exploring_digital_biomarkers_a_day.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring dataset (a day)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking sensor data for a day (2020-02-14)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normal range: HbA1c 5.2–5.6, Pre-diabetes range: HbA1c 5.7–6.4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gender & HbA1c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.signal import find_peaks, peak_prominences\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.collections import LineCollection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\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>ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HbA1c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>MALE</td>\n",
       "      <td>5.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>5.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  Gender  HbA1c\n",
       "0  13    MALE    5.7\n",
       "1   1  FEMALE    5.5\n",
       "2   3  FEMALE    5.9\n",
       "3   4  FEMALE    6.4\n",
       "4   5  FEMALE    5.7"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dg_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/Demographics.csv')\n",
    "dg_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "biological_sex = dg_df.loc[dg_df['ID'] == 1, 'Gender'].values[0]\n",
    "hbA1c = dg_df.loc[dg_df['ID'] == 1, 'HbA1c'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Biological Sex : FEMALE\n",
      "HbA1c : 5.5\n"
     ]
    }
   ],
   "source": [
    "print(f'Biological Sex : {biological_sex}')\n",
    "print(f'HbA1c : {hbA1c}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Food Log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "fl001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/Food_Log_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "fl001_df['date']=pd.to_datetime(fl001_df['date'])\n",
    "fl001_df['time_begin']=pd.to_datetime(fl001_df['time_begin'])\n",
    "fl001_df = fl001_df[(fl001_df['date'] >= '2020-02-14 00:00:00') & (fl001_df['date'] <= '2020-02-14 23:59:59')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>time_begin</th>\n",
       "      <th>time_end</th>\n",
       "      <th>logged_food</th>\n",
       "      <th>amount</th>\n",
       "      <th>unit</th>\n",
       "      <th>searched_food</th>\n",
       "      <th>calorie</th>\n",
       "      <th>total_carb</th>\n",
       "      <th>dietary_fiber</th>\n",
       "      <th>sugar</th>\n",
       "      <th>protein</th>\n",
       "      <th>total_fat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>07:10:00</td>\n",
       "      <td>2020-02-14 07:10:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Natrel Lactose Free 2 Percent</td>\n",
       "      <td>8.00</td>\n",
       "      <td>fluid ounce</td>\n",
       "      <td>(Natrel) Lactose Free 2% Partly Skimmed Milk</td>\n",
       "      <td>120.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>07:10:00</td>\n",
       "      <td>2020-02-14 07:10:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Standard Breakfast</td>\n",
       "      <td>0.75</td>\n",
       "      <td>cup</td>\n",
       "      <td>(Kellogg's) Frosted Flakes, Cereal</td>\n",
       "      <td>110.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>09:38:00</td>\n",
       "      <td>2020-02-14 09:38:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Breakfast Trail Mix</td>\n",
       "      <td>0.50</td>\n",
       "      <td>cup</td>\n",
       "      <td>(Giant) Breakfast Blend, Trail Mix</td>\n",
       "      <td>280.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>12:38:00</td>\n",
       "      <td>2020-02-14 12:38:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Spinach Salad w/ strawberries and cheese</td>\n",
       "      <td>200.00</td>\n",
       "      <td>grams</td>\n",
       "      <td>Spinach And Strawberry Salad</td>\n",
       "      <td>286.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>12:38:00</td>\n",
       "      <td>2020-02-14 12:38:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Egg</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Large Egg</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.2</td>\n",
       "      <td>6.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>19:30:00</td>\n",
       "      <td>2020-02-14 19:30:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Acai Smoothie</td>\n",
       "      <td>20.00</td>\n",
       "      <td>fluid ounce</td>\n",
       "      <td>(Smoothie King) Acai Adventure Smoothie</td>\n",
       "      <td>440.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>20:00:00</td>\n",
       "      <td>2020-02-14 20:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(Trader Joe's) Mac and Cheese</td>\n",
       "      <td>0.50</td>\n",
       "      <td>cup</td>\n",
       "      <td>(Trader Joe's) Macaroni and Cheese</td>\n",
       "      <td>135.0</td>\n",
       "      <td>23.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>20:00:00</td>\n",
       "      <td>2020-02-14 20:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Coconut Shrimp</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Coconut Shrimp</td>\n",
       "      <td>317.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date      time          time_begin  time_end  \\\n",
       "3  2020-02-14  07:10:00 2020-02-14 07:10:00       NaN   \n",
       "4  2020-02-14  07:10:00 2020-02-14 07:10:00       NaN   \n",
       "5  2020-02-14  09:38:00 2020-02-14 09:38:00       NaN   \n",
       "6  2020-02-14  12:38:00 2020-02-14 12:38:00       NaN   \n",
       "7  2020-02-14  12:38:00 2020-02-14 12:38:00       NaN   \n",
       "8  2020-02-14  19:30:00 2020-02-14 19:30:00       NaN   \n",
       "9  2020-02-14  20:00:00 2020-02-14 20:00:00       NaN   \n",
       "10 2020-02-14  20:00:00 2020-02-14 20:00:00       NaN   \n",
       "\n",
       "                                 logged_food  amount         unit  \\\n",
       "3              Natrel Lactose Free 2 Percent    8.00  fluid ounce   \n",
       "4                         Standard Breakfast    0.75          cup   \n",
       "5                        Breakfast Trail Mix    0.50          cup   \n",
       "6   Spinach Salad w/ strawberries and cheese  200.00        grams   \n",
       "7                                        Egg    1.00          NaN   \n",
       "8                              Acai Smoothie   20.00  fluid ounce   \n",
       "9              (Trader Joe's) Mac and Cheese    0.50          cup   \n",
       "10                            Coconut Shrimp    5.00          NaN   \n",
       "\n",
       "                                   searched_food  calorie  total_carb  \\\n",
       "3   (Natrel) Lactose Free 2% Partly Skimmed Milk    120.0         9.0   \n",
       "4             (Kellogg's) Frosted Flakes, Cereal    110.0        26.0   \n",
       "5             (Giant) Breakfast Blend, Trail Mix    280.0        30.0   \n",
       "6                   Spinach And Strawberry Salad    286.0        14.0   \n",
       "7                                      Large Egg     72.0         0.4   \n",
       "8        (Smoothie King) Acai Adventure Smoothie    440.0        92.0   \n",
       "9             (Trader Joe's) Macaroni and Cheese    135.0        23.5   \n",
       "10                                Coconut Shrimp    317.0        30.0   \n",
       "\n",
       "    dietary_fiber  sugar  protein  total_fat  \n",
       "3             NaN    8.0     12.0        NaN  \n",
       "4             NaN   10.0      1.0        NaN  \n",
       "5             NaN   22.0      4.0        NaN  \n",
       "6             NaN    8.5      7.6        NaN  \n",
       "7             NaN    0.2      6.3        NaN  \n",
       "8             NaN   75.0      5.0        NaN  \n",
       "9             NaN    1.5      5.0        NaN  \n",
       "10            NaN    0.1     11.0        NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fl001_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\smyie\\AppData\\Local\\Temp\\ipykernel_16460\\3700245159.py:6: FutureWarning: 'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
      "  for window_data in fl001_df.rolling(window='2H', on='time_begin'):\n",
      "C:\\Users\\smyie\\AppData\\Local\\Temp\\ipykernel_16460\\3700245159.py:18: FutureWarning: 'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
      "  for window_data in fl001_df.rolling(window='8H', on='time_begin'):\n",
      "C:\\Users\\smyie\\AppData\\Local\\Temp\\ipykernel_16460\\3700245159.py:30: FutureWarning: 'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
      "  for window_data in fl001_df.rolling(window='24H', on='time_begin'):\n"
     ]
    }
   ],
   "source": [
    "calories2hr = 0.\n",
    "protein2hr = 0.\n",
    "sugar2hr = 0.\n",
    "carbs2hr = 0.\n",
    "\n",
    "for window_data in fl001_df.rolling(window='2H', on='time_begin'):\n",
    "    calories2hr += window_data['calorie'].values.sum()\n",
    "    protein2hr += window_data['protein'].values.sum()\n",
    "    sugar2hr += window_data['sugar'].values.sum()\n",
    "    carbs2hr += window_data['total_carb'].values.sum()\n",
    "\n",
    "\n",
    "calories8hr = 0.\n",
    "protein8hr = 0.\n",
    "sugar8hr = 0.\n",
    "carbs8hr = 0.\n",
    "\n",
    "for window_data in fl001_df.rolling(window='8H', on='time_begin'):\n",
    "    calories8hr += window_data['calorie'].values.sum()\n",
    "    protein8hr += window_data['protein'].values.sum()\n",
    "    sugar8hr += window_data['sugar'].values.sum()\n",
    "    carbs8hr += window_data['total_carb'].values.sum()\n",
    "\n",
    "\n",
    "calories24hr = 0.\n",
    "protein24hr = 0.\n",
    "sugar24hr = 0.\n",
    "carbs24hr = 0.\n",
    "\n",
    "for window_data in fl001_df.rolling(window='24H', on='time_begin'):\n",
    "    calories24hr += window_data['calorie'].values.sum()\n",
    "    protein24hr += window_data['protein'].values.sum()\n",
    "    sugar24hr += window_data['sugar'].values.sum()\n",
    "    carbs24hr += window_data['total_carb'].values.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calories2hr : 3181.0\n",
      "protein2hr : 86.5\n",
      "sugar2hr : 293.29999999999995\n",
      "carbs2hr : 455.4\n",
      "calories8hr : 5505.0\n",
      "protein8hr : 175.20000000000002\n",
      "sugar8hr : 417.4\n",
      "carbs8hr : 663.5999999999999\n",
      "calories24hr : 7035.0\n",
      "protein24hr : 226.20000000000002\n",
      "sugar24hr : 537.4\n",
      "carbs24hr : 858.5999999999999\n"
     ]
    }
   ],
   "source": [
    "print(f'calories2hr : {calories2hr}')\n",
    "print(f'protein2hr : {protein2hr}')\n",
    "print(f'sugar2hr : {sugar2hr}')\n",
    "print(f'carbs2hr : {carbs2hr}')\n",
    "\n",
    "print(f'calories8hr : {calories8hr}')\n",
    "print(f'protein8hr : {protein8hr}')\n",
    "print(f'sugar8hr : {sugar8hr}')\n",
    "print(f'carbs8hr : {carbs8hr}')\n",
    "\n",
    "print(f'calories24hr : {calories24hr}')\n",
    "print(f'protein24hr : {protein24hr}')\n",
    "print(f'sugar24hr : {sugar24hr}')\n",
    "print(f'carbs24hr : {carbs24hr}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dexcom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "dexcom001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/Dexcom_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "dexcom001_df.drop(dexcom001_df.loc[:11].index, inplace=True)\n",
    "dexcom001_df.rename(columns = {'Timestamp (YYYY-MM-DDThh:mm:ss)': 'datetime'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "dexcom001_df['datetime']=pd.to_datetime(dexcom001_df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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p6el477338NRTTwkrVJ6enjAyMsLKlSuRkJCAvXv3YsmSJc0+15gxY5Cbm4tly5YhPj4eP/zwA/bt21fvmI8//hifffYZvvvuO9y5cwfXrl3Dxo0b8fXXXzf5vBEREbhx40aTqz+asrS0xIwZM7BgwQIcPXoUN27cwPPPPw+RSCRcbbp06RIqKiowYsQI4XEvvvgiYmNjsWDBAsTExGDbtm3YtGlTo69x7do1REVFCV/R0dHCfSdPnsTIkSPbvQpICCGEaENiXjliskthJBZhQl8X4faQmuAnuh3BT7VCha8Pqi82zh3tixdG+uDTh/thUU0RhZ/PJuOlrZfx4pZLiFhxArHZTZeo3nddfbF5sJdts3t5XG3Uf2/TKfjROx0e/HzxxReQSCR4/fXXG70/KysLjo6O9W6TSCSwtbVFVlZWo4/57LPPYG1tLXx5eHh09LB1ztfXF1euXMH48eOxcOFCBAcHY9CgQVi5ciXmz5/f5Mm/VCrFr7/+itu3b6N///744osvsHTp0nrH9OrVC//99x+io6MxZMgQhIeHY8+ePZBI1KmAn3/+OR599FE8++yzGDBgAOLi4nDgwAH06NEDAGBkZISFCxeif//+GDVqFMRisVA22czMDCdOnICnpyceeeQRBAUF4fnnn0dVVRWsrKya/Z49PT0xfvx4FBYW1itw4ODggE2bNmHHjh3o3bs3Pv/8cyxfvrzZ5woKCsKPP/6IH374AcHBwTh//jzmz59f75gXXngB69evx8aNG9GvXz+MHj0amzZtanblp1+/fhgwYAB+//33Zl9fE19//TXCw8Px4IMPYvz48Rg+fLhQdhsA9uzZg/vvv1/4uQDqOdq5cyf+/PNPBAcHY/Xq1fi///u/Rp9/1KhRCA0NFb7qVqn77bff6u11IoQQQvRJXI46PT3A2bJeEQF+5ed6RjHkytalkvO2X0hBakEl7C2MMXO4l3D78yO8sfKpUAzztcMQL1u4WJsgu0SGJ9eew/X04gbPU1hejQ0nEwEAjw10b/Y1+eCHVn70EGsHAGz37t3Cvy9evMicnJxYenq6cFvPnj3ZN998I/z7008/Zb169WrwXA4ODuzHH39s9HWqqqpYcXGx8JWamsoAsOLi4gbHVlZWsps3b7LKysq2f2OE1PH333+zoKAgplQqO/R5y8rKmLW1NVu/fj1jjLF+/fqx7du3d+hrMMbYv//+y4KCgphcLm/2OPrdIYQQoivrTyawnu/8zV7ecqne7UqlivX9cD/r+c7f7FpaUaufVyZXskFLD7Ke7/zNNp9JbPbYgjIZe2jlSdbznb9Z38X72fnE/Hr3/98/N1nPd/5mEd8cZ0qlqtnnis0uUT/Ph/tbPWbSesXFxU3GBnfr0JWfkydPIicnB56enpBIJJBIJEhOTsZbb70llNd1dnZusH9DoVCgoKAAzs7OjT6vsbExrKys6n0R0lkeeOABzJkzB+np6e16nitXruDXX39FfHw8Ll++jGnTpgEAJk+ejOrqajz66KNCufGOVF5ejo0bN9ZbUSKEEEL0SWqBuhqpu2399GyRiKtNfUsravXzXk4pRG6pDHbmRpg62LPZY3uYG2Hr7KEI87ZFqUyBZzdE4vidXABAVnEVNp1JAgC8PSEAIlHzBRJcrNXfR2mVAiVV8maPJZ2rQ8+Gnn32WYwfP77ebREREXj22WeF/i3h4eEoKirCpUuXhLScI0eOQKVSNajCRYi+qFuqvT2WL1+OmJgYGBkZYeDAgTh58iTs7dXVYj788MMOeY278YUkCCGEEH3FBz+ejVR0C3a3wcnYPESlFGFaWM9WPa9QltrfHkaSlq/5WxhLsHnWELy05RKOxuTihc0XMLqXA9IKKyFTqDDYqwfGBji2+DzmxhLYmElRVCFHZlEVrJwb9gMiutHq4KesrAxxcXHCvxMTExEVFQVbW1t4enrCzq5+OT+pVApnZ2ehn0lQUBAmTJiA2bNnY/Xq1ZDL5Xj11VcxderUJptJEtIVhIaG4tKlS7oeBiGEEKJ3UpoJftqz8nOqJvhpqix1Y0ykYqx5dhD+93sU/rmaiUO3ajOW3p4QqHFZbFdrUxRVyJFRVIkAZ8uWH0A6RauDn4sXL2Ls2LHCv998800AwIwZM5qsQnW3rVu34tVXX8W4ceOEJqffffdda4dCCCGEEEIMHGOs2eCnv4e6dUZsThnKZApYGGt2+lpSJReqxLUm+AEAI4kI300NxZQQN+SVqRvN97Qzw2AvW42fw9XGFDczS6jim55pdfAzZsyYBs0km5OUlNTgNltbW601NOW1ZoyEEPqdIYQQohu5pTLIFCqIuNoqaXU5WprAzcYU6UWVOB6Tiwf6uzTyLA2di8+HigE+9uZwa+R5WyIWcbi3t1OrH8dzs1FXc6WKb/qlw0td6xrfVLWiokLHIyHEsPC/M3c3JiaEEEK0iV/1cbUxhVTc+Knpw6FuAIAVh+5AqdLsYt3pNqS8dSTq9aOfulz5J7FYDBsbG6GinJmZmca5mYR0R4wxVFRUICcnBzY2Nk021CWEEEK0obmUN97sUT745VwyYnPKsPtKeot9doC27ffpSG49qNePPupywQ8AoWT23SW1CSFNs7GxabLcPCGEEKItfPDj0aPp4MfaVIqXxvji83238c3BO5gU7AJjSdMX6zKLKxGfWw4RB4T72DV5nDbVNjqt0snrk8Z1yeCH4zi4uLjA0dERcjnVViekJVKplFZ8CCGE6ISw8mPXdPADADPCvbDxdCLSiyqxLTIFM4d7N3ns6bh8AEA/dxtYm+kmnZvfZ5RVUgWFUgVJEyl9pHN1yeCHJxaL6YSOEEIIIUSP8T1+PJpJewMAUyMxXh/nj/d3X8f3R+Lw+CCPJiu//XcjCwAwyl83KW8A4GBhDKmYg1zJkFMqa7SYA+l8FIISQgghhBCd0WTPD++JQR7wsjNDfnk1fjqV2OgxxRVyHIvJBQCNK8Npg0jEwdmaKr7pGwp+CCGEEEKITlTJlcguUffR0ST4kYpFePO+AADAuhMJKCyvbnDM/huZqFaqEOBkiUBnq44dcCu5WlPFN31DwQ8hhBBCCNGJtEJ1UGBhLEEPDffmPNjPBb1drFAqU2DV8fgG9/95JQMAMDnUteMG2kZuVPRA71DwQwghhBBCdKLufh9NW5OIRBwWTFCv/mw6k4TM4tpVlaziKpxLVBc7eChY98FPbcU3WvnRFxT8EEIIIYQQnagtc926YgBjejlgiLctqhUqfHc4Vrj976sZYAwY7NUD7s2Uzu4s1OhU/1DwQwghhBBCdKI1xQ7q4jgO79Ss/vx+MQ0JuWWQK1X441IaAOChELeOHWgbudpQwQN906VLXRNCCCGEEP2laZnrxgzsaYvxQY44dCsHn++7DYWK4XZWKUykIjzQT3dV3uriV59SCyrAGNM4tY9oD638EEIIIYQQncio2a/j1sYeOPMjAsBxwH83s3Hkdg6MJSKsemYgbM2NOnKYbeZpawYRB5RXK5FTKtP1cAgo+CGEEEIIITrCV0FrawPQQGcrTKlJcbMwluDnWUMwNsCxw8bXXkYSkbCqFZ9bpuPREIDS3gghhBBCiA5UVitRUNOnp60rPwDw0aQ+6Glnhgl9nXXe16cxPvbmSM6vQEJuOYb52ut6ON0erfwQQgghhJBOx6e8mRuJYWXa9uvx1mZSzBvfSy8DHwDwcbAAACTmlet4JASg4IcQQgghhOgAXwHNrYdply4E4ONgDgBIoLQ3vUDBDyGEEEII6XR88NPW/T6Gwtu+JvihlR+9QMEPIYQQQgjpdOntLHZgKHxr0t5SCypQrVDpeDSEgh9CCCGEENLphLS3Lh78OFoaw9xIDBUDUgpo9UfXKPghhBBCCCGdLr2QT3sz0fFItIvjOKHoQXwuBT+6RsEPIYQQQgjpdHy1N1frrr3yA9TZ90PBj85R8EMIIYQQQjqVSsWQ2U32/AC1Fd8S86jim65R8EMIIYQQQjpVXrkM1UoVRBzgbN21096A2l4/tPKjexT8EEIIIYSQTpVRs+rjZGUCqbjrn476ULlrvdH1322EEEIIIUSvdJcePzx+z09BeTWKKqp1PJrujYIfQgghhBDSqbpb8GNuLIGzlTq9j1Z/dIuCH0IIIYQQ0qnSi7pHmeu6+KIHtO9Htyj4IYQQQjpARbUC2SVVuh4GIQahuzQ4ras2+KGKb7pEwQ8hhBDSAeb+cgkjlx3FtbRiXQ+FEL2X3g2DH297dcW3REp70ykKfgghhJB2qqhW4HRcHqoVKnyx/7auh0OI3svoRj1+eJT2ph8o+CGEEELa6Xp6CVRM/f+n4vJwOi5PtwMiRI9VVitRUK6ueNadgh9ffuUnvxxK/gODdDoKfgghhJB2ik4tAgBwnPrfy/bfBmN0ckNIY2JzSgEANmZSWJlIdDyazuPWwxRGYhGqFSphzxPpfN3nHUcIIc24nl6MHRdTUa1k4Dggoo8zRvdy0PWwiIGISisCAMwc5o3fLqQgOq0YB25kYUJfF90OjBA9xF8sCHa3AcdfMegGxCIOPe3MEJtThoS8cnjYmul6SN0SrfwQQrq9k7G5eHz1WWw+m4xfz6dgW2QKntt4Hlsjk3U9NGIg+JO58UGOmDncCwCw/UKq7gZEiB6LSlUXBQn2sNHtQHSAKr7pXquDnxMnTmDSpElwdXUFx3H4888/hfvkcjneeecd9OvXD+bm5nB1dcX06dORkZFR7zkKCgowbdo0WFlZwcbGBs8//zzKyuhNQAjpfPuvZ+H5TRdRKVdimK8d3rq3Fx7s7wLGgPd3X8ea4/G6HiLRc3llMqQVVoLjgL7u1hgT4AgAuJ1VquOREaKfolILAQAhHtY6Hknn83FQ7/uhoge60+rgp7y8HMHBwfjhhx8a3FdRUYHLly9j0aJFuHz5Mnbt2oWYmBg89NBD9Y6bNm0abty4gYMHD+Lvv//GiRMnMGfOnLZ/F4QQ0gbZJVV4/dcrqFaqcH8/Z2yaOQSvjfPHyqdC8fIYXwDAZ/tu49DNbB2PlOizqzUpb74OFrAykSLA2RIAkFlcheIKuQ5HRoj+KamSI77mxD/Y3Ua3g9EBH3v1yg+Vu9adVu/5mThxIiZOnNjofdbW1jh48GC9277//nsMGTIEKSkp8PT0xK1bt7B//35cuHABgwYNAgCsXLkS999/P5YvXw5XV9c2fBuEENJ6x+/kolqpQm8XK3w3NRQSsfp6EMdxeHtCICqqldh0JgnLDtzG2EBHiEXdJzedaE5I4ak5kbMykcLNxhTpRZWIyS7FEG9bHY6OEP3C98HysDWFnYWxjkfT+SjtTfe0vuenuLgYHMfBxsYGAHD27FnY2NgIgQ8AjB8/HiKRCJGRkY0+h0wmQ0lJSb0vQghprzM15YjvCXQUAp+6/ndvL1ibSnEnuwx7otI7e3jEQPD7feqm8PCrPzFZ9PeKkLqi6hQ76I58aspdZxRXoaJaoePRdE9aDX6qqqrwzjvv4KmnnoKVlRUAICsrC46OjvWOk0gksLW1RVZWVqPP89lnn8Ha2lr48vDw0OawCSHdAGMMp+LyAQDD/ewbPcbaVIoXR6vT374+eAfVClWnjY8YBsYYomvS3upu3uaDH9r3Q0h9tRcLbHQ6Dl3pYW6EHmZSAEBSXoWOR9M9aS34kcvleOKJJ8AYw6pVq9r1XAsXLkRxcbHwlZpKFXQIIe1zJ7sMeWUymEhFGNDTpsnjnhvmBUdLY6QVVuLX8ymdN0BiEJLzK1BUIYeRWIRAZyvh9kBh5YeCH0LqauxiQXcjFD3Io9Q3XdBK8MMHPsnJyTh48KCw6gMAzs7OyMnJqXe8QqFAQUEBnJ2dG30+Y2NjWFlZ1fsihJD2OFWT8jbE2w7GEnGTx5kaifHqPX4AgN8v0oUXUh+/shPoYgkjSe2fVD4QiskqpWanhNTILK5EdokMYhGHvq7dr9Ibz9ue3/dDRQ90ocODHz7wiY2NxaFDh2BnZ1fv/vDwcBQVFeHSpUvCbUeOHIFKpUJYWFhHD4cQQhp1uib4Ge5r18KRwPggJwDqE90quVKr4yKGJae0CgDgYm1S73YfB3NIxRxKZQqkUyd3QgDUprwFOFnC1Kjpi05dHRU90K1WBz9lZWWIiopCVFQUACAxMRFRUVFISUmBXC7HY489hosXL2Lr1q1QKpXIyspCVlYWqqurAQBBQUGYMGECZs+ejfPnz+P06dN49dVXMXXqVKr0RgjpFHKlCpEJze/3qcvF2gQOlsZQqhiupxdre3jEgOSWygAAjpb1gx+pWATfmtQWSn0jRO1KShEAILgb9vepiy96QHsCdaPVwc/FixcRGhqK0NBQAMCbb76J0NBQLF68GOnp6di7dy/S0tIQEhICFxcX4evMmTPCc2zduhWBgYEYN24c7r//fowYMQJr167tuO+KEEKaEZ1ahPJqJXqYSdHbpeU0Wo7jhMpEfKUiQgAgp4QPfhqW7KWiB4TUdyZefdGpu5d/H+JtC4mIw+2sUsTT6k+na3WfnzFjxjSbv6xJbrOtrS22bdvW2pcmhJBmXUouxNxfLuKlMX54foR3k8edjFWnvA3ztYdIw949oZ42OHQrG9FptPJDavFpb45WTQc/tPJDCFBYXo3rGerPz+G+La+4d2W25kYY6W+PozG52BOVgTfv7aXrIXUrWu/zQwghnYExho/23kBeWTW+PHAbOSVVTR7377VMAMDoXg4aP3/tyk9hu8dKuo6cmrQ3h0ZWfqjiGyG1zibkgzGgl5MFHK1MWn5AFzcl1A0AsDcqnYqidDIKfgghXcK+61m4VrMfp0quwsojcY0edzurFLE5ZTASixDRt/EKk43p567OUU8tqER+maz9AyZdQlN7foDaim/xuWXUI4p0e0KRGQ32WXYH44OcYCoVIym/gjIKOhkFP4QQg6dQqrD8QAwAYEyAejXn1/MpSM5vWEZ0T1QGAGBsoAOsTaUav4a1qRS+NRV6rtIfKgJAqWLIK2t6z4+LtQmsTCRQqBjuZNPqD+ne+OBnBAU/AABzYwnu7a2uJLonKl3Ho+leKPghhBi8Py6lISGvHLbmRlj5VChG93KAQsXw9cE79Y5TqRj+ilYHP5ND3Fr9OnxTvitU9IAAyC+XQcUAjlPn8N+N4zjhPcM3diSkO0otqEBSfgXEIq7bFzuoa0qousrxX9GZUChpdbizUPBDCDFoF5MK8Ok/twAAr4z1g6WJFAsiAgAAe6MzcDOjRDj2Ukoh0osqYWEswT2Bjq1+rRD+RJaCH4LaSm925saQiBv/c8rvFaP3DOnOzsSrV31CPGxgaaL5intXN9LfAT3MpMgrk+HQrWxdD6fboOCHEGKwTsbm4tkN51EqU2CIly2eGeoJAOjrZo0H+7uAMWD5fzHC8XxqQUQfZ5hIW99gL6TOVXzaoEpym0l54/HvGSqRTrqzU3Ga91XrTqRiEaaF9QQAfPXfHShVrfu7olIx+lvUBhT8EEIMUlxOKZ7fdBGVciVG93LA5llDYCypDWjeui8AYhGHI7dzcCGpAMn55fgrWl3lbXJI2xoqBzpbwUgsQlGFHMn5FR3yfRDDlcv3+GmkzDWvf00zx9icMpTJFJ0yLkL0CWMMZ2i/T5Nmj/KBtakUsTll2H1F870/cTllGP/1cTy48hQyiiq1OMKuh4IfQohB+udqFqqVKgzxssXa6QNhalR/Jcfb3hxPDPIAAHy45wYeX30WxZVy+DtaYJivXZte00gigp+jujM3NaYjfI8fB4umgx9HSxO42ZiCMeAaFcog3VByfgXyy6thJBEJK6GklrWpFC+P8QUAfHPwDmQKZYuPuZ5ejCfWnEVCXjluZJTg8dVnkZTXsMAPaRwFP4QQg8RXDnp4gFu9FZ+63hjnD2OJCDczS5BTKkOgsyW2zg5rcn+GJjxtzQAAKQW08tPd8T1+mlv5AYDgmtUfSn0j3RH/vu/jagUjCZ12NmbGMC84WRkjvagSP51KanC/UsXw3eFYTFt/DtPWn8NTa8+hoLwafd2s4GNvjvSiSjy+5iz1FNMQvQsJIQanXKbA5RR1s9Hm0iicrU3w/AhvAOpKbb/NGdpoP5bW8LRTBz+pBZRm0N011+OnLiqUQbozPvjhi3+QhkykYswb3wsA8MX+2/jlXLJwX7VChTd+u4KvD97B6bh8nI7LR6lMgcFePbBt9lBsnxuOQGdL5JbK8OTas/Q5owGJrgdACCGtdT6xAAoVg4etKTxqVmKasiAiAOOCHNHH1bpNRQ7u5kErP6QGv/Lj0EzBA6BOxTcqd026If59H+ppo9Nx6LsnB3kgJqsUm84kYdGf15GYWw5vezMcvJWDE3dyIRVzWBARACcrE5gbSTCyl70668EE2D4nHDM2nkdUahGeXncOG54bjKE+bUvv7g4o+CGEGJxTrdg8y3EcBvbsuL4SfNpbKgU/3R6/56e5am+AuvqgiAMyi6uQXVIFJ6v2rT4SYiiqFSrcqGk3QCs/zROJOHw4qTcsjCX4/mgcfjqdKNxnIhVh9TMDMSag8RYN1mZSbHkhDLM3X8TZhHy8tOUSTrw9lsqKN4HS3tpJplAKVUyawxhDtYIaWBHSEfj9Proom1p3zw+VGO2+GGNCn5+W0t7MjSXo5WQJgPb9kO4lJqsU1QoVrE2l6GnX/Co9UV+smx8RgK8eD8b9/Zxxfz9nPBzqhl9nD20y8OFZGEuwceZg+DqYo7BCjnUnE5s9vjuj4KcdFEoVXv/1Cp7ZEInfL6Q2eVxuqQxTfjiNsP87hHMJ+Z04QkK6npzSKtyu2dQ5zLfzgx83G1NwHFApVyKvrLrTX5/oh1KZArKaC1otpb0Btft+rqQUaXFUhOiXqFT13sxgDxtwHKfj0RiORwe648dpA/HjtIH45skQhHr20OhxJlIx5t+nbvK9/mQC8mp6kZH6KPhpB47jYGtuBBUD3t55FRtONYyy04sq8cSas4hOK0ZhhRwzfjqPo7dzdDBaQrqGs/HqCwh9XK1ga27U6a9vJBHBpSZtKbWQUt+6K37Vx9JY0qDMemMG9lSfvNAFMNKdRKWqy7tTievOM6GvM/q7W6OiWonvj8Tpejh6ifb8tINYxOH/Hu4HC2MJ1p1MxJK/b+LPK+mQiGuvbqTU1Ld3szGFn6MFjt/JxeyfL+LbqaF4oL+LDkdPiGE6Fav7ZnketmbIKK5CakEFBmh4Rc5QZJdU4d2dV1FUKQcABLlYYenkvhCJ6KptXUKPnxbKXPP4FM2raUUoqZLDinLxSTfAFzsIqSn3TrSP4zi8HRGIZzZEYltkCqaFecK/Ju2WqNHKTztxHIf37g/Cm/eqSxReSy/GlZQi4Su/vBq+Dub446VwrJ8xCA8Fu0KhYnjt18vNpsoRQhp3qabE9dA2NirtCMK+n/yut/Lzx6U0HI3JFT7DtkWm4Fo6Nee8W22Za82CH1cbU/jYm0PFgHPxtPpDur6SKrnQDLo/FTvoVCP87THCzx7VShWeWncON2uKThA1WvnpABzH4fVx/hgf5IT0ovq9PyRiDkO97YS0iG+eDIG5sRi/nk/F2zuvorxagZnDvXUxbEIMTpVcKXSx7uNipbNxdOVGp/yG/KfDPHEzowRRqUWITitCMKWt1JMrlLnWvHLbcD97JOSV43RcHu7r46ytoRGiF66lFYMxwL2HKewtNLtIQDrOt1NDMP2n87iRUYKpa89i06whXS5Toa1o5acD9Xa1wr29nep9jQ1wrJcPzqfKzR6pDng+/usmrqXRVVVCNBGXUwYVA3qYSTXaZK4tfKPTrhb8MMaE4OfhUDeM6uUAgCqUNSanlSs/QG3q2ykNKoQSYuiE5qZ04UQn7CyMsW32UAzq2QMlVQq8svUyquRKXQ9LL1DwowN8qtykYFcAwJf/xeh4RIQYBr7KW4CzpU4rB7n3UAc/aYWVLRxpWLJKqpBbKoNYxKGvqzVCa05aKPhpKKdEsx4/dYX72EHEAfG55cgqrtLW0AjRC9E1nxuhFPzojLWpFD8/PwSu1ibILK7ClnPJuh6SXqDgR0c4jsP8+3pBIuJw4k4uVQAiRAMxWeq85UBn3aW8AbVpbxnFlV2qf1dUTRnmACdLmBqJ0d9dvUk5IbccxTUFEIiasPKjYcEDQN2IsJ+bek5P0+oP6eL4Yge08qNbZkYSzBuv3pf+w9E4lFbRZzkFPzrU084cU4d4AACW7b9NDRMJaUHdlR9dsrcwgqlUDMbQYJ+fIYviKzN52gBQp03wgd7VmvuIGr9y49SKPT9AbeobBT+kK8sqrkJ2iXoVuY+rbi9WEeCRAW7U/LQOCn507PV7/GEiFeFyShH2RmfoejiE6LUYPQl+OI7rkkUP+DSVkDqVmfirttGU+iZgjAlBr1sP01Y9dkSdfT90wYt0VXxz015OljAzotpauiYRi4Tmpxuo+SkFP7rmaGWC50eoix+89Xs0BUCENKGgvFpINeqlBz0LPLpY8KNUMaH4Cr/yA9Q2J+SbFRL1e1FWk+7obN26lZ8BPXvAWCJCTqkMcTll2hgeITpHzU31D9/8tLxaiR+Odu/mpxT86IF543thcoi6/88bv13B4j3X8fV/MVh/MoHy7Ampcbtmv4+nrRksjHV/JZFf+UnrIsFPXE4ZyquVMDcSw9fBQridb04YlVpEKxU1MopqGpxaGsNYIm7h6PpMpGIM8bYFQFXfSNclrCJTc1O9wTc/BYCt51KQVtg1/na1BQU/ekAqFuGbJ0IwLcwTjAE/n03Gd0fisPSfW5i69ly3X54kBNCflDeep6063Skpv1zHI+kY/MlKP3driEW1lfT6uFpDIuKQVyZDBlUoA1C7z8vVpnUpb7xhvvy+Hyp0Q7oepYoJjZGp2IF+GeFvj2G+dqhWqrDiUKyuh6MzFPzoCZGIw9IpfbHssf6YHt4T08N7wt7CGLcyS/DEmrPILO46m6oJaQs++AnUk+DHy94cAJCY1zWCnyvCldr6TfBMpGIEuqjnnK8G1xWVVslxI6MYNzKKkZRX3uwqVwa/38emdSlvPH7fz7mEfCiUXadaICEAEJ9bhjKZAmZGYvg76sfnNam1IEK992fX5TTEZpfqeDS6QcGPHuE4Dk8M8sAnk/vik8l9sePFcLhamyAhtxwzfjpPfyRJt6Yvld54fGpYUn4FlCrDTwdrLk0luKYAQnQXrfhWrVDhvm9O4IHvTuGB705hzPJj2HExrcnj+eDH1bptKz+9Xa1gYyZFmUyBaGpyTboYvi9YX7f6q8hEP4R69kBEHyeoGLC8m/aZpOBHj3nbm2PHS8Nga26EO9ll2Hm56T/GhHRlKhXDnWz9WvlxtTGFkUSEaoVKOBk2VHKlCrE56vnt49ow+Olb05vmVmZJp46rs1xJKURmcRUkIg7WplIAwD/XMps8PqO4bZXeeGIRh2G+dgCo5DXpeqi5qf6bf18ARBxw4EZ2t2xiTcGPnnOzMcXLY3wBACsOxaJKrtTxiAjpfGmFlaioVsJIIoKXnbmuhwNAfQLrZacuehCfa9hVuxLzyiFXMlgYS+DeyAk9H3Dyq29dzel49d6b+/u54Lc5QwEA5xMLmmxgm15T8KCte36A2n4/VPSAdDXU3FT/+TtZ4pEB7gCALw/c1vFoOh8FPwbgmaE94WptgsziKvxyNlnXwyGk0/GV3vwcLCAR68/Hlo+9OvUtIdew9/3wKzoBzpbguIZpKnxp8dxSGfK7YAEWfvVluJ8dApwsYW9hhEq5EldSChs9vnbPTzuCn5qiB1dSClFRrWjz8xCiT0qq5LiZof48oTLX+m3eeH8YiUU4HZePU7Hd6yKM/pxFkCaZSMWYd28vAMAPx+JQXNGw/HW5TIH1JxOEk0RCuhJ9K3bA83ZQr0Il5Bn2yk9LlfTMjSVCae+YLrb6U1olF9I+hvvZQyTi6lRja3hCIFMokVvTb6o9Kz897czgZmMKuZLhfGJBm5+HEH1yLj4fKgb42Ju36/eDaJ97DzM8HeYJAFh24HaX2LuqKQp+DMQjoW7wc7RAUYUc0zeeR1FFtXBfUUU1pq2PxNJ/buGRH89QDjnpcm7z+31c9Cv48ekiFd80CS4DumjqW2RCAZQqBi87M7j3UAd4I5pJScuqKfdtIhWhh5m0za/LcRxG+qtfZ+fl9DY/DyH6pHYV1V7HIyGaePUeP5gZiXE1rRjztkdB3k0Ka1HwYyAkYhFWPBmCHmZSRKcWYeraczgTn4cz8XmYuvaccOWyolqJmZsu4NDNbN0OmJAOdFtIy7LS8Ujq83HoGmlvQiU9p6aDHz4w6morP6caOVkb5qcuRhCdVozSqvor7XV7/DSWItgaz4b3BAD8FZ2BGxlU9Y0YvlN1UkiJ/rO3MMZXjwdDKubwV3QGXtpyqVvsLafgx4D0dbPG9rnhcLA0xu2sUjy9LhJPr4vE7axSOFga4+/XRiCijxOqFSrM3XIJe6LoaiIxfFVyJZLy1Z2o9S3tzbcm7S2zuMpg922UVMmFE/rAZoJLYeWni/WF4K9Uj6gT/Lj3MIOXnRmUKobIhPopaRk1xQ7as9+H18fVGg8FuwIAvjzQPUvOkq4jq7gK8bnl4Dgg3IdWfgzFxH4uWDt9EIwlIhy6lYNZmy6gXGaYf8801erg58SJE5g0aRJcXV3BcRz+/PPPevczxrB48WK4uLjA1NQU48ePR2xs/S6yBQUFmDZtGqysrGBjY4Pnn38eZWWGnTPfWXo5WeKPF8Mxws8e3vbm8LY3x3A/O+yYG46+btb44ekBeCTUDUoVw7ztUdgWmaLrIRPSLnE5ZVCqGGzMpHC0NNb1cOqxMTMSUp8MdfXnTs1KjrOVCaybSePiA6PY7FKoukhueE5JFWJzytQna771r1Q3VY2tvT1+7vbmvb0gEXE4FpOLyIT8DnlOQnSBv5DQ38262c8Son/GBjhi86whsDCW4Ex8Pp7ZENno/vKuotXBT3l5OYKDg/HDDz80ev+yZcvw3XffYfXq1YiMjIS5uTkiIiJQVVUlHDNt2jTcuHEDBw8exN9//40TJ05gzpw5bf8uupmedubY8kIYjs4fg6Pzx2DrC0OFbvMSsQjLHw/Gs0N7gjHgvd3XsPMS9QcihiumTkpWe9OMtIFPfTPUfT+aNo/1sjODkUSEimolUgsrOmNoWnc6Xn2y1s/NGjZmRvXu41eCzsQ3Efx00GZuL3tzPDnYAwCw7EAMGOsagSXpfmi/j2Eb6mOHrS+EwcZMiispRXhy7VmhuEtX0+rgZ+LEiVi6dCkefvjhBvcxxrBixQp88MEHmDx5Mvr374+ff/4ZGRkZwgrRrVu3sH//fqxfvx5hYWEYMWIEVq5cid9++w0ZGRnt/oYIIBJx+GRyH8wa7g0AWHU8nv6gEoMVo2fNTe/GFz0w1JUfodhBC8UkJGIR/B3Vgd6tzK6R+nYhSV3KeqhPw/0J4b524DjgTnYZckpqL97V7vkx6bBxvD7OHyZSES4lF+LI7ZwOe15COgtjTFglHUHBj8EK9rDB9jm12yueWHNW+MzrSjp0z09iYiKysrIwfvx44TZra2uEhYXh7NmzAICzZ8/CxsYGgwYNEo4ZP348RCIRIiMjG31emUyGkpKSel+keRzHYd69/jCSiBCXU4abXbQzO+n6alcm9KvYAU8oeqBH5a6VKoZtkSk4FtPyiXRryogHdLGiB811orcxM0JfV2sAtStEQMf0+Lmbk5UJnhumvlj15YGYLpNWSLqP+Nwy5JTKYCwRYUDPHroeDmmHAGdL7JgbDjcbUyTmlePxVWcMNrOhKR0a/GRlZQEAnJyc6t3u5OQk3JeVlQVHR8d690skEtja2grH3O2zzz6DtbW18OXh4dGRw+6yrEykGBeonus9UbSqRgxTTFZtA0595K1n5a7lShXe+O0K3tt9DS9svojk/KbHxRjDLX5+nVoOLoWKb9mGfzGlSq4UAuumOtEL+35i1XtxGGNCwYOO7mHy0mhfWJlIcDurFHuj6fOaGJbfL6rT64d428JEKtbxaEh7edmbY8eL4fBxMEdGcRUeX31WaIbdFRhEtbeFCxeiuLhY+EpNTdX1kAzG5BB1JaG9URl0NZEYnKKKamSXqHOO9TX44Su+JeSW6zy9tEquxIu/XMLfVzMBAAoVw9cH7zR5fGZxFUqrFBCLOPg6mrf4/HzRg67Q6+d6ejGUKgYHS2O4WDeewlZ33w9jDEUVclTWlIF1buIxbWVtJsXc0b4AgK8OxuBYTA6O38kVvq6nUyls0ryU/AqdlCnOLK7EpjNJACCk2xPD52pjit/nhqO3ixXyymSYuvYcrqQU6npYHaJDgx9nZ2cAQHZ2/R4z2dnZwn3Ozs7IyamfiqFQKFBQUCAcczdjY2NYWVnV+yKaGRPgCEsTCbJKqhBJXcSJgeFPsj1sTWFhLNHxaBrnaWcGEQeUyRQ63xy68kgsDt/OgbFEhIUTAwGoV32b6iHDX8nzsTeHsaTlq7X8yk9SXrnB94Lge6MFu9s0WUhjkFcPGElEyCyuQkJeubBKZm9hrJWr2zOHe8HB0hipBZV4buMFzPjpvPD14MpT1MCaNIoxhu+PxGLUl0fxzPrITr8I893hWFQrVBjiZYsxAQ6d+tpEu+wtjPHrnKEY4GmD4ko5nlkfibPxhl+VskODH29vbzg7O+Pw4cPCbSUlJYiMjER4eDgAIDw8HEVFRbh06ZJwzJEjR6BSqRAWFtaRwyEATKRi3N/XBQCo7w8xOEJzUw1SsnTFWCKGew8zAEC8joseHLqpvrC0dEpfzB3ti0k1PWSWN9FDhv8jNsBTsxx9B0tj9DCTQsXUJcgNWXSaOiAM9bRp8hgTqRiDavYvnIrNw3eH1W0b7gnUzgmemZEEnz3cD8EeNujjaiV8OVupV5l+v0hZD6Q+xhg+33cby/9Tr/BeTC7EvuuNbyHQhoTcMiHl7e0JAXpZkZO0j7WpFL88H4bhfnYor1ZixsbzOHwru+UH6rFWX0otKytDXFyc8O/ExERERUXB1tYWnp6emDdvHpYuXQp/f394e3tj0aJFcHV1xZQpUwAAQUFBmDBhAmbPno3Vq1dDLpfj1VdfxdSpU+Hq6tph3xipNTnUFdsvpuLfa5n4cFIfmBpRPm5XUCVXYvqG8/C0M8OXj/Xvkn909L3SG8/HwRwpBRVIzCtv0C+ms+SUViEmuxQcB4wLUu+7fOveXth3LRNHY3JxMakAg7xs6z1G6Mbur1l1Jo7jEOBsiXMJBbiVWYK+btYd+010oug6Kz/NGe5njzPx+Vh7IgHpRZUwEovwxvheWhvX+N5OGN+7/r7ZKymFePjHM/jvRjbKZQqY6+kqqKErkynw1u9ROH4nt8F9/d1t8P1ToXC06th0x/b66r87WHMiAQAwwNMGl1OKsPy/GNzX2wkSsXZ2NkSlFuHN36OQUVQJhZJBqWIYH+TY4POFdB3mxhJsmDEYr/16BQdvZmPuL5fwzZMhwgU2Q9Pq34yLFy8iNDQUoaGhAIA333wToaGhWLx4MQDg7bffxmuvvYY5c+Zg8ODBKCsrw/79+2FiUvuBsXXrVgQGBmLcuHG4//77MWLECKxdu7aDviVytzBvO7j3MEVJlQKbzybpejikg1xIKsD5pAL8cSkNx2Ia/rHuCq6nq1d+glz0d+UHAHzsayq+5epuNYRfxentYgVbc3XPGi97czw6wB0A8NuF+qsGeWUyIa1wWCsCNn7fjyFXfCsor0ZKgbpXUT/35gM4ft8PX+712fCeHVrpTRMhHjboaWeGSrkSB28a9hVXfVVUUY1p6yNx4EY2quSqBl/nEwvw+JqzSC3Qnx5XqQUVWHMiHgDw2SP9sHnWEPQwkyIhtxw7L2unv9/Z+HxMW3cOCbnlqJKroFAxmEhFWBARqJXXI/rDRCrGj9MGYHKIKxQqhtd/u4Lfzqfoelht0urLR2PGjGk2n5TjOHzyySf45JNPmjzG1tYW27Zta+1LkzYSizjMG98L83dEY9WxeDw1xBPWptR92dDxV64BdXPE0b0cIBLp3+pPYXk1vjoYg9IqBQCgl5MlXh7j2+JKVZVcKexJCWkmNUkf+PBFD3RY8e1UbOM9Nh4b5I7tF1Ox/3oWlk7pK+xVOVMTLAW5WMHewljj1xHKXWd3XPDDGMPOy+k4GasO4o3EIswd7QM/R+2s+PG/Oz4O5i1+FvZ1s4aViQQlVQqYG4nx8hhfrYypORzHYXKIG747HIs9UemYEurW6WPoyoor5HhyzTnEZJfCxkyKH6cNgKetmXB/UYUcL229hOT8Cjy++iy2vBAGv5qeV7r0zaE7kCsZRvrb46khngCAV8b6Yek/t7DiUCwmh7h16N60E3dyMfvni5ApVBjuZ4f/e7gfxCIO1qZSWJrQOUV3IBWL8M0TITA3lmBbZAre3XUNZTIFXhjpo+uhtYpBVHsj7fdwqBv8HS1QXCnHupolcmLYolJrN7HfyizB39cydTiapn2+7za2nEvBnqgM7InKwJcHYnDgRstXr29klEChYrC3MIZrB1fW6mi1jU51s/LDGGuyu/pAzx5wszFFmUxRr4HmaSFYal2aHp+C2FEV3xhj+GJ/DObviBbeIzsupWH+jqta27jNFzsIaSHlDVBfPBoToG4ZMHuUD+xaESh2JL5y54nYPOSXdc2u67ry89kkxGSXwsHSGL/PDccwX3u49zATvvq6WWPH3GHwc7RAVkkVnlxzVufV9+5kl2L3FfU+3gURAcLtzwztCVdrE2QWV2HLueQOe70quRIL/oiGTKHC+CAnbJgxGD3tzOHew4wCn25GJOLw6ZS+mDtKHfB8eSAGaYX6syKqCQp+ugmxiMP8mg/IDacSkVNa1cIjiD5jjAkncGNrqut89V8M5EqVDkfVUFxOGXZcUqdbvT7OHw/0UxffWP5fDJQtlF7nr86HeFjr/X4mvtFpamElqhWd/zNIzCtHRnEVjMQiDL4r714k4oS8bL7oSd1u7MNa2Y29l5M6+MktlaGgvLpd41apGBbvuYHVx9WpOzOHe+H9+4NgKhUjKrVIayle0WlFADRfUfxwUm/8OG0AXrvHXyvj0YSvgwX6uVlDqWL4V08vdGhLelEl9l3LbPLrxJ1cKNr42ccYw581vxfvTAgU3t93c7Y2we9zw9HXzQr55dV4at05XEru3AqqVXIlDt/Kxr5rmfjkr5tgDJjY1xn96wTxJlIx3hivfp/+cDQOpVXyDnntn88mIbtEBjcbU3z/dCj18unmOI7DuxMDsSAiAKufGSgU/TEUtGuyG7mvtxNCPGwQlVqE17ZdwYbnButt+WDSvMziKuSVySAWcVj+eDAiVpxAcn4F/r2Wickh+pMS8/XBGKgYMD7ICW/e2wslVXKcjs9DXE4Zdl1Ow+ODmm5YzJ+gtrQhXR84WRnDzEiMimolUgoqOj0l5jRfta2nTaMFTaaEumL18XgcvZ2L4go5iiqrkV5UCamYw5BWblI2N5bA09YMKQUVuJ1VgmG+rQue6vrlXDJ+OZcMjgM+ndIPT4epU3eKKqvxw9F4fHkgBuOCnCDuwHTOMpkCl5LVvSr6a/jesrMwxv01gbsuTQ5xxbX0YvxwNB7D/eyFoLsrK5cpMOWH0y2WkR/VywFrnhnY6oI+NzJKEJ9bDmOJCBF9nJo91tbcCNtmD8Xzmy7gQlIhnll/HuumD8IIDQuGtEduqQzTfzpfr9GkiAPeuq9h8Y1HB7hjzYkEJOSWY93JRLx5b/sKdJRUyfHjMfUFijfG+1PgQwCoA6BXxvrpehhtQis/3QjHcVg6pS8sjSWITCzAtPWRKKpo35Vbohv8qkigsyXsLIzx6ED1pvYTd/SnD8jVtCL8ey0LHFeblmFlIsVLNY0cVxyKhUzRdK8YoQ+Lh422h9puHMfBW4epb6eb2O/DC3S2QoCTJaqVKvx7PRMna44P9ezRpsph/L6f25ltT30rlymE0tEfPNBbCHwAYM4oX1ibShGbUyak9nSU9ScTUFqlgI+9OfoZWLW6xwd5wNfBHFklVXhizTm967jOGOvwVMWfTiUit1SGHmZSDPGybfTLVCrGiTu5mP5TJEpaudLBr4aOD3LSKH3LykSKn2eFYaS/PSrlSszadAEHbmRBpWJNfrVXelElnlxzFrcyS+rNw+IHeze6L04iFmH+fTWZHicT2p0mue5EAooq5PBztMAjtN+MdAF02b+b6etmjW2zh2L6T5GITi3Ck2vO4ZcXhsDRUr/3VJD6ovhVkZrAYKSfA9YcT8DpOHUnel2niZXLFPhw7w0AwMMhbsLJMgDMGOaFn04nIr2oElvPpWDWiIYdwQvLq5Gcr84hNoSVH0Cd+nYjo6TTix4oVQxn4hvf71PX5FBXLNsfg4W7rgm3NRUstSTQ2RIHb2a3q+LbT6cSkV9eDS87M0wP71nvPmtTKV4a44vP993GNwfvYEqIa4eU7S0or8b6k4kAgDfv69WhK0qdwdpUiu1zwzF9w3nczCzB1LXnsO+NkXDt5OpzjckqrsKLWy5BxRhWPTOwQyriFZZXY23NHtWPJ/fFQ02U1b2UXIDnNqpXY2ZuvIAdc8M1Kv6iVDHsjc4AADwUonnJXlMjMdbPGIQ3fo3C/htZmPvLpSaP5Thg9kgfvHd/kMbPX1eZTIGpa88itaASbjam2PJCmHChpTkT+zqjn5s1rqUXY/XxeLz/QO82vf6NjGJsOKX+nZl/X4DWymcT0pnoXdwN9XO3xva54XC0NEZMdimeXHNOKONKDEP0XRu2+U70WSVVOm+0yZeMvZJSBAtjCf53V8qFiVSMN8apb/vhaBzKZIoGz8GnvPnYm8PazDA20/JFDxI7ef6vpxejpEoBSxNJsysZj4S6o0eduTQzErc5lUtY+Wljxbe6J7Vv3hcAaSMnVDPCvdDDTIr0okqhMl17/VjzfuvjaiU0fzY09hbG+HX2UPRxtUJxpRwrDt3R9ZCQkl+Bx9ecQVRqEa6mFeOJ1WeR2AEXAVYdj0epTIHeLlZ4sJn36sCetvhtzlBYGktwKbkQf13N0Oj5zycWILtEBisTCcYEtK5xrbFEjO+fDsVTQ5pO3QUAxoBNZ5LavPdmw8lEIfDZ8WK4RoEPoF6Nnlez92fn5fQ27Qe9lFyAqWvPoaJaiSHeti2mBRJiKGjlp5vq5WSJHS+GY9r6SCTmlePxVWfw+4vhBrdprTtSqhiu1XSn51d++E70Z+LzcSY+r1P2nJRUybHiYCxS76rycie7FMn5FbAxk2LTzCHwsG34nnp8kDvWnohHUn4FNpxMFDbo8qJT639/hqC23HXnpr2drln1Gepj1+xVWWdrE0S+N14INs2MxG3O3ed7/cRml0KlYq0usa7JSa2pkRgP9HcRKgWO6tW6k1PeX9EZ+Cs6AwwQmlcuiAjQy7LwmrI2k+KTyX3x6Koz+ONSGuaM0l5Z8JbcyS7FM+sjkVMqQ087M4g5Dgl55Xh89Vn88vyQNvfoSi2owOYzSQA0+3n1cbXG3NE+WP7fHXz13x1M7OsCI0nz13f5lLf7+7nAWNL63wWJWITPHumPhfcHQaFsPL3t8dVnEJ9bjv3Xs5rd49iYgvJqrDupvkjw7sTAVq/wje7lADtzI+SXV+NUXB7G1lQt1MSFpAJM33AelXIlBnv1wPoZg3SeUUBIR6GVn26sp505drwYDl8Hc2QUV+HTf27pekhEA3E5ZSivVsLMSFwvyOFTnvh+L9pUUF6Naesi8dPpRBy8mV3vKzm/Ag6Wxtg+JxwhTQQvUrEIb9XkpK87mdCgalhUqnpDenALDSj1SW2j085d+eFLXGuSwmYkEcHW3Ai25kbt2rTsZWcGI4kIFdXKBsFvSzKLK7GJP6md0PxJLV+848CNLFTJm94f1pSs4irM3xGN/2rem9UKFcK8bTG6jYGUPhnYswfu7e0EFQO++k83qz/X0orx5JqzyCmVIcDJEjvmhuP3F8MR5GKFvDIZpq49hyspha1+3sS8ckxdew4yhQpDvGw1XpWZOdwb9hbGSCmowPaLqc0eK1Mohap5rUl5a4yViVT4vbr7a0rNe3hPlGarUXXVXal8oA2rtBKxCA/2Vz9ubytff9n+26iUKzGqlwN+nhUGKypnTboQWvnp5lysTfHjtIGY8O0J7LuehejUIoO62m4orqQUws3GFI5W7d9bxae89XOzrrdnYYSfPb48EIOzCflQKFVay83OKanCtPWRiM0pg525Ed4Y718vbUks4jA2wBEOls33Q3mgnwtWHYvHzcwS/Hg0Dh88qM5JZ4whOs3wVn68a1Z+8surUVwh75R0vSq5EheS1CeXze336WgSsQj+juo9TrcyS9HTTrNUHAD47nAsqvmT2haCEL5HUXpRJQ7fysED/Vt3Avjt4VjIFCr0d7fGU0M8IRZxGBfo2GWuYM+/LwCHbmVj3/UsrD+ZABszo2aPtzCWYGygQ5tWOe52IakAMzdeQJlMgWB3a2yaOQQ9zNWv/9vsoZi56TwupxThmfWRWD9jMMJ9NesndTurBM+sP4+8Mhm87c2xYmqIxj8vc2MJXrvHDx/uvYHvDsfisQHuTVZ/OxaTi5IqBZysjBHm3bpeV60xOcQNXx28gzPxecgpqdL4b0B6USV+runT056Vysmhbth8NhkHbmSholoBM6OWT/vSCitwIakQHAcse7R/qyvoEaLvKPghCHC2xMOhbth1OR1fHojBlhfCdD2kLuVaWjEeWXUGgc5W+Pf1Ee0+8bqaXgQADVZV6naiv5ZejFDPHu16nab87/coxOaUwdnKpF2dzkUiDm9PCMBzGy9g45kk9HO3xuQQN2w4lYiC8mpIxVybU2Z0wcJYAicrY2SXyJCQV6a1+a/rYlIhqhUqOFuZwNdB8wCkIwQ6W+FGRgnOxudhQl9njR6TkFuG3y+mAQDenhDQ4u+CSMThoRBXrDoWjz+j0lsV/KhfS331f/GDvTGolSW9DUHdz+6lGq7ch3nbtrvNQXGlHLN/vogymQJDvG2xYcagepXSrM2k+OX5MMz55SJOx+XjuY3nseqZAbgnsPk9I1GpRZjx03kUV8oR6GyJX54Pa/Eiyt2eGuKJdScTkFZYiY1nEvHymMZL8fIrIQ8Fu2q18IWnnRlCPW1wJaUIf13NxPONFHhpzOYzSR2yUhnqYQMPW1OkFlTi0K2cJotG1MUXgRjqbQdnPW8wTUhbUNobAQD8b3wvSMUcTsXlCWk0pGMcupUNxoBbmSW4kdH+0rR8FTTfu4IOsYgTeq5o62d4KjYPp+PyYSQWYdvstgc+vNG9HPDYQHcoVQzztkdhzs8XhZO4V8b6GVw/idpy152T+sbv9xnmZ9fpqxl8qtCvF1KRoWHBlK8O3oFSxTAu0FHjYGRyzesci8lBcYXmm8a/bsNrGaJ3JwZiUrArRvdyaPHLooPaHNQtfbx55pBGS0SbG0uwYcZg3NvbCTKFCnN+voQ9Uekokyka/ToVm4dp686huFKOUE8bbJ8T3urAB1CndvK9b1Yfi2/0PVNaJcehW+oGup3RF6029U3zsu0navanPTO0Z7t+tzmOw+Rg9evvvpyGMpmixRTSPVfUwc+U0PalAxKir2jlhwAAPGzNMC2sJzadScLHf93A9jnhQgoDaR++DDGgvqLWt529RVIL1MGPZyOFBIb722P/jSycisvDqx3cjZ4xhmUHbgMApg317JAGixzHYdmj/WEiFWHLuRT8d1N9QjL/vl4G2TzNx8EC5xIKENdJvX5as9+no43yt0eYty0iEwvw7aFYfPFY/2aP/+9GFv65mgmOA+bX9H3SRKCzFQKdLXE7qxR7r2bg2aE9W3zM9fRi/N2G1zJEjpYmWPlUqEbHXksrFtoczNx0AbteGtbqE+uc0qp6pY+bS4kykYrx47QBmL8jGnuiMvDGb1EtPv9wPzusfXZQm/pP8R4KdsPqYwmIyS7F6hPxeGdCYL37D9zIhkyhgo+DOfq4an91+YH+Lvjk75u4mlaMxLzyFiu25ZbKcLumjPwwDdMFmzMl1BXfH43D0Zhc9P3wADhO3VursVWo21kliMkuhZFYhAkGWhGRkJbQyg8RvDLWD3bmRriTXYYn155FTkmVrodk8MpkClxJKRL+vTcqA8p2NL1TqhjSCtVX2RsLfviT4MvJRaisbv0G8ebsv56Fq2nFMDcSd2hgIhJxWDK5L167xw/WplJ8NKk3Xr3H3yD3ZfClx4/cytH6axVVVONaunpvVGfu9+FxHIe3a04qd1xKRVxO0wHfnqh0vLT1MgBg6mDPVqcz8lWyVh2N06jwwZcHYgAAk4NdDSp1Utv6uVvj97nhMJGKcCWlSHj/tMYPR+JQKVci2MNGo9LHUrEI3zwRgpnDvVpML3so2BUbZgxuV+ADqFfB+cbKG08nNvhbxq/ATAlx65TPGXsLYwz1Ua8+Ho9p+bOBv2DW28UKdhatX/26m5+jJe7tXfuzYgz45uCdBoVmgNrCDGMDHWBtSkUOSNdEKz9E4GBpjO1zh+KZ9edxJ7sMk74/BT9HC4g4DpOCXfFEK8t0GrIt55Kx77q6EpBULMIrY/0wuA2pM+cT86FQMbjZmKK0So6skiqcTyzQePPv3TKLK6FQMRiJRXBqZOOsl50ZXK1NkFFchQtJBW0uD3w3hVKFL/9Tn1A+P9IH9h3wB7kujuPw1n0BePPeXgYZ9PAi+jjjgz+vIya7FLcyS7R64n02Ph+MAf6OFo2+FzrDwJ49MD7ICYduZePzfbew9tlBDTZmb4tMwft/XgNjwCOhblgyuU+rX2damCfWnUhARnEVtpxLxgsjfZo89lxCPo7fyYVExDXoMUUAfydLjA9ywt9XM7EnKgP9W9FEOC6nFNvOpwAA3oloec8WTyTi8OGkPlg4MQgq1vjFH45DhxRi4I0LcsQATxtcTinClwdisOyx/uA4DulFlcKKqSb7XzrKCD8HnI7Lx6m4fDw3vPl9P8KKrn/HXdRYN32QcOHgsdVncD29ttDMpeRCrDoWj0q5Qmij0BnpgIToCq38kHr8HNX9fzxtzZBdIsPpuHycjM3D239cxdcH74A18YerK0nILcOHe2/gdFw+Tsfl41hMLv7v37aVAT8Vq27OOKqXAybWpBDsjdY87/tuKTUpb+49TBu9ispxnLAK0JH7fnZeTkNCbjl6mEkxe6RmG3bbwpADH0C90Zsvy9uW0raaYozh57PqSlAj/XVbtnlBRABEHHDoVg7m/xENRZ1mimtPxOO93erA59mhPbH88eA2VSE0kYqFho0/HotvsmEkYwzL9qtTM58a4tmqKnTdCX9i+1e05ivRt7NKMHVtJORKhpH+9hjWhtVGI4kIJlJxo18dGfgA6s+Sd4SVyTQs/ecWUgsqMG3dOaiYOnD30rBhaEcY7qe+4BVZU42zKYwxnI7Lr3lMx67o8nO9IEI9Lz+fS8Zv51Mwbf05HLqVjdNx+SipUqCHmRT3BGreE4gQQ0PBD2nAw9YMf78+Aj88PQDfTg3BnFHqq6zfHY7F239cxS9nk7AtMgXZXTQtjt+UHeZti2WP9YeIA66kFCE5v/Wb2Pn0hRF+9sLG7X+vZUGmaFtKGr/fp7HGoTz+auGpDgp+quRKrDgUC0CdGtnY5mZSa0qo+sRyb1Q6VO1IcQSApLxynLiT2+Ciw6m4PJxNUBeemDXCq12v0V4Bzpb4+okQiEUcdl1Ox4tbLuGXs0n44M9r+L9/1YHIy2N88cnkPu1qLPrYQHf4OJjXNH5MbPSYQ7dycDmlCCZSEV67x/D2jHWW0b3UKU05pTKcS8hv8fjo1CI8ueYc8spkCKz5eRuCMB87fDRJXUJ/w6lE3PvNcSTlV8DD1hTfdPL30MfVGtamUpTKFLjaTLphcn4F0osqIRVzGOylnYqRo/ztMdTHFtUKFd7ddQ1VchVG93LAt1ND8O3UEOx6ebjBFZshpDUo+CGNsjKR4oH+Lpgc4ob37g/Cxw+pU1V2XErDoj038N7ua3jgu1O4ldn+6mX65Hp6sbAp+6OH+uCJQR7C1bfWNonLKa3C7axScBwQ7muHMB87OFoao7hSjjPxLZ9wNCalmWIHPL7i242MkkZzultry7lkZBZXwdXaBM9osNm8u7sn0BEWxhJkFFfhYnLrGzzyTsfl4f7vTmL6T+ex5O9bQgDEGBP2tEwb6gn3Hk2/FzrLlFA3rJo2AEZiEQ7dysGiPTew5Zw6PertCQF4e0Jgu1f1JGIRFtQ0xl11LA7/XM2sd79SxfBlTUGOWcO9O6SnVldlJBHh/pqmmX9eaX4lukquxItbLrW7CpuuPDfcG1/WXMSqkqvg52iBHXOHwdOuc39v1NU41as/p5tpRM1ftBrg2UOjnjxtUXe/HqAuyLBu+iBMDnHD5BC3FgsyEGLoKPghGpkxzAtrnx2IB/u74P5+zvCxN0demQxPrjnbpg7e+mpZIxul+RSRP6PSW5X2d7YmwOntYgVbcyN1g8UgdSrBqWb++DUnpUBd7MDD1rTJYxwsjRHobAmgfqW5tiitkuOHo3EAgHnje9HVQA2YSMVC35s/W1Hatq5DN7Mxc9MFVNQUrfjpdCLe2XkV2SVV2HU5HVfTimHWwYUn2uu+Ps7YNjsMU0JccX8/ZzzQzwUrnwptss9KW0zo64zJIa6QKxle+/Wy0McHUG9iv5NdBisTCeaO8u2w1+yq+JXo/dezmi0i8cvZ2osfvzwf1inNezva44M8sHHmELwwwhvb5wzVWe8aPlXwdDOfy51VwXGAZw8se7Q/Fj3YG99NDYWRhE4HSfdBBQ+Ixu7r44z7+qhP6oor5EIH72nrI7F+xiBhxcFQnY3Px4lGNkpH9HHCe7tFiM8tx42MEo1LVZ+pyduu+0dsuJ89fj2f2ub9OJqs/PCvczurFKfj8vBg/7Zv6l13MhGFFXL4OpjjkQG0AVZTk0Nc8celNPx7LRMfTerTqhOLKymFeHHLJShUDBF9nDAmwBHv776G3y+mCQ1CAeCFEd4dXniivQZ52Wq1pw7Hcfj6iRCYSsX47UIq3v7jKsplCkwL64mvD94BALw0xs8gT9A72xAvW7hYmyCzuAr/3cxudPN/SZUcPxyrufhxb692NUbVNb7XkS7VrcZZUa1osLKjVDEhK2B4BxY7aMoTg7tPESNC6qJQn7QJ38F7uJ8dKqqVeG7jBRyuaRpniOr2sLl7o7SliRTja1Zs+M7XmkguUO8R6l2nj0S4jzrt4XZWKXJLZa0epyZ7foDaP7L8xtm2yCuTYf3JBADqfh5t2ajeXQ3ztYe9hTGKKuRCs0JNMMbw2b7bQuDzw9MD8NQQT/zw9ADYWxhDLOIgFnEIdLbEC6OarnjWlYlFHD57pJ/Qo+Tjv27i2Q2RSCushKOlMZ4b5qXbARoIkYgTSoh/dzi20cIH62uamfo6mOORULr40V5edmZwszFFtVKFC0kNMyZuZpSguFIOS2MJ+rezHxwhpGl0NkParG4H72qFCnN/uYS/WhEc6JODN7NxpZmN0nzq296oDI03sfP7bepenbezMEbvmnS61qaklckUwnO2FPwM8baFRMQhpaACKfkVrXod3vdH4lBRrUR/d2shjYtoRiziMClYvadiTyt+J47fycX5xAIYSUT46KE+QsA5sZ8LLn4wHvH/dz/i/+9+7J83ClbduPAEx3H44IEgoQJcZGIBAOD1cf7NNt0k9b0w0hs2ZlLE5ZRh1+W0evfllsqwvqaZ6YIIuvjRETiudt/PmUZW//n9PmE+djTfhGgR/XaRduE7eE8OcYVCxfD6b1fwW00fCEOhVDEsr+lh09RG6TEBDjCWiJBVUiWknrWED1RszY3q3c5XY2tt6hu/6tPDTNriia+5sQShnjbq12nDvp/Uggpsi6zZsB7R/s3q3dGUmoD54M0slMkULR6vUjEs269+H84I7wkX66b3dRH1ieS88b3wwQNBANT9jp6kNJ5WsTKR4uUx6v1RKw7F1qtC+cNR9cWPYHdrRPShix8dpblqnLX7fdrWB44QohkKfki78R28nw7zBGPAu7uuCelShuDPKy1vlDaWiOHeQ30ymlFU2eJzqlQMhRXqXiR2dwU/fPW4U7F5rSqgoOl+nwav04b9RSsOxaJaqcJwP7sObbTXnfR3t4aXnRmq5CocvJnV4vH/XMvEzcwSWBhL8FIHFgno6l4Y6YNj88dg58vDIKWr5a02PdwLzlYmSC+qFCr0pRZUYGukuo9UR1TqI7WaqsZZJVfifJJ6BZM+cwnRLvpLQTqESMTh0yl9MbdmH8LSf25hxSH9b4oqUyjxzSHNNkq72qiDn3QNgp/iSrmQQ29jVj/4GezVA0ZiETKKq5DUipQ0fuXHXcPgh9/3cyYur1X9Zu5kl2L3FXUKzNsRgS0cTZrCcVxtpcArzae+yZUqfFWz+jhnlE+D1ULSPC97826dBtgeJlIx3qhJH1y2/zaO3M7GikOxkCsZRvjZd3ijze7OwdIYAU7qapxn67Q8uJRciGqFCk5WxvB1sNDV8AjpFij4IR2G4zi8OzEQ8+9TV0pbcSgWS/+5hcS8ciTmlTdbTrU5JVVyrQVRv0amaLxR2s2GX/lpublrfs0VPUsTSYNKX2ZGEgzoaQOgdasyrV35CfawgbmRGIUVctxsRT+m5QdioGLAhD7OCPaw0fhxpCG+nPCpuDzklTVd4GLHxTQk5VfAztwIs2o28hPSWR4f6I57eztBplBhzs+XsKvm4seCiAAdj6xramxVnk95G+5rTytthGgZBT+kQ3Ech1fv8ceHdbpqj11+DGOXH8PEb09CoVS16vl+OZuE0E8O4oM/r3f4WMtlCnxf08NGk43Srjaap73x6Qx3p7zxhtekPpxsRSWw1gY/UrEIQ2uqy2m6v+hySiH+u5kNEQfMj+jV8gNIs3wcLNDf3RpKFWuymWSVXIlvD6tXH1+9x8+gywkTwyQRi+rt3WQMmNiXLn5oywj/hp/LQvBDK22EaB0FP0QrZg73xlePB8PZygSWxhKIOCAxrxyn4zUvvfzjsTgs2nMDShXDzstpGm0ab42fTiUir6waPe3MNNooLQQ/xZoHP02lL40NVJfOPnYnF6VVco3G29rgB6j9Q6rJvDPGsGy/utz3YwPd4edoqfHrkKZNHewJAFh9PB7ljbyHN59JQnaJDG42png6zLOzh0cIgNq9my+O9kWwuzUWTgzS9ZC6rCHedkI1ztSCChRXyHE1vRgABT+EdAYKfojWPDrQHefeG4drH0fgmaE9AQB7mrj6fbfVx+OFylcmUhGq5CocuN7ypnFNFVVUY+0JdVGGN+/tpdFGaVcbdRU4Tfb81AY/jTeh7ONqBV8Hc1QrVNivwfelUjGkFahftzXBD79x9nxifr1KTo05GZuHcwkFMBKL8MZ4WvXpKI8NdIenrRnyyqqx8XRivfuKK+X48Vg8AGDeeH8YS6hMM9EdkUidurzn1RHwtNP8c4a0joWxBCE1q2qn4/Jw+HY2GAP8HC3gbN2w2ighpGNR8EM6Bb/34cCNLFRWN38SXiVX4ocj6nS0BREBeGm0uvJVa/qltGRPVAZKZQoEOFliUv+Gnc0b41Yn7a2lPUgF5er9HU2lvXEcJ5RC1qRxanpRJaqVKkjFHFxa8cfR39ECDpbGqJKrcDm5qMnjVKraJq/PhvcUvlfSfkYSEd68Vx1MrjmRgKKK2gpP604koLhSDn9HCzwywF1XQySEdDJ+hWfTmSQs3HUNADA+yEmXQyKk26Dgh3SKAZ494N7DFOXVShy6ld3sscdiclAqU8DV2gQvjfat3TQem4vc0qY3jbfGnij1CtTjg9whEmm2uZS/IlclVwllrJvCFzywtWi6ahdfCex0XB5ySpsvonA7qxQA4Otg0armdxzHYbhvy/t+9l3PwvV0dZllvu8H6TgPBbsi0NkSpVUKrKpZ6cktlWFDTRPJt+4LgFjD9yEhxPDxwc/trFLIFCqMD3IUmvYSQrSLgh/SKdRlf9VBzJ6o5lc6+PsnhbhCJOLgZW+OYA8bqBjw99X2r/6k5FfgckoROE59UqopY4kYDpbqNLb0wuZT34S0N7Omgx9POzOEeqq/r7+iM5t9vpgsdbW2IBcrjcfL4//IHrmd0+j9ijplll8Y6Q07i8ZT9UjbiUQc5t+nrpy19mQCtkWm4PsjsaiUKxHsYYOIPnTFl5DuJMTDRihuMinYFaueGQgTKaW9EtIZKPghnYZP8zp+J6de6k9dJVVyHK45SZ8c7FbnsZoFTprYG61e9RnmawdHq9blV2va66elggc8IfUtqvm9ULdqVn4CnFtfhGB8kBMkIg43M0sQl1Pa4P4/LqUhIa8ctuZGeGGkT6ufn2hmXJAjnh3aE4wB7+2+hi2R6oaS70QEUGlbQroZI4m6wt4nk/tgxZMh1KCXkE5Ev22k0/g7WSLIxQpyJcPuJgofHLiehWqFCv6OFghyqT3Rf6C/C0QcEJVahDvZDU/gNcUYw581AVTd4EpTbjVFD1oqd51f1nLaG6D+vsQiDtFpxbid1XQvnph2BD89zI0wupcDAGDvXcFjlVyJFYdiAQCvjKUyy9rEcRw+mdwHL45WpxUqVeomksOouhMh3dKoXg6YHu5FKa+EdDIKfkinenqIuqT0j8fiUVHdsOwvv/l/cohrvavhjpYmuK+3MwDg6//utPn1b2WWIi6nDEYSESb0c27149007PXTUp8fnr2FsZDy1NT3VSVXIjGvHAAQ5Nz6tDcAeIhfOYvOqFes4eezScgqqYKbjSmmUZllreMbAS9+sDcGe/XARw/11vWQCCGEkG6Fgh/SqZ4c7AkPW1Pklsqw8XRSvftySqqETfkPNbIq8+Z9vcBxwP4bWYhOLWrT6/9Zk152T4AjrEykrX68Jr1+GGMap70B6lLbIg7472Y2rqQUNrg/LqcMShWDtakUTlZt249zb28nmErFSM6vQHSaup9ESVX9MsuUb955Zo3wxo4Xh1EvJUIIIaSTUfBDOlXdsr+rj8fX2/uz6ng8VAwY1LNHoz0mejlZ4pFQdTlgvixzaxSUV2NbzT6LRwa0PuUNqLvnp+nqbOXVSlQrVQAAuyb6/NTl52gplDn+8kBMg/vrpry1dW+ImZEE99WsMPGV7tadSEBRhRx+VGaZEEIIId1Ehwc/SqUSixYtgre3N0xNTeHr64slS5bUS7VhjGHx4sVwcXGBqakpxo8fj9jY2I4eCtFTDwW7CWV/+ZWH1IIKbD2nDkz+d2/TDTbnjfeHVMzhdFw+TsU2Xbq5MT8ejUOZTIE+rlZt7qegSdpbQc1+H1OpGKZGmq2mzBvvDyOxCGfiG35fMTV7nILasN+nLr7a3p9X0rHk75tCmeX5VGaZEEIIId1Ehwc/X3zxBVatWoXvv/8et27dwhdffIFly5Zh5cqVwjHLli3Dd999h9WrVyMyMhLm5uaIiIhAVVXzvU5I1yAWcVgQUVP290QCfjmbhG8O3UG1UoXhfnZCaebGeNiaYVpYTwDAlwdut9hslJdRVImfzyUDAN6eEKhxb5+78Ss/uaUyVMkbb9aaX9PgVJOUN557DzM8XbPnZu3JhHr33cpUF0IIaON+H95IfwfYmhuhsEKODacSUVFNZZYJIYQQ0r10eGmnM2fOYPLkyXjggQcAAF5eXvj1119x/vx5AOpVnxUrVuCDDz7A5MmTAQA///wznJyc8Oeff2Lq1KkdPSSih+4JdMTM4V7YeDoJi/bcEG5/OyKwxce+MtYPv19MRXRaMQ7cyMKEvi4tPubbQ7GoVqgw1McWo/zbXl2rh5kUJlIRquQqZBVXwcvevMExrdnvU9dzw7yw6UwSTsflIbdUJvQUak+lt7qkYhHWTR+IQ7dywBggFXN4fKAHlVkmhBBCSLfR4Ss/w4YNw+HDh3HnjrpyVXR0NE6dOoWJEycCABITE5GVlYXx48cLj7G2tkZYWBjOnj3b6HPKZDKUlJTU+yKGjeM4LH6wN167x0+4bWJfZwR72LT4WAdLYzw/whsAsPy/O1DU7K9pyl/RGdhxKRWAetWnPSf7HMfVFj1oIvUtv43BD9/MVali+KemmWtBeTVyStUrSe0NfgBgYE9bvDMhEO9ODMRb9wU0ureKEEIIIaSr6vDg591338XUqVMRGBgIqVSK0NBQzJs3D9OmTQMAZGVlAQCcnOqn2jg5OQn33e2zzz6DtbW18OXh4dHRwyY6wHEc3rovAEum9MXYAAe8/0CQxo+dPcoHNmZSxOWUYVcTPYMAYPuFFLz+2xWoGDB1sAcGePZo97jdWmh0qmmZ68ZMDq4tSQ1A6P3jYWtKPXgIIYQQQtqpw4Of33//HVu3bsW2bdtw+fJlbN68GcuXL8fmzZvb/JwLFy5EcXGx8JWamtqBIya69uzQntg4cwjce2i+CmFlIsXLY9TNIj/YfR0DlxzEiC+OYOelNOGYDacS8c7Oa2AMeGqIJz59uF+HjNfVml/5aXyPWlvT3gDgwWB1M9crKUVIzi9HZEIBACCwnft9CCGEEEKIFvb8LFiwQFj9AYB+/fohOTkZn332GWbMmAFnZ3VjyezsbLi41O7VyM7ORkhISKPPaWxsDGPjtvU3IV3X9HAvbI1MQXJ+hTrVrBx4a0c0iivlKK1S4JtD6tTLOaN8sHBi+9Ld6nK2NgEAZJU0kfZWU+3N1qL1wY+jpQmG+9njZGwe3vw9Gpdr+v4M97Vr42gJIYQQQgivw4OfiooKiET1F5TEYjFUKvW+DG9vbzg7O+Pw4cNCsFNSUoLIyEi89NJLHT0c0oWZSMXY98ZIpBWqg5DtF1Kx4VQiPvn7pnDMW/f2wqv3+HXopn7HmkajuTV7ce5WWNH2tDcAeCjYFSdj83ApWR34TA/vienhXm16LkIIIYQQUqvDg59Jkybh008/haenJ/r06YMrV67g66+/xqxZswCo93nMmzcPS5cuhb+/P7y9vbFo0SK4urpiypQpHT0c0sWZGUnQy0ldCOCDB4JgZSIVVnwWP9gbs2oKI3QkR0v1yk9OE8EPX/Cgh1nbgp8JfZ2xeM8NVMqVeHmMLxZEBFBFNkIIIYSQDtDhwc/KlSuxaNEivPzyy8jJyYGrqyvmzp2LxYsXC8e8/fbbKC8vx5w5c1BUVIQRI0Zg//79MDEx6ejhkG6E4zi8Md4f/T2sYSwRYZhv20taN8expgR1TknjwU9BTZ8fuzakvQGApYkUvzw/BAXl1bivj3PbBkkIIYQQQhrgmKZdIvVISUkJrK2tUVxcDCsr2ghOOldGUSWGfX4EEhGHO0snNmiY2mfxfpRXK3F0/hh4N9IHiBBCCCGEdJzWxAYdXu2NkK7O3kK98qNQMWF/D69KrkR5tRJA26q9EUIIIYQQ7aHgh5BWMpKI0MNMCgDILauf+saXuZaKOViZUF8eQgghhBB9QsEPIW0gFD24a98PXwHOztyYihQQQgghhOgZCn4IaQO+3PXdFd+yStSNT52sqXgHIYQQQoi+oeCHkDZwsGi81092TfDjbEVNeQkhhBBC9A0FP4S0gYOw8lNV7/asYj74oZUfQgghhBB9Q8EPIW3QVKNTSnsjhBBCCNFfFPwQ0gYOli2lvVHwQwghhBCibyj4IaQNHJsIfjIp7Y0QQgghRG9R8ENIGzQV/GQXU9obIYQQQoi+ouCHkDbg097KZApUVCsAAKVVcpRXKwHQyg8hhBBCiD6i4IeQNrAwlsBUKgZQ2+iU3+9jaSyBubFEZ2MjhBBCCCGNo+CHkDbgOK626EGZOvjJKlb/15lS3gghhBBC9BIFP4S0Eb/vh1/54ctcU/BDCCGEEKKfKPghpI0c72p0yqe9OdF+H0IIIYQQvUTBDyFt5GBRv+JbFpW5JoQQQgjRaxT8ENJGjjVBTk5p/bQ3KnNNCCGEEKKfKPghpI0c7ur1w6e90coPIYQQQoh+ouCHkDbig58cSnsjhBBCCDEIFPwQ0kaOwspPFeRKlVDy2snaWJfDIoQQQgghTaDgh5A24ld48surcTWtCIwBEhEHe3MKfgghhBBC9BEFP4S0kZ2FMYb62IIx4P3d1wGoV4NEIk7HIyOEEEIIIY2h4IeQdnh7QiAA4HZWKQCq9EYIIYQQos8o+CGkHQZ49sB9vZ2Ef1OxA0IIIYQQ/UXBDyHtND8iAHymmxMFP4QQQggheouCH0LaqZeTJZ4c7AkA6O9urePREEIIIYSQpkh0PQBCuoKlU/ri6SGe6ONqpeuhEEIIIYSQJlDwQ0gHEIs49KNVH0IIIYQQvUZpb4QQQgghhJBugYIfQgghhBBCSLdAwQ8hhBBCCCGkW6DghxBCCCGEENItUPBDCCGEEEII6RYo+CGEEEIIIYR0CwZZ6poxBgAoKSnR8UgIIYQQQgghusTHBHyM0ByDDH5KS0sBAB4eHjoeCSGEEEIIIUQflJaWwtq6+b6LHNMkRNIzKpUKGRkZsLS0BMdxOhtHSUkJPDw8kJqaCisrK52No6ui+dUuml/toznWLppf7aL51T6aY+2i+dU+fZljxhhKS0vh6uoKkaj5XT0GufIjEong7u6u62EIrKys6JdKi2h+tYvmV/tojrWL5le7aH61j+ZYu2h+tU8f5rilFR8eFTwghBBCCCGEdAsU/BBCCCGEEEK6BQp+2sHY2BgffvghjI2NdT2ULonmV7tofrWP5li7aH61i+ZX+2iOtYvmV/sMcY4NsuABIYQQQgghhLQWrfwQQgghhBBCugUKfgghhBBCCCHdAgU/hBBCCCGEkG6Bgh9CCCGEEEJIt0DBTxOoDoR2qVQqKJVKXQ+jy6qqqsL27duRnJys66F0WfQZoV00v9pVUVGB33//XdfD6NLkcjnS0tKEf9N7WjtoXrWnq84tBT+NWLFiBR566CG8/PLLiIyMRHV1ta6H1KWsXLkSkyZNwrPPPotdu3ahrKxM10PqUr799ls4OTlh48aNyMjIgEKh0PWQupwVK1Zg8uTJePnll3Hq1ClUVlYC6Lp/KDrbDz/8gKeeegqvvvoqTp48SZ/BHezLL7+EhYUFVq9eTXOrJV9//TWCg4Px8MMPY8qUKbh+/To4joNKpdL10LqE3377DX/++ScAgOM43Q6mi+rK58IU/NRRXl6ORx99FN9++y1CQ0Nx8eJFPPvss1iyZImuh9YlnDt3DsHBwfj+++8xZswYFBYWYtGiRThw4ICuh9ZlrF69GmvWrMG6deuwb98+DB06FBKJRNfD6jKysrIwYcIE/PDDD7jnnnuQlJSEefPmYeHChQDoj3B7XblyBYMHD8bKlSvh7++PyMhIzJ07Fzt27ND10LqE48ePw9PTEz/++CN+//13HDlyBEZGRroeVpdSWlqKqVOnYtWqVfjkk08wa9YsFBcXC58RIhGddrXHjRs3MH78eDz99NPYsGED4uLiANCFp47UHc6F6bewjps3b+LatWvYtWsXPvnkE5w/fx5PPfUUfv31V/z222+6Hp5BS0lJwZo1a3DPPffg8uXLWLBgAfbt24f8/HwUFhYCoA+v9lAqlZDJZNi9ezdeeOEFPPHEE8jMzMS+ffsQExOD0tJSAKCrju104sQJFBYW4uzZs5g3bx7+/fdfTJo0CWvWrMGuXbsAgNI52ygrKwsrV65EaGgoIiMjsWTJEly4cAH29va4cOECAPqMaI/CwkIsXrwYFRUVSExMxGOPPYbc3Fykp6cLnw+k/a5du4bo6Gjs2rULjz32GF566SUMGjQI9vb2ANTvYXoft01lZSV27twJOzs7/PDDD7h27RoOHDgAhUJBF546UHc4F6bgB7UnhEVFRcjPz4eDg4Nw3wsvvIAxY8Zg0aJFuhpel2Bvb4/p06fjnXfegbm5OQCguLgYISEhCAwMpA+vdmCMQSwWo7q6GlFRUbj33nuxfv16BAcHY8mSJRg9ejRmz54NxhhddWwjlUoFhUKBkydPwsbGBubm5kKQ4+/vD5lMhtdff134WRDN8SeCRkZGsLCwwIsvvghra2vIZDIAwKBBg4Tghz4jWo+f3x49euDtt99GeXk5jhw5go8//hjh4eF48MEHMXjwYGzfvl3HI+0aysrKkJKSAqlUKtx2/fp1uLu748aNG+A4jt7HbWRkZIR7770Xr776Kl566SWMGTMGv/76K6KionQ9tC6hO50Ld9szob/++gs7d+5ESkqKcBJTXFwMNzc33Lp1SzjOw8MD06ZNg0gkwldffaWr4RqcuvMrl8thZmaGESNGwNnZGQDw/fffw9vbG9evX8dTTz2FRx55hFJbWoGf3+TkZOH9m5OTg759+2LDhg3Yvn07Nm3ahN27d+Prr7/GhQsX8MorrwCg1R9N1Z1jhUIBiUQCMzMz5OTkICEhQQhyoqOj8dxzz8HExARffvklAFqh0MS1a9cAQNgHYWtriy+//BIDBgwAABgbGwMAUlNTMXLkSJ2N01DVnV/+/Th27FhMmTIF48ePx5kzZ/D555/jk08+QUhICD799FOsWbNGl0M2OPwcA7W/846OjhgyZAgiIiIwf/582NraIjExEUePHsUDDzyA2bNn62q4Bufo0aM4ffo0cnJyhAtLQ4YMET4PPv74Y6SmpmLPnj0oKSkBQJ+9rdVtz4VZN3P79m0WEhLC3N3dWWBgIPPz82PvvfceY4yxiooK5unpyd59911WXl4uPCYvL48999xz7JFHHmEVFRW6GrpBaGx+P/jggwbHzZw5k3333XcsJyeHnT17ls2cOZMNGjSIFRQU6GDUhqOx+X3//fcZY4zJZDI2YcIEZm9vzx5++OF6j9uwYQOzsLBgWVlZuhi2QWlsjhcuXMgYY6ysrIz5+/uzPn36sNdee435+Pgwf39/duLECfboo4+y6dOns+rqah1/B/otKiqKhYWFMVdXV3bo0CHGGGMKhUK4X6VS1fv/YcOGsd9//73Tx2moWprfy5cvs4ULF7I7d+4It+Xk5LCZM2eye+65h5WUlHT6mA1NY3Msl8uF+1NTU9nu3bvZkCFD2IcffsjkcjkrKipiR48eZRzHsUuXLjHG6r/XSa1z586x/v37M19fX+bj48NCQkLYtm3b6h3Dz/fHH3/MgoKC2P79+3UxVIPV3c+Fu93Kz8aNG+Ho6IgbN27gwIEDePHFF7FixQqsXbsWpqameP3117Fq1SpcvHhReIydnR1sbW2Rk5MDU1NTHY5e/zU2v19//TU2btwIoPaqzPr16/Haa6/BwcEBQ4cOxeDBg1FcXIzc3FxdDl/v3T2/c+fOxTfffIN169bByMgIL7zwAvLz8xvk8Ht7e8PZ2ZlKX2ugsTn+9ttvsXbtWpibm2Pbtm2YMWMGkpKS8OKLLyI6OhojR46EiYkJqqqqIJVK6epjE06ePInZs2fD2toavXr1wpYtW6BUKiEWi4U5q5sSFBcXh2vXrqFv377CbfweQdJQc/PLr/j27t0bCxYsgL+/PwD1Z7KDgwPc3NyQn59PK8MtaGqOJRKJMHfu7u7o2bMnkpOT8cILL0AikcDa2hp9+/aFm5sbjhw5AoDSOBuze/duPPfcc5g4cSLOnj2LXbt2ISAgAFu2bEF6erpwHL/y/v7770MqlWLHjh3IzMwEAMTHx+tk7Iak258L6zb26lwVFRXM3d2dffPNN8JtMpmMffDBB8za2polJyczxhjr168fmzJlCouOjhaOe/3119mkSZPqXd0h9TU3vz169GAJCQmMsYZXdhljbNGiRWzMmDGsqqqqU8dsSFp6/yYlJTHGGHv88ceZl5cX27Fjh3Dctm3b2MCBA1lRUVFnD9ugNDfHNjY2wnu4LpVKxfLy8lhYWFijq5ykVkpKCpszZw6Li4tjX375JQsLC2M///wzY6zxz4XvvvuOhYSEMMYYy8/PZzNnzmQPPPAAy83N7fzBG4Dm5lepVDb6GP725557jj300EP0N64Fmr6H//vvPzZs2DB24cIF4baDBw+yoKAgdvXq1U4ftyGoqqpiS5cuZQsXLmTFxcXCfP7666/Mx8eHFRYW1jueX9Hctm0b8/HxYV988QV75JFHWN++fVlGRkZnD99g0LmwuupIt8B/wA8bNozNmzePMVb7QVVcXMz8/f3Z7NmzGWOMHT9+nIWHh7PAwED27bffso8++ojZ2tqyrVu36mbwBkCT+X355ZfrPaa6upqVlZWxL774gvn6+rJffvml3uNILU3md86cOYwxxqKjo9kjjzzCzM3N2f/+9z/2zjvvMCcnJ/Z///d/TKFQ0Pw2oTXvYf6PblFRESsuLmaffPIJ69u3L7t+/boORm5YSktLGWOMZWRksMcee4w9+OCDLDs7mzHW8AT9lVdeYR988AFbsWIFs7S0ZIMHD2ZxcXGdPmZD0pr5raioYMXFxWzZsmXMx8eH/fXXX50+XkPU3BzzJ4XR0dFs5MiRLCwsjK1bt4598sknzNnZmb366qusoqKCPoebcPbsWSH9nZ+jyMhI5uXlxTIzMxt9TEVFBXNwcGAcx7FRo0bVS+kk9dG5sFq3CX4YU19VePnll9n9998vXMHl3wjr169nJiYmwi/dzZs32UsvvcQmTpzIQkND6Y+CBlqaX1NTU2Hl4ejRo2zBggWsT58+zMfHh/J1NdCa929RURH79NNP2YwZM9jo0aPZ3r17dTZuQ9Ka93B6ejpbvXo18/b2Zl5eXuzgwYM6G7eh4YPHLVu2sKFDh7LPPvuswTGFhYXMzc2NcRzH3N3d2e7duzt5lIZLk/k9c+YMW7BgAevVqxd9BreBJnN88OBB9vDDDwtBEJ1HaE6lUgmfvZ9++ikLCwsTbq/rxIkTzMzMjPn5+bHDhw93+jgNEZ0Ld7Hgp7S0lF27do0xVn+DJ2O1vzC//fYbGzBgAPv666/r3X/t2jUWGBjIdu3a1eA5iVpHzm9BQQH76KOP2IYNGzph5IZBG+9furpYX0fMMX8SLpfL2fHjx9mWLVu0P3AD0dz81sXPdUVFBZs9ezYbM2aMkArEPy43N5eNGzeOrVmzRsujNhwdMb/8ykRBQQH76quv2E8//aTlURuWjphjvugJfwwVmqml6fzyVCoVmzhxIlu6dGmj98fHx7OvvvqqQ8do6AoLC9nOnTsbvY/OhdW6TPBz8+ZNxnEcCwwMFKpQNHXi99RTT7Hx48ezo0ePCrddunSJmZubszNnzjT72O6qo+e3ucd3R9qYX1IfzbF2tWZ+Gau90nj48GE2evRo9uabb7KkpCT25JNPCjnmhp5X3pE6cn75k3T6DK6vI+eYUmAbau38MsZYZWUl6927t1BVr7S0lH355ZcsJSVF6+M1RB9//DHjOI5Nnjy5xc/P7nwu3GWqvV2/fh0BAQGws7PD8uXLATSs985XYpk3bx6MjY3xyiuv4PLly8jOzsa+ffsQHBwMLy8vAFSF5W4dPb8AzXFd2phfUh/NsXZpMr918Q1377nnHgwePBg//fQTAgICEBkZCXNzczDGIJFIOmXshqAj59fMzAyMMfoMvktHzrGJiQlVfbxLa+cXUPdSkslk6NevH9atWwdXV1fs3LmTPhvusn//fri4uGDLli3Yu3cv/vzzzybniM6FYfjV3viodO3atezRRx9lH3zwAevTpw+LjY1ljDVd4SYqKoqNGzeOeXh4MC8vL+bi4sL+/fffThu3oaD51S6aX+2jOdauts4vY+r0oN27dzMXFxfm7e1N+3oaQfOrfTTH2tWe+V28eDGztbVlAQEBzNbWltKMG5Gbm8sGDhzIevbsKdyWmZnJ0tPT66WrNbaK013/zhl88MObM2cOW79+Pbtx4wYLDw8XqlXc/cOu+2+ZTMZiY2O7xQ+6vWh+tYvmV/tojrVL0/mtq7y8nAUGBrK33367s4ZpsGh+tY/mWLtaO79KpZLNmjWLmZqaso8//rgzh2oQ+HlTqVTs999/ZyYmJuzMmTPs3XffZb6+viw4OJj179+f/fHHH00+lrHu+XfOoNLerl692uA2fvnOxMQEFRUVCAgIwIwZM3Dq1CnMmjULL7/8MoqKioTj6y7hGRkZwc/PDxMnTtT62A0Bza920fxqH82xdnXE/PKUSiXMzMwQFRWFL774QttDNwg0v9pHc6xdHTm/IpEIs2bNQmZmJhYvXqztoRsMfo75v1Ucx2HChAm49957MXz4cFy/fh3Lly/HJ598An9/f3z88cf45ZdfANT+LLr73zmDCH7Onz+P0NBQPPTQQzh79iyA2h8gn3N7/PhxhIaGQiwWg+M4pKen4+eff8bQoUNhY2Ojq6EbBJpf7aL51T6aY+3SxvzyHdqNjY0755vQYzS/2kdzrF0dPb+sZi/Q8OHDYW1t3XnfiB5rbI6VSiUAwNLSEu+//z4WLlyIlStXYsqUKXjooYfw7bffol+/fvj1118hk8mEn0V3p/ezcOjQIbz88stwcnJCz549sXnzZgC1v0wqlQoKhQL9+vVDRkYGJk6ciDfeeAPDhw+Hv7+/EN3ybxBSH82vdtH8ah/NsXbR/GoXza/20Rxrlzbmt8tutG+jpuZYLBYLQWZwcDDmz59fryiPm5sb7O3tUVhYSO/funSdd9eSO3fusBdffJElJiayJUuWsLCwMCF/se4mOVtbW8ZxHHv00UdZfHw8y87OZrNnz2ZeXl6suLhYV8PXezS/2kXzq300x9pF86tdNL/aR3OsXTS/2qfpHNelVCqZQqFgjz/+OHv66ae7bNnqttD74IcxxsrKyhhjjCUkJLDJkyezhx9+WOiyLpPJGGPqOvv//vtvvTfB7t272XvvvcdKS0vph94Mml/tovnVPppj7aL51S6aX+2jOdYuml/ta26O7w6AKioqWGFhIfv444+Zn5+f0CeJqBlE8MNYbSfg9evXs7CwMLZixQrGWONVQvjbmiufSOqj+dUuml/toznWLppf7aL51T6aY+2i+dW+pua4rmPHjrG33nqLeXt7s8DAQHb8+PHOHqbe06s9P+yuZleN5X8+9thjCAwMxF9//YXY2FhwHCccd3cVC9rYVR/Nr3bR/GofzbF20fxqF82v9tEcaxfNr/a1ZY4BQKFQAAACAwPh7OyMJUuW4NatWxg1alQnjdxw6PRdt3HjRqxevRpHjx4FoP6hMsaEHzRfSQVQ/4IolUpYW1vjiSeegEwmw6ZNm5CYmIgnnngCycnJ9Et0F5pf7aL51T6aY+2i+dUuml/toznWLppf7euoOX7yySeRmJgIJycnzJ8/H9OmTdPJ92MQOnupiTHG9u7dy9zc3NjAgQPZ4MGDmYODA3vrrbcYY7VLeowx9uuvv7LBgwezo0ePNniOV199lVlZWTFjY2PWq1cvlpaWRvmiNWh+tYvmV/tojrWL5le7aH61j+ZYu2h+tY/mWHc6PfjZu3cvCw4OZsuXL2dKpZJlZWWxzZs3MyMjI5aWlsYYYywzM5MNHTqUOTs7s2+//ZZVV1cLj5fJZGz79u3Mzs6OBQQEdKuOtJqg+dUuml/toznWLppf7aL51T6aY+2i+dU+mmPd6vTgZ+fOnezZZ5+tV9bwypUrrFevXkI1ivLycrZkyRKWmZnZ4PEFBQXM19eXffTRR502ZkNC86tdNL/aR3OsXTS/2kXzq300x9pF86t9NMe6pfXg58yZMywjI0P4d0lJCausrKx3TFJSErO3t2fJycnNPhe/DFg3+u3uaH61i+ZX+2iOtYvmV7tofrWP5li7aH61j+ZYv2ht59nhw4fh4+ODp556CkOGDMHs2bMRGxsLS0tLmJiYCBU/AODo0aNwc3ODu7s75HJ5k8/Jb/qSSqXaGrbBoPnVLppf7aM51i6aX+2i+dU+mmPtovnVPppj/aSV4Cc1NRUffPABnnnmGRw+fBjffPMNjhw5gnfffRfJycnCcXwli5MnT6JPnz4QiUT0w9QAza920fxqH82xdtH8ahfNr/bRHGsXza/20RzrMW0sJ/3333/M1NSUxcXFCbft3LmTjRo1is2dO1e4TS6XM8YY69evH9u0aRNjjLHk5GT29NNPs1u3bmljaF0Cza920fxqH82xdtH8ahfNr/bRHGsXza/20RzrL62s/BQUFCAoKKheY6bJkycjIiICJ0+exPHjxwEAEokEd+7cgUKhwKhRo7Bo0SIEBgYiMTERrq6u2hhal0Dzq100v9pHc6xdNL/aRfOrfTTH2kXzq300x3pMGxHVtWvXmImJCduzZ0+9269cucIiIiLY//73P+G2FStWMI7jmLW1NfP29mbHjx/XxpC6FJpf7aL51T6aY+2i+dUuml/toznWLppf7aM51l9aWfnp27cvxo4di6+//hplZWXC7SEhIXB0dERCQgIUCgUA9YYtKysrfP/990hISMCoUaO0MaQuheZXu2h+tY/mWLtofrWL5lf7aI61i+ZX+2iO9Zi2oqqoqCgmkUjYqlWrmEwmE25///33mZ+fn/DvvLw8bQ2hS6P51S6aX+2jOdYuml/tovnVPppj7aL51T6aY/0k0VZQFRwcjHfeeQdLliyBVCrF1KlToVKpcPHiRTzzzDPCcXZ2dtoaQpdG86tdNL/aR3OsXTS/2kXzq300x9pF86t9NMf6iWOMMW2+wCuvvILdu3fD09MTWVlZMDc3x44dO9C7d29tvmy3QfOrXTS/2kdzrF00v9pF86t9NMfaRfOrfTTH+kXrwU9VVRVu3bqFy5cvw9jYuF6kS9qP5le7aH61j+ZYu2h+tYvmV/tojrWL5lf7aI71i9aDH0IIIYQQQgjRB1qp9kYIIYQQQggh+oaCH0IIIYQQQki3QMEPIYQQQgghpFug4IcQQgghhBDSLVDwQwghhBBCCOkWKPghhBBCCCGEdAsU/BBCCCGEEEK6BQp+CCGEEEIIId0CBT+EEEK0ZsyYMZg3b163e21CCCH6iYIfQggheuHYsWPgOA5FRUUd8rhdu3ZhyZIlHTdAQgghBk+i6wEQQggh2mBra6vrIRBCCNEztPJDCCGkQ5SXl2P69OmwsLCAi4sLvvrqq3r3//LLLxg0aBAsLS3h7OyMp59+Gjk5OQCApKQkjB07FgDQo0cPcByH5557DgCgUqnw2WefwdvbG6ampggODsYff/zR4uPuTnvz8vLC0qVLhTH27NkTe/fuRW5uLiZPngwLCwv0798fFy9erDfuU6dOYeTIkTA1NYWHhwdef/11lJeXd/T0EUII6QQU/BBCCOkQCxYswPHjx7Fnzx78999/OHbsGC5fvizcL5fLsWTJEkRHR+PPP/9EUlKSEKh4eHhg586dAICYmBhkZmbi22+/BQB89tln+Pnnn7F69WrcuHED//vf//DMM8/g+PHjzT6uMd988w2GDx+OK1eu4IEHHsCzzz6L6dOn45lnnsHly5fh6+uL6dOngzEGAIiPj8eECRPw6KOP4urVq9i+fTtOnTqFV199VRtTSAghRMs4xn/CE0IIIW1UVlYGOzs7bNmyBY8//jgAoKCgAO7u7pgzZw5WrFjR4DEXL17E4MGDUVpaCgsLCxw7dgxjx45FYWEhbGxsAAAymQy2trY4dOgQwsPDhce+8MILqKiowLZt2xp9HKBe+QkJCRFe28vLCyNHjsQvv/wCAMjKyoKLiwsWLVqETz75BABw7tw5hIeHIzMzE87OznjhhRcgFouxZs0a4XlPnTqF0aNHo7y8HCYmJh04i4QQQrSN9vwQQghpt/j4eFRXVyMsLEy4zdbWFgEBAcK/L126hI8++gjR0dEoLCyESqUCAKSkpKB3796NPm9cXBwqKipw77331ru9uroaoaGhrR5n//79hf93cnICAPTr16/BbTk5OXB2dkZ0dDSuXr2KrVu3CscwxqBSqZCYmIigoKBWj4EQQojuUPBDCCFE68rLyxEREYGIiAhs3boVDg4OSElJQUREBKqrq5t8XFlZGQDgn3/+gZubW737jI2NWz0OqVQq/D/HcU3exgdmZWVlmDt3Ll5//fUGz+Xp6dnq1yeEEKJbFPwQQghpN19fX0ilUkRGRgpBQWFhIe7cuYPRo0fj9u3byM/Px+effw4PDw8AaFBYwMjICACgVCqF23r37g1jY2OkpKRg9OjRjb52Y4/rKAMGDMDNmzfh5+fX4c9NCCGk81HBA0IIIe1mYWGB559/HgsWLMCRI0dw/fp1PPfccxCJ1H9mPD09YWRkhJUrVyIhIQF79+5t0IOnZ8+e4DgOf//9N3Jzc1FWVgZLS0vMnz8f//vf/7B582bEx8fj8uXLWLlyJTZv3tzk4zrKO++8gzNnzuDVV19FVFQUYmNjsWfPHip4QAghBoqCH0IIIR3iyy+/xMiRIzFp0iSMHz8eI0aMwMCBAwEADg4O2LRpE3bs2IHevXvj888/x/Lly+s93s3NDR9//DHeffddODk5CQHGkiVLsGjRInz22WcICgrChAkT8M8//8Db27vZx3WE/v374/jx47hz5w5GjhyJ0NBQLF68GK6urh32GoQQQjoPVXsjhBBCCCGEdAu08kMIIYQQQgjpFij4IYQQQgghhHQLFPwQQgghhBBCugUKfgghhBBCCCHdAgU/hBBCCCGEkG6Bgh9CCCGEEEJIt0DBDyGEEEIIIaRboOCHEEIIIYQQ0i1Q8EMIIYQQQgjpFij4IYQQQgghhHQLFPwQQgghhBBCugUKfgghhBBCCCHdwv8D3o9QPKCbT5QAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dexcom001_df[(dexcom001_df['datetime'] >= '2020-02-14 00:00:00') & (dexcom001_df['datetime'] <= '2020-02-14 23:59:59')]\\\n",
    "    .set_index('datetime')\\\n",
    "    .plot(y='Glucose Value (mg/dL)', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Glucose 그래프에 식사한 시간을 표시함"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 날짜 필터링\n",
    "filtered_df = dexcom001_df[(dexcom001_df['datetime'] >= '2020-02-14 00:00:00') & (dexcom001_df['datetime'] <= '2020-02-14 23:59:59')]\n",
    "\n",
    "# 인덱스를 datetime으로 설정\n",
    "filtered_df.set_index('datetime', inplace=True)\n",
    "\n",
    "# 그래프 그리기\n",
    "ax = filtered_df.plot(y='Glucose Value (mg/dL)', figsize=(10, 3), legend=True)\n",
    "\n",
    "# 특정 구간 강조 (오후 2시부터 오후 6시)\n",
    "for idx in range(len(fl001_df)):\n",
    "    start_time = pd.Timestamp(fl001_df.iloc[idx]['time_begin'])\n",
    "    end_time = start_time + pd.Timedelta(minutes=10)\n",
    "    plt.axvspan(start_time, end_time, color='yellow', alpha=0.3)\n",
    "\n",
    "# 그래프 제목 및 축 라벨 설정\n",
    "plt.title('Glucose Value on 2020-02-14 with Highlighted Interval')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Glucose Value (mg/dL)')\n",
    "\n",
    "# 그래프 출력\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\smyie\\AppData\\Local\\Temp\\ipykernel_6964\\3161243059.py:2: FutureWarning: 'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "  dexcom_resampled = dexcom001_df.resample('5T')['Glucose Value (mg/dL)'].mean().interpolate()\n"
     ]
    }
   ],
   "source": [
    "dexcom001_df.set_index('datetime', inplace=True)\n",
    "dexcom_resampled = dexcom001_df.resample('5T')['Glucose Value (mg/dL)'].mean().interpolate()\n",
    "\n",
    "# 지난 24시간의 데이터에 대해 개인화된 평균 및 표준 편차 계산\n",
    "window = 24 * 12  # 24시간을 5분 단위로 환산\n",
    "dexcom001_df['PersonalMean'] = dexcom001_df['Glucose Value (mg/dL)'].rolling(window=window, min_periods=1).mean()\n",
    "dexcom001_df['PersonalStd'] = dexcom001_df['Glucose Value (mg/dL)'].rolling(window=window, min_periods=1).std()\n",
    "\n",
    "# PersHigh, PersLow, PersNorm 분류 함수 업데이트\n",
    "def classify_glucose(value, mean, std):\n",
    "    if value > mean + std:\n",
    "        return 'PersHigh'\n",
    "    elif value < mean - std:\n",
    "        return 'PersLow'\n",
    "    else:\n",
    "        return 'PersNorm'\n",
    "\n",
    "# 각 측정값을 PersHigh, PersLow, PersNorm으로 분류\n",
    "dexcom001_df['class'] = dexcom001_df.apply(lambda x: classify_glucose(x['Glucose Value (mg/dL)'], x['PersonalMean'], x['PersonalStd']), axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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>Index</th>\n",
       "      <th>Event Type</th>\n",
       "      <th>Event Subtype</th>\n",
       "      <th>Patient Info</th>\n",
       "      <th>Device Info</th>\n",
       "      <th>Source Device ID</th>\n",
       "      <th>Glucose Value (mg/dL)</th>\n",
       "      <th>Insulin Value (u)</th>\n",
       "      <th>Carb Value (grams)</th>\n",
       "      <th>Duration (hh:mm:ss)</th>\n",
       "      <th>Glucose Rate of Change (mg/dL/min)</th>\n",
       "      <th>Transmitter Time (Long Integer)</th>\n",
       "      <th>PersonalMean</th>\n",
       "      <th>PersonalStd</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2020-02-13 17:23:32</th>\n",
       "      <td>13</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>61.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11101.0</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:28:32</th>\n",
       "      <td>14</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11401.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:33:32</th>\n",
       "      <td>15</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11701.0</td>\n",
       "      <td>59.333333</td>\n",
       "      <td>1.527525</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:38:32</th>\n",
       "      <td>16</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12001.0</td>\n",
       "      <td>59.250000</td>\n",
       "      <td>1.258306</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:43:31</th>\n",
       "      <td>17</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>63.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12301.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:48:31</th>\n",
       "      <td>18</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>67.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12601.0</td>\n",
       "      <td>61.166667</td>\n",
       "      <td>3.371449</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:53:31</th>\n",
       "      <td>19</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12901.0</td>\n",
       "      <td>62.142857</td>\n",
       "      <td>4.017817</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 17:58:31</th>\n",
       "      <td>20</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>63.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13201.0</td>\n",
       "      <td>62.250000</td>\n",
       "      <td>3.732100</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:03:32</th>\n",
       "      <td>21</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13501.0</td>\n",
       "      <td>61.888889</td>\n",
       "      <td>3.655285</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:08:32</th>\n",
       "      <td>22</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>60.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13801.0</td>\n",
       "      <td>61.700000</td>\n",
       "      <td>3.497618</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:13:32</th>\n",
       "      <td>23</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14101.0</td>\n",
       "      <td>62.454545</td>\n",
       "      <td>4.156047</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:18:32</th>\n",
       "      <td>24</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>86.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14401.0</td>\n",
       "      <td>64.416667</td>\n",
       "      <td>7.867752</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:23:32</th>\n",
       "      <td>25</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14701.0</td>\n",
       "      <td>67.538462</td>\n",
       "      <td>13.543851</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:28:31</th>\n",
       "      <td>26</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>118.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15001.0</td>\n",
       "      <td>71.142857</td>\n",
       "      <td>18.740565</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:33:31</th>\n",
       "      <td>27</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>127.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15301.0</td>\n",
       "      <td>74.866667</td>\n",
       "      <td>23.111119</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:38:32</th>\n",
       "      <td>28</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>133.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15601.0</td>\n",
       "      <td>78.500000</td>\n",
       "      <td>26.640821</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:43:32</th>\n",
       "      <td>29</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>139.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15901.0</td>\n",
       "      <td>82.058824</td>\n",
       "      <td>29.676318</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:48:32</th>\n",
       "      <td>30</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>143.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16201.0</td>\n",
       "      <td>85.444444</td>\n",
       "      <td>32.174565</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:53:32</th>\n",
       "      <td>31</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>141.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16501.0</td>\n",
       "      <td>88.368421</td>\n",
       "      <td>33.765878</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 18:58:32</th>\n",
       "      <td>32</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>132.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16801.0</td>\n",
       "      <td>90.550000</td>\n",
       "      <td>34.282841</td>\n",
       "      <td>PersHigh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:03:31</th>\n",
       "      <td>33</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>122.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17101.0</td>\n",
       "      <td>92.047619</td>\n",
       "      <td>34.112280</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:08:31</th>\n",
       "      <td>34</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>116.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17401.0</td>\n",
       "      <td>93.136364</td>\n",
       "      <td>33.679576</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:13:32</th>\n",
       "      <td>35</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17701.0</td>\n",
       "      <td>94.043478</td>\n",
       "      <td>33.191563</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:18:32</th>\n",
       "      <td>36</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>113.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18001.0</td>\n",
       "      <td>94.833333</td>\n",
       "      <td>32.691797</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:23:31</th>\n",
       "      <td>37</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18301.0</td>\n",
       "      <td>95.480000</td>\n",
       "      <td>32.166390</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:28:31</th>\n",
       "      <td>38</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18601.0</td>\n",
       "      <td>96.038462</td>\n",
       "      <td>31.644880</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:33:32</th>\n",
       "      <td>39</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18901.0</td>\n",
       "      <td>96.555556</td>\n",
       "      <td>31.146470</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:38:31</th>\n",
       "      <td>40</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19201.0</td>\n",
       "      <td>97.214286</td>\n",
       "      <td>30.762359</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:43:32</th>\n",
       "      <td>41</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>119.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19501.0</td>\n",
       "      <td>97.965517</td>\n",
       "      <td>30.477723</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13 19:48:32</th>\n",
       "      <td>42</td>\n",
       "      <td>EGV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>iPhone G6</td>\n",
       "      <td>123.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19801.0</td>\n",
       "      <td>98.800000</td>\n",
       "      <td>30.294417</td>\n",
       "      <td>PersNorm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Index Event Type Event Subtype Patient Info Device Info  \\\n",
       "datetime                                                                       \n",
       "2020-02-13 17:23:32     13        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:28:32     14        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:33:32     15        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:38:32     16        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:43:31     17        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:48:31     18        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:53:31     19        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 17:58:31     20        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:03:32     21        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:08:32     22        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:13:32     23        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:18:32     24        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:23:32     25        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:28:31     26        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:33:31     27        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:38:32     28        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:43:32     29        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:48:32     30        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:53:32     31        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 18:58:32     32        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:03:31     33        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:08:31     34        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:13:32     35        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:18:32     36        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:23:31     37        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:28:31     38        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:33:32     39        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:38:31     40        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:43:32     41        EGV           NaN          NaN         NaN   \n",
       "2020-02-13 19:48:32     42        EGV           NaN          NaN         NaN   \n",
       "\n",
       "                    Source Device ID  Glucose Value (mg/dL)  \\\n",
       "datetime                                                      \n",
       "2020-02-13 17:23:32        iPhone G6                   61.0   \n",
       "2020-02-13 17:28:32        iPhone G6                   59.0   \n",
       "2020-02-13 17:33:32        iPhone G6                   58.0   \n",
       "2020-02-13 17:38:32        iPhone G6                   59.0   \n",
       "2020-02-13 17:43:31        iPhone G6                   63.0   \n",
       "2020-02-13 17:48:31        iPhone G6                   67.0   \n",
       "2020-02-13 17:53:31        iPhone G6                   68.0   \n",
       "2020-02-13 17:58:31        iPhone G6                   63.0   \n",
       "2020-02-13 18:03:32        iPhone G6                   59.0   \n",
       "2020-02-13 18:08:32        iPhone G6                   60.0   \n",
       "2020-02-13 18:13:32        iPhone G6                   70.0   \n",
       "2020-02-13 18:18:32        iPhone G6                   86.0   \n",
       "2020-02-13 18:23:32        iPhone G6                  105.0   \n",
       "2020-02-13 18:28:31        iPhone G6                  118.0   \n",
       "2020-02-13 18:33:31        iPhone G6                  127.0   \n",
       "2020-02-13 18:38:32        iPhone G6                  133.0   \n",
       "2020-02-13 18:43:32        iPhone G6                  139.0   \n",
       "2020-02-13 18:48:32        iPhone G6                  143.0   \n",
       "2020-02-13 18:53:32        iPhone G6                  141.0   \n",
       "2020-02-13 18:58:32        iPhone G6                  132.0   \n",
       "2020-02-13 19:03:31        iPhone G6                  122.0   \n",
       "2020-02-13 19:08:31        iPhone G6                  116.0   \n",
       "2020-02-13 19:13:32        iPhone G6                  114.0   \n",
       "2020-02-13 19:18:32        iPhone G6                  113.0   \n",
       "2020-02-13 19:23:31        iPhone G6                  111.0   \n",
       "2020-02-13 19:28:31        iPhone G6                  110.0   \n",
       "2020-02-13 19:33:32        iPhone G6                  110.0   \n",
       "2020-02-13 19:38:31        iPhone G6                  115.0   \n",
       "2020-02-13 19:43:32        iPhone G6                  119.0   \n",
       "2020-02-13 19:48:32        iPhone G6                  123.0   \n",
       "\n",
       "                     Insulin Value (u)  Carb Value (grams)  \\\n",
       "datetime                                                     \n",
       "2020-02-13 17:23:32                NaN                 NaN   \n",
       "2020-02-13 17:28:32                NaN                 NaN   \n",
       "2020-02-13 17:33:32                NaN                 NaN   \n",
       "2020-02-13 17:38:32                NaN                 NaN   \n",
       "2020-02-13 17:43:31                NaN                 NaN   \n",
       "2020-02-13 17:48:31                NaN                 NaN   \n",
       "2020-02-13 17:53:31                NaN                 NaN   \n",
       "2020-02-13 17:58:31                NaN                 NaN   \n",
       "2020-02-13 18:03:32                NaN                 NaN   \n",
       "2020-02-13 18:08:32                NaN                 NaN   \n",
       "2020-02-13 18:13:32                NaN                 NaN   \n",
       "2020-02-13 18:18:32                NaN                 NaN   \n",
       "2020-02-13 18:23:32                NaN                 NaN   \n",
       "2020-02-13 18:28:31                NaN                 NaN   \n",
       "2020-02-13 18:33:31                NaN                 NaN   \n",
       "2020-02-13 18:38:32                NaN                 NaN   \n",
       "2020-02-13 18:43:32                NaN                 NaN   \n",
       "2020-02-13 18:48:32                NaN                 NaN   \n",
       "2020-02-13 18:53:32                NaN                 NaN   \n",
       "2020-02-13 18:58:32                NaN                 NaN   \n",
       "2020-02-13 19:03:31                NaN                 NaN   \n",
       "2020-02-13 19:08:31                NaN                 NaN   \n",
       "2020-02-13 19:13:32                NaN                 NaN   \n",
       "2020-02-13 19:18:32                NaN                 NaN   \n",
       "2020-02-13 19:23:31                NaN                 NaN   \n",
       "2020-02-13 19:28:31                NaN                 NaN   \n",
       "2020-02-13 19:33:32                NaN                 NaN   \n",
       "2020-02-13 19:38:31                NaN                 NaN   \n",
       "2020-02-13 19:43:32                NaN                 NaN   \n",
       "2020-02-13 19:48:32                NaN                 NaN   \n",
       "\n",
       "                    Duration (hh:mm:ss)  Glucose Rate of Change (mg/dL/min)  \\\n",
       "datetime                                                                      \n",
       "2020-02-13 17:23:32                 NaN                                 NaN   \n",
       "2020-02-13 17:28:32                 NaN                                 NaN   \n",
       "2020-02-13 17:33:32                 NaN                                 NaN   \n",
       "2020-02-13 17:38:32                 NaN                                 NaN   \n",
       "2020-02-13 17:43:31                 NaN                                 NaN   \n",
       "2020-02-13 17:48:31                 NaN                                 NaN   \n",
       "2020-02-13 17:53:31                 NaN                                 NaN   \n",
       "2020-02-13 17:58:31                 NaN                                 NaN   \n",
       "2020-02-13 18:03:32                 NaN                                 NaN   \n",
       "2020-02-13 18:08:32                 NaN                                 NaN   \n",
       "2020-02-13 18:13:32                 NaN                                 NaN   \n",
       "2020-02-13 18:18:32                 NaN                                 NaN   \n",
       "2020-02-13 18:23:32                 NaN                                 NaN   \n",
       "2020-02-13 18:28:31                 NaN                                 NaN   \n",
       "2020-02-13 18:33:31                 NaN                                 NaN   \n",
       "2020-02-13 18:38:32                 NaN                                 NaN   \n",
       "2020-02-13 18:43:32                 NaN                                 NaN   \n",
       "2020-02-13 18:48:32                 NaN                                 NaN   \n",
       "2020-02-13 18:53:32                 NaN                                 NaN   \n",
       "2020-02-13 18:58:32                 NaN                                 NaN   \n",
       "2020-02-13 19:03:31                 NaN                                 NaN   \n",
       "2020-02-13 19:08:31                 NaN                                 NaN   \n",
       "2020-02-13 19:13:32                 NaN                                 NaN   \n",
       "2020-02-13 19:18:32                 NaN                                 NaN   \n",
       "2020-02-13 19:23:31                 NaN                                 NaN   \n",
       "2020-02-13 19:28:31                 NaN                                 NaN   \n",
       "2020-02-13 19:33:32                 NaN                                 NaN   \n",
       "2020-02-13 19:38:31                 NaN                                 NaN   \n",
       "2020-02-13 19:43:32                 NaN                                 NaN   \n",
       "2020-02-13 19:48:32                 NaN                                 NaN   \n",
       "\n",
       "                     Transmitter Time (Long Integer)  PersonalMean  \\\n",
       "datetime                                                             \n",
       "2020-02-13 17:23:32                          11101.0     61.000000   \n",
       "2020-02-13 17:28:32                          11401.0     60.000000   \n",
       "2020-02-13 17:33:32                          11701.0     59.333333   \n",
       "2020-02-13 17:38:32                          12001.0     59.250000   \n",
