKoCQUNvm2HoEhgTzqVVy0fd4nh3JDzGuaHaquv7Hm6qGc/KAgquaeMkE/jOeQV/uTQZ0yRnF25dI1+j8SKTjpztVKNRN9ng46pp1GqzCOgGKpD/0uux72hDn8JDDwTQIhE8w2gp8OtfaCiaimoEQA+h6kGCWoCAFugaGB3eoykQChoEAypBQ5f1CzEmSHiMc4Pdquu7Np6Zw7Oy+G6+FbqTTuOm023fMrs+ZJwszdkMpmUXrKVINpngxBs7qDh2jtnZjjUaAdylS5i34gp2vXiYoNZ5PUBTVFIZ6/zbdX6NbqBHI3jBQH6m0WEHVWvjwWY7SYlRxKryFcwrqm5/s6qg6QEUPYgaCBHQggT0AIYSQEHpEhjnL3gHA1q/a0uEGGkSHhNAsBTKFoMzFfTS/I/7ws2l8LJJ/Jb1Cs9ysJNJfLt9XcH0XeKZJOmsWbB1jeaGemrffInKE3HmdKnRuIQ5C9un+EWRAFnTRlfaH/e4vkcs0v0xsF0OYzpvptGx8WBQDZKys2yteYMNytUsKJmJGgijBkIEjUh+hqEY3QYGgKZCOGgQDGiEAkP3Vy995J0xcea1GF8kPMa59JF3aHju56DpKKEYTqop/+ObP9/lC4zv+/iujW9beHYO3279bl3ByeZwEsm23VSuDwkzTTydwXYHd/rd6foU+442kMxYFEUCLJtbzvQpMepPf0x892tUfZxkVsuShqPB6RkxYpetYv7Mru08ls0tZ+cHZwEPTVFxfQ/X9Vk2t/NWx74extSx8SBAQNPxFYMPUse5dPZqjJbAoEPNfcfAUBQIB3RCwXxgDPUMoz+/v0IMpREJj6effpqf/exnAFx33XV8/etfH4lhTAjNbzwNmo5q5BfMFSOER47mN54mOu8yfNdpCwrfsVpmGe1f/nwUnGQaN5N/TOV7kLYtGrMpctaFHwX1xen6FDs/OIumKQR1jaxps2/P+2TjR5l2JkNxy9d001A4M6uYyVdcw8LKnms0pk+JsWp5FfuONpDKWMQ6hBHkC/z0cBjCQRxF6fUEv9bGgwHNIGiECOkhfBSazWbCetc1FAXQNRVDVwkYKqGAXtBdUr39/gpRKMMeHtlsls2bN/Pcc89RXFzMXXfdxeuvv87VV1893EOZEJx4HUqo5YucqqFoBmowiu9aOMlGPNukp5Vtz/Vwkkm8XP41Gcclnk2TNnP4Q7Qavu9oA5qmoKsqsdxpZp47RtV5NRo1c8qYvmoNi0vL+nTP6VNiXRbH2w5jioZx1ZbDmHr5NWi6zvSiabj4GJqB6dgk7SxZO0txoKj93goYmkrA0Ib8kVRvOv3+to5HD+LEB74VW4i+GPbwcF0Xz/PIZrNEIhEcxyEY7NzyOpFIkEgkOl2rqakZzmGOG8bU2SSP1ZA81ISTMtEjBrE5YaLVk/HOqwRv5fvgmVbL+oaD6bqkTItELoPjOd2+Z6ASqRxV7ilm1H9MZX37WkoyqlI3r4I5V93Akkh0wPfP12qEUKORPh3GpGg6oWCYYLgYQ49wneKz5eDToCgYqoHt2biew42z1xALGQQCKgFDRxuhHVJ6aQVOqgnFaN+K7TsmeunAuiaL8a313I67776bu+++m1tuuaXt5zKZDGvXruX3v/89ZWW9f6M27OERi8W4//77+eQnP0koFOLKK6/ksss6T68ff/xxHnnkkeEe2pjn+z64Dp5t4tsmvmvj+hU0vv02qKCoCnYmR9PeLNH5V3Z9P+BmTdx0Gs+yyTkOOdMh5VotPamGbkHcdRyO7HqFq08dp7ypY42GxsmqKTQXL2HD1fMHfH9FUdACQbRopMthTOdTVY1AMEQ4XIxuRNHVQFu+LCpfxO0LbmXHyZdozDUxJVrGLQtvZNXMiwc8tqFUsvp2Gp77OR45FD2I75jgOpSsHljXZDHyhuPY6E2bNvHss892Co+tW7eyatWqPgUHgOIP5VeEPti/fz/f+MY3eOyxxygqKuKv//qvueiii/j85z/f9pqeZh733HMP27dvp7q6+vzbTii+6+A7Dr7n4LsOeC5+yz/55Yr239L9/8//i1lfD25+q62i6aCFCU6ZwuIH/7LtdZ7n4yRSuJkMWdvBstyWKvHskM42rJzJ0Td3UHbkDCXJDjUa5TofT62i1piD76usWl7V96K+89Q4cT6yz3DGjaOjceX5W2vJL5gHjCCRcDG6HkUzgt0Wj6tKfodUaBRvqZXdVuNHx150Heuy5g7i2OiOWmce6XSatWvXsnXrVkpL89svP/vZz3Lvvfdy/fXX9+lewz7zePXVV1m9ejXl5fndL5s2beKJJ57oFB7FxcUUFxcP99BGHd/Pf7fsu24+KBynZVHb7fV5fSvzXANaNIaitD+jz7dMb+nSqSi4ORMnkSSTzZHLObhAxjMxbXPIZhvZZJITb+5gytF65nSo0ThbGSAxbwFn/WmkMzaxcOcF7v7QdINaNc2O1H4ytommqmQ9K7+1ltUsKJnZEhhFGEYEVQ/j+fkwOD84dFUhEtKJhIxR3xbk/F5jYuwqRC+67kSjUdatW8dzzz3HnXfeSW1tLceOHePaa6/t8z2GPTwWL17MP/zDP5DJZAiHw7zwwgusWLFiuIcxKrTNFtyWsyA8r+Wa0/bf588k+is4uZxcbT1uNovvOPk/mOEw4WlTWxbEU2STKbI5B9cHB29IZxvNDfXU7HyZyhNNzDHbazTOTAujX3Qxsxflf+8vGsRndDyM6YXjr5O2c/kzvVEoCobQVI1j5lk+MWk1SiCC5+eLCM9f+mhtDRIKaoSDQ7+tVojeFKIXXU/uuOMOfvSjH3HnnXfyP//zP9x2222oat+/URr28Ljmmmv48MMP2bRpE4ZhsGLFCr74xS8O9zCGje+5+cdMroPvum2PmPCc/Hf1gwyH3sQWLyB58Eh+S5Cq4Lsemu9TtHwJ6do60mkrX9ynqOR8k6yVHZLZxrkzp2jc/Vr+HA0nfz9HhdMzokQvvZJ5swe+ntFK1TSMaBQ/GGw7jCluJSgOFOVP2tMDOK6L6TkcS5zBN4raJmwK+bAIGDqGrmDo0tpcjLyhPjb6QlauXEl9fT1nz57lmWee6fc684jUeXzxi18cd4HRGhJ4XoewsPv1iKkQUvsPoRcX4WXzva30kmI8x+Xcm2/jzZ4HCviKT8rJYDvmoD/v7NGDZN7dTdXpNEWdajSKKF95DQunTh/0Z6iahhEO44dDLQV+LpqqETACzC+dTdxM4voecTOFh4LlWkwKTUJRIGToBAMqhq5h6OqIzC52f1TLlhcPU9uYobIswqY181m5pHLYxyFGn6E+Nro3Gzdu5Cc/+QklJSXMnDmzX++VCvM+8H0P3JZF6ZYzqn033//Id538v9tq60YuKLpjnmvAKC5CKSlGKynBbGjEc128eBpFUTB9h4ydxhtka5ETH+7Be38vVWdztO7VyAQVauZMYtpVa1hcOvjDbFRVRQ+HUcJhXCW/oyqkB/OtzTUDQw9weeWl/Obw/6KpOoZq4HgWnu9y66IbqSyLjtiW2la7P6rl0S170XWForBOUyLLo1v2wqaLJEDEkB8b3Zs//uM/Zt26dWzevLnf753w4eH7fv4RkueB13KkqO+3PGJyetzFNBZYjoteVobdnEAxDBTPz//aHButpISEkx3UbMNzXY7veQv9owNMrW+vNk9GVOrnTWHW6rUsiRRd4A55J9M17I0fJGmnKTKiXFS6kJnR9jPR2w9jikBAw1ANYmogHxCaDoEwvhbAUzQWhy5ik2rw4sf5rbUV0XL+eOmGUdPiesuLh9F1pa2QMBTQyeGw5cXDEh4CyAdIocLi/HM7pk6dyr59+wZ0r3EdHvlgaF1j8PF9J//v8xelYUyGQ3d8zydrO2Sz+e62kWuvpem3T6P4Pj4+nm3ng/Gy5QMODtdxOPLWK8QOHmd6hxqNpmKNpvnTmXfVGiYHghe4Q7uT6Rpeq38XFY2AGiBt53it/l3gUmZGp2IEQxhFRRjhMLqio6OhouTbngfCeFqAjn2lDE1l9eyLuWHh5aNyl1RtY4aicOe/dkFDo64xM0IjEmJgxnR4tM0KWkPA81pmEB1mDDBuguFCXM8jZ+aL+pwO204jSxYDkHzxZXzThGgU7RMrUWf3v1bGypkc27mD0sNnmNWhRqO+TCe1cA4LVl7DVL1/f6T2xg+iomG0tFE3NA18nZN2PRdVXIYeDqP5Gorvg6KgBcOgh/FVvb3FeUvzwUhQJxgc3X+kK8siNCWynVqYmLZLRVlkBEclRP+N7r9p3XDTzdjNwfyMYhh2K41mjuthWg6W7WG7Xo/r8tGlS9CWzscyM/j19f3eTZVNpTjxxg6mHKtjdqZzjYa9eDHzL7lywAvPSTtNoOURVFAzKIoUE4hEqfPSBINRcH00Q0UJRvD1EB7ts4nWWoxwyBgzJ+5tWjOfR7fsJYdD0NAwbRfH8dm0ZvC7z4QYTmMuPDzbxHfs3l84hmVP7iP53nbcRANacTlFl6wjPHMZAJbtYDter4EB+bUCR/FJ2WksO4fRz4xNNDVw9s0XqTx+fo1GCHX5xcxZMpjqjPz4KiLlePhEjAhqJESzanMue5aIHkLTjQ6h0fqe/I6pcKgwLc4LbeWSSth0EVtePExdY4YK2W0lxqgxFx6j0QdHzrF110kamrOUl4TZcOVMls+bPKB7ZU/uI/7Kf4GmoQQjuJlm4q/8F+ZVLt7kBTiu37d5lgppN0fWyuL10nb8fA01p2nY9WqnGg23pUYjcskVzJuzoP+/sBaKoqCpestJexqrp1zMK4kPaQi45Jw4GSeHi8ets26GWBme39LmvGWWEQoaGPrYmGX0ZOWSSgkLMeZJeAzSB0fO8eS2A2iaQjSokUjleHJbfkfDQAIk+d520DRUPQj4+GoA1zVJ7dmO0YdHG4qiYOKQMtO4bv+qxM8cP0LmnZ1MO5VmVkveWLrC6VlFlF/xCRZMHVhPMVVRUFWdYEtgaKj59YtQiLnlU7BTMbbX7CThpCkPl7Fm5lqWTFlCQNMIBlQCAZ2gofX+QUKIYSPhMUhbd53MH2TU8sUtaGiYuGzddXJA4eEmGiAQwfV8vNZnUpoB6aYLvq/1EVXaTmPaJv1ZBzq5/33cve8x9WyO8pa3ZYMKZ2dPouqq61k8qfOvo7ettQCq2jLD0IIYioqG1nLwkoIWDKJFo/i6Bj4snbKIpdWXgWYQ1PPtQYKGNip3Swkh8iQ8BqmhOUs02Pm74oCu0tic7fM9PM/Ddlxs28ePlOJlkmB0OHPbsSE6qecbqAoZzyRjZvKHHJ3HOXAU99WdeKqG7diolyxHnTWdo3vewvhoP5V159VozJ3CrKvWsiTWtUbjQltrZxdVoakGQS2A3jLD8H0P/HwVux7Mt0j3jQC+76MFghCMoWr5BoRjaeFbiIlOwmOQykvCJFK5To9VLMejrCTc85t8H8t28wvfTueFb2XR9fDO/wc2oBv54PAdtEVd2yQrqorlO6TNNLbb/SYC58BR7Ge3gqZDxRTceJyje94k9kqK6sb2x1rxIo3GBdOYe+VaJod6rtHovLVWIRoIo6kqp8w6Lipf1DkwWpa5tUAAPRrFNwx8RUELhlCMMEYw1NKE0JCeUkKMMRIeg7Thypk8ue0AJi4BXcVyPFzXZ8OVnfvEOK6H47jYjo9pO7g9rGGrVYvhsj/GPfBS/lFVdBLaouvz11spCp7ik3bSmL0c0uS+uhPHV2g2HeJmHeV2gtnH22s0zpXpJBfOZsHKa6nsQ41Gyk4TM2IEjQCGZuB5LqZjcypZg9ohMABUw0CPRiEYRNFUtGAEIxQlFDIIBnSZZQgxhkl4DFLrusbWXSdpbM5SMSnM+itnMX9GKRnTxrHzj6Rcv+/9EdWqxZ3DotNPKuQ8i7SZ7vYR1fkSTXHeWxRm1slG5h1pn53UTDGwli5m7oqVTO9DaKiqiqEazCyeTtJK54sS7RQ+PrbrUGK0t5FWdR09EkWJhFD1AHo4SjAcJhwKjPmdUkKIPAmPIbB83mQWz56E7XjYtofluDQlzCEtXVQUBVtxSVkZbMfq9fWJZII39+/gwIYAad1nztF8jcbZqUFcDCbFfWZdetUF76GpKoZmENAC6KgoKCyJzWHr2TfQFQ1d1XA8F8d3uXLyChRNw4hE0aIRlFCEYDhGOBIkNMqrvoUQ/Sd/qwfI9TxsO/8YyrKdfs0s+stXFVJullwfztqoP1fHrqMvcyjcTC6qAiqq77P34lKUoypTP24A2yQVjHb7/s6BoaFA22f6+MwrqmYDq9l17n3idpJSo4jVlZeysHIBeqwYLRIlFI0QCgVlliHEOCbh0Uee52M7TktYuDieX/hjOlQV07NI5zK4vZzsd/rsx7z18ascjmRxYgqgYng+8+oVFnyYpro+S6R8MlkVsmEF3Wt9hKWgqQoBPUBANdA6BUb3BYnziqqZV1SNoqoY0ShGSSlatJhwNExETuATYkKQ8LgAx82vV+Ss/M6o4TrTKf+IyiNtJ7DsCz+iOnLiIO/W7uJo1MKLKYBC2PVYmJvEqgVraH7xCYy0STxmYBcZmKaOavs4MYNwINTnwOg0PlXFiEYwJpUTKColHA50avQnhBj/5G98B47r4bru8M4uzuOrCmk32+txsPsOvsf7zXs4HvUgBqBQZHssciq5avH1xKL5Go1XlsVYvdPEdj3wfQwPNFQ+WjyJ5Wqoz4EBoKgagVgMY1I5RlEx0XCAgFR+CzEhTejw8D0f23Exba/g6xa9UhQsHFK5dI+PqDzX5b39u/ggt58zYaBl2WKS5bHEn8mVS68jFOxco5GeU8mhcxbLP0oQTTpkbI8js2Mkq0r63F1XUzX0ohJCZeWESosJBY0RP5FPCDGyJlx4OG5LcZ6V3xU1yNNXB01RFDzFI2VnyPXQVsS2bXbve5UPvWPUhxRoqT+syPksNeazcsXV6Fr3v5XXNZcTOrofK2LglwSwTJXqEwnmzF3Ry8BA03T0aDGRKZOJlBQTDBqD/NUKIcaLcR8ew7krqt9ULthWJJvLsevDF/lIPU08oNJ6Yt70jMLy6DIuvvgyVK3nx0aaplP17glygQgJxULFB0MjrBiE9h6D5Vd2eY+iKKi6gRqKEC0rp3jKJPSAhIYQorNxFx4jsiuqvxQFE5u0mem28+2+mkPsP/oWZ2NZUqH8dlvF95mV0bm47FKWLL3wrEFRFEKBMDE9zOmGJoKRCBVKFCNYih3w8VQXN9Hc5T2qEUQJhomUlFBUXkoweoEWK0KICW3sh4fvYzlunw9IGknnH850vobGel479AJHIylype01GjOSKvPLV3DFspW9foam6RQHYhiKhu/66GVluMkESqC90aLv2GjFJW1jUo0gSiBMpDiWD42iWE+3F0IIYIyGh+242K6HPUrWLfrkAp1vz9R8zFsn8zUadlF7jUZ1UseKFpEs9zlk1HPFBW7fOtuIamEUz29bDC9acx1Nv30aDwsfH8+28V2P2FVXtjUoDEUjFE2eRKg4JjUaQog+GXPh0ZTIYgSHtvVHIV2o8+3RE4d4t3YnRzrUaIRcj+nJIJnSGJnKfIW27vs028kedKKvBgAAFrNJREFUP0PTdIoCMQKKjn9eMEWW5HtkJV98Gd80UWMxSlavJrJ0BaFwiFhJjNCkEtQ+9LcSQohWY+4rhuv155ijEdSyi6q7zrcfHtrD3vh7nWo0Yo7HYquC+iKFpikWRoeOs47nUmJ0PVsjP9sIEdUiLbON7hslRpYsJrpsKYZu4KVNAiGDcCxCsLgILRQa6l+5EGICGHPhMRp5Z/e3t1CPlaMtvQFrysxOnW8912XPgd18kP2Q011qNGZw5dLrCQWDHEmeYmvNG+DS1njQxWVVeedF8gvNNjpSW1uhR2JENFDCGfRYDD0SKdT/DiHEBCDhMUje2f3s++BpXo5p5CaVMFU1WHTwOWbkVqFOmYvj2Oze9xofukepO79GQ5/HyuVXo+vtW2FbGw/ubHifZjtJiVHEqvIVzCvKnx+uKCqRQJiIFgSPHmcbmqahhiIY4RixSJBgUMd3XYhFUFRpWCiE+P/bu/fgKOt7j+Pv5/7sPrub+42AKFiKIMYCyknhFJGjIwIiwTtjmRamMnUs2s5USxlgqFaZXtLpYZxjx8tYD04VCqbiZUq5WANYitpGbqcKiCjkAoHEZC/Z2/kjEAkJliWXZ9d8X/9oNrs8n+zM5pPn+T2/369nXCmPzZs3s2rVKoLBIJMmTWLJkiVuxOgVez76C2/k2mTZAZxEnMPhkxww4vznwW2cOPIh+9VPOWmqYLQPRA8KKYzxjqKsbNx552icWXjwXIZu4jMdjKRK8jx3CWiGjmo5mB4Hr7fzmlPKl8wJEUKIVPR7eRw5coRly5axZs0a8vLymDdvHm+99RaTJ3fdZjXdKYrCPwIWAV0nGGmlLRZBj0J2SGdroI0W/SjQ/lf+pa0aZTn/fo5G98c5c7ZhQyLZ7UpUmmFgeHx4/A4ey0STXfqEEH2o38tj48aN3HzzzRQXFwNQWVmJZZ1/z+x0pCgKcSVJOB7hGG0kW5rQ2lT8bSqfBWLUeeDMHI1hrSZjSyYwbNTXLupYpmHhGN7uzzYUBU030D0OHr8PxzZlL3AhRL/o9/I4fPgwhmEwf/58GhoamDJlCg8++GCn5zQ3N9Pc3Nzpsdra2v6M2S3l9N7hwXiYUDREIpHAEzJRghE+DSSIOl/M0Rjyuc7EYddTOrrr5acLoaoqjunDoxgkzz3bUEA3LBTLi+118DtypiGE6F/9Xh7xeJxdu3bxwgsv4PV6+f73v8/69eupqKjoeM7zzz/PqlWr+jva+SmQVBRCZ03y+/iTA7xbu4NPnDYS2V/M0RjUrNPkWIy7chKl3YxbXAjTsAkYHpSk0mXlW83QUWw/uuUh4DWxZItXIYQL+v03T35+PuXl5eTm5gIwdepUampqOpXHvHnzmD17dqfX1dbWMnfu3H7N2n6mAeFEG6FIiHgixv4DNfyj8f0uczRKWjycyNKJlfq5/qy7o1Khqipe08GjWnDO7beqpqLaDqrpxXEsHNu44Nngje++x9H1VYTr6rGLChk0exa548amnE8IIc7o9/KYMmUKDz/8MM3NzTiOw9tvv83UqVM7PScQCBAIBPosw76mQ2yt+zuNbU3kmllcV3QNV2Rd1vH9s8c0QtEQsWhbt3M0stsSjEwMZsKoyXh6ONnONCx8hoOeVDrN29A0DcX2opgePLaFz2OkdImq8d33OPjU0yi6jubzEWk8ycGnnob7FkiBCCEuWr+XR1lZGQsWLOCee+4hGo0yceJE5syZ02/H39d0iJcObSQSSZCIQ4vWyEvBjdx52Q2MyhlOjATheIhwNExbNMKuPdvZGzvQaY5GQTjJKG0Y46+ciKH3bLnyM2MbtmJ0upOqvTR8YNp4LBOf10C/iHGNo+ur2ovjdLlptk08HObo+iopDyHERXPlgvltt93Gbbfd5sahef2THQRDMbSkjq4qWKqFjsqO4/sY5CskGosSCgfZufct9imn52jop/fRCMFozxVcXXbNl+6jcaFMwyJgeFGSascmI4qmotkOuuXDtnVsy8DQL34wPFxXj+brvEqualmE6+p7lF0IMbANuNHW4+EmHN3Ba1oYmkYkFiUYDfOvE4dozB7NO/u2st+sp8VqXxId4NJWlauyvsGocVf1SgZFUfCYXpzT8zYgiaKqaLYH3fbhODYeS++VFW7tokKCnx0lHgySjMXaz0K8Xrylg3r+gwghBqwBUx6KqhInQaFRRFhppSUapC0UJUkSsy3O4LYYTx98mbD3i300hrWafKPoWoaPGtFrOVRVxWf5sGi/THWmNDTLi+N48KYwEH4h/GOupGnvPqD9PUhEoySamvDfdGOvHUMIMfB8pcujvTDitCXiRKJhYvEYiRNeTvo+Q0mqOGGFnESEzwJxDvm+mKNxedDD+CGTKB09pFfzmIaF33BQk6CoCprlJWl68dg2AadvJvh9/sFuzOxs4sFWEtEYmmmgeR0+/2A33Hl7rx9PCDEwZFx5/O+h15huT+l0d9TZ2u+UStCWiBFuixCPx0ictXjgt4aN5K+7T6L7j/GpP0GT8sUcja+Fsphw+WTycwt6NbOqqHit9ltwlWQSzdNeGigaAcfE5zH//T9ykcJ19ehZWRjZ2R2PJZNJGfMQQvRIxpVHSzTIuiObqGBqe4EooKAQI0FbMkYkGiEWj3W72uz+A7v5R+N7HBsUI3m6NHyxBMNac5k0ZioBX+/fHmwYJn7DQUdF0w3w+EkoOqaukeUzMY2+XazQLiok0niy074diUgEu6iwT48rhPhqy7jyMDQdWzP524kPGJFzKW2JWPslqUSsy2xsaN9H44N/vUdNcA+feZKn52go7XM04qVMGHUdHk/vb4jUvpihF69mnb7t1k9Sbx+kdzx6rw2I/zuDZs/i4FNPEw+HUS2LRCRCMhZj0OxZfX5sIcRXV8aVR8D24/X4aIw0cTJ0qtvCAIjFY7y7Zzt7Yh91P0dj9EQMo2dzNM7H0Ax8loOlGiiWl6ThRdM0/I6Bx+qbY55P7rixfD51CseqXiUeCqF5PJTMmilzPIQQPZJx5dEc/pzmz0P4DE+3xdEWjfC33W+xTzlC41lzNAaFYLQ1km+UXdsrczS6074trAe/7kEzbZKWD00zcLwG3n460zhX47vv0bBpC0Z2NlZREYlIhIZNW/BfPlwKRAhx0TKuPMKxNgyULtuytgRbeGffVv5Pr+Pzs+ZoDG1VGZN1NVeOK+vTXGe2hfUYHrB9qLqB4zVTWoOqL8gMcyFEX8i48nB0m+uK/6Nj4cGTpxp558Ot/Ms+SchzzhyNwmsYPurrfZxIwTZtsiwfqukjado4p5cTSYdl0mWGuRCiL2RcedwyeDIF/gLqGo7xt0Nv86G3pWMfDf2sORqDe3mORndUVcNv+/DaAZKmg2EY+B0Tq4/voEqF3G0lhOgLGVcen9Z+wl8//jMHnQhxX/vttlY8wYhQgGuHTaYgv39+KVqGTcCbhW4HUDSDLMfCa/fvYPiFkLuthBB9IePK49XmdzBzvYCCE0vw9Ug+E74+haw+XML9bKqq4bMcHG82ScPBNA2yfOZFrXjbH3LHjYX7Fsh+HkKIXpVx5YFyZo7GoNNzNDz9dWBsw8Jv+9DtLNCtPp8d3ltyx42VshBC9KqMK49ro6VMHX1zn83R6I6q6vgsL17DQfX6sW3PRe+vcSF27atj3daPqGsMUpTrpeK6yxl/RVGfHEsIIS5Gel5r+RLjRn2zX4vDNCxyPQF8nmzsnDzycvxk+60+LY6n1tVwsjmE36NzsjnEU+tq2LWvrk+OJ4QQFyPjzjx6Q6LhIPFDf4dgE3iz0C67BrVgWKfnKIqC1/ISsAKYThaO34tt9v3btW7rR+i60nEs29QJE2Pd1o/k7EMIkTYy7syjpxINB4nv+QuEWkG3IdRKfM9fSDQc7HiOpurk+HLJzy4mu6iYvLxAvxQHQF1jsMutvpahUd8Y7JfjCyHEhRhw5RE/9HdQdNANUJTT/9XbH6f9MlVhThEFBaXk5uf2+1pURbleItF4p8ci0TiFud5+zSGEEF9mwJUHwSbQzjmL0HSUSCs+r59BhUMpLCrBcWxXlhWpuO5yYrEk4bb2VYLDbTFisSQV113e71mEEOJ8Bl55eLMgHuv0kGZY5F1yFaWDLiM3N9vVZUXGX1HEfRVXkRPw0BKKkRPwcF/FVTLeIYRIKwNuwFy77Jr2MY8YoBnY/lyybYe8kd/E6YN9PS7G+CuKpCyEEGltwJWHWjAMRv8XyU9r8Hv8BEwfWVdOxBl+tdvRhBAiYwy48gDwDhlF8dgbyM3OczuKEEJkpAFVHqqikpOdR3F+MZbdX8uaCCHEV0/GDZj/eedhPj7WnPLrvLbNJYOGMnTwZVIcQgjRQxlXHsFwjK3vHrngAlE1leKcfIYNGUFubkEfpxNCiIEh4y5b6ZqCpim8u7+eS0u+fBl2x+NhUF4Rvqw8FDV9NmgSQohMl3HlAaCrKs2tkfN+X1VVCrKyKcwrxvD4zvs8IYQQF8fV8li5ciUnT57kiSeeSOl1sUSCgGN1+z2Px6Ykp4CsnEI52xBCiD7i2pjHjh07WL9+fcqvi8WTxONJxo3svN2srikU5uQwvHQY2XklUhxCCNGHXCmPU6dOUVlZycKFC1N+rdfWuW7ckE7jHV7LpLSwmEHFQzHlMpUQQvQ5Vy5bLV26lIceeohjx451+/3m5maamzvfTVVbWwvAjdcOpaCwvThUFXJ8DgU5hXj8eShKxt08JoQQGanfy2PNmjWUlJRQXl7OunXrun3O888/z6pVq77037FMg8KsLLKzCjA8/r6IKoQQ4jyUZDKZ7M8Dfuc736GhoQFN02hqaiIYDHLrrbeyePHijuec78xj7ty5/Pf/VHL5ZUMpysrF48tFNbofOBdCCNF3+v3M47nnnuv4/3Xr1rFz585OxQEQCAQIBLqfw1GYlc3g/EEY3oAMigshhEsybp5HXnYhpi/H7RhCCDGguVoeFRUVVFRUpPQaxUyPPTeEEGIgk9uThBBCpEzKQwghRMqkPIQQQqRMykMIIUTKpDyEEEKkTMpDCCFEyqQ8hBBCpEzKQwghRMqkPIQQQqQs48qj/pVKWg+853YMIYQY0DKuPGKtzZx482kpECGEcFHGlYdqWKDpNO2ocjuKEEIMWBlXHgCKbhE7Ve92DCGEGLAysjySsQh6dqHbMYQQYsDKuPJIRCMQj5FVPsvtKEIIMWBl3GZQuhMg76a5OMPHuh1FCCEGrIwrj8JbH8IZPNjtGEIIMaBl3GUrIYQQ7pPyEEIIkTIpDyGEECmT8hBCCJEyKQ8hhBApk/IQQgiRMikPIYQQKcuYeR7xeByA2tpal5MIIcSFKS4uRtcz5tdsSjLmp/r4448BmDt3rrtBhBDiAm3atInBX9FJzRlTHkOGDAHg97//PaWlpS6n6aq2tpa5c+eyevVqiouL3Y7TheTrGcnXMwM1Xzr+rL0lY8rDNE0ASktL07rJi4uLJV8PSL6ekXw9k+750okMmAshhEiZlIcQQoiUSXkIIYRImbZ8+fLlboe4UJZlMWHCBCzLcjtKtyRfz0i+npF8PZPu+dKNkkwmk26HEEIIkVnkspUQQoiUSXkIIYRIWUaVx8qVK3nkkUfcjtHF5s2bqaio4KabbuLRRx91O063qqqqmD59OtOnT2flypVuxwGgpaWFGTNm8OmnnwKwfft2Zs6cyY033khlZaXL6brme+mll5gxYwYzZ87kJz/5CW1tbWmV74zVq1dz7733upTqC+fme//997njjjuYPn06P/zhD9Pu/auuruaWW25hxowZ/PjHP3Y9X7rLmPLYsWMH69evdztGF0eOHGHZsmU8+eSTvPrqq+zdu5e33nrL7VidhEIhHnvsMV544QWqqqrYtWsX27dvdzXTP//5T+6+++6OZWfC4TCLFy/mySef5PXXX2f37t2uvo/n5jt06BDPPPMMf/jDH/jTn/5EIpHgxRdfTJt8Z3z00Uc89dRT7oQ6y7n5WlpaeOCBB1ixYgWvvfYaAGvXrk2bfAA//elPqaysZMOGDYTDYaqqqlzLlwkyojxOnTpFZWUlCxcudDtKFxs3buTmm2+muLgYwzCorKykrKzM7VidxONxEokEoVCIWCxGLBZz/Y6Sl19+mWXLllFYWAhATU0NQ4cOZciQIei6zsyZM3nzzTfTJp9pmixfvhyfz4eiKIwYMYKjR4+mTT6AtrY2li5dyqJFi1zLdca5+bZt28bVV1/NyJEjAViyZAk33HBD2uSD9s9JS0sL8XicSCTi+mck3WXE8iRLly7loYce4tixY25H6eLw4cMYhsH8+fNpaGhgypQpPPjgg27H6sTn87Fo0SKmTZuGbdtce+21jB071tVMjz32WKev6+vrKSgo6Pi6sLCQurq6/o7V4dx8paWlHWuqNTY2snr1ah5//HE3ogFd8wH86le/Ys6cOWmxvMa5+Q4fPozX6+X+++/nk08+Yfz48a5egu7u/Vu+fDn33nsvPp+PwYMHc9NNN7mQLHOk/ZnHmjVrKCkpoby83O0o3YrH4+zYsYNf/OIXvPzyy3zwwQdpd3lt//79/PGPf2TLli1UV1ejqirPPPOM27E66e6OcUVRXEjy5erq6pg3bx5z5sxhwoQJbsfpsG3bNo4dO8acOXPcjtKteDxOdXU1jzzyCK+88gqhUIjf/e53bsfq0NDQwC9/+Us2bNhAdXU1ZWVlrv5xkAnSvjxef/11tm3bxqxZs/jtb3/L5s2b+fnPf+52rA75+fmUl5eTm5uLbdtMnTqVmpoat2N1Ul1dTXl5OXl5eZimSUVFBTt37nQ7VidFRUUcP3684+v6+vpOlxTSwYEDB7j77ruZPXs2999/v9txOtmwYQMffvghs2bNYsmSJezevTutzoDz8/MpKytjyJAhaJrGtGnT0upzsmvXLkaMGMEll1yCqqrccccdafcZSTdpXx7PPfccGzZsoKqqih/84Adcf/31LF682O1YHaZMmUJ1dTXNzc3E43HefvttRo8e7XasTkaOHMn27dsJBoMkk0k2b97MmDFj3I7VSVlZGYcOHeLw4cPE43E2bNjAt771LbdjdWhpaWH+/PksWrSI7373u27H6eLxxx/njTfeoKqqikcffZQrr7yS3/zmN27H6jBp0iT27NnTcel5y5YtafU5GTFiBDU1NR1/wGzatCntPiPpJiPGPNJZWVkZCxYs4J577iEajTJx4sS0u3QwadIk9u7dS0VFBYZhMGbMGL73ve+5HasTy7J44okneOCBB4hEIkyePDmtrjmvXbuW48eP8+yzz/Lss88CcP3116fF4HQmKCkpYcWKFSxcuJBIJMIVV1zBww8/7HasDsOHD2fRokV8+9vfRtM0hg4dyooVK9yOldZkeRIhhBApS/vLVkIIIdKPlIcQQoiUSXkIIYRImZSHEEKIlEl5CCGESJmUhxBCiJRJeQghhEiZlIcYkNavX8/UqVNpbW0lGAwybdo0XnnlFbdjCZExZJKgGLB+9KMf4ff7aWtrQ9M0fvazn7kdSYiMIeUhBqyWlhZmzZqFbdusW7dO9m8QIgVy2UoMWCdOnCASidDc3Ex9fb3bcYTIKHLmIQakaDTKXXfdxV133UUikWDt2rW8+OKLGIbhdjQhMoKceYgB6de//jUFBQXcfvvt3HnnnWRnZ1NZWel2LCEyhpx5CCGESJmceQghhEiZlIcQQoiUSXkIIYRImZSHEEKIlEl5CCGESJmUhxBCiJRJeQghhEiZlIcQQoiU/T/q1v0AlDFZ4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 409.975x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# hue는 데이터의 종류에 따라 다른 색으로 그래프를 표현합니다.\n",
    "# 여기에서는 회귀선이 다 같아서 선이 하나로 표현되었지만 겹쳐보이는 것입니다.\n",
    "sns.lmplot(x=\"x\", y=\"y\", data=df, hue=\"dataset\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f952b14dfd0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# regplot은 lmplot과 기능이 거의 같지만 hue옵션을 사용할 수 없습니다.\n",
    "sns.regplot(x=\"x\", y=\"y\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952c833fd0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# lmplot그리기\n",
    "sns.lmplot(x=\"x\", y=\"y\", data=df, hue=\"dataset\", col=\"dataset\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952cd20d50>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ci == Size of the confidence interval for the regression estimate\n",
    "# ci는 신뢰구간을 의미하며 0부터 100까지의 값을 가집니다.\n",
    "# 만약 95라면 데이터를 샘플링했을 때 그 숫자가 해당 범위에 있을 확률이 95% 라는 의미입니다.\n",
    "# 여기에서는 위에서 그린 신뢰구간을 제외하고 그려봅니다.\n",
    "sns.lmplot(x=\"x\", y=\"y\", data=df, hue=\"dataset\", col=\"dataset\", ci=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952d298b50>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# height는 그래프의 높이를 의미합니다\n",
    "# scatter_kws에서 s는 점의 크기를, alpha는 투명도를 의미합니다.\n",
    "sns.lmplot(x=\"x\", y=\"y\", data=df, hue=\"dataset\", col=\"dataset\", \n",
    "           col_wrap=2, ci=None, palette=\"muted\", height=4, scatter_kws={\"s\": 70, \"alpha\": 0.8})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f952d879650>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uXU/R9W+ReDnZS0auljmQ7K0/1CR7cWVmn9wML95PSr/x0efK7G9luvcj5apb1MrYnAKN2F4obHjpvTJeWF5a18oMv6wNN1zVDneyWhmReDrZS0buM/vgW/ZM/S86HLi75Z3cDKEgNe88HX27ZhmkDvod7i69j/qekvgUaMTWNpXW8NiCIn4ojv6k1b61h38fkcuZHdXKiFjhZC8ZOTypNL/2oUMuF+Fw0Pzah47pA8FHnMFEAEju1pfUAbfiTE0/6vuJPSjQiC2Fw4YFK8uY9+52QmGD44BWxqNWRsQyDXHJKCn3LDLumEtww0rCu0pwZWbj7pZ3zHc3HXEGwN1zMM0G3nZM7yX2oUAjtrNlu5+/LNjK9z9FW5mcVm4mj8ile6c0iycTkYa4ZATgcKcc891M9c6wdHr9LyZ7Sb3iphN6X0lsCjRNjC8QZuW6SorLA+S09pDXI4NUj8vqsY5JOGJ4+f0dPLe0lFA4en182CWtGX91O7xue/weRBq7hrhkdLJMrR9X2851K2MD4EoGV1LcZpD4U6BpQtZvrub+2ZswxuAPGrxuB9OXFPPw+M4J324Ulfn5y8Iivi3yAdCupZvJBbn0ODWx5xaxo5NdduBkLxmdKGMMwa/eo+adpzH+agBcbU/DlduNpKzOcZlBrKNA00T4AmHun72JmkCkbps/aADD/bM3Me+ebqQkYFMTjhhe+SDaytSGoq3M0ItbcePA7IScV8TuGmrZgZO5ZHQiItW78BX+L7XfrYoeP6U5qQNuJblbXxwOxwm9p1XrScmJUaBpIlauq8Qc5jZGYwwr11Vy9QWt4jzVkW3bEeCxhVv5emu0lWmbGW1lzjlNrYxILFix7MDJMsZQu2ElvneextRUAZDc5WJSB96GM63lCb+vFetJyclRoGkiissD+xqZQ/mDhuKdwThPdHjhiOH1j8qZ/XYJwX2tzJCLWjFhkFoZkVhqyGUH4iGytzLaynz7EQAObxopA27