ch09/9.2 pandas에서 seaborn으로 그래프그리기.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "PREVIOUS_MAX_ROWS = pd.options.display.max_rows\n",
    "pd.options.display.max_rows = 20\n",
    "np.random.seed(12345)\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "np.set_printoptions(precision=4, suppress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9.2 pandas에서 seaborn으로 그래프 그리기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* matplotlib = 저수준의 라이브러리\n",
    "* 데이터를 어떻게 보여줄 것인지부터(선그래프, 막대그래프, 산포도 등) 범례와 제목, 눈금 라벨, 주석 같은 기본 컴포넌트로 그래프를 작성해야 함\n",
    "\n",
    "\n",
    "* pandas를 사용하다 보면 로우와 컬럼 라벨을 가진 다양한 컬럼의 데이터를 다루게 됨<br>\n",
    "    => pandas는 Series와 DataFrame 객체를 간단하게 시각화할 수 있는 내장 메서드 제공<br>\n",
    "    => 다른 라이브러리 : seaborn (흔히 사용하는 다양한 시각화 패턴을 쉽게 구현할 수 있도록 도와줌, matplotlib의 기본 컬러 스킴과 플롯 스타일을 변경함)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2.1 Line Plots (선그래프)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Series와 DataFrame은 둘 다 plot 메서드를 이용해 다양한 형태의 그래프를 생성할 수 있음\n",
    "* 기본적으로 plot 메서드는 `선그래프`를 생성함"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a4579c10>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.random.randn(10).cumsum(), index=np.arange(0, 100, 10))\n",
    "s.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Series 객체의 색인은 matplotlib에서 그래프를 생성할 때 x축으로 해석됨<br>\n",
    "    * use_index=False옵션을 넘겨서 색인을 그래프의 축으로 사용하는 것을 막을 수 있다.\n",
    "    * x축의 눈금과 한계 => xticks, xlim 옵션으로 조절\n",
    "    * y축도 => yticks, ylim 옵션으로 조절가능\n",
    "    * p.368 표 9-3에서 사용 가능한 plot 메서드의 옵션을 확인할 수 있다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### use_index=False옵션을 넘겨서 색인을 그래프의 축으로 사용하는 것을 막기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a47bc130>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.random.randn(10).cumsum(), index=np.arange(0, 100, 10))\n",
    "s.plot(use_index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### xlim, xthicks "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a5e87880>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.arange(10).cumsum(), index=np.arange(0, 10, 1))\n",
    "s.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0\n",
       "1     1\n",
       "2     3\n",
       "3     6\n",
       "4    10\n",
       "5    15\n",
       "6    21\n",
       "7    28\n",
       "8    36\n",
       "9    45\n",
       "dtype: int32"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a5f25250>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.arange(10).cumsum(), index=np.arange(0, 10, 1))\n",
    "s.plot(xticks=[1,3,5,7,12])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a70148e0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.arange(10).cumsum(), index=np.arange(0, 10, 1))\n",
    "s.plot(xlim=[0,7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a716b490>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.arange(10).cumsum(), index=np.arange(0, 10, 1))\n",
    "s.plot(xticks=[1,3,5,7,12],xlim=[0,7])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* DataFrame의 plot 메서드는 하나의 서브플롯 안에 각 컬럼별로 선그래프를 그리고 자동적으로 범례를 생성함"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120afd9e4f0>"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(10, 4).cumsum(0),\n",
    "                  columns=['A', 'B', 'C', 'D'],\n",
    "                  index=np.arange(0, 100, 10))\n",
    "df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot 속성에는 다양한 종류의 그래프 패밀리가 존재한다. 예를 들어 df.plot()은 df.plot.line()과 동일하다. 이런 메서드에 대해서는 잠시 뒤에 알아보자\n",
    "<br>\n",
    "* DataFrame에는 컬럼을 쉽게 다루기 위한 몇 가지 옵션이 존재.<br>\n",
    "예) 모든 컬럼을 같은 서브플롯에 그릴 것인지 아니면 각각의 서브플롯을 따로 만들 것인지 지정할 수 있음 (p.368 표 9-4 참고)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<표 9-4> <br>\n",
    "\n",
    "|인자|설명|\n",
    "|:---:|:---:|\n",
    "|subplots|각 DataFrame의 컬럼을 독립된 서브플롯에 그린다 => True로 하면 각각의 서브플롯을 따로 만든다.|\n",
    "|sharex|subplots=True인 경우 같은 x축을 공유하고 눈금과 한계를 연결한다.|\n",
    "|sharey|subplots=True인 경우 같은 y축을 공유한다.|\n",
    "|figsize|생성될 그래프의 크기를 튜플로 지정한다.|\n",
    "|title|그래프의 제목을 문자열로 지정한다.|\n",
    "|legend|서브플롯의 범례를 추가한다.(기본값은 True)|\n",
    "|sort_columns|컬럼을 알파벳 순서로 그린다. 기본값은 존재하는 컬럼 순서|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2.2 Bar Plots (막대그래프)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot.bar() : 수직막대그래프\n",
    "* plot.barh() : 수평막대그래프\n",
    "* Series 또는 DataFrame의 색인은 수직막대그래프(bar)인 경우 x 눈금, 수평막대그래프(barh)인 경우 y 눈금으로 사용됨"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a48a0c10>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1)\n",
    "data = pd.Series(np.random.rand(16), index=list('abcdefghijklmnop'))\n",
    "data.plot.bar(ax=axes[0], color='k', alpha=0.7)\n",
    "data.plot.barh(ax=axes[1], color='k', alpha=0.7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* color='k' 옵션과 alpha=0.7 옵션은 그래프를 검은색으로 그리고 투명도를 지정한 것"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 막대그래프를 그릴 때 유용한 방법\n",
    "* Series의 value_counts 메서드를 이용해서 값의 빈도를 그리는 것이다. =>  s.value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>air_store_id</th>\n",
       "      <th>visit_datetime</th>\n",
       "      <th>reserve_datetime</th>\n",
       "      <th>reserve_visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>air_877f79706adbfb06</td>\n",
       "      <td>2016-01-01 19:00:00</td>\n",
       "      <td>2016-01-01 16:00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>air_db4b38ebe7a7ceff</td>\n",
       "      <td>2016-01-01 19:00:00</td>\n",
       "      <td>2016-01-01 19:00:00</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>air_db4b38ebe7a7ceff</td>\n",
       "      <td>2016-01-01 19:00:00</td>\n",
       "      <td>2016-01-01 19:00:00</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           air_store_id       visit_datetime     reserve_datetime  \\\n",
       "0  air_877f79706adbfb06  2016-01-01 19:00:00  2016-01-01 16:00:00   \n",
       "1  air_db4b38ebe7a7ceff  2016-01-01 19:00:00  2016-01-01 19:00:00   \n",
       "2  air_db4b38ebe7a7ceff  2016-01-01 19:00:00  2016-01-01 19:00:00   \n",
       "\n",
       "   reserve_visitors  \n",
       "0                 1  \n",
       "1                 3  \n",
       "2                 6  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"air_reserve.csv\")\n",
    "data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a9194d30>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(18, 6))\n",
    "data['reserve_visitors'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* DataFrame에서 막대그래프는 각 로우의 값을 함께 묶어서 하나의 그룹마다 각각의 막대를 보여줌"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(12348)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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>Genus</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>0.355275</td>\n",
       "      <td>0.513329</td>\n",
       "      <td>0.306168</td>\n",
       "      <td>0.945081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>0.932493</td>\n",
       "      <td>0.520682</td>\n",
       "      <td>0.402644</td>\n",
       "      <td>0.587002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>0.333642</td>\n",
       "      <td>0.879628</td>\n",
       "      <td>0.852004</td>\n",
       "      <td>0.620666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>0.464247</td>\n",
       "      <td>0.846397</td>\n",
       "      <td>0.442342</td>\n",
       "      <td>0.189303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>0.643572</td>\n",
       "      <td>0.600775</td>\n",
       "      <td>0.427939</td>\n",
       "      <td>0.939054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>six</th>\n",
       "      <td>0.505451</td>\n",
       "      <td>0.462759</td>\n",
       "      <td>0.839412</td>\n",
       "      <td>0.350779</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Genus         A         B         C         D\n",
       "one    0.355275  0.513329  0.306168  0.945081\n",
       "two    0.932493  0.520682  0.402644  0.587002\n",
       "three  0.333642  0.879628  0.852004  0.620666\n",
       "four   0.464247  0.846397  0.442342  0.189303\n",
       "five   0.643572  0.600775  0.427939  0.939054\n",
       "six    0.505451  0.462759  0.839412  0.350779"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.rand(6, 4),\n",
    "                  index=['one', 'two', 'three', 'four', 'five', 'six'],\n",
    "                  columns=pd.Index(['A', 'B', 'C', 'D'], name='Genus'))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a7369490>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlMAAAF1CAYAAADMXG9eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAbd0lEQVR4nO3df5RedX0n8PfHAQztslQR2kKEhB4oIIEIEUXAUrZVqNv152kRKtTWRVxRWXZdo9tWbc9x1dpz7AoFUWxtd4V6VKhVlJ4jEoviNkFTCCQoIkrUYqAtioJK+O4fM0nHISRP+M7M88yT1+ucOcm9z3dm3rlnzjzvfO+931uttQAA8Ng8btgBAAAWMmUKAKCDMgUA0EGZAgDooEwBAHTYbVjf+ElPelJbsmTJsL49AMDAbrzxxntaa/tu67WhlaklS5ZkzZo1w/r2AAADq6qvP9prTvMBAHRQpgAAOihTAAAdhnbN1Lb8+Mc/zsaNG/Pggw8OO8oOLVq0KIsXL87uu+8+7CgAwBCNVJnauHFj9tprryxZsiRVNew4j6q1lnvvvTcbN27M0qVLhx0HABiikTrN9+CDD2afffYZ6SKVJFWVffbZZ0HMoAEAc2ukylSSkS9SWyyUnADA3Bq5MgUAsJAsqDJ1991354wzzsjBBx+cY489Nscff3yuvPLKYccCAHZhC6ZMtdby/Oc/P8961rNyxx135MYbb8wVV1yRjRs3DjsaALALWzBl6tprr80ee+yRc889d+u+gw46KK9+9auzefPmvO51r8vTnva0HHXUUXnPe96TJLnuuuty8skn58UvfnEOO+ywnHnmmWmtJZl8nM0999yTJFmzZk1OPvnkJMmqVauyfPnyLF++PE996lPzve99b37/oQDAgjJSSyNszy233JJjjjlmm69ddtll2XvvvbN69er88Ic/zAknnJBnP/vZSZIvfelLueWWW7L//vvnhBNOyOc+97mceOKJj/p93vnOd+aiiy7KCSeckPvvvz+LFi2ak38PADAeFkyZmulVr3pVrr/++uyxxx456KCDctNNN+XDH/5wkuS+++7LV77yleyxxx457rjjsnjx4iTJ8uXLc+edd263TJ1wwgm54IILcuaZZ+aFL3zh1s8FANiWBXOa7ylPeUq++MUvbt2+6KKL8ulPfzqbNm1Kay3vfve7s3bt2qxduzZf+9rXts5MPf7xj9/6ORMTE3nooYeSJLvttlsefvjhJPmJ9aJWrlyZ973vfXnggQfyjGc8Ixs2bJiPfx4AsEAtmJmpU045JW984xtz8cUX55WvfGWS5Ac/+EGS5DnPeU4uvvjinHLKKdl9993z5S9/OQcccMB2v96SJUty44035rTTTstHPvKRrfu/+tWvZtmyZVm2bFluuOGGbNiwIYcddthjzr3+sMN3avzhG9Y/5u8FAMy/BTMzVVW56qqrsmrVqixdujTHHXdczj777Lz97W/Py1/+8hxxxBE55phjcuSRR+YVr3jF1hmoR/OmN70pr33ta3PSSSdlYmJi6/53vetdOfLII3P00Udnzz33zGmnnTbX/zQAYAGrLXe3zbcVK1a0NWvW/MS+9evX5/DDd24mZ5gGyWtmCmA8+H2+a6uqG1trK7b12oKZmQIAGEUL5popRtuSlZ/YqfF3vu25c5QEAOaXmSkAgA7KFABAB2UKAKCDMgUA0GGkL0Df2Yuad2TQi56vvPLKvPCFL8z69eu7FuwEAMafmaltuPzyy3PiiSfmiiuuGHYUAGDEKVMz3H///fnc5z6Xyy67TJkCAHZImZrhqquuyqmnnppDDz00T3ziE3/i4coAADMpUzNcfvnlOf3005Mkp59+ei6//PIhJwIARtlIX4A+3+69995ce+21WbduXaoqmzdvTlXlHe94R6pq2PEAgBFkZmqaD3/4wznrrLPy9a9/PXfeeWfuuuuuLF26NNdff/2wowEAI2qkZ6bm+/ltl19+eVauXPkT+170ohflgx/8YE466aR5zQIALAwjXabm23XXXfeIfa95zWvmPwgAsGA4zQcA0EGZAgDooEwBAHRwzRTsKt68906Ov29ucgCMGTNTAAAdlCkAgA6jfZpvZ09L7PDr7fi0xcTERJYtW5bWWiYmJnLhhRfmmc985uzmAADGxmiXqSHYc889s3bt2iTJNddckze84Q1ZtWrVkFMBAKPKab7t+O53v5snPOEJw44BAIwwM1MzPPDAA1m+fHkefPDBfPvb386111477EgAwAhTpmaYfprvhhtuyFlnnZV169alqoacDAAYRU7zbcfxxx+fe+65J5s2bRp2FABgRJmZ2o4NGzZk8+bN2WeffYYdBebdsg8sG3jszWffPIdJAEbbaJepIazAvOWaqSRpreUDH/hAJiYm5j0HALAwjHaZGoLNmzcPOwIwLjzCB3YJrpkCAOigTAEAdHCaDwCYN+N4c4uZKQCADsoUAEAHZQoAoMNIXzO1M+dVBzHoudd/+qd/yvnnn5/Vq1fn8Y9/fJYsWZJ3vetdOfTQQ2c1DwCw8JmZmqG1lhe84AU5+eST89WvfjW33npr3vrWt+buu+8edjQAYASN9MzUMHzmM5/J7rvvnnPPPXfrvi0rogMAzGRmaoZ169bl2GOPHXYMAGCBUKYAADoMVKaq6tSquq2qbq+qldt4fe+q+tuq+sequqWqXjb7UefHU57ylNx4443DjgEALBA7LFNVNZHkoiSnJTkiyUuq6ogZw16V5NbW2tFJTk7yJ1W1xyxnnRennHJKfvjDH+a9733v1n2rV6/OqlWrhpgKABhVg1yAflyS21trdyRJVV2R5HlJbp02piXZq6oqyb9L8s9JHuoNN4xl5KsqV155Zc4///y87W1vy6JFi7YujQAAMNMgZeqAJHdN296Y5OkzxlyY5GNJvpVkryS/2Vp7eOYXqqpzkpyTJAceeOBjyTsv9t9//3zoQx8adgwAYAEY5Jqp2sa+NmP7OUnWJtk/yfIkF1bVv3/EJ7V2aWttRWttxb777rvTYQEARs0gZWpjkidP216cyRmo6V6W5KNt0u1JvpbksNmJCAAwugYpU6uTHFJVS6cuKj89k6f0pvtGkv+QJFX1s0l+MckdsxkUAGAU7fCaqdbaQ1V1XpJrkkwkeX9r7ZaqOnfq9UuS/FGSv6iqmzN5WvD1rbV75jA3AMBIGOhxMq21q5NcPWPfJdP+/q0kz57daAAAo88K6AAAHUb6QcfrDzt8Vr/e4RvW73DMxMREli1blh//+MfZbbfdcvbZZ+f888/P4x6ndwIAjzTSZWoY9txzz6xduzZJ8p3vfCdnnHFG7rvvvrzlLW8ZcjIAYBSZbtmO/fbbL5deemkuvPDCtDZzaS0AAGVqhw4++OA8/PDD+c53vjPsKADACFKmBmBWCgB4NMrUDtxxxx2ZmJjIfvvtN+woAMAIUqa2Y9OmTTn33HNz3nnnpWpbjygEAHZ1I3033yBLGcy2Bx54IMuXL9+6NMJLX/rSXHDBBfOeAwBYGEa6TA3D5s2bhx0BAFhAnOYDAOigTAEAdBi5MrVQliFYKDkBgLk1UmVq0aJFuffee0e+qLTWcu+992bRokXDjgIADNlIXYC+ePHibNy4MZs2bRp2lB1atGhRFi9ePOwYAMCQjVSZ2n333bN06dJhxwAAGNhIneYDAFholCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDosNuwAwDAo1my8hM7Nf7Otz13jpLAozMzBQDQQZkCAOigTAEAdFCmAAA6KFMAAB2UKQCADpZGALqtP+zwnRp/+Ib1c5QEYP6ZmQIA6KBMAQB0UKYAADoMVKaq6tSquq2qbq+qlY8y5uSqWltVt1TVqtmNCQAwmnZ4AXpVTSS5KMmvJtmYZHVVfay1duu0MT+T5M+SnNpa+0ZV7TdXgQEARskgM1PHJbm9tXZHa+1HSa5I8rwZY85I8tHW2jeSpLX2ndmNCQAwmgZZGuGAJHdN296Y5OkzxhyaZPequi7JXkn+tLX2lzO/UFWdk+ScJDnwwAMfS14AeHRv3nsnx983NznYpQwyM1Xb2NdmbO+W5Ngkz03ynCS/X1WHPuKTWru0tbaitbZi33333emwAACjZpCZqY1Jnjxte3GSb21jzD2tte8n+X5VfTbJ0Um+PCspAQBG1CAzU6uTHFJVS6tqjySnJ/nYjDF/k+Skqtqtqn4qk6cBLXEMAIy9Hc5MtdYeqqrzklyTZCLJ+1trt1TVuVOvX9JaW19Vn0pyU5KHk7yvtbZuLoPDo/FoEwDm00DP5mutXZ3k6hn7Lpmx/cdJ/nj2ogEAjD4roAMAdFCmAAA6KFMAAB2UKQCADsoUAEAHZQoAoIMyBQDQQZkCAOigTAEAdFCmAAA6KFMAAB2UKQCADsoUAEAHZQoAoIMyBQDQQZkCAOigTAEAdFCmAAA6KFMAAB2UKQCADrsNOwC7qDfvvZPj75ubHADQycwUAEAHZQoAoIPTfIlTTgDAY2ZmCgCgg5kpAGCrJSs/sVPj73zbc+coycJhZgoAoIMyBQDQQZkCAOigTAEAdFCmAAA6KFMAAB2UKQCADsoUAEAHZQoAoIMyBQDQQZkCAOigTAEAdFCmAAA67DbsAAALxZKVn9ip8XcumqMgMErevPfOjV964NzkGCIzUwAAHZQpAIAOyhQAQAdlCgCggzIFANBBmQIA6GBpBIARsewDywYee/PZN89hEmBnmJkCAOigTAEAdFCmAAA6KFMAAB1cgA7ALmtnLvr/0BzmYGEzMwUA0EGZAgDooEwBAHRQpgAAOihTAAAdBipTVXVqVd1WVbdX1crtjHtaVW2uqhfPXkQAgNG1wzJVVRNJLkpyWpIjkrykqo54lHFvT3LNbIcEABhVg6wzdVyS21trdyRJVV2R5HlJbp0x7tVJPpLkabOaEGItGABG1yCn+Q5Icte07Y1T+7aqqgOSvCDJJdv7QlV1TlWtqao1mzZt2tmsAAAjZ5AyVdvY12ZsvyvJ61trm7f3hVprl7bWVrTWVuy7776DZgQAGFmDnObbmOTJ07YXJ/nWjDErklxRVUnypCS/VlUPtdaumpWUAAAjapAytTrJIVW1NMk3k5ye5IzpA1prS7f8var+IsnHFSkAYFewwzLVWnuoqs7L5F16E0ne31q7parOnXp9u9dJAQCMs0FmptJauzrJ1TP2bbNEtdZ+uz8WAMDCYAV0AIAOyhQAQAdlCgCggzIFANBBmQIA6KBMAQB0UKYAADooUwAAHZQpAIAOA62AvtAsWfmJnRp/56I5CgIAjL2xLFMAwMK3/rDDd2r84RvWz1GS7XOaDwCggzIFANBBmQIA6KBMAQB0UKYAADq4mw8WKEuAAIwGM1MAAB2UKQCADsoUAEAHZQoAoIMyBQDQQZkCAOigTAEAdFCmAAA6WLTzMVj2gWUDj/3QHOYAAIbPzBQAQAdlCgCggzIFANBBmQIA6KBMAQB0UKYAADooUwAAHZQpAIAOyhQAQAdlCgCggzIFANBBmQIA6KBMAQB0UKYAADooUwAAHZQpAIAOyhQAQAdlCgCggzIFANBBmQIA6KBMAQB0UKYAADooUwAAHZQpAIAOyhQAQAdlCgCggzIFANBBmQIA6KBMAQB0UKYAADooUwAAHQYqU1V1alXdVlW3V9XKbbx+ZlXdNPXx+ao6evajAgCMnh2WqaqaSHJRktOSHJHkJVV1xIxhX0vyS621o5L8UZJLZzsoAMAoGmRm6rgkt7fW7mit/SjJFUmeN31Aa+3zrbV/mdr8QpLFsxsTAGA0DVKmDkhy17TtjVP7Hs3vJvnktl6oqnOqak1Vrdm0adPgKQEARtQgZaq2sa9tc2DVL2eyTL1+W6+31i5tra1ora3Yd999B08JADCidhtgzMYkT562vTjJt2YOqqqjkrwvyWmttXtnJx4AwGgbpEytTnJIVS1N8s0kpyc5Y/qAqjowyUeTvLS19uVZTwnAT1h/2OE7Nf7wDevnKAmwwzLVWnuoqs5Lck2SiSTvb63dUlXnTr1+SZI/SLJPkj+rqiR5qLW2Yu5iAwCMhkFmptJauzrJ1TP2XTLt7y9P8vLZjQYAMPqsgA4A0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKCDMgUA0EGZAgDooEwBAHRQpgAAOihTAAAdlCkAgA7KFABAB2UKAKDDQGWqqk6tqtuq6vaqWrmN16uq/vfU6zdV1TGzHxUAYPTssExV1USSi5KcluSIJC+pqiNmDDstySFTH+ckuXiWcwIAjKRBZqaOS3J7a+2O1tqPklyR5HkzxjwvyV+2SV9I8jNV9fOznBUAYOTsNsCYA5LcNW17Y5KnDzDmgCTfnj6oqs7J5MxVktxfVbftVNo5Ujv9GeuelOSeQUbOnMLbcZidT7MQOebzzzGff475/HPM598udMwPerQXBilT20rWHsOYtNYuTXLpAN9zpFXVmtbaimHn2JU45vPPMZ9/jvn8c8zn3zge80FO821M8uRp24uTfOsxjAEAGDuDlKnVSQ6pqqVVtUeS05N8bMaYjyU5a+quvmckua+19u2ZXwgAYNzs8DRfa+2hqjovyTVJJpK8v7V2S1WdO/X6JUmuTvJrSW5P8oMkL5u7yCNhwZ+qXIAc8/nnmM8/x3z+Oebzb+yOebX2iEubAAAYkBXQAQA6KFMAAB2UKQCADsoUwBBM3f385B2PBEadMsXIqqqjq+q8qY+jh50HZlObvPvnqmHngLlWVb+yjX1nDyPLXFGmBlBVh1bVp6tq3dT2UVX1e8PONc6q6rVJ/m+S/aY+/k9VvXq4qcZbVf1sVV1WVZ+c2j6iqn532LnG3Beq6mnDDrEr8ft8KP6gqi6uqp+e+j3zt0l+fdihZpOlEQZQVauSvC7Je1prT53at661duRwk42vqropyfGtte9Pbf90khtaa0cNN9n4mipRf57kf7bWjq6q3ZJ8qbW2bMjRxlZV3Zrk0CRfT/L9TD6aq/k5nzt+n8+/qqok/y3JK6Z2/UFr7fIhRpp1gzybj+SnWmv/UD/5AMWHhhVmF1FJNk/b3pzH8jxNdsaTWmsfqqo3JFsX7N28o0+iy2nDDrAL8vt8/j0hydOTfDWTj5s7qKqqjdFsjtN8g7mnqn4hUw9vrqoXJ/G4nLn150n+X1W9uarenOQLSS4bbqSx9/2q2if/9nP+jCT3DTfS2GuP8sHc8ft8/n0hySdba6cmeVqS/ZN8briRZpfTfAOoqoMzufz9M5P8S5KvJfmt1tqdw8w17qrqmCQnZnJG6rOttS8NOdJYmzre705yZJJ1SfZN8uLW2k1DDTbGqurmTL6pV5JFSZYmua219pShBhtjj/L7/MzW2teHGmyMVdWBrbVvzNj3rNbaZ4eVabYpUzth6rqdx7XWvjfsLOOuqv4wyd8n+fyW66aYe1PXSf1iJt/cb2ut/XjIkXYpU4X2Fa21V+xwMI9JVU201jb7fT73quqw1tqGqZ/rR2itfXG+M80VZWoAVfX4JC9KsiTTrjNrrf3hsDKNu6r6nUzOSh2f5HuZLFafba39zVCDjbGq+qkkFyQ5qLX2n6vqkCS/2Fr7+JCj7VKq6outtW2++dCvqr6R5FNJ/jrJteN03c6oqapLW2vnVNVnpu3eerxba6cMIdacUKYGUFWfyuS1Izdm2kXRrbU/GVqoXURV/VyS30jy35M8obW215Ajja2q+utM/oyf1Vo7sqr2zOQdlMuHHG1sVdUF0zYfl+SYJPu01p4zpEhjb+rn+teTnJ7J4/3xJFe01q4farAxVlW/keRTrbXvVtXvZ/K4/5GZqV2M22bnX1W9L8kRSe7O5KzU9Um+2Fpz180cqao1rbUVVfWlabeM/2NrzYKpc6Sq3jRt86Ekdyb5SGvtweEk2rVU1ROS/Gkmr5maGHaecVVVN7XWjqqqE5O8NcmfJHlja+3pQ442ayyNMJjPV9Wy1trNww6yC9knyUSSf03yz0nuUaTm3I+m/te+5S6nX0jyw+FGGm+ttbckSVXtNbnZ7h9ypF1CVf1Skt/M5NIUqzM5+83c2XJG57lJLmmt/c3UXdpjw8zUAKYW1jskyR2ZfHOxsN48qarDkzwnyX9NMtFaWzzkSGOrqn41ye9lckbw75KckOS3W2vXDTPXOKuqI5P8VZInTu26J8nZrbV1w0s13qrqa0nWJvlQko+5wWXuVdXHk3wzya8kOTbJA0n+YZxmvZWpAVTVQZlcdOykqV2fTfKvbqWdO1X1HzN5vJ+VyWN/Q5K/b629f6jBxlRVPS7Ji5N8OskzMvkfhi+01u4ZarAxV1Wfz+SK85+Z2j45yVtba88carAxVlX/vrX23WHn2JVM3dxyapKbW2tfqaqfT7KstfZ3Q442a5SpAUw9J+7lST6ayTeZ5yd5b2vt3UMNNsaq6v1JrslkgfrW1L63t9ZeP9xk46uqPttae9awc+xKtnVNmuvU5kZV/Y/W2juq6t3ZxsKorbXXDCEWY0KZGoDnxM2/bd0evuUixmFlGndTd9k8kMlbxree+mit/fPQQo25qroyyRczeaovSX4ryYrW2vOHl2o8VdW9rbV9qur8TC7W+RNaax8YQizGhAvQB+M5cfOkql6Z5L8kOXiqxG6xV8bs8QMj6Hem/nzVtH0tycFDyDLWquqvWmsvzeSdqkvyb7Peq5K8bIjRxtndU5dsvCzJLw87DONFmRrMlufEXTm1/fx4Ttxc+WCSTyb5X0lWTtv/PTMkc6u1tnTYGXYhx069sZ+dyTf2yr+devIftblxcSYX6zw4yZpp+7cce/9p4DFzmm9AnhPHrqCqnplHrvT/l0MLNKaq6jVJXpnJN/BvTn8pk3cKe2OfI1V1cWvtlcPOwXhRpoAkk6eekvxCJm8b33Jau7kwd+54Y4fxoEwBSZKqWp/kCM8qA9g5jxt2AGBkrEvyc8MOAbDQuAAddnFV9beZvAB3ryS3VtU/ZNpjZFpr/2lY2QAWAmUKeGcmL3x+eybvVN1iyz4AtkOZgl1ca21VklTV7lv+vsXUg48B2A5lCnZxFkoF6ONuPtjFVdXemXyYtIVSAR4DZQoAoIOlEQAAOihTAAAdlCkAgA7KFABAh/8PmWTE+00s8KMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* DataFrame의 컬럼인 'Genus'가 범례의 제목으로 사용되었음"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 누적막대그래프\n",