       "2020-02-13 17:43:31                          12301.0     60.000000   \n",
       "2020-02-13 17:48:31                          12601.0     61.166667   \n",
       "2020-02-13 17:53:31                          12901.0     62.142857   \n",
       "2020-02-13 17:58:31                          13201.0     62.250000   \n",
       "2020-02-13 18:03:32                          13501.0     61.888889   \n",
       "2020-02-13 18:08:32                          13801.0     61.700000   \n",
       "2020-02-13 18:13:32                          14101.0     62.454545   \n",
       "2020-02-13 18:18:32                          14401.0     64.416667   \n",
       "2020-02-13 18:23:32                          14701.0     67.538462   \n",
       "2020-02-13 18:28:31                          15001.0     71.142857   \n",
       "2020-02-13 18:33:31                          15301.0     74.866667   \n",
       "2020-02-13 18:38:32                          15601.0     78.500000   \n",
       "2020-02-13 18:43:32                          15901.0     82.058824   \n",
       "2020-02-13 18:48:32                          16201.0     85.444444   \n",
       "2020-02-13 18:53:32                          16501.0     88.368421   \n",
       "2020-02-13 18:58:32                          16801.0     90.550000   \n",
       "2020-02-13 19:03:31                          17101.0     92.047619   \n",
       "2020-02-13 19:08:31                          17401.0     93.136364   \n",
       "2020-02-13 19:13:32                          17701.0     94.043478   \n",
       "2020-02-13 19:18:32                          18001.0     94.833333   \n",
       "2020-02-13 19:23:31                          18301.0     95.480000   \n",
       "2020-02-13 19:28:31                          18601.0     96.038462   \n",
       "2020-02-13 19:33:32                          18901.0     96.555556   \n",
       "2020-02-13 19:38:31                          19201.0     97.214286   \n",
       "2020-02-13 19:43:32                          19501.0     97.965517   \n",
       "2020-02-13 19:48:32                          19801.0     98.800000   \n",
       "\n",
       "                     PersonalStd     class  \n",
       "datetime                                    \n",
       "2020-02-13 17:23:32          NaN  PersNorm  \n",
       "2020-02-13 17:28:32     1.414214  PersNorm  \n",
       "2020-02-13 17:33:32     1.527525  PersNorm  \n",
       "2020-02-13 17:38:32     1.258306  PersNorm  \n",
       "2020-02-13 17:43:31     2.000000  PersHigh  \n",
       "2020-02-13 17:48:31     3.371449  PersHigh  \n",
       "2020-02-13 17:53:31     4.017817  PersHigh  \n",
       "2020-02-13 17:58:31     3.732100  PersNorm  \n",
       "2020-02-13 18:03:32     3.655285  PersNorm  \n",
       "2020-02-13 18:08:32     3.497618  PersNorm  \n",
       "2020-02-13 18:13:32     4.156047  PersHigh  \n",
       "2020-02-13 18:18:32     7.867752  PersHigh  \n",
       "2020-02-13 18:23:32    13.543851  PersHigh  \n",
       "2020-02-13 18:28:31    18.740565  PersHigh  \n",
       "2020-02-13 18:33:31    23.111119  PersHigh  \n",
       "2020-02-13 18:38:32    26.640821  PersHigh  \n",
       "2020-02-13 18:43:32    29.676318  PersHigh  \n",
       "2020-02-13 18:48:32    32.174565  PersHigh  \n",
       "2020-02-13 18:53:32    33.765878  PersHigh  \n",
       "2020-02-13 18:58:32    34.282841  PersHigh  \n",
       "2020-02-13 19:03:31    34.112280  PersNorm  \n",
       "2020-02-13 19:08:31    33.679576  PersNorm  \n",
       "2020-02-13 19:13:32    33.191563  PersNorm  \n",
       "2020-02-13 19:18:32    32.691797  PersNorm  \n",
       "2020-02-13 19:23:31    32.166390  PersNorm  \n",
       "2020-02-13 19:28:31    31.644880  PersNorm  \n",
       "2020-02-13 19:33:32    31.146470  PersNorm  \n",
       "2020-02-13 19:38:31    30.762359  PersNorm  \n",
       "2020-02-13 19:43:32    30.477723  PersNorm  \n",
       "2020-02-13 19:48:32    30.294417  PersNorm  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dexcom001_df.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2dfb7114830>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_filtered = dexcom001_df[(dexcom001_df.index >= '2020-02-15 00:00:00') & (dexcom001_df.index <= '2020-02-15 23:59:59')]\n",
    "\n",
    "df_norm = df_filtered[df_filtered['class'].isin(['PersNorm'])]\n",
    "\n",
    "# 나머지 데이터 선택\n",
    "df_other = df_filtered[df_filtered['class'].isin(['PersHigh', 'PersLow'])]\n",
    "\n",
    "# 그래프 그리기\n",
    "plt.figure(figsize=(10, 3))\n",
    "\n",
    "# 'PersHigh' 또는 'PersNorm'인 데이터 플롯\n",
    "plt.plot(df_norm.index, df_norm['Glucose Value (mg/dL)'], 'r', label='PersHigh/PersNorm')\n",
    "\n",
    "# 나머지 데이터 플롯\n",
    "plt.plot(df_other.index, df_other['Glucose Value (mg/dL)'], 'b', label='Other')\n",
    "\n",
    "# 그래프 제목 및 레이블\n",
    "plt.title('Glucose Value Over Time on 2020-02-14')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Glucose Value (mg/dL)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GHA6HNm7cGLDesiwtXbpU6enp6tOnj/Lz83XkyJGAbRobG1VYWKiEhAQlJSVp9uzZam5uvqgDAQAA0anDYebkyZMaPHiwSktLQ65fs2aN1q1bp7KyMtXU1Khv374qKCjQ6dOn/dsUFhbqk08+UUVFhTZv3qyqqirNmTOn80cBAACiVmxHd5gwYYImTJgQcp1lWVq7dq0ee+wxTZkyRZL06quvKjU1VRs3btSMGTN0+PBhbd26VXv37tXw4cMlSevXr9ett96qp556ShkZGRdxOAAAINp0OMx8n6NHj8rtdis/P9/flpiYqNzcXFVXV2vGjBmqrq5WUlKSP8hIUn5+vmJiYlRTU6OpU6cG9ev1euX1ev3LHo9HkuTz+eTz+ew8hKjRWjfqd3GiqY6uXlZQm53H3VW1bHscPfF7F03nZbhRS3uEu462hhm32y1JSk1NDWhPTU31r3O73erfv3/gIGJjlZyc7N+mrZUrV2rZsmVB7du3b1d8fLwdQ49aFRUVkR5CjxANdVwzMrjt3Xfftf11wl3LtscRjmPoLqLhvOwq1NIeO3fuDEu/toaZcFmyZImKior8yx6PR5mZmRo/frwSEhIiODJz+Xw+VVRUaNy4cXI6nZEejrGiqY6DSrYFtR0qKbCt/66qZdvjsPMYuotoOi/DjVrao7WOY8eODUv/toaZtLQ0SVJ9fb3S09P97fX19RoyZIh/m4aGhoD9vv32WzU2Nvr3b8vlcsnlcgW1O51OTq6LRA3tEQ119J51BLWF45jDXcu2x9GTv2/RcF52FWppj3DV0Nb7zGRnZystLU2VlZX+No/Ho5qaGuXl5UmS8vLy1NTUpNraWv82O3bsUEtLi3Jzc+0cDgAAiAIdnplpbm7W559/7l8+evSoDh48qOTkZGVlZWn+/PlasWKFBgwYoOzsbBUXFysjI0O33XabJGngwIG65ZZbdP/996usrEw+n0/z5s3TjBkz+CQTAADosA6HmX379gX8zav1WpZZs2bplVde0aOPPqqTJ09qzpw5ampq0ujRo7V161bFxcX593n99dc1b9483XzzzYqJidH06dO1bt06Gw4HAABEmw6HmTFjxsiygj+i2crhcGj58uVavnz5ebdJTk5WeXl5R18aAAAgCM9mAgAARiPMAAAAoxFmAACA0QgzAADAaIQZAABgNMIMAAAwmhHPZgKASLpq8Zagti9WTYzASACEwswMAAAwGmEGAAAYjTADAACMRpgBAABGI8wAAACjEWYAAIDRCDMAAMBohBkAAGA0wgwAADAaYQYAABiNMAMAAIxGmAEAAEYjzAAAAKMRZgAAgNEIMwAAwGiEGQAAYDTCDAAAMBphBgAAGI0wAwAAjEaYAQAARiPMAAAAoxFmAACA0WIjPQAA5rpq8ZaA5S9WTYzQSABEM2ZmAACA0WyfmTl79qxKSkr02muvye12KyMjQz/5yU/02GOPyeFwSJIsy9Ljjz+uF198UU1NTRo1apQ2bNigAQMG2D0cAO3QdoZFiu5ZllD1ANB92T4zs3r1am3YsEHPPfecDh8+rNWrV2vNmjVav369f5s1a9Zo3bp1KisrU01Njfr27auCggKdPn3a7uEAAIAezvaZmd27d2vKlCmaOPHcb3VXXXWVfv3rX+ujjz6SdG5WZu3atXrsscc0ZcoUSdKrr76q1NRUbdy4UTNmzLB7SAAAoAezfWbmhhtuUGVlpT777DNJ0h/+8Ad9+OGHmjBhgiTp6NGjcrvdys/P9++TmJio3NxcVVdX2z0cAADQw9k+M7N48WJ5PB7l5OSoV69eOnv2rJ544gkVFhZKktxutyQpNTU1YL/U1FT/ura8Xq+8Xq9/2ePxSJJ8Pp98Pp/dhxAVWutG/S5OT6mjq5cV1Nb2mEJtc6F9OqKratn2OEK9XriPNdx6ynnZHVBLe4S7jg7Lsi78U9sBv/nNb7Rw4UI9+eSTuvbaa3Xw4EHNnz9fTz/9tGbNmqXdu3dr1KhROn78uNLT0/373XHHHXI4HHrjjTeC+iwpKdGyZcuC2svLyxUfH2/n8AEAQJicOnVKd999t06cOKGEhATb+rU9zGRmZmrx4sWaO3euv23FihV67bXX9D//8z/605/+pKuvvloHDhzQkCFD/NvceOONGjJkiJ599tmgPkPNzGRmZuovf/mLrcWIJj6fTxUVFRo3bpycTmekh2OsnlLHQSXbgtoOlRRccJsL7dMRXVXLtscRaszhPtZw6ynnZXdALe3RWsfc3Fylp6fbHmZs/zPTqVOnFBMTeClOr1691NLSIknKzs5WWlqaKisr/WHG4/GopqZGP/3pT0P26XK55HK5gtqdTicn10WihvYwvY7es46gtrbHE2qbC+3TGeGuZdvjCPVaXXWs4Wb6edmdUEt7hKuGtoeZSZMm6YknnlBWVpauvfZaHThwQE8//bTuu+8+SZLD4dD8+fO1YsUKDRgwQNnZ2SouLlZGRoZuu+02u4cDAAB6ONvDzPr161VcXKwHH3xQDQ0NysjI0L/9279p6dKl/m0effRRnTx5UnPmzFFTU5NGjx6trVu3Ki4uzu7hAMD34gZ5gPlsDzP9+vXT2rVrtXbt2vNu43A4tHz5ci1fvtzulwcAAFGGZzMBAACjEWYAAIDRCDMAAMBohBkAAGA02y8ABtD98QkeAD0JMzMAAMBohBkAAGA0wgwAADAaYQYAABiNMAMAAIxGmAEAAEYjzAAAAKMRZgAAgNG4aR6AkLixHgBTMDMDAACMxswMAHRC25mrL1ZNjNBIADAzAwAAjMbMDIAeg9kSIDoxMwMAAIxGmAEAAEYjzAAAAKMRZgAAgNEIMwAAwGiEGQAAYDTCDAAAMBr3mQHQY/F8KSA6MDMDAACMRpgBAABGI8wAAACjEWYAAIDRuAAY6OG4CBZAT8fMDAAAMFpYwszXX3+te+65RykpKerTp4+uu+467du3z7/esiwtXbpU6enp6tOnj/Lz83XkyJFwDAVAF7pq8ZagLwAIN9vDzN/+9jeNGjVKTqdT7733nj799FP96le/0qWXXurfZs2aNVq3bp3KyspUU1Ojvn37qqCgQKdPn7Z7OAAAoIez/ZqZ1atXKzMzUy+//LK/LTs72///lmVp7dq1euyxxzRlyhRJ0quvvqrU1FRt3LhRM2bMsHtIALqRULM1X6yaGIGRAOgpbA8z77zzjgoKCnT77bdr165duvzyy/Xggw/q/vvvlyQdPXpUbrdb+fn5/n0SExOVm5ur6urqkGHG6/XK6/X6lz0ejyTJ5/PJ5/PZfQhRobVu1O/imFBHVy8roq/ftjahxvPdn+WLqWUkj7U7nQMmnJemoJb2CHcdHZZl2frTHxcXJ0kqKirS7bffrr179+qRRx5RWVmZZs2apd27d2vUqFE6fvy40tPT/fvdcccdcjgceuONN4L6LCkp0bJly4Lay8vLFR8fb+fwAQBAmJw6dUp33323Tpw4oYSEBNv6tT3M9O7dW8OHD9fu3bv9bQ8//LD27t2r6urqToWZUDMzmZmZ+stf/mJrMaKJz+dTRUWFxo0bJ6fTGenhGMuEOg4q2RbR1z9UUhCwHGo8h0oKLljLtvu17fd8fXeVUOOJFBPOS1NQS3u01jE3N1fp6em2hxnb/8yUnp6ua665JqBt4MCB+u1vfytJSktLkyTV19cHhJn6+noNGTIkZJ8ul0sulyuo3el0cnJdJGpoj+5cR+9ZR0Rff0Dx9jYtweP5bu3OV8u2xxHcb+i+u0qo8UT6WqDufF6ahlraI1w1tP3TTKNGjVJdXV1A22effaYrr7xS0rmLgdPS0lRZWelf7/F4VFNTo7y8PLuHAwAAejjbZ2YWLFigG264Qb/85S91xx136KOPPtILL7ygF154QZLkcDg0f/58rVixQgMGDFB2draKi4uVkZGh2267ze7hADAQ96cB0BG2h5kRI0bo7bff1pIlS7R8+XJlZ2dr7dq1Kiws9G/z6KOP6uTJk5ozZ46ampo0evRobd261X/xMAAAQHuF5dlMP/rRj/SjH/3ovOsdDoeWL1+u5cuXh+PlAQBAFOHZTAAAwGiEGQAAYDTCDAAAMBphBgAAGI0wAwAAjEaYAQAARiPMAAAAoxFmAACA0QgzAADAaIQZAABgNMIMAAAwGmEGAAAYLSwPmgQABLtq8Zagti9WTYzASICehZkZAABgNMIMAAAwGmEGAAAYjWtmgB4m1HUZ6Fm49gYIxMwMAAAwGmEGAAAYjTADAACMRpgBAABG4wJgAAgTLsYGugYzMwAAwGiEGQAAYDTCDAAAMBrXzACIuKsWb5Grl6U1I6VBJdskOSI9JAAGYWYGAAAYjTADAACMRpgBAABGI8wAAACjEWYAAIDRwh5mVq1aJYfDofnz5/vbTp8+rblz5yolJUWXXHKJpk+frvr6+nAPBQAA9EBhDTN79+7Vv//7v+uf//mfA9oXLFigTZs26c0339SuXbt0/PhxTZs2LZxDAQAAPVTYwkxzc7MKCwv14osv6tJLL/W3nzhxQi+99JKefvpp3XTTTRo2bJhefvll7d69W3v27AnXcAAAQA8VtpvmzZ07VxMnTlR+fr5WrFjhb6+trZXP51N+fr6/LScnR1lZWaqurtb1118f1JfX65XX6/UvezweSZLP55PP5wvXIfRorXWjfhenO9bR1cuK9BA6xRVjBfw3WnTm3An1Pf5uP93xvDQVtbRHuOsYljDzm9/8Rvv379fevXuD1rndbvXu3VtJSUkB7ampqXK73SH7W7lypZYtWxbUvn37dsXHx9sy5mhVUVER6SH0CN2pjmtGRnoEF+cXw1siPYQu9e6773Z4n1Df41D9dKfz0nTU0h47d+4MS7+2h5mvvvpKjzzyiCoqKhQXF2dLn0uWLFFRUZF/2ePxKDMzU+PHj1dCQoItrxFtfD6fKioqNG7cODmdzkgPx1jdsY7nHgdgHleMpV8Mb1Hxvhh5W6LncQaHSgo6vE+o7/F3++mO56WpqKU9Wus4duzYsPRve5ipra1VQ0OD/uVf/sXfdvbsWVVVVem5557Ttm3bdObMGTU1NQXMztTX1ystLS1kny6XSy6XK6jd6XRycl0kamiP7lRH71mzg4C3xWH8MXREZ86bUPUJ1U93Oi9NRy3tEa4a2h5mbr75Zv33f/93QNu9996rnJwcLVq0SJmZmXI6naqsrNT06dMlSXV1dTp27Jjy8vLsHg4AAOjhbA8z/fr106BBgwLa+vbtq5SUFH/77NmzVVRUpOTkZCUkJOihhx5SXl5eyIt/AQAAvk/YPs30fZ555hnFxMRo+vTp8nq9Kigo0PPPPx+JoQAAAMN1SZh5//33A5bj4uJUWlqq0tLSrnh5AADQg0VkZgYAcM5Vi7cELH+xamKERgKYiwdNAgAAozEzAwCICGalYBdmZgAAgNEIMwAAwGiEGQAAYDTCDAAAMBphBgAAGI0wAwAAjEaYAQAARuM+MwAQpdre50XiXi8wEzMzAADAaIQZAABgNP7MBBgs1J8J0PN05feZRwzARMzMAAAAoxFmAACA0QgzAADAaFwzA3QBrkMAgPBhZgYAABiNmRkA6AG+O/vn6mVpzcgIDgboYszMAAAAozEzAxiE+8oAQDBmZgAAgNGYmQEAnBcPo4QJmJkBAABGY2YGAHqoQSXb5D3r8C8zo4KeipkZAABgNGZmgG6KTy5FJxO/71xXg0hjZgYAABiNMAMAAIxGmAEAAEYjzAAAAKPZHmZWrlypESNGqF+/furfv79uu+021dXVBWxz+vRpzZ07VykpKbrkkks0ffp01dfX2z0UAAAQBWwPM7t27dLcuXO1Z88eVVRUyOfzafz48Tp58qR/mwULFmjTpk168803tWvXLh0/flzTpk2zeygAACAK2P7R7K1btwYsv/LKK+rfv79qa2v1wx/+UCdOnNBLL72k8vJy3XTTTZKkl19+WQMHDtSePXt0/fXX2z0kwAgmfiQXALqDsN9n5sSJE5Kk5ORkSVJtba18Pp/y8/P92+Tk5CgrK0vV1dUhw4zX65XX6/UvezweSZLP55PP5wvn8Hus1rpRv4vT3jq6elkh9/u+baKNK8YK+C8673y1bHvedfaca08/7Xlvac/PRaTxXmmPcNfRYVlW2N45WlpaNHnyZDU1NenDDz+UJJWXl+vee+8NCCeSNHLkSI0dO1arV68O6qekpETLli0Lai8vL1d8fHx4Bg8AAGx16tQp3X333Tpx4oQSEhJs6zesMzNz587VoUOH/EGms5YsWaKioiL/ssfjUWZmpsaPH29rMaKJz+dTRUWFxo0bJ6fTGenhGKu9dRxUsi1g+VBJwQW3iTauGEu/GN6i4n0x8rY4LrwDzivctWx7/oY6d0Od42215+fiQvu0d7/O4r3SHq11HDt2bFj6D1uYmTdvnjZv3qyqqipdccUV/va0tDSdOXNGTU1NSkpK8rfX19crLS0tZF8ul0sulyuo3el0cnJdJGpojwvV8bsP+2vd/kLbRCtvi4Na2CRctRxQvL1NS/BrtOd9pT0/Fxfap737hdL2OrVQj2AYVLJNa0ZKQ5/YIe9ZB49puEjh+vfG9k8zWZalefPm6e2339aOHTuUnZ0dsH7YsGFyOp2qrKz0t9XV1enYsWPKy8uzezgAAKCHs31mZu7cuSovL9fvfvc79evXT263W5KUmJioPn36KDExUbNnz1ZRUZGSk5OVkJCghx56SHl5eXySCQBgnPbM8CC8bA8zGzZskCSNGTMmoP3ll1/WT37yE0nSM888o5iYGE2fPl1er1cFBQV6/vnn7R4KAACIAraHmfZ8OCouLk6lpaUqLS21++UBAIYKda8lZjnQHjybCQAAGI0wAwAAjEaYAQAARgv74wwAAOgsnlmG9mBmBgAAGI0wAwAAjMafmYAIYOoc6Fr8zPVszMwAAACjMTMDAIBCz964el14G0QeMzMAAMBohBkAAGA0wgwAADAa18wAAGzX9tqScD4wkgdUgpkZAABgNGZmgA5o+xugq5elNSMjNBgA58WnjqILMzMAAMBozMwAAMKOmZJA3e06n+42no5iZgYAABiNmRnAZvwGCgBdi5kZAABgNMIMAAAwGmEGAAAYjTADAACMxgXAwPfgYl4A6P6YmQEAAEZjZgawwaCSbfKedUR6GAC6gc7egM6uh3N25UM+uwtmZgAAgNGYmemhTL81dVeIxt9eAESfaPj3gJkZAABgNGZm0K11ZvYkGn4LAdDz8V7WfszMAAAAo0V0Zqa0tFRPPvmk3G63Bg8erPXr12vkyJGRHFKP9t2U7+plaU07St2e3wwifeW+XbinDIDurru9b3YXEZuZeeONN1RUVKTHH39c+/fv1+DBg1VQUKCGhoZIDQkAABgoYjMzTz/9tO6//37de++9kqSysjJt2bJF//Ef/6HFixdHaliSOvcbejjTcTiTeGfuj9Ke+nSmhuHq92L2AwA7dLf3oO42nosVkTBz5swZ1dbWasmSJf62mJgY5efnq7q6Omh7r9crr9frXz5x4oQkqbGxUT6fz/bxxX57ssP7/PWvf7V9HK3ajqc9r3WhY4htsXTqVItifTE628LN3jqLOtqHWtqHWtqnu9cy1L8Hnfk3rL19d5bP59OpU6fU2NgoSbIsy7a+Wzvscl9//bUlydq9e3dA+8KFC62RI0cGbf/4449bkvjiiy+++OKLrx7w9dVXX9maK4z4aPaSJUtUVFTkX25paVFjY6NSUlLkcHS/pGwCj8ejzMxMffXVV0pISIj0cIxFHe1DLe1DLe1DLe3RWsdjx47J4XAoIyPD1v4jEmYuu+wy9erVS/X19QHt9fX1SktLC9re5XLJ5XIFtCUlJYVziFEjISGBH1AbUEf7UEv7UEv7UEt7JCYmhqWOEfk0U+/evTVs2DBVVlb621paWlRZWam8vLxIDAkAABgqYn9mKioq0qxZszR8+HCNHDlSa9eu1cmTJ/2fbgIAAGiPiIWZO++8U//3f/+npUuXyu12a8iQIdq6datSU1MjNaSo4nK59Pjjjwf9+Q4dQx3tQy3tQy3tQy3tEe46OizL7s9HAQAAdB2ezQQAAIxGmAEAAEYjzAAAAKMRZgAAgNEIMz3c119/rXvuuUcpKSnq06ePrrvuOu3bt8+/3rIsLV26VOnp6erTp4/y8/N15MiRCI64ezp79qyKi4uVnZ2tPn366Oqrr9YvfvGLgOeLUMvQqqqqNGnSJGVkZMjhcGjjxo0B69tTt8bGRhUWFiohIUFJSUmaPXu2mpubu/AoIu/76ujz+bRo0SJdd9116tu3rzIyMvTjH/9Yx48fD+iDOp5zoXPyux544AE5HA6tXbs2oJ1antOeWh4+fFiTJ09WYmKi+vbtqxEjRujYsWP+9adPn9bcuXOVkpKiSy65RNOnTw+6qe6FEGZ6sL/97W8aNWqUnE6n3nvvPX366af61a9+pUsvvdS/zZo1a7Ru3TqVlZWppqZGffv2VUFBgU6fPh3BkXc/q1ev1oYNG/Tcc8/p8OHDWr16tdasWaP169f7t6GWoZ08eVKDBw9WaWlpyPXtqVthYaE++eQTVVRUaPPmzaqqqtKcOXO66hC6he+r46lTp7R//34VFxdr//79euutt1RXV6fJkycHbEcdz7nQOdnq7bff1p49e0Leep9annOhWv7xj3/U6NGjlZOTo/fff18ff/yxiouLFRcX599mwYIF2rRpk958803t2rVLx48f17Rp0zo2EFuf9IRuZdGiRdbo0aPPu76lpcVKS0uznnzySX9bU1OT5XK5rF//+tddMURjTJw40brvvvsC2qZNm2YVFhZalkUt20uS9fbbb/uX21O3Tz/91JJk7d2717/Ne++9ZzkcDuvrr7/usrF3J23rGMpHH31kSbK+/PJLy7Ko4/mcr5b/+7//a11++eXWoUOHrCuvvNJ65pln/OuoZWihannnnXda99xzz3n3aWpqspxOp/Xmm2/62w4fPmxJsqqrq9v92szM9GDvvPOOhg8frttvv139+/fX0KFD9eKLL/rXHz16VG63W/n5+f62xMRE5ebmqrq6OhJD7rZuuOEGVVZW6rPPPpMk/eEPf9CHH36oCRMmSKKWndWeulVXVyspKUnDhw/3b5Ofn6+YmBjV1NR0+ZhNceLECTkcDv9z7Khj+7W0tGjmzJlauHChrr322qD11LJ9WlpatGXLFv3TP/2TCgoK1L9/f+Xm5gb8Kaq2tlY+ny/gPSAnJ0dZWVkdeu8kzPRgf/rTn7RhwwYNGDBA27Zt009/+lM9/PDD+s///E9JktvtlqSguy6npqb61+GcxYsXa8aMGcrJyZHT6dTQoUM1f/58FRYWSqKWndWeurndbvXv3z9gfWxsrJKTk6nteZw+fVqLFi3SXXfd5X+oH3Vsv9WrVys2NlYPP/xwyPXUsn0aGhrU3NysVatW6ZZbbtH27ds1depUTZs2Tbt27ZJ0rpa9e/cOenh0R987I/Y4A4RfS0uLhg8frl/+8peSpKFDh+rQoUMqKyvTrFmzIjw6s/zXf/2XXn/9dZWXl+vaa6/VwYMHNX/+fGVkZFBLdCs+n0933HGHLMvShg0bIj0c49TW1urZZ5/V/v375XA4Ij0co7W0tEiSpkyZogULFkiShgwZot27d6usrEw33nijba/FzEwPlp6ermuuuSagbeDAgf6ryNPS0iQp6Krx+vp6/zqcs3DhQv/szHXXXaeZM2dqwYIFWrlypSRq2VntqVtaWpoaGhoC1n/77bdqbGyktm20Bpkvv/xSFRUV/lkZiTq21wcffKCGhgZlZWUpNjZWsbGx+vLLL/Wzn/1MV111lSRq2V6XXXaZYmNjL/jv0JkzZ9TU1BSwTUffOwkzPdioUaNUV1cX0PbZZ5/pyiuvlCRlZ2crLS1NlZWV/vUej0c1NTXKy8vr0rF2d6dOnVJMTOCPS69evfy/eVDLzmlP3fLy8tTU1KTa2lr/Njt27FBLS4tyc3O7fMzdVWuQOXLkiH7/+98rJSUlYD11bJ+ZM2fq448/1sGDB/1fGRkZWrhwobZt2yaJWrZX7969NWLEiO/9d2jYsGFyOp0B7wF1dXU6duxYx947O3q1Mszx0UcfWbGxsdYTTzxhHTlyxHr99det+Ph467XXXvNvs2rVKispKcn63e9+Z3388cfWlClTrOzsbOvvf/97BEfe/cyaNcu6/PLLrc2bN1tHjx613nrrLeuyyy6zHn30Uf821DK0b775xjpw4IB14MABS5L19NNPWwcOHPB/yqY9dbvlllusoUOHWjU1NdaHH35oDRgwwLrrrrsidUgR8X11PHPmjDV58mTriiuusA4ePGj9+c9/9n95vV5/H9TxnAudk221/TSTZVHLVheq5VtvvWU5nU7rhRdesI4cOWKtX7/e6tWrl/XBBx/4+3jggQesrKwsa8eOHda+ffusvLw8Ky8vr0PjIMz0cJs2bbIGDRpkuVwuKycnx3rhhRcC1re0tFjFxcVWamqq5XK5rJtvvtmqq6uL0Gi7L4/HYz3yyCNWVlaWFRcXZ/3DP/yD9fOf/zzgHwpqGdrOnTstSUFfs2bNsiyrfXX761//at11113WJZdcYiUkJFj33nuv9c0330TgaCLn++p49OjRkOskWTt37vT3QR3PudA52VaoMEMtz2lPLV966SXrH//xH624uDhr8ODB1saNGwP6+Pvf/249+OCD1qWXXmrFx8dbU6dOtf785z93aBwOy/rOLUwBAAAMwzUzAADAaIQZAABgNMIMAAAwGmEGAAAYjTADAACMRpgBAABGI8wAAACjEWYAAIDRCDMAAMBohBkAAGA0wgwAADAaYQYAABjt/wHHkk/IY6wnmAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dexcom001_df['Glucose Value (mg/dL)'].hist(bins=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ACC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/ACC_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>acc_x</th>\n",
       "      <th>acc_y</th>\n",
       "      <th>acc_z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-13 15:28:50.000000</td>\n",
       "      <td>-34.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-13 15:28:50.031250</td>\n",
       "      <td>-34.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-13 15:28:50.062500</td>\n",
       "      <td>-34.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-13 15:28:50.093750</td>\n",
       "      <td>-36.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13 15:28:50.125000</td>\n",
       "      <td>-35.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     datetime   acc_x   acc_y   acc_z\n",
       "0  2020-02-13 15:28:50.000000   -34.0    17.0    55.0\n",
       "1  2020-02-13 15:28:50.031250   -34.0    17.0    52.0\n",
       "2  2020-02-13 15:28:50.062500   -34.0    19.0    51.0\n",
       "3  2020-02-13 15:28:50.093750   -36.0    18.0    51.0\n",
       "4  2020-02-13 15:28:50.125000   -35.0    17.0    52.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acc001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc001_df['datetime']=pd.to_datetime(acc001_df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc_resampled = acc001_df[(acc001_df['datetime'] >= '2020-02-14 00:00:00') & (acc001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "acc_resampled.plot(y=[' acc_x', ' acc_y', ' acc_z'], figsize=(10,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc_mean = acc_resampled.mean()\n",
    "acc_std = acc_resampled.std()\n",
    "acc_min = acc_resampled.min()\n",
    "acc_max = acc_resampled.max()\n",
    "acc_q1g = acc_resampled.quantile(0.25)\n",
    "acc_q3g = acc_resampled.quantile(0.75)\n",
    "acc_skew = acc_resampled.skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "acc_mean :  acc_x    13.138889\n",
      " acc_y    -0.472222\n",
      " acc_z    22.927083\n",
      "dtype: float64\n",
      "acc_std :  acc_x    38.123970\n",
      " acc_y    29.569842\n",
      " acc_z    33.008576\n",
      "dtype: float64\n",
      "acc_min :  acc_x   -63.0\n",
      " acc_y   -75.0\n",
      " acc_z   -63.0\n",
      "dtype: float64\n",
      "acc_max :  acc_x    72.0\n",
      " acc_y    60.0\n",
      " acc_z    73.0\n",
      "dtype: float64\n",
      "acc_q1g :  acc_x    -5.0\n",
      " acc_y   -19.0\n",
      " acc_z    -1.0\n",
      "Name: 0.25, dtype: float64\n",
      "acc_q3g :  acc_x    45.25\n",
      " acc_y    21.00\n",
      " acc_z    55.25\n",
      "Name: 0.75, dtype: float64\n",
      "acc_skew :  acc_x   -0.629853\n",
      " acc_y   -0.562086\n",
      " acc_z   -0.488216\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(f'acc_mean : {acc_mean}')\n",
    "print(f'acc_std : {acc_std}')\n",
    "print(f'acc_min : {acc_min}')\n",
    "print(f'acc_max : {acc_max}')\n",