FfdblJ9zKgD2DnSjQNBk5rT143Y56Q43X7SCnlduCqQ5VXB7gsUVFfLV5LwBZGcncVZDLeafrCZ4isdZQyw7EQ/Dr9/EVPvVzK3P6haQOvv2kWpkD39tOwU6iFGiaiLweGUxfUgwc+pfU4XCQ1yMj/kMdIBIxvPFxOc8WlhCojc448IKWTBycQzOvWhmReGiIZ8jEWsS3G9/bf6P26/cBcHiakXLVJNxn9z+pVuZAdgp28jMFmiYi1ePi4fGdD7nLyeFw8PD4zpZeyimpCDB1YRFfboq2Mq1bJHPXNbn06qJWRiSeGuoZMrES/OZDfIX/i/HtBiDptPNpNvh2nM1bN+hx7BDs5FAKNE1I905pzLunW/Q5NDuD5LRyk9cjw7IwE4kYlqzeyazCEvzB6N1XA85vyaQhamVErJAIz5CpT8RXhe+dv1G7YWV0gyeV1Ksm4T77ygZrZQ6U6MFO6qdA08SkeFwJcTfT9l1Bpi4sYu2P0WdFtEpP4o7huVzYVeuqiFjJqmfIHE7w21X4Cqdh9lZG5zu1F80G34EzvWFbmQMlarCTI1OgkbgyxvDmJzuZ+WYJNftamSt7ZnJLfnvSUtTKiCSCeD9Dpj6Rmj3ULP07wfX/jG5wp5B65c24zxkQk1bmlxIt2MnRKdBI3JRVBnl8URFf/BBtZbxuJ1f1ymT81dm2WX5BRGIv+P1qfG9Nw1RXAJDU6VyaDbkTZ4usuM6RCMFOjp0CjcScMYa3P6tg+pLiuicVO53gD0ZYuqaCZZ/vssXyCyISW5GaPdQse4bgl+9GN7hTSL1iAu7zBsallRF7U6CRmNpRGeSJl7ex5vs9B22P7FuBwQ7LL4hI7NX+8Cl73/wrpnonAEkdzyF1yJ24MtpaPJnYhQKNxIQxhnfWVDB9cTG+fa1Mlw4pbNleQ6C2/v0TcfkFEYkt49+L791nCK5dGt2Q7CXlihvx9ByMw+G0djixFQUaaXDlu2t54uUiPvsu2spkpCXxu2Ht+bbIx3fbaur9nkRbfkHEzuyyqGLtj2vYu+RJzJ5yAJJOOTvayug5L3ICFGikwRhjWPb5Lv6++Cf2+qOtTF6PDH77q/a0aJbEnpqwLZZfELEzOyyqaAI+fO/OIPivt6Mbkj2k9LsRT68hja6VsUu4bAwUaOS4+ALh6IP5ygPktPaQ1yODVI+LiqpannhlG598E11XJb2Zi98N60Cfs39eUiHRl18QsTs7LKpYu+kL9i55AlO1A4CkDmeRmn9X9Om8jYwdwmVjokAjx2z95upDlk74++Kf+PWlbVj88U6qa8IAXNq9Bb8b1p6MtOSDvj+Rl18QaQwSeVFFE/DhWz6L4BdvRTckeUi5/AY8F/yq0bUyYI9w2dhYEmhee+01pk+fDkBeXh7/+Z//acUYchx8gTD3z95Ud9s1UHfp6MV/lgHQPMXFbb9uT97ZGYe9xTLRll8QaUwSdVHF2s1r8S15nMju6LnC1eFMmg2ZjKtVe0vmiYdEDpeNVdwDTU1NDVOmTKGwsJD09HRGjRrFRx99xCWXXBLvUeQ4rFxXiTncX07g1Gwv/33jqbRsnnzYffZLlOUXRBqbRFtU0QRrqFn+LIHPl0Q3JLlJ6TsWzwXDcDgb9w8xiRouG7O4B5pwOEwkEqGmpobU1FRCoRAej+egfaqqqqiqqjpoW2lpaTzHlF8oLg/U+2He/Xqd0fyYwoxIQ9K54mCJtKhi7ZYv8S2ZSqRyOwCu9l1plj8ZV6sOcZvBSokWLpuCuAeatLQ07rzzTgYNGoTX6+XCCy+kZ8+eB+0zZ84cpk2bFu/R5AhyWntIToLa0KGved0O2rf2HPqCSIzpXHGwRFhU0QT91Lw3m8Bnb0Q3uJJJyRuD56Lhjb6VOVAihcumwmGOdB0BuP322xk1alSDXRL65ptv+K//+i9mzpxJ8+bN+Y//+A969OjBxIkT6/Y53E9do0eP5t1336VDh6aR8BNFZXWIJ18pYtWGqnpfT/E49ZRfsYTOFfUzwRpLFlWs3bo++lmZfZdTXNldoq1Mm1NifuxEVN9dTvvDpe5yanhHbWgGDBjAU089xUMPPcRvfvMbCgoKyMg48dtrP/jgA3r37k2rVtHPUFxzzTW88MILBwWa9PR00tPTT/gY0nA+WF/JtFd/YvfeaDXjdEKyCwK16A4lsZzOFfWL96KKptZPzXvPEfj0dcCAK4mUPqPxXFzQpFqZX9KK3fF11EAzdOhQhg4dysaNG1m0aBEjR47k3HPPZezYsfTo0eO4D9i1a1f+53/+B5/PR0pKCsuXL+fss88+oeEldqr2hnjq9Z9Ysa4SgFSPk1uHtufSs9J5/8vdukNJRAAIFW1g75KpRCqKAXC1Oz3aymR1snawBKEVu+PnmD5DE4lE2LJlC5s3byYUCtGqVSsefPBBevfuze9///vjOuBll13Ghg0buOaaa0hOTubss89m0qRJJzS8xMZHX+1m2qvb2FUdbWV6ndGcOws60KZF9Em+ukNJRExtgJqVcwmsfhUw4EzCe9kovL1H4HDpEWcSf0f9r27q1Km8/PLL5Obmcv311/PEE0+QnJyMz+ejX79+xx1oACZNmqQQk4D2+EL87Y2f+Oe/oq1MisfJpCE5XH1+y8M+V0ZEmp7QT9+w942pRCq2AeBqexqpQyeTlNXZ4smkKTtqoKmoqOCZZ56ha9euB21PTU3lL3/5S8wGk/j6+OvdPPnKNnbtibYy552exl0FuWRlNM71lQ63hIOIHJ4JBalZ+TyB1a+AiYDThffS6/Be8hu1MmK5o/4X+N///d+Hfe2yyy5r0GEk/qprwvx98U8s+3wXACluJxMH5zDowsbbytS3hMP0JcU8PL4z3TulWT2eSEIKFX8bbWV2FgHgyuocbWXanmbxZCJRitRN2CffVPHkK0XsrIq2MuecmsbkEbm0zWycrQwcaQkHw/2zN+n2c5FfMKFa/B+8gH/Vwmgr43DivfRavJdei8Olh2lK4lCgaYL2+sNMX1LMO59VAOB1O5kwMJvBF7XC6Wycrcx+R1rCwRjDynWV+tCzyD6hku+jrUz5FgBcbTpFW5l2p1s8mcihFGiamDXfVfH4y9so310LQPfOzbh7RC7ZLZvGk36PtISDP2go3hmM80QiiceEa/F/8CL+j176uZXpPRLvZaNwJKmVkcSkQNNE7PWHmfFmMYWfRlsZT7KTGwe2Y+jFrRt9K3OgnNYevG5HvaHG63aQ06rxXm4TORah0h/wvTGV8I7NADhbn0KzoXeTlH2GtYOJHIUCTRPwxQ97eHxREWWV+1qZTs2YXJBLThNcfymvRwbTlxQDhwYah8NBXo8Tfwq2iJ2ZcC3+D+dHW5lIeF8rMwLvZderlRFbUKA5Rna8zdcXCDPzrRLeXL0TAE+yg3EDshl2SdNqZQ6U6nHx8PjOh9zlpCUcJFGYgI/g1+8TrijG1TIH95l9cHhSY3rM0PYf8b3xGOGyTQA4W3WItjI5/xbT44o0JAWaY2DH23zXbqxm6qIitu+KfiakW8dUJhecQoc2Ta+V+aXundKYd0+3aEDVEg6SQOpbzNC37JmYLWZowiH8qxbg/+Af0VYGB56LryElbwyOJF1+FXtRoDkKu93mWxMIM6uwhMUfR1sZd9K+VubS1riaaCtTnxSPS3czSUIxAV80zARrft5Y6wdgz/wHyLhjboMuahgu28zexY8RLt0IgLNle5rl30VSh24NdgyReFKgOQo73ea77sdqpi4sonRfK9M1N5W7R+SSm+W1eDIROZrg1+9Hm5n6GENww8oGWeTQRMLRVub9f0AkBDjwXDiMlL434EhWgyv2pUBzFHa4zdcfDDP77VJe+6gcgCSXg3ED2jH8sjZqZURsIlxRXNfIHKLWT3hXyckfY8cW9i6eSrjkewCcmTk0y59MUq5aGbE/BZqjSPTbfNdvquaxhUWUVESDVZcOKdw94hQ6tlUrI2InrpY5kOytP9Qke3FlZp/we5tImMDql6lZ+TyE97UyF/yKlMtvwJGsc4U0Dgo0R5Got/n6gxGee6eEVz8qx5hoKzPmyraM6JOFy6VWRsRu3Gf2wbfsmfpfdDhwd8s7ofcNl2+NtjLF3wHgzGhHav5kkk/pfqKjiiQkBZqjSKTbfPffOr5uYzVfbKymsjq6BtMZ7VO4e0Qundo13AcGRSS+HJ5Uml/70CF3OeFw0Pzah477A8EmEibwyavUrJgL4egzqDy98knpdyMOt1oZaXwUaI5BItzmu35zNf/Psz9SGzKEf77hiqsvaMnvhnUgSa2MiO0l5Z5Fxh1zCW5YSXhXCa7MbNzd8o47zIR3bou2Mj99A4CzRVtS8+8iuWOPWIwtkhAUaI6Rlbf5+gJh7pv1I4HaQy97rVxXyS1DckhyJc6t4yJy4hzulBO+m8lEwgQ+e52a956DUPRzdZ6eg0m54qYGveVbJBEp0CS4YG2EP76wpd4wA4l367iIWCNc8RO+xU8Q2vYVAM70NqQOuYvkzudaPJlIfCjQJLBvi3z8ZeFWisoCh90nUW4dFxFrGBMh8Okb1Lw3B0LRc4X73IGk9p8Q8yUTRBKJAk0CCoYivPDudhasKCNiwOEAp4ODPjuzXyLcOi4i1gjvKsG3+HFCResBcKS3odngO0g+tafFk4nEnwJNgvn+Jx+PLShi8/bosyg6tfXy22HteWDOwcsv7KcVokWaHmMiBNYsoeafz0LtvlbmnAGk9p+Iw9vM4ulErKFAkyBqQxH+sXw781eUEYlEG5mRfbO4vn9b3EnOhLl1XESsFa4sjbYyW78EwNG8VbSVOe18iycTsZYCTQL4oTjaymwqjbYyuVke/n3EKfxb7s/XvxPh1nERsY4xEYKfv4Vv+ay6pwm7e1xJypU34/SmWTydiPUUaCwUChvm/3M7//jndsL7Wplr+rRh7JXtcCc7D9lfK0SLNE3h3WX4ljxOaPNaABxpLWk2+HaST7/Q4slEEocCjUV+LKnhLwu28mNJ9CetDm083D0ilzNP0fVvEYkyxhD8VyG+d2dCsAYAd/crSLlqEs6U5hZPJ5JYFGjiLBQ2LFhRxgvLtxMKGxwOGH5ZG264qh2eeloZEWmaIrvL2PvmXwlt+hwAR7NMUgCze/oAACAASURBVAf9DneXiy2eTCQxKdDE0ebSGv6yoIgfiqM/abVv5ebukafQraNaGRGJMsYQXPtOdKHK/a3MWZeTMuBWtTIiR6BAEwfhsGHh+2U8v+znVubXl7TmhgHZeN1qZUQkKlJVzt43nyT04xoAHKkZpA66Dfe/XWLxZCKJT4EmxrZs9/PYwq18ty36k1Z2Szd3j8ile2fdlSAiUcYYgl8uo2bpM5jAXgCSz8wj9epbcaa2sHg6EXtQoImRcNiw6IMdzF1aSigcXYdp2CWtGX91O7xu3WotIlGRPTvxvfVXan/4FABHSjqpA2/DfeZlFk8mYi8KNDGwbYef/29BEd8W+QBo19LN5IJcepyqVkZEoowxBL/6JzXvPI3x72tlul5K6tW/xdlMT/8WOV4KNA0oHDG8+uEOnnunlGAo2srkX9yKmwZm6wF4IlInUl2B761p1H6/GtjXylz9f3B3y7N4MhH7UqBpINt2BJi6aCsbtkRbmayMZCaPyOXc03RXgkhTYgI+gl+/T7iiGFfLHNxn9qlb9doYQ+2GFfjeeRpTsweA5C69SR14G860TCvHFrE9BZqTFIkYXvuonDnvlBCojbYygy9sxYTB2aSqlRFpUkJFX7Fn/gNgTHR5gmQvvmXP0Pzah3Bm5uAr/F9qv1sFgCOlOakDbiW5W18cDofFk4vYnwLNSSguDzB1URHrN0evf7dpkcxdBbn0PEOtjEhTYwK+aJjZ9+wYoG7NpT0v/AGH2/tzK3PGRaQO+h3OtJZWjCrSKFkSaJYvX860adPw+Xxcdtll3HfffVaMccIiEcPij3cyq7CEQG0EgIEXtGTi4ByaedXKiDRFwa/