    "* stacked=True 옵션을 사용\n",
    "* 각 로우의 값들이 하나의 막대에 누적되어 출력됨"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a8c06790>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.barh(stacked=True, alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 팁 데이터\n",
    "* 요일별 파티숫자를 뽑고 파티 숫자 대비 팁비율을 보여주는 막대그래프를 그려보자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "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>size</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size  1   2   3   4  5  6\n",
       "day                      \n",
       "Fri   1  16   1   1  0  0\n",
       "Sat   2  53  18  13  1  0\n",
       "Sun   0  39  15  18  3  1\n",
       "Thur  1  48   4   5  1  3"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips = pd.read_csv('tips.csv')\n",
    "party_counts = pd.crosstab(tips['day'], tips['size']) # 요일과 파티 숫자에 따라 교차 테이블을 생성함\n",
    "party_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>size</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>48</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size   2   3   4  5\n",
       "day                \n",
       "Fri   16   1   1  0\n",
       "Sat   53  18  13  1\n",
       "Sun   39  15  18  3\n",
       "Thur  48   4   5  1"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1인과 6인 파티는 제외\n",
    "party_counts = party_counts.loc[:, 2:5]\n",
    "party_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "size\n",
       "2    156\n",
       "3     38\n",
       "4     37\n",
       "5      5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "party_counts.sum(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day\n",
       "Fri     18\n",
       "Sat     85\n",
       "Sun     75\n",
       "Thur    58\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "party_counts.sum(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": true
   },
   "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>size</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>0.623529</td>\n",
       "      <td>0.211765</td>\n",
       "      <td>0.152941</td>\n",
       "      <td>0.011765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.240000</td>\n",
       "      <td>0.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>0.827586</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>0.086207</td>\n",
       "      <td>0.017241</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size         2         3         4         5\n",
       "day                                         \n",
       "Fri   0.888889  0.055556  0.055556  0.000000\n",
       "Sat   0.623529  0.211765  0.152941  0.011765\n",
       "Sun   0.520000  0.200000  0.240000  0.040000\n",
       "Thur  0.827586  0.068966  0.086207  0.017241"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 각 로우의 합이 1이 되도록 정규화\n",
    "party_pcts = party_counts.div(party_counts.sum(1), axis=0)\n",
    "party_pcts"
   ]
  },
  {
   "attachments": {
    "image.png": {
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OCgEVUkcFo55ECSgBJaAElEB0EWAFnf1LWHmlAOLYR6ywU2BxTpfmEyZMEKsA3aRzzChaCmjJ4nZaZsz+bOpGL3Xs27Jp06ZqW5nl/ZIb752caFnivdN68tBDD4kYYhM+NkNj8zU2kaRFihV/Nvljc0n2gaLVjoLBeOcjf4raf//73yIIaJGiiKAQq24T+bFZHl3GUzxSBFEc0VkEBTsdR9BCR2cdHOeMwpSiiX2qyNHsz2PIlI4+eMx5550nzSm1j1R1yzFV+35USFXt9NHYKQEloASUgBIoNwKsuLMyS6sTrSpGIFEo0NJEhxRsokaLE8fvoStvWlPoTGLs2LHiXIF9gJ599lmxzFB40RLD81S3KdQKx2WKqF27dknzO3qLo4BiRZ/WE46DRNfdubm5mDx5sghV0x+KlX8y5286W+AAvjNmzJBBednfh/2rKCjYdI2Wm+o2kR2bQVIosgkkLUn/+Mc/xOkE+5iZ/MgBoNnniVxplaKVjmKLHiNff/11fP/99+KMgyKf3OmGnoMeM+/qpAQqioAKqYoirddRAkpACSgBJVDFCNDNNL/284s++6uENh+jGOJvBi7TEkXnB3RQwSZ/rABTFLDSb/pSsfkaBQatDtVtMhzIgvdHa9GgQYPAcbZoXSJDBg5gzH5k7DdG4UnR8N133xW6PKcwoPMEWmTolY8e7Njcj2N3caBjCilypYWQVq3qNpEjxTZd5LN/FD3tUahTdLI5H/MWRRMtdGTyv//9T1iRM13Hs0ngmjVrpG8eBT2bQLKJH8UY9+f5dVICFUVAhVRFkdbrKAEloASUgBKoQgQoBmgBYSd/NpdiHxSKICOgTPM185uCgOMhsSkgm1UZ4cA5j+d6igNasaqrkOJ9kQuZjB8/XpqTsdJPBmRCDqavDy0kX331lYgkWvdoXaI3w/nz54urdDpboCAYOXIkPvjgA7Hq0ZpFoUXRMG3atGoppMiOze8Y2CySeY7LXM8+Yew3RWHOAXspRCkmKbzYHJDMX3nlFXTo0EGsefwIQGsVhSxFGa2A1THvVaHXhkalCAEVUkWA6E8loASUgBJQAscKAVZMaUGhAHj//ffFWx8rtEUDxQMrsw888IC4nmZfn7ffflssBBQSbFpFS4Kp/FfHyizviYGVflbY6aqcFX4KKDZHowAaOHAgbr31Vpx55hmyjl792F+K/GgpoXDgsfR0+NJLL4nwZH8gWqEoBmjdI08KhM6dO8ugtNUtL5IhhSXnzGdkw2VaPNkMks33yJX9o8iL22mxY/87CnljBSUnilbmPfaPYrNSijKdlEBFElAhVZG09VpKQAkoASWgBKoIAVZiOZYPK/IUA927d5cKKyu1ocE0aWPll04VeAwtKRxo9rrrrpNKL11Pf/7553K8sS6Yc/B2Q5eryO1HHA3eA1kwsBkaXW+zMs9KP51F8P7ZZ4oOOdhkklYlujw3A86St2FJj30UsDyWAooijMEIM87ZtC0zM7OQHa9fHSbehxFPZGK4sokjBzamdY8D7tKax+0Mqamp4syDjiVoQaWgoqdJevyjJZSsZ86cKfuGcuKyCdWBnd5D1SOgQqrqpYnGSAkoASWgBJRAuRJg5ZKCJzExUZpIUUg9/fTTIgTCXZiVWX7tpxCglYB9Wji2Dyv8dJpAT3R0QmGERuic1+LxpvIc7vzRsM7cB+e0ntARAsfXYqCTBDZDMyKS2+fMmSP9eThQL+/dMOHxjz/+uAgoNv+jqKLYeuutt6TfGS0stHB9/fXX2L9/f6H4IkMeyxDNE+NvWHBONmy+R6cltMTRysS+UGbMLeY3WqTIgwNAc79Vq1Zh2LBhYgVl0z4KMO5vOBtO5vyc66QEyoOACqnyoKrnVAJKQAkoASVQhQmwoslKPx0m0PJBiwodH7DZWbjJCCFWSGkd4NhJrPSymRUHTeU6VoYpIFjpZaWWFgVaaegAgNYsHhvNIoBxJwcGikqKHPbpYWB/JzZ9NPuwQk+rFXkYAWqO5ZwDFnOspAULFogo/eGHH0TQ0rpCpg8//LBw4/FkR7Y8D4+tDhx5P8wjDBTln332mVhGaWGipe63334TnsyjZMl7N/lq27ZtchytoRTxtFCxWR/7UDGv0QMiPxAwfXgsmUVzvgv3POq6qkNAhVTVSQuNiRJQAkpACSiBCiPAyiUr/8nJyeKNj2MeseIabuK+rMBTaA0ZMkSaobHS365dOxmIlmNH0UvdL7/8IuNNsUkbK8T07Md+WLQqRLsAMNYOUznn3KwzlihyYjCCx1TiuR/Xm/0okMiezClg2TSNlhiKKLrznjt3rogBerajVzuK0rVr11YLYUAmFPC0aNLL41NPPSV5haLokksuEQcoFEEUkNyXgcuGN4XU888/L/3J2KeM/fZ+/fVXfPPNN+K5j01V6fSEXg9NnuM5dFIC5UFAhVR5UNVzKgEloASUgBKo4gRYMTUVVVNJZWU/3GREACvAjzzyiPRjoctpLtNbGivDtBCwmRWbprGfC/sP0dJFC4GxyhR3/nDXrGrryMoIIlbQucw51/O+DMvi1plKvTmWFhaKUooHNq0kN4oCjivFcZLuvPNO2UbBykDX6LTkmOtVNT6ljQ/vn6KQfcN4z7x33h/7RbGJJAeCDuXM++UxDBSfbOLHfXkMHZw8+eSTaN26tVhI6TSFeY99qBYvXlwoxqI535WWq+5XOQRUSFUOd72qElACSkAJKIFKJcCKqan801LCyibXhZu4jVYBNsVipZWVX1ZYWRlmcyw286NFgUKKVihaqiiw6O47Jyen0PtaNFdoyYbxNwKKy6GBfIzFicLRLBvGnBsvdNzOij4tUexnZgQAB0YmTzIkSzM4LYUB+wSZ46OZI+NOV/oUixRCl112GW644QZxXsImkqEcycwwJjNamegenSKKzIyHQzOn9z4OMk22dDfPNDPpFi5f6zolUFYCKqRKIFj0ZVX0dwmH62YloASqIAF9jqtgomiUKpyAqeDzeTAV1iNFghXc9PR0GWyWzfZY4Wf/FFZe2ZSPDgLo+W/MmDFgUz86WTBiwlzjSOev6tt4DyYYXuZ36Dx0G+/JbDNWFm7nWFt0H2+sd8cdd5w07aOoovvviy++WATrQw89JG7WOVgyLVjmXJxH68S4My/RI+Hs2bPF5TndwZNJqKAPvVcyozWOzOghkrwopMiP4pNOOx577LFCMcZ9ebxJC851UgLlQUCF1BGohj6EoQ+0Lh8sTJSFsojWPBD66Jt7CF2ny0pACRxKgJVRVnRpFWCfHTbD+uKLL8RSMm/ePOnoz+1qATiUW9FffN/QEcV//vMfsTpRPLGZJAUU+w3Rix8HR6Y1j32FjvWJ+Y6B/fNoxaILdPaNIrPzzz9fxpv6+eefRZgx7+mkBCqSgAqpUtLmQ1ycOd9UwnSuokLzQHTkAT7PLHA510kJKIGSCfDdxueFgRVaVvDp7ptWJ+OdjlYGFVElsyRDCk46mvjyyy/RtWtXcZRAgcpxqMiWzdJMv7KSz1i99zDlKpnROyQHQu7SpYs4paAbdOZD9p2iAw/uq5MSqEgCKqRKQds8xGZuChOdW4WqclAO0ZYHzLPMx18L3lK8BHWXY54AnxNWZDkPfd7NsxQ653b+1ik8AYpNfpilUKJjBTbZ49wIUW4zDDk/1icyMMwoligy2ZfK9L0zH8XMx+5jnZfef8USUCFVCt6hBYR5YPlga1AGmgeiMw+Y5zj02S7Fq0B3UQLHLAE+K3zfcc7nhyH0+THbzT7HLKgSbtzwY6Wfwom8KFD5m4HLhqGZl3DKar+ZHBhMvuPciCYum+0mD1Z7IHqDVYqACqkjJId5ifHh5MuNX0LYgZGByxqUgeaB6MwD5jk2TWe0AD7Ci1A3KQHbcsvKa9FKa2g5yefIPEuc63Q4AcOH3IwwMKLAbDNz7qMTCsUlhadhw3loMIKKLHVSAhVJQIXUEWjzJcYHl4O/caC3/v37o2/fvhqUgeaBapAH+vXrh7feeks6dRtvWEd4HegmJVBmAqEVPy6z8sePdOzfwaZd7G8UOudyVQomfiaO7MsTGj9uD90ndNvRXjbXMdfknPGhW+2i8Tra1y7r+ULjfKTlsl6ntMczDmZfsuP7kBxNk0PDM3Q/s39FzQ0nXs/Ew6wzvysqLuGuY+Jg5tyHTQ9DLYyhz3+ZXyZ6gipDQIXUEZKCmZ4Pw7hx48CRsulqk15iOPq4BmWgeSC68wDHIaG3rJYtW2LRokXydfMIrwPdpATKTIBlCr+Yc84KFscEysjIEK9377//Pj777DMZjPXjjz/GRx99pKEEBuREboMGDcKnn36KAQMG4MUXX5QPJNzGwLGslGfxeYncOAAwA/McHTn07NkTvXr1ErZcN3DgQNnOfTVfhmdJfsyHnDPPMdCRCIcBYAuIota0Mr9M9ARVhoAKqSMkBQs7jmswePBgcMwMjlfAQfIuvfRSNGrUSIMy0DwQpXmAA0DS1TCfaQ4IOWPGDBVSR3gX6qajQ4BliqlQ0RrF8oWVL36o42C2zJOcc3BbDsaqITwDur7m2EGck5lZ5pzMyI/byJJz5RieI7mY/BbKkMzMQMBmu7IsnqHhSG4mv3F+2mmn4b777pOPJXz2TXNOLutUfQiokDpCWjKz0zvMDz/8gLPPPlte1mza98svv0jFi5UvDcpA80B05YHp06dj0qRJeOCBB0CrFAdyZBpqf4QjvAx101EhEFqZopBi+fLCCy+IGGBe5MC2F1xwgYyNw/FxGLhOw6EMyOXCCy8UVuRFIcoympXXmjVrypwfPbnN8FSGhzIkD8PRsOT81FNPFUt9rVq1cMYZZwhbridjzY+HMzT5imxMXjN5sV69emjVqhW2bNlSKKJYzmhZc1Rep1XmJCqkjpAULPTYtO/HH3+UkbT5Uhk9erR8RTzCYbpJCSiBKkyAzzXHwWEfKTbPvOqqqzBt2jRpclWFo61RqwYEjJDinIF9KJ5++mn5SMcK7JAhQzBr1izMnz8fc+fO1XAEBrNnz8avv/6KOXPmyDw2NlZaCFBIsfI6cuRIcB+zn/IMn5/Ij2zM/Pnnn5cuDGz2/PbbbwtbDrasHMPzM/mKeZGBrIYPH4527drJh7omTZpgw4YN8rzz4wkDn32dqg8BFVJHSEtmdg40+O2338rXLo6mHRcXJ+uOcJhuUgJKoAoT4HPNzv19+vSRgo7NdCmk9CthFU60ahI15j2TzzinkHruuedESPFD3bp16yRv0pskPYKyD5WG8AzIhx9EDKuUlBS0aNFCmuu2b98eW7duFYbczqAcw3M0/Iw3YjY1ZTM/CimKUa4nO2UYnp/JV+RjGNJBGZv0kWGzZs0kL7JvpOkfad4B1eS1dszfhgqpI2QBFnpsw/7999+LkGJBxy8NXKeTElAC0UmAzzUrYGymy+ZUFFJs2sf1OimB8ibAfGYCP9TRIsX+JyxfKAaKevkq7/hE6/nJkBVSM6dwoiWKVuY77rgDaWlphaI1Wu+xIuJt+Jk8SWcSzI9sljZmzJjCvGq2V0ScovUaZESLEx3IUEixDy4tUps3by7Mq8oxWlO3+HirkCqejWwxQorWqNNPP11cJauQKgGablYCVZgACzLTtI8FHYXUzJkzq3CMNWrViUBoRcoIKfbtYfmycePGwq/W3E+nIxMIZWSEFPv2dOzYEenp6fpx5Mj4CreaPMk5PRwyP/Ij09ixYw8RUoUH6EKxBEKFFEV948aNxXNfaF4NXS72RLohagiokCohqVRIlQBINyuBKCPAQkyFVJQlWjWKLvOfqUipkCpbwhqOPIsKqT/P0uRJzlVI/XmOPFKFVNn4RePRKqRKSDUVUiUA0s1KIMoIsLKgQirKEq0aRddUWnlLKqTKlrBkaSYVUoZE5HOTJzlXIRU5v9AjVEiF0jg2llVIlZDOKqRKAKSblUCUEWBlQYVUlCVaNYquqbTyllRIlS1hydJMKqQMicjnJk9yrqPgMkEAACAASURBVEIqcn6hR6iQCqVxbCyrkCohnVVIlQBINyuBKCPAyoIKqShLtGoUXVNp5S2pkCpbwpKlmVRIGRKRz02e5FyFVOT8Qo9QIRVK49hYViFVQjqrkCoBkG5WAlFGgJUFFVJRlmjVKLqm0spbUiFVtoQlSzOpkDIkIp+bPMm5CqnI+YUeoUIqlMaxsaxCqoR0ViFVAiDdrASijAArCyqkoizRqlF0TaWVt6RCqmwJS5ZmUiFlSEQ+N3mScxVSkfMLPUKFVCiNY2NZhVQJ6axCqgRAulkJRBkBVhZUSEVZolWj6JpKK29JhVTZEpYszaRCypCIfG7yJOcqpCLnF3qECqlQGsfGsgqpEtJZhVQJgHSzEogyAqwsqJCKskSrRtE1lVbekgqpsiUsWZpJhZQhEfnc5EnOVUhFzi/0CBVSoTSOjWUVUiWkswqpEgDpZiUQZQRYWVAhFWWJVo2iayqtvCUVUmVLWLI0kwopQyLyucmTnKuQipxf6BEqpEJpHBvLKqRKSGcVUiUA0s1KIMoIsLKgQirKEq0aRddUWnlLKqTKlrBkaSYVUoZE5HOTJzlXIRU5v9AjVEiF0jg2llVIlZDOKqRKAKSblUCUEWBlQYVUlCVaNYquqbTyllRIlS1hydJMKqQMicjnJk9yrkIqcn6hR6iQCqVxbCyrkCohnVVIlQBINyuBKCPAyoIKqShLtGoUXVNp5S2pkCpbwpKlmVRIGRKRz02e5FyFVOT8Qo9QIRVK49hYViFVQjqrkCoBkG5WAlFGgJUFFVJRlmjVKLqm0spbUiFVtoQlSzOpkDIkIp+bPMm5CqnI+YUeoUIqlMaxsaxCqoR0ViFVAiDdrASijAArCyqkoizRqlF0TaWVt6RCqmwJS5ZmUiFlSEQ+N3mScxVSkfMLPUKFVCiNY2NZhVQJ6axCqgRAulkJRBkBVhZUSEVZolWj6JpKK29JhVTZEpYszaRCypCIfG7yJOcqpCLnF3qECqlQGsfGsgqpEtK5KgspFiEm8DYKl+2yxZ4V3mHR34UbdEEJHEMEWFmIbiGlT3I0Z1dTaeU9VFUhxRwWtP+kZLFWSBlTWNAEQ8qcSkoQsjSTCilDIvK5yZOcq5CKnF/oESqkQmkcG8sqpEpI5yojpFheBGy1ZC+6AbgAuBGAx++DD0EJ8PjgDwbgRhCBIItD61APAgjwl10olnDrulkJVEsCrCxEr5Diw+sDggHroeY7wQRu0qnKEzCVVka0KgopZidPEHDCAzccQNArWY7ZzmtnP3gB+AEvgvBLBqwc7GRpJhVShkTkc5MnOVchFTm/0CNUSIXSODaWVUiVkM5VRkgxngfLDFlkWeZBEJ6gHz6KKVA8BRDw+eELBqSQ44uR4snP/SiszHlCzlUCAt2sBKoVAT4T0S2k7Fosn+FQEVX4THNl4Y9qlXbV4WZMpZX3UhWFFLWJ128JKa8IKQfgcyIQ9PMX/IGgiCgKKYoo+ThXSQlDlmZSIWVIRD43eZJzFVKR8ws9QoVUKI1jY1mFVAnpXFWElKkzFRYb9gJffD6/JZwoqJwBH7wBP3wBP/yBAAKBgFinKKz8odWrwhOVAEA3K4FqRoDPTPQLKZ/1NPM5PuRZpojiNgY+8fLppJqlYHTfjqm08i6qopCS/ERrUzAAH9xAkFapPPiRh3zkwYU8IOgCAiaPHZIBKzRxyNJMKqQMicjnJk9yrkIqcn6hR6iQCqVxbCyrkCohnauKkGJ1yGNXjSTKXMF6kp9fBy3BREsUl4P+gPVJ0RcAgsFCIXWwyDn0potbf+he+ksJVA8CrCxEs5CyGvCyIS/tzHx6QwNfCqzgWvZqa7l6pFt1uQtTaeX9VEkhJYVNUFqPShnDgscTQMDvhRO0SjHfeQG/Bwh4gCDzXOVMZGkmFVKGRORzkyc5VyEVOb/QI1RIhdI4NpZVSJWQzlVJSNkNeqwP0Cw/pL4UEPEEiqY8N7CnAEjbD+wrABx+EVLSd4p9Kuwyx1S7Qn+XgEE3K4FqQ4CVhegVUrQxmT82rGKllo2rWPs1TzaXjZjiXKeqRMBUWhmnqimkrLZ9oo88biA3E8jaARRkAv5c2qisosPvtsSUCqmqlL3+VFxMnlQh9afwHXKQCqlDcBwTP1RIlZDMVUVIsYpkqkqcMxiLVDAQAFxeYNt+ZMbOwh9vfo0DsxKAzBzpL+VFQPpMyf5B61g53q53yXIJHHSzEqguBKJfSJlGexRUoZap0BTiU00RVXnWgtDY6PJBAqbSyjVVUkixXPAE4KfFqWArsDYOe+d+AMfKIUDOKvjpfIL7+CikuFx5JQhZmkktUoZE5HOTJzlXi1Tk/EKPUCEVSuPYWI4aIcXMyYecfX5MML+5jYHrzQvhaCVfVRFSUnCxvLL7+fKroKwLBuH2+wCnDztHzMHvd/fB7A49MPe595G/ZB38bq84mWB1S1wu2UJKvlPbQopVrYPF0dEip+dRAlWTAN8RUW2RCgJsxUsZ5RcXM15591nvA/NeMOz1yTYkqso8tIyqikKK2sQv+SsP3p2jsfuXptg9+lLsHt8SSH4P8O0AXVHQAUVlFxxkaSYVUoZE5HOTJzlXIRU5v9AjVEiF0jg2lqNGSPEB9/l8UmEwwolzrjfCysy57mhNVUpIUfGwJZ9VjMktslEPPfUhx4Ftn41GfOsXsbxNN8x/cAByZiTA63SJG3T5Lk2ftvbxbPZuKl4qpI5WbtHzRAMBvh+iWkj52M8/CH+Afjid8AccCAZsKwE/ttgfXKy0OHrvwmhI22iII/OfKaOqqpCi1z4fsuHb8TUOjDgRBcNqIH/42cDC5wFnKoK0SjH/cTSNSsxihiPTXYXUn8/9Jk9yrkLqz3PkkSqkysYvGo+OGiFFkcQMGjrnQ2/ElNfrFaEV+mI9GglSpYQUzUgBq8FOAW9OdBGrUgEEswuw44PhWNfkRWxo3g3x9/SHe9py+N0cC8QeX8rFsWe4zLGnVEgdjfyh54g+AnxHRLOQspr00rEM3wK5QJDBZX0YUSFV5TMk858pp6qikGIW8sowZXkIpn4Jx9AaCMQynArM7QIU7BQfRxxfin6N6A29sibDkddXIfXnU8HkSc5VSP15jjxShVTZ+EXj0VEjpGiN4kNe1CpVVFiZ30crMaqUkLItUhRCHM9DKlSBoHhR8mbnIX3QKKQ0fhFrm3VF4l39EZiUAL/TDZcRUlRPdOhnD+QrFilbmFViWXi0kkrPowRKRYDvkagVUnxQxVzAZlUHgOAuILgHCOYcMkgvd7MCq8U6VSUCptLKOFVFIUULEwWS+IndGgPP4BMRHHw8gjEXADO7wufIgYuZi1ZQ7sflSprI0kwqpAyJyOcmT3KuQipyfqFHqJAKpXFsLEeNkOIDbixSFEtOpxP79+/Hnj17QLFjLFPcRuvU0ZqqjJDiDVk1I9FPYlFi+zwfrUsBuLLzkDpoBNY0fRErWndD4j0DgEmJCLq9B4WU66CQcprzqZA6WllFzxMlBPguiV4hxQ5SbsCbDXh3Imd/EjzOLQgG9oIWAvOOsF4VbPgrvSGjJGWOjWiaSivvtioKKclD0vrBD2yJhXtIA3hjasAz7GQE5zyAAt92GU0qiPxK92dClmZSIWVIRD43eZJzFVKR8ws9QoVUKI1jY7lKCanQl2JR/KFCiVapjIwMfPjhh3jggQfw22+/iXgy1qrQ85gXhDmf+W32MXOzvei8/IQUHRazjwNF36FfjTk2zME/K0YsLoyjY84t5xGWkOLAiRRSGz+Mw8qWz2F5m39j6d19EJgUD7+HQopWKFbAeB0/vHbgdXkd6jEuWfHgPtEWrGpjYS3S1Car3bxo7tTff4YAmyIVFDjQt9+rqF2nLho1ugIzZ8468qlCKmwmtxVmL3lcOLyA76CY4TruKJ89+IzzieWfvdos0OOZedzY36Twe4m1b2ikrDX0AkAhlQl35q9YNaM3dq8ZB3iygICzyLnss9kjH0g/SV7MjhvHoQrI+8d+5M3FZTsjwwUeZQ2jEBI5WbRPExpFXS4FAVMGcdcKE1JMW3syyRyyymwqTGI6gg0GAwhuG4L8uNpwxdWAc1Q9+ObdAW9gA5woQAAFYrmSbMLnozKCFVG59rYtW9CmZUvUqVkTd3bsiIy0NKvdYWXEK9quSY4Sgvj0o49x8oknon7duhg/ZoyVrmZ7tN1XJcQ36PcjMyMDD9x7L+rWqoWm112HLRs3HZoXWQhVQtz4gPO5t7/BW8+9/YpnG12u50d6+fzGHc02+iKwRy40733OGWSyXyqFtVn+Njvap+Gqwyb7OPPi4U9eUs5rH2DWmWO53exv1sncvjf7sNDLy+68J8ZPtvO/kP3NMYecL4IflSakTBO8UCuTEUvh4m8KH7P/3LlzcdVVV6Fu3bp48803kZ+fX2ixokWK5y96DR5LseXxeAotWEe6JuNRXkKKUsiLLPiRYzW0Y0raudIPv2z1wSeZipuYeVwyzjzXMktwL1aFLA9Lrux8JH88BMvaPoXkVo9gyX29kD8zQQQmhZQTQbjghVuGVCwAggXwg83+/GBPC16Joq48gpV9mYXLK5BHaYN5TAk72sKfeNx5SBQGKWPKKeocwzq/wI0+/QagVp36uOzyqzBj5txiMcmGAMWEFSHJQVxm9pG3Mz1iUtzkAb4DgCcIDrFDAxECfLqyEESeyBZ5cs2xPBGtSyy5GMRTGk/JtwNFzsGXvnUIn3k3vLyoZx2wfiCyRp4JLH4fOOCyr2/HSSqYdhzdVjT5DqBrGnkMfbxcATzItj6iWF9TrB2lJGXFijfBRsQUaLbpWm7AGgdcbi/cy1rXHZGAKcu4U4UIKZPf7IqDeVOaNyE3c+Kc65j8efK29sG381vsHV8DBSNqIG/kCfDMuwNwrqO3E7iDzNksU+j9xFTEK3huD0JPRZe2aTPaNW+B+scdj86334Hd23dYhaN05KrgeFUWj0ivSzYS2OeSIYAvPvwQpzVoiBNr18GEUaPtcSrpfcTaXmlpHem9Vcb+ZOn1YW9aOh66pzMa1KyJltdei+0pKYV8D/KujDxpPeNZ9jPOMoavd1YCA24f9sKP3Qgil6WPlwVlAHBaeaTA75VuJC778xuLDJYB8v6wXybZtkizK6xWeWJ3JeEuMoW+cBgBbrCrhlxkdPgOMgUgd2Ed1pS/0q3FHBd6LnGQY52O+/KU5ppczgVwwL6UbJAy0Iqi2c+KYOT/V5qQYmFiLEgUPPx9JFFj9jeF0PTp03HFFVegdu3a6Nu3rwgpns8ILc5NMOcPFVfGOYURW8WhKz8hZSWyZGSTKZiasoK5g0nP7GQHVuS4nUEqbyHLzGV7fNj83lisav4SNl3XAyvvfB3+KaukM1XoR2/r9EGp7PFarLCay/Kq5RWK43t01jPWvLOSA7+rVKU/6zsPv/WUJhy0aJQunXjO8hHH5X1ejo9E596lD9yfI6