    "print(f'acc_q1g : {acc_q1g}')\n",
    "print(f'acc_q3g : {acc_q3g}')\n",
    "print(f'acc_skew : {acc_skew}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "eda001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/EDA_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>datetime</th>\n",
       "      <th>eda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-13 15:28:50.000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-13 15:28:50.250</td>\n",
       "      <td>0.001281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-13 15:28:50.500</td>\n",
       "      <td>0.026905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-13 15:28:50.750</td>\n",
       "      <td>0.028186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13 15:28:51.000</td>\n",
       "      <td>0.029467</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  datetime       eda\n",
       "0  2020-02-13 15:28:50.000  0.000000\n",
       "1  2020-02-13 15:28:50.250  0.001281\n",
       "2  2020-02-13 15:28:50.500  0.026905\n",
       "3  2020-02-13 15:28:50.750  0.028186\n",
       "4  2020-02-13 15:28:51.000  0.029467"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eda001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "eda001_df['datetime']=pd.to_datetime(eda001_df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "eda_resampled = eda001_df[(eda001_df['datetime'] >= '2020-02-14 00:00:00') & (eda001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eda_resampled.plot(y=' eda', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "eda_mean = eda_resampled[' eda'].mean()\n",
    "eda_std = eda_resampled[' eda'].std()\n",
    "eda_min = eda_resampled[' eda'].min()\n",
    "eda_max = eda_resampled[' eda'].max()\n",
    "eda_q1g = eda_resampled[' eda'].quantile(0.25)\n",
    "eda_q3g = eda_resampled[' eda'].quantile(0.75)\n",
    "eda_skew = eda_resampled[' eda'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eda_mean : 1.6719155729166668\n",
      "eda_std : 3.3140254377832212\n",
      "eda_min : 0.019218\n",
      "eda_max : 27.837559\n",
      "eda_q1g : 0.1727055\n",
      "eda_q3g : 1.52700675\n",
      "eda_skew : 3.734634262316951\n"
     ]
    }
   ],
   "source": [
    "print(f'eda_mean : {eda_mean}')\n",
    "print(f'eda_std : {eda_std}')\n",
    "print(f'eda_min : {eda_min}')\n",
    "print(f'eda_max : {eda_max}')\n",
    "print(f'eda_q1g : {eda_q1g}')\n",
    "print(f'eda_q3g : {eda_q3g}')\n",
    "print(f'eda_skew : {eda_skew}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# peak detection\n",
    "peaks_idx, properties = find_peaks(eda_resampled[' eda'], height=0, distance=4, prominence=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "peak_eda = len(peaks_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rolling window에서 피크를 찾는 함수\n",
    "def find_peaks_in_rolling_window(data, window_size):\n",
    "    number_of_windows = 0\n",
    "    peaks_in_window = 0\n",
    "    for window_data in data.rolling(window=window_size):\n",
    "        peaks, _ = find_peaks(window_data[' eda'], height=0, distance=4, prominence=0.3)\n",
    "        if peaks.any():\n",
    "            peaks_in_window += len(peaks)\n",
    "        number_of_windows += 1\n",
    "    return number_of_windows, peaks_in_window\n",
    "\n",
    "number_of_windows, peaks_in_window = find_peaks_in_rolling_window(eda_resampled, window_size='2H')\n",
    "\n",
    "peakEDA2hr_sum = peaks_in_window\n",
    "peakEDA2hr_mean = peaks_in_window / number_of_windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PeakEDA : 28\n",
      "PeakEDA2hr_sum : 565\n",
      "PeakEDA2hr_mean : 1.9618055555555556\n"
     ]
    }
   ],
   "source": [
    "print(f'PeakEDA : {peak_eda}')\n",
    "print(f'PeakEDA2hr_sum : {peakEDA2hr_sum}')\n",
    "print(f'PeakEDA2hr_mean : {peakEDA2hr_mean}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BVP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "bvp001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/BVP_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>datetime</th>\n",
       "      <th>bvp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-13 15:28:50.000000</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-13 15:28:50.015625</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-13 15:28:50.031250</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-13 15:28:50.046875</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13 15:28:50.062500</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     datetime   bvp\n",
       "0  2020-02-13 15:28:50.000000  -0.0\n",
       "1  2020-02-13 15:28:50.015625  -0.0\n",
       "2  2020-02-13 15:28:50.031250  -0.0\n",
       "3  2020-02-13 15:28:50.046875  -0.0\n",
       "4  2020-02-13 15:28:50.062500  -0.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bvp001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "bvp001_df['datetime']=pd.to_datetime(bvp001_df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "bvp_resampled = bvp001_df[(bvp001_df['datetime'] >= '2020-02-14 00:00:00') & (bvp001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bvp_resampled.plot(y=' bvp', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "hr001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/HR_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>datetime</th>\n",
       "      <th>hr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/13/20 15:29</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/13/20 15:29</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2/13/20 15:29</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/13/20 15:29</td>\n",
       "      <td>82.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2/13/20 15:29</td>\n",
       "      <td>82.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        datetime    hr\n",
       "0  2/13/20 15:29  94.0\n",
       "1  2/13/20 15:29  99.0\n",
       "2  2/13/20 15:29  94.0\n",
       "3  2/13/20 15:29  82.5\n",
       "4  2/13/20 15:29  82.6"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hr001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "hr001_df['datetime']=pd.to_datetime(hr001_df['datetime'], format='%m/%d/%y %H:%M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "hr_resampled = hr001_df[(hr001_df['datetime'] >= '2020-02-14 00:00:00') & (hr001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>hr</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:00:00</th>\n",
       "      <td>68.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:05:00</th>\n",
       "      <td>67.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:10:00</th>\n",
       "      <td>59.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:15:00</th>\n",
       "      <td>58.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:20:00</th>\n",
       "      <td>55.48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        hr\n",
       "datetime                  \n",
       "2020-02-14 00:00:00  68.65\n",
       "2020-02-14 00:05:00  67.55\n",
       "2020-02-14 00:10:00  59.60\n",
       "2020-02-14 00:15:00  58.73\n",
       "2020-02-14 00:20:00  55.48"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hr_resampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hr_resampled.plot(y=' hr', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "hr_mean = hr_resampled[' hr'].mean()\n",
    "hr_std = hr_resampled[' hr'].std()\n",
    "hr_min = hr_resampled[' hr'].min()\n",
    "hr_max = hr_resampled[' hr'].max()\n",
    "hr_q1g = hr_resampled[' hr'].quantile(0.25)\n",
    "hr_q3g = hr_resampled[' hr'].quantile(0.75)\n",
    "hr_skew = hr_resampled[' hr'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hr_mean : 74.21739583333334\n",
      "hr_std : 12.773160169700324\n",
      "hr_min : 53.98\n",
      "hr_max : 124.55\n",
      "hr_q1g : 65.0825\n",
      "hr_q3g : 83.005\n",
      "hr_skew : 0.7961777945916989\n"
     ]
    }
   ],
   "source": [
    "print(f'hr_mean : {hr_mean}')\n",
    "print(f'hr_std : {hr_std}')\n",
    "print(f'hr_min : {hr_min}')\n",
    "print(f'hr_max : {hr_max}')\n",
    "print(f'hr_q1g : {hr_q1g}')\n",
    "print(f'hr_q3g : {hr_q3g}')\n",
    "print(f'hr_skew : {hr_skew}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IBI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "ibi001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/IBI_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>datetime</th>\n",
       "      <th>ibi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-13 15:33:22.059328</td>\n",
       "      <td>0.828163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-13 15:33:22.934368</td>\n",
       "      <td>0.875040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-13 15:34:21.593303</td>\n",
       "      <td>0.984420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-13 15:34:22.483969</td>\n",
       "      <td>0.890666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13 15:34:23.421512</td>\n",
       "      <td>0.937543</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     datetime       ibi\n",
       "0  2020-02-13 15:33:22.059328  0.828163\n",
       "1  2020-02-13 15:33:22.934368  0.875040\n",
       "2  2020-02-13 15:34:21.593303  0.984420\n",
       "3  2020-02-13 15:34:22.483969  0.890666\n",
       "4  2020-02-13 15:34:23.421512  0.937543"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ibi001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "ibi001_df['datetime']=pd.to_datetime(ibi001_df['datetime'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5분 간격 resampling할 때, NaN을 보간하여 채우기 위해 interpolate 보정해줌"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "ibi_resampled = ibi001_df[(ibi001_df['datetime'] >= '2020-02-14 00:00:00') & (ibi001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first().interpolate(method='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " ibi    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ibi_resampled.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "ibi_resampled[' ibi'] = ibi_resampled[' ibi'] * 1000 # 0.xx 초 -> 밀리초 단위로"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>ibi</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:00:00</th>\n",
       "      <td>875.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:05:00</th>\n",
       "      <td>843.789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:10:00</th>\n",
       "      <td>968.794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:15:00</th>\n",
       "      <td>1156.303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14 00:20:00</th>\n",
       "      <td>953.169</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          ibi\n",
       "datetime                     \n",
       "2020-02-14 00:00:00   875.040\n",
       "2020-02-14 00:05:00   843.789\n",
       "2020-02-14 00:10:00   968.794\n",
       "2020-02-14 00:15:00  1156.303\n",
       "2020-02-14 00:20:00   953.169"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ibi_resampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ibi_resampled.plot(y=' ibi', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "maxHRV = ibi_resampled[' ibi'].max()\n",
    "minHRV = ibi_resampled[' ibi'].min()\n",
    "medianHRV = ibi_resampled[' ibi'].median()\n",
    "meanHRV = ibi_resampled[' ibi'].mean()\n",
    "sdnn = ibi_resampled[' ibi'].std()\n",
    "\n",
    "nn50 = 0.\n",
    "for i in range(len(ibi_resampled)-1):\n",
    "    if np.abs(ibi_resampled.iloc[i+1][' ibi'] - ibi_resampled.iloc[i][' ibi']) > 50:\n",
    "        nn50 +=1\n",
    "\n",
    "pnn50 = nn50/len(ibi_resampled)\n",
    "\n",
    "rmssd = 0.\n",
    "for i in range(len(ibi_resampled)-1):\n",
    "    rmssd = np.abs(ibi_resampled.iloc[i+1][' ibi'] - ibi_resampled.iloc[i][' ibi'])**2\n",
    "rmssd = np.sqrt(rmssd) / len(ibi_resampled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "maxHRV : 1625.0739999999998\n",
      "minHRV : 421.8939999999999\n",
      "medianHRV : 856.8098333333332\n",
      "meanHRV : 861.4760243055555\n",
      "SDNN : 150.723369258299\n",
      "NN50 : 173.0\n",
      "pNN50 : 0.6006944444444444\n",
      "RMSSD : 0.5968124999999994\n"
     ]
    }
   ],
   "source": [
    "print(f'maxHRV : {maxHRV}')\n",
    "print(f'minHRV : {minHRV}')\n",
    "print(f'medianHRV : {medianHRV}')\n",
    "print(f'meanHRV : {meanHRV}')\n",
    "print(f'SDNN : {sdnn}')\n",
    "print(f'NN50 : {nn50}')\n",
    "print(f'pNN50 : {pnn50}')\n",
    "print(f'RMSSD : {rmssd}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TEMP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp001_df = pd.read_csv('./big-ideas-lab-glycemic-variability-and-wearable-device-data-1.1.2/001/TEMP_001.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>datetime</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-13 15:28:50.000</td>\n",
       "      <td>30.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-13 15:28:50.250</td>\n",
       "      <td>30.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-13 15:28:50.500</td>\n",
       "      <td>30.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-13 15:28:50.750</td>\n",
       "      <td>30.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-13 15:28:51.000</td>\n",
       "      <td>30.21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  datetime   temp\n",
       "0  2020-02-13 15:28:50.000  30.21\n",
       "1  2020-02-13 15:28:50.250  30.21\n",
       "2  2020-02-13 15:28:50.500  30.21\n",
       "3  2020-02-13 15:28:50.750  30.21\n",
       "4  2020-02-13 15:28:51.000  30.21"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp001_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp001_df['datetime']=pd.to_datetime(temp001_df['datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_resampled = temp001_df[(temp001_df['datetime'] >= '2020-02-14 00:00:00') & (temp001_df['datetime'] <= '2020-02-14 23:59:59')].set_index('datetime').resample('5Min').first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='datetime'>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mf8N6eIjzfbaczsX1saY9VxVqDY5nFKNPgCtcHRQora7F+/+cxdf703DjgEC8f9sAkx6PiIiIbFutVocnf0xAda0OIyM8ce9I0y8lUtegEDekF1biaHoRxkR6t/n1ja3x2B7tnmOj1WqxZs0aVFRUIC4uDnl5eThw4AB8fHwwYsQI+Pr6YuzYsdizZ0+z+1Gr1SgtLa33VdfgUA/MGarvZCWTSvDRHQOb7LVtDYzzbPak5GPS+zuRklcOpVyKaX39zDIeY2vpwsrOC2xKqmrx1E/HIQj6eS4Pj2392jSuDgoEuOozWWdaMc9GEAT8aFhw6o6hIR0OagB92+cbB+qDmV+Pmr4c7eU/TuGOzw5g0Bubcfun+zHxvZ34cl8adIK+8UHd+VhERERELVm+5RwSL5XA1V6Bpbf27/SEgHFawZE2zrMpKFdj3hcHEfnC35j0/k489WMC/krMatA4rLXaHNicOHECTk5OUKlUePjhh7Fu3TrExMTgwoULAIBXXnkFDzzwADZu3IhBgwZh4sSJOHeu6fkRS5Ysgaurq/gVHNywHe+i6b1x86AgvD+7v9U0CmhK3wBXKOVSVNZocf5yBQDgzmEhcGlFJqIzeIrNAzovsHnp95PILK5CqKcDXq6zlk5rRRuyNqdb0ZL6QGohLuRXwFEpw4z+psusGMvRdp69bNIOcmqNFhsN6zBpdQLiLxTicpkaPb0c4eOsgkYnYJ+hFTgRERFRSzKLq/B/O88DAJbc1K9L5qMb1/pLSC9usousTidg+5k8bDyZg8ziKpzKKsENH+3FrrOXodUJSMkrx6/HMrHw+2O4/dN4nM1te+OoNt/OjoqKQkJCAkpKSvDzzz9j/vz52LlzJ3Q6/VyAhx56CPfcc4/+hxw4EFu3bsUXX3yBJUuWNLq/xYsX46mnnhK/Ly0tbRDcuNor8N7s/m0dqkWyV8rwydzBOJVZgj4Brugb6ApvZ/NloNw7uRTtr8Qs/J6QBZlUgg9uGwCndmRQevs7Y9uZvFYFNmsOpgPQl/aZIltjFOHjhP5Brjh+qQR/JGTh3lGmSenGXyhEuVoDb2cV1j4Uhx3JeVApZLhpUCDeWn8aX+2/iJ1nL2NKH/Nk9IiIiMi6fLUvDRqdgLienri2X9c0por2c4aDUoYytQbn8soR5edc7/mTmSV44beTDZY8AYAwTwe8N7s/Sqs0iE8twFf70nAgtRDXLt+Nt2+OxZRerZ8b1OYrP6VSiYiICADA4MGDcejQISxfvlycVxMTE1Nv+969eyM9Pb3J/alUKqhU1lta1h7jo3wwPsrH3MMAcKUrWmc0D9BodXh3UzIA4NFx4WLXjLYyTnZLym4+ci+urMEGQ/ajMxY6vWlQEI5fKsH6E9kmC2w2J+nHO6m3L8K8HHG315X9jo3yFgMbQRAsduFZIiIisgxl1bX44YD+uvuBMZ07r6YuuUyK/kFu2H+hAEfTi+oFNiu3p+C9f5KhEwAnlRzBHg44m1sGrU7AmEhvrLh9IFwd9JVL46N9MHd4KF75IwlbTufijfVJGLFgSOvH0dEfRKfTQa1WIywsDAEBAUhOTq73/NmzZzF9+vSOHoY6iTGwKamqhUarM+mCTX8cz8LFgkp4OCrxUBvm1VzNGNiczSlrdnLZDwczxIU4Y4PathBna4zq5QUASMoqNckkN0EQsCUpDwAwJca3wfPDe3pCKZPiUlEVzl+uQISPU4eOR0RERLbtx0MZKFNrEO7tiHGRXXsTfVCoPrA5nFaEOUP1N5gvFlSIQc2M/gF44bre8HWxQ3WtFvnlagS62Te4cRvk7oBP5g7G5Pd34kJ+BX44eLHVY2jTVezixYuxa9cupKWl4cSJE1i8eDF27NiBO++8ExKJBM8++yw+/PBD/Pzzz0hJScGLL76IM2fO4L777mvLYagLudlfmdtTXGW63uNanYCPDOvV3D+6R4fKwsI8HWGnkKKqVouLBRWNbnMyswQfbNa3kr57RGinZDfCPB2hkuvHkV5Y2eH9ncgsQU5pNRyUMsSFezZ43kEpx7Ce+jllO89e7vDxiIjIMuWXq7F0UzKyS9q+7h+RkUarw+q9aQCA+0f37PIOwkN76K9lNp3KQV5ZNQDgk10XoBOAcVHeWDFnIHwNS5vYKWQIcndo8npNJpVg4QR9hdhXhp+pNdoU2OTl5WHevHmIiorCxIkTcejQIWzatAmTJ08GADzxxBNYvHgxnnzySfTv3x9bt27F5s2bER7e/rv11LnkMincDOk/UzYQ+CsxCxfyK+DmoMC8uLAO7UsmlSDKV5/SPN1IOVpJVS0WfHcENVodJsf4YvaQhg0oTEEmlYip1TOtmO/Tks1JuQCAsZHeTa7JNNbQMpGBDRGR7Xprw2l8tD0Fj353tMmJ10Qt+dswKd/TUYlZ7ViUvKNGR3ihf5ArytUavLsxGXml1fj58CUAwCPjItq8vxv6ByDM0wHFVa3vDtumwObzzz9HWloa1Go18vLysGXLFjGoMVq0aBEyMjJQUVGBffv2YdSoUW05BJmBh0PrOqMlZBTjTE7LF/RanYAPt+o74d0/qke7GgZcrXcTndF0OgHPrj2OjMIqBLnbY+kt/Tt1Lkq0IbA53YrW0y0xBjaTGylDMzIGNgcuFHTp4qBERNQ1iipq8FdiNgDgaHoxfjycYeYRkbX6yfBv567hoWZZxF4qleClGfrut2uPXMLzvySiRqvD4FB3XBPW9nnWcpkUj45vW0BkugkVZLXcW9HyeevpXMz6eC9u+yQeGq2u2f39cTwT5y9XwMVOjnkjwkwyxsYCm3K1Bg9/ewT/JOVCKZNi1Z2DxclnnSXaTz+OjmZsMgorcSanDDKpBBOim66BjfBxQqCbPdQaHeIvFHTomEREZHnWHtHPD1XJ9Zdkb/99xqTLClD3UFWjxYHUQgAw6XIXbTU41F3MFm1P1lebPDIuvN03nW8cGIhAd7tWb8/AhsQGAk0FNudyy/CvNQkQBH3Z16WipmuAq2u1WLpJP9flobHhJluf5+rA5mJBBW76eK8Y1Lx7ayz6dULDgKtF+xtK0TqYsdl1Tv/LPjjUHW6GjFljJBIJxkTqmxbsOcf1bIiIbIlOJ+A7Qwerl2bEIMbfBSVVtXhr/Wkzj4yszYHUAtRodAhwtUO4t6NZx7JoejQclPqMUZSvc4c6AStkUjw4umert2dgQ2IpWmNr2RRV1OD+rw+jXH2lvjG1iQn8APD1/jRkFlfBz8UO9440XZtBY0CRVVKN5VvOYfry3TibWw4fZxXWPDQcMwd0TS2pMWOTXlhZ7z1pq5OZJQCurNTbnKE99A0EDrdxNV8iIrJsu1PycbGgEs52cswaGIg3Z/WFRAL8eiwTMz/ag58OZaCqhmXI5lSr1aFG03yliiXYbbj5OSbS2+zLQ/i62OHf1/aGvUKGRdOjO9zE4KZBQa3eloENwcOp6bVsXv3zFC4WVCLI3R7DDBfYafmNBzbFlTViJ7SnpkTCXmm6+k4XOwUC3fQr536w5Swqa7QYGuaBPx8b1e71cdrDw1EJXxf9ukvJHcjanDAENv0CW84yDQnVv++nsko4z4aIyIZ8G69vY3vzoCA4KOUYGOKOZ6dGQSGT4PilEjz3SyJuXrUPgsCGAuZQq9VhzqfxGPbWFhRXds5C5qay21AJMrqXt5lHonfX8FCcfn0axjdTbt9abQnUGNjQlYzNVb+0giCI3bjevaU/BhoCiKYCm4+2paC0WoNoP2fc3IbourX6B+uDAHcHBd65ORZrHhwutg3sSuI8m1Y0UmhMjUYnBkWtCWyC3O3h46xCrVZA4qWSdh2TiIgsS25pNbae1jeRuWt4qPj4I+MisH/xRCyaHg2ZVIKk7FJkl1Sba5jd2uq9qTh8sQhFlbVIyCg293CalFNSjbO55ZBIgJERDZeP6E4Y2FCTzQOySqpRVFkLuVSCgSFu6OHlAABILWi4hsvelHys3pcGAOIfY1P7z3UxeG1mH2x7ehxmXxPc5f3ZjcR5No20nm6Ns7llqNUKcLVXIMjdvsXtJRIJhhi6iRy+WNiuYxIRkWWJv1AAnQDEBrk2WIDZy0mFh8eGi504Lfmi2lZlFlfhg83nxO9T8srNOJrmGeftxga5NTtvtztgYEPwbCKwOWHIDkT6OsNOIUOYp34yWmp+/V/u1PwKPPLdUWh1Am4aFCi2KDa1QDd7zIsLEwMxc+ndwYyNcX5N30CXVqdXjeV2R9I4z4aIyBYYM/ADg92a3GaA4TkGNp0nu6Sq0cW/X/njFKpqtTB+TJ+/bLmBjXF+zdheXmYeifkxsCExULi6ecCprCsX4ADQw0sf2GQWVYkT6Uqra/HA14dRUlWLAcFueGtWP7NPWutsdTM27al7Ns6v6RvQ+i5uQ8L082yOpBdx8TYiIhtgvHnYL8ityW3EwCa9uPMH1A0l55Rh8vu7MG7pDvxn3QmUVNaioFyN9/9JxuakXMilEjwyTr/IvKVmbHQ6AXuM82s66cayNen4yolk9YwZm4KKGgiCIAYmV09w93ZWwVEpQ0WNFumFlYjwccI7G88gJa8cfi52+HTuYLMsCNXVeno5QSGToEytQWZxFYLcHdr0+pNZ+kxP31bMrzHqE+ACO4UUxZW1uJBfjggf5zYdk4iILIdWJ+Ck4eZh/2aWKjAGNicyS6DR6iCX8X60qRRW1OC+rw6JHU6/O5COvxKzUVmjQa1WfwPxwTE9Mb2vP1ZuP2+xgc2prFIUVdbCSSUX/710Z/wNITFjo9boUGXouiUIglgy1cdwAS6RSBBqKEdLy6+AIAjYkpQHAHhzVl/4mGEivzko5VKEe+vrods6z6ZWqxPX4mlN4wAjhUyK/oa7ekfY9pmIyKql5JWjskYLR6UMPb2dmtwu3NsJzio5qmq1SM7