fjzYz9QnXYmpqcXibkTLgVtxn9VMrI9LA4h5oioqKeOCBB1iwYAGtWrVi3LhxrFixgr59+8Z7lBNSUhFg6sIivtwUbWVat0jmrms60KtLusWTiYiVwhXFdY1MfZyZ2TQf8yjO5lpgViQW4h5oli5dyuDBg2nXrh0AU6dOxePxxHuM4xaJGN78ZCcz3yrBH4y2Mlf1yuSW/PZqZUQEV8scSPbWH2pcyXguHqEwIxJDcQ80W7ZsITk5mQkTJrBjxw769evHXXfdddA+VVVVVFVVHbSttLQ0nmMeZPuuIFMXFbF2YzUArdKTuGN4Lhd2VSsjYqVEOle4z+yD752n63/RlYTnLHu00CJ2FfdAEw6H+eyzz5g7dy6pqan89re/5ZVXXuGaa66p22fOnDlMmzYt3qMdwhjDW59UMOPNYmr2tTL9z8vklqE5NE/R56lFrJYo54pIzR5q3nkaQsGDX0jygNNJ82sfwuFOsWY4kSYi7v8qt27dmt69e9OyZfTT/f3792fdunUHBZpx48YxfPjwg76vtLSU0aNHx23Ossogjy8q4osfoq1MZvMk7hjegYvP1LoqIokiEc4Vwe8+xvfWNMzeXQAkdTqHpM49Mf5qXJnZuLvlKcyIxEHcA02/fv34z//8T6qqqmjWrBnvv/8+/fv3P2if9PR00tOtuZxjjOHtzyqYvqSYmkC0lbni3ExuHZpD81S1MiKJxMpzRaRmDzVLpxNcvzy6wZ1Cav+JuM+9WncwiVgg7v9Cn3POOUycOJHrr7+e2tpaLr30UgoKCmJ6TF8gzMp1lRSXB8hp7SGvR0a9D73bsTvIE4u2seb76LMiMtOSuH14B3p3UysjIj+r/eET9r45DVO9E4i2MqlD7sLVIsviyUSaLksqhxEjRjBixIi4HGv95mrun70JYwz+oMHrdjB9STEPj+9M907RxSKNMSxds4u/L/4J375Wpm+PDH77q/akN1MrIyJREX81NcueIbhuWXRDspfU/hNwnzdIrYyIxRr1v9a+QJj7Z2+qu3QE4A8awHD/7E3Mu6cbe/0R/vpKEZ98G21lWjRL4ne/bs9l3bXarYj8rHbjZ+x980nMnn2tTMcepA65E1dGO4snExFo5IFm5bpKzGGe3BmJRHj6jZ/46Ksqqv1hAPLObsH/+VUHMtIa9R+LiBwH49+L790ZBNe+E92Q7CGl3014eg3G4XBaO5yI1GnU/3IXlwf2NTKHCtTCO2uidyWkp7q4bVgH8nqolRGRn9X++Hm0lanaAUBS7lmk5k/GlZlt8WQi8kuNOtDktPbgdTsOG2oALjmrBb8b1p7M5slxnExEEpkJ+PC9O5PgvwqjG5I8pFw+Ds8FQ9XKiCSoRh1o8npkMH1JMVB/oJlc0IGrerXUh/lEpE7tpn/hW/I4kf2tTIezSM2/E1fL9hZPJiJH0qgDTarHxUPjOvGHWZuoDf0capxO+MPojlzSTZeYRCTKBGuoWT6LwOdvRjckuUm5/AY85/8Kh1PrtYkkukYdaCqra3n9o511Ycad5KDfuRlMGpJDqrdR/9ZF5DjUbl6Lb8kTRHZvB8DVvivN8ifjatXB4slE5Fg12n/V3/+ykmmvbaNqb/QOpgu7pnPH8A60StdnZUQkygT91PzzWQJrFkc3uJJJ6TsWz4W/VisjYjONLtDs3hviqde2sfLL3QA08zq5Jb89V/bM1GdlRKRO7db1+BZPJVIZXZ3blfNv0Vamda7Fk4nIiWhUgebDr3Yz7dVtVFaHADi/S3PuvCaX1i3UyohIlKn1U/PecwQ+fR0w4EoiJW8MnouuUSsjYmONItBU7Q3xtzd+4r21lQCkepxMys9hgO5gEpEDhIq+Yu/ix4nsKgbAlX1GtJVp09HiyUTkZNk+0KzasJu/vrKNXftamZ5npHHXNbm0yXBbPJmIJApT66dmxVwCn7wGGHAm4e1zPd7eI9TKiDQStg00e2pC/P2NYt79Ivq03xSPk5sH5zDwArUyIvKz0Lav2bt4KpGKnwBwtTuNZvl348rqZO1gItKgbBloVn9dxZOvFFGxJ9rKnHd6GncV5JKlVkZE9jHhWnzLZxFY/QqYCDhdeC+9Du8lv8HhsuWpT0SOwHZ/q2e8WczqTdHVbr1uJxMHZzP4wlZqZUTkINXzHyAtFD1XuNqeSmr+ZJLanmrxVCISK7YLNB+s301ysyzOOTWNuwo60K6lx+qRRCQBRSpLId2L95Jr8V76Gxwu3e0o0pjZLtC4k53cOrQ9+Re3wulUKyMi9XO17EDzMX8gqd1pVo8iInFgu0Dz/97YmZ7dW1s9xnHzBcKsXFdJcXmAnNYe8npkkOrR3RUisdLsN/eT1K6T1WOISJzYLtDY8YO/6zdXc//sTRhj8AcNXreD6UuKeXh8Z7p3SrN6PJFGyeG03elNRE6C0+oBGjtfIMz9szdRE4jgD0YXyfQHDTWByL7tYYsnFJH9TMBH4F9v41v+LIF/vY0J+KweSUSOkX6EibGV6yoxxtT7mjGGlesqufqCVnGeSkR+KVT0FXvmPwDGQK0fkr34lj1D82sfIin3LKvHE5GjUEMTY8Xlgbpm5pf8QUPxzmCcJxKRXzIBXzTMBGuiYQai/x+sYc/8BzDBGmsHFJGjUqCJsZzWHrzu+u/G8rod5LSy32eCRBqb4NfvR5uZ+hhDcMPK+A4kIsdNgSbG8npkHPahfw6Hg7weGXGeSER+KVxR/HMz80u1fsK7SuI7kIgcNwWaGEv1uHh4fGdSPM66psbrdpDice7brlu3RazmapkDyd76X0z24srMju9AInLc9KHgOOjeKY1593SLPodmZ5CcVm7yemQozIgkCPeZffAte6b+Fx0O3N3y4juQiBw3BZo4SfG4dDeTSIJyeFJpfu1Dh9zlhMNB82sfwuFOsXpEETkKBRoRESAp9ywy7phLcMNKwrtKcGVm4+6WpzAjYhMKNCIi+zjcKXjOvdrqMUTkBNjuQ8Er1lXi09N1RURE5AC2CzQvvFvKmEc2sH5ztdWjiIiISIKwXaAJ1GodJBERETmY7QLNfvvXQRIRERGxbaDROkgiIiKyn20DjdZBEhERkf0sCzSPPvoo//Vf/3XC3691kERERGQ/SwLNqlWreOWVV07oez3JWgdJREREDhb3B+tVVlYydepUbr31Vr755pvj/v7R/dsxvP+ZCjMiIiJSJ+6B5v7772fy5MmUlJQcdp+qqiqqqqoO2lZaWgqgRR1FpM6RzhUi0rTENdAsWLCA7Oxsevfuzcsvv3zY/ebMmcO0adPiOJmI2JHOFSKyn8MYY+J1sBtvvJEdO3bgcrnYvXs3Pp+PX//619x7770H7Xe4n7pGjx7Nu+++S4cOHeI1sogkMJ0rRGS/uDY0zz77bN2vX375ZT755JNDwgxAeno66enp8RxNRGxI5woR2c+2z6ERERER2S/uHwre75prruGaa66x6vAiIiLSiKihEREREdtToBERERHbU6ARERER21OgEREREdtToBERERHbU6ARERER21OgEREREdtToBERERHbU6ARERER21OgEREREdtToBERERHbU6ARkUYpuGElJuCzegwRiRMFGhFplGo++AeVf72BUNFXVo8iInGgQCMijVMoAMEa9sx/ABOssXoaEYkxBRoRadyMIbhhpdVTiEiMKdCISONW6ye8q8TqKUQkxhRoRKRxS/biysy2egoRiTEFGhFp3BwO3N3yrJ5CRGIsyeoBRERiIskDbg/Nr30IhzvF6mlEJMYUaESkUUq5bBQZlw9XmBFpInTJSUQaJXe3PIUZkSZEgUZERERsT4FGREREbE+BRkRERGxPgUZERERszzZ3OYXDYQBKS0stnkREYqVdu3YkJZ3caUnnCpHG7XDnCdsEmh07dgAwevRoiycRkVh599136dChw0m9h84VIo3b4c4TDmOMsWCe4+b3+1m/fj1t2rTB5XId9/eXlpYyevRo5s2bR7t27WIwYcOww5yaseHYYc54ztgQDU1TOFfYYUawx5yaseHEa07bNzRer5fzzz//pN+nXbt2J/0TYDzYYU7N2HDsMKcdZoSmda6ww4xgjzk1Y8Oxak59KFhERERsT4FGREREbE+BRkRERGzP9eCDDz5o9RDx4vF4uOiii/B4PFaPckR2mFMzNhw7zGmHGRuSHX6/dpgR7DGnZmw4Vs5pm7ucRERERA5Hl5xERETE9hRoRERExPYUaERERMT2FGhERETE9hRoRERExPYUaERERMT2FGhERETE9hRoRERExPYUaERERMT2FGhERETE9hRoRERExPYUaOSYFRYWMnbs2KPuN23aNJYtWxaTGW666SYqKipO6j3Gjh1LYWEhAH/96195+OGHAVi9ejX5+fknPaNIU9bYzhOvvPIKAwcOPOT18vJyzjvvPHbs2HFSx5GGo0AjDW716tWEQqGYvPeHH34Yk/cVkfiyy3li8ODB7Nq1izVr1hy0fdGiRVxxxRW0adOmwY4lJyfJ6gEksT3xxBO88cYbZGRk0LFjx7rtmzZt4uGHH8bn81FWVkbXrl15/PHHWbhwIevXr+fPf/4zLpeL008/vd79PB4PTz75JEuXLiU5OZnMzEweeeQRsrKy2LhxI1OmTKGyspJwOMzYsWMZMWIE99xzDwDjxo1j+vTpZGdn180zffp0lixZcsj8s2fPJjMzM/Z/UCJNWGM+T3g8HgoKCli0aBG9evUCwBjDggULePTRRxvyj1FOlhE5jKVLl5rBgwebPXv2mNraWjNp0iQzZswYY4wxf/rTn8yrr75qjDEmGAya/Px8U1hYaIwxZsyYMeatt9464n7FxcWmZ8+eJhAIGGOMmTlzplm6dKmpra01gwcPNuvXrzfGGFNVVWUGDRpkvvjiC2OMMV26dDE7d+48qd/XgfM9+eST5qGHHjLGGPPxxx+bIUOGnNR7izQ1TeE8sXXrVtOzZ09TXV1tjDHmgw8+MMOGDTup95eGp4ZGDmvVqlVcddVVpKWlAVBQUMDcuXMB+P3vf8+HH37IM888w+bNmykrK8Pn8x3yHofbr23btnTt2pXhw4eTl5dHXl4evXv35ocffmDr1q3ce++9de/h9/vZsGED55577mFnVUMjYo2mcJ7Izc2lV69evPXWW4wYMYL58+czevToY/4zkvhQoJHDcjgcGGPqvna5XHW/vvvuuwmHwwwaNIjLL7+ckpKSg/Y92n5Op5Pnn3+eL7/8klWrVvHHP/6Riy66iJEjR5Kens5rr71W9x7l5eU0b978iLNOmjSJSZMmNcDvWkSOR1M5T4wePZq//e1v9OvXjzVr1vDnP//5hN5HYkcfCpbD6tOnD4WFhVRVVRGJRA46eXzwwQfcdtttDB48GIfDwdq1awmHw0D0hLb/w36H2++bb74hPz+f0047jVtuuYXx48fz7bff0rlzZzweT92xSkpKyM/PZ/369Ye8t4hYr6mcJ/r06UN5eTlPP/00Q4cOxev1Nuj7y8lTQyOH1bdvX7799lsKCgpIT0+na9eu7Nq1C4DJkydz22230aJFC1JSUrjgggvYunUrAP369ePRRx+ltrb2sPuNHDmSQYMGUVBQQGpqKl6vl/vuuw+3281TTz3FlClTmDFjBqFQiDvvvLPuw3hXXXUV119/PU899RRdunSx7M9GRKKaynnC6XRy3XXX8dhjj9U99kESi8PU1/+JiIiI2IguOYmIiIjtKdCIiIiI7SnQiIiIiO3ZJtCEQiG2bdumO1xE5Ih0rhBpmmwTaEpLS+nfvz+lpaVWjyIiCUznCpGmyTaBRkRERORwFGhERETE9hRoRERExPYUaERERMT2FGhERETE9hRoRERExPa0OKU0Sf6wnzW7PmWHfzttvG3plXkBXpdWzxURsSsFGmlyfqj+nqe+fxKDIRgJ4HZ6WFT0Er894w5OTzvD6vFEROQE6JKTNCn+sJ+nvn+SQMRPMBIAIBgJEIhEt/vDfosnFBGRE6FAI03Kml2fYjD1vmYwfL7r0zhPJCIiDUGBRpqUHf7tdc3MLwUjAXb4y+I8kYiINAQFGmlS2njb4nZ66n3N7fTQxpsV54lERORowjU17FqxgrKXXjrsPgo00qT0yrwAB456X3PgoGfmBXGeSEREjsT33Xf8MHky2194gZ1vvnnY/RRopEnxurz89ow78Di9dU2N2+nB44xu163bIiKJI1xTQ9FjjxHx+zGB+j8usJ9u25Ym5/S0M/hjj//h812fssNfRhtvFj31HBoRkYRT9cknGFP/jRy/pEAjTZLX5eWS1n2sHkNERI6gdvv2ozYz++mSk4iIiCQcYwyhvXuPeX81NCIiIpJQQlVVlM6Zw541a475exRoREREJGFUffIJpXPnEt6zB4CUM87Av3UrwBEvPynQiIiIiOVCVVWUPv88ez75BABnairtRo8m/ZJLMIEAVatXEyw7/MNPFWhERETEUlWffkrpc8/VtTJp55xDu/HjSc7MBMDh9ZLRt+8R30OBRkRERCwR2rOH7XPnUrW/lUlJoe3119PisstwOOp/COrhKNCIiIhI3O1Zs4aSOXMIV1UB0Kx7d7Jvuonkli1P6P1iGmiqq6u57rrrePrpp+nQoQPz589n7ty5OBwOunfvzkMPPYTb7Y7lCCIiIpJAwtXVlM6bR9WqVQA4vV7ajhpFi7y8425lDhSz59CsXbuWUaNGsXnzZgA2bdrEzJkzefHFF3n99deJRCK88MILsTq8iIiIJJg9X3zBxj/8oS7MNDvrLE6dMoWMvn1PKsxADBual156iQceeID/+3//LwBut5sHH3yQtLQ0ALp06UJxcXGsDi8iIiIJIrx3L9tfeIHdH34IRFuZrOuua5Ags1/MAs2UKVMO+rp9+/a0b98egIqKCubNm8cjjzxS7/dWVVVRte+a2n6lpaWxGVREbEvnCpHEt+df/6J09mxClZUApHbrRvaNN+Ju06ZBjxP3DwVv376diRMnUlBQwEUXXVTvPnPmzGHatGlxnkxE7EbnCpHEFd67l+0vvsju998HwOHx0Pbaa8no16/BWpkDxTXQbNy4kZtvvpkxY8Zw0003HXa/cePGMXz48IO2lZaWMnr06FiPKCI2onOFSGKq/vJLSp59llBFBQCpXbuSPWFCg7cyB4pboKmurmbChAlMnjyZYcOGHXHf9PR00tPT4zSZiNiVzhUiiSXs80VbmZUrAXC43WT95jdkXnEFDmds18OOW6BZuHAh5eXlzJo1i1mzZgFwxRVXcOedd8ZrBBEREYmR6vXrKZk1q66VSenShZyJE3FnZcXl+DEPNMuXLwdg/PjxjB8/PtaHExERkTgK19RQNn8+le+9B+xrZUaMIPPKK2PeyhxITwoWERGRE7J3wwaKZ84ktHMnEF0ZO2fCBNzt2sV9FgUaEREROS4Rv5/tL71E5b6rMI7kZNoUFNBywIC4tjIHUqARERGRY7b3668pmTmT2vJyAFJOO43siRPxZGdbOpcCjYiIiBxVJBCg7KWX2PXuuwA4kpKirczVV1vWyhxIgUZERESOyPfttxTPmEHtjh0AeE89lZyJE/Hk5Fg82c8UaERERKRekUCAsoUL2bVsGRiDIymJ1sOH02rgQBwul9XjHUSBRkRERA7h+/77aCuzfTsA3s6do63MvnUZE40CjYiIiNSJBIPsWLSIinfeAWPA5aLNsGG0GjIk4VqZAynQiIiICBBtZUpmziS4b9V6b8eOZE+ciDc31+LJjk6BRkREpImLBIPsePllKt5+u66Vaf2rX9F6yBAcSfaICvaYUkRERGKiZuNGimfMIFhSAoDnlFPImTgR7ymnWDzZ8VGgERERaYIiwSDlr77Kzrfe+rmVyc+n9dChtmllDmS/iUVEROSk1Pz4Y7SVKS4GwNOhAzk334y3Y0eLJztxCjQiIiJNRKS2lvLXXmPnm29CJAJOZ7SV+dWvbNnKHMje04uIiMgxqdm8mZIZMwhs2waAp317sm++mZROnawdrIEo0IiIiDRiJhRix2uvsXPJkmgr43DQasgQWg8bhjM52erxGowCjYiISCPl37KF4hkzCBQVAeDOySFn4kRSTj3V4skangKNiIhII2NCIcoXL6b8jTcgHI62MoMG0frXv8bpdls9Xkwo0IiIiDQi/q1bo63M1q0AuLOzyZkwgZTTT7d4sthSoBEREWkETChE+ZIllL/+el0r0/Lqq2lzzTWNtpU5kAKNiIiIzfm3baNkxgz8mzcD4G7bluyJE0k94wxrB4sjBRoRERGbMuEwO998kx2vvvpzKzNgQLSV8XisHi+uFGhERERsKPDTTxTPmIF/0yYAktu2JWfCBFK7dLF4Mmso0IiIiNiIiUSoKCxkx8svY0IhADKvvJKskSObXCtzIAUaERERmwgUF0dbmR9/BCC5TRuyJ0ygWdeuFk9mPQUaERGRBGciESrefpsdixb93Mr07x9tZbxei6dLDAo0IiIiCSxQWkrJjBnU/PADAMmtW0dbmTPPtHiyxKJAIyIikoBMJELF0qXsWLgQU1sLQMYVV5A1ciSulBSLp0s8CjQiIiIJJlhaSvHMmdR8/z0ASa1akXPTTTQ76yyLJ0tcCjQiIiIJwkQi7Fq2jLKFCzHBIAAZffuSdd11amWOQoFGREQkAQTLyiiZORPft98CkNSyJdk33kja2WdbPJk9KNCIiIhYyEQi7Fq+nLKXXqprZVr06UPbUaNwpaZaPJ19KNCIiIhYJLhjByWzZuH7+msAkjIzo61Mjx4WT2Y/CjQiIiJxZoyh8p//ZPv8+ZhAAIAWl10WbWWaNbN4OntSoBEREYmj2vJySp59lr1ffQVAUkYG7caPp/m551o8mb05Y/nm1dXV5Ofns23bNgA++ugjhg4dyoABA5g6dWosDy0iIpJQjDHseu89frzvvrow0+KSSzh1yhSFmQYQs4Zm7dq13HfffWzevBkAv9/Pvffey9y5c8nOzuaWW25hxYoV9O3bN1YjiIiIJITanTspmTWrLsi4WrQge/x4mp93nsWTNR4xa2heeuklHnjgAbKysgBYt24dHTt2JDc3l6SkJIYOHUphYWGsDi8Sc9WhaiqDu6weQ0QSmDGGyhUr+PEPf6gLM+kXXxxtZRRmGlTMGpopU6Yc9HVZWRlt2rSp+zorK4vt27fX+71VVVVUVVUdtK20tLThhxQ5ARET4b2y5bz+08uAgz/2+B9Sk3RrpRV0rpBEVltREf2szJdfAuBKT6fduHGk9+pl8WSNU9w+FGyMOWSbw+God985c+Ywbdq0WI8kctzK/GU8v2U2G6ujjyNv62lHktNl8VRNl84VkoiMMez+8EO2z5tHpKYGgPQLL6Tt2LEkNW9u8XSNV9wCTdu2bSkvL6/7uqysrO5y1C+NGzeO4cOHH7SttLSU0aNHx3RGkcOJmAgrd/yTV7e9TK2JPvjq0tZ9GN5hJG6nx+Lpmi6dKyTR1O7aRens2VSvXQuAq3lz2t1wA+kXXGDxZI1f3ALNOeecw6ZNm9iyZQsdOnRg8eLFFBQU1Ltveno66enp8RpN5IjKAzt4fvNsvq/+DoCM5AxGdxxHtxbdLZ5MdK6QRGGMoeqjjyidN4+IzwdA8/PPp90NN5Ck/0bjIm6BxuPx8Kc//Ynbb7+dQCBA3759GThwYLwOL3LcIibC+ztW8OpPCwlGoq1M71aXUpD7G1Jc+syMiESFKispmTOH6i++AMCVlka7sWNJv+giiydrWmIeaJYvX1736969e/P666/H+pAiJ21noJznt8zmuz3RReJaJGdwfccb6N5Ci8SJSJQxhqqPP2b7888T3rsXgOa9ekVbmRYtLJ6u6dGTgkUOYIzhg/IVvLJtIYFI9HHkF7XqzYgO15KapMeRi0hUaPduSp97jj1r1gDgataMtvtamcPd8CKxpUAjss/OwE5e2DKHb/ZEF4lrkdyCUaeM5eyMcyyeTEQShTGGqtWro61MdTUAaeedR/a4cSRlZFg8XdOmQCNNnjGGj8rf5+VtC/BH/ABc2PJiRuReRzO1MiKyT6iqKtrKfPYZAM7UVNqNHk36JZeolUkACjTSpO0KVjBvyxy+V5OHCgAAIABJREFUrtoAQHpSC0Z1HEOPDK2rIiI/q/r0U0qfe47wnj0ApJ1zDu3Gjyc5M9PiyWQ/BRppkowxrNr5AYuKFuCPRB98dX7LCxmZO4q0pDSLpxORRBHas4fSuXPZ88knADhTUmg7Zgwt1MokHAUaaXJ2BSt4YctcNlStB6B5UnOuO2UM52b2tHgyEUkkVZ99Fm1l9i2v0ezss8m+6Sa1MglKgUaaDGMMH+/8iEXb5lMTjrYyPTPP59pTrictSY8jF5GoUHU1259/nqqPPwb2tTKjRtGiTx+1MglMgUaahMpgJf/Y+hzrd0cXiUtLSuPaU0bTM/N8iycTkUSy5/PPKZk9++dWpnt3sm+8keRWrSyeTI5GgUYaNWMMn1R8zIKiF///9u48Pur63vf465fJZCYhRLZsQCBWQK0VVDSIUixSkC3sKDuyVFvPqbWcnuNyeirHXr3nyC1QL3of94gFDzvI5lYsRcVavYBYQesCqIFAViAwZJnJZOZ7/xiIhgRkySy/4f18PHw8ZH4z8/vklzy+eeczv+/3S00gtBz5ja16ck+nibR0ajlyEQkJVFZSsnw5nvffByDB7SZjwgRa9e2rroxNKNBI3DrhP8HKA0v5+ERok7gWjlTu6TSRnm20SZyIfOPkRx9RsmQJdcePA9DiuutC98qoK2MrCjQSd4wxfFCxg7UHV1IVCC1HfkOrm7in0yTS1JURkVMCVVWUrljBib/+FTjVlbn7blr166eujA0p0Ehc8fg9rDq4jN3HQ5vEtXC04O5OE+jZOk8DlIjUq9yzh+LFi6mrqAAg5dpryZ4xg6T09ChXJhdLgUbigjGGXRU7WXNwJVWB0HLk3a+4gfGdJ3OFU5vEiUhIoLqa0pUrOfGXvwBgJSWRcc89tO7XDyshIcrVyaVQoBHbO+n3sOrgcj46/iEAyY4U7s6ZwC1ttEmciHyj8uOPQ12ZY8cASLn6arJnziQpIyPKlUlzUKARW/uw4gNWH1xOZV2oK/ODK7ozodMUWiVpkzgRCQnU1FC2ahXHt20DTnVlxo2jdf/+6srEEQUasaXKupOsPriCDytCm8QlO5IZmzOeXm16qysjIvUqP/kk1JU5ehSA5G7daD9zJkmZmVGuTJqbAo3YzkcVH7Lq4DJO1oU2ibsu7Xomdp5CqyQtRy4iIYGaGspWr+b4228Dp7oyY8bQesAAdWXilAKN2EZlXSVrD67kg4rQJnHuhGTG5tzDrW0jv0mcN+BlV8VOyr2lpLsz6dn6FtwOd0RrEDmbQE0Nnh078JeW4szMJC0vD0dycrTLipiqzz6j+IUX8B85AkByly5kz5qFKysrypVJOCnQiC3sPv4RKw8s5WRdaDnya9OuY1LnqbROahPxWvZX7uO5fc9gMNQGfSQluFhXuIYHuj5Il9SuEa9H5Nuq9+6lcN48jDEYnw/L5aJs5UpyZs8mpVu3aJcXVkGvl7K1a6nYuhUAy+kkfcwY2gwcqK7MZUCBRmJaVV0VawtXsfNYaJM4d0IyY3LG0bttn6jcK+MNeHlu3zP4gt76x2qDPgCe2/cMT3Wfq06NRE2gpobCefMIer/5+TQ+HwYonDePrgsWkOCOz5/Pqs8/D3VlyssBSL7qKrJnzsTVvn2UK5NIUaCRmPXx8d2sOLAUT90JAK5p+X0m5U6lTVL0liPfVbETg2nymMHwYcVObmv3wwhXJRLi2bEDY87y82kMnu3baXXHHRGuKryCPh9lL71ExZYtAFiJiaSPHk2bQYPUlbnMKNBIzKmuq+KlwtVsPxbaJM6V4GJUx3H0aRf9TeLKvaX1HZkz1QZ9lHvLIlyRyDf8paUYX9M/n8bno7Ysvn4+q7/4gqIXXsB/6utyX3kl7WfNwtWhQ5Qrk2hQoJGY8smJPaw4sJQT/tAmcd1aXsPkztNo62oX5cpC0t2ZJCW4mgw1SQku0t1aoEuix5mZieVyNRlqLJcrbhaQC/p8lK9bx7EtW8AYrMRE2o0cSdvBg7EcjmiXJ1GiQCMxobqumnWHVvP/jr4HhMLBqI5j6dOuLwlW7LSNe7a+hXWFa5o8ZmFxU2vt5C3Rk5aXR9nKlU1+KGpZFmm9ekW8puZWvW8fxYsWUVtaCoA7N5fsWbNwd+wY5cok2hRoJOr+fuITVhx4keOnujJdU69mcu402rlib5M4t8PNA10fbDTLycLiga4P6oZgiSpHcjI5s2c3muVkWRY5s2fb+obgYG0t5evXc+yNN8AYcDhIHzGCtkOGYCXqV5ko0EgU1QSqWV+4lveOvgtAUkISIzqMoW/6j2KqK3OmLqldear7XD6s2Em5t4x0dwY3aR0aiREp3bpx1X/8B2Vr1+IrLsaVnU3GuHEktrLvdiA1+/dTtGgRtSUlALg6daL9T36COycnypVJLFGgkaj4zPMpywtepMIf2iSuS2o3JudOI91lj8/43Q63ZjNJTDpzHRrf4cOc3LXLluvQBGtrObJxI0f/+Mf6rky7/HzaDRumrow0op8IiShvwMv6Q2v565F3AHBaSYzoMIo7Mu6M6a6MiB3E0zo0NV99FerKFBUB4MrJof2sWbg7d45yZRKrFGgkYj73fMayA0uoqA11Zb7XogtTcu8lw61N4kSaQzysQxP0+0Ndmddf/6YrM2wY7fLz1ZWRc9JPh4SdN+Blw6GXePfINgCclpP8DiPpl/FjdWVEmpHd16Gp+fprihctwnf4MACujh3JnjWL5Nzc6BYmtqBAI2G19+TnLCtYwtHaowBc2eJ7TMmdTqZbm8SJNDe7rkMT9Ps58vLLHH3tNQgGISGBtkOH0m74cBKczmiXJzahQCNh4Q142XR4Pe+UvwVAopVIfvuR3Jk5QF0ZkTCx4zo0NQUFoa7MoUMAJLVvT/uf/ITkK6+McmViNwo00uz2nfyCpQVLOFp7BIDOKVcyNXc6WcnZzfL+3oCXXRU7KfeWku7OpKemTIsA9lqHxtTVceSVVzjy6qsQCIBl0XbwYNqNGqWujFwUBRppNr6Aj5eLNvB22VYg1JUZ2n44/TMH4rCaZzny/ZX7Gi1qt65wDQ90fZAuqV2b5RwidpbSrRtdFyzAs307tWVlJGVkkNarV0yFGe/BgxQ9/zy+wkIAkrKzaT9rFslXXRXlysTOFGikWeyv3MeygiWU+0I3HXZK6cyU3Om0T26+TeK8AS/P7XsGX/CbKamn91R6bt8zPNV9rjo1IkCC2x2Ts5lMXR1HXnuNIy+/XN+VaTNoEOmjRpGQlBTt8sTmFGjkktQGfbxyeCNvlW3FYHBYDoZk5zMga1CzdWVO21WxE9Pk3QFgMHxYsVOL3YnEKG9hIUWLFuE7cACApKwssmfNIqVLlyhXJvEiKoFm06ZN/Nd//RcAffv25eGHH45GGXKJvqrcz9KCxZSd6srkJHdiypXT6ZAcnk3iyr2lTe5yDaFgVe6N7SmpIpcjEwhw9LXXKN+06ZuuzMCBpI8Zo66MNKuIB5qamhqefPJJNm/eTFpaGhMmTOC9997jtttui3QpcpFqg7W8WrSJN0u31HdlBmcPY2DWIBxW+H6k0t2ZJCW4mgw1SQku0t2xOSVVJNICNTV4duzAX1qKMzOTtLw8HMnJEa/Dd/gwRYsW4f36awCSMjNDXZmuut9Nml/EA00gECAYDFJTU0NKSgp1dXW4XK4Gz/F4PHg8ngaPlZzalEyi6+vKL1lasIRSX+j70TE5hym50+mYEv5N4nq2voV1hWuaPGZhcVPrW8Jeg8QWjRWNnbmXk+VyUbZyZUT3cjKBAEf/+EeObNyIqasDy6L1j39MxtixJJwx3os0l+8MND//+c+ZMGFCs3VQUlNT+cUvfsHgwYNxu93k5eVx0003NXjOiy++yMKFC5vlfNI8/EE/rxZtYmvpnzAYEnAwKHsIg7KHXHBX5mKnXbsdbh7o+mCjWU4WFg90fVA3BF+GNFY0FAt7OfmKikJdma++AsCZkUH7mTNJufrqsJ5XxDJn2/jjlFdeeYXVq1dTXl7O3XffzZgxY2h1CdvQf/755zzyyCO88MILtGzZkl/96ld0796dWbNm1T/nbH91TZo0ia1bt9KxY3ju0ZCmFVR9zdKCxZR4iwHokNyRKbnTyUnpdMHv1dS069OB5HynXXsDXj6s2Em5t4x0dwY3aR2ay5bGioYqtm2jdMWKs64UnDVxYthmP5lgkGObN1O+fn2oKwOhrsy4cerKSER855/W+fn55Ofn8+WXX7Ju3TrGjRvHDTfcwJQpU+jevfsFn/Ddd9+ld+/etG3bFoDRo0ezYsWKBoEmLS2NtLS0C35vaV7+oJ/Xi19hS8nmU12ZBAZmDWZw9jASEy7808rmmnbtdrg1m0kAjRVnitZeTr7iYooXLaLmyy8BcKankz1jBi2uvTYs5xNpynn9VgoGgxw4cICCggLq6upo27Ytc+bMoXfv3vzzP//zBZ3wmmuuYe7cuVRXV5OcnMybb77J9ddff1HFS/gcqCpgacFiir1FALR3d2DKldPplNL5ot9T065FwivSezmZYJBjb7wR6sr4/QC0uvNOMu++O6YW8pPLw3cGmvnz57N+/XpycnKYOHEiv//973E6nVRXV9OvX78LDjR9+vTh008/ZfTo0TidTq6//nruu+++i/4CpHn5g342F7/Kn0o2EyR4qisziEHZw3AmXNpy5Jp2LRJeaXl5lC5f3vRBY5p1LydfSUmoK7N/PwCJbdvSfuZMWnz/+812DpEL8Z2B5tixYzz//PNcc801DR5PSUnhd7/73UWd9L777lOIiUEHqw+wtGAxRTWHAchyZzM1dwadW+Q2y/tr2rWI/ZlgkIotWyhbtw5TWwtAqx/9iIx77onK1HCR074z0Pz2t78967E+ffo0azESHXXBOjaXvMYbxa8TJIiFxYCsQQzJzr/krsy3adq1SHh5duwAy2r6oGXh2b79km4Kri0ro2jRImr27gUgsU0bsmfMIPUHP7jo9xRpLtr64DJXWH2QpQWLOVxzCIBMdxZTcqdzZYvvNfu5NO1aJLzCdVOwCQapePNNytas+aYr07cvGePH40hJueh6RZqTAs1lKmDqeKP4j/yx+DWCBLCw+HHmQIa2H3HOrszFriFzWpfUrjzVfa6mXYuEQThuCq4tK6P4hReo/uIL4FRX5t57Sb2IWa4i4aRAcxk6XH2IpQWLKaw5CECmK4spufdyZepV53xdU2vIrCtcc0FryICmXYuES1peHmUrVzY5l9CyrAu6KdgEg1S89VaoK3MqIF3xwx+SOWGCujISkxRoLiMBU8efSjbzx+JXCZhQV+bOzAEMaz+CpIRzbxLXXGvIiEj4OJKTyZk9u9HWB5ZlkTN79nlPpa4tL6f4D3+g+rPPAEhs1Yrs6dNJ7dEjnOWLXBIFmstEUc1hlhYs5mD1AQAyXBlMzp3OValdzuv1WkNGxB5SunWj64IFeLZvp7asjKSMDNJ69TqvMGOM4fi2bZStWlW/fcIVt99O5sSJOFq0CHfpIpdEgSbOBUyAP5e8wevFr1Bn6rCw6JfRn/wOI0lKOP/lyLWGjIh9JLjdFzybyX/0KMV/+ANVf/87AI4rriD73ntpeeON4ShRpNkp0MSx4poilhYs5kB1AQDtXOlM6XwvXVpe+I67WkNGJD411ZVJ692brEmTcKSmRrk6kfOnQBOHAibA1tI/8VrRy9SZ0CZxd6TfyYgOo3E5Lm6TOK0hIxJ//MeOhboyn3wCgCMtjexp02jZs2eUKxO5cAo0cabEW8zSgsUUVH0NQLukdCbnTqNry6sv6X21hoxI/DDGcOLddyldsYJgTQ0Aab16kTl5MoktW0a5OpGLo0ATJ4ImyJulW3ilaGN9V6Zvej9GdhjToCtzKevIaA0ZEfvzV1RQvHgxVXv2AOBo2ZKsqVNJu0VdVrE3BZo4UOotYWnBEr6u+hKAtkltmZx7L91aNtx/qznWkdEaMiKxL1BTg2fHDvylpTgzM0nLyyPB7ebEe+9RumxZfVem5S23kDVlColpaVGuWOTSKdDYWNAEebtsKy8f3oDf+AH4YfqPGNlhTKOuidaREbk8VO/d22gdmtIVK3B36kTNvn3Aqa7MlCmk5eVFuVqR5qNAY1Nl3lKWFizhq6r9ALROasPkzvdyTdq1TT5f68iIxL9ATQ2F8+bVz1YC6lf5PR1mWt58M1lTp6orI3FHgcZmgibItvK32HRoPX4T2iTu9nY/ZFTHcSQ7ks/6Oq0jIxL/PDt2YEzTf7gAtLrjDrLuvRfrbDtyi9iYAo2NlPvKWFbwIvsr9wLQ2tmGSblTuTbtuu98rdaREYl/59ptG8CRmqowI3FLgcYGgibIO+VvsenwemqDoa7MbW37MDpnHMmO89skTuvIiMQ/Z2YmOJ3g9zdx0HlRu22L2EVCtAuQczviK+eZvb9jbeEqaoO1JDtSuLHVTeSmfg/rAr59p9eRcSW467c8SEpw4Upwax0ZkTiR2r1702EGwO/X5pIS19ShiVFBE+Td8m1sOLyu/mOiBBzUBev42/EP+bvn7xc85VrryIjEt8o9e7CcTkwTocZyOqncvfuC93gSsQsFmhh01HeEZQdeZO/JzwFIc15BdV01dcZP0ASAi59yrXVkROKXv7S0yTADYPx+ast087/EL33kFEOMMbxb/g5PfjqnPszktbmVgZmDSLCa/ladnnItIuLMzMRyNb1fm+Vy6R4aiWsKNDHiWO1RFu5bwMqDS/EFfaQlXsFPr/pHpl05kxP+45pyLSLfKS0v76yzmCzLIq1XrwhXJBI5+sgpyowxvHfkL6w/tBbvqVV8b2nTi3E5E2iR2ALQlGsROT+O5GRyZs/m4O9+hwkEoK4OEhOxHA5yZs8mwa375SR+KdBEUUXtMZYf+G8+8/wdgJaJLZnQeQo9Wt3Y4Hmaci0iInJu+sgpCkJdmXf5H3+fUx9mera+hV9f9++NwgxoyrWInJ/TWx8Yny/UnQGoq8P4fI22RBCJN+rQRIg34GVXxU4Kqw6wv3I/xd7DAKQmtmR8p0nc2LrnOV+vKdci8l3OtfWBMQbP9u2ati1xS4EmAvZX7uPZvb8nQICAqat/vGvLq5l55f20dLY8r/fRlGsROZdzbX1gfD5N25a4po+cwswb8PLs3t9Ta3wNwgzAwaoDOBOcUapMROKNpm3L5UyBJoyMMbxUuJpac5a/mLSGjIg0I03blsuZAk2YnPCf4P9++SzvH333rM/RGjIi0pxOT9tOcLvrOzWWy0WC261p2xL3dA9NMzPG8EHFDtYeXElVoAoAiwQMwUbP1RoyItLcUrp1o+uCBXi2b6e2rIykjAzSevVSmJG4p0DTjDx+D6sOLmP38b8BkOJIYVTHcaw9uKrJj520hoyIhEOC263ZTHLZUaBpJruO7WT1wRVUBSoBuP6KHkzoPJkrnK3IcGfy3L5nMBhqgz6SElxYWFpDRkREpJko0Jyn0+vIlHtLSXdn0vPUGjAn/SdZfXA5fzu+C4BkRwrjcsaT1+bW+pvztIaMiIhIeCnQnIf9lfsadVjWFa5hQNZdvF32JpV1JwH4wRXXM6HTVFoltWr0HlpDRkREJHyiEmjefPNNFi5cSHV1NX369OHXv/51NMo4L96Al+f2PYMv+M2S4ac3iXy1aBMAyY5kxuaMp1eb3medMikiIiLhE/FAU1hYyOOPP87atWtp27Yt06ZNY9u2bdwRozew7arYiaHppcQBst3t+ceuD9EqqXUEqxIREZFvi3ig2bJlC0OGDCErKwuA+fPn4zpjZUuPx4PH42nwWElJScRq/LZyb2l9R6YpP0i7XmFGJEpiaawQkeiKeKA5cOAATqeTmTNnUl5eTr9+/XjooYcaPOfFF19k4cKFkS6tSenuTBKtROrO2LYAQuvIZCRnRqEqEYHYGitEJLoiHmgCgQAffPABS5cuJSUlhQceeIANGzYwevTo+udMmzaNUaNGNXhdSUkJkyZNimitVXVVfOH5rMkwA1pHRiTaYmWsEJHoi3igadeuHb1796ZNmzYA9O/fnz179jQINGlpaaSlpTXbOc825fpcPj6+m5UHl3LCfwIIrfabaCXiN7VaR0YkRjT3WBEvAjU1eHbswF9aijMzk7S8PBzJydEuSySsIh5o+vXrx8MPP4zH46FFixb85S9/oX///mE739mmXD/Q9UG6pHZt9PzqumpeOrSK7UffB8CV4GJUx3Hc3DqPvx3/QOvIiEhMq967l8J58zDGYHw+LJeLspUryZk9m5Ru3aJdnkjYRDzQ9OjRg1mzZjFx4kT8fj+33347Y8aMCcu5zjXl+rl9z/BU97kNQsknJz5mxYH/5oT/OADdWl7N5M730tbVDkDryIhITAvU1FA4bx5B7zdjnvH5MEDhvHl0XbBAezpJ3IrKOjRjx45l7NixYT/PuaZcGwwfVuzktnY/pCZQzbrCNbx/9K9A6GbfUR3G0Cf9DhIsbUguIvbg2bEDY84y5hmDZ/t27fEkcSuuVwo+15Tr2qCPcm8Zn574hOUH/pvj/goAuqZ2Y3LuvbRzpUeyVBGRS+YvLcX4mh7zjM9HbVlZhCsSiZy4DjTp7kySElxNhhqnlcSXVfv5U+lmAJISkhjRYQx903+kroyI2JIzMxOcTvD7mzjoJCkjI/JFiURIXP/m7tn6Fiya3orAb2r5snI/AFelduWx7z/OjzLuVJgREdtK7d696TAD4PeT2qNHZAsSiaC4/u3tdrh5oOuDuBLcJCWEViNO+NaX7LSSGJsznoe6/Yp0l/5yERF7q9yzB8vpbPKY5XRSuXt3hCsSiRzbBZpdFTvxBrzf/cRTuqR25anuc/lhu764E9wECQLwvRZdeOz7v6FfRn91ZUQkLvhLSzFn6dAYv1/30Ehcs909NK8Xvcq2ujfPuo7MmbwBL5sOr+Od8rcBcFpO8juMpF/GjxVkRCSuODMzsVyuJm8Mtlwu3UMjcc12v9H9phZfMLS+zHd1avae/IKnPv33+jBzZYvv8ej3f0P/zIEKMyISd9Ly8rCspu8btCyLtF69IlyRSOTY9rf66XVkmuIL+FhzcCW/3/u/OFp7hEQrkZEdxjL76ofJdGdFuFIRkchwJCeTM3s2lssFiaca8ImJWC4XObNna1E9iWu2+8jptNPryJxp38m9LCtYwpHacgA6p1zJ1NzpZCVnR7pEERERiRDbBpqkBBfp7m8+D64N+nj58AbeKtsKQKKVyND2w+mfORCH5YhWmSIiEXN664MG99DU1WHq6rT1gcQ92wYaC4ubWt8ChDagXFawhHJfqGPTOSWXKbnTyU5uH80SRUQiSlsfyOXMdoHGaSXhSgitL5NgJbCucA1vlf0Zg8FhORiSnc+ArEHqyojIZUdbH8jlzHaBZmj7YQz8/mCKag7zPz99gjJfKQA5KZ2YkjudDskdo1yhiEh0aNq2XM5sF2iub3UDrxe/wpulWzAYEnAwOHsod2UPxmHZ7ssREWk2aXl5lK1cSVMfOmnatsQ72yWA/7P/f1OVdhKADskdmZo7g44pOVGuSkQk+k5P2y6cNw9jDMbnw3K5sCxL07Yl7tku0BzxldOCFgzKHsKg7CHqyoiIfEtKt250XbAAz/bt1JaVkZSRQVqvXgozEvdslway3Fn87Nqfk5PSKdqliIjEpAS3W7OZ5LJju5WC77/qHxVmREREpAHbBRpNxxYREZEz2S7QiIiIiJxJgUZERERsT4FGREREbE+BRkRERGxPgUZERERsT4FGREREbE+BRkRERGxPgUZERERsT4FGREREbE+BRkRERGxPgUZERERsT4FGREREbE+BRkRERGxPgUZERERsT4FGREREbE+BRkRERGwvaoHmP//zP3nkkUeidXoRERGJI1EJNO+//z4bNmyIxqlFREQkDkU80Bw/fpz58+fz05/+NNKnFhERkTiVGOkT/uY3v+GXv/wlxcXFZ32Ox+PB4/E0eKykpCTcpYmIzWisEJHTIhpo1q5dS3Z2Nr1792b9+vVnfd6LL77IwoULI1iZiNiRxgoROc0yxphInWz69OmUl5fjcDg4ceIE1dXVjBw5kscee6zB8872V9ekSZPYunUrHTt2jFTJIhLDNFaIyGkR7dAsXry4/v/Xr1/Pjh07GoUZgLS0NNLS0iJZmojYkMYKETlN69CIiIiI7UX8puDTRo8ezejRo6N1ehEREYkj6tCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtJUa7gPMVCAQAKCkpiXIlIhIuWVlZJCZe2rCksUIkvp1tnLBNoCkvLwdg0qRJUa5ERMJl69atdOzY8ZLeQ2OFSHw72zhhGWNMFOq5YF6vl08++YT09HQcDscFv76kpIRJkyaxfPlysrKywlBh87BDnaqx+dihzkjW2BwdmsthrLBDjWCPOlVj84lUnbbv0Ljdbm6++eZLfp+srKxL/gswEuxQp2psPnao0w41wuU1VtihRrBHnaqx+USrTt0ULCIiIranQCMiIiK2p0AjIiIitueYM2fOnGgXESkul4tevXrhcrmiXco52aFO1dh87FCnHWpsTnb4eu1QI9ijTtXYfKJZp21mOYmIiIicjT5yEhEREdtToBERERHbi8tAM3XqVIYOHcqIESMYMWIEu3fvbnD8vffeIz8/n4EDBzJ//vyo1Lh27dr6+kaMGEHPnj154oknGjxn4cKF9OvXr/45y5cvj0htlZWVDBs2jEOHDgHnd72KioqYNGkSgwYN4mc/+xlVVVURr3PPudZHAAAHeklEQVT16tUMGzaM/Px8Hn30UWpraxu9ZuPGjfTp06f+mob7+39mjY8++igDBw6sP/+WLVsaveazzz5jzJgx3HXXXfzrv/4rdXV1Eatx27ZtDX4ub731Vu6///5Gr4n0dQyXWB8rYnmcAHuMFXYYJ5qqU2PFRTBxJhgMmttvv934/f4mj9fU1Jg77rjDHDx40Pj9fjNjxgzz9ttvR7jKhvbu3WsGDBhgjh492uDx+++/33z44YcRreWjjz4yw4YNM9ddd50pLCw87+t13333mVdffdUYY8zChQvN008/HdE6v/rqKzNgwABz8uRJEwwGzb/8y7+YxYsXN3rdE088YV555ZWw1na2Go0xZtiwYaa0tPScrxs6dKj529/+Zowx5tFHHzXLly+PaI2nlZWVmf79+5uvv/660esieR3DxW5jRSyNE8bYY6ywwzjRVJ3GaKy4GHHXofnqq6+wLIuf/OQnDB8+nGXLljU4vmfPHjp37kxOTg6JiYnk5+ezefPmKFUbMmfOHH75y1/Spk2bBo9/8sknPP/88+Tn5/PEE0/g8/nCXsuaNWt4/PHHycjIAM7vevn9fnbu3Mldd90FwOjRo8N+Tc+sMykpiTlz5pCamoplWXTr1o2ioqJGr/v444/ZuHEjw4cP51e/+hUnTpyIWI3V1dUUFRXxb//2b+Tn5/PMM88QDAYbvObw4cN4vV5uuOEGIPzX8swav+3pp59m/Pjx5ObmNjoWyesYLnYbK2JpnAB7jBV2GCeaqlNjxcWJu0Dj8Xjo3bs3zz77LEuWLGHVqlX89a9/rT9eVlZGenp6/b8zMjIoLS2NRqlAqEXr9XoZPHhwg8erqqq49tprefjhh9mwYQMej4fnnnsu7PU8+eSTDZaNP5/rVVFRQWpqav3eGunp6WG/pmfW2aFDB2677TYAjh07xvLly+nfv3+j16Wnp/Pzn/+cTZs2kZ2d3ah9H84ajx49yq233spTTz3FmjVr+OCDD3jppZcavObM6x3ua3lmjacVFBSwY8cOpk6d2uTrInkdw8VOY0WsjRNgj7HCDuNEU3VqrLg4cRdobrzxRp5++mlSUlJo06YNY8eOZdu2bfXHTROz1C3LimSJDaxatYrp06c3erxFixY8//zzdO7cmcTERGbMmNHg64iU87lesXRNS0tLmTZtGmPGjKFXr16Njj/77LP06NEDy7KYNWsW77zzTsRqy8nJ4dlnn6Vt27YkJyczZcqURt/TWLmWq1evZuLEiSQlJTV5PJrXsbnYaayI9XEC7DVWxPI4ARorLlbcBZoPPviA999/v/7fxpgGu3JmZmZy5MiR+n+XlZU12UKLhNraWnbu3Mmdd97Z6FhRUVGDRH7m1xEp53O92rRpQ2VlJYFAAIDy8vKoXNMvv/ySCRMmMGrUKP7hH/6h0fGTJ0+yZMmS+n9H+pp+8cUXvPHGG+c8/5nXO1rXcuvWrQwZMqTJY9G+js3FLmOFHcYJsM9YEevjBGisuFhxF2hOnjzJ008/jc/no7Kykg0bNjBgwID64z169ODrr7/mwIEDBAIBXn31Vfr27RuVWr/44gtyc3NJSUlpdMztdjN37lwKCwsxxrB8+fIGX0eknM/1cjqd3Hzzzbz++utA6K72SF/TyspKZs6cyS9+8QtmzJjR5HNSUlJYtGhR/UyWZcuWRfSaGmN46qmnOHHiBH6/n9WrVzc6f4cOHXC5XOzatQuIzrU8duwYXq+XnJycJo9H+zo2F7uMFXYYJ8AeY4UdxgnQWHHRInLrcYTNnz/fDBo0yAwcONAsWbLEGGPM8OHDTUlJiTHGmPfee8/k5+ebgQMHmieffNIEg8Go1Pnaa6+Zhx56qMFjs2bNMnv27DHGGLN582YzdOhQM3DgQPPII48Yn88Xsdr69etXfyf72a7XY489Zv785z8bY4w5dOiQmTx5shk8eLCZMWOGOX78eETrXLx4sbnuuuvM8OHD6/9bsGBBozp37txpRo4caQYNGmR++tOfGo/HE7EajTFm2bJlZvDgwWbAgAFm7ty59c/59vf9s88+M2PGjDGDBg0ys2fPjsj3/ds17t6924wbN67Rc6J9HcPBDmNFLI8TxthjrLDDOPHtOo3RWHExtPWBiIiI2F7cfeQkIiIilx8FGhEREbE9BRoRERGxPQUaERERsT0FGhEREbE9BRoRERGxPQUaERERsT0FGokpGzZsoH///lRVVVFdXc3gwYPZuHFjtMsSkRijsULOpIX1JOb80z/9Ey1btqS2thaHw8Fvf/vbaJckIjFIY4V8mwKNxJzKykpGjBiB2+1m/fr1uFyuaJckIjFIY4V8mz5ykphz9OhRfD4fHo+HsrKyaJcjIjFKY4V8mzo0ElP8fj/jx49n/PjxBINBXnrpJVasWIHT6Yx2aSISQzRWyJnUoZGYMm/ePNLT0xk3bhz33HMPrVq1Yv78+dEuS0RijMYKOZM6NCIiImJ76tCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO0p0IiIiIjtKdCIiIiI7SnQiIiIiO39f/7QV6FLM1kuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the results of a linear regression within each dataset\n",
    "# seaborn 사이트에 있는 예제의 그래프를 이해하기 위해 위에서는 옵션을 하나씩 그려봤습니다. \n",
    "sns.lmplot(x=\"x\", y=\"y\", col=\"dataset\", hue=\"dataset\", data=df,\n",
    "           col_wrap=2, ci=None, palette=\"muted\", height=4,\n",
    "           scatter_kws={\"s\": 50, \"alpha\": 1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
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