aVHHzwIM+Zjd79X0bNesfh0isvxvTZU4o9lvd68BsemTKnMYY+uOXPCyd88rLn00r3Ln6wqZ3HelbN57+gZUs2jy/PKqKID4E8mNZ5KZd4fplCs7Q8n3ZjPXc6fClfYO+oM+Bb9gZQQEGUJ18UeV5ak/hsS2T9HAKBn1DsdYyAfH10iU2cu/Fy1nNhHyKvF8aOn1pM0UaLG2vjBwkcbjezoq3/F0/AlGHco0KEFC9k8oKJlpWEB8sU5rOQL7SS/ehxYvNwOGP/gsCPp8Iz5BIEZz0C5GRaNRs38wwlP5+9yvkzzwqvvnnbZrRo3QLH1z4et995B3Zk7JDPjZUTs+i6KjlafwF8+OmHaHByQ9SuXwejx42WlD24NbruqzJi6w36kJaZjs73d0bNOjVxbZNrkbI55ZC8SJ6VETd5rjnsqN3PXgQL3wVWYQSfPwBPMAgvnZL5AuKozM2x4igQfZbDNxmX1LxHTPlkV0vlfNzGMsb+wVPzp7l2aH1TTmN2sN9Bsp/ZyV5nLsNd83kQt/tF/8miHCPdXKx742belllv7WQdZpWJ1jZTFkv8JDJ/7r9KFVIUOhQ/RgDxNwuZcFNo4cP9pkyZgksvvVSE1IABA8RyxPNQIJnzsh8VLVXm/OwXwT5VXG/WGXEV7ppcV15Ciue26yNWYhfJOFbBR6XDz9R2RmYu4n5MdTbTY+7ib2bYPX5seu8XJDV7FSnXvopVnd4GJq8E8tmkz97PFk5yHI8JWS/riL66h+ISurLWlydvuSdmmmgMJnMyg5cmcP/S3Seb1BY4stH31ZdRp+5xaHTFRZg5a0qxx1NIscIoDxwfWkYnyKKQ4sSBAriQD584gHH5AFcgHx6kg8WQ7Fv46Y7noDChQLEa9vJrPoVKUJpKUepQ+PLBtp9F84xzbucVvhLg2g/Ppm+wb/SpcMf3Btx7kAen2Lfli52w4AE8jlYsj4iswmcelJMe+Wk9+x6JEf9nIWsCPX6yKTDjbIlJczMmfexrWFfS/0tBILQsqwghxRRiah2SYlxZJG/xJ1OZqS1eID1+YOMoeGJOR/CH0+AaegE8czsDeelWmcNMQvOuPSy0ZUm1mp1X1LL1ZPKaAWxM3YxmbVqiRp2auO3OO5C6M03WV1Rcovc6Bz8/keOgTz/CCSc3RK36dTBy/BhhaD5PRe89VlS+pBDxYUdmOu5+4F4cV7cWrm56HTZs2VgkL7JEqag4HbyOlEd8yO0GBuY9L+tzfcCObDhXpcKTkgnsy0euzw0HSyUfrc5BBP0B+Gnp4xTy/uApWaWU0oDlE182XmsdyyOuknUBa53ZhbuZ9Vxm6SITz82TmfeU/VuKPu7AncUibh/D/fidz76WxND8sOMiLzcu8yQh52PcubosU6UJKQqZ7Oxs7Ny5Ey6Xq1BQFSekjOAxIolCihapOnXqoE+fPuJ4goUSz8Wmezz3woULsXTpUvnN9cuWLcPAgQOxZs0a2Y/ndLvdcu3iIJankLIyClObSWl/9RXhZCe2yQAm8eUbBl91rN444YHT+h4e9MKVXYDkD8dgSeu+IqaW3/06MHUJ4HBIMwy2d+e39MIMYz9MoubEBG5XEJnJjnZgpi3PEGl8CeFYCOaFUZ7sy+vckaZpJPHgl6s8J17r3R8n1KyHqy69AnOnzy4+j9rfIiQP87lh6cM3vozJRkFCe1Q+4M0FHHmA1yGNZmmXcrOFhBiTabsxB/MELHY80v4viBz4pJlv/sEnlK8FtqOXJoUsIRjsjye8tvMAfFt+QPbohvDEdwU8GdgHSJChEaTBLpfYPM+SZvLhRuJNWE54GR8uyrNgAQ8TQ9nM3ayz2P2luIKHMJ46RUSgooUUk4pfcRlYqTHf0Kw0tZJRspS9T4HI7jzrA97WWDhG1IYrtgayxtRE1tLrEPQlS0kkGaOS0z+0vqDOJiLKhofsbPIk50WdTfD9YbYfcpD+CEuAdVT24b/vvvvkQ3/jxo2xadOmQ4wEofk27EnKa2XoCz5gFWNs8iZF05YDyP1+FpY+8yGW9fgcO4fPRWBfHjxefoazhtmhoA56fVaZYdcv+B7h+4OnlvLA1K2CVnM6NveTbXZ5Id9f7HVc5jHcxObEmQD227VhnpdBJnNO7sjJbmnPJoqsOctriPuYiJiXGzcw8DhGwrz8rCFV5VTc1ZzWOnnk/1eakEpOTkaHDh1w3XXXYdGiRSJomAHDZTCuozjau3evZMjFixeDVqgzzjgD9erVw/nnny/n+dvf/oauXbti48aNGDNmDJo2bYq2bdti+fLlMsbEgw8+iHPPPRddunTB7t27C5sBUtQVN5WbkGLimsSWbMpKVIHVh4GROWS7nROkadDB5k78rs1mFeyQEcjKxoZBsVjeqhvWNOuJ+M794Z25FHA75Gsyv3w7pKeG7Trd1J9scWZnxeIwlHk976D8AiuppWkaZ/bh/lXjrzypSKKVH/TyjXpIM6OjfQvUJ/kFTvTt1x+169RDo8uvwIyZs4vNn3w75EsjQ/uNz5c1A8sTNntgM76CeLjX/A+5s15E/tJ34N05Hcjfbb24/dyd/ZH2i2CSB58nFS3Fu7Pcv0ihwZ9ckB/cicWELYhM6eF3Ae5tCGwZDFfsucAf/YH8LLFG5UrvSlaZ6RqdLtIZP4eVViwt2ERDTFr2JXgdH++L+/E6PIZfH+3ShVHgcYyXPDMSMWs7t8n6Mr8ejqkThFZKK8IiZaWcjZjpZfKYWS6yib13HazW8APb5uHwxtaHf3A95I04EdkL2yLo3iGbREhJ5mCess9b0XPptG9de9uWrWjdshVq16yFTuJsIt1uilpJcatoFmW5nny0sZrtfvLxxzjpxBNRr25djBsz1mJYuF1ZlpTXA34/dmZk4P5770Od2rXRpHFjbN60qUheLMcCrqR8wFc4X/dB65sge+nzt3fhBix96B0svaEnVtz0MpI6v4mNH8QBq9OAXBfyva6DHqB5DgZbkLCIYHHAIK8Ent8WaizBWFwKN+7IbfZ2noLHmFXcLJN9XruYta4Vcj2u5zG8VftU1nVtocRdrTLU2l5oFbPZ8DpyLfuCsr996T8zqzQh9eWXX+Lss89G/fr1MWLECLEKhRNRvCkKrA0bNqB3795o0aIFLr74Ypx++ulybM2aNUVMUVCdeOKJaNasGVauXIkvvvgCZ511Fi688EIMHz4c8fHxaN68uXwh6NixI9LS0kS0FSfeDMxyFVJMRHme2MSmwA78js0vQNZzx5YTllxidhHZJBmHhxZmIHZ037cfGwf9hOWtn0Vyi+ex7N5X4Z2ZCLg4ihS/PbOXBP0sWULKtFBiHxRmcwoRZqbShuKe1eKO51XKL5CQ8UVYUXMP/Ig0HB63g40qTOMJa840OzxYza/YKKx0gaK79GnKfcOl69E4B88b6XmORn4Jd02eN8/hQO9+/VCzbl1cevkVmDZzpsQv3DX5nFGaMJeJCGGzWr797b7X8KUjkDoceyZ2RG7MWcgfdQmyp3cEVnwKpM0HctMA3277W1u+BSK09DBfxxhZEwFZZ70XvNJwkGluIBYAns3wbfkJ3qEXAPNeA3JzbJs2n+U8q2kWK8LyfrGFEQUS9oMjz/Fpl1ZZYrGiNwo2NOH3QYoup90m3n7J8DDRkOwVxnjYnwMZVyasThERqHAhxTSSgoR9Y01fW6siZ54PSUb7IWVZkC35IghsHQ5PXD0EB9dH/rC/IOf39oAzU/wSUI/7pWrFJ6SCJ8ZV4ssHxSost2zejNatWqF2rVq4s1MnZKSlIyjPgF2YVnAUo+ZyrAyw2Rb7qgcCoJA6+aSTcEL9+geFFK1S8hFGckrU3FqFRtTOjwHfQSFVt04dNG3SBJvptc9U6mzelfHu5Cubr3Nem88+dQfLNlYm3Us2YuGj72Bp625Y36wH1jXphmW3voJ1vb+Bd/YqIC0LgXwXfHTkxkdKxPXBhhJ8C1A0Id8D7HUAB9zA/gIgj03c6f0hYK1PSod/+VYgMxdwW43Ggx4fsN8JLNoEz+xVcC/eAP+eHHi9dGpz8EONfUmJM+MuN8APgZ4AkO+Ta/D9GmAZTQdMOW7A40OOlIr0Smi1q7CLtMJKdFlzdaUJKYqihg0b4uSTT8acOXNELBUnpGiNGjJkiFie2JSPookCjIHLtExdc801uPHGG/HZZ5+J9em7777DOeecI4KrZ8+eePXVV0VUHX/88bj99tuxY8cOEVJs3lfcdZlO5S6kpFpCkeOCW3ot+K0PxGzJ4xcHMHAF/HBzFHnplWHlHWZaBnE96/YBeyikfsCyNl2wku7P730NwelrgTwv4GFgz2CpCkpdzVQEpUT0ueRixl5TmjkzXtFQ3HFWF/uD7XSPbttgq9M/v6KGhooXVoeLpNLEITIhRZFFORwu0JdO0cBmoJEJmKJpyt/y8rLrK4csF3PucOeQ8xSzf6RxDL9/eJtkOLujPxhAbn4e+r3aD3Xq1cVllzfC1OnTwPXh8jALH760xUemWHno9dIy5Hh4Y75MBDd+h8y4vyMwpAYwtAaCQ2rAOfw0FEzpAH/8B0DGQiCXnfTpNc8vHkXZQDePww8YOHy7M/AGRdawBxb7YDnF16aMXiD78FNfKvI3fQ33sL8Cf/QFcrPkURZTQdDLsoNllDheYvnl8QfhChyABzvgxD6xkHmDbN6XBwecyPOLPz94Am74gwUI8p1gC8agj88uJRRda/CDD7/v0XJlGmkwvjqVlkBlCKkAm+N4fDKuIB9oH8sUaa5jVX7kizFvwK5hsJkoF7Hdatrnj6mDgmGnI3vu7YArg7pbsocTeeJypbT3frT2k3cMHVSFeOdl86mWLVsWfixNT0+3Wp3Y+x2ta1e380jFk5XPgNX/5SNapE4+GQ0aNsTYsWOFsbzm6MCLwlSnsATkNU4nanbTvnvvuw916tZFk6ZNsXHTJoujzflIdc6wJz9KK1mOUexIMWLXIeXZp4e+rfuw4fOxWHx3fyS37oVt1/XA6ubdkdC2J1Y98A4yPvsZuX+sQSDbCbfPD68MDM9iwCcNHVga8EN9VuJGbI2bCeesJKR+PwXZUxOAvS4RVtkzE5H8wudY0vVTbBo6HdibD6/LC+wuQHbcb9hy33tYeXNvLH/kfaQMnQbfrmx4ffTADfi8fvhY13XTIBCEmyvz/UCeD4HNu4HkDOQGfMgP+OHLyMK+iQuRO3UZghsykB/win9atvtieW4XsVbBbreYLwviShNS3bt3FyFEq9H8+fNFzBSXuWg1Yvvnhx9+GO3bt0evXr0QGxuLiRMnSrM9vkC3bdsmVib2jWKzPW6/6KKL5KV60kkniWhr0KABaMHiOSikTL+rIwEsNyHFmhi9ekkVxergzV9MZBE+Djbf8VjLbhfgt/pTSCZgLjBPAp+MgiCQkYMN747AghavYGnrN/HbfZ/BMTvVempYiAY84s7Yqu5bxwdE6VNgMftTlvHsh4bI5Q9l0+GhKH9AdAAAIABJREFU9N7XDjZdDHcMbXKHBj/8LCj5xbxIIKZwQQrhcEIwnFgoZp18XIrgHMVdk+vDTcXuT29sYfiGlxHlK2GLyxv+oAfhQiDoRWlDMOhF2BDwIBA2uBEIuEoV/H4nCgoOoH//V1CnTg1ceeUlmDlzshwbDLpRNEg/JT4ePvYpYkOIPXAjH/nwS7vuABvV7Z2N/b91wa5h58M5uB7wY024h9RG3rD6yBp7CvZMvAjZc++AP+kdIHM+4NwNj8+PQnexTHDJrPKpT9LYAY/YjmhT5scksSaw0xWffe825Gz8D7JHnAXf8gGAay/8bifg3Qf4s6V8KeAHOj7O0hWKfSoPiDCj6wm/n5VqD7gP74htzambvOw3Ks+YHwG/DwGv9fWRrxnKJwbaYaUECvK9IdXtcFlY1xVDoKKFFLNVnvh0pJfJAFxeDzwBCmP2e6Ad0rJ9ywuUqt4DOJmstEBsi0PeyFPhiW2IgmHnoWDWPYBjA+BlfuS7yCmtAcyHvQqds8l/gJ+iGJUANm7bhma0SJ1wAm657TakpqfLNqdXegPKcoXGzy5Vo+GarJR6yTMYxIeffooGp5yCWvXqYfiYMXD52dfTcrcjr54ouq+KZk8+ZLU9IwOdH3wQtevXx7VNm2JzaipcdIYWDMJNJ2uVxJB1TBPkEbfrNz5/UAQR9hQgOH8DVnT9Dxbf1AvLW3bDmta9sLplDyy5vjsW/PMNrBw4FNi4G8hxweNkWc9yIwiPPyACa8NPkzH93r6Yf99r+P32V5DwxEAEJiwHlm7Dom6fIuGWV7D4Hy9hQddPkJe0FcEsB3J/Xozkf76HxHtex9pHB2HBPf2R+NgHyFuw1voamO0C1u2Cc/oKBOesAbYfAPI84Ec+7MjC0vd+QvxznyBn5z4cWLEJK7p/gdn398Ov9/RBwgsfI7hjHzxumits6xbfzSxzCcP0gS7mfV2a1ZUmpHr06CFCitakkoQUCx5636PHPQqq1NRUTJs2TZxMvPLKK3jrrbcwbNgwrF+/XixIFD/jxo3DZZddJkKKVqtTTjkFRkjdeuuthU37ihNvBl75CSm74mQnIisqLPBEMBWkAfsTgbQ5QMYMIGMqkDkV2DkZ2DUdyJwFZMwGMmYCaTOAbTOBVTOQ2v89rGj5byS06Iuld/eGe9QYIHUBkMb9JwMZvwC77HNkzAIypwG7JgGZ44Gdk+x9uF9ISJ8ERBQmAulhQtpEoNRhApAWJuyYAByV8AuwI0zY/jMQSUgdD0QUfgZSSxvGA9uKhNRxQCrTNEzYNgYoGlJHAqlxRydsiwXKGrYOBSIKMcDW0oYhwNbBh4ctg4HDwk/wrP0aY96/BU9dXwN9O5+MVeO7AZt/CrPvYGBzLLBhLLAxBtj8DbDtc/i2fwvX9hg4UkfBz+tueA9Y+k94frkIrtgG8A6uA9fQGiiIq4G8YTWQP4zzk5Az6krkTr8P7rXfAI6UQueb8vQH6RiCbwLp0itWMH7l8/EjiGcfkJMCZC4GMhcC+6fCufZ1ZMVdBOeKj+H37AfyUxBIHwvsmWh9reMHlIJ9wIEUBPIWIuBdBS/HunI6pCkgsveKHnL4gFyav50pQP5aBF1bAedmwLEFcKUD3gPwB1kJN0LKfjvKOFMUVTpFQqCihRRTKAcBcX8Pt1e8cXlTMpCbmIL8lZuQt3ITClZsgmf5JgSXbUJwaSq8SzPhjd8K15QfkP1RE+S983/Ifrcdcr98Hlg4D1i2AVi8GZ6E9XAnbIQ3YUuFBk/CFriXbYJv+VaZe+I3I3XiH3im6a1oe+KF6HnjvcicGQ+udyxJqdC4VTSLsl6PjMhS5vGbMeyVD3DLaY1w48kXY86nQwrZkXlZr3UsHE+Wu2YloF+Hh3DDSRfhsatvxI7JCy2+NmfX0k2VwtIfvwWBZVvgi98Cs4ylW+BL2ApX/Ca4FqcAc9YB3/+G1Ic/wqo2vZDcvDuSm3bDWlqnWnXHotv7IPm1H+FZthnIdtme0WmJY/NPIO27KbJPfOtuWH7jS1jWvjey+sUi8/1R+ONfb2LPi99i3S2vYvHj76Fg0XoE16Rj3as/YPlt/bDzmynArxuxsuvnWHVrP3hmrAT2FmD3jHgs6/4fLL3vdcR3fh2r3/gJ2LQHBcEAvGvTMe+ZD7Dl4Q+BpVux7r1YJN7aF8k9/4v1jw9C4q29sefnP4CsfGl1Ylkr7Dc21eRR+BxYaUKKze3YNO+0007D77//XmIzO1qP6Nqc3vcSExPFqsTBeGvXri2e+yjI6ERi3bp1IqYmTJiAK6+8UgbspXc/jjVFpxRs2nfXXXeBZn9ToB1JTJWbkLK/QNMoZH0Jto1B7t1A+hTkLeiNrGmdkTO9PfZOuRE5U2+AY0IL5ExuiZzJLZA3qRnyJzWBY0JzOMe1Q87we7Ht2VuxuUUnrG/5PNbfdjuc792FvHEPwPXLrQj80hrBn5vANbE5HBNawfNzWxRMbI38iS3gmtAYgZ+bAeObHxYCY5shojCuGQJFQ6TnGNMU/lKHJvCPvRr+cX8/PIz9O/xhQmDsVQgbxlyJQCmDf8yVCBtGXwl/2HAFfKMPD/5RVyAQJnD94eFy+Ec1gn/UZaUKvlEXwzfqggjD+fCNOjR4Rp4Hz4jSB+/I8xEuRHIOz4hz4RlxTtjgHnEODg9nwz0iTBh+Ftxhgmv4WTjw40nI/F9t7P32BOTF/CXsfnLssL/CG3sBfHFnwzvsNLhHnAzHiNORP+KvyB9xIZzDL4B72BnAiAZAXA344mogP64O8kfUgGtEDXi57rvaCHxbGxhaHzmxx2PnhObAtu8BJzv1m++TxubD/nF2szy2y/MeAHKWIbDqc+TN6oI9Mx5G/h+PwznvXuQMbgTHyh/g9eTAl/4L0mfehayF9wO+tUDOCiBlFJx/9EDGH09j/5qPgAPJwIaFQPJsYMNUYPdOwOlEwJ2GA8v7IXfpKyhI/BSOhEFws4/XplggOx7wclwsqyUEW4HQIms1I+SCTpEQMOUOj6kIZxP8QEdnKTKg6j4XXFMTkNz/OyQ8MwgJT32AZV2sEN/lAyx/8gMkPT4Qax79CAlP/QdJj/bGxjtvx9aOnbCpw8NYe3sPJHV5F0ldPkLyox8jqcvHWPX4IPmKzC/JFRXWPDIQqx96H+sf/wjrHvsQKU9+gpUPvI0prZ/FuMaPYdr1zyHpn+8i+WFrH+5fUXGLtusYhmRFlvNufQljr3tUwtK7B+Agu4FY/9iHyrHYfD5Q8iPzZfLDH2BGuxcwvsnjmNrmWaz617vCjevXPTZI9quMfLLh4UHY+NAgrH/ECvyd8tAgSfcVj/L5H4jkRwdi278GIb3TO1jX+iWxRiW16I51zXtg/XVdsa5pdyy5sReW9fwcubQYuQLwePzw+oPwewLIifkVK2/ti03Ne2H1zX2QdEsfpHZ8C/G39kH8I+8Cw5dgQ6c3sfLJD+GevRrZsb9hycPvYP1znwNp2fAmpeLX5wZiy93vAFNXo2DBOvz22NtYePNLWNmqh4i6xM5vIGviEmkazw8lix5/D7se/Aj4bAaS7n1L4o/47fB+PgUpN/bGpkHDgIxs+L1eaUQh5StfwGK9KJxF8ho/ZN9KE1LGIlVUSB0Su5AfFFL0rpeVlYUnnnhCLEzsL3XeeeeJUwlam9jfKi4uDgcOHMDIkSPFKQUtUeyP9euvv6JRo0bStO+pp55CZiYdLbIuYJMMuVboYrkJKZHFbHDB3gd2k76AA3CshDfhNewa1RhZw06XCllObC04h9WDb2hDOIadAMfwOnANPw5OVtSG14Zj6OnY910zbH6iLTY1fwCrmvbH+ls7IH/ANdj30zXIHXIuvEMawvvT8XDF1YMjriHcQ09F/rBTkDec56wH57AGcA5rWObgiGuAcMEZ2wClDY7YE+AYenhwxp4Q9hzWvvXhGFq64BxaD4eHunAOjSSEO4dZd/h5XLH14Iqtf1hwx9ZHuOAaWg+Hh7pwxdYJG9yxdVE0uGLrhjlHuPPa6ySOjGeYEC4+xeznjKmLcME1lPEpfXDH1EXR4IqpA9eQMCGmNlwxtQ4L7qG14R5ap0jgutpwDqkJx+Dj4RtWX7ZzOez+sTXhiqsBd+xx8MbUgm9IHQR/qgf8VB8YXB/4sS4wpB58Q+rCObgWnN/Xh/e7E+GNqQH3kBrw/FTD2o9N/n46DrmDa2D/z02A9f8Fcnbbjh741rEboohIAfx8Mfj8gGMzHInvI3N8K+SOOgu+0VchN/avcIw6CZ7BNRBYOwjw7QW2/oy88Tcjf0ITuLd+idzfH0TWiCvgG3YV8ideh/1zbkDmvLuQOfIa5MWdC8/wU7B7+iPAzmlAbhL2jW2GghHnwTXiYjiHn4esoechc9jVcCzoBuyje/gD8tZiLC07FG1UapEKLS9Ks1zRQooplM10YjOY9Hwk9foCi27uibVte2FDqx5Y27oHVl3fAyva9kBiux5YfX0PbGrVA0tv6IOlN3THmraPIrn1Q0hu9QySWvXEwlufxJIbn0Zi8+5Yef1rWNGmD1a27VXhIandS2BIbNMT8S27Ib5lV1le0ux5rLi+F1YwTu1ewuobX0Fimx4VHr/KYPJnrpnQurtwJMtVN7yM+FbdrNCyG5bb21bf1FtYKsfi8znZJLV7GatueEXyH603i5s9j+VtemBZixeFH7eZPPtn0upoHMPnYnk7KyS2s+6H61b9ozeW3/Qy4tv1Qnxbvg96IalFDyQ1747lTbvK8uoWPbGm1UtY2aIH4jv0w5J/fwzsdEtffbpR50e2PTFzseL2AVh3XTdk945FQqfXsL7lS0i+oTfW9PoavoRtWHD3ACQ+9REwawO2//t/WPDQOzgwZiGwJQsZ30zFwrsHILXX98CklVj+6ndIvrEPdr7wLRLvexuJrXogoeMAHBg2HwFPEP75KZj3yNtY/9AgbLjpVax44F1kTViC7JxcHBj/B9bd9ipS3hsK7NgP6c7CvsN26wp5X7O8LeP3wEoTUsYiRe97tEhRJB3JMsRtbN43c+ZM8fbHfk90nR4TE4OXX35Z+kDVqlVLxkDYt2+fCCp67OP52fyP7tafe+45XHvttRg8eLBYrQix0rz2iRRmlzm6XrCVsZ/j0CTCk/A6do1pjuxhZ8AztBa8g2vAzwrZkOPgHFoD7qE14I+pAW9sDXjYfOin+tj9zd+x+YnW2NL8QSQ3fh1bbr4F3j6NkPNDIxQM+Qt8Q2vCN6SGNDdyxdSA/6facMbUhGPowXUubi8SPDHHwTP08OCOOQ6lDXIOnieCEO7cnpjjES64Y9gfpVbpQkwtuGNqhw0uqYyzQl4kDK0N12GhDtyxhwcKHWfYUBfO2OJCPThjSw4UOMWdQ0QThVNI4DkdsfXDhBMgYpWCtcyhARyxpQkN4Yg7qdTBGXcSIgsnwhkXQYg9EflDGiD7x7rI/qEuCoY2LPZ6jmEnIW84Az8+/AXO2L/AM+Sv8A8+E4hpiABFVMxpcMVcgvzYc+COOReBH/4Kz2AKwRrwxNRAcPDxCP5YB/4hpyB3xMXImv0osGsa4OMgvPT/SL+dLhm0UV4IrPfSs4cnHdg5EbuntMf+SW2BxJ7Auv/COfUfMraPL7YBsO4jwJsGpE5A3vhb4Bx2NgpmtMLu8U3hmHU/kPAJsLYHnPPbYPv40+CZ9DAwowscs9ti35i/wb/oZSBzHgpGN0LuqPPgnXc3fPHdEFzyCrInP4Qd45rBse59wL8Ofulrab2vxCpVGuWg+xxCoKKFlGWRsr1mpeci6dVvsPC2l7GyVTekNOkqYX3Trkhu3hWrWnTF2mbPI7Xx01jaog/iW/XBxuYvSLOe5GbdsLL5c5h787NYdOMzSG72HFKavIbkpr2R1KJbpYRVLbtjZXNW8rphVavu1rxldyS1tOKzotkL4D5mW2XFsypf17AhR1kmuyKBDKvyPVSFuBWya9ENK1sczJOG74rmL2JFsxeFrdle0fFObt4Nyc26Y2XL7khsZYUVLbtjRfOuWNmiG7ic2LIbVrTqjuXNu2J18x5Y3awHKKBWteyJpBY9kdS8B5Ja9kT8zX2wutuXwC4/fN6g9Pf1+4GsYb8joUM/pDTtgeBXc5D09CdIbtodCbf0xo4vJyKYdgCLOr2KNU9+DIxNwOr2/ZDw2AfIGbMQe76cgqWPf4Df//kmcqckYP9X07Dk/jeR9syXwNS1WPvqj0hq2g1JHV+DY9xSOH1+BH9bj/n/egsL2r+MdW1expa+P8G5Y581OuOUJVh752tY0/876UvlYxMwu5sxm82LGYX/lfF7YKUJKTqboNc+42yCQoqipriJhc+uXbvQrVs3UERxPKivvvoKq1evBi1MPBebCn7//fdikWLTvquuugpnnnkm+vXrJ84o6JBiwYIFYtWiJYrnNPPirlt+FinKJ7unm0lIGR9mK5AxHrtmP4OM0W2RM/zvcMddDu+oK5A96jIcGH0J8kdeCM/wc+AaeQYco85BzvArsDPmFqzrcgs2NHsQaxoPwKYbOyEw4CbkDmuPrJHXInvURcgeeSYOjD4XuaMugjuuEfJHXIbcURcjb9T5yB95EfJHXHxYKBh5CQ4Pl8Ix8jI4RjYqnzC6ERyjL48gXAXH6NKGv6FgzNXhw9irUXBYuAb54w4PBeOuQcH4aw8L+eOvQ/74xqUOjl+aodRhQnO42BQzTHBPaomiwTmpJQomtTosOCa3hjOSMKUNXGFDW7imlDa0g2vaP8KHqTfBVTRMuyn8vsWcwzPjFnhntj88zGgPbisanFNvxtovL8LsfrUx/82G2DuqBbwzOsA387bDgmfmHXDNvhfO2Z3hmHMnnHNvg3vmA/DMuBe+WTcjMLsdAjM6wTvlCXimdwKmtAHiLoRzcAN4YmvJhw/fUFq7TkPe8Ovgn98DyJwCn2e7DKDrEifSbuyDE1wWIUUna3Tt4FkJd+Jr2DfuCrj+eAbI3oiAywlnwptwx9aEJ+5SYN3X4sXPkzYR2ZNvgyfuJHiH1UHgj8eBXb9a7fF2jcCuac2QNfUUYM1MYMd2uNPHIXvkBfBO6whsmwznqAuRPa0NsGckgoE0ID8TWD8FGeMuR8aCfwLOuQgE8iynG96geLOVgqi4l6euD0ugMoQURxMM0rqZ5UT2tKVY2vMz/NbpZSTe3herOliBy8s69kXibS9h/c0vYmGnd7Hsjv5IafsQNtz0b6y/6VGsurkzpj3YG7M790Ti7S9gXfv3sarDW4i/o28Fhz5YetsrWHZ7byTe2R+L2r+E5R374bd2L2B262dlzu3LO/XDirv6Y0mHlys4fhXN489dL+GOvsIooWM/YZnQsS8W3NwDc69/DjNbPi1cyZHryZnzik/r6LimxaaP5LXEO1+VPEiOc69/Xtgyr67q/Hoh58rguPK2fljVoR8Sb++H+Dv6YVnHfljSqR8S7hqAxR16Y1mHPlh71xtIvOElcTSR2PhFrG35ElY27orkZj2s0IZWq5ew+IG3gFnrgT1uaTghbtT9wL6hc5BwW19sbPkSMGEFkl/9XpoHLrr/deTMSIQ7fT9WdOyPTY9+hANfTRUL3eI7+2HeU++J2Fr60Nso+GUp3Kl7sKH3d0i+503sGfEbsO0A9o2ejxS6Zr/jNfh/SUCe0wXMS8Gie1/DwnY9sOLm3sgd9ru4PxevuFOXYe09b2BD32+BVI7jyHbploCSBh98Q1N28EcZpkoTUrRIcdyn0KZ9R7IO0WvVzp078eijj8pxFE3s80SLE5v1MdD1KQf3ZT8qjjvFkaU5rhTFFb35ud1usWqxrxXPRxF1pGuSa/kJKaYcfXbRjbDti58JTMHsz0fQnQYUrAfy1gDZa4AD64GcbUDODiB7B5CVCuRsAHJWAQcSgdTF2PjOx4hv2xXxLQdg6f2fwDd1NZC1GyjYArjXAu4kwLUGKEgBclKB/G1AwWagYAPg2gS4Nx8ePFsAz9aKDd6t4pWMnslKFTzbAc+O0gX3DsC1PXxwbgeKhuL2LW69cwfgSCu/kL8dKBoKirkmnZaEDemAo6whA3DsBByZpQwZgHv74UE4pgKuMCHs/mH2k2OZpkzbUgTndgSyNuLjAf/G+SfWQJu/nYn5k4ZYaeZMAw4LO6x84doMeNcB/lWAbxuCHD/KtwNwbxLHEchbD6T/AueCf8Exui68Q49DUJr1HQ9HzCnIm9IB2Pgd4NgGuHMBfjgJZFlNrkQ48Y2TDwQdVjtuqpTsJGTNfQx7xtwK//pvEQzuB4I5QMp/geEXIhB3FbAuBnDuBdImIXtSW+QOPwX5MzoBu6cD7gOWW/R1X2HfhFZwL2oN5M4R5xUeRwZ2/Hw19s1sD2yNk48z+VP/gcC+afBgJ+A6AGSuQGBMS+z55RZg9wgEA3nSfIO9ufYjWwZsKEP5c0weWjlCKgBn0Ac/HZBwXJe9BUBmHpCWIx5fsTMH2J0D394c0HMXMv3A3gPwrhyOgh+awvHfy+D+TyMg7g5g2zxg7zYgMx3IKAB2FgC7cio+7MkDducBmdnA7lxkxCej03WtcXGdk/H4zZ2wNylF3CsjI8varzLiGA3XJL+dBwDy3JWD798YhMsbnI5L656K6T8Otxia+8ishHQ2146G+e5cyYs7E9bguY4P4OLaJ+PWq5oifdlqyafB9P0AGXK/Srgf395cePfymckDMvKAnXkI7MmDa3c2AlxPb3iJGSgY/Cvm3/8aFt7YE8tb98DaFj2Rcm1XpDTuLlarP+5/DWnD58p7xO0PoCDgF7fqtPLsHv4blt7VHym3vSYeANd9Mkr6Wv3+xLsIJqcjZ1umCLctj3yEzLdHIOmmV7Dqlr5Ivv9tpPb6DvkzVwC78+Fdthkpz/4H8zv3R/q+ffDlOIE/UrDixpexvEVXrH50IByzkoCfk7C88xtYckNP/N7lfWAF60OWN+eCqfFYc++bWNPna3HvTj+j9j/RTqKfWM5Gq5BiH6kTTjhBxoCaN29eia7IabGiGPrhhx+k7xP7Q1E80TpFqxPHkOKYB/v37xenFBRNCQkJmDx5MrZs2YKMjAxxi87tFFo8HwUVhdSRLGHlJ6Qog9mqlLrZHi/RtlGxgY8HBfAgB95gDnwBVq4KgECe5RLaVtD0kCKfAlws+DKQ8s63WNHyBaxp/hIW3TcQ7nmpCLjoRprfClgB24cgPf1zYE4aw/jxW1yg0xEuxxwK53qc68OFcPtWzjrrquGdghd1xG4NO8ynpvTBan55+OhX4c4RnlU4fmbd/7P3HnBWVOf/f0TpoFKMGjXG2E2iwUgRNLGhRr9JFEv8/hN/3zQ1CtjF3qNgSUwzGpXeEcVCtaKC0puAsHQWWOq2u7ffuZ//63Nmzt1Z2N3Z2bt778ydZ3hdzuydcs98njNzznuec57TfJql0yllX9q4eT7VE0ercPBWEII612sLF88J8ugZruXD+2L/D595tc31VGN+qzpC1ut9GNW5MhTBoPsfQstWbXHa6T/EtGkz1a20/+/xb+X/54R/yYi6BxlMmtZT82aoDMWB8Epg0yuo+OR6lE46DqGR31LdcCMjD0f5qDOQmv1nYOtkILROAZSa3JKN2njEvBet+xGMhGeYA2LVPVryGSpmXoB9k36lIk2GVADzMFDyJiJTzkdo0inAujeAyB4V0bJ8yjmomHgMEl//A4ishcHzcfaDrx5A6ZvnILb0j0in5iCW3oLwrnnY9dYp2DerL4ytbyI09lhE3vs5UPIFKuL0PBlAWREw8yrsevNyYNMbQKwESDIAOufyCFkjPAPJQ42+6FyDlCrCnG8plTInVeUNQO8UU8O89/h0Y03EUOgc+cbNMYSR2DECleOPQWJEe6Re6wJMusyMHslJ4BNRVKnJ3o0D557Yfy6KJv/bgJrEM2kgnUjCiCewYU0RzuvVG+1bt8GVl12O7Zs5ETaDtbCfLK93v/kx5G9TE6UPy4T5eXHIc+hy2OHo2LYdJo+faDVOLA25j+hWjwbmvbVj6zZce9XVaNeqNbp3OxsbOCEvu6ElkuqTr/LIOaT4Ekw1f1jncIpRtkJZaXMi3TW7seOltzH/2sfw1c/uwJzzB+Cr3v2xuPftKnDEqt88i81/GYs9nJ+puBTpWArRZAphw5yaO5pOY++ojzHvFw+g6PpnkJi/HkX/fhtre96hIv1h3V6Elm/EoisfxMb/exFbnxqLBRfdjU0DXkZqykJgxQ5gTwQojQOzvsbya5/A4t8Nxu5ERHUJLHpuHOZccDvm3/AEPr3hUXxx45PYcevLWHTR3Zh/4V1YOmQUUFyuXk6yTRF6bx6WXvMolg0iSJkBk8z+fNWtN/U329JZLHnzSLG7HQNB0Cs1a9YsBTP1BX4g9BCOOP7ptddew5VXXomzzz4bP/3pTzF48GAsW7ZMARKhiKDE8VQMTMFQ6Qw8ceedd6oxUn/5y18UWHE7YSp/XfvYpGdUezZJzElPaUt+4gbnfKlAQn0qrdlkKgGUqJlriD2xtHlDcFqZdDSN9M5SFD3+Olb2+DM2sD9qv4eQmL0CRpRer1IFUfSAJdl5iDcN55ZRz0RWpAlz9l/lDmPlavuwu2VtHyNF11nzfAh3pio1UwV9pL+aHz0je8NS6s3w0vEGfhhBrfZPbZPpclLgBOIN/jR8T/OsNacdtk9BfOA6w5i4Bzs3x1DLhv0zgdYs37qc67QupNXbG5LWdQ6Or9//w0B4FVUx3DPoIRzcqh1OPOUMvPP+DHMibOsetP+mojkVB4KzkHI+NjNADCslTqYONiqLJ6F0+rmoGnUwEsO/heSob6Fi9GHYPbk30ssGA+UrgEiZqoCT6SQSnBeO95lVmamKTf0o7z090TaA7e+jcuqZKJ1wBbBzphpHVc4mb+kn2DvjWux+90TEN70KxPaoMVKht89B5eTTgX3LkDLKVEnnvZ6afRNKJ/4Y8ZXPIJVCV4oyAAAgAElEQVReiVRqNcIr/4nK8ccj/ME1wI6PsG/i9xGZejVQvAhhVrDMY2gxKmdejm1v/twMXR/dAcSrAEY/Ipkq0syiBgrgoTkHKdrInJVZlT/+fjzNN8hW40e9zjOLor6PWCyjBOWdIxCacBTi7Eb638NgjL0cKNuj6g8+hisQVU+7A9541PZGoim/Mxhq2QTBRCymui2uW1uE887tjbatW+OKy3+ObVuLkeJk9PoNSlP+fsGcq/qtk8FZlo00nhs8GId3PBQdCFITJ1mNEwNqUmd9zxfM9dfyti6bazMYuS6hyt41V/dDuzZt0Z3zSK1dC4OT2HJC9pSh1jPPz2x+z+WxfPnHFyWqvrGiBpl/p4FN+1D8wiQsuvx+LPvJbVj149tU4IkvL7sX8657DLtfegeYvxHYuk9Nimt2iTP7ybEqY/hzjuvlxLrzrn4Yq/7wApIrtmLNK1PwdY+BKB32IbCpHKHZK7Hkfx7C+v7/QuW4z/HVpffimwdeU+HMk6GYCqmOjWXA+PlY9ouHVVTQxNa92Dx0Oub+39OYe+0jaj6p9a++i3m/flzNdzW/9wDMu+BO7Jz6FVKVUVWXU9+yd+Zi/rUPY8nDr6iufUpz1rNWPc/nnXp2scmZxZI3kJo8eTJ69OiBM844A5999lnGM8SHfG2L7oZH+IlEIgqUGDqWH3qNqqqqMjDG79577z3ccsstalJeeq70GCp6sLp3744vvvhCjZFiF798eKTS6s2fOZmgsisvmyts9SWiZmOFDRZOssnZnFkhpMKmN8nalTcFKzy+wE7sqsDKJ0dgYfeBWHn23Zjb7zEk565CKsne8REk0vRwxdVbdB5DJuF9xJtInYOiu7wpm3N/N1nR9WRDUr5M4/Xyuhv64f61fWo7XtmyDg6sjQ1da1jXuWsTjPsyQ7V96jpPbd/XdnxjvrMDelOvKzdYLWW41utJI1xZhQcHPYC2rVrjjFNPw8xpM6rBYD8teQpOPcsXGAwLwSlrY6hAFSLsiAdEd6Fs4RDsGH0sMLQ18FoLhEccgciMG4CNbwHRfeZLcdVmYeMvDBgRJFO8I2keTpMdUudMqSlT6fEhpu0Cdk9CaPpFKB19EbByBBAqBRiUZs+n2DPtRuyccgrC614BYuzu9w5CY89DaML5QIhedz42eKOnkZpzC8on9gIW/wvYswXY/AUi714LY3hv4MshwLaF2DP5VJR+dD2wdxkQ3w3s/RDG0oEoffMwlM66BNj7nvl2nw8O5Y6zylZtD2z5rk4Fcg5SzIkFHSlOuJxMKJCiF0p1deGDk/UOJ+PlGzrWNwl2L2XXv4mIjDsZVSMY8bUdku9cYI6do/35SZhjjff3/Ofibw4cTxic3DQNrq9dvw7de/VEi5aH4Mpf/gJbthWrqcu5jZ9c5Mnvv0GdhrzwPA7tdDjatG+H8ZMmIs6JuVXbu2G9PvyuQWPzH0slVDljmdyyvRhXXdMPB7duiW7n/ESVTX3eBMujeoWeez1V85p1t1nxKJ5i3caxk6GJc7Co771Yfc5AfPOTAfj6p3dj2dWPYfsLbwKrS5CsjIKTW3PC4WgkpiZrN9usVmMqkkI8kYIxcznm3fwcVjw5HLFvtmH9uA+wpN9jwJwiFTW05M3P1IS7K54ajvjqbVhy3RNY+MuHUPqvqdi9YDUqPlmO4ucmYvHPH8CXF92J2Rfcji9/fh++vOgufHndo9g++kOk2C1yXwxYUIzov2dg6dWPYsGFdyG2doeaGDhleVd3vfUZPr72fix46jWgmHUnvdJmO0E3YdSDmnV+FkveQIpd7Nilj94orrNyqc8jZQcse0WkAYvfEYjotVq8eDF+9KMfoVOnTgqgOA6LEfyOPvpoFf6cfz/xxBOZ7oT5ASmCDG8o0/eSoWJaN+M+tzaq76xGi62RZ75Q4KuAKGK7d2HZ069hTp9bsbDX7Zh7zcPAbMb4j5iT/KYIYuzqZTU2+cOq8PA/a4C73taQVBW6huzYuH0Img3/54IBG5cdFz9AXZ36uOVqu2Xj5rpmVw8eVsW14WhTfce7Qb9Prz9Np+OoqirH/fffjVatWuDUU7+PmTPfN/s51HIO+t0ITPwF1aLgiqJ2A7ytEC1B1bIh2Db2WCSHdkR07I8Q+/wuYNtUILRVHcg2KtudhG/6Dnnns8so7z1Wp/RjhhBR+GTVcXQ1AxVLEJn/FEom90Dp9AuRWDAQWPEM8NVAVE7sifIJxyO5+kUguhFY9Sr2TeyJivcuQTpaqeCNv6sU/noIdr55LiLTLgO+uhfxj/4XOyedgMSs3wJbJyFd8gEqxp2KOLcX/QuRlXdi32eXouSt01E65WIYq/8NJNYjgpgCSlqTPYTNZ4irghD4ne31Vy7mkVLFNs2nKc1lwpN6tuqXDzQmP5l6JqnG6fE+wdZ3ERt7BmIM/z/qW4hOOQ2IfmPuyyrFfCFd6zsifdrmS9Nqgk3CYCptYN2G9ejRqycOPuQQXPE/V2JrcbGtG7B5ic2XFz+f3ywTunv1kOefR8fDDkWrNm0wfuLEjMZml2o/X2cu8k6vTApbtxXj6n79cEirlvjx2d1QtH6d2X1d3WqW3tZtl8syqe5xXeVadQNf2WFnGEVPj8a83gPUJLzzLr4bi259EVUfLgW2lAJV5vQJrO7CVjfgDJTxSz4yDPOFI8dMxj9fjaqVW4DyGFKbdiP2wXJgV0gB25apczFrwBB8M/ED5T3aPfEzfPnHZ/HFVQ9i/s3PYf5vnsLcXz2IJb8fgnUvTMCSvwzHkj8Mweb7Xkdo1KfmmE7OIs/uWGVJYO1eLHpqKObd809U7S5T74zMF0IpbJr8MaZcfy8W/XOcOSaNL5T4nLOeW/amUTYVU95AKptM24+1A5YeR/XCCy+oCH4tW7ZUodLZrW/ChAmqCyDnnmJ3QoZE1wEn7Oewn5vrzTdGyrypaUi17GdR3lyqjWb1aWXZZ22V2Z878Au6o2IRGCU7sfypVzG3z62Yd25/fHXNQ8AnK4Ew+7KzSxKBy1brqVk12RKKAWneSlxv6C3NksjcNd+nru50tX9vNkrrGstk/17dRcobotwDVoO4Cdfr6H64f3fEzN/qrqaezfFh1ddc/1TzRUFAw96r0Ua1d5Fsmu8bXgboBw6Fy3Hf/XejZesWOPnU72P6zPetqQgOPE8SKdCvq245Fnl2MicR8aZkmtgHlLyNPZ9ci7KJFyE25zHTq8PJtWPsBseGnrkrDzXvNuuGV54C887jm0F9avaajdELzcl4dy/G7jn/i42TT8b28SeifPL5qJzQE+Wjz0D52B/BWP0yEClCauMwbH//SoS+vAlJo8Ls/pti+Io0jD3TUfr5H1Ay4TRUTPgh9kw8DXs+7gWUjAUiC5DcPgnxUacjNfp0RKf2xc63j0fx5KOxd9aFwOoJQNV21QSnLy6uPhwjZT41zAeY/N9QBXINUixpfLqw/GbqD67ox71VFJl/c19ifkwdg60zkBp9FowR5kTTsSknAPEV5rmsnqmap/Vpcpmy8a9/b/2GDejZq5cJUldeoUDKfPqZ16X3k/RAPTREUa8hzz+Hjod2ROs2rTFh4kQTvq0xrKLdgdrtr0nKSGHb9m0mSLVsiR9364a1RUUK6vW+Zs3sfC69f1Ol6qZmHcZenFb1xRd82BPF9len4stfPqC8RbP/PASVX6xEPMrngNVu5EPEavWZLwTNv/WDhact51d8IMTN1qHaxr/JPezSGE0CW0tRtaAIqe1lSLFi3BtG5YzFmHfrC5h9zYNY9JunseuZicCna9QEvdhRASwrAYrKVIRAs9lpepaS9J5XxBHbuAtVa4oRjsaRiqfMSjZhYOsH8zDznuexefocpPeFkFQ9u8wHHTXloh+D1p+NSnwPUvQm0SvFDysoBpW49tpr0aZNGxWMgmOpGDL9mmuuwXe+8x3lkWK0v/Hjx6v9OfYqXyCVqQGURVlK2dCMwWBXPITBobxVCCOkRkaw2RJR21WpVF0xrJYXh0FtCGPTA6Ox4id3YdXZd2N+v8eBz9YCUesmsMbZsu3HX2HVym5KZi95zmXDt+RsLDbkQ8c092+eD9/PHzjip77vOGalYf941frGaY5USevqxIThZvroN85N9RTe/zxulOSxrnRpxv05x21lAvff+whaH9IBp570Q8yc9nGd+WO2ORKE7xFVRaRrEXaT4iDbdBLJVKUZCXHPbiBsIKoCuRCZyoFUmZp0l/UJKy1+y0pHlRUNZHzXob5nNz9zjyT2IZauMKPuVX0NrJ0EzH4R0Q8fQfSze2EsfhCphX9R46GSRhKJyEakOLlu6WxEjTSq2LVPvXWsANJbkdz1MSrmD0H80weARS8BO79Q4x4SsX0Irx+H5MgzYLx2KBJjT0By6g0AvVCcIJzvajQ0WZUwa8pKBsMxr6RRlU9QD8oHSNFsVjvILOf8w2rgqA28P619zHJoepuw+RNgRC/gjQ4w3miL+KQeKqqlfhttzoDGVw3m+XOd8rWH/s2ijRvQ/dxeOKjlIbj8f67AZqtrn94uad020q+P2Gge/PxzaH9YR7Rs2xrjJk00u0dar5lEw7o11Nok0ils3bENv7qmH1q0aokzz+6GNeuKrL4H+vjqcquPy0XK5wA/rNPYFmRNo4JP0LuzcS82Dp+OFa9PwZ6Fa5CKMugZR5PzVae1WJnk44ItUjY9OXqf5+OizmU9SxRUWXV+qQqtxh4crHzTpocrnDIzEaYrKwkjkkBlRQjhyrBaB71OUcPqbmyoLntRRtrm+Ej2RjasfKmpONLYx54dBDPruUZHCSoJbiEFW4iz3VrdtU9l2Goe85BsFt+DFCslDVFMd+/ejYceekh5nQhTHBPVuXNn9Tc9UYzw99RTTyngsgNYXSI2p0dKNaRY6FStZJU49aU9N9yB5idIRNXoDBZvVVp4HEt4VVq5X9c/8l8s6/EnrOr+e8yjR+rzjarlph0wdEKxIcejzfJk3szq18yfMe8InZX6UpVvqzHos/X6LquQtvGZp9tKklZrwVumPBLB3fffjxat2+D7p56K92fNqlMrNi74ckPdbBSVJ2BXhhTfU8TV7E9VaQaISSGZTKkHvAke7OYRRzLFibdZ7fDus3Wj1YVNBXMxIc38ij/C36xAEiEk2IeOnq3KfcDeYjOSXtVSILUACM+DkdqrHgGqQjP2AoltavwVkYwjSJAMI5kuRSJVAqNqI1C6EqjYAETL1XuWZHwvwitHoorz1U2/HFg3HCguAsp3ALHdisboaFWPJl47P8o7bl2P/XEl644K5BqkaDqWXn5oMZrPLGE1s6qrAD4rzBduDHYyFfFxP0R0VAtUjjoYpe+cjVRqnVmHZMoAAzpYralcp2w4Wb+5ed0G9OnRC61bHIJf/PwK7NhSbPU4yFPecq1FNr9HHZWWaTBqX6cOHdG+VWszah+7MWe2i5a6vNWZJlMoKd6G667qhzYHt8Q5Z3Uzo/ap7uBav+pyW+d5srFnHcfya977upmZ+Zs3fWUCKAmZXfAq9Bgo5tPKqxVbSD8fbO8A1SXw+aEWntTqgaEqVRWUJq2eP+rHrUZoKplGmK/jdTs2nEI4baiP8lRF00ikDETYPSNuDvNkTVoOBsthUDZDdTPU+qk6l9yV4ihmPuuYiRRQye4dSTWeki8+a2SW77CtdpLOfmNS34MUPUoapLiu55CiB+rMM8/ESSedpD6nnHIKevfujb/97W8qDLo+jtSaX4+Urr5oTquA69LNEq9bwMrgaesNgdlAMt8Dsn9FCti+F6sf+w8Wn/s7fN3zRsy77gHg8w3qVbIdpHThJ7zpX9YFMTCpJTOv3+nj9qaym47mk49dg4Z1AjRHDTXfvvSjVkRCuPuBe9GiTUt8/9STMHXWdOuN4YG/q0Lmq0iRvAlZm5hPXyb0HHOaAr7iiBicviKOeNoMD84XFzEV4Y/v9TjtgBUsRhcKVT+xWcvutUklFOsUliGWS/N3okglKxkoUIFbIk5/LSuQCKpQhhR2gmNZ+EKRb/0q03wrVwEkq9ReBse5RBkTgMDHEU4EK7qqGDbafIOYSmxFeMm/UTXqe0gsuNOcdJevFlU/wzKz5a0GRCXV5asMqmcTW9Iqp25vk0Dvn2uQooVYyghH/Og6QMMSTWnVPsourBlYghPcc8dbSEw4FZFRB6F8dAvsfffHSBir1Ws95UnnmXlv8AT5+GiQSgFb1m3AeT16oU2LQ/DLy69ACUFKb89H3vzym+p5VA1Lfx38HDq374gOLVvjLR3+XECqYeWbWiZS2Ll1G66/qh/aHtwS3c/qho1rimqWxXyVS/24Zqo/vHX1Q0BRkvWCnhUYez4p25v7s0jzWcLd1MIvLMDiauYZYH2n/9bPHoPnopeJjikFRRbwKO+T+R1hSYFUVQqxhNk/gz+YTvK5xD4eJpSZsASkdUAlS1NzH76GtOrrmKHqZUIbvWuZ6+b1m1V59fVYl+U28T1I2T1SOpw5UwLSxo0bMX/+fBUVcOnSpSp0OrsC6o/2SDGta2l+j5RpTTbWWJY1N3GdW1RjSuF49QttbmCOOe+HKtB8YV0SwrLHRmJ+zzuwvPtAzLvuIWDOShWaWc0npN5Oc3wDZ6mKAmkWQ2vQFX9M/Z6bJiy9ZM3zMbVoWCfDhnREtO+jGsXqUcDHQTN82OBUje6aIdrr/K458qDPybyoNzDNFKae4/Ma/DFBwRNkSY6oqMLD9wxC+4Nb4QcnnoyPps6wE9+B67zRrNslqUZM8U+W/70AdgOppPnKX93EhuIiAg4BiqEqDAuU1PWrxw3LHkcvlSKu5o3j3c6RWNXPgIwLIR5SABcGO/tVqi6/0XRCjYFS81BF0uq3zYS5qgCinAcqpd6xJDk1FYtlmu/oykw+M8cOo4JolfgaVQseQ3z0ETAW3Y0492P9qboYl6sixC5ccexGJSKKrxQ/qdDSdT87zaeK/L+/ArkGKVWR6JaMrRzrspaxIIsgv0yzRLLTTrmaYBojzwL+eyiM1zoixq59sVVqHxVSneez6iOeJ9efhnbty3W+/PJ7NLdZDsyRxA3p2ueXa8tHPqmlvWvfwa1a4qx6uvblOo/qWcAfzdjdrG/4eOBcUkzJIwqgoikVIEPfY5mDWHVxR6bW80Sd1zxt5hnA7zTskMdY2/HdHA8jLFWqfhq2neL8zpxdlfNRqYOt9zSlhCvmWz3HqvfjC0Ez0+bu6m1mwtxepuLrEtr4twlWqobl9emP1UGEl5HN4nuQ4sVrj5KuoHRKrxOj+DFcOsHKHp3Pfkx9AjYrSGV+2BwSq21rT02LW29+WZBsG1mmVAFgCNptZVj10BtY0vN2LO0+AHOvexj4aq0ZNp2FkpOyqlhh9GaxYW2ejKervglsJ7f/UI7XtRrNlTZ/de9GR9qhGT/K9rR/c3xYLhv62e9NkBuJmnpfI41IqAoP3DcIbVq2wqknnYxZ02fUuLfqLPLqdmHVwt35P6sKepQUeVjnsK5V2dUcfaA22K/D2sZagOjDEsC7ucYuupVjUpDayiYuu+uZdzOLDud5Mx8E5u7MFcOpsQYyg1yoCognVmRGqDPHTrFrOj0PCC9F2Zx7UDbuRCRXPG29IGGO+QqCY0i5zjxGlSfCajubzxBulMWVArp+4kG5itpX4xFjmaxGWdNXoLaxfIXUGFoUv4f0uDORfKM94sNao2riaUBkjemZ1Y2omtVSjTJs/43mWK8r2MTPrWATvE+a43cL7Zzm88R8NcpgEx0O7YhWEmyiUWWHUfuKdbAJK2rf2nUeCTbB+5yFd797lvUP6w+marPVJLGX88xB1rbMztb5zLOax+uvdBXGv/m40I8Mvc7t6jzWjxOy+OFPqP+sDLGtq87Jv1Pm2CieQ31p7ZM5lzVMKnMe5WDjMazR9lusjOr87re1wX8WBEg1+GobsWNuQMo5Y6wO2KxRpYuNF1vEJBXnuHgf1jzAMVIDsLRHf8y57hFg3npwgJ0qbFaDRxdkXaJ4RllEgSApwIYs553jpOCM4nnyySdjxowZBSmBrsDMapKd09mhwnyJV6UqIEY9mo/yzwag7M0fIf3NSwWpg5cuKi8g5UoA+iUiJtZvm4bExB8hOrwdoiMORuWkE4DwWrORQ4a3vFGuTt+EO+sXojzlhg0b0KtXLxzC8OdXXIHi4uLMS9Ym/MmCPJUuk0yfe+45Naa8devWmMiofRwGYH0K8uKb+KL4wp5Bz/r164eWLVuiW7duKCoqqlEWqacshaOAgJSDLf0KUnOvfwSYLyDlYF7ZHEAFWIkFBaTISubbPI1PhCmzAcwZEZDk3B6zUfnRHxCe9ANg3b8CWCJye8n2RmnOPFKuLtEGUtunIznpTAVSkeEWSCmPlPkKW0DKlbCe3VmXSaYCUtmZSUAqO/38eLSAlIPV/A1SG8xAFGxDiUfKwdKyOSgKBA2k2PnQ7NJAfzS7Idq6RCT2Ajs/QOm0/0PszbOBTa8HpRjk7Tp1o5UZ8DJIqTKzY6YNpFqgctL3rK59ZucIAam8FaMm/WFdJgWkspdVQCp7Df12BgEpB4v5F6QeBebbQEpFGzODU6jufFZnUbXuoIFsFgUKSYGggRR9UKo/ueoaHLfGy1l90BN7gJIPsWfanxGafCGwcVQhmdqT16Ibrcycd0EqasL3jplIvXmW5ZE6CJWTjheQ8mSpyi5TukwKSGWnI48WkMpeQ7+dQUDKwWJ+Bakvr38UWLCx2iNlTVgsY6QcDC6bC16BoIFUtUeKr03MIBSKqehOSJYBe75CyUePYPO4XyG8akzB2z/fF6gbrcyHd0EqZoHULAuk2iMynB4pAal8l5/m+H1dJgWksldXQCp7Df12BgEpB4v5A6QMYMserB70qhVsYgDmEqQWbbaCTZhRxPiQFJByMLhsLngFeB8EZYwUe/HR+czUDFRjxntV8WoYKCBeCUQ2IbHpfez8YjDi2z4vePvn+wJ1o5X58C5IcZoMADs+gDH5bESHt0d0RAtUTPwuEP7GDDZhmHOu5bNXA7XUiwSb0Eq4T3WZZCpjpNzrZz9CQMquRjDWBaQc7OwvkHoFy1XUPgEpB7PK5gArwMZCUECq2sx8mWJNo2BFWmN42CTDpKfKgPhmoHwREN9efYisNYsCutHKk3sTpBgMW03drEAqbYFUZEQLlE84zgIpFiIzcD/3ztdCLfUiIKWVcJ/qMslUQMq9fvYjBKTsagRjXUDKwc4CUg4CyWZRwGcKsLEQHJBiQ5NeqGqIsr5R0fxinGPDYFy/MGCUAQanTJSlORXQjVb+hndBijOWmR6p9OSfKI9UZPhBKJ9wLBBebc4hpkCKk3JUw0xz6lbbuamlXgSktBLuU10mmQpIudfPfoSAlF2NYKwLSDnYWUDKQSDZLAr4TAE2FoIFUtUQxTYvm57sjhVPp5FIG2p6XyPN+eYSSHPyX1maVQHdaOWPeBWkjLTlkSr5EOm3foLIMHOMVNl4gtQqM2CJ5ZEyp7xtVsnqPDm11IuAlFbCfarLJFMBKff62Y8QkLKrEYx1ASkHOwtIOQgkm0UBnynAxkJwQMpmHLY5rXanmuA7nUAqnQAhipW/kUojzeiesjSrArrRyh/xLkhZHqmSDwELpMLDDoICqSqClJHp2icg1azFJScn12VSQCp7uQWkstfQb2cQkHKwmGdBil1ydFhjzqy5mcEmXqkZbGKxBJtwMK9sDqACQQMpzU8KkfQfRgppg/H8OK8UI/kZSFs9AANYJHJ6ybrRyh/1IkilYSjAVjNklHwE4+3uyiOlQGrcsUDVSpiFhRP3smNf/uCbWupFPFJaCfepLpNMxSPlXj/7EQJSdjWCsS4g5WBnL4EUh/ZygC+st8asQthFx0gmgQ27sPre/2BJj/5Y2r0/vvz1Y8DiTUAiCVXZqAYUoyxZL6WtlepqyEEI2SwKFIgCvB8C6ZE6wH7qoaCfCAdslS+aRwHdaOXZvQhSrGeSfE3HyqXkU0TfOR/RkR0QY/jzMcebQUnScbPuySNEUT9Vt1lmEpBqfHnVZZKpgFTjdeSRAlLZ6efHowWkHKzmZZBi1lnXpQhS63dh9T02kLqBILX5AJDi/gqeOBTCGi/hIIFsFgUKSgE2FgSkCsqkvroY3Whlpr0KUgmCFF+2lcxG+N2fITqqvQKp0JjvAaULAMMcQ8Vryedi/30BqcZbQpdJpgJSjdeRRwpIZaefH48WkHKwmj9AKmV6pO55GUt6DjA9UgSpJQJSDuaVzQFUgI0FAakAGt4jl6wbrcyOp0FKeaQskBrZHrFhLSAg5ZFC1MTZ0GVSQCp7YQWkstfQb2cQkHKwmJ9AatUBILUFSHDgg+V6SrNHu3ikHEwumwtcAQGpAjewxy9PN1qZTT+AVOTdC0yP1LCDUDn6eNMjlTI9UoZ4pDxe2hqWPV0mBaQapld9ewlI1adOYW4TkHKwq9dBisN9eeNiw26sutv0SC3rMQBf/e/jwFILpHiNajiEgJSDuWVzABQQkAqAkT18ibrRyiz6AqTe2w+k9s0HUlEV7EhAysMFzUXWdJkUkHIhWh27CkjVIUwBfy0g5WBc/4DULqy8+9+qa18GpJZtNT1SvEYBKQdLy+agKCAgFRRLe/M6daOVufMqSMUzwSZmI+IAUryefC3235YxUo23gi6TTGWMVON15JECUtnp58ejBaQcrOZ1kDKDTaSAdTvx9Z3/wuIe/VUI9Hn/3xPAUgEpB/PK5gAqwMaCjJEKoOE9csm60crseBek4mawiZ2zEX3/QkTVGCl27fsesOcrFWyC02/kD6FMY1JLvQhIaSXcp7pMMhWQcq+f/QgBKbsawVgXkHKws79A6p/VIPWbJ4EaHimOk5KufQ7mls0BUICNBQGpABjao5eoG63MnqdBim/pdn6G2NSL9gOpLzNd+6oxJj9iU0u9CEhpJdynukwyFZByr5/9CGoBV0sAACAASURBVAEpuxrBWBeQcrCzX0FqvgKp4upgE5x7SkDKwdqyOQgKsLEgIBUES3vzGnWjlbnzPEjt+vxAkNptglQ8nc+peE3bUku9CEhpJdynukwyFZByr5/9CAEpuxrBWBeQcrCzb0Hqt08By02QUpWNgJSDpWVzUBTg/SAgFRRre+86daOVOfM8SO3+HPFpF9s8UscDAlLeK1RZ5kiXSaYCUtmJKSCVnX5+PFpAysFqfgWpBXaQIkQZBmBI1z4Hc8vmACggIBUAI3v4EnWjlVn0Pkh9gcS0SxAd1QHRoQehYhRBai6QjEI8Uh4uZC6zpsukgJRL4WrZXUCqFlEK/CsBKQcD20Hq8MMPx0svvYSVK1di48aNOf1s2LgB6zZtwNb1G7Bl/QZssH5/PdN1G1AyezHm3zQES3r0x9Ie/fHZtQ+hbNZCbCpaj/UbNmDDuvXYuIHn2KiO3bZuIzZt2IgN1t+5vh75vdyWH9G7Wm92AVq1ahVuvvlmtGrVCieffDKmT5/u8CSQzaJA0yigG608m1dBKoEk1KSDu79AfPqliI46VIFU5ahjgF2fA8kIEtb0hPkMOUEt9SJd+7QS7lNdJgWk3Gu3/xECUvsrUvh/C0jVY2M+VDRIHXXUUarRdeaZZ+Kiiy5C3759c/q5pG9fXHxpX1x2SV9c2rcvLrysL/jdJX0vxS8uuxI3n3sFxpz3eyzrNRALz7kVk372J9zR+39w+aWX4ZJL++Liiy/GpZdeiosu7av+vvIiM/88J7fn+nrk90TzfJYB3g8nnHACWrZsiZNOOgnvvvtuPU8C2SQKNJ0CutHKM3oRpIgmnJ8QnJ9wz+eIz/wFwiO6ID7sIIRHdwF2zAQSYXZwgAGOk6qGmaZTqWFnopZ6EZDSSrhPdZlkKl373OtnP0JAyq5GMNYFpBzsTJD6z3/+gyOPPBKHHHIIWrdujbZt26Jdu3Y5/bRt1w6t27dDh7bt0L5tO7Tq0A78rl279ujU/jD0bHcMXv3xdaZHqtdAjOz5W/y07TE4/NDD0L5DB3Ts2BEdOnRAG+u4w1qb+W/Tvh3a8pPj68m1fvJ7uS2vXte7ffv24KdNmzY49thjMWbMGHNia4fngWwWBbJVQDdaeR7vgpSaEKcapEbaQGq7HaSIUgzvl59FQKppdNdlUkAqez0FpLLX0G9nEJCqx2KGYaiK7pVXXsExxxyjGl2nnXYaevXqhT59+uT007tPH/Q6rw/OP7cP+vTug57n9wG/63Pe+fjZuefj9+f0xeg+v8PyXrdjUffblEfqlrMvwU/7nIc+552n8nr++efj3PPPw7l9+uCCXmb+eU7+rc6V42vKtYbye7kts17Vu3fv3ujZsyeOO+44dU9///vfx5QpUwSk6nkWyqamU0A3WnlGT4MUx9Xu/QKJWb9E2AKpqtGdge0zMh6plPJdCUg1XenIz5l0mRSQyl5/AansNfTbGQSk6rEYHyqs6AhS9Eh17doVL7/8MtavX4+dO3fm9FOyayd27NqJ3SU7sWvnTmzbvRP8rmTnLpRs2Y6KOauw/Na/Yfm5t2PBT/6Mr258EuUfLkbJtu3YXrJD5XXXrl3YYR1Xut3MP8/J8+T6euT3RPN8lYGSkhJs2rQJt99+u/Iuc4zU1KlTwRcnsogCza2AbrTyd7wNUgD2zkVy1q8QHtkVsWHfQtXoTiZIxauQMtgFkJ0A83ffUEu9SNc+rYT7VJdJptK1z71+9iMEpOxqBGNdQKoeO/Ohwq59r7/+Oo4++mgFUiNGjEBZWRmSyWROP4lUEnEjiXQiiVQyiZiRBL9LJJNIRRLAyu1YesuLWHj2n7G010B89dsngSWbEQtHEIlFEY/HkUgkEOMxqSQQN/PPc/LvJD85vib5PdE8H2WA9wEbsIMGDVJjpE4//XRMmzZNPFL1PAtlU9MpoButPKOnQYqMsu9LpD64uiZIbZsOCEg1XYHwwJl0mRSQyt4YAlLZa+i3MwhIOViMIKU9Ut/+9rcxevRoVfnZHzy5WGdPdDUA2JoPKqneA5rDfNOxFPD1dnzd/+9qjNSSXgOw4HfPAEu3IBVPIGUYCpKYT/P9IQcSp2H/Ww0Z5gSL8hENCrwM0PMUCoVw3333qQAyp5xyiorax7IviyjQ3AroZyx/x9MgRUdTbSBVPA2IhyyPlFkTNbdmdZ3ffs+KR6oulZy/12WSqXiknPWqbw8BqfrUKcxtAlIOdtVR+3TXPg5K53e5XtjEUx0orLZeEmbQWf6pQGp1CVbc9hKWdO+PxT36Y+HvnwFWbFMgZaTTmW5LKes4cMU6pzQfc21N+b18KsDGgkzIm08LBPu3daOVKngVpJK6wtn3FZKzrkZk5BGIs2vfmE7A1veARCWSnJoQBCmrMsmDWamlXgSktBLuU10mmQpIudfPfoSAlF2NYKwLSDnY2e8gZSSS0CDFh6SAlIPBZXPBK8D7QECq4M3s2QvUjVZm0A8gxa59dYNUAmnOOZWnhVrqRUBKK+E+1WWSqYCUe/3sRwhI2dUIxrqAlIOd/QpSi37/rOrup0CK3QANw+rKZ02fKB4pB8vL5kJVgI0FAalCta73r0s3WplT74PUPKQ+6FcPSMUFpLxf5BxzqMukgJSjVI47CEg5SlRwOwhIOZjU9yCVTKlJEwWkHAwtmwOjgIBUYEztyQvVjVZmzqsglWA/cn5Kq0FKRe07oGufgJQnC5nLTOkyKSDlUrhadheQqkWUAv9KQMrBwH4FqcV/GAys3IG0AimIR8rBzrI5OAoISAXH1l68Ut1oZd68CFLkp2qQmo/UB9coj5SAlBdLU9PkSZdJAans9RSQyl5Dv51BQMrBYp4EKQbd00EjmP+4AazaoeaRWtqjv4rct+hPQ4BV2wENUuxLbpgzfqigFdZ1s4d5dS9zBzFksyhQAAoISBWAEX18CbrRykvwIkixPkjxP0aILV2IxIe/QXjUkYgNOwjh0V2AzW8C8TK1TwpJGBJswsel0cy6LpMCUtmbUkAqew39dgYBKQeLeQ6kSEEHgFRazSO17M9/xdKeA0CYWnDTEGD1diDBrn1WxD+GWWIlCVQPD04LSDkUAdlcYAoISBWYQX12ObrRymx7E6Q4GUYSSCeA8sWIffhHVI05GrHhByM88ghgw2ggvkeBFENNcGqOfC3UUi8SbEIr4T7VZZKpBJtwr5/9CAEpuxrBWBeQcrCzX0Fq4c3PZUAqM/e8imkrIOVgctlc4AqwsSDBJgrcyB6+PN1oZRa9DVJJBVLxj/5UE6Q2jhKQ8nD5akzWdJkUkGqMejWPEZCqqUcQ/hKQcrCyr0Hqmx3KIyUg5WBk2RwoBQSkAmVuz12sbrQyY14FKTU/VJogtQQEqcrRRyE6/GA1VgobRgLx3ZZHyhCPlOdKmPsM6TIpIOVeu/2PEJDaX5HC/1tAysHGvgWpW54DBKQcrCubg6iAgFQQre6da9aNVubIqyDFsU/pdAooX2oDqRY1QIpDqBJg13H7qNvc6kwt9SJd+7QS7lNdJplK1z73+tmPEJCyqxGMdQEpBzv7HqTiKYhHysHIsjlQCrCxIF37AmVyT12sbrQyU94FqVQ1SH18EyrH0CNlA6nYbpBhkgJSnipbjc2MLpMCUo1VsPo4AalqLYKyJiDlYGlfgFTMAL7ehqW3vGgGm+g5AIv+/LzpkYqnkExb3S9UKCYZI+Vgctlc4AoISBW4gT1+ebrRymx6EaQYPEIBUtoAKpYh8ekt1SA1qivS64YD8V0KpBixz4wFmx/RqaVexCOllXCf6jLJVDxS7vWzHyEgZVcjGOsCUg529gVIRVPAim1YcvMLCqSW9RyIxX9+QUDKwbayOZgKsLEgHqlg2t4LV60brcyLV0EqwaDmCqSWIzn7VlSOOdr0SI3qCmPtUAVSDNZH5EpL+HMvFKus8qDLpIBUVjKqgwWkstfQb2cQkHKwmO9AqscAVINUiQo2IR4pByPL5kApICAVKHN77mJ1o5UZ8yZIAXHiEb09FbWA1JrXgdhONW+GCkohIOW5MuY2Q7pMCki5Ve7A/QWkDtSk0L8RkHKwsH9AqhiLb3peTca7rOcALL71RWANQcqo2bXPmoMqqa9b5pHSSkgaEAUEpAJiaI9epm60MnteBin6mlBpB6mDEBnZBYYCqRI1OaEBziTFmQnzs1BLvUjXPq2E+1SXSabStc+9fvYjBKTsagRjXUDKwc6+AanlxVj0p+ewuPttWNpjAJbUBlKcR0pAysHisrnQFWBjQbr2FbqVvXt9utHKHPoNpMIapKIapOi7yryWy7no1FIvAlJaCfepLpNMBaTc62c/QkDKrkYw1gWkHOzsF5BKL99qgtQ59YGUAY4Q5vvDTNUnHimHEiCbC00BNhYEpArNqv65Ht1oZY79CFKpb14DojuURyqNmL02ybkRqKVeBKS0Eu5TXSaZCki5189+hICUXY1grAtIOdjZqyCVmbmD9UjUAJZtxaI/DsHS7v1Nj9RtfwXW7rRNyEtXlFnpZECKfwpIOZQA2VxoCrCxICBVaFb1z/XoRitz7E2Qoo/JAPOJypWIfnE7qkYdg+jQFoiM6YL0in8DkW0qap8ZbCJTG+XcCCqP1q8KSDVefl0mmQpINV5HHikglZ1+fjxaQMrBal4CKYVBrLPS6mWgmXMbSC3+QzVILe3/N6BoJ2CfR8rqyi4g5WB02VzQCrCxICBV0Cb29MXpRisz6UWQSqtRT4ZZyYRWIzznToRHHofY0BYIj+sCLPsHEC5W0/BK+HNPF7UGZ06XSQGpBktW544CUnVKU7AbBKQcTCsg5SCQbBYFfKaAgJTPDFZg2dWNVl6WH0AqYgepsQJSBVYc1eXoMikglb11BaSy19BvZxCQcrCYb0FqAD1Su2xd++hzNi9WPFIORpfNBa2AgFRBm9fzF6cbrcyo90HqG0Tm3oXIKMsjNbYzsOzv4pHyfClzl0FdJgWk3OlW294CUrWpUtjfCUg52Nf/IGXrfCEg5WBt2RwEBQSkgmBl716jbrQyh54GKXYbr9Ig9V3Vta9qTGeklxKktqohtyk1Ia+MkfJuaWtYznSZFJBqmF717SUgVZ86hblNQMrBrn4CqUX2MVIZj5QNpBj+3HJMqah9/FOCTTiUANlcaAoISBWaRf11PbrRylz7FqSqqkGKNUy+FmqpFwk2oZVwn+oyyVSCTbjXz36EgJRdjWCsC0g52NkfIJWCsWQzFvzuWSzr3h+ckHfZwJeAdbuAeBIppNXAYIna52Bs2RwIBdhYkGATgTC1Jy9SN1qZOa+CFGsNVWmEViMx/15UjTzW8kh1grHkJbNrnwp6lKld8qI1tdSLgJRWwn2qyyRTASn3+tmPEJCyqxGMdQEpBzv7BqQWb7KB1EAsF5BysKxsDqoCbCwISAXV+vm/bt1oZU68CFIG0khwpkH22AutRnL+fRmQCo3uhNTivwlI5b8YNWkOdJkUkMpeVgGp7DX02xkEpBws5l+Q+juwbvd+4c+la5+DuWVzABQQkAqAkT18ibrRyix6EaQY/tzukUouuA9hyyOVAamIhD/3cBFznTVdJgWkXEt3wAECUgdIUvBfCEg5mNi3IHW7BVKJlHTtc7CxbA6WAgJSwbK3165WN1qZL/+A1HGIDz0YodGHI7noryrYBF/L2Ubg5kVmaqkX6dqnlXCf6jLJVLr2udfPfoSAlF2NYKwLSDnY2a8gteL2fwDrd+8X/lw8Ug7mls0BUICNBenaFwBDe/QSdaOV2fMHSA1CeNRxiA8zQSqx8EUFUuz5J1H7PFrIXGZLl0kBKZfC1bK7gFQtohT4VwJSDgb2CkgxmwqDWHupQb5WxvllNAXDGiO1tIcZbCIDUknbO8OUgJSDuWVzABQQkAqAkT18ibrRyix6G6TSQOgbJBc+YAOpTkgseB6o2qLqo1Q6qUMZ5UVxaqkX8UhpJdynukwyFY+Ue/3sRwhI2dUIxnpOQIo3JwsX02QyqVLDMFRqv4H5XV3L/vtx3/3Pwd/Q3+uUv2f/vq7z1/W9l0Aqk0fWHVb9oZJoCli4CfP/31+wuNcALD+nP1be+S/TI6VACkilDYDhz61w5ypgrXUe61SZ08uKKFDICvBZIh6pQrawt69N12XMpTdBii/fYmqkFCLrEF/8F1SOOQ6x4S1QNaozEvMfB6rWwUibc7zXXWs3vx2opV4EpLQS7lNdJpkKSLnXz36EgJRdjWCsNztI8cYk1CQSCQVRLGR2sNHr3I/rTPdf+F04HEZ5eblK4/G42k8fq4/jfvbz8DftQFXbuff/rf3/9hpIZdSxai+VEKQW1AJSG3YDlkcqA1KGyWACUvtbWv4OigJ8DghIBcXa3rtOXU8xZ94EKY6rjcJg5L7IBsQWD0bFmOMQHd4C4VGdkZz/KFBVBL6bYz0iIOW9MuY2R7pMMhWQcqtezf3ZHt22bRv69euHli1bolu3bigqKqrRtqXOshSOAs0OUhpkCDUEIA09/J7eIjvs8LvaChj3++KLL/DCCy/gs88+QzQarQFjGtL0+XkeglckElENJh7PY2o7t5Mp/QpSq+iRUiBlBptI0ttHj5SAlJPJZXuBK8DngIBUgRvZw5fH8qfrIu+CVEwFkhCQ8nBBasKs6TLJVEAqO2EFpLLTz49HNztI8cYk2LBw6ZTAQ7DZt28ftm/frtZjsZiCKl3B2MXkvpdccgm+853v4Gc/+xlKS0sVhGnwIjRt2bIFGzduVA0kws/s2bPx1ltvYd26dRl4q+3c9t+pbd23IHXXv4GNe4CkgFRtdpXvgqsAnwMCUsG1f76vnOVP10XeBCl27YtbILURsUVDxCOV70LTzL+vyyRTAansxBaQyk4/Px6dE5DizcnCRc8RK45Fixbh2WefxY033ojf/OY3+Pvf/46tW7dmgGd/IQlKZ5xxBjp06IAzzzxTuU1DoRD44Xk/+OADXHfddcqVOmfOHBQXF6N379447bTTMHjwYAVwOg/7n9vpb7+C1Oq79weplHiknIwt2wOhAJ8FAlKBMLUnL5Lljx8u3gYpA4hokPqurWvfI0DVWvASUirURP66KWkdqaWMkWp8cddlkqmAVON15JECUtnp58ejcwJS7FpH7xEbL2vWrFFepa5duyowatWqFY477jg88sgjyjPF/bjwhiZA0Wu1efNmtQ/3PfXUU5Wn6dVXX8X8+fNV9717770X7dq1U+cbMWIE5s6di7Zt2+LQQw/FoEGDanQfdGskX4HUjdXBJkyQ2qs8UoyrlDQEpNzaXvYvTAX4bBGQKkzb+uGqdKOVefUuSCVgsB94ZCPii59DxZjjbSD1MFC1xgIp7iUg5YdyV18edZlkKiBVn1LO2wSknDUqtD2aHaR0dz6mq1evxuWXX4727dsr8Pne976nuusRejggb+3atRmYovdq5syZuOCCC9CpUyc1aO+QQw5RaceOHXHYYYfhrLPOUt6nm266CW3atFEeKHbn44fQxeMeffTRjEdKQ5obI3odpFQVFjOA+Rvw1W+fykTtW3PPf2xd+6wgfzJGyo3pZd8CVUBAqkAN65PL0o1WZtebIJW25ocCEN6E1LIXUT76u4gOM4NNROc+YIIUgKTCLQEpnxS9OrOpy6SAVJ0SNXiDgFSDpSqYHZsdpHhjsmARYl5//XUFToQcRjSZPHky/vjHPyrP0YknnqjAid316MHimKlnnnkGJ5xwgvI0Eb4OP/xwBUf0ZhHC2DVw165duOWWWxRgffvb38bFF1+MHj16oEWLFmr/Bx98MNNlkHlxu/gWpO6tDaTMsOlUQaL2uS0Jsn+hKMDngHikCsWa/rsOlj9dF3kXpNhpT4PUX02PVAak7geqvlHbk0iZnqs8mUHryJ+Xrn2NN4Iuk0zFI9V4HXmkgFR2+vnx6GYHKe2RYuF6/PHHQW8Su9xNmjQJO3fuVGOlCEbHH388Jk6cqEKc8xh6pBYuXKjGUF111VXg5xe/+AWuv/560AM1dOhQrFy5EgSdgQMHKnA6+OCDlSeKIScPOugg9Tvs9kcw0w8Kt0byL0i9YvNIpc1KkfQk80i5LQKyf4EpwGeBgFSBGdVHl2Ovi7wPUpuRWva3DEhVjeyEyJxBNpAyfVL5kp9a6kVASivhPtVlkqmAlHv97EcISNnVCMZ6s4OUlpFw9Nhjj2VAit3vOP6JwSDoSaJHih4qzhXFfQk//DBiX0lJCcaPH48hQ4bgT3/6k/Jm0QvF8VCsiDgOit0D6YWi5+r0009XIEVou+OOOwLqkRKQ0mVPUlHArgAbCwJSdkVkPZcK6EYrf9OrIEVPk+mRMkGqcsz3VNe+0MjDEZlzH1C12vJICUjlsuw012/pMikglb3CAlLZa+i3MzQ7SPHGJBjxM3z4cAU5vXr1wueff64A6eGHHwY9Ugwi8dFHH6lIfNyXhZFeKYZH5zgnRuA76qij0KVLF+Vp4jGM5EfA4nZCE8dQcQzW6NGj1Tq/GzBgQCBBau29AlJ+uxklv7lRgM8kAancaC2/cqACutHKLb4BqbEWSI04DOEv7gWqVglIHWha336jyyRT8UhlZ0YBqez08+PROQEp3pyEInqWxo0bh/fffx979uxRkPS73/1OgRGhiGHR6YGiJ4owxfmmpkyZosZJ0dPUuXNn1QWQHiwGl2DAiXvuuQfPP/88jjzySAVPHFf1ySefoHXr1mr77bffXvggFU0B8zbgq988iUW9BmDZOf2x5r5XgE3VUftULETp2ufHe1Ty3MQK8HkkINXEosrpGqyAbrTyAG+CFOeRYnd4jpHagtTyv6Ni7AmIDGuB0IhDEf78HiC0SnUTN2cprO5e12ARmmhHaqkX6dqnlXCf6jLJVEDKvX72IwSk7GoEYz0nIKXHKDElHLGgMf36669xzjnnKChiysAR/J4QxX3LyspUWHR6mghN7M43depU3HfffQqqONaK81HRA3XSSSep83C8FLsIErzovXryyScLA6RYX1jjm1TR1PUH03AKmLsB8/73CROkegzAN/e/CmzZB4NaM/w5D7JAilAlwSaCcYPLVR6oABsLAlIH6iLf5EYB3Wjlr3kRpMzaIQojZQDRYqRWvYzSsd9HZHgLREYeivCntwOVX4PR0VmX6KooN+rV/BVqqRcBKa2E+1SXSaYCUu71sx8hIGVXIxjrOQEp7V3ivFDr16/H008/jSuuuEJBFGGIUfyOPfZY3HnnnXjvvfewY8cO5cEqLS3FbbfdpsY+sSsfvU933323Gk/FbnvHHHOMmkuKc1NdeOGF6u+77rpLBaLgvFLf/e53VQAL/j4fECzgbhfPBJtgfdEokDIQV2FqBaTc2l72L0wF+CwQkCpM2/rhqnSjlXn1JkgRj/hCM10NUuPsIDVQQMoPBc1FHnWZZCog5UK4WnYVkKpFlAL/qtlBSnuXmPKN0a9//WvlKWLXO0bXI0Sxm16HDh2U14nhzvv3749t27YpjxShi9CktxOoCEmcxJdQxeAUu3fvxuzZs5WnigEohg0bpgJYMBT6ihUrMl0FmQe3i69A6oZqj9SaB/5reaQEpNzaXPYvbAUEpArbvl6/Ot1oZT69DFJpVpfRbUit+g/Kxp2oPFLhkR0R/nQgUKE9UmmZkNfrBa4B+dNlUkCqAWI57CIg5SBQAW5udpDijcmCxTFSDG/O+Z8IUAxVzi57BClG7KN3SX//wx/+EB988IEKPPHZZ5/hZz/7mQIpbid0MegE54faunWr6gpYXFysgk4wsMS5556r5o9iV0B6vSZMmJDpKsjugm4X/4DUeszTINVzIBRIbS1V3TOqPVKmS4v1o3Ttc1sSZP9CUYDPJPFIFYo1/XcdutHKnHsfpLYjteqVapAa0RHhTwhSKwCDEMV/1d3rcm0NaqkX6dqnlXCf6jLJVDxS7vWzHyEgZVcjGOvNDlL0AulxTzNmzMApp5yiQpUTpBg04re//a2K4Lds2TIwJDphiGHO9+7dq0CKHid2B2SXv1dffVXtw305BxUhh90AH3jgAeWhOuKII9TYKHqsGA6d3Qa7d++OL7/8EuxWyALudvETSH11w+NY2LM/liuQeg3IgFQaCVZ2SQEpt/aX/QtPATYWBKQKz65+uSLdaGV+vQtSSZgeqe0wVr+KsvGWR2pEB1R90h+oWC4g5ZcC14B86jIpINUAsRx2EZByEKgANzc7SPHG1N37GMqcgSL69OmD8847T41/IhSxUUOPFWGHAMWxUSyMPI4frjOaH/fjR2+LRCIqqh9Dp9OzRZDq3bs3brzxRjV5b6dOnXD00UerqH6cs4p5cbv4BqTmrMdXv35cBZsgSK190AIpgiwskEoJSLm1v+xfeArwOSAgVXh29csVsfzpusibIMV6MmVGkojuQPqb/6J8/ElWsImOCH18K1CxDEgxul9K+aTypb3Wkb8vHqnGW0GXSabikWq8jjxSQCo7/fx4dLODFEWxAxEhafHixSpiHyGF3e24nTcw1+0PRidBeTznodKeqJtvvhnz5s1TE/2yayC7CDJkOr1c9Fy5Obf+bd+A1Bfr8OWvH8ficwcqj9S6h95QHqm0AimYHikBKW1WSQOsAJ8DAlIBLgB5vnSWP10XeRak0tojVQKsfR1lYwlSByM66lCUzboJqFgKpDhtbwLEqXwtWkf+voBU462gyyRTAanG68gjBaSy08+PRzc7SGmI4g3KdcISvUvs7sd1eqL0TcztbhZWQnfccQfoeWI3Pk7Ou3LlSmzatAmjRo1SIdEZAp1d/9gVkAXc7eIvkHpMgdSyHgNQVCtImZH/ZIyU21Ig+xeSAnzeCEgVkkX9dS26vmOuvQtSKatrnx2kWtQCUkkBKX8Vv1pzq8skUwGpWiVq8JcCUg2WqmB2bHaQ0jeoBioNU3ZPFAue3s79G7qwK+DLL7+sJunlvFE/+MEPcP311+P3v/+9CjrBaH+Mbvb8MwAAIABJREFUAjhy5EhVYbkFNebDVyB1/WNYdO4ACEg1tATJfkFUgM8YAakgWt4b16zrRObGuyBl2EDqDZSNO1l5pCIjO9o8UvRGiUfKG6Uqu1zoMslUQCo7LQWkstPPj0c3O0gRXnhz6oXrGpx0qvdxCzr0ZnEOqRtuuEGFTmdIdUb143gprhOkrrzyStWtLxaL1ciHzo9T6h+QKsKXBKleJkite/gNoLgUNbv2iUfKyd6yvfAV4DNIQKrw7ezVK2T503Wid0HK7pEaivIaIPUnoGIJYBCi4uKR8mpBc5EvXSaZCki5EK6WXQWkahGlwL9qdpDSNyg9UCxg+u/9U27nh983dOG+bBAx/PmLL76oJuU966yz0K1bN5x99tlqnqmNGzeq7oP8bcKU28U3IPV5EeZe/6gCqaXd+0ODFOG0OtiEgJRb+8v+haeAfm4MGjRIvXQ5+eSTwYiisogCuVBA1338Lc+ClJFCmj3hozuBtUNRPv4U5ZEKj+iA0pl/FJDKRUHJ4W/oMslUQCo74QWkstPPj0fnDKR4g+pF37T8W3uj7N/p/RqS8jiOuWKYdI6NWrp0KebMmaNSTtTLbdxH/05DzmnfxzMgxUyZQffMWTusdfVHOAV8thZzr3sEi3r2B0Fq7aNDge1lQNJAEmn1AQdHWWZgHZmxSGbFfuWyLgoUpgJ8HohHqjBt64erstd13gQpzgwVt7r27YKxbgwqCVLDWqBqZEdUzPh/QMVCcAczZl/+KhBqqRcJNqGVcJ/qMslUQMq9fvYjBKTsagRjvdlByu8yeg2kMiy0P0jNXoM515ogxTFS3zw+DCgpBxIpBUwqjAfrHOsEnJo4Yf2pv/O7rST/okBDFGBjQUCqIUrJPs2hgG608txeBKm0wqOI+aYttgeJDZMRGn8KosMOQmjUoaia9mugfJ6qV1iHuA/h1HSqUku9CEhpJdynukwyFZByr5/9CAEpuxrBWBeQcrBzoYCUquyMtICUg71lc+ErwMaCgFTh29mrV6gbrcyfP0DqLYTGn4rI0G8JSHm1UGWZL10mBaSyFFLCn2cvoA/PICDlYDS/gtSaJ2p6pJRfSkDKwdqyOQgKCEgFwcrevUbdaGUOvQtS0WqP1PqaIBWadr14pLxbvBqVM10mBaQaJV+Ng8QjVUOOQPwhIOVgZv+DFPu7s7MGvVHikXIwt2wOgAICUgEwsocvUTdamUXvglTMAqm9SNhAqnJkR4SmXgeUfaWqk7h07fNwSWt41nSZFJBquGZ17SkgVZcyhfu9gJSDbQWkHASSzaKAzxQQkPKZwQosu7rRysvyPEhFawOpa4GyL2GkVUgKGSNVAOVTl0kBqeyNKSCVvYZ+O4OAlIPFfAFSVUmkP12NOdc8jMU9B5hR+54cDuwoAxL0SHFAcBpIiUfKwdyyOQAKCEgFwMgevkTdaGUWvQlShpofSlUcsX0wNr+LynFmsAl6pCrevwYom6s2J1Rvh/yJTS31IsEmtBLuU10mmUqwCff62Y8QkLKrEYx1ASkHO/sFpIyPV5kg1UuD1Ahge6kKf26CFGnKkGATDvaWzYWvABsLEmyi8O3s1SvUjVbmz9MgxQiv8TJg6/uoHHsyosNawASpfvuBVDXM5FpzaqkXASmthPtUl0mmAlLu9bMfISBlVyMY6wJSDnb2K0gVPTXS9Egl9RgpxjoXj5SDuWVzABRgY0FAKgCG9ugl6kYrs+d9kCoHtk5D5dhTERt+MEKj6JG6Gij7AmkYSIBzSVXDTK4lp5Z6EZDSSrhPdZlkKiDlXj/7EQJSdjWCsS4g5WBnv4LUuqdHmvNIJRlqgsEmBKQcTC2bA6IAGwsCUgExtgcvUzdamTXvglTC7L0Q3x+kDkX5e1cDpQJSHixajc6SLpMCUo2WMHOggFRGisCsCEg5mNq/IDUK2FkBCEg5WFg2B00BAamgWdxb16sbrcyVd0EqWQ9IXQWUfi4eKW8Vq6xyo8ukgFRWMqqDBaSy19BvZxCQcrCYX0Fq/V8EpBxMK5sDqoCAVEAN75HL1o1WZsdvIFU1mh4pE6TYqS+BFFLgYKr8LNRSL9K1TyvhPtVlkql07XOvn/0IASm7GsFYF5BysLMvQCqURPKDFZjLqH09+mN59wEoIkjtKgfihpoPhFUdw9XqhWuZvzIrequkokDhKsDGgnTtK1z7ev3KdKOV+fQiSJmuqIRZQcQrkN7+CcrGmcEmqkYejsp3rwD2fKzG3HJ8lBkXNj+qU0u9CEhpJdynukwyFZByr5/9CAEpuxrBWBeQcrCzF0FKZVnXH0wJUrNWYG6/h7G4e3+s6D4Aa58ZhTRBKmZG6uNuSVXpWQDFL/Q5HDSQzaJAISnAxoKAVCFZ1F/XohutzLV3QSpu1g+JShg7vkDp+JMQGX4QwiM6I/TOpcCuDzmnhvJFCUj5q/zVlltdJgWkalPH3XcCUu70KoS9BaQcrOhXkCp6ZjSwu8IEqRTDTQhIOZhaNgdEAQGpgBjao5epG63MnudBKt4QkMqf0NRSL+KR0kq4T3WZZCoeKff62Y8QkLKrEYx1ASkHO/sVpNY9OwbYUykg5WBf2Rw8BdhYEI9U8OzulSvWjVbmx78g9YHlkZKufV4pV9nkQ5dJAalsVDSPFZDKXkO/nUFAysFivgWpwWOAvSFzjJTlkTL7s0vXPgeTy+YCV0BAqsAN7PHL041WZtOzIJXWY6Rq8UhNYde+apAy+zvkR3RqqRfxSGkl3Ke6TDIVj5R7/exHCEjZ1QjGuoCUg529CFKq6tD1B9NaxkitHzy2FpAy+7RnjtfncNBANosChaQAGwvikSoki/rrWnSjlbn2JkilgXTSfOMWDx0wRqpySl8BKX8VOcfc6jIpIOUoleMOAlKOEhXcDgJS9ZiUDxVWdP/9739x1FFH4YgjjsCYMWNAuMr5QuhJ20DIDMZnVnZVSUSnLcbnv3oAi865DSt73QEFUuzaF08DSQMpg8Fqbcdb55OAEzm3pPxgnhUwDAOhUAj3338/WrVqhZNPPhnTpk3Lc67k54OigG608nq9CVKsXCyQSoSBnV+ifOIpiA4/CFUjDkeIILVzpqpMkukEDAl/7vuiq8ukgFT2phSQyl5Dv51BQKoei/Ghoj1SRx99NI488kgFUqz87A+eXKyDXRjSZn901ZXC4P8WWVXGFUjNveYRLO5+G77uOdAEKQabYPhz1bUvDXbt40cdZ52P58xF/uU3RGevlAGCFD1SBKnWrVvjtNNOw4wZM8DvZREFmlsBfR/wd7wJUqxrUuZLOoLUrnkon3gqoiMskHrnEmDnDBX+PJGOw3xF19yq1X5+aqkX6dqnlXCf6jLJVLr2udfPfoSAlF2NYKwLSNVjZz5UCFLaI/Xtb38bY8eOzY9Hivm0e6RY11nfoTKhQGrO1Q9h0Tm3KpDa9PwEs2sfw59nQKoWj1Q91y+bRIFCVID3tQYp7ZGaPn16IV6qXJMHFdCNVmbNuyBldXlIRIBd802QynikqkEqmY4JSHmwjLnNki6TTAWk3KpXc38BqZp6BOEvASkHK7Oie+WVV3DMMceorn0jR45EeXl57r04BikqjRS9UnwLlzJTI5kCKmKoen8hvrjqQSzpMQAregzEhufGVUftSxpIGpyB3vRIqeOt86Xp2RKvlGgQoDLAiq6srAz33Xef8kideuqpIEiJR8rhYSibm0QB/bzlyTwNUnTQJqPAbhOkzHmk2LXvEqBkOmCkkISAVJMUijyfRJdJAansDSEglb2GfjuDgFQ9FuNDRXuk2K2va9euGDp0KHbt2oVwOJzTTyQcRqQqjFDE/N1YlZlGqiJI7K5A6VtzFUgt7TkQy7sPQNGzoxEt3o1UaQjxUBhV4TAqwlWZ43muaFUYPG+ur0V+TzTPZxmgN2r37t24++67M2OkCFK832URBZpbAd1o5e94E6TY+yGNtAapPQuURyoy7FsIjzgclQqkpglINXdByeH5dZlkKh6p7IQXkMpOPz8eLSBVj9X4UGFF9+qrr4JjpA477DD1Fvvtt99WYyo4riJXn5kzZmDm9BmYPnMGplvr/O2Z02fi0ykzsGDwcHz087uxtNdALDn7Vswe8Bw+f3saPn5nKj6YPgMzZs3E+zOmY9qM6SrPPJf65PAacqWV/E7uyqUftSY08R6+4YYblEeKwSamTp0qIFXPs1A2NZ0CutHKM3oWpDiSVoFUDNizUIFUWIHUYaicchFQMtUCKY6Ryt/YQmqpFxkjpZVwn+oyyVRAyr1+9iMEpOxqBGNdQKoeO/OhwoqOXfsIUocccggOPfRQdO7cOeefLp07oyt/t0tnHN61MzoeYf7dtXNXHHf4t/HHo8/Bu31uwsIet2F5jwF49AeX48QuR+E7h3fBkV2PQKeuXdDpiK7o1KUL9LmY8nyduphpPq5LfjP3ZUk074xOnTqhXbt2aNOmDY477ji8+eab0rWvnmehbGo6BXSjlWf0IkgxpJEBAhKARALYswKlE85AmGOkRrZH5TvnAzumKJAixlSjTNNp1NAzUUu9CEhpJdynukwyFZByr5/9CAEpuxrBWBeQqsfOHDOhPVLs2teyZUt07NhRNcK6EEhy+OnapQuO6NIFTA8/ogs6HNkFR3Tmpyu+2+Vo3HT0OXi/z01YfO5ALPnJrXjkB5fhpCO+g+906qpAqvMRXdHlyG+jS9eu6hw8lufiNXTumttryaVu8lti29rKAGGS9zKDTRx//PEYP348WAHKIgo0twK60crf8SZIpWAgpqbLQCIJ7F2J0gk/tECqHSrf6QPseFuBFK+hGmWaW7kDzy8gdaAmjflGl0kBqcaoV/MYAamaegThLwGpeqxMkCotLcV//vMfNY8UvVHXXXcdHn/8cTz77LM5/wx+xvzNp4Y8i8effxb8e8gzg/G3p5/DW79/FB/3vQNLet+OZd37Y/Jv7seLjz6FF556Bs89OxhPP/sM/jJkMJ4ZbJ5Dn+uZZ5/NfJePa5LfzH05CrrmzzzzDJ544glceOGFyivFrn3vvfeeeKTqeRbKpqZTQDdaeUZfgNS+VQJSTWd+T55Jl0kBqezNIyCVvYZ+O4OAVD0WI0gxQp8Of84322+88QZKSkrUhJ6c1DNnn8oQqipDCFWGUFYVwp6I+Te/C+8uR8XYzzDnfwZhQY/bsOrcO7Fm8GiUb9mBWFmlOq6iKoSyUCUqKivVOfS5KkMhVIRCYJqza5HfEq3zWAYYQIYBY+68807lkWLUPo71Eo9UPQ9D2dRkCuhGK0/oeZBKJoF9q1E28Udg1L6qke1Q8U5vYPtbgOXBFY9UkxWNvJ1Il0kBqexNICCVvYZ+O4OAVD0W0yDFYBPs2sd5pMaMGaMqP/uDJxfrekJepkmkEWWHCvYPNwCjMobE2wvw1a8eVCDFMVLrXxiPdFkVEE8BBqdM5HGGGTqdx1kfTs5rcGBxgMJfy7UG2968rxm5b9CgQQqkTjnlFEybNk2CTdTzLJRNTaeAfv7wjL4AqdJvUD7pTNW1LzSiLSqmaJBKmtVI00nj+kzUUi8yRkor4T7VZZKpjJFyr5/9CAEpuxrBWBeQcrAz314z2MRRRx2VASl+l/OF9YX1SQKIMgP82wKp+OR5+PKXD2JZnztU174NL040QSoSV/NPEZYSaQ4itmbytc5lnUKdKufXJD8oCuRBATtItW7dGuzaR5BK8u27LKJAMyugG638Ge+DVAooqwlS5QJSzVxCcn96XSYFpLLXXkAqew39dgYBKQeLEZq0R4rzSNEjlReQYj5JPZwjEUBM/83QSuEkIpO+VB6pJeea80hteulNoDxseqRMx5XyZFmnyJzL4inzxPK/KBAABdhYsHukCFLs2ieLKJALBXSjlb/lVZBKIYIkKwd236sowr7xVrCJEW1R9lYvYNubKtiEwQndcyFaHb9BLfUiHimthPtUl0mm4pFyr5/9CAEpuxrBWBeQcrCzF0GKscUyIMV6pBaQ2iwg5WBZ2RxUBdhYEJAKqvXzf9260cqceBWkkgJS+S8oOcyBLpMCUtmLLiCVvYZ+O4OAlIPFfANSE+dmPFKM2rf5pclARUQ8Ug72lc3BU0BAKng299IV60Yr8+RVkEohipTySBmmR0qHPx/RFqVv9QSKxSPlpTKVbV50mRSQylZJOnFT2LZtG/r166emzOnWrRuKiopqjMGlzrIUjgICUg629DxI6a59E+eqMVKcR2rZOf2x5e8WSCUM1Y2PuzFIReb2tVaYZL5z0EI2iwKFoAArMfFIFYIl/XkNutHK3HsapJjBlAFUrqsR/rx0MkFqkjkhrzXkNl+WsDdIpWtf462gyyRT6drXeB3VLSMglZ2APjxaQMrBaP4CqQewuNeAOkGKXQIz0CQg5WB52VyoCrCxICBVqNb1/nXpRitz6ieQ0uHPFUhtFZDyfklreA51mRSQarhmde0pHqm6lCnc7wWkHGzrKZBiXq3AEXGdbwJROIHIhDn46hcPYEmvAVjavT+2/OMtoDIC2DxStYGUdUp9NklFgYJXQECq4E3s6QvUjVZm0psgxeky4gwIq6bOQGgzyiaciejwFqga2Rblb/4E2DIxEw0283IuD6pTS72IR0or4T7VZZKpeKTc62c/QkDKrkYw1gWkHOzsFZBidWFWbCZM6eqDcGREkoiM/gyLrngAy3oMwOIe/bHpn28hzTFSqTTShhn2/ACQ0idx0EA2iwKFpAAbC+KRKiSL+utadKOVufYmSKWR4pyDnCzDSAGRPQhN+AliQw9CaFRrhCeeDmwcY069oWYoVDVTXoxALfUiIKWVcJ/qMslUQMq9fvYjBKTsagRjXUDKwc6+Bal/CUg5mFY2B1QBNhYEpAJqfA9ctm60Miv+AKm9CE04pw6Q4shbvqLLz0It9SIgpZVwn+oyyVRAyr1+9iMEpOxqBGNdQMrBzn4Fqc3/etvs2iceKQcLy+agKcDGgoBU0KzunevVjVbmSEAqO7tQS70ISGkl3Ke6TDIVkHKvn/0IASm7GsFYF5BysHOhgFQK6QOj9lXXQQ4qyGZRoHAUYGNBQKpw7Om3K9GNVuZbQCo761FLvQhIaSXcp7pMMhWQcq+f/QgBKbsawVgXkHKws79BKpoZI2WClDlWSl0y65/qOshBBdksChSOAmwsCEgVjj39diW60cp8C0hlZz1qqRcBKa2E+1SXSaYCUu71sx8hIGVXIxjrAlIOdvYHSCUQGTU7E2xiSY/+qNm1j73YxSPlYGrZHBAF2FgQkAqIsT14mbrRyqz5BaSqOEZqGINNtKoRbCKl+jnIGCkPFjNXWdJlUkDKlWy17iwgVassBf2lgJSDef0CUlUjPlEgtbznQCzpOQBbX37HHCOV5IS8JkhJ1D4HY8vmQCggIBUIM3v2InWjlRn0KkglkUSKQSTSBhDdh6qJ3REb1gKVI1shPOl0YMNoFbUviQQYLD1fC7XUi3iktBLuU10mmYpHyr1+9iMEpOxqBGNdQMrBzv4GqSggIOVgYdkcNAXYWBCPVNCs7p3r1Y1W5si7IEWMqgOkGP58/SgBKe8UqaxzosukgFTWUkJAKnsN/XYGASkHi/kVpIr/8y4QIkilxSPlYGPZHCwFBKSCZW+vXa1utDJfXgYpjqhVHqlYKcJ2j9TE04B1IwWkvFawssiPLpMCUlmIaB0qIJW9hn47g4CUg8X8D1LVXfs440emIwRXMn84iCCbRYECUkBAqoCM6cNL0Y1WZt2rIKUn5FWVBEFqUg/EVde+lqiacKqAlA/LXX1Z1mVSQKo+lRq2TUCqYToV0l4CUg7W9CtIbXvlPSAUM7v2GdXBJgxNTwJSDpaXzYWqgIBUoVrWH9elG63MrW9BqmgE0ilAxkj5o8w55VKXSQEpJ6WctwtIOWtUaHsISDlY1EsgpYb0GqYnSTuT1J+RBCqGfoSFV9yPZT0GYDGDTbzyLlBljpHiw5HeKNMjxa5+ljfKOok+l4MUslkUKAgFeD/IGKmCMKUvL0I3Wpl5b4IUAYm1AmucFBAvReXkPogOa4Wq4a0RHnciUPQ6jDRgpBkPNn81CLXUiwSb0Eq4T3WZZCrBJtzrZz9CQMquRjDWBaQc7OwVkCIwJZnX/UBKVSORJEpfm4UFPx+Epd37K5Da8uq7MAhSRhr0QiVVbCWr0mGiP9LDz6EEyOZCU4CNBQGpQrOqf65HN1qZYy+CFKuYuJIzAaQTMJKlKJ1yIcJD2yM6tB2i444H1r0Mdv9Lp6wXc3mSn1rqRUBKK+E+1WWSqYCUe/3sRwhI2dUIxrqAlIOd/QpSW199D0Y4ZgMpdu+zFg1RVh1UXRXpHSQVBQpXATYWBKQK175evzLdaGU+PQ9SSCCdKkPZlIsQGdahGqSKLJCiWyqPFQi11IuAlFbCfarLJFMBKff62Y8QkLKrEYx1ASkHO/sWpP77PtKRuICUg31lc/AUYGNBQCp4dvfKFetGK/PjB5BCqhxl7+wPUv82PVJWD4l8aUst9SIgpZVwn+oyyVRAyr1+9iMEpOxqBGNdQMrBzn4FqeLX3gcEpBysK5uDqAAbCwJSQbS8N65ZN1qZG++DVBIwylH+7sWIDu+ImO7at/bfSHJ8lICUNwpVlrnQZVJAKkshOaowlcK2bdvQr18/tGzZEt26dUNRURGorV7s6/o7Sf2rgICUg+38ClLbXpsKRBPikXKwr2wOngKsxASkgmd3r1wxy59uSPkFpCrevQTR4YeaXfvGHg+s/ZeAlFcKVBPkQ5dJpuKRyk5QAans9PPj0QJSDlbzA0ilwwns++8MLLh8kBm1r9cAbH99mnikHGwrm4OpABsLAlLBtL0Xrlo3WpkXr4JUgplLx1WwCXbtq3yvb8YjFRn7XaTX/BNJjrrlS/bqF+05l5da6kW69mkl3Ke6TDIVkHKvn/0IASm7GsFYF5BysLMfQMqoimPvq9MxnyDVcyAWE6TeEJByMK1sDqgCbCwISAXU+B64bN1oZVa8ClJmhFgbSL3fFxHVta89ImOOg/HNP9QYKQEpDxSoJsiCLpMCUtmLKSCVvYZ+O4OAlIPFCgekDHDGD7Xot4i2Px1kkM2iQMEoICBVMKb05YXoRisz72mQokcK7B5ejtDUSy2PlICULwudQ6Z1mRSQchCqAZsFpBogUoHtIiDlYFC/gtSON6bvN0ZKQMrB1LI5IAoISAXE0B69TN1oZfb8AlJVUy9TY6RiQwWkPFqsssqWLpMCUlnJqA4WkMpeQ7+dQUDKwWKFAlKJtKFmq1dOKPFIOVhdNheyAgJShWxd71+bbrQyp34BqfC0yxEbcSgEpLxfvhqTQ10mBaQao17NYwSkauoRhL8EpBysLCDlIJBsFgV8poCAlM8MVmDZ1Y1WXpa3QYohJ8yufeHpAlIFVgxrXI4ukwJSNWRp1B8CUo2SzdcH5Q2kWNh403Jhqv82DEP9bU/1tkQiobYlk0lwPRKJqOP0vtyP6/rDv7mv/g39e+qLBv7naZDSY5yqEtjz8lQsZLCJ7gOwtNdA7Bg2E0bMDH/O6zaQRophd2u57tq+q2U3+UoUKAgFeD9IsImCMKUvL4LlT9dFXgQp1hJJ1hgpXReXIjLrF4iNOBzxoW0RHXME0qv/yph9MGuU/NUgWkcWBIna1/jbQZdJphK1r/E68ki2O2Ueqew09NvReQMp3rCxWEzppUGJ0GOHIK7rbVzndh6zY8cOzJw5Ex9++KF6o0eoCofDajvXeQxT7q/XmWqocmMkP4AUqhLY/e/3FUgt794fywhSw2ciFYureaRIT6zqUmkDev7E/FV9btSXfUWBpleAzx4BqabXVc7YMAV0o5V7exOkOJ42CYNz8aaBpLEXkQ9+hdiITki+0RaxMYcDq19Q2/iCrvbXcw3TItu9qKVeBKS0Eu5TXSaZCki5189+BNuaAlJ2RQp/Pa8gxQLHj4YnnWoI4t8ajLgfb/JQKIQnn3wSxxxzDI488kjMnTsX+/btw65du0DoIWhxPR6Pq2MJWCUlJSgvL1e/5dakvgKpywahfpCiZyrvU3+4NYHsLwo0qQJ8jghINamkcjIXCuhGKw/xA0il0vuB1OjDgFXPC0i5sLnXd9VlkqmAVHbWEpDKTj8/Hp03kNLQxEJHD9OSJUvwj3/8A3feeSfuuusujB49Glu3blXd9whF2ltVWlqK0047DW3btkWnTp1w4403om/fvjjvvPMwcOBAPPLII7j44ovx7LPPori4GPPnz8cFF1yAX//611izZo1rG/kJpBZcdh+WndPf7NqnPFJm1z5YXUn49lBAynURkAMKTAEBqQIzqM8uRzdamW1vglRaeaTSnG83zZ4M+xD98CrERnZGcuj/z955gNlVlG986b2oIOpfRGkqIoqUhB46UqWLIiqIkB5CAkkgVOkKCCIlvUMSAimUAOlts+mdhIT0ssn2vbu33/f//ObeWW5iSNhsdvfe3e/sc3ZOmXbeOXe+8873zTdopL4iUkl91FdaobpuCrD0m2mkPBLVD/07SWhEqvr4pacwIpWORuM4rjcixcsWDAb15Zdf6tFHH9UJJ5zgNEyHHXaYI0honF588UVt2rSpSmvF8UcffaTDDz9c++67r/bZZx8ddNBBOvjgg/Xtb39bF1xwgX75y1+KPK644gpNnTpV//rXv1zcH//4xxo+fHi1WzXjiRRme+Vh5b86Qkki1UJzmrRypn3x8FdzpOggjUhVu/ktQQNEgN+CaaQaYMNmySP5j1aqm7lEKqZtiVQ4RaSC/Q5TYtHzijmTcTPty5LXbofV9O8koRGpHUK105tGpHYKUYOLUG9Eih9sQUGBI0uQpr322quKHEGSOEfzlJeX54gUWqlevXo5srXffvtp7733dnEIjznmGF133XWONJ1//vk68MADdfbZZ2vMmDHq2rWrI1wQKeZUVXfLKiJ1GRopI1LVbWOL37jPXzHKAAAgAElEQVQQoO8xItW42jyTntZ/tFKn7CRShyqx8DnF4nKDczZHKpPerl2ri38nCY1I7RqGPpURKY9E4wnrlUgxdwlTviOOOELf+9733NynESNG6IYbbnCk6sQTT9TYsWMdkWLuE6Z/Rx55pL773e/q+OOP12233aY333xTEydO1JIlS7Rq1Sr97ne/E0SL+VNNmjRx8SBlkK3PPvus2i2bDUQKZxMbXn5PeZd11PwzW2vWmS2V3/dTJSKp2cIpb32mkap281uCBoiAEakG2KhZ9Ej+o5UqZzKRwg4cy7m4ihQdd5NCvb+tcLf9FOp3mGLzn0nNkUq6m6gv+MHSb2ba55GofujfSUIjUtXHLz2FEal0NBrHcb0RKV42HED06NFDp556qpvXhMbolVdeceQHrdRpp52mRYsWOSLFHKm5c+fqoYce0t/+9jc3N+quu+7SzTff7M67d+/uPKXcdNNNTlOF2R/zqCBVe+65pyNSDVUjBZFa/9IwI1KN4zdrT1lDBPhYMI1UDUG05LuMgP9oJYOMJlKY7qWIVGz8zW6OlCdSUSNSu9z+mZjQv5NGpGreOkakao5htuVQb0SKHyzkiHlPI0eO1JAhQ/TCCy8IE7z999/fESDM82bMmOGIFC8nHvzwyHf55Ze7eVFomjDtY0ejNWrUKN14442OSHEPZxTMndpjjz30k5/8pMGa9n0tkYrGUu7Pk8YXppHKtp+n1bc2EKDvMSJVG8hant8EAf/RStxsIlLMkYJIBfsequg800h9k7bOljj+nSQ0jVTNWs2IVM3wy8bU9UqkvIvyZcuW6ZZbbnGkBxKFBgmNEiSoc+fOjkjxA8fMDtM/TPuIh5MJHE+gdcLkjzlUaKRwQIE2CmcVaK8gWscdd5wmT55c7TbKFtO+bTVSm/t+KhmRqnZ7W4KGjwB9iRGpht/OmfqE/qOV+hmRqlkrgaXfzLTPI1H90L+ThEakqo9fegojUuloNI7jeiVS/Gh56ebNm6fTTz/dkaKTTjpJl1xyiVsnCjIEwSouLnbx0EZ16tTJaZrQQDVv3tw5mYBUQa7QbOEOHbNA7uNC/ZprrnGk7JRTTtHSpUur3apZS6T6QaSYDZxcjRdxYxqpaje/JWiACNDvGJFqgA2bJY/kP1qpbvYSqadtjlSWvG/fpJr+nSQ0IvVNEPv6OEakvh6bhnqnXokUa0nhAh0nEbgpR3uEeR4OJnBfjsaJEBfpxGNdqNtvv91d/8UvfqG33npLP/3pT935D3/4Q6HZuvvuu51GinPu/+Y3v3HECpM/Vpuu7pYpRAoiFKPyHCS5UdWxczbxYmqOVJOks4nNECncKjFil4rvpwWnsqguFBbfEGgQCBiRahDNmLUP4T9aeYBMJVJx52mCwbeUs4nxtyrc5whFcDbR9xBF5z3l5JGtI5W1r+FWFffvpBGprWDZpRMjUrsEW1YnqlcihRBhracHHnhAQ4cOde7QGSlesGCBI1CY7V122WVCZe/nR0G2vDnfoYce6rRN3/nOd3TPPfc40z8W5T3kkEN09NFHO0cWOKPAjTpmf+Xl5UrvMGg5zne0ZQqRcnVMr2rqGEEHkcp/dohmXdrRrSE158xW2tz/MzcHLf353LPv6GHtniHQCBDgd2AaqUbQ0Bn6iK4fTsmdTCRSbrAuzsBdVBFFFI0VKzrxbwr0/r7C3fdRrNfeis15VFEnP/0S7/UDdrp8M9O+XW8D/04SmkZq13EkpRGpmuGXjanrlUht3rxZHTt2dPOXzjjjDE2bNs2RJhxPoGlirhNEiHgQKUgN5nuYATInCmcSmPAxLwqnFNzH6x/XmF/VrFkzXXvttbr++us1adIk5yWQRvKdhj/eUcNlDJHaVo2UTqTKI9ryzGBHpGY3aaUkkRpTNbfMP1+60PHXLDQEGhsC/A6MSDW2Vs+c502XPxlLpGIQqbAiCisWLVF04r0K9P6hwj32UaLnnorP6aqIk6XYSaSP8NUtzukyzYjUrmPv30lCI1K7jiMpjUjVDL9sTF2vRGrLli1OG+VJ0Zlnnqmrr75av/71r50DCTRPuDuHRPEDJ0Tw4Ma8S5cu+vOf/6znn3/eabAgPLhK5xrrUuGsAicU7GiurrrqKmf65zsMzArZON/Rlq1EasuAJJHa0bPZPUOgMSLAb96IVGNs+cx4Zi+DqE1WEKlYqWKT7lWgD0RqXyNSmfEa7dZa+HeS0IhUzaA1IlUz/LIxdb0RKUgRHzNooc477zxHdg488EBnloeTCY5xc868J0gPO+7S8fTHfCkIDutQsWOyt3LlSqeZQhOF8wnIGQ4m0GxBqnBGgfaLPHynQYOlH2+vAbOWSA0c6zDzz8Rz2mYIGALJ37wRKXsT6guBdJmTDUQqHi9TfHJzVfQ9WpGeSSIVM41Ufb0+tVKufycJjUjVDGIjUjXDLxtT1xuR4gcLKeKDZvTo0WrXrp0uvfRSNW3aVFdeeaW6du2q+fPnO8LEi8kO+YIIcQyxIg9CyA4L8jJXCo99aLJwm47Tit69e7s1pHBcwXyrysrKqrS+89hRw2UrkSoYOG4rbRvPapshYAgYkbJ3oH4RSJc7GUukol+Z9iWJVAtV9P2RI1LxnnsoNtub9tkcqfp9m3ZP6f6dJDQiVTNMjUjVDL9sTF2vRApSBBGCIBUWFmrx4sWOPC1fvtyRo1AoVKVB8uTJp0n/4UN2cHWONsovzvvJJ59o/fr1ysvLc5opNFy4VSeuJ2E+jx01XNYQqae3niNVMGjcVo/Fs9pmCBgCRqTsHahfBNLlTkYSKbhRGpFKJMqUmNJClf1SRKoHROrh1BwpI1L1+zbtntL9O0loRKpmmBqRqhl+2Zi63ohUOlj8eD2h8lon/8NOj7e9Y9Lx4jLfqmXLlo5MMS/qmGOOcZ7/0EJh6ocnvzvvvHMrLc328tv2WrYQqU3/eDvpta9pa806vYUKtyFS2z6XnRsCjRUB+hYz7WusrV//z50u2zKSSDHm5ogUPvtCisdKpamtnGkfziZiPfZQdNZDRqTq/1XabTXw7yShEamawWpEqmb4ZWPqjCBSNQHOEylM9iZPnuzM93A2wTwrzPnw/AeRwtMfpn7V3bKGSD05SLMu6aA5EKkzjEhVt50tfuNBwIhU42nrTHxS/9FK3bKSSHXPUcSIVCa+WrtcJ/9OGpHaZQirEhqRqoKi0RxkPZHipYVMsWMKuHDhQnXq1MmZ8x177LFuPalzzjlHw4cPr3J/Xp3WzRYitfHJQZqZIlKzz2ipwkHjq/OYFtcQaDQIGJFqNE2dkQ/qP1qpXOYTqbDi8VJpWmtV9v2Rc38ehUjN7GIaqYx8u3atUv6dNCK1a/ilpzIilY5G4zhuEESKeVOQKDoBPPqx48lv1apVzptfUVGRu0+86m7ZQ6QGOiI196w2blHeoreNSFW3rS1+40CAfsJM+xpHW2fiU/qPVuqWHUSqTMpt4+ZIYdoX6Zaj8IzOCjuvtzZHKhPfserWyb+ThGbaV130to5vRGprPBrDWYMhUmikmF/ltVO8zHgF5Fq61qq6jZodRCqsDU8M1MyL73emfXOatJIRqeq2tMVvLAgYkWosLZ2Zz+k/Wqld1hCp6W0V7HeM00hBpEJ5EKmEEgkjUpn5llWvVv6dNCJVPdy2F9uI1PZQadjXGgSRgjzx8tIJ+JBjNFDpHcSuNGXGECkqn0hbQz7lhA8xprJtiFTT1ip6e8KuPK6lMQQaPAL0CaaRavDNnLEP6GUSFcxYIhXD/XlEUfROsTIpr70q+v9E4R57JTVSeZ0UTSBzjUhl7ItWjYr5d5LQNFLVAG47UY1IbQeUBn4p64lUbbdPRhEpSY448dCpA8enyiJa/2g/52xiZpNWwryv6B0jUrX9blj+2YmAEansbLeGUmv/0crzZCSRYsROcUUVUTwRkcKlYgHeogHHKdw9R9Eeeyo+/UEpGlRCcfRS9dY0YOm3FStWuHUoWQKFtSjXrl1bbS+9Pq/GFvp3ktCIVM1a34hUzfDLxtRGpHbSatlBpMJa/0gakTq7jYoGT9zJk9ltQ6BxIsDHgmmkGmfbZ8JT+49W6pLZRCqaRqQeUdHA4xTukSJSuQ9I0UolFDMilQkvVQ3r4N9JI1I1BFJyVlHr1q3TDTfcoH322Uennnqqli1bthWpB2fbGg4CRqR20pbZQqTWPdLXzZFCIzXv7LYqNiK1k5a1240VAYSYEanG2vr1/9z+o5WaZCeR2kOx3I5SpEIJRY1I1f8rVeMa+HeS0DRSNYPTNFI1wy8bUxuR2kmrZQ2R6uqJVEvNO6edEamdtKvdbrwIGJFqvG2fCU/uP1qpS7YQqfjcR1Q86HhFeqKRShGpaMCIVCa8ULuhDv6dNCJVczCNSNUcw2zLwYjUTlosm4jUjIvv18wmLTX/3HYqHjJpJ09mtw2BxomAEanG2e6Z8tT+o5X6ZCaRomYY7cUVT8SkcJm2JVLRaR2kSHmKSFXN3K1ziMHSbzZHyiNR/dC/k4Smkao+fukpjEilo9E4jo1I7aSds4VIrX24T9K0r2mrpEbKiNROWtZuN1YE+Fgw077G2vr1/9z+o5WaZC6RkqI4kkgRqcS8x1U86IQqjVR02v1SpEwJ5wTdiFT9v1U1q4F/J41I1QxHUhuRqjmG2ZaDEamdtFh2EKmIVnXp5RbknX1Wa805q41KjEjtpGXtdmNFwIhUY235zHhu/9FKbTKVSFHHqHckEQ5Ii55WydsnOiIV64lpX3spWqZYPOm5r76QpZ5+M42UR6L6oX8nCU0jVX380lMYkUpHo3EcG5HaSTtnFZG6+H7NOqu15p5tRGonzWq3GzECfCyYRqoRvwD1/Oj+o5VqZC6RQiOFY/OEtA2RiuK5bxpEqlSxBEQqVm+IgqXfjEh5JKof+neS0IhU9fFLT2FEKh2NxnFsRGon7ZwdRCqsVZ17OtO+WU0hUm1VMmTyTp7MbhsCjRMBPhaMSDXOts+Ep/YfrdQl84mUviJSg5IaKYhUZGo7KQKRSrpAry9cwdJvRqQ8EtUP/TtJaESq+vilpzAilY5G4zg2IrWTds4WIrWyc0/NuCipkZp3TluVDjUitZOmtduNFAE+FoxINdLGz4DH9h+tVCVbiVRoclslIiWKm0YqA96omlfBv5NGpGqOpRGpmmOYbTkYkdpJi2UNkerUQzMuai/mSOG1z4jUThrWbjdaBIxINdqmz4gH9x+tVCabiFRxmkYqNLmNEpFi00hlxBtV80r4d9KIVM2xNCJVcwyzLQcjUjtpsUwkUs6Y4SuLBqk0rFUP9tDMi9on50id104l707ZyZPZbUOgcSJgRKpxtnumPLX/aKU+mUikEC344Ys5ZxNxKRqQFv9TJQN/oUiPHIV75Sg0ubkU2qJ4IqSEi10/6IKl38y0zyNR/dC/k4Rm2ld9/NJTGJFKR6NxHBuR2kk7ZxSRSiDckkKOOcBuIywOa80D3TXrwvaaeVZrzTq/nYqHGZHaSdPa7UaKAB8LZtrXSBs/Ax7bf7RSlUwlUsiZRCKshCJKxCukJa+qdMCpCnfbS5V9IFJ3SZUblYhHqkRRfUALln4zIuWRqH7o30lCI1LVxy89hRGpdDQax7ERqZ20c7YRKbz2zb7gPiNSO2lXu914EeBjwYhU423/+n5y/9FKPYxI1aw1wNJvRqQ8EtUP/TtJaESq+vilpzAilY5G4zg2IrWTds4OIhXSmo5JjRREak6z9ip5b+pOnsxuGwKNEwE+FoxINc62z4Sn9h+t1MWIVM1aBCz9ZkTKI1H90L+ThEakqo9fegojUuloNI5jI1I7aedsIVKrO3bTzGb3uTlSRqR20qh2u1EjwMeCEalG/QrU68P7j1YqYUSqZk0Bln4zIuWRqH7o30lCI1LVxy89hRGpdDQax7ERqZ20c9YQqQ5GpHbSlHbbEHAI8LFgRMpehvpCwH+0Ur4RqZq1Alj6zYiUR6L6oX8nCY1IVR+/9BRGpNLRaBzHRqR20M50KhCpN998U0cddZSOPPJI9e/f313bQbLauYW82J6zCdwrFQW1Oo1Izb3wfpW+P6126mG5GgJZjgC/6/Lycj3wwAPab7/9dOKJJ+qjjz4SAtA2Q6C2EfAfrZSTyURKOJpQRPFYQPridZUN/I0i3ZPOJoKT7pQqNkjmbKK2X5c6yd+/k4RGpGoGuRGpmuGXjamNSO2g1ehUiouL9frrr+sHP/iBI1MDBgxwwi+946mLYzHyFk8oqoRzSssx5TrPs8Uhrbr/TeWd31Z5Z7bQ/Is7OiJVF/WyMpLtYDhkDw7xeNwRqU6dOmn//ffXCSecoA8++CD5e9pBf2C3DIHdgYDvK8gra4jUl2+p3BGpvVXRJ0eVE/8qBdZLCfPatzveifrOw7+ThEakatYaRqRqhl82pjYitYNWo1NB0L3xxhv63ve+pyOOOEJ9+vSpPyKVSJKoGKopSFQioUQs4TRSK+57XXMu7uDmSCWJ1FT3YZjeQdpx9nzsW1vVXlt5ItWhQwftu++++ulPf6pRo0aJ67YZArWNgP9tU05WEqneRqRq+x2p6/z9O0loRKpm6BuRqhl+2ZjaiNQOWo0PK0+kMO2DSPXt27feiVQ8jUh5jdTnLV9JOps4u43mXthBZcNzjUhBNG03DLZ5B/hdY7L74IMPOo0UROrDDz90OO2gO7BbhsBuQcD3SWSWVURq0GmK9thbFb1zVDHxL1I5GilsJOpvA0u/2Rwpj0T1Q/9OEhqRqj5+6SmMSKWj0TiOjUjtoJ3pVEpKSpxpH0TqW9/6ljtevXq1CgoK6nwv3FKg/MICbS4sEMfUoXBLoQJfbhREasYF7TT77DZuHamNA8fUef3qAxMrs+7fw2zHfMuWLVqzZo1at27tNFJ+jlT6R9kOugW7ZQjUCAH/0UomWUukJkCk1hmRqtGbkDmJ/TtJaESqZu1iRKpm+GVjaiNSO2g1OhXmSOFs4vvf/74OOuggXXHFFWrevLnatm1bp3u7tm3F3qpdW7Vu11bt2iTLv69tOz3893b64LdtNeWsFprRtJVyz2qp129pXaf1q2s8rLy6ff8aGt4tWrTQGWecUeVsAo1UNBrdQW9gtwyB3YOA/2glNyNSNcMULP1mGimPRPVD/04SGpGqPn7pKYxIpaPROI6NSO2gnelU0Ej17t3bOZvYe++9dfDBB+uwww7T4YcfXuf7tw47XId863Ad+q3DxTF1+Pbh39bxhx6lbr+6WZOa3OuI1MTT7tYfvv/rOq9ffWBiZdb9e9gQMMdMl9/yAQccoJNPPlmjR4+2OVI76Avt1u5DwH+0etPxO++8U4ceeqizeOAYJyidO3d2pqf+mPM62zt1VucHu+ihTp3UqcsD6vxwOw1+tJnWv/VTRbrnqLJXjnJf/Y2e7XK3unS5Xw92frDu6rYdHMDooYce0l133aWjjz5ae+65p5v3yIBnly5dHJ6EdYbfduqYyWWDH2bOHqMLL7zQDTAxf/Taa691uHGPOJn8HJlUt3vuuUc///nPncXDaaedpmXLllWZjvvf/+7rUSyn+kbAiNQOWoCRhcrKSo0dO1aXX3658+51/PHHi/24446r0/34447TCccdp5+ccJyOPT55nLx2vJr85CT1PPX3mnp2S80+p60mn3GP7jnxvDqtX13jYeXV7fvXkPDm94unvp/97Gc66aSTdOuttzpBFw6Hd9Ab2C1DoOYI8BGFXPEfU8zVw8QUYs9AHVYPEPxDDjnEhRzX9X7IwYfoW4ccrm8fergOOvQgHfKdvXXzyTn6/KWjFemRo0ifHPVpdZB+9oM99a3vHKCDD637OnpMIKB+B7t99tlHe+yxh/uA5Rwc/e7TWPj17QWWDC7xLkJIDzzwQMOvGr9B3jWmgDDYztIa7E2bNnWm5P437/uAmvcmlkOmIGBEagctwQuPuU8kEtHy5cuVm5uryZMna8qUKZo6dWqd79OmTNWkaVM1edpUcUwdpk2ZplkfTVDen/6h3HNbK/eM5prTrL3mvDigzutXH5hYmXX/HjYUzPkdT58+XZs2bRIkit+7bYZAbSLgZYoPWc8Mr7DM0/Mfr3vttZcjBJACrtX1vs/e+2jfvfbVvoQH7KN9Ds5xRGrRCz9Q8K0cxfrtoT6tDtSJ38vRfgfkaK999qzzOoIJGhNCcOKjnzD9GBz9/brGMJvK87j5OoNb+p6OIXF9PAu3/m1CmngnPZ4cQ6gYKEHG8C3J797vtdnPWN51i4ARqR3gzQuP+QU7mqlgMKiKigq3c17Xe7CiUuXBSgWCleLYlR+oUGxjiRbe86Lz2jfzrFZuHamidyfXef3qGg8rr+7fwYaEOb9lftPsXsjtoDuwW4ZAjRFAlqCRYnAO8k64ceNG5eXlafz48VvtEyZMUL3s4ydowriJmjhugsZMGKPPJo3U2k+6anPvUxTtmaPKHjlaM+RKzRo7SBMmjNa48WPrpZ7g5fHxxx5Drqcf+3gWbv+dGjdunMMrHbftXTP8to8fuIAXO8cTJ050OwPvK1eudDLGEyj6AI5tazgIGJHaQVt6oedDXn4/cu1/FHUV+nWjWEPqf9yfF4W06N6XlHd+O0GkFl76oAIj86pGPuqqjlbOV6NNhkVmY+E/ZmknSBQ7v3PbDIHaRMD3C7xr7JB4L1+8yR/n28bz8essZH3CeEKRREQV0QJpzQCVDjpTiT57KNwrR+Wf/VEqWapYrFzxRMw9Q53VLYVdOl7+GNx8PWhHj2P6dX/fwuQ76DECD3Ak9Nf8efo1wy2J27Y4eMx8mH6f70bO09/T2uxnLO+6RcCI1A7w5gfBBxYvP2F9kSjqkU6k0hfkRdipKKilrV517s9nNGnpiFT5iOlVnaH/YVuY2R/31j512z5e0HkSxblthkBtIsBv3L93/ve+7QdW+nWO63xLSLEYi73HFU1EFVZJFZGK9cxRhHWkxvxJKlumeCzghvbqvI7bIUket21Dj3d91DEbygSfdMx8nbnmP/zTCZW/b+HWCHgMPZ7+rscuPSSubQ0HASNSO2lL/+Pw4U6i1+5tBJzk1uCtWgWR32NRSEta/NsRqVlnt9aCSx5UxagZtVsXy90QaAAI+N+1CbYG0Jj2CLsHAcbt4kltTlQxRVQqrX9bZW83STqb6JWjABqp0qVSvMJLpN1TtuWSkQhY/7jrzeKx8+Gu52QpMxUBI1KZ2jLbq9fXEanikBY3fzlFpNo4jZQRqe0BaNcMAUPAEDAEdoQAY3PeCCKquMIqkzYOThKp7jmKQKQ+TZr2KWZEakdY2j1DwBBo+AgYkcqmNv46IlW0LZHqpIoPTCOVTU1rdTUEDAFDIBMQgEhhMQ6ZSidS5W83UdSIVCY0kdXBEDAEMggBI1IZ1Bg7rcrXEqmgFjd/qUojteiyTqr8YOZOs7MIhoAhYAgYAoZAOgKeSDFjcFsiFeue4zz3BT75g1S8VKaRSkfOjg0BQ6AxImBEKptafQdEKum1r61mnd1Giy/vbEQqm9rV6moIGAKGQIYg8LVE6p0mivUwIpUhzWTVMAQMgQxBwIhUhjTEN6oGHmnTp/Y6Y3acTQS16N4XNf38tpp5dmstSiNSPgqh21IH/rq/bKEhYAgYAoaAIYBswLQvrriSzibKk3OkUkQq0jNHgdF/lIqXSNFyKRFL2gEytyq1OxS//sRANgQMAUOgwSBgRCqbmhK79RSRco6ao872QioOa8FdLyj3gnaacm4rLbiisyo/nOXiBiWxE9W5/OMgnjwPpy5VeQDMJiysroaAIWAIGAI7RSChhGKKi2UzkB/uH+5f/e6ECf/cwhqpCBElFFRUEcUSlVLhu9oy7DcK9sxRee/vqOyTO6WCPClSKEXKpXClY19hlyqueHKClRRJsTInhcLJsndaY4tgCBgChkD2IGBEKnvaygkhBCHyzxEj/nFSEtbiv76gvPPbamqKSAVTRCqkpCxzwhOhRpqEVKnkTnJ/LZugsLoaAoaAIWAI7ByB9MG3KiLlTRvcBQhU2Dk6h3BBueKqdNYPbrmbWEAqGKWCYU0U6pWjst77qmT0HVLBAilaIUUjUiSmaDw5aBdCKCWiSbkSRdxA5MgvlDSpcGXuvN4WwxAwBAyBbEDAiFQ2tJKvY0ojBRdCm1Rl51cc0ud/fl6zzm2r6We30uIruij8wSxHmNxgo49bpYKScFqLpsrJNAiWCTePsoWGgCFgCDQoBL7q3jlKDsUlFHHkJqqgIm6POOcSEXdWoRhRETaRMin/M5UMOV+xXjkK9s9R2Se/lwq+dOQpwtzdhCdRSZNARSuTaVPkKui0W0akGtRLZQ9jCBgCDgEjUln2IiDb4D1olBz54UJJSMvueF5zz26rWWe11pIrukgjZokBQG4Tt2q1D2RommZqq4HJLMPCqmsIGAKGgCHwDRBAELgdAYCdQoXiqlBYIaFB4oo3cEA8BJTUMDlZEQpLm8YoMPg8qXuOwn1zVPrxzdKWBQonYm5AjkG5QFwKI1BYzRciFUu4sb4yl19YYTKjeOphmyFgCBgCDQQBI1JZ0pBeDlJdLwq55jROpSEtveM5zT2rTZJI/fYhxUfNdpKR+wg5iBQC0gkxMnACL/nwJtey5CWwahoChoAhsEsI0OFjckfnj2kC9CniCFSVoQK3nGyIKKaw0zbBiRQJSfmjVTH4XKlbjkK99lPph7dIBZOlyNLkHl2tRDyquEuPigrtE0aCUrkSjrLhuMLMyHep8SyRIWAIZDACRqQyuHHSqwbZQSh5AoR8gxQ5uVUW0pI7ntOcs9po5lmtteiqh1T58WwX1VlmpEgURMrF/yqbJLFKI1XpZdqxIWAIGAKGQLYjwCyl1GxZ52GPDh+PfElKFXNkKTXiFsiXKldLkQ2KxzHyk6KJgLTlAwUgUm/kKNDjMAU+ulnKf1fK7yGt/Le0YZAUXCVFg0kZFY840oZOKk9k2wMAACAASURBVKSo0Ec5mUWG7iDbMbX6GwKGgCGQRMCIVJa8CcieMDN/QyljdNRMlXHFonFFy4Na8Odnk3OkzmmteVd1UdHHMxRIRJ3pRSQec/6YQgnGGZlWnDYwmK7qyhIsrJqGgCFgCBgC3wwByExMFame/yvTOsef3D9IVFgqWiIt66nE3GelNQOlUL4qEiGVaosjUqVDLlLsDZxNHKDAyMukRc+q+L3TtHnACdr0TjNp2VApsFFRRFQirqRhH8wJYRVOEij4nBGpb9ZwFssQMASyAgEjUlnRTMl1PWLM6N1cKS0rkBbnSxsrHZmKlAU158/PKPec1so9t43mXf2QAqNnKRKOSKGoFIw54/V4iFHClCFfikB5TVfqapagYdU0BAwBQ8AQ+CYIQGiizmsepn1fERn880WQB5FKqWK5tOi/Wv/uucofcoqKhl8jFYxWPLZB5YkyqeATlbx/qSLdcxTou4/KBp+k0MjLVdnrEFV231+BASerdNILUmBtagYWWrB40ntfHLfn0aQ5BKN4RqS+SbNZHEPAEMgSBIxIZUlDIXxiFWEFxi/U+PYvamLLFxT/dIFUGFaiNKRZf35auRe0dYvyzr2ysypHzpDKw0nitapYWl0ibSqTKiJJQZZGpBgzNCKVLS+C1dMQMAQMgW+OAJQmqlCSv0BiHJHBSiHprU/RLVJprgrH3K38wd9V6YC9Fej7I4XyWknB6YpFglLRGBWOvESh3jmq7LWnyvt+W0U9vyO9maNE9wNU1veXis/tJlVucPqncmf7EHPzpJJeLFJ26NiWm7D55o1nMQ0BQyDjETAilfFNlKpgNK7ElnKNuudJfXx5W+Ve3kEz73lBmrdOKg4p749PaNr5bRyRWvDbLop/OEcqDCr23nTNa/5PfXp9Ry15vr+0aovLMOCdT3Bmwi1b3gKrpyFgCBgC1UIguY5TarHd1CRZDLwjKlcFbogSpVLZXJVNbK/Ng76vij45Cr+xr8rfO1Fa+qxUXiBtGaHNoy5QqH+Oom/sp2j3vRXsnaNEt71U3utYVYy+UyqeI0XLnEYqpJSEoTwmY1VpoTgwJlWtBrTIhoAhkNEIGJHK6OZJqxyLdWwo1We3P6pp57bW/NNaKveqB7VpwBhpQ5lm3fGUpp3XRjPObaNFV3RRov8kbR4yXrP/+pSmX9xOUy5opdG3dFI0Fy9LXzmdMJGWhrEdGgKGgCHQ4BBIUinHX1JEChcQQVUK1+QRiE5ZgfT5YJUMuUiVvY6Q3tpXoT77q2LEpdLy4VJ+P+V/cIkCvfaV/nug9Maebk2pit77qfSDq6Q170qhIsVizMPFaLBISgSdoMG/BUVExbwpSuTMNkPAEDAEGgYCRqTqqR0hMFWDdKmFdqtITdqgXZWyiBm8JVFNb/FPzWnWXl+c2kq5TVtqQYf/SpOXae5tT2o6jibObadlF3XS6pavasLtj2jquS01p2lLzTi/jcb84WHFpi9zRIoi0oqpJxSsWEPAEDAEDIHaRyCR7PCriBSe9OJJIsW1UFwqWSXNeUlFA5oq8ta+Uo8cBXv/QOGRf5JWP67CEWepuNv+0puHSK/vrXCPvVU0+GhFFj4hhdfg3s+5TI85yVIsJZIL8OIVEPNxlv+Nq9QZGtb+81oJhoAhYAjUDQJGpOoG5/8pBRKDLyO3xZMyrmqczq+O6NbgSAoh5gQnQjGVvD9N0258WHNPb6nZpzXXoss6KdblbS2+9hHNPruNFp/RWl/8upUWndVWeU2ba8npLTX/zJaaflVHre0+Son8ElduScr1rRul3HaSFIzu63ZfZwsNAUPAEDAEsgIBN0iH0HEjc9Fk/47c4TDBvNlyKRSUAisUmPe0igYdrkTvHDcHSm8cqcS7P1Zg8JEq6bWP9Ob+SryxnwK9j1Bg3E1S0dj0YcEUHlXDgtvg83XXt4lmp4aAIWAIZAkCRqTqqaEQJ/AXN3iXIjJVGiIYFQLPkx1uIPBYNn5FsZY/2U8TL2qrWee01ayz22juxR0089KOmnZea+Wd1UrzmrbW/NNbaM7pzTX9/NaafHMXFfT8WMLpREWSrvGfbN2WOthKxHHydbtPZ6EhYAgYAoZAhiNAR87oXMr0AT0UXvRSRCoWjyqRiDkFkvPgVzxFm6ffreIBx0rdDpb+s7fCAw5VQf+9VTggR5EeOQr3OFgFfc6Qlr0rBTdl+PNb9QwBQ8AQqD0EjEjVHrY7zBnRVkWkUqwGPuP4EzdTRMfRHv5FpCiuzEujik1Yotx7nteEC1pr1jltNOOMFso7r42mntfa7Zj8QaIWnNdOk2/rqvUDPpU2lEhBbCwSSRN1CkuVQ+BPOU5d3rr+/oYPt75rZ4aAIWAIGAIZiQCddmrpC9e5M08Jl+RSnPlLibDw4RdBxkRjikU2KFw2QQUf36ZQ/+Okbnu7uVFFffZQUd8chXrmqLLfUar4+K9SMYvwpkb9MvLZrVKGgCFgCNQuAkakahffr80d4lLlOc8JtyS/YZkNxBIhY4jO/I/70YQisbhi4ZhUUKmCEdM05roHNL1pS31+ehtn5pfXtKWmNm2hvKatNOusVpp9dScVvj1O8c0lbhUR5wCXtahgcJCz1AAl5aXv6aRqqwegHn7f6oadGAKGgCFgCGQsAnTqvpP3w2aJuOKJkKIqVcTtOIoIur9QIi5tGa7QmOsU6HeAynvsr2D3/RXttrdi3XNUPuhn0tIXpdgmt9xvxj63VcwQMAQMgVpGwIhULQP8ddkj1ypSZAn5xjm72zhIzQ2GUMF5iBOOxVURiyoeikkby7Wl28fKvaaz5p3eUktObaklp2HS11Lzm7bR9OsfUln/sdK6UiXCUVUorvJ4alQylT9leV7ky0+vS1q0ZL18ZELbDAFDwBAwBLICgfSuOyFcoadYVSKihIKKxkLOUQQ+J2IIHEbwAvnSpg9UMOYWlQ88QYnueyTnTPXKUcnQU6R1gxWLlLl0WQGCVdIQMAQMgVpAwIhULYD6TbPEGSziLJryY+T4CewFQZZiT1zjEHGHGQZaKmcSyHyp5UVa+fRA5V3xgBY0baOFp7dyJGrGeW315QtvS+uKpGDMuaStiEdUiflGIq6E81zBJGO39ryrA+VQH4pPitmkuN2KTKVL42/6kDuJ5+oCoUskvnaPx1N1/pq8ts2DaNte8/n7LL7ufNvrPv72wvQytne/ptd8/tvm83XXt41n54aAIWAIJIfL8JmHAV/CyRJckXMuBtcQLMmOX1EveyojKbOIQkU2vqst71+lcJ/vSt1yFO6/l8o/uUHaPFmxaBBjiUa7eXnhQ4BIP840YDK5bpmGldXHEPimCBiR+qZI7e54CK7K5JwliEIoEVMMgsN15jGFElIwIYWTBCMaZ6gwuVA8RApNFYwqPn+t5j/cTVOvfECTz2uliRe01pw7n1NZ3lKnhYqRLk6+SQGKy9uIM4wnP0RpQpUQOohMirDEEnFFE3GF4wjeZJWqZKUnU7sBDzp11h1JD8GCa5FIxIUcR6NRtxNvextp/E787R37a+SVfuzLCofDrkx/z5dFyM719GvpdfL3/P3t1bG613yZ/nn8+fbC6uZt8Q0BQ6AxIYBQCSieCCiiiBM7yI9wLCZhwpcczUuG/jhc6EgVIiia2KjYsrdU/sENKu37MxUPa6b4wv9IgbWKueE5EjWObdv+l76fPtrvXn5wTtz62CjXl51+TF0493X2cqs+6mhlGgINCQEjUvXVmlVEKq6wEipRRBVKKKCom88E2YmHI1Io4jRWTlQ56Qf5wBhDqkRbxcjhygKVj8jT0n+9o3XdP5RmrlSkrDK1Ykey46TTZI5UKMqM4niSqEUTCsWiKlDEERV3nXvxhCBg3gCEqlaJhN1IpIDed+aemECguLbtdS8YttdcPq0nHV6IeaFBGAqFBFnyeROWlZVp+PDheuSRR/TWW29p/fr1Lh73vGCkPuzkwe7L8Ofc8+VzbXdt/hl86PHYtnzK5J5thoAhYAhsFwHcm4c3SqH1UqxEkZiEQUPEdewJiXmzMcy+8eaH7UNEQZU7eRR0q01tkSJfSKWzpS3Tpc3zpdJNwjtF2EksN6y33aIb4kUvH3zf62UB15Ez6ffr4/kpn31beYSc8vLE15lz2wwBQ6BmCBiRqhl+u56ab+5ossMLxaMKh0KKVoYUDCLCYgoouUJ8Ipoc84NspZv80f1BpCBUcWwrioJSfoWUXy5VxhSJx52myZkNpkgR2qgoHSfxK7ETTI6aBVCDQaCcdI05wYp2Kg5xSGmkauNT3XfmvuP3AogOH9