t2PppdEWNRocF3x7BpaIqhHg44NO5gxHh44SSqlrUagX0D3LFO7fE4pkpUehpWBOmqLK22YXMzeWXo5cAACPCPaFg4MvAhgBHpQxKwy+D8Zc2t1SN/PIayKQSxBgWxwSulKOlFVTgQn4FckqroZRJMTKie9V1GhcMbes8m5S8ctRodHBWyRHi0bZMj3HNm8OcZ0NEZNUSLxUD0N84bK7ZjlQqQayhIyjn2ZjOsi1ncSC1EE4qOT6bPwRT+vhhw+Ojsfrua/DXY6Pw+8JRmD1E36TIQSkXl5uwtKxNQbkaaw7pF3idPyLMvIOxEAxsCBKJBB5XNRAwlqH18nGqV15mDGxS8yuw73wBAGBQqFu3KEGry9jBJjW/YYe45pwQs2Aube7qZuyMxowNEZF1MzYOaK4MzYjzbExLEAT8fESf5XhzVl9E+upLu5VyKcZH+zRaJm78zLe0wOarfWmortUhNsgVI8K7d5tnIwY2BKBhy2exDO2qCe5hdTI2+1L0XThGhnevbA0AhHrqsy1pjXRSac7JdjQOMDJ2RruQX4Hc0pbXNMgqrmrVdkRE1LWMGZvYZhoHGA0I1v/tZ8bGNE5mliKvTA0HpQzT+vq16jXG8nNLCmzK1Rp8aVhmY8HYcJtv3NRaDGwIQMOWzyfFxgEu9bYzrmVzPq8C+y/oMzYjuuFiUGF15hq1hfi+tuIu3dXcHJTi3b0n1iSgVqtrclu1Rotpy3bhug/3iB3siIjI/Go0Opw2zM+MbUPGJuVyOcqqaztzaN3CFsOiqKN7eUElb121iTFjY0ktn384kI7Sag16ejtiap/WBWjdAQMbAtAwYyO2JL4qJWu8oM8prUZxZS0clbJW3XGyNcbMVUFFDUpb8UEjCAI2J+XilKEj2tWZsNZ655b+cFTKsP9CAV77M6nJ7cqrNSit1iC/XC123iEiIvNLzilDjVYHNwdFq+ZaejurEOhmD0G4UsJG7bftjL7p0cTevq1+jaWVolXXavHZngsAgIfHhJttwXJLxMCGAAAeDgoAQFFlDfJKq5FXpoZEAsQE1M/YeDgq4Wx3pUv4sJ7dswuHk0oOLycVAOBiC/NsDqUVYubKvXjg68NQa3SI8nVGT0Ng1FZRfs5YdvtASCTAN/EX8d2Bi41up6mz1s3htMJ2HYuIiEzvuKEMrV+ga6vLhwaEuAFgOVpH5ZZW40RmCSQSYHyUT6tfZwxsMourUFmj6azhtdpX+9KQW6pGgKsdbhwYaO7hWJTud0VKjfJw1F+kF1bUiHf4w72d4KCsv9SRRCIRGwgA6NaT1YxlealNzLMRBAFf7k3F7Z/GI/FSCRyUMjw8Nhw/PDi8Q3dXJsf44pkpUQCAZVvONbpN3cDmELuoERFZDOPCnK0pQzMaaFzPhhmbNqmu1WLGij2Y82k8ytUaMVvTP8gN3s6qVu/Hw1EJd8MN4AuX21aCbmpFFTX4aHsKAOCpKVFQynkpXxffDQIAeDjqf2EzCquwYpv+Fya2iXVWjOVoADCiGzYOMDKu6XOxkXk2NRodFv1yAq/8mQStTsAN/QOw67nxWDQ9WuxA1xF3DQsFAFwuU6PasPZQXZo6828OpxVCEIQG2xARkWnllVXjvi8PYd4XB5FdUtXgeUEQcCxDf7OpLWXc4YaMQVsb1nR3m5NycSKzBPsvFGDBt0ew8WQOAGBS79Zna4yammdzuUyNg6ldVxnx0fYUlFVrEO3njFnM1jTAwIYAXMnY7EnJx7H0YrjaK/DwuPBGtzVmbDwclYj2c+6yMVoasfV1Ix80/9t9AT8ezoBUAvz72mgsv32AWLpmCi72ctgbWmznlDTsfFY3Y1NUWWtREx6JiGzR8Yxi3LBiL7aeycOus5cxY8VeHLlY/4J3w4kcnM0th1ImFdcma40enlc6kup0vFHVWr8nZIn/v/tcPnaevQwAmBDd+vk1Ro3Nszl/uRzXfrgbsz/Z3yVlgukFlfh6fxoA4N/X9m52DaTuioENAQDcDRkbAHCxk+Pb+4aJvd2vNqynBwDg2n5+3XrCWlOd0TRaHb6N1899ef3GvnhwjOnbMEokEvi72gEAshsLbLT1P/hYjkZE1Hm2ns7FrZ/sR05pNcK9HRHt54z8cjVu/zQePxzUL6BYVl2LV/88BQBYMC68TTe7gtztIZdKUF2rQw7b+LdKcWUNdp7Vl569cF1vyA3XKwGudujt3/absle3fE7Nr8CcT+NxuUwNADiWbrrP2ZLKWlz34W68/PvJeo8v23IWtVoBo3t5YUykt8mOZ0vkLW9C3UGYpyOkEsBRJcc39w1rth3xiHAv7HhmHPzd7LpwhJbHuJbNxYL6zQO2nslDdkk1PByVuHlQUKcd38/VDhfyK5BT2rDc4epW0IfSCjFnaEinjYWIqDt7++8zqNHoMDHaB8tuHwCpRIJn1h7H3ydzsPjXE0gydMTMK1MjzNMBC5qoiGiKXCZFsIcDUvMrkJZfgQA3+874MWzK3ydzUKsVEO3njPtH94SnkxLP/3ICdwwLadfNRmM54N8nczD23e0or9agoKIGUgmgE4CzuWUmG/s/STk4lVWK5JwyLL62N+wUMuh0gtiq+l8Te5nsWLaGGRsCAAS42WPdIyPxz5Nj0N8wSbE5YV6Ore7/bquaavlszNbcOiQIdorOe4/8msnYaK8qVTjMjA0RUac4f7kc5/LKIZdK8P5tA+Bsp4CjSo6P7xyEpydHAtB3sfymTia/PZ8NYZ7NN6yh+n47lgkAYtewWQODcOrVqVg4oX1BwdAwD3EtuYsFlSioqEEvHye8dH0MAOBsrulKvo0lcxqdgOOGEreUy+UordbAXiFr1XVad8WMDYn4i9I2xpbP+eVqpOVXIDbIDWn5Fdh9Lh8SCXDn0NBOPX6Aq/6OXeNzbPQZG09HJYoqa5BeWInc0mr4unTvLBsRkaltOqWfkD4iwguu9lfKuiUSCR6b2AvR/i548scElKs1uKF/AEb3al8JUQ8vJ2xPvtzmhaG7o6ziKhw0LHUwo3+A+HhHlqdwVMnx+8JRKK6swcnMUqQVVOC6fv7IM5Sinc0pgyAIHS491+oE7D6XL35/+GIRhvX0FG9QDgh265bLbLQW3xmiDjC2fE4zlKMZ15UZG+mNEM+WF17riOYyNsY5Nm4OCkT76dciOsT1bIiITG6TodPWtCZWf58c44s/HxuFl66PwVs39Wv3ccQlBlpYO42AvxKzIAj6LEugicv23ByUGNXLC3cND4W7oxI9vBwhl0pQptY0+nncVgkZxSipulIFcuSiPqA5bGhE0ZamE90RAxuiDqjbQKCqRou1Ry4BuNKOuTMZmwc01xVNLpViaA99s4dDXdiOkoioO8gqrsLxS/oFHyfHNN1pq4eXI+4d1QNOqvYXyhjLn9nyuWXGbmg3DAhoYcuOU8qlYpdUU8yzMZahGUsPj6YXQacTcNQQ4AwOY2DTHAY2RB0gftDkV+Cj7edQXFmLIHd7jI9ue4/8trqSsWnYPEAMbGQSMbDZe76g08dERNSd/GMoQxsS6t6mBR/bw3gjLb2gssE8yo7S6QS8v/ksPtx6DhVqjUn33dVS8spwKqsUcqkE1/Xz75JjRhqWvjBlYPPgmHDYKaQorqzFwbRCpBVUQiIBBoUwsGkOAxuiDjB+0BxILcSnuy4AAF64LqZLesv7G+bY5JfXQK2pv0incYFOuVSCkRFekEklSMkrR0YhSxiIiExl0yl9l6qpTZShmVKAmz2UMilqtDpkFTe8odURPxxKx4dbz+H9zWcx+f2d2Hgy22oXdjZma8ZGesPdBAtit0akjzGw6VgDgcKKGiReKgYATOztIy7iary+iPRxrjePixpiYEPUAcaWz5nFVajVCpgY7YOpfdq+8Fd7uDsooJTrf4XzStX1nruSsZHC1V4h1uTuSM7rkrEREdmq3NJqxF8owI7kPBxI1WfCuyKwkUkl4mdOqgkbCFwuU+O/f58BADjbyZFVUo2Hvz2KTwwX09ZEEIQuLUMzivLTt4JuLmOj0wm49f/24drluxvcjDTafe4yBAGI9nOGr4sdhhg+u7ed0X92D+L8mhYxsCHqAGMpGgDYKaR45YY+Jl+MsynNLdJpbB5gzByNj9KXxhn/OBIRUdutT8zG6P9ux+2fxuPu1YegE4AYfxcEe3Rusxijzphn89aG0yit1qBvoAviF0/EPSPDAADf7L9odVmbhIxipBdWwkEpa3bOk6kZFzQ/l1sOXRNlggmXinEorQhJ2aViQ4Cr7UzWl6GNjdJ3zhty1XyaIQxsWsTAhqgDnFRy+BlaKP9rYmSXfbgZGY999TwbY7tnhcwQ2ETr/0juO1+A6trG7xQREVHTvtmfhoU/HEWNVodAN3tE+Diht78LnjSsVdMVjJPUTZWx2ZeSj3XHMiGRAG/e2A+OKjmemxoNO4UUmcVVSMouNclxuooxWzMlxhcOyq5b0STU0xFKuRRVtVpcKmq8THBzUq74/3tT8hvdZv8FfQZwbKT+M/vq+TRXBzrUEAMbog5aclM/PDU5EveP7tHlx26qM9qVjI3+VzzK1xkBrnZQa3TiH04iImqdL/em4sXfT0EQgHlxodj13HhseWos/v7X6C7NDNTtxNlRFWoNFq87AQCYOzxUXMvOXikT19qpezFu6TRaHf5K1Ac2MwcEdumxZVIJIrz15WjJTZSj1X0v95xrGNhU1WjF6osYf/0yDW4OSvTy0e/Xy0mFkC6+eWqNGNgQddD4aB88PrGXWRbM8jf0529QimbM2BhK0SQSCcYZOrVtt6FytNLqWqsrlSAi67N6XxoA4NHx4Xj1hj5d0iCmMWFXrZ3WEa/9mYSLBZUIdLPHM1Oj6j1nDNasKbDZfS4f+eU18HDUrzPT1SJ9m55nk5pfgZS8cvHfTWJmCUoqa+ttk1GkP6cudnK4OVxpemDM0gwJde+yUndrxsCGyIo1mbHR1Z9jA9SfZ2MLwUDipWIMfG0zbvskHpfL1A2eFwQBCRnF2JuSj5S8MpQ30sI0Ja8MuaUdX1CNiGyXTicgu1j/d2LO0BCzXlwaS9HSCytRa+h+2R4bT+bgx8MZkEiA92b3h4td/U5bE6N9IJUAp7JKkWniDmyd4WxuGZ5ZexwAMCPW3yw3Gptr+bw5Sd8WPK6nJyJ8nCAIwP4L9bM26YZg9erFve8b1QMjwj3x0NienTFsm8PAhsiKiXNsShsvRav7x31khCeUMikuFVXh/GXrX+DtUFoRtDoBB9MKccNHe8QWmQBQUlmLx344hhtX7sWdnx3ApPd3YdDrm/HbsUxxm6PpRZi6bDdu/zTeJgI9IuocBRU1qNHqIJEAvoa/uebi62wHe4UMWp3Q5FyOluSWVmPRr4kAgIfGhGN4T88G23g6qcRumlssPGtzLrcMd/wvHgUVNegX6IqnpkS1/KJOEGVoIJCc01hgo38PJ8f4YlSEPpu0+6pytHTDcgxXl5tF+Djj+weGYyDXr2kVBjZEVsy4lk1Og+YBVxboNHJQysXFOm1hnk3ddRyyS6pxy6r9mP3Jfrz65ylMX74LfyVmQyaVINzbEc4qOWo0Ovxn3QlkFldBo9XhP+tOQqsTkJpfgXN5HVt7gIhsl/Fvja+znVkyAXVJ67R8bu88m3c3JaO4shZ9A13wVDOND6yhHK24sgZ3fHYA+eU16BPggm/uG2q2dV6iDBmblLxy5JVdudlYUK4Wu6BNqhPYXN1AwBjYdHUTIlvDwIbIivkZStHyytT1yhKMC3ReXQfey1ADfKnI+hfqNF5sPD05EhOjfVCj1eFgaiFW701DVkk1wjwd8PPDcdj69Dgcf3kKhoS6o6JGi0W/JOLLfWk4Xafbz9V3zoiIjIxdJ/3dzJutMYo2XEAfyyhu82vTCyqxzpC5fuPGfuJaaI2ZHKNfmyf+QgFKqmqb3M6cNp7MweUyNUI9HfDtfcPqzU3pakHuDhgY4gaNTsA3+y+Kj289kwedAPQJcEGgmz2G9fSATCpBWkFlvUWzm8rYUNswsCGyYp6OSihkEggC6s0zMWZsFNL6v+KBhmYDWcXWP68kyzCvKMrPGZ/NH4J/nhyDpbf2x/y4UDwxqRfWPz5aTN1LpRK8c0ssVHIpdp/Lx1sbTgMA+gW6Ami69SYRkfHvZYAhQ25uceH60rF97fi7tXJ7CrQ6AWMjvTHA0AWtKT28HBHh4wSNThC7jVkaYzbplkFBcHc0X1Bj9MBo/TyYb+MvoqpGC41Wh+8PpAO4kgFztlOI733dzx4GNqbBwIbIikmlErHmu25nNLHds6x+xiZADGwsfzJoS4w/Q4CbPSQSCSJ9nXHL4CC8OrMvnpgUCUdV/TUMeno7iWUXOgEYHOqOJTf1A6C/I9mRibhEZLuu/K2xjIzNiHB9KVNCRjEqGmmK0pSMwkr8cvQSAODxib1a9Zo7hoYAAJZvOYfKmtYfqytU1miwxxAYTO7TdS23mzO1jx+CPexRVFmLn49ewqod55GQUQxnlRyzhwSL24nzbAzj1+kEMXsT6uHYcMfUagxsiKxcY53RtFe1ezaylcBGrdGKGSrjz9Qa94/uiWE9POCkkuPNWX0R4+8CT0clKmu0OJZe3EmjJSJrZrxp5G8hGZtgDwcEe9hDY2ie0lof7zgPjU7A6F5eYmOAltw5PATBHvbIK1Pjs92p7R1yp9h1Nh9qjQ7BHvbixH1zk0kluHekfk27FVvPYdnWcwCA127sU++zaoQh63YwtRCCIOByuRpqjQ4yqcRiSh6tFQMbIitn/LDNrtNAoFZXf4FOI+Mdx9zSaqvOUBiDODuFFO4OrZ8oKpNK8O39w3Dg3xMR7ecCqVSCEYY7Z3tYjkZEjciskx22FCN66v9u7T/fukYwSVml+PlIBoDWZ2sAQCWX4dmp0QCAT3aeb7S1vrmIncZ6+1nU+i6zhwTDxU6OvDI1tDoBM/oH4MarFgztH+wGhUyCy2VqXCqqEsvQAtzM36DC2vHdI7JyxoxNdr2MjbHdc/0/9l6OKihlUugEWPX6LWLNu6EMrS0UMmm9MrVREfo7Z5xnQ0SNMd40spRSNAAY0Ya/WxmFlbh79UHUagWMi/LGNWEebTrW9f380T/IFRU1WizferZd4zU1jVaHbWeutFC2JI4qOe4YFgoACHC1wxsz+zb4nLJTyNAnQD/H8/DFQlws4PwaU2FgQ2TljBMmi+usYlzbRFc0qVQifjhntnMNBEtgLKULNMEd1JERV+rVS6sts/MPEZlHrVaHPEOWwlJK0YArDQSSsktRVFHT5HaFFTWYv/og8srUiPJ1xvLbB7b5WFKpBIum9wYA/HAwwyI6pB25WISiylq4OShwTZjlre/y2IQIPD6xF768dyhcm6gqGGIoBzycVsTGASbEwIbIyhnT1hpd3XbPxnVsGv6Ki/NsSqw/sDFmqzoiyN0BPbwcodUJOHCh9fXqRGT7ckqqIQiAUi6FpwV03TLycbZDpK9+Bfv4RtYl0xk6md2yah8uXK5AgKsdvrq3/Wu8xIV7IsjdHlqdgFNZJR0dfocZy9AmRPk0+jlnbo4qOZ6aHInIZub+GOc5HblYJDYO4Bo2Hdemfw2rVq1CbGwsXFxc4OLigri4OPz9998NthMEAdOnT4dEIsFvv/1mqrESUSOM5WbGYAaos0CntGGZVkAjLZ+1OgE6ndBgW0uVVWLamveRLEcjokZcaRxgB2kjf0/Nydgdbd9V82xS8sowffluLPz+GC7kV8DLSYmv7xsqrnvWXsb2+CczzR/YbEvOA2B5ZWhtMdiQaUrOLRODRXZE67g2BTZBQUF4++23ceTIERw+fBgTJkzAzJkzcerUqXrbLVu2zKImchHZMmPGpqaRBTrlsqYDG+OE2EtFlej/6j94/pfEzh6qydSdY2MKxprz9ix4R0S2S2z1bEFlaEbGzlp7z9e/IfPqn0lIzi2Ds50cT0zqha1Pj0OET8e7hvUVA5vSFrbsXFqdgHTDnJQBIW5mHUtH+DjbIcTDAYIAnM0tB8BSNFNoU2AzY8YMXHvttejVqxciIyPx5ptvwsnJCfHx8eI2CQkJeO+99/DFF1+YfLBE1JAxK1O3y5m2iQU6ASDQMMfG+IG9/UweytUarDuWaRG1061hyjk2ANA/yA0AcDq7FDUa6+0WR0SmZcwOW2IL3mE9PSGTSnDhcgXO5ZYBAPLKqsXM8++PjsQTkyLbXX52tb4WkrEpKFdDoxMgk0rg42x556UthlzVdpuBTce1uzBRq9VizZo1qKioQFxcHACgsrISd9xxB1auXAk/P79W7UetVqO0tLTeFxG1nlJumGNTpxTtSrvn5krR9B/YxiyFRidghyG9DwD/nMrBe/8ko7pW2ynjbi9BEEw6xwYAQj0d4GqvQI1Gh7OGCwQiomxjdtgCMzau9gpMjPYBAHxnWN1+fWI2dAIwMMQNPb2dTHq8vgEuAIAL+RUoM2OjlSxDeaCPs6rRzzhrMrhO4wMXO3mTjQao9doc2Jw4cQJOTk5QqVR4+OGHsW7dOsTExAAAnnzySYwYMQIzZ85s9f6WLFkCV1dX8Ss4OLjlFxGRSC5tWIomLtDZXClaURUEQUBCnfKrfwwTMkura/HEjwlYsS0FT/2UIGaALEFplQYVNfpgy1SlaBKJBLFB+ruRiZfMXz9ORJYhywLXsKnrruH6tsK/HLmEyhoNfkvIAgDM7B9g8mN5OqkQYLiZlJRlvpvQOSWmvbFlTnUXSg3xZLbGFNoc2ERFRSEhIQEHDhzAggULMH/+fCQlJeGPP/7Atm3bsGzZsjbtb/HixSgpKRG/MjIy2jokom7tSvOAK4FNrbbxBTqBK3ceK2q0uFRUhQuXK8TndiZfhlqjxdrDl1BpCB42nMjBa3+egiC0P7ipUGtQUmmaO3zG0hBPRyXsFDKT7BO4MjE28VKxyfZJRNbNmB2wxFI0ABgV4YVQTweUqTVYvvUcjmcUQyoBros1fWADXClHO2HGcrQrDR0sM9hsi0gfZzjb6ddVY+MA02hzYKNUKhEREYHBgwdjyZIl6N+/P5YvX45t27bh/PnzcHNzg1wuh1yuP1E333wzxo0b1+T+VCqV2GXN+EVErWdsHlBbpxTNmGFprHmAvVIGD0Pb0r9PZgMAgj3s4eOsQrlag33nC/DVvjQAwNQ+vpBIgK/2X8Qnuy60a3wllbWYvnw3xi7dbpJVq8UyNBNfaMQa5tkcZ8aGiAyMi3Oaaj6fqUmlEtxlWAzyk536v9EjI7zg7azqlOMZA5tTZs3Y6AObjnZ5swRSqQSDQvRZmyAPy/w3Zm063Pxbp9NBrVZj0aJFSExMREJCgvgFAB988AFWr17d0cMQUROuBDZ1MzaGrmhN1B8bF+lcn6gPbAaFuGNib33bzDf+SkJ6YSVc7OT44LYBePE6fanp+/+cRX552wITQRDw799OIL2wEsWVtfjhYHqbXt+YzupS1D9Y/4F9NrfM4uYVEVHXq6zRiAsfW3LZ0y2Dg8S5lgBw44DATjtWP4vK2FjuOWmLh8b2xMAQN9w6mFMxTKFNgc3ixYuxa9cupKWl4cSJE1i8eDF27NiBO++8E35+fujbt2+9LwAICQlBjx49OmXwRHSlFK2xrmhNLVxmDAqM2YkBwW6YYlgP4LyhNO32oSFwUMpx76ge6B/shhqtDj8caFtgsu5Yphg8AcC38Rc73HUs08Stno38XOzg5aQyLEDHJiZE3Z2xrbyzSg5nO8ud1O3uqMQMQ+mZSi7FlD6dt7aLMWNz/nI5KtSaTjtOc2wpYwPo1yNa98hIRPiYttlDd9WmwCYvLw/z5s1DVFQUJk6ciEOHDmHTpk2YPHlyZ42PiFpgDF40dSb4GzukNZ2xqR8UDAh2Q1y4JxyU+jkrUgkw1zApFQDuGREGAPgm/mK9AKo5GYWVeOl3/RpXj0/sBW9nFfLK1GL5W2vVanV4c30SZn60B2dySjutNEQikaB/EOfZEJGepTcOqOvBMT3hpJLjzmGhnRqEeTur4OuigiDo2+ObQ3ap7TQPINOTt2Xjzz//vE0778hkYyJqHaWxFK1OJqRW13wpWt2gQCmTIibABSq5DGMjvfH3yRxM6u2L4Dr99K/t5483N5w2BCY5uKGZjjs6nYAfDqXjnY3JKFdrMCTUHf+a2AsyiQQfbDmLL/elYWYrSyUKytVY8N1RHEwtBADM/+IgHFX6P1udMZk3NsgNW8/k4QTn2RB1e9kWvIbN1aL8nHHilSldsjh6v0BX5Jbm4URmCYYYFjfuKjqdgNwSfUm0nw00DyDTa1NgQ0SWx9ggoFbXuuYBQP07kL0NQQ0APDM1Cg5KOf41sVe97ZVyKe4cFoJlW87hy72pTQY2hRU1uPfLQ2IL6d7+Llg+ZyBkUgnuGBaCj7afw7H0YvyekIlLRVU4lVWC2CA3TOrti3BvR/FDWRAEbDmdh1f+OIXM4io4qeTwclIiraASgLrBz2AqsYZ5NseZsSHq9rI6qey1s3RFUAPoy9G2nM7Dycz6GZt1xy4h8VIJHhjds9Pes8LKGtRodZBI9OvYEF2NgQ2RlWu8eYCxFK2JOTZ17kAODHYT/z/c2wnvze7f6GvuGBaCldtTcDS9GImXisUuYnV9vD0FCRnFcFLJ8fSUSMwdHiqWynk7qzAjNgC/HsvEv9YkiK/ZcCIHb/99BkHu9hgQ7IZoP2f8k5QrrifTw8sR/5s3GI4qOW76eJ84cbQzuhTFGurHjQvQWXJdPRF1riuNSiw/Y9OVjGt+xV8ogCAIkEgkKFdr8PzPJ1Cj1eHHQxn418ReuHdUD/HzyVSM82u8nVQm3zfZBv6rILJyYvMATcMFOpvK2AS6XwkKBtQJbJrj42yH6w0TVL/Zf7HB86XVtVhzSL8O1YdzBuCekT0aNC+4f3RPKOVSKOVSTIj2wdOTIzE20htKmRSXiqrwV2I2lv5zFomXSuCglGHBuHD89uhIRPg4w9/VHl/fOxQejkqEejrA28n0d+s8nVQIdLOHIIDlaETdnC2tl2JKw3t6QiWXIrO4CmdyygDo10AzZlIqa7RY8vcZzP5kP0qrTbN+mZHY7p/BJjWBGRsiKydmbBptHtD4vQsvRxWcVHKUqzViD/3WuGNYCNYdy8SGE9l4bWZf2CuvLJD506EMlKs1CPd2xLhIn0ZfHxPggvjFE2GnkMJBeeXPT7lag4T0YiRmFiMpqxShng64d2QPeF4VvPTydcau58ZDLpVA2sT8oY66JswdmQlV2Hn2MkZEeHXKMYjI8llT84Cu5KCUY3QvL2w5nYfNSbno7e+CzUk5AID7RvZAtL8LXv8rCcfSizH/i4P4+t6hJst+55Qy2KTmMWNDZOXkjbR71rQwx0YqlWDlnYOw/PYBCPF0aHSbxgwJdUewhz0qarT4x/BBBgAarQ6r96YB0Gdlmgs6PByV9YIaAHBSyTGqlxceGReBj+4YhGenRjcIaupua6eQNfqcKUwytL3enJTbaccgIssmCAKySoyBDbMDV5tc5+9krVaHbWfyAABT+vjhlsFB+P6BYXC1V+BYejHuXn0I5SZqDZ1tY62eyfQY2BBZOWNXNEG40jRA08ICnQAwNtK71d3JjCQSCWYNDAIA/Ho0U3x8w8kcZBZXwdNRiVkDO29xuK4wNtIbCpkEF/IrkJJXbu7hEJEZFFfWorpW/3eUF9ENTeztC4lEv1DnHwlZKK3WwMNRicGh+gqAPgGu+O7+YXCxk+PIxSLcu/qQSda9ybGxxTnJ9BjYEFm5uvNYjFkbMWPTRClaR9xkCFx2n7uMvNJqaLQ6/G/XBQDA3LjQTs2mdAVnOwXiwvUlaMzaEHVPmYYyNC8nldg1kq7wclJhsKGM+a0NpwEAE6N9IKtzM61voCu+vX8YnO3kOJhWiHu/PITKmo4FN8YW3Aw2qSkMbIisnKJOuVmDwKaJUrSOCPNyxKAQN+gEYN2xTDy99jhOZJbATiGtt6inNTOWWdQttyOi7sNY8sQytKYZ/04WVNTU+76u2CA3/RwblRwHUgtx/1eHxYqC9shhQwdqAQMbIiunkNbN2LS+FK0jbhqkL0d7Z1Myfk/IglwqwfLbBzY5L8baTO6t/4BOyChGXlm1mUdDRF3NmBkI4AV0k+oGMnYKKUb38m50u4Eh7vjy3qFwVMqw73wBdqfkt+t4giDU6VTHgJMax8CGyMpJpRIx/a/pglI0ALg+1h9KmRRanQCZVIIVcwZiah+/TjmWOfi52iE2yBWCAGw9nWfu4RBRFzOWovkzY9Oknt5OCPd2BACMivCu1yXzaoND3TE+Wt8t86yhRXRbFVfWQm1Y1sDHxTZuopHpMbAhsgHGcrQaY2Cj7bxSNABwc1Di5sFBUMml+PD2gZjez79TjmNOxqzNz0cuYX1iNjaezEZJpWnXZCAiy5RdbChFY8amWfNHhEEiAe4aHtLitr18nAEA59rZlMWYrfFyUnLeEzWJ69gQ2QCFVIpq6K6Uouk6txQNAN6a1Rcvz4ix+mYBTZncxxfvbT6LIxeLcORiEQD9Yqa/LBhRb4IsEdkermHTOnOHh2LO0BBxPbXmRPg4AUC7u03mlLJxALWMgQ2RDVDIpYBaX4qm0wkwrtUpb8WHTXtJJBKbDWoAIMrXGY+OD8fhNH1QczKzBAkZxfhiTyoeGNPTzKMjos4kzuVgKVqzJBJJvQY2zenlqw9szueVQxAESCQtv06t0eLdjcnwclahxlCGxsYB1BwGNkQ2wJiZqdHqxPk1AJhZ6ACJRIJnp0aL3/90KAPP/ZKIpf8kY2JvH/T0djLj6Iios2h1grjCfSAzNiYT5ukImVSCMrUGuaXqVmVe/jyejc/2pNZ7jI0DqDmcY0NkA4xlABqtIJah6R9nYGMqtw4JwuheXlBrdHj+l0To6gSQRGQ78sqqodUJkEsl8LKRTo+WQCmXItTTAcCVcrTES8Xo98omfHFV8GJkLAN2sbtyHz6cN5WoGQxsiGyAMYCpvSpj01ld0bojiUSCJTf1g6NShkNpRVh/ItvcQyKiTpBlaBzg62LHrLeJRRiCknN5+s5oPx7KQFm1Bp/vSYUgNLxZdCxdH9i8e2t//PXYKLx7SyxuHxrcdQMmq8OrHiIbYMzY1GoFsSMa0LnNA7qjIHcH3D5U3/3nYGqhmUdDRJ3B2DiAZWimd3UDgb2GNW0yi6twOrt+G+jS6lok5+ofGxTijr6Brrh1SDA7olGzGNgQ2QC5GNjoxFI0qUS/xg2ZVmyQKwDgZFaJmUdCRJ3BuDgnGweYnrGBwLm8cmQUViKtoFJ8bnNSbr1tj2cUQxCAEA8HeDuzJJBah4ENkQ1QGkrRNDrdlTVsWIbWKfoF6gOb09ml4oKoRGQ7jKVobPVsehHe+rVszueVY995fbbGWO63+XROvW2N82sGhbh13QDJ6vHKh8gGGEvRajRCpy/O2d2FeTrCSSVHda0OKZfbtx4DEVkucQ0bdt8yuXAfRwBAQUUN/jyun6d4x9AQSCXAycxS8b0HgKPpxQCAQaHuXT5Osl4MbIhsgLxuxsZQisZJr51DKpUgJsAFgP6DmIhsi7iGDddLMTkHpVycu7THML/mhgEBGGwIXrac1pej6XSC2DhgUAgDG2o9BjZENkBRb46NUO8xMr2+AYZ5NpmcZ0Nka4xzbFiK1jmM82wAwFEpw4BgN0yO8QVwZZ5NyuVylFVr4KCUIdrP2SzjJOvEKx8iGyAGNnVK0Zix6Tz9gvQZmxMMbIhsQl5ZNQ6nFaKgXI388hoAQACbB3SKiDrr0Azr6QmFTIrJMX4AgPgLBSitrhXn1/QPchOb4xC1hrzlTYjI0onr2NQpRVMwsOk0xgYCSVml0OoEBpFEVkyt0WLWyn3IrDO/w0Epg6u9woyjsl11MzajIrwAAD28HBHh44SUvHLcu/oQ7BT6ls6DQt3MMUSyYgyDiWyA2O5Zc6UUTcbmAZ2mh5cTHJQyVNVqcYENBIis2q9HM5FZXIW69yf6BrhCIuHf0M5gXMsGAEb18hL///lp0XBQynD4YpE4/2YwGwdQGzFjQ2QDlIbARqO7UoqmYLvnTiOTShDj74LDF4twMqsEvXxZA05kjbQ6AZ/sPA8A+Pe1vXHjwECczS1DFH+nO01vfxcEuNrBx8UOveoEOZNjfLHlqbF4/a8k/H0yB0qZFAODGdhQ2zCwIbIBcsOtxpo6C3Sy3XPn6hvoisMXi3DiUilmDTT3aIioPf4+mY20gkq4OSgwZ2gIHFVyeDlxMcjO5KCUY+dz4yEIaJAVC3Czx6q7BuNQWiEAwN1RaY4hkhVjYENkAxRyQ8ZGW7d5ADM2nalvIDujEVkzQRCwaoc+WzM/LgyOKl4SdZWWunZeE+bRRSMhW8MrHyIbYGwUUKvVQSu2e2bGpjP1DdR3RjuVVQKd4T0nIsuRkleOldtTEH+hABqtrsHz609k41RWKewVMtw9IqzrB0hEJsfbE0Q24Mo6NgJqtVygsytEeOsbCFTUaLHz3GWMj/Ix95CIqI5//3oCBw0lTa72CoyM8ERskBtCPRyw5lAGdp69DACYMzSEJU9ENoKBDZENMJai1Vugk6VonUouk+LOYSH43+5UvL3hDMb08mYwSWQhSqtrccSwcr2bgwLFlbXYcCIHG07kiNvIpBLcOjgIz0yNNNcwicjEGNgQ2YC6pWhiu2deZHe6R8dH4MdDGUjOLcMvRy9h9pBgcw+JiAAcuFAIrU5ADy9HbHlqLI6mF+HIxSKcuFSCc3ll6B/khoUTIhDq6WjuoRKRCTGwIbIBdUvRjLXk7IrW+dwclHhsQi+8ueE03vsnGTNiA2CvlJl7WETd3l7DOigjIzwhk0pwTZgHJ6QTdQOsVSGyAeICnXUyNnJmbLrE3LhQBLrZI7dUjc/3XDD3cIgIwO5z+vkzxpXtiah7YGBDZAOMHdA0Wp3Y7lneQjtNMg07hQzPTYsCAKzacR55pdVmHhFR95ZdUoXzlysglQBxPRnYEHUnvPIhsgF1S9G0xgU6mbHpMjNiAzAg2A0VNVr8d2OyuYdD1K3tTSkAAPQLcoOrg8LMoyGirsTAhsgGKOqUotUyY9PlpFIJXp4RAwD45eglHDN0YxIEATWahutnEFHn2SOWoXmaeSRE1NV45UNkA4yNAuot0MmMTZcaGOKOmwcFAQBe+eMUPtp2DqP+ux2DXt+Mv09km3l0RN2DIAjYY8jYjIrwNvNoiKirMbAhsgFKQ3ZGoxNQq+MCneby/LQoOCplOH6pBEv/OYvM4iqUqzVY8N1RvP9PMnSGoJOIOsfZ3HLkl6thp5BiUKibuYdDRF2MgQ2RDTBmbGo0OmhZimY2Pi52WHRtbwDAkFB3fHBbf9w7sgcA4MNtKXh8zTEGN0SdaHOSfgHOoT08oZKz9TpRd8N1bIhsgKJexobtns1p7vBQ3DYkGEq5/pzMGgj0CXDB4l9P4K/EbPQNdMXDY8PNPEoi26PVCfjhYAYA4Ib+AWYeDRGZA2/pEtkARZ05Nlyg0/yMQY3RzYOD8MoNfQAA725KxoELBeYYFpFN25Gch8ziKrg5KHB9rL+5h0NEZsDAhsgGGDM2NZorzQOYsbEsc4YGY9bAQGh1Ah774Rgul6nNPSQiq2e8kQMA38ZfBADcOjgIdgqWoRF1RwxsiGxAvVI0zrGxSBKJBG/c2BcRPk7IK1PjxpV7cSit0NzDIrJa/1l3AoNe34z1idnIKKzEjrP6Ns93DAs188iIyFzadOWzatUqxMbGwsXFBS4uLoiLi8Pff/8NACgsLMRjjz2GqKgo2NvbIyQkBI8//jhKSko6ZeBEdIWiXrtnLtBpqRxVcnwydzCCPeyRWVyF2z7Zj/f+SYYgsKEAUVvtSL6M0moNHv3+KO7/6jAEARjdyws9vBzNPTQiMpM2BTZBQUF4++23ceTIERw+fBgTJkzAzJkzcerUKWRlZSErKwtLly7FyZMn8eWXX2Ljxo247777OmvsRGQgZmy0dZsHMGNjicK9nbDh8dG4eVAQdAKwYlsKNp7MMfewiKxOcWWN+P/JuWUAgLuGM1tD1J216cpnxowZuPbaa9GrVy9ERkbizTffhJOTE+Lj49G3b1/88ssvmDFjBsLDwzFhwgS8+eab+PPPP6HRaDpr/ESEK0FMjbZuu2dmbCyVs50C783uj7tHhAEANjCwIWqT6lotKmq0AIBXb+gDlVyKaD9nTIz2MfPIiMic2t3uWavVYu3ataioqEBcXFyj25SUlMDFxQVyedOHUavVUKuvTKItLS1t75CIui2lXB/EaLQ6cYFOlqJZvhn9A/DlvjTsOJOHGo2uQTc1ImpccWUtAP1CxPPiQnHrkCAAnFtI1N21+S/AiRMn4OTkBJVKhYcffhjr1q1DTExMg+3y8/Px+uuv48EHH2x2f0uWLIGrq6v4FRwc3NYhEXV7xoxNrVa40hWNH/AWb2CwG7ycVChTa3AglS2giVqrsEJfhubuoIBEIoGDUg4HJZfmI+ru2nzlExUVhYSEBBw4cAALFizA/PnzkZSUVG+b0tJSXHfddYiJicErr7zS7P4WL16MkpIS8SsjI6OtQyLq9hRyY2Cjg0bLds/WQiqVYFJvfenM5qRcM4+GyHoY59e4OyjNPBIisiRtDmyUSiUiIiIwePBgLFmyBP3798fy5cvF58vKyjBt2jQ4Oztj3bp1UCgUze5PpVKJXdaMX0TUNgppnQU6dVyg05pMjvEFAGxJymV3NKJWKjQGNo4MbIjoig7Xquh0OnGOTGlpKaZMmQKlUok//vgDdnZ2HR4gEbXM2BVNJ+gX6QSYsbEWIyO8YK+QIaukGqeyOMeQqDWK6pSiEREZtakgdfHixZg+fTpCQkJQVlaG77//Hjt27MCmTZvEoKayshLffvstSktLxUYA3t7ekMm4CjBRZ6mbnak0dApiu2frYKeQYUykFzadysXmpFz0DXQ195CILF5hhb55gAczNkRUR5sCm7y8PMybNw/Z2dlwdXVFbGwsNm3ahMmTJ2PHjh04cOAAACAiIqLe61JTUxEWFmayQRNRfYo6jQKqaw2BDUvRrMbkGD8xsHlycmSXHrtcrYGjUgaJhP9eyHoUcY4NETWiTYHN559/3uRz48aNY304kZnUDWyqapmxsTYTo30glQBJ2aXIKq5CgJt9px9TEASs2nke7/1zFtF+znj9xr4YFOLe6cclMgVjYMOMDRHVxSsfIhsgk0pgnFJjDGxknGNjNdwdlRhoCCp2JF/u9ONV1Wjx2A/H8M7GZGh1Ak5lleKmj/dh8a+JYsaPyJIZ2z27MWNDRHUwsCGyEcasTVWNzvA9AxtrMsGwYvq2M3kNnhMEAU/9mIBbVu0TL+jao7S6Fl/tS8O1H+7GX4nZkEsleOG63rhlsH5xwx8OZmD51nPt3j9RV7mSsWHzACK6goENkY0wBjbVzNhYpXFR3gCAvSn5UGvqZ012n8vHr8cycfhiERZ8e0TsfNcWvx3LxLA3t+LlP04hNb8Cno5KfHf/MNw/uieW3tofy28fAAD4el+a2HGqowRBwIu/ncTzPydCo237mImaUmRoHsA5NkRUFwMbIhthzNAYS9Hqzrshyxfj7wJfFxWqarU4cKFQfFwQhHpZlAOphXj1z1Nt2rdGq8Mb65NQVatFpK8TXr2hD7Y/Ow7DenqK29zQPwAx/i6oqNHi8z2pHf+BAKQVVOKb+Iv48XAGVu04b5J9EgGcY0NEjeOVD5GNkBsCGa1O38SD69hYF4lEgvFR+nK07clXytH2nS/AkYtFUMqlWHJTP0gkwHcH0vHZ7gut3vfe8wXIL6+Bh6MS6x8fjfkjwuBiV7+ERyKR4PGJvQAAX+5LQ0llbYd/pqMXi8T/X7b1HBIyiju8T6LqWq3Y1p5zbIioLgY2RDZCeVWGhu2erc84Q2BTt4GAMVtzx9AQzBkaguemRgMA3lh/Gi//fhK1rSjx+j0hEwBwXT//ZjN5U2J8Ee3njHK1Bp/v7XjW5ki6PrBRyaXQ6gQ8seYYKtSaDu+XujdjtkYmlcDFrk3NXYnIxjGwIbIRVwcybPdsfUZGeEIhkyA1vwKp+RX451QODqYWQimT4qGxPQEAD4/tiacMa918tf8i5n5+oNnsSlWNFptO5gAAZg4IaPb4UumVrM2qHSmY/X/78fpfSTiWXlRvu8RLxdh2JrfFn8eYsXltZh/4u9ohraASi349IWYVidqj7vwarr9ERHXxyofIRlx9J57NA6yPs50C14R5AABu/b/9ePCbIwCA2dcEwd9Vv7aNsWTs07mD4aiUIf5CId7eeLrJfW49k4uKGi2C3O0xOLTldWqm9fHD6F5eqNUKOJhWiM/3pGLWx/vw3M/HcS63DM+sPY4bPtqLe788jL0p+U3up6y6Fsm5ZQCA8VE+eH/2AMikEvx5PAvP/ZwIHYMbaqcri3OyIxoR1cfAhshGXD2nhs0DrJOx7XN+uRpKmRSzBgbiWUP5WV1T+vjhf/OGAAB+OZqJ/HJ1o/v7PSELgL45QGvubkulEnx1z1BsfnIM3ru1v5jl+enwJUz+YBd+PnJJ3PbXo5lN7ud4RgkEAQhyt4ePix3iwj2xYs5AyKQS/HL0Ehb9yuCG2sfY8tydjQOI6Cq88iGyEUo5Mza2YM7QEMyLC8Xi6dHYv3gCPrhtAFztG78zHRfuif5BrqjR6PDN/osNni+qqMEOQyOCmQMCWz0GqVSCXr7OuHlwEJbfPhC/LIhDtJ8zAKBPgAteuj4GALDpVE6TC3oeMZShDQq5kiW6tp8/lt02AFKJPlB6+NsjKOecG5RU1TZo8U1NEzuisXEAEV2Fs+6IbMTVGRou0GmdHFVyvDazb6u2lUgkuH90Tzz2wzF8E38RC8aFAwBWbDuH3efycSa7DLVaAdF+zogyBCbtMTjUA389Ngpnc8sR6esEqUSCz/ekIrO4CtvO5OHafv4NXnPUMC/n6vK3Gf31GaCnfzqOf5JyMWvlXiy7fQC8nVSABPB2UnWreRPncstw86p9UClk+L+7BmFwqIe5h2TxxDk2zNgQ0VUY2BDZiKtL