LjO346ey8Atgc4+XCf+OmCjGvkyfWKigp3j/vE5zrE6corr9QPf/hDnXzyyRo8eLAjV544+Xql19On9fUhb+L5ONur365cIz9ff/9s/hrn/t7uLndX6mppDAFDIIMRiJVK60aoaEEPVWwcr0S0QhH6EKqMHOLAnUCkYs50vNDpmvDmV6lEoswN80VZUpdBG3hTyHEuJ4OcqXkGP/7urJqXCYTIqDVr1ujDDz/UtGnTtGXLlqpBN98/786yq5MXcsHLJdKln3uZ4cPq5GtxDQFD4H8RMCL1v5jUyRWICQ4gKlnPA7fmyzepdNJ8Vc7/UpHKoMqjYQXiSfO2SuJh0+6FXnLSlLPKgBMxbyoQjyW9/DkzQT7Ck6Z7iVjSTA/TwaT5IEORseRwJInDMSU4r4gk15jCkUU46oiV63xTMtYNXtYCMpThhQ4kh2PIJNqigoICR4AqKyvddeJubyMdcSBLXkNE6PPasGGDPvnkEy1atGgrrRRC8M4779T3vvc9/exnP9N7773nyvUCiDz9MSGkiXx9eYFAwB0jUCnr6+q3vTrv7Bp5+Z1yyZ9y0sviPvVit80QMAQMge0iEF6v4NR79fm7V2pNblcpusot9R5xzodSk3CRKVColDwpcmechx3JYtAOp+ks5M4qGtFocs5uMJrSbG234IZ3kT6Xvpg+Fznwn//8Rz/+8Y916aWXOjJFX53eb9cXAr6ehH7zcoRrXm7wLLYZAoZAzRAwIlUz/HY5Nd1XmdMyxaWVRfqi4+uadu2Dmn774yoeMU3aWCaVBhXLL1YiFFEwhue91NwohF5ZRNpcIZWEnUMJ7yrdGVngeon5V2VhRcsrHQFgzpPrXPHRFI860sVHucpD0uoC5c/9XCXL10oBCFXYEax4DPcTVfOQ3fFX3fIuP3pVQt+hc4GOnY4eAvXBBx/ojDPO0HHHHaf7779fy5Ytqxrpq0qcOiDdypUrdfvtt+uGG27QunXrHBGD8JSUlGjkyJFq0qSJvv/97+v666/X6tWrXV4IEAQhWqkVK1a4PCibdOwOqxQ54hhStWnTJi1dulTjx4/X22+/rX/961/673//qxEjRmjjxo2u/sTdHRv5gAdtRNk845IlS/Tll1+qvLzc3eMZiLe7ytwd9bY8DAFDIMMQCK1RZPR1Kni/meJLHpfCS6V4Ea6H3JRc988thVGiqKLJATsESrxSile4tXv53nbf3FXaK6RRocLxiNz83Qx75NqqDn2tl1UM+D3++OM64ogjdMEFF2jChAmOZCE/6Jvrk6SkywXqixwpLi5WaWlplZxKj1NbeFm+hkBjQMCIVD21Mp1YmPk1i9aqvMenyru4veZc1VlTr+uk5Z3ekt6doXWvDdfSFwaq6NNZUlGlypB4JUElZq9WUY9PlP/v4Srq/ok0folUWKHKCAQpkSRXc9aqsMdorfjPu9r08XQpvyyp+SoKqnz+lyqYsUShLSWqXLhK8x96U+/8vasmPP66NG6xVFIpHE7QATv2lLIA2T0U4SvAvVAiROhAZAYNGqQzzzxTBx98sPbZZx8npC655BKNGTPGEYivUiePSIcmCdJ1+OGHa8iQIY5AQTaGDh3qSBR5ce/mm292RMtrdRCEaLEQLmiXeF528iSEwEC8Pv74Y73wwgv661//6vL7yU9+oh/84AeOnEHQfvWrX7lyyS/9mciDc79T4/Rj/yzp1/wxoa8DZiM33XSTTj31VEcGX3zxRUeqIILESS/H52mhIWAINFwE0EF/ZSVAz5zcvzryz47Toi8VHXGRioZcIq3tLSXWKR4LJDMgWiqzmJAfGPB5m3HYFDN38eaaHFxK2nrTp2FsjpuiiqQzIwb3IFlVlfL1ITXHdbel96GUyjl9M4NmH330kZMx06dPd+QiPS79KH1qfn6+kwn0/2zIi8LCQs2dO1ebN292coG4XJ85c6a6du3qBtaIg+zwO3n78tPL8cfbu+cSpMkJyknf0tNyPb3v3/Ye52zIwkmTJqlVq1b697//vdVgoo+TXoYdGwKGQPUQMCJVPbx2X2zmR60v1tIXBin36gc1r9n9yu/UW+P+8Ijm3fiYVt78tOY2u18zzmmj6X97Vpq7RoFQWJq7Xsvu+6/mX9hBuWe30pxLO2rR7c9ow+DxCm8pUyAcUWzFZq16tK8WXthBM89ooWm/f1T5gyckTffmbdD8Lm8pr/k/VT5jmeb9Z7DmnNtOE6/vpPHXdFDZ/T2V2FisoHOOm1qxt5bkIJ04goAdQjNjxgydcsopOuSQQxyJ2muvvcTO+Y033qgvvvjif/BHawPROeaYY3TggQfqnnvucYICoXfaaae5a6S/4oorHBlDoFIe6RAwjCK+/PLLmj9/flVduIdA5dq9996rn//859p///2177776oADDqjKE3LGDonr06ePE9b+mciDcjzZ4bonaBz7nWv+mJA0jGgSco9RRITfUUcd5bCgDkceeaQjhQsWLHBC3acjDbvP73/AsguGgCHQIBCAt7CnPtVhC27nPMWLks/J9YoVig4/V8Xv/E7a8JnKVJKcEgVjSqBqSpIgTMdDbm4uzidITgQM0EOKqNjRLPKGcLkkrvBQMi6cC3MIKuW+/ZOLe3y1iEaqsrUkS3yj0vf5PtX3wRCezz//XG3atHF9OYNgF154YZUZN/fpNwlXrVql++67T08++aQjTeQFefrnP//p0jz00EOOVPn+mTIgXOxetpDG36f/R84wSOg1QpwTNz2ePyYdm+/D/Xn6NX/Pp6He/lmJz/30+BDItm3bOln1y1/+Up999lnVs5PONkPAEKgZAkakaobfrqdmbtIX+cpr97Imn99aSy7vIr36mSbf0lWsAzW1SQvNvaiDvrz+SU26uavKP5ipSEmFZrV/VeNu6KwZ7f6tyn4TtOSxXvr0D1017qYuyh8+VSqq0No3RmnSbztowXntlde0peaxxtRdL6iyIqjA+9M15ZauWtTiZUWG5GraXc9o7aUPS70na8ZdT2v2NZ2lFfnuYz6Km/T0LSUEd5csRBCw05lDktC6QHq+/e1viw4fjRRECvLyox/9yNmgp1eHYwQH5m6YAhLv+OOPd6SGuU+HHnqoDjvsMGe/jnkgZM2XRzrmSF199dXO2cQf//hHlxfX0U5B6k4//XRXn/3220/f+ta33Dyqyy67TO3bt9err77qnFMw0XjKlCkqKipygtiTIPLxuzf14BwhR0g9/DFCGAy8gCTkPvXFnI9nQqvG8+EYg2eiPpBLTA19vj4/n8+2WNm5IWAINAwEYm6gK/nR7dhUkuF8xaI45xsZLlS2VsFRp6l4aDNp42BFtT7pLSKGIV+pc4nuenrXsRdKidJkWudPttIZAOKfz90mP/LFc7rjW6WKqiylywo7fRZ+ZqFa1DFpHO6YQTJBqsq11Qq+D6T/pN+FZGAWfdddd7l+0w+G/frXv96KEJEOeXDbbbc5wsGcWczCSd+9e3c3D4o++LzzznOyyvff9NHMve3Zs6fmzJnj4vt+H8I0a9YsR8IwOz///PPdgN5f/vIX9e3b1zmngGj5/po8kQPs5OFD7rP5+75srhOHc+Kn5+XzJN3y5cvdwBvy8Oyzz3ayLT1ubbWF5WsINBYEjEjVV0uHoorOX62ZLf6l6c3aaeUfnpN6TlHeH57Q3CatNeuSDlp718va3OJ15f7+MZX3Ha+yCQs1/YaHNfvu51UxfZm0plhasF5Lnh+oSZe118oXBis67QvNu/5RzbnpMS25+0XlNmunuae31OxbHtOG9ZtU0G+s8m55VKvuf0urOnbTxBsfUlnXQVLuGq18qp+mXNRGRR/nSSUVzrwPAeu6cf4hBFNLXe0O2Ojs6dAhLmhdIAlola677jr16NGjSguE8EPzg/Zo2408IDGPPvqoDjroICcsMYE79thjHfFo2rSp00R5EuWFHMKH0UfmT5EOAYPQ5PratWvVvHlzfec733HlXnzxxXrqqaecwwoIH/OhKJNRRnZGFxFopCd/T6Z4NoQpI5p4dML0gxDnF8zL4nkw22Ok0gtHLxTJj3ho2CCX2OFjWjhw4EBh6giRApPHHnvM5e+fywtQH26Ll50bAoZA9iOQ9KcKm0l10D50i1aw0EVQCaciYqmLL1X+4ekqfPcCacNgxRMlSS0SH+3KT7kwTxEkSBJaCkd4kjQoKQNw05ciZlxIESLoUlghBRV0eivnGTbJs5JRfL1Yr8rVx/mZrbUGoN+j7/T9MfNk0S793//9n/bcc0/tvffeboAOCwbmvBKPPpcdQvSLX/zCxTnrrLOq+mdMzelrjz76aL3++uuu7ycdZSFDIEbImw4dOlTdQz5gKUFfjfk3fThEDFnz3e9+1xGyefPmbbffpy/3ciA99LKSvJFRWCQgj7hOfZA7hKT3/T/h4sWL3YAhZWOZwaAiafxz11pjWMaGQCNBwIhUfTV0MKronJWa+ffnlXdRe61u+7o0YLqm/v5RzT+9laZf3VnRlz7Upk69NOmWrgq/NlqFr47U7Cs768sn+ileXCmVhpyjioXP9de0Kx/QxicGatULg/XFOfcrv2s/Bd7L1aSL2invrFaacusj2rRqnUoHTdTUGx/Wl61f05IbHtfUm7uqaOR0aV2Zyt+ZqNxL7tPCF/pLm0qdq3QGIJ3MRCCmWFVKhtYYOTpySAhmF5dffrkjTggk5jkh1BhBg0ShmYLUbI9IUQkEx6effupcmKM9Ij47ZOOZZ55xZMYLzHQhhRD8zW9+48gbwhLNEPcZRUSQIngYmezVq5ebW4UAI44nXD4vnsMLMI6JA4FCW+SdUlCP5557Tv/4xz/UunVrXXPNNc708Le//a0ztfB5eQHIOfPCMHVEE4WbdgQnAnDcuHFuhBRsTjjhBI0aNapKKJKetOy2GQKGQANFAGKCpiJFVHz3zCwn1nYKqlSVCqgSI+34MpV8dLa2DLtY2vhe0mkEHXuYVBsUU2myj8c0r6rDx6QvWUTyplu1MCUMiBRImv2lVuXAbQUczPU6/ENW+N1lxIn3/UfM2tno/+iL2Rk8mzhxopjTijzwRAoyhadWNFDE80QEzQ1yACsItEfImxYtWri4WElgGsj8KZ8/ZWGNQBoGALGC4D4ybeHChc4UkL4bOYIsgkBRLgOGWF9gbYC8YKe/Tq87daL+eK4lT6wukEvM8cIa4s9//rPLn3yQY54Y+UE88mInXwgbhI56XHXVVS6+H/QzOVE776Hl2rgQMCJVX+0djCow8wtNv/tZTbvsfi17rI80cq4m3fGE5p3ZWnl/fVoaMUdLH+6h8bc/qujLH2pLpz4ae0Mnrfjv+ypfslaa/IWK/vme5lz7sGbf9qTKXnhfs1u+pBk3PaLKkTOlz/M164oHNe38tvr0li4KrdosDZ+lvBu7au5VXbTkzDZa+KdntOXzVUpUhFTyYZ6mX9ZeM+972RE0HE5g+o4IdAIb+efN53cDbnT0aKNeeeUVN2qHsGnZsqUbbcP7HuYXzE1CCGLaN3Xq1O2WimBD4OAQgpHDPfbYw43+nXvuuU74eKGxrZBBK4RJIGVAnHw8b2YIkYOYMScJM7p+/fq5/NBCeWGKEOQ5fEgZEC7c4p500kmOADIaiTmeH5X0ZnoIWYQ8+SLQSOsFKyEeAdFEQZiefvpphxXlMsrKnCw/wvn73//eETfyYPd1oV62GQKGQANEwBEo98+Zz6VzFo7pqlPLPSkR3qTykZdq87DLpM3DVA4cRHIuXjHlCzjGRJqAyhXQZoVUpHC6OR/LaTg9F2sXYriHM3ScpKdkgy8UjuVIWiok0yp2xWK/tauRojr0gfSTzA1i0Iq+12uiPKGC1GAd4PtKQiwNmBOLPOA+zhkIOccrH+Ro27lNEJuf/vSnTk5AupAN9OPDhg1zfTvyA2+xkydPdhow5BoEDnnl5Y2vgyc+1B/rBTRaWCGQPzII+cizsEOKkB/IxbFjx1bVKz0PjtkhUs2aNXNk79prr3WWDpTty082ov03BAyBXUXAiNSuIlfTdMGIAtOXavpfnnJEavnLQ6XRCzX+T49pzpmttLjzW9Kk5Vrw4Bsaf/tjCv77Qy1/oJs+u/J+Tb/9Sc1r96rm3vGMZl3fVXNufUIb+32mYI8xmnvL41rc4t/SnDXS+nJtbt9Dsy66X5NvflhaXyqNmqvcGx9W3nlttaRJWy2992UFi8oVikYVmLJI8294RNP/+g9p8aaUkUjKXB6ZvZuJFAIEYQbhQThgbsEIHyNxmMPdfffdjhgx2sd8pdmzZ/8PUfDkgTQQIPJgRBEBdtFFFzmzBoQJZfm4PmSUD42PJ1JcJx5EBRfs2LUzgkj51A/zEEYqmSOFkKOOjAR6geXzZQTxT3/6k4sPsSMdo5CYhiD4TjzxRGFySBxGF7Hh9/UjL/LhQ+Dhhx92AhMyhTdDTwQJeVZGGSFTeA1kTpfXqJHW16mmr6mlNwQMgQxEIMmh3Cyk5NLtsCIWeEoRJK9dguAEVyg68kIVDL1A2jhAxVwifZxIhUrEyt2ahCioShVTuZs1hZuJoJj15PKMRB2NKlOF0yu5ZXsTAcWYR4t2jDWpYn4nDcepe6kBnVSVaxVM33/Sh+KpDosDCAcOg+h36euRD/TrkBnikYb+FxkCKcH6gX6VfhcCTOaPdgAAIABJREFUhmnea6+9VtW/ppcBYaJ/R9506tSpSjP0zjvvOCdEXGeQDk+reApE3tFPU57Ph2N/zjX6bywsMDtH7lAXdogUhIr6MEgHKXriiSccQYMUpefhn4v8cLzE3C5wwGwek0ZkCPfYbTMEDIGaIWBEqmb47XrqyogCExdp9h1PK+/S+7Wy+wfSp4scaZrdpJXWvvSuNH2Vltz/X03+0xOqfH205nTtpmlXPqgZF7TTvN92Vt51D+nztq9JHy5w7s3zu32kWZd21Bf/6CetLZEKKqXXPtXsi+7X3BsfVfn4hdJHizT1hoecx79Z57XTykf7KB6OOYv6illfaMkfn9LM25+QZq7C4W2taqQY3UPYMeqHtgb35MwXQghAZpjkC/Fg9I15St60DYFBHHYvPMgLW3A8MiEo0eKg7enWrZsTkD5NugBBI4VAQrgiaHx+CDIEEyaH2MRjukEdMe/wgg3ywrwphBKC0QsliBV17927txuJxMsTpooQL0zyMNeDLOIRkNFJhDflkp6Q+lFXngdPS4yg8hw4tSCOfw4EMmuYIFghaJgf+jVCfJxdfzktpSFgCGQ0AinLPuhNRJWKuVUGQ0nSgwUdyzwF8chXIQXnSSPOUenQs6X1vdyiuuXO916pKlQiHEmEI0nuE2G9dvhVAEM8Zj6FkxqlWFiheInz+AdXc4u2VxQqHo0pEosoHKlQNM6y8UFFYmWKJspT87SQIrGkBWLSsWCtw0o/Sj+M/MCqABLCPCYGxpAzyAa8oDIQRp/qB57oNxlcw+wamYMpIDsaf5bB4L7v53kIymHOKnIBwkR/zDVkB6bpyBTuUSb9NF5kMfEmL0y/iefLJ53PmxBnFKSBzGGZgTMk1lRE5mAuztxaTBHRgPn+nnT+OD0/nGCcc845Ts797ne/qzJPrPWGsAIMgUaCgBGp+mroiohiE5Zowe//oYWXdVL+wLHSuGUad+vDmtmkpcLvTJVmbdCqv/9bU299RBowVcv++56bC7Wm5WvSJwsVWZEvlYWUKAspml+qFc8N0vhL79P8UeNVEChXZVG51j3UR7mXtNfUC9tpactXpDfGa8b1D2vqua015qoOWtv/U7caCCuChOat1Od3Pq+Ztz0mTVnqyFWVyTwDV4xufhXUGDnMFx555BEn7CADAwYMqCIlECpczjJyiOBjlLB///7OvA0hgfBDaPiQ0UXiEw8i5ckUWimv5fICk4ojdCBSzDFipA6i5gUZ+UNoIEiYHlIXbO0ZccQpBWUgONE2sRAwmjJfD0J2CBJCjtDnwzECnh0hShmU5QW0F36cQ4rQyPHseDCEhHlBSYgghqDheh1hy4Rqb6ri86lxA1kGhoAhkJkI0BfH6ZIxlvPOHkKKxCNJj+bRuMIKqkJlikRnSyPOV/Cd86R1fVUZxaqvQmFtcdopjPTclMpwTCoukraslUpWSLGAwn6+U5h1p4KKIAewzitdK20Yo3hZifNNgQk4/I2ZU+yYD8LluJ4yZEiah7v5UrUHKX0j/S99IaZ29NM//vGP3YAalgSQGsgRFgJ+0C69/+UaZtnII7RRkDAGweiz0+PRx7LhrQ+LBWQI5te+/0duIBcgQAyEeVM8yse6YvDgwc58j/r6/prQp0c2ocViIA/ihSyhz2dHnjDQ9nXygzzZ2QjTiRRmhhBI/yw+nots/wwBQ2CXEDAitUuw7YZEFRFVjl+oeX/4h9MiFY6aLo1ZpPF/eVKTL2yr6Oj50qx1WnvHvzTlj49LH81XYPwC5d76qDPli/ebJC3cJC0v0JbPZiv3ye6a/fsnNPPi+7Xhg1xF1xWpbNoSzb6+q2be8phm3vaE5l3cUetvfc65VZ/ZtJXG3vqwKiYtdnOOI4m4YvNXaeE9/9T0Pz6myKRFbinGFHeqmtTMk1ddqyEM2Ioz9whhxVwlJtMiJBAQeCVirQ9GFNHKINQwdcDkDqGGwCEeIQKIibu4MofcYFOOdyKEF6QHEzo0R5AXLwAJGX30RAozOS+AEDLkS+iFGwKMPHJzc/X888+7UULqDdH729/+5ibw+vpsO9LohRZ5+fwI08uh7PT7EENGUfkQQPBCBn39iIfW691333X15xnxWoiA9Pn7uDVsIktuCBgCmYgAH/JxFspNkhW4DYNe0UiFFA04EhRLBJx5XiT0hRIfXa3ydy6UVveQIqWKV85T6YaPFSwplCoLpPK5iq98WUVT71bBxDtVueBpKZAnBVZKBauk4pVSZcBZ7MGYEis/1PrPblNg7utSyQKpcrMULFYiUqFINOxMB9OXlnKf9fxjsarkN36toEq/Rz8MEcGkDmsD7/IbT7DIB+TJySef7Oay0l/6vpeQeVIssMvgFH0v6bEuoL/1farvp3mAN954w+WHrGGOrpcx1IE0eMh7//331aVLF2fOTV9NHTApR+tEP+/lAPlyTFoG3SB1DKhBmvw9X1dfB+Jz7OvGuT+mfhxj2retRmrbeLXSGJapIdBIEDAiVV8NzRyp3M+V9+enlHt1J20aM0vKXaFRdz3m1oSKzFghzd+glbc8rXF/fVLKWynlV2rJM/01/paHNfbqjlr+cE/NbP+qPr69qybe9qimNWunhRd11Jb/jJI+mKdJzZ/T9Ms7at1zg6XRizX/909qZrP79PnFD2rO2W01o/0r0ooCRaNuaFOJuas0594XNO1Pjys0ZbEwzqgSgCmcnCzcTZgxCZYOntE8CBVzhRAaCBCEF6N3CCjMIxj1QwBhHgGZQZsFofIChUm/aGfIi1FA4mASQR4IL++2FsHCRkh52M6Thsm4XiD5PImDwPFChxCChTOJESNGOJM/hC028jiMYBQSIUg86sZzEJe6snPMzmgprs29WSBpyJfyKJv0CPQ//OEPrm7Mp8rLy6uqN3HID5fxEDls5hm9pDxfd5/fbmoqy8YQMAQyCYFE2C2mC5GCQLnBrURECq2UymdImz5WYsOnUslcqWSKwh//VoWDL5FW9ZLCWxRa2V8rR7dQydSB0tqRiszspFUjT9K6kSdozcjTVDjtbmnD6wrkPaPi99tLua9KxQsUoqCwFF3aU/nDTlBo1CXSwkelRa9Jn/eXNoyXypdLkfIqx0QkSfW6UqJKP1VraEJmMKFGq4TcwESavh6tvjfDQ+5AdOgvfb9Lnw0Bw5QbWcPgHTtEjEG39D6VNOxor9BwIWfog7nm+3OfN/WhLAgN3vYw2YOgMYiHpQP9PXG97PB9OOe+HEKukxcy0u8QLn+P+pGXTwPAHFMu85CRc8yrQu5sG6/WGsMyNgQaAQJGpOqrkSMxhZZvdGRm2p+eVOHCldKXhVrR+0OtfnGoQis3K7xwrRZc94hGt35OWr5ZqogqvLFES956X/Nue1JTL2rnHFXMue1JbXp2sKLPvK8Fl3dW3mUdNef8+5zJIE4ponNWSaVBbVqwXCueGqC5v+uq6Vc+oM1DJ0kl4aQUjiQUm7lcuX9/RlP/8qRiM5arHPGHBExKQRcguJNGDTUHDveyjMxhvoa3JAgGwuCTTz5xDhQYOWQOEyQIt60INwQQafBaBxkhPgIQgUY+aLCwI2ckb+jQoVVECVJFeX7EEAGD21jmOvlRSy+QvCDzAin9nPI4R4CRH7b2CFFsz7nmhR3zn5hwjLtzJgQ/++yzTpPFMZ6k0J6hBUs3OyQtAo46kv6WW25xHwII8pkzZ7q8qRNx+DDAZTxEEzLIR4Iv3+dDXNsMAUOgISIQdf1xlC4apgI/CS2XvnhR5R9crKL+P1BZ/x8p9M5vpLHXqGjEcVo37BJp5RCpokLR+U+r4J1fSB9fJ42+UJVvn6jCwT+VpjwiLX1fWv+xNo69SesGfF/qc6CCA36swPwWKtC45IpRS3upctCx0ls5Us8cBfvsq+J+R2vLsMsVmvEPqThXiuYniZOXIa47QnrUXr9En0f/SX8LYcFqADnAwBPzipjripygz0SD7/tzQuK8/PLLjnBAwFiKAxNx5A4aJYgNfStl+BC54+PgOMiTH/LzxIj+mh05BYlhLhWkBlmF1QHxsMQgDbvPnzSUwzVfHgSKejNfGC+2zLX15ZDO78T3GwOWOEnimZj/hWwhbx/Xx7PQEDAEdg0BI1K7hlvNU8UTSlSEVbFwlcpmLHXHCkSkzeXS6kIpEFZ0U7GW9ByhhcPHSoWYayQUD0UV31Si4PSlKhkzR6Vj5yqS94W0ukRaukXF703RtKe6a3yXV7Ts9WGKzFohFQWVCEYUqwy7vMN5y1QxdYm0uUxidjF9Lvbx4xZp0TUPadLfn1J06XoFEHgIad8np2Tg7hKDeEhi/g8dPCN1dPh4K8IsD6cO7JisYQKIxyPICtoXiA/aJ5xT4EwCj3Vob9AOIfxwzIBwwXseiyR6t7EdO3asImsIGmzPGamDjGBaiEbJCy0EjT9OF2ZeuCGs0Rphf0968iE9cSFxkCgIn58wTIgQJ2RUFOHMOTb22L+Tjp38qTvCkvlXnjhClBCiftQUwU4e7EyiRhvlhTACks2HNX9ZLQdDwBDIJARYLwon5K5vpl8ObpbyR6lyVBOVDD5ZlR/fpOJx16vk3fMV6n2KKvv8UJuGXCCt7pM00VvwlAoGHyP1P0qBd47ShpFnKrr6TalgjlS0QJHFb2jz0NNUPOBoVbz9KwX6/VxF752iolk3KxbaoIqlb6l4yDEK9z5K8dGXKzKrvYqntNX6kedqy4gmUt4TUhnzrFLyI6WIYt4Ul2pro8+jj2Rgjr6RQS40MsgCiA7X0DJhujdy5Miqvpe+E60/Xv4YwGNh3rfeesuZAEJ4sITAMRKDVZ6EkIYlKiBSyCpIGOX7ftz36YRc94SJOUtYGUDy0Izhpt0P8JEn9af/xzMrZIm5sGi7cMfOulHIR9Kx8DzrCyI3qZcvOz3kGNLFXGGwYEAS7Rp18fFqqy0sX0OgsSBgRKoeW5rPXb9XVYMLmNpFYlIoqmBhqRKBYNJLUioyHSBrPLHTSbuZwqn4Kg8pvKFQ4Y2FihcHpGDU5QMJwz7dl5ceUnakMqjA8FwtubijJnd4SdF1BQogpVOCkPj+uKquNTxAwPmRMszjLr30UjdSCNFAeDF65kfc6PhZ4BYBiYtzhBA7xISJw6SHdECIEEDgQhrvAheShfaJeVgIKoQhAgUyhoCB9DDPCrICEULYIVjTRy3BnZ04jCDi1Q+SRnrIDPOoEISkZ/4SwpK6Qu4gXBwTck55lE2Z5OUFKfWmbpAySCAkjWdkfS3MQCCJECw0YTwvCwajwbPNEDAEGg8CrPEU867JISmBVdKs51Qy8EjFxvxOyh+veOUH0spXVNb3MoXf+j8VDGkibXhTqqxQdMGzKnj7aKnbnip85ycqn99BkegaKVwpFS9UcW4blQ45RZp8s7TsVWl6Z1UMO1Mlg49UeP2nii57UYXDjlV4ZDNpfW8p9IVU+oVCczto09snKD7iemnDdCczMD10siMhlbmFe500qbXGon/3nvcYrMJcDzIB6aA/9aZ4zG1lLi79LX03DnswA0dbhNaIvpklKBi8Ix9MBBk8o49nRxZgLQHxQl699NJLVSTLyeg0jRJl0LcjO5A7OH1AbiCvmEeFrPL5ojF64IEH3D1ctuOJFplI3Rl0pH7IPkghmjXkAvmSv68Xx37HgyDWC6RhAXjklteAUU/bDAFDoGYIGJGqGX41Su3JzFaZcBEixaRcFkGEIKE1Cke3Yl0MQjKDKZ6IK5GaeCzsPHCzhCE7rm8JuRaNKxFNTUrVdshUIqGyklJNerG3xl7aRpuHTpBKKuTWtod/pZYmcQe7ca4wphQ4boAoIIwY2SNEYDBnCSKDgEPIIIgQEowsMh8JgcCoImkQjIwykg7NFpom4pLGe/ND0BEfcoIGyOfVrl07JyQhOHgNhDhhAsJkZAgao5jk48kXxwgf6oH5CMKM+j/33HNOOHEfUgSZYjSRuVRMNmZUES0VBAvBhzBFmPln80LP50/IGiXHH3+8I0zgggAl9Md4g2ICNc9jmyFgCDQeBJxxAINcsBTc5eWvVeCzDip69xeKzn9FoaC03hkarJM+76eK/kerYNjPpY0vS+URJeb8W6UDfia9eZiCw26TNk1SLIq7dJaWylXZJxdr47tnKfrlaypzvtCLFZn5uIrfOULBeY9Ii+9XYOjJKvvkj1LhJCeyArjr2/S5St/7qwJ9TpFWvC/FQyrGJXqqaeIqUaLqrHbai371sssuc8SBASc0TxAiSBJmfcgL+lL6Vu7Rt+NKnDQMuDF3iQV0IScMymFtwHUIzfjx4911ZAB9Ni7WkTuQIpxN0G/7HTng+3euEZ9z5Jrv11no15uokyd1R74xMIhsQ64RslMGfT6m3mim2rRp4ywymH/liZSXI75+lMczEB+tGQOXeBP08amXbYaAIVAzBIxI1Qy/3Z8aIoXmCCLl9pTGyXs7Sg0gJYlUkkzF0GJEWQSRBRkTSeIF+XJOJMgnrjgdORqsNC1YKiv3DKFwWOsnzVZpr0+lNcWKV4YVgqilvEJhkuHVWenpagIAgoYRPtZAQqODqQJCi9FAzBUgI+mCCPKD0IMcMaqGg4nHHntMt956q/Ocd+eddzoB6MkXQoX4jPghuBBEECQED/lCQCA3jPohZP0IJfOWMDmEfOH5CSLEnCQEHiQNLdmDDz7ohBpaISYnI5y8VgnhRF3RKlEXdsrieQgRluxe4BIi+Hzoj3lOCBjeC1lPCyJIPdFsYd4xfPhwZ6pIXrYZAoZA40Eg6Wo8uT6Tmx9VtFhFE1opf9jPpMWvofpRkZs6VSoVTVV42DkqHHKatOKfUnlMWviaSgcdq0SPHGnCI1LxRsWiSV6mwrGqHHGayplTteZdRd26UhXS7GdVOuC7Ck1+XJr9hBIDz1Xwwxukog+kWLFUEZe+GKjCdy5S2ZBzpY3vKa5SFbtlg71NH47RUaHVzkbfSZ9PX461AIQJL65oldDmQJKwfPBzWxl4Y/1BTKzpV0lzzz33VGmqMJnDfI/0kClkDRoj5Adl4cYcbRV54+3PyyfM/JgHy2AYA4b07dxDy4UXWerFABxpPOEiP+QGlhfNmzd3WiRCBulY+gNTeEzc0a6hZUN2eq9/5E+dSJ8uRzinvn//+9/doB8yloE85BDykbJtMwQMgZohYESqZvjt9tSQFIhRnE6V0S1GsWJRR4Q8kaFQT6RYkDGaii/U9IwqhqOKhyOKpk+OTZkDosWijG3JEGXhkEJry6WK5KRa8ma8CqGN+Ntuwhog4EfoIBh09oycsSMcvHBBKCAMiIugIeQaIQQCIcUEXuzM0RJxDYHFfZ+G+UMIVjzcQZrQBpE/o3III9YbYfFEBBYaKeZkIcAQnozioa1ifhZ5MLKHOQXCE2KG1or1q/DGR55ekPl6+9DXx9eJZ/H79q55oQoJW7hwofNiiOkJc8YQztSR+lMecW0zBAyBxoMAS/CGkAKYbNNJV3yuTXkPat3wnys8ubWUv1KJSJESeM8LLFfsg2tU/E5Tae7jUkVYWtFbhUN+rkCfHGlxN6k86AbuQgorXjhaFcNOV2BoMxdPFeVS4XwlprZRcb/vSTO6S7NfUajfuSr5+Gppc3epZIy0epgqx/xR+YN+pfD4e6WKiW7B31KaBYGFWiqOt0FOamejL6X//+yzz5xpNWQFszgGoZj3hLMfiATaJ8gPWiYWur3jjjtcX0+fDzlCJtGvkh/ygoE+LAHQFOHoyBMpTK2RKQyooSEiHYNu1113ncsPc0IsHCA+aLkohzoRH20UZneUgZzwOzLMD9oh25At9PX+PiGblx+cexnJsb/u5QrpmWMFoWRQDjLm5/MSxzZDwBCoGQJGpGqGX81Sb/P9yylEJ8TIEnOg3NhdQuE4lGZrD3qeSPk4jE1CvjDzY6eDdKZ/rCufmk/l5lR9DZHinnM4EYgk41NeLFkHtFHOeMwXuk29dxUEOvx08uEFiqt7SiCmExN/fXuCg3te8HE//RyhwTwi5hYhNP1oHHGIi4aKkUJIC+UhiBkVhDShlfLmg+mmFpiIYGaBgMLOPr1uvnw/Qki9/DVfR8L06+n19fVKD4nrSVN6HuTLbpshYAg0HgTiEBJWx2WEK4xJ91qVrR+gFSN+oaJhJ0sTmkvrP5QChVJZoaIfXafSt8+Uch+UwqXSxuHaMKKZNr2zp7RmoNyquolyhdFjlY9R6ONrVTj0NMWmt5DWjVBo4UPaOOJ0FQ46RloxUVrQXUXvNdXnn1yo4My/KD7+NhW+9yttfvsoVX5ynrTmQyW0WiUKJGUHJMovdrWb5MfXtTb9I304Zngsoo42BtM+zKzRMNHPQ7TovyFHaIcgVGicuAbhgcz4/pm8MMnGGgACxPIaECb6YywR8L6KJgtvrHieZSCQxdTJG/nB/CTmw6INowx2LCOwqPDleFnh+3MvTyjDHxP6vt9f49zLBdJynr4TDxkLGWSgELNBBh9JQ3xC2wwBQ6BmCBiRqhl+NUu9jUBJEikGGBOORCVJEgN5SRO7dI2Qjwu3IR47x1xn99d86DmQj7Pdiqc6YZT9xCMT8vKr1ldl6m5uN4dqX6TTZ/OhzyBdGKQf+/vbS+PvpefFMQID8uS1VtsKHIQJuxdOHCN80I4NHDjQESqcOiAIGdW7+OKLnYt15kAhNBktpBwv6NLrkV4Xf/2bhNVJV52436Rsi2MIGAKZjUBYUffnlFJO2RNTPFKg+KIXFBh2mSp6naTA+2do82eXq3DaDSoe/n8qHnqS4nkdpPhmqfhzFef9R4Xjb1K4cJpTbLGQbwLaE1whLRyozUPOU/Gg41U+9NfKH3yiNr53phKzH5AK10pf/H97d+8rx1WHcfzvQKJIkzYUBoUXpSA0oFRRCkRpQUFLAS0dNUSy0gRBRBQjJ7kOsQkxUUhCAREgmUgGhGNbiRNybV/f932d3ZkHPWf2dz13fR1bN7NvJ98rrXd33ucz0jl+ds6c84w6a1/QrRce0s7pR7Xx/Ld0/ZUn1P/bT6X1N6XdDanspQGB97SbWql7/Kl0V6ou8mcK7LLYIcUtDHx3x60VXAc4FLlsdysF31ly6wLfrfKdGndkdOrUqYOQ5HLVdYVDjoPIyZMnUx3gO0/edtQrvuPkMf3cQZG37eXd+6w7FHJI8zNUDlT+8c0tGfyckoOc7xR5Wf+5zvH+4vUgOFHux/u91rGF9+NztkHUf17+fuvea5tMRwCBOwIEqTsW8/80VaH4awSeCED+vcivo7JLc/lYz9P88vpez+/T8zw//qY/ex3Xd2m6V25saxZBKo5jGd6jEot3V0C+W+Vmh75j5bGc3BTDz0m5gnal6QowKqaoDJfhXDgGBBDIV6Au0/2vO3KoUpmdCvrd/0iXfqnijz/U7fOP6/qrX9GH50/o47WHtP7yY9KlX2hYbUr9Qtq+Ie3+QeV4Pd0s0rgvjQup35M211W+93PtvfFdbZ1/XLffflK9Sx4f6u91y4Wrz6r74hfVP31Ceuuk9M+fSR+vSTtXpF5Rtwd3X0caqa/tVBfVLfqaNc78ro/LdJfTDhTx7nDl53P9TJR7d3XgcnnvsNWsA1yuu1WDy34/U+um1t6G6wfPcz0Q63m6p/muz4ULF1KTcPfe6mdt/WxW9AboO2Nezi//eT3vkz8EEFg9AYLUIq/ZVLnpr/FyFdkMU5NMc9fRxvLT716+GaQ8f/qvuY7n+bvX8Sst74NorljX3oenTW90Rb+7EnPFGO/xufk9GTWW8zxXhF7WLyrDFb34HDYCqyYQd3e0Xd/mcTntQr83kvql5KZnt/6s4sppDS8+rdHFn0jvPZ26JO+WfQ18I8RNDYpbGsk9tLr5QXHQ/MAtB931X7l7VYOdd9UvL2moTfkGSukK4v0X1DnzNRXnvi9tnPWEdFdr4BbidUex6ZHduv4oUqfnA421nzptb1Yq84GPcrxZZjtUufyOH8SizI8y3ctGmR5lvNfxy98jlHmZeMU2Yr6b+rlzIv8I56DmfXneUct7f/whgMDqCRCklvSauUiN3DKdZx7kkJvrHyzviY2yurlMY3JaJPad1o0FJ6s3lz3YdqYfXOFF5disYP3ZFV/z5eX4QwABBGYv4IejtjVUN/3wlSqLNFbgUEU1UmdcqBjclPbWpa3/STv/lvZvSvtDdStp4LDjsDTqaKye+upr6GZ9Dlip975tVU5MhV/7GumGetpWt5oMAvz+cype/LJG574tbf7Oc+pcpkID7aqrIt0pS8flwFb1U4zys7bOYYv4i3LcZXaU5Z7mu0NRdnue70j5e7wcmKKc97QIXp7m7zHP764vmt+9rp/Jio6Bppf392ZdsggX9okAAp9NgCD12fzmuvZdAcYT7vVqZqajlpnM93/9485XOplJavO0VP954mQhV4DxQ+hdxzJXidnsLCrA5tY9LSq/6feYF9OPWr+5LT4jgAAC7Qj0U4M+5570800q4/2sppvSlR75KfVFkZrqjbtS1a0Let+wUqmBY47vQPVLlUWZYlRHDk9OOmMNta5hNQlWPeergQYOS+NBPazG5efUW3tUO288Ke28k/bnHDcqHewc8Hr1cXl7PkgHsDSgRjtnf5ytRGhx2IkgFXeXoiz3u+fFy+vE3aP4US2mxfb87leU/83vsW5z2qcte5zzYh0EEFisAEFqsf6fvvdmAGoGo1irOf+oz17uqOmedicfpV8IU13nia7vPASVe9SNfU6SlkOUu0I/CFj1ZrL5NyrCo96jIox3LzNdsXoafwgggMDMBVwmu5BOt3dcMruJ365Kj6nrcdzLKo3N3lOhHd3Sfmq+V6qnSn11VKRRpvbrAn1Yj+O+7aZ7GqkqXRtsaqQtpQ5Bu2kowrrLo/FQ6pXS5d/o5tpXdeWtH6jauliHJbcH9AqpS/ZufWxu6heH6WN2z30p+c1c6NAOokxvBptmiGpOdxnv71HGN9cegkasAAAGbklEQVT15+b85mfP85+nNZeLeiIOKOb5PT7H/mIZ3hFAYHUECFKrc61mcqTNnJV2MMkCfjuo7yYL+Xu8ZnIwbBQBBBBA4P4Chwpuf3GiclI5/NuZh8AYq9B4MihuXX576mR5T5iMrOGOIdIog96c01hZyU83bcWAuikoOCxV0tVntffKI/ro9e9Jm3+pd5p+tYsDKA8OJA41zZ7s7/4nyBIIIIDAaggQpFbjOnGUCCCAAAIIzF4gBak6mzmCbWi/DlilY9ao/jXt2q/VOfuINn7/lLTx9uyPiT0ggAACSypAkFrSC8NhIYAAAgggMH8B36Iq0w0uD+vuQXVTevJNKh+Mb3xdO6Peyye0d+4J6caF+R8ie0QAAQSWRIAgtSQXgsNAAAEEEEBg0QIe/j2NTJVaClbqpSdj69763CAwPUL1wWsavPQNDc8+Vo8fteiDZv8IIIDAggQIUguCZ7cIIIAAAggsm4DvQhXuIsJBKt2YSgNOyQNDuRuKkf/56E31176p0Utfkj54ftlOgeNBAAEE5iZAkJobNTtCAAEEEEBguQXcMUXfz0I5SKVeAZ2cBpNuK6Shu+H75B11Xv2OijMPp44nlvuMODoEEEBgdgIEqdnZsmUEEEAAAQRWSsD5ycNcpBDlDJU+DDROo0+VqUM/7fxVt197Snu/fVjVf585GEMpTtTdevOHAAIIfB4ECFKfh6vMOSKAAAIIIPAAAg5SHu4p5ad0R2qkUkONNFRRFSo9XlTnH9p898e6fvrr6vzrVwdjJz3A5lkEAQQQyEqAIJXV5eRkEEAAAQQQOL6Ag5SfikpN+/xFozQSVYpSxUCqOtLosopPzmj9Tz9S99rrBKnjc7MmAgisuABBasUvIIePAAIIIIBAWwLu4jzdiCrdDbqH5C3SHaq6lZ+b7O1LuinpQ2n7ojS4kZr2xf7drK8sy0PTYh7vCCCAQG4CBKncrijngwACCCCAwDEFHJXSeFGVo5O7nSjSSFLuY8Kd+ansaqROauyn3lAqxodCk4NUvI55CKyGAAIIrIwAQWplLhUHigACCCCAwOwF6q4iIkiNUucTk8elpHKgohrf6ZBi7J7RD3cuMf199kfMHhBAAIHFCBCkFuPOXhFAAAEEEFhygTogHY5J9SEfNW3JT4bDQwABBFoXIEi1TsoGEUAAAQQQQAABBBBAIHcBglTuV5jzQwABBBBAAAEEEEAAgdYFCFKtk7JBBBBAAAEEEEAAAQQQyF2AIJX7Feb8EEAAAQQQQAABBBBAoHUBglTrpGwQAQQQQAABBBBAAAEEchcgSOV+hTk/BBBAAAEEEEAAAQQQaF2AINU6KRtEAAEEEEAAAQQQQACB3AUIUrlfYc4PAQQQQAABBBBAAAEEWhcgSLVOygYRQAABBBBAAAEEEEAgdwGCVO5XmPNDAAEEEEAAAQQQQACB1gUIUq2TskEEEEAAAQQQQAABBBDIXYAglfsV5vwQQAABBBBAAAEEEECgdQGCVOukbBABBBBAAAEEEEAAAQRyFyBI5X6FOT8EEEAAAQQQQAABBBBoXYAg1TopG0QAAQQQQAABBBBAAIHcBQhSuV9hzg8BBBBAAAEEEEAAAQRaFyBItU7KBhFAAAEEEEAAAQQQQCB3AYJU7leY80MAAQQQQAABBBBAAIHWBQhSrZOyQQQQQAABBBBAAAEEEMhdgCCV+xXm/BBAAAEEEEAAAQQQQKB1AYJU66RsEAEEEEAAAQQQQAABBHIXIEjlfoU5PwQQQAABBBBAAAEEEGhdgCDVOikbRAABBBBAAAEEEEAAgdwFCFK5X2HODwEEEEAAAQQQQAABBFoXIEi1TsoGEUAAAQQQQAABBBBAIHcBglTuV5jzQwABBBBAAAEEEEAAgdYFCFKtk7JBBBBAAAEEEEAAAQQQyF2AIJX7Feb8EEAAAQQQQAABBBBAoHUBglTrpGwQAQQQQAABBBBAAAEEchcgSOV+hTk/BBBAAAEEEEAAAQQQaF2AINU6KRtEAAEEEEAAAQQQQACB3AUIUrlfYc4PAQQQQAABBBBAAAEEWhcgSLVOygYRQAABBBBAAAEEEEAgdwGCVO5XmPNDAAEEEEAAAQQQQACB1gUIUq2TskEEEEAAAQQQQAABBBDIXYAglfsV5vwQQAABBBBAAAEEEECgdQGCVOukbBABBBBAAAEEEEAAAQRyF/g/i/NfuYyiKKsAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120a98f2280>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "party_pcts.plot.bar() # 요일별 파티 규모"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 파티의 규모는 주말에 커지는 경향이 있음을 알 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  seaborn 패키지로 팁 데이터를 다시 그려보자\n",
    "* 그래프를 그리기 전에 요약해야 하는 데이터는 seaborn 패키지를 이용하면 훨씬 간단하게 처리할 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.063204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.191244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.199886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.162494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>0.172069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip smoker  day    time  size   tip_pct\n",
       "0       16.99  1.01     No  Sun  Dinner     2  0.063204\n",
       "1       10.34  1.66     No  Sun  Dinner     3  0.191244\n",
       "2       21.01  3.50     No  Sun  Dinner     3  0.199886\n",
       "3       23.68  3.31     No  Sun  Dinner     2  0.162494\n",
       "4       24.59  3.61     No  Sun  Dinner     4  0.172069"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "tips['tip_pct'] = tips['tip'] / (tips['total_bill'] - tips['tip'])\n",
    "tips.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abc29a90>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', data=tips, orient='h') # 에러막대를 포함한 요일별 팁 비율 그래프"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 수평으로 그리려면 x, y축을 바꾸고 orient 옵션에 'h'를 넘기면 된다.\n",
    "* seaborn 플로팅 함수의 data 인자는 pandas의 DataFrame을 받는다. 다른 인자들은 컬럼 이름을 참조한다. <br>\n",
    "\n",
    "\n",
    "* day 컬럼의 각 값에 대한 데이터는 여럿 존재하므로 tip_pct의 평균값으로 막대그래프를 그림.\n",
    "    * 대부분의 경우 데이터의 평균을 보려고 하겠지만 때로는 다른 것들을 보고 싶을 수도 있다. \n",
    "    * 예를 들면 \n",
    "        + 데이터에 극단치가 많은 경우 중앙값을 그리는 게 좋을 수 있다.\n",
    "        + 데이터가 범주형인 경우  각 카테고리가 몇 번 표시되는지 계산할 수 있다.\n",
    "* 이때 `estimator` 를 지정하면 됨 => [seaborn 그래프 설명 블로그 참고](http://hleecaster.com/python-seaborn-barplot/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abcb7c70>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', data=tips, orient='h',estimator=np.median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abd79f10>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', data=tips, orient='h',estimator=len)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 막대그래프 위에 덧그려진 검은 선은 95%의 신뢰구간을 나타낸다 (이 값은 옵션으로 설정 가능)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abde09d0>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', data=tips, orient='h',ci=\"sd\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### seaborn.barplot 메서드의 hue 옵션을 이용하면 추가 분류에 따라 나눠 그릴 수 있다"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abde06a0>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', hue='time', data=tips, orient='h')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### seaborn 라이브러리는 자동으로 기본 색깔 팔레트, 그래프 배경, 그리드 선 색상 같은 꾸밈새를 변경한다.\n",
    "* seaborn.set 메서드를 이용해서 이런 꾸밈새를 변경 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abdd60a0>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', hue='time', data=tips, orient='h')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2.3 Histograms and Density Plots (히스토그램과 밀도 그래프)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 히스토그램"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 히스토그램은 막대그래프의 한 종류로, 값들의 빈도를 분리해서 보여줌\n",
    "* 데이터 포인트는 분리되어 고른 간격의 막대로 표현되며 데이터의 숫자가 막대의 높이로 표현됨\n",
    "* 팁 데이터를 사용해서 전제 결제금액 대비 팁 비율을 Series의 plot.hist 메서드를 사용해서 만들어보자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120abf5d760>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips['tip_pct'].plot.hist(bins=50) # 팁 비율 히스토그램"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 밀도 그래프"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 관찰값을 사용해서 추정되는 연속된 확률 분포를 그린다.\n",
    "* 일반적인 과정은 kernel 메서드를 잘 섞어서 이 분포를 근사하는 방법인데 이보다 단순한 정규 분포다.\n",
    "* 그래서 밀도 그래프는 **KDE**(Kernel Density Estimate : 커넬 밀도 추정) 그래프라고도 알려져 있다.\n",
    "* plot.kde을 이용해서 밀도 그래프를 표준 KDE 형식으로 생성한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120acfb6310>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips['tip_pct'].plot.density() # 팁 비율에 대한 밀도 그래프"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120ad2fae80>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips['tip_pct'].plot.kde()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### distplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 히스토그램과 밀도 그래프를 한 번에 손쉽게 그릴 수 있다\n",
    "* 예) 두개의 다른 표준정규분포로 이루어진 양봉분포를 그려보자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120ad1b0a30>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "comp1 = np.random.normal(0, 1, size=200)\n",
    "comp2 = np.random.normal(10, 2, size=200)\n",
    "values = pd.Series(np.concatenate([comp1, comp2]))\n",
    "sns.distplot(values, bins=100, color='k')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* bins : 막대 개수\n",
    "* binwidth : 막대그래프의 크기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2.4 Scatter or Point Plots (산포도)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 두 개의 1차원 데이터 묶음 간의 관계를 나타내고자 할 때 유용한 그래프\n",
    "* statsmodels 프로젝트에서 macrodata 데이터 묶음을 불러온 다음 몇 가지 변수를 선택하고 로그차를 구해보자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "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>cpi</th>\n",
       "      <th>m1</th>\n",
       "      <th>tbilrate</th>\n",
       "      <th>unemp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>5.379386</td>\n",
       "      <td>7.296210</td>\n",
       "      <td>0.157004</td>\n",
       "      <td>1.791759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>5.357407</td>\n",
       "      <td>7.362962</td>\n",
       "      <td>-2.120264</td>\n",
       "      <td>1.931521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>5.359746</td>\n",
       "      <td>7.373249</td>\n",
       "      <td>-1.514128</td>\n",
       "      <td>2.091864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>5.368165</td>\n",
       "      <td>7.410710</td>\n",
       "      <td>-1.714798</td>\n",
       "      <td>2.219203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>5.377059</td>\n",
       "      <td>7.422912</td>\n",
       "      <td>-2.120264</td>\n",
       "      <td>2.261763</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          cpi        m1  tbilrate     unemp\n",
       "198  5.379386  7.296210  0.157004  1.791759\n",
       "199  5.357407  7.362962 -2.120264  1.931521\n",
       "200  5.359746  7.373249 -1.514128  2.091864\n",
       "201  5.368165  7.410710 -1.714798  2.219203\n",
       "202  5.377059  7.422912 -2.120264  2.261763"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "macro = pd.read_csv('macrodata.csv')\n",
    "data = macro[['cpi', 'm1', 'tbilrate', 'unemp']]\n",
    "np.log(data)[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "scrolled": true
   },
   "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>cpi</th>\n",
       "      <th>m1</th>\n",
       "      <th>tbilrate</th>\n",
       "      <th>unemp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>-0.007904</td>\n",
       "      <td>0.045361</td>\n",
       "      <td>-0.396881</td>\n",
       "      <td>0.105361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>-0.021979</td>\n",
       "      <td>0.066753</td>\n",
       "      <td>-2.277267</td>\n",
       "      <td>0.139762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.002340</td>\n",
       "      <td>0.010286</td>\n",
       "      <td>0.606136</td>\n",
       "      <td>0.160343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>0.008419</td>\n",
       "      <td>0.037461</td>\n",
       "      <td>-0.200671</td>\n",
       "      <td>0.127339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>0.008894</td>\n",
       "      <td>0.012202</td>\n",
       "      <td>-0.405465</td>\n",
       "      <td>0.042560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          cpi        m1  tbilrate     unemp\n",
       "198 -0.007904  0.045361 -0.396881  0.105361\n",
       "199 -0.021979  0.066753 -2.277267  0.139762\n",
       "200  0.002340  0.010286  0.606136  0.160343\n",
       "201  0.008419  0.037461 -0.200671  0.127339\n",
       "202  0.008894  0.012202 -0.405465  0.042560"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans_data = np.log(data).diff().dropna()\n",
    "trans_data[-5:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### seaborn 라이브러리의 regplot 메서드를 이용해서 산포도와 선형회귀곡선을 함께 그릴 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Changes in log m1 versus log unemp')"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot('m1', 'unemp', data=trans_data)\n",
    "plt.title('Changes in log %s versus log %s' % ('m1', 'unemp')) # 선형회귀곡선과 산포도"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 파란색 범위 = 잔차\n",
    "* 잔차란? 통계학에서 실측치와 회귀 모형의 예측치 사이의 차이값 (오차의 범위) \n",
    "* ci=None 을 하면 잔차가 안 보이게 할 수 있다.\n",
    "* fit_reg=False 을 하면 회귀선을 없앨 수 있다.\n",
    "* line_kws={'color':\"red\"} : 회귀선의 색을 바꿀 수 있다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 짝지은 그래프 또는 산포도 행렬 (pairplot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 탐색 데이터 분석에서는 변수 그룹 간의 모든 산포도를 살펴보는 일이 매우 유용함.\n",
    "* 이런 그래프를 직접 그리는 과정은 다소 복잡하기 때문에 seaborn의 pairplot 함수를 통해 대각선을 따라 각 변수에 대한 히스토그램이나 밀도 그래프도 생성 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x120ad4617c0>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(trans_data, diag_kind='kde', plot_kws={'alpha': 0.2}) # 거시경제 데이터의 산포도 행렬"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot_kws 인자는 각각의 그래프에 전달한 개별 설정값을 지정함\n",
    "* 설정 옵션에 관한 자세한 내용은 seaborn.pairplot 문서 참고"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2.5 Facet Grids and Categorical Data (패싯 그리드와 범주형 데이터)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 추가적인 그룹 차원을 가지는 데이터는 어떻게 시각화할까?\n",
    "* 다양한 범주형 값을 가지는 데이터를 시각화하는 한 가지 방법 = 패싯 그리드\n",
    "* seaborn의 factorplot이라는 내장 함수를 통해 다양한 면을 나타내는 그래프를 쉽게 그릴 수 있다.\n",
    "\n",
    "* Facet Grid란 쉽게 말해 Multi plot이라고 이해하면 된다! => 즉, 하나의 데이터를 여러 개의 plot으로 나눠서 보고자 할 때 사용됨"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x120ad3b6040>"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792.225x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 요일/시간/흡연 여부에 따른 팁 비율\n",
    "sns.factorplot(x='day', y='tip_pct', hue='time', col='smoker',\n",
    "               kind='bar', data=tips[tips.tip_pct < 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x120ae9c7760>"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432.225x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 요일/시간/흡연 여부에 따른 팁 비율\n",
    "sns.factorplot(x='day', y='tip_pct', hue='time', row='smoker',\n",
    "               kind='bar', data=tips[tips.tip_pct < 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 'time'으로 그룹을 만드는 대신 패싯 안에서 막대그래프의 색상을 달리해서 보여줄 수 있다.\n",
    "* 또한 패싯 그리드에 time 값에 따른 그래프를 추가할 수도 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x120af29ca00>"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot(x='day', y='tip_pct', row='time',\n",
    "               col='smoker',\n",
    "               kind='bar', data=tips[tips.tip_pct < 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* factorplot은 보여주고자 하는 목적에 어울리는 다른 종류의 그래프도 함께 지원함\n",
    "* 예) 중간값과 사분위 그리고 특잇값을 보여주는 상자그림(boxplot)이 효과적인 시각화 방법일 수도 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x120ad294550>"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot(x='tip_pct', y='day', kind='box',\n",
    "               data=tips[tips.tip_pct < 0.5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 일반적인 용도의 seaborn.FacetGrid 클래스를 이용해서 나만의 패싯 그리드를 만들고 원하는 그래프를 그릴 수도 있다.\n",
    "* 자세한 내용은 seaborn 문서를 참고"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### seaborn 시각화방법 17가지 [블로그링크](https://dining-developer.tistory.com/30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9.3 다른 파이썬 시각화 도구"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 여러 오픈소스와 마찬가지로 파이썬에서 그래프를 그릴 수 있는 라이브러리는 일일이 나열하기 힘들 정도로 많이 존재함\n",
    "* 2010년 부터 웹을 위한 대화형 그래픽 도구 개발이 본격적으로 진행되었는데, Bokeh(보케)나 Plotly(플로틀리) 같은 도구를 이용하면 웹 브라우저 상에서 파이썬으로 동적 대화형 그래프를 그릴 수 있다. [보케](https://diplabs.tistory.com/11) [플로틀리](https://towardsdatascience.com/the-next-level-of-data-visualization-in-python-dd6e99039d5e)\n",
    "* 웹이나 출판을 위한 정적 그래프를 생성한다면 matplotlib과 pandas, seaborn을 기본으로 사용하길 추천"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}