0Zix6R6m9/VDoJs9MoursGrHeexIzsPxSyXi824OCvzL0BCgI+QyKWICXMTvbxgQgFU7zuO3Y5kNAhudThADm7oZG6MZ/QMQ5G6Ph745gnN55bjuwz3ic/2D3bDqzkEIcLPv8JgtnVqjxb/WJKC0WgNUa3D7p/F4fWZf3D40xNxDs2icY0NETWEpGpGNuLoUjXNsuge5TIp7RoYB0LeGPn6pBG4OCrx7Syx2PTsex16cjOmNZFQ66kZDaduO5MsNurKdv1yOsmoN7BUyRPs3nikaGOKOvx4bhVERXpBJJWIgfjyjGDd8tAeH0gobfZ0tef+fs0jKLoW7gwKTY3xRqxWw6NcT+Ca+YVkhXWGcY8PFOYnoarzyIbIRzNh0X7ddEwxnlT4BH+3njD8eHYVbhwQjxNOh08q6ovycEe3njBqtDhtPZdd7zji/JjbItdkA28fFDt/ePwzn37oW59+6FrufG49oP2fkl9fgjv/FY3NSyy2lrdW+8/n41LDI6ts3x+LTuYNx/6geAIBfj15q7qXd3pWMDQMbIqqPgQ2RjWgwx4br2HQbznYKfDpvCJ6bFoVfFoxAiKdDlxz3BkPHtN+OZdV7XCxDa0V76bqCPRzw6yMjML2vH2q1Ap5Zexw5JdWmGawFEQQBL/52EoIA3H5NMKb28YNEIsHcuFAAwKnM0iabMlCd5gHM2BDRVXjlQ2Qjrg5srl6wk2xbXLgnHhkXAUdV102dNHZai08twKWiSgBArVaHbWf0ndiG9mj7RHgHpRzLbx+IfoGuKKmqxTNrj9tcW+h95wtw/nIFnFRy/Oe63uLjIR4O8HRUokarw6mskmb20L0Zmwe4cY4NEV2FgQ2Rjbi6CxpL0aizBbrZY0S4JwQB+OWIfk2b7WfykF9eAy8nJUZFeLVrv0q5FMtuHwB7hQx7UvLxxd5UUw7b7IytuWcNDISz3ZWLc4lEIma5jl4sNsfQrALn2BBRUxjYENkIeYN2z/z1ps5365AgAMDPRzOg0wlYa1jAc9bAwA79Gwz3dsIL1+uzGe9sTEZGYWXHB2sBckqqsfm0fu7QXcNDGzxv7CJnnKdE9VXVaFFlKNNju2ciuhqvfIhsxNUXkUzYUFeY1scfzio5MgqrsOFkNrYbytBuHRLc4X3fMTQEQ8M8UKPV4Y/jWS2/wAqsOZQOrU7A0DCPRtcWMq77cyS9CIJgWyV4pmCcXyOXSsSGGURERgxsiGxE3VI0hUzSrRY5JPOxV8pwvWHRzcW/nIBGJ6B/sBsifdu/IKiRRCLBrEH6eTx/n8xuYWvLV6vV4YeD6QCAO4c3vlZNbJAr5FIJLpepcamoqiuHZxWMgY2bg5J/44ioAQY2RDaibsaG82uoKxnL0crUGv33g4NMtu+pffwgk0pwMrMU6QXWXY62PjEbuaVqeDoqMa2vX6Pb2Clk6GNYCNXYXY6uMDYO8HBk4wAiaoiBDZGNqBvYsNUzdaWBwW4I93YEAKjkUswwZHBMwcNRieE99d3VrDlrsy8lH8//kggAuGNYCFRyWZPbDgwxNhBgYHO1Qq5hQ0TN4NUPkY2oW4omY6tn6kISiQR3DtNPhL8+NgCu9qa9mz69rz8AYMPJHJPut6vsP1+Ae786BLVGhwnRPlg4IaLZ7Y3zbI6mF3fB6KxLETuiEVEzGNgQ2Yi6GRs5MzbUxe4eEYav7h2K12/sY/J9T+3jB6kEOJ5RjEtFlcgrq8bne1KtolPaxpM5uPfLQ6iu1WF8lDdW3TWo2WwNcGVh06TsUlTWaLpimFYjNb8CgH6ODRHR1Xj1Q2Qj6i7IKeccG+piUqkEYyO94aA0facqb2eVuNjnv9edxMSlO/H6X0m4edU+8ULX0uh0At7ffBYPf3sEVbVajIvyxqq7BrcY1ABAgKsd/FzsoNUJOJ7BhTqNtifn4ev9aQAglicSEdXFwIbIRijrZmxYikY25tp++nK0XWcvo0ytgVIuRV6ZGnM+jUeahQU3Wp2Ax9ccw4dbzwEA7hkZhs/mDYGdouWgBtCX9l1jCOT2puR32jjNoaiiBsczitv8upS8cjz+/THoBOC2IcG4wYTzuIjIdjCwIbIRdbM0XJyTbM30vv7wcFTCxU6ON27siz3Pj0cvHyfklFZjzv/icTa3zNxDFC39Jxl/JWZDKZNi6a398fKMPg0W0G3JuEhvAPoshS3Q6gR8E38RY9/djpkr92Lt4Qzxubyyatyz+iBmrtyLmSv3Ys6n8ThX53yWVtfiga8Po0ytwTVh7nj9xr5s9UxEjeLqVkQ2QiFnu2eyXd7OKmx/ehxUCqmY+fj+geGY8794pOSVY9bKvfjgtgGY0qfxNspd5feETKzacR4A8O6tsZg5ILBd+xkb5Q2JBDiVVYrc0mr4utiZcphdKqOwEo9+fxSJl66U1S39JxnXxfrDQSnHq38mYXvy5XqvefT7o/hj4SjYKWR4+fdTSM2vQKCbPVbdNRhKOW/cEFHj+NeByEbUbfHMOTZki1wdFPXKubydVfjpoTgM7+mBihotHvzmiBhUmENCRjGe+1nf0nnBuPB2BzUA4OWkQmyQGwBghxVnbTIKK3H7p/FIvFQCZzs5Xp4RgyB3e+SWqvH57lTsSM7D+sRsyKQSvHdrf3w6dzC8nFQ4m1uO/248gz+OZ2HdsUxIJcCHcwbAy0ll7h+JiCwYAxsiG6GQ12kewDk21E14OCrxzX3DcPeIMADAfzeewfnL5eLz+eVqfBt/Efnl6k4dx8nMEsz/4iDUGh0m9fbBs1OiOrzPCVE+AIDtZy63sKVlulSkD2oyi6vQ09sRm58ci3tG9sCzU/Xvzf/tPI8XfjsJALhnRBhuHhyEKX388O6tsQCA1XvTsMiw9s/CCb0wOJQNA4ioeQxsiGyEXMp2z9Q9KWRSvHJDH0yM1gcC38Wni88t/P4oXvjtJCYs3YFv4y9CqxNMfvykrFLc9fkBlFTVYlCIG5bdPhBSE2RNx0fr59nsSclHjUbX4f11lctlany8IwU3fbwPmcVV6OHliB8eGA4/V3053YzYAPQLdEVFjRaXiqrg72qHJyZHiq8fH+WD+XH6dZEqa7ToH+yGx1pY+4eICGBgQ2Qz6q9jw4wNdT93GS6Gfz6SgaoaLQ5cKED8hUIAQGm1Bi/8dhI3r9JfbJvKmZxS3PlZPIorazEg2A1f3TsUTirTTF/tG+AKLycVytUaHE4rNMk+O9vyLecw4u2teGdjMvLK1GJQU3eOkFQqweJro8XvX57Rp8F7tvja3ugT4AJ3BwWW3TaADVGIqFXYPIDIRihZikbd3Nhe3gj2sEdGYRX+PJ6F349nAgBuvyYY0X7OeO+fs0jIKMYNK/bg4zsHYVhPzw4d72xuGe783wEUVdaif5Arvr5vKJztFKb4UQDoA4BxUd74+cglbE/Ow4gIL5PtuzNsPZ2LD7acBQAMDHHDHUNDcH1sAOyVDdtcjwj3wiszYqDRCZjax7fB83YKGX57dCQ0WqHR1xMRNYa3QIhsBEvRqLuTSiW4c5g+a7P0n2TsTSmAXCrBwgkRuHtkD/z9xGjE+LugoKIGd352AL8nZLb7WOdyy3DH/+JRUFGDvoEu+PreYXAxYVBjNN44zybZsufZXC5Ti40T7hvVA+seGYlbhwQ3G5TcPbIH7h/ds8nWzQqZlEENEbUJr36IbISCC3QS4dbBQVDK9It3AsAtg4MQ5O4AAAhyd8AvC0bg+lh/aHQC3lh/GoLQ9jk3KXnlmPO/A8gvr0GMvwu+vW8YXB1MH9QAwKheXpBLJUjJK8eFOk0RLIkgCHj+l0QUVNQg2s9ZbA5ARNTVGNgQ2QhFnWCGc2you/J0UuHafvq1bGRSCR4dX3/Sub1ShqW39odSLsXlMjUu5Fe0af8XLpfjjv/FI79cjd7+Lvju/mFwc1CabPxXc7VXiCVof5/M6bTjdMTvCVnYdiYPSrkUy24fUK8lNxFRV2JgQ2Qj6jcP4K82dV8PjQ2Hq70CD4zuiWAPhwbP2ylkGBjsBgA4cKH1k/LT8isw53/xyCtTI9rPGd/dPwzujp0X1Bhd21cfqG04kd3px2qPzUm5AIAHR/dEtJ+LmUdDRN0Zr36IbETd8jOWolF31tvfBcdfnoJF06Ob3MbYOCD+QkGr9lmr1eHhb48gt1SNSF8nfHf/MHh0QVADAFP6+EEmleBUVikuFrQtw9QVEjKKAQAjIjrWjIGIqKMY2BDZCCXbPRO12vAe+sUeD6QWtGqezZd703AmpwzuDgp8e/8weDqpOnuIIg9HJYb31I/X0srR8sqqkVlcBYkEiA1yM/dwiKibY2BDZCPk9ZoH8FebqDkDQ9yhkEmQW6rGxYLKZrfNLK4S2xgvvrY3fJztmt2+M1zbzx+A5ZWjJaQXAwB6+TiZbP0eIqL24tUPkY1g8wCi1rNXyjDAOM8mtflytFf/OIXKGi2uCXPHLYOCumB0DU2J8YNUAiReKkFGYfOBWFcylqEZ30siInNiYENkI9jumahthvXQzwlpqoFAZY0Gb204jX+SciGXSvDGjf0gNdNNA29nFYYayuc+230B6QWV7WpVbWpXAht38w6EiAgMbIhsBruiEbXNMMO8lfgLDefZbD2di0nv7cSnuy4AABZOiECUn3OXj7EuYznaV/svYsy72zHsra3Ydz7fbOPR6gQkXioBwIwNEVkGXv0Q2Qg5S9GI2mRwqDvkUgmySqpxqahKfDwpqxQPfH0YWSXVCHK3x2fzhuCJSZFmHKnerYODcd+oHugf5CouQrrg26NIbWEtns92X8C9Xx7CZcOipaZy/nI5ytUa2CtkiPR1Mum+iYjao02BzapVqxAbGwsXFxe4uLggLi4Of//9t/h8dXU1Hn30UXh6esLJyQk333wzcnNzTT5oImqoblc0GUvRiFrkoJSjX5ArAGB/nbbPH249B50ATIz2weYnx2JSjK+5hliPvVKGF6+Pwe8LR+H4y1MwMMQNJVW1uP+rQyiprMW2M7l48scE/HQ4Q3xNSl4Z3tpwGtvO5OGhbw5DrdGabDzGxgH9glzZsISILEKb/hIFBQXh7bffxpEjR3D48GFMmDABM2fOxKlTpwAATz75JP7880+sXbsWO3fuRFZWFm666aZOGTgR1Ve3FE3BUjSiVhkd4QUA+GhbCsrVGpzJKcXGUzmQSIBF06Nhr5SZeYSNs1fK8Mldg+HnYofzlytwzVtbcO+Xh7HuWCYW/ZKIQ2n6eUNv/50MnaHK7mh6Mf6z7qTJ5uYcM8yvGcgyNCKyEG26+pkxYwauvfZa9OrVC5GRkXjzzTfh5OSE+Ph4lJSU4PPPP8f777+PCRMmYPDgwVi9ejX27duH+Pj4zho/ERnIpBJIJFf+n4hadv+Yngh0s0d6YSVe/eMUVmxNAaCfz9LL17xzalri42KH/80bApVcihqNDm4OCsQGuUInAE+sScDW07nYcjoXMqkEr8yIgVQC/HzkEj7fk2qS47MjGhFZmnY3nddqtVi7di0qKioQFxeHI0eOoLa2FpMmTRK3iY6ORkhICPbv34/hw4c3uh+1Wg21+krdb2lpaXuHRNTtKWT6CxwFS9GIWsXFToEPbhuA2z/dj7VHLomPPzYhwoyjar1+Qa74ZcEIXCqqxLgoH9Rqdbj2w93IKKzCg98cAQDcfk0w7h7ZAzoBeO2vJLy14TR6+TpjbKR3u49bWaNBco7+83pAiJspfhQiog5rc73KiRMn4OTkBJVKhYcffhjr1q1DTEwMcnJyoFQq4ebmVm97X19f5OQ0vVLykiVL4OrqKn4FBwe3+YcgIj2FIVMjYykaUasN7eGBBePCxe+n9fFDtJ+LGUfUNn0DXTGtrz/sFDI42ynwwewBkEr0XcsclDL8a1IvAMA9I8Mwe0gQdAKw8PujOH+5vN3HPJVVCp0A+Lqo4O9qb6ofhYioQ9p89RMVFYWEhAQcOHAACxYswPz585GUlNTuASxevBglJSXiV0ZGRssvIqJGKeT6X2lmbIja5l8TIzE41B12CqkYCFirIWEeeNLQxe1fE3vBx9kOACCRSPD6jX0xJNQdZdUaPPDVYazcnoKHvzmCOz+Lx8WC5rur1XUqU9/muV+gq+l/ACKidmpzKZpSqUREhD5FP3jwYBw6dAjLly/HbbfdhpqaGhQXF9fL2uTm5sLPz6/J/alUKqhUqraPnIgaMK5fw3bPRG2jlEvxwwPDUVmjgZuD0tzD6bDHJvbCbdcEw9u5/uerSi7D/80djBtW7MGF/Aq8uylZfO7+rw7j10dGwNlO0eL+T2Xpy9Bi/K0ns0VEtq/D9So6nQ5qtRqDBw+GQqHA1q1bxeeSk5ORnp6OuLi4jh6GiFpBacjUyNh6lajNlHKpTQQ1Rj4udpBIGt7k8HJS4fO7r8Hwnh6Y0T8Ai6ZHw9dFhXN55XhiTQK0upa7pomBTQAzNkRkOdqUsVm8eDGmT5+OkJAQlJWV4fvvv8eOHTuwadMmuLq64r777sNTTz0FDw8PuLi44LHHHkNcXFyTjQOIyLSMa0komLEhomb09nfBmgev3HSM6+mJ2Z/sx9YzeVj6TzKenxbd5GtrNDqcyysDAPQJYMaGiCxHm27r5uXlYd68eYiKisLEiRNx6NAhbNq0CZMnTwYAfPDBB7j++utx8803Y8yYMfDz88Ovv/7aKQMnooaMc2vY7pmI2qJ/sBveuSUWALBqx3kk55Q1ue25vDLUagW42MkR5M7GAURkOdqUsfn888+bfd7Ozg4rV67EypUrOzSo1tBqtaitre3043RHCoUCMpllLkpHzTMu0qlgKRoRtdHMAYH451Qu1p/IxofbzmHlHYMa3S5JLENzabTUjYjIXNq9jo25CIKAnJwcFBcXm3soNs3NzQ1+fn780LIyxoCGGRsiao/HJkZg/YlsbDiRjXO5ZY0uUnqlcQDn1xCRZbG6wMYY1Pj4+MDBwYEX3iYmCAIqKyuRl5cHAPD39zfziKgtlHJmbIio/aL9XDCtjx82nsrBim0p+HDOwAbbGDM2nF9DRJbGqgIbrVYrBjWenp7mHo7NsrfX10zn5eXBx8eHZWlWZP6IMLjYyREXzt8PImqfxyZGYOOpHPyZmIXHJ/ZChI+T+JxOJyAp2xDYBDKwISLLYlW3dY1zahwcHMw8EttnfI85j8m63NA/AKvvGQpX+5bXoSAiakyfAFdMjvGFIACf7jpf77mMokqUqzVQyqUI93ZqYg9EROZhVYGNEcvPOh/fYyKi7uvOYSEAgCMXi+o9bpxfE+XrzJJXIrI4/KtERERE9RibBqQXVkKj1YmPix3R/FmGRkSWh4ENERER1ePvYgeVXIparYDM4irx8VNZJQA4v4aILBMDGyIiIqpHKpWgh5cjAODC5QrxcbFxADuiEZEFYmBjJl9++SXc3NzMPQwiIqJG9fQ2BDb5+sAmv1yN3FI1JBJ9W2giIkvDwIaIiIgaMGZsUvPLAVxpHNDD0xGOKqtaLYKIugmrD2wEQUBljcYsX4IgtGvMO3bswD333IOSkhJIJBJIJBK88sorAAC1Wo1nnnkGgYGBcHR0xLBhw7Bjxw7xtcZMz19//YWoqCg4ODjglltuQWVlJb766iuEhYXB3d0djz/+OLRarfi6sLAwvP7665gzZw4cHR0RGBiIlStXduStJyIiG9bDS9/O2ViKJjYOYBkaEVkoq7/lUlWrRcxLm8xy7KTXpsJB2fa3cMSIEVi2bBleeuklJCcnAwCcnPQfIAsXLkRSUhLWrFmDgIAArFu3DtOmTcOJEyfQq1cvAEBlZSU+/PBDrFmzBmVlZbjpppswa9YsuLm5YcOGDbhw4QJuvvlmjBw5Erfddpt43HfffRf//ve/8eqrr2LTpk3417/+hcjISEyePNkE7wYREdkSYylaqqEUzdg4gIENEVkqqw9srJFSqYSrqyskEgn8/PzEx9PT07F69Wqkp6cjICAAAPDMM89g48aNWL16Nd566y0A+kUzV61ahfDwcADALbfcgm+++Qa5ublwcnJCTEwMxo8fj+3bt9cLbEaOHIlFixYBACIjI7F371588MEHDGyIiKiBnoZStOySalTWaMSMTZ8AV3MOi4ioSVYf2NgrZEh6barZjm1KJ06cgFarRWRkZL3H1Wo1PD09xe8dHBzEoAYAfH19ERYWJmZ9jI/l5eXV209cXFyD75ctW2bCn4CIiGyFm4MS7g4KFFXWIimrFKkF+swN17AhIktl9YGNRCJpVzmYJSovL4dMJsORI0cgk9UPmuoGLQqFot5zEomk0cd0Oh2IiIjaq4eXI4rSi7H+RDYEAfBxVsHbWWXuYRERNco2IgIrpFQq603uB4CBAwdCq9UiLy8Po0ePNvkx4+PjG3zfu3dvkx+HiIhsQ09vJxxNL8aGE9kAuH4NEVk2q++KZq3CwsJQXl6OrVu3Ij8/H5WVlYiMjMSdd96JefPm4ddff0VqaioOHjyIJUuWYP369R0+5t69e/HOO+/g7NmzWLlyJdauXYt//etfJvhpiIjIFhlbPueWqgGwcQARWTYGNmYyYsQIPPzww7jtttvg7e2Nd955BwCwevVqzJs3D08//TSioqJw44034tChQwgJCenwMZ9++mkcPnwYAwcOxBtvvIH3338fU6eaZ34SERFZPmMDASM2DiAiSyYR2rsYSycpLS2Fq6srSkpK4OJS/85QdXU1UlNT0aNHD9jZ2ZlphNYpLCwMTzzxBJ544olWbc/3moiIknPKMHXZLvH7nc+OQ6inYzOvICIyreZig6sxY0NERESNCvV0gESi/38nlRzB7g7mHRARUTMY2BAREVGj7BQyBLjaA9C3eZZKJWYeERFR09gVrZtIS0sz9xCIiMgK9fR2RGZxFRsHEJHFY8aGiIiImjSljx/sFFJM6eNr7qEQETXLKjM2FtbvwCbxPSYiIgCYOzwUdwwNgYxlaERk4awqY6NQKAAAlZWVZh6J7TO+x8b3nIiIui8GNURkDawqYyOTyeDm5oa8vDwAgIODAyQS/rE1JUEQUFlZiby8PLi5uUEmk5l7SERERERELbKqwAYA/Pz8AEAMbqhzuLm5ie81EREREZGls7rARiKRwN/fHz4+PqitrTX3cGySQqFgpoaIiIiIrIrVBTZGMpmMF99ERERERATAypoHEBERERERNYaBDRERERERWT0GNkREREREZPUsbo6NcWHI0tJSM4+EiIiIiIjMyRgTtGbxeIsLbAoKCgAAwcHBZh4JERERERFZgoKCAri6uja7jcUFNh4eHgCA9PT0FgdPneuaa67BoUOHzD2Mbo3nwPx4DsyP58D8eA4sA8+D+fEcdL2SkhKEhISIMUJzLC6wkUr1035cXV3h4uJi5tF0bzKZjOfAzHgOzI/nwPx4DsyP58Ay8DyYH8+B+RhjhGa36YJxkJV69NFHzT2Ebo/nwPx4DsyP58D8eA4sA8+D+fEcWDaJ0JqZOF2otLQUrq6uKCkpYURMRERERNSNtSU2sLiMjUqlwssvvwyVSmXuoRARERERkRm1JTawuIwNERERERFRW1lcxoaIiIiIiKitGNgQEREREZHVY2Bjo1auXImwsDDY2dlh2LBhOHjwoPjcQw89hPDwcNjb28Pb2xszZ87EmTNnWtzn2rVrER0dDTs7O/Tr1w8bNmyo97wgCHjppZfg7+8Pe3t7TJo0CefOnTP5z2YtmjsHALB//35MmDABjo6OcHFxwZgxY1BVVdXsPnfs2IFBgwZBpVIhIiICX375ZZuP2500916cP38es2bNgre3N1xcXDB79mzk5ua2uE+eg9bbtWsXZsyYgYCAAEgkEvz222/ic7W1tXj++efRr18/ODo6IiAgAPPmzUNWVlaL++U5aL3mzgEA3H333ZBIJPW+pk2b1uJ+eQ5ar6VzUF5ejoULFyIoKAj29vaIiYnB//3f/7W438TERIwePRp2dnYIDg7GO++802Cblj63u4slS5bgmmuugbOzM3x8fHDjjTciOTm53jaffvopxo0bBxcXF0gkEhQXF7dq3/xdsDAC2Zw1a9YISqVS+OKLL4RTp04JDzzwgODm5ibk5uYKgiAIn3zyibBz504hNTVVOHLkiDBjxgwhODhY0Gg0Te5z7969gkwmE9555x0hKSlJeOGFFwSFQiGcOHFC3Obtt98WXF1dhd9++004fvy4cMMNNwg9evQQqqqqOv1ntjQtnYN9+/YJLi4uwpIlS4STJ08KZ86cEX788Uehurq6yX1euHBBcHBwEJ566ikhKSlJWLFihSCTyYSNGze2+rjdSXPvRXl5udCzZ09h1qxZQmJiopCYmCjMnDlTuOaaawStVtvkPnkO2mbDhg3Cf/7zH+HXX38VAAjr1q0TnysuLhYmTZok/Pjjj8KZM2eE/fv3C0OHDhUGDx7c7D55DtqmuXMgCIIwf/58Ydq0aUJ2drb4VVhY2Ow+eQ7apqVz8MADDwjh4eHC9u3bhdTUVOGTTz4RZDKZ8Pvvvze5z5KSEsHX11e48847hZMnTwo//PCDYG9vL3zyySfiNq353O4upk6dKqxevVo4efKkkJCQIFx77bVCSEiIUF5eLm7zwQcfCEuWLBGWLFkiABCKiopa3C9/FyyPyQObjz76SAgNDRVUKpUwdOhQ4cCBA+JzVVVVwiOPPCJ4eHgIjo6Owk033STk5OS0uM+ffvpJiIqKElQqldC3b19h/fr19Z7X6XTCiy++KPj5+Ql2dnbCxIkThbNnz5r6R7MaQ4cOFR599FHxe61WKwQEBAhLlixpdPvjx48LAISUlJQm9zl79mzhuuuuq/fYsGHDhIceekgQBP058PPzE959913x+eLiYkGlUgk//PBDR34cq9TSORg2bJjwwgsvtGmfzz33nNCnT596j912223C1KlTW33c7qS592LTpk2CVCoVSkpKxOeLi4sFiUQibN68ucl98hy0X2MXdFc7ePCgAEC4ePFik9vwHLRfU4HNzJkz27QfnoP2a+wc9OnTR3jttdfqPTZo0CDhP//5T5P7+fjjjwV3d3dBrVaLjz3//PNCVFSU+H1Ln9vdWV5engBA2LlzZ4Pntm/f3urAhr8LlsekpWg//vgjnnrqKbz88ss4evQo+vfvj6lTpyIvLw8A8OSTT+LPP//E2rVrsXPnTmRlZeGmm25qdp/79u3DnDlzcN999+HYsWO48cYbceONN+LkyZPiNu+88w4+/PBD/N///R8OHDgAR0dHTJ06FdXV1ab88axCTU0Njhw5gkmTJomPSaVSTJo0Cfv372+wfUVFBVavXo0ePXogODhYfDwsLAyvvPKK+P3+/fvr7RMApk6dKu4zNTUVOTk59bZxdXXFsGHDGj2uLWvpHOTl5eHAgQPw8fHBiBEj4Ovri7Fjx2LPnj319jNu3Djcfffd4vctnYO2nntb1tJ7oVarIZFI6rWOtLOzg1QqrXceeA66VklJCSQSCdzc3MTHeA46344dO+Dj44OoqCgsWLAABQUF9Z7nOehcI0aMwB9//IHMzEwIgoDt27fj7NmzmDJlirjN3XffjXHjxonf79+/H2PGjIFSqRQfmzp1KpKTk1FUVCRu09x56s5KSkoAAB4eHm16HX8XLJ9JA5v3338fDzzwAO655x6xRtTBwQFffPEFSkpK8Pnnn+P999/HhAkTMHjwYKxevRr79u1DfHx8k/tcvnw5pk2bhmeffRa9e/fG66+/jkGDBuGjjz4CoJ/XsWzZMrzwwguYOXMmYmNj8fXXXyMrK6tBHWt3kJ+fD61WC19f33qP+/r6IicnR/z+448/hpOTE5ycnPD3339j8+bN9f5AhoeHw8vLS/w+Jyen2X0a/9vScbuDls7BhQsXAACvvPIKHnjgAWzcuBGDBg3CxIkT681JCgkJgb+/v/h9U+egtLQUVVVVrT733UFL78Xw4cPh6OiI559/HpWVlaioqMAzzzwDrVaL7OxscXueg65TXV2N559/HnPmzKm3ABvPQeeaNm0avv76a2zduhX//e9/sXPnTkyfPh1arVbchuegc61YsQIxMTEICgqCUqnEtGnTsHLlSowZM0bcxt/fHyEhIeL3TZ0D43PNbdPdz4FOp8MTTzyBkSNHom/fvm16LX8XLJ/cVDsyRqWLFy8WH6sblQ4dOhS1tbX1otbo6GiEhIRg//79GD58OAB9puDuu+8WswX79+/HU089Ve9YU6dOFYOWljIFt99+u6l+RJty5513YvLkycjOzsbSpUsxe/Zs7N27F3Z2dgCArVu3mnmEtkun0wHQN3G45557AAADBw7E1q1b8cUXX2DJkiUAgK+//tpsY7R13t7eWLt2LRYsWIAPP/wQUqkUc+bMwaBBgyCVXrnfw3PQNWprazF79mwIgoBVq1bVe47noHPV/Yzs168fYmNjER4ejh07dmDixIkAeA4624oVKxAfH48//vgDoaGh2LVrFx599FEEBASI1zbGzwXquEcffRQnT55sUCXRGvxdsHwmC2yai0rPnDmDnJwcKJXKeiUGxufrRq3MFHSMl5cXZDJZg+5Oubm58PPzE793dXWFq6srevXqheHDh8Pd3R3r1q3DnDlzGt2vn59fs/s0/jc3N7fe3Yzc3FwMGDDAFD+a1WjpHBjfn5iYmHrP9+7dG+np6U3ut6lz4OLiAnt7e8hkslad++6gNb8HU6ZMwfnz55Gfnw+5XA43Nzf4+fmhZ8+eTe6X58D0jEHNxYsXsW3btnrZmsbwHHSunj17wsvLCykpKWJgczWeA9OpqqrCv//9b6xbtw7XXXcdACA2NhYJCQlYunRpgzIno6bOgfG55rbpzudg4cKF+Ouvv7Br1y4EBQV1eH/8XbA8FtfueevWrVi4cKG5h2G1lEolBg8eXC/jotPpsHXrVsTFxTX6GkHfRAJqtbrJ/cbFxTXI4mzevFncZ48ePeDn51dvm9LSUhw4cKDJ49qqls5BWFgYAgICGrSaPHv2LEJDQ5vcb0vnoD3n3la15b3w8vKCm5sbtm3bhry8PNxwww1N7pfnwLSMQc25c+ewZcsWeHp6tvganoPOdenSJRQUFNS7QXU1ngPTqa2tRW1tbb1MMQDIZDIxu9+YuLg47Nq1C7W1teJjmzdvRlRUFNzd3cVtmjtP3YkgCFi4cCHWrVuHbdu2oUePHibZL38XLJCpuhCo1WpBJpM16PYxb9484YYbbhC2bt3aaJeJkJAQ4f33329yv8HBwcIHH3xQ77GXXnpJiI2NFQRBEM6fPy8AEI4dO1ZvmzFjxgiPP/54e38cq7ZmzRpBpVIJX375pZCUlCQ8+OCDgpubm5CTkyOcP39eeOutt4TDhw8LFy9eFPbu3SvMmDFD8PDwqNd6cMKECcKKFSvE7/fu3SvI5XJh6dKlwunTp4WXX3650XbPbm5uwu+//y62z+3O7Z6bOgeCoG8r6eLiIqxdu1Y4d+6c8MILLwh2dnb1OtPNnTtXWLRokfi9sa3ks88+K5w+fVpYuXJlo20lmztud9LSe/HFF18I+/fvF1JSUoRvvvlG8PDwEJ566ql6++A56JiysjLh2LFjwrFjxwQAwvvvvy8cO3ZMuHjxolBTUyPccMMNQlBQkJCQkFCv3XDdTk88Bx3T3DkoKysTnnnmGWH//v1CamqqsGXLFmHQoEFCr1696rWe5znomObOgSAIwtixY4U+ffoI27dvFy5cuCCsXr1asLOzEz7++GNxH4sWLRLmzp0rfl9cXCz4+voKc+fOFU6ePCmsWbNGcHBwaNDuuaXP7e5iwYIFgqurq7Bjx456f2sqKyvFbbKzs4Vjx44J//vf/wQAwq5du4Rjx44JBQUF4jb8XbB8Jm33PHToUGHhwoXi91qtVggMDBSWLFkiFBcXCwqFQvj555/F58+cOSMAEPbv39/kPmfPni1cf/319R6Li4tr0GZ46dKl4vMlJSXdts2w0YoVK4SQkBBBqVQKQ4cOFeLj4wVBEITMzExh+vTpgo+Pj6BQKISgoCDhjjvuEM6cOVPv9aGhocLLL79c77GffvpJiIyMFJRKpdCnT58m2277+voKKpVKmDhxopCcnNypP6cla+ocGC1ZskQICgoSHBwchLi4OGH37t31nh87dqwwf/78eo9t375dGDBggKBUKoWePXsKq1evbvNxu5Pm3ovnn39e8PX1FRQKhdCrVy/hvffeE3Q6Xb3X8xx0jLFt6tVf8+fPF1JTUxt9DoCwfft2cR88Bx3T3DmorKwUpkyZInh7ewsKhUIIDQ0VHnjggQYXXDwHHdPcORAE/QX13XffLQQEBAh2dnZCVFRUg79H8+fPF8aOHVtvv8ePHxdGjRolqFQqITAwUHj77bcbHLulz+3uoqm/NXX/3b788sstbsPfBcsnEQRBMFX258cff8T8+fPxySefYOjQoVi2bBl++uknnDlzBr6+vliwYAE2bNiAL7/8Ei4uLnjssccA6Fs6G02cOBGzZs0Sy9H27duHsWPH4u2338Z1112HNWvW4K233sLRo0fFbhb//e9/8fbbb+Orr75Cjx498OKLLyIxMRFJSUniZHgiIiIiIrJdJmseAAC33XYbLl++jJdeegk5OTkYMGAANm7cKE7s/+CDDyCVSnHzzTdDrVZj6tSp+Pjjj+vtwziZ12jEiBH4/vvv8cILL+Df//43evXqhd9++61ei77nnnsOFRUVePDBB1FcXIxRo0Zh48aNDGqIiIiIiLoJk2ZsiIiIiIiIzMHiuqIRERERERG1FQMbIiIiIiKyegxsiIiIiIjI6jGwISIiIiIiq2dzgc0rr7yCAQMGmHsYRERERETUhToU2OzatQszZsxAQEAAJBIJfvvttya3ffjhhyGRSLBs2bJm95mWlgaJRNLg66677urIUImIiIiIyIZ1aB2biooK9O/fH/feey9uuummJrdbt24d4uPjERAQ0Op9b9myBX369BG/t7e378hQiYiIiIjIhnUoYzN9+nS88cYbmDVrVpPbZGZm4rHHHsN3330HhULR6n17enrCz89P/HJ1dQUAFBcX4/7774e3tzdcXFwwYcIEHD9+vMHrP/nkEwQHB8PBwQGzZ89GSUlJ239AIiIiIiKyCp06x0an02Hu3Ll49tln62VfOuLWW29FXl4e/v77bxw5cgSDBg3CxIkTUVhYKG6TkpKCn376CX/++Sc2btyIY8eO4ZFHHjHJ8YmIiIiIyPJ0qBStJf/9738hl8vx+OOPt/m1I0aMgFR6Je7avXs3KioqcPDgQeTl5UGlUgEAli5dit9++w0///wzHnzwQQBAdXU1vv76awQGBgIAVqxYgeuuuw7vvfce/Pz8TPCTERERERGRJem0wObIkSNYvnw5jh49ColE0ug206dPx+7duwEAoaGhOHXqlPjcjz/+iN69e4vfBwcH47PPPkN5eTk8PT3r7aeqqgrnz58Xvw8JCRGDGgCIi4uDTqdDcnIyAxsiIiIiIhvUaYHN7t27kZeXh5CQEPExrVaLp59+GsuWLUNaWho+++wzVFVVAUCD+TfBwcGIiIio91h5eTn8/f2xY8eOBsdzc3Mz+c9ARERERETWodMCm7lz52LSpEn1Hps6dSrmzp2Le+65BwDqZVVaY9CgQcjJyYFcLkdYWFiT26WnpyMrK0vswhYfHw+pVIqoqKi2/RBERERERGQVOhTYlJeXIyUlRfw+NTUVCQkJ8PDwQEhISIOSMYVCAT8/v3YHGJMmTUJcXBxuvPFGvPPOO4iMjERWVhbWr1+PWbNmYciQIQAAOzs7zJ8/H0uXLkVpaSkef/xxzJ49m2VoREREREQ2qkOBzeHDhzF+/Hjx+6eeegoAMH/+fHz55ZcdGlhjJBIJNmzYgP/85z+45557cPnyZfj5+WHMmDHw9fUVt4uIiMBNN92Ea6+9FoWFhbj++uvx8ccfm3w8RERERERkGSSCIAjmHgQREREREVFHdOo6NkRERERERF2BgQ0REREREVk9BjZERERERGT1GNgQEREREZHVY2BDRERERERWj4ENERERERFZPQY2RERERERk9RjYEBFRu4wbNw5PPPFEtzs2ERFZJgY2RETU6Xbs2AGJRILi4mKTvO7XX3/F66+/broBEhGR1ZObewBERERt5eHhYe4hEBGRhWHGhoiIWlRRUYF58+bByckJ/v7+eO+99+o9/80332DIkCFwdnaGn58f7rjjDuTl5QEA0tLSMH78eACAu7s7JBIJ7r77bgCATqfDkiVL0KNHD9jb26N///74+eefW3zd1aVoYWFheOONN8QxhoaG4o8//sDly5cxc+ZMODk5ITY2FocPH6437j179mD06NGwt7dHcHAwHn/8cVRUVJj67SMioi7AwIaIiFr07LPPYufOnfj999/xzz//YMeOHTh69Kj4fG1tLV5//XUcP34cv/32G9LS0sQgJDg4GL/88gsAIDk5GdnZ2Vi+fDkAYMmSJfj666/xf//3fzh16hSefPJJ3HXXXdi5c2ezr2vMBx98gJEjR+LYsWO47rrrMHfuXMybNw933XUXjh49ivDwcMybNw+CIAAAzp8/j2nTpuHmm29GYmIifvzxR+zZswcLFy7sjLeQiIg6mUQw/oUnIiJqRHl5OTw9PfHtt9/i1ltvBQAUFhYiKCgIDz74IJYtW9bgNYcPH8Y111yDsrIyODk5YceOHRg/fjyKiorg5uYGAFCr1fDw8MCWLVsQFxcnvvb+++9HZWUlvv/++0ZfB+gzNgMGDBCPHRYWhtGjR+Obb74BAOTk5MDf3x8vvvgiXnvtNQBAfHw84uLikJ2dDT8/P9x///2QyWT45JNPxP3u2bMHY8eORUVFBezs7Ez4LhIRUWfjHBsiImrW+fPnUVNTg2HDhomPeXh4ICoqSvz+yJEjeOWVV3D8+HEUFRVBp9MBANLT0xETE9PoflNSUlBZWYnJkyfXe7ympgYDBw5s8zhjY2PF//f19QUA9OvXr8FjeXl58PPzw/Hjx5GYmIjvvvtO3EYQBOh0OqSmpqJ3795tHgMREZkPAxsiIuqQiooKTJ06FVOnTsV3330Hb29vpKenY+rUqaipqWnydeXl5QCA9evXIzAwsN5zKpWqzeNQKBTi/0skkiYfMwZd5eXleOihh/D444832FdISEibj09ERObFwIaIiJoVHh4OhUKBAwcOiBf8RUVFOHv2LMaOHYszZ86goKAAb7/9NoKDgwGgwSR9pVIJANBqteJjMTExUKlUSE9Px9ixYxs9dmOvM5VBgwYhKSkJERERJt83ERF1PTYPICKiZjk5OeG+++7Ds88+i23btuHkyZO4++67IZXqP0JCQkKgVCqxYsUKXLhwAX/88UeDNWZCQ0MhkUjw119/4fLlyygvL4ezszOeeeYZPPnkk/jqq69w/vx5HD16FCtWrMBXX33V5OtM5fnnn8e+ffuwcOFCJCQk4Ny5c/j999/ZPICIyEoxsCEioha9++67GD16NGbMmIFJkyZh1KhRGDx4MADA29sbX375JdauXYuYmBi8/fbbWLp0ab3XBwYG4tVXX8WiRYvg6+srBg+vv/46XnzxRSxZsgS9e/fGtGnTsH79evTo0aPZ15lCbGwsdu7cibNnz2L06NEYOHAgXnrpJQQEBJjsGERE1HXYFY2IiIiIiKweMzZERERERGT1GNgQEREREZHVY2BDRERERERWj4ENERERERFZPQY2RERERERk9RjYEBERERGR1WNgQ0REREREVo+BDRERERERWT0GNkREREREZPUY2BARERERkdVjYENERERERFaPgQ0REREREVm9/wf5AwKSZruQGQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp_resampled.plot(y=' temp', figsize=(10,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_mean = temp_resampled[' temp'].mean()\n",
    "temp_std = temp_resampled[' temp'].std()\n",
    "temp_min = temp_resampled[' temp'].min()\n",
    "temp_max = temp_resampled[' temp'].max()\n",
    "temp_q1g = temp_resampled[' temp'].quantile(0.25)\n",
    "temp_q3g = temp_resampled[' temp'].quantile(0.75)\n",
    "temp_skew = temp_resampled[' temp'].skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp_mean : 33.847951388888895\n",
      "temp_std : 2.170633179929283\n",
      "temp_min : 28.93\n",
      "temp_max : 36.61\n",
      "temp_q1g : 31.66\n",
      "temp_q3g : 35.832499999999996\n",
      "temp_skew : -0.46255126682033076\n"
     ]
    }
   ],
   "source": [
    "print(f'temp_mean : {temp_mean}')\n",
    "print(f'temp_std : {temp_std}')\n",
    "print(f'temp_min : {temp_min}')\n",
    "print(f'temp_max : {temp_max}')\n",
    "print(f'temp_q1g : {temp_q1g}')\n",
    "print(f'temp_q3g : {temp_q3g}')\n",
    "print(f'temp_skew : {temp_skew}')"
   ]
  }
 ],
 "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": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}