analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as sp\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import matplotlib.font_manager\n",
    "import matplotlib as mpl\n",
    "matplotlib.font_manager.findSystemFonts()\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "import warnings\n",
    "\n",
    "from cycler import cycler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adjust Plot Styles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adjust matplotlib's style using custom made style sheet\n",
    "plt.style.use('presentation.mplstyle')\n",
    "\n",
    "# highlight parts on graphs\n",
    "facecolor = \"whitesmoke\" \n",
    "\n",
    "# plt.rcParams['font.family'] = 'Impact'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data\n",
    "sales = pd.read_csv('data/business.retailsales.csv')\n",
    "sales2 = pd.read_csv('data/business.retailsales2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Product_Type</th>\n",
       "      <th>Net_Quantity</th>\n",
       "      <th>Gross_Sales</th>\n",
       "      <th>Discounts</th>\n",
       "      <th>Returns</th>\n",
       "      <th>Total_Net_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Art &amp; Sculpture</td>\n",
       "      <td>34</td>\n",
       "      <td>14935.0</td>\n",
       "      <td>-594.00</td>\n",
       "      <td>-1609.00</td>\n",
       "      <td>12732.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Basket</td>\n",
       "      <td>13</td>\n",
       "      <td>3744.0</td>\n",
       "      <td>-316.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3427.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Basket</td>\n",
       "      <td>12</td>\n",
       "      <td>3825.0</td>\n",
       "      <td>-201.60</td>\n",
       "      <td>-288.00</td>\n",
       "      <td>3335.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Basket</td>\n",
       "      <td>17</td>\n",
       "      <td>3035.0</td>\n",
       "      <td>-63.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2971.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Art &amp; Sculpture</td>\n",
       "      <td>47</td>\n",
       "      <td>2696.8</td>\n",
       "      <td>-44.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2652.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1770</th>\n",
       "      <td>Kitchen</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-2.81</td>\n",
       "      <td>-25.19</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1771</th>\n",
       "      <td>Jewelry</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-28.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1772</th>\n",
       "      <td>Basket</td>\n",
       "      <td>0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>-23.20</td>\n",
       "      <td>-92.80</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1773</th>\n",
       "      <td>Kitchen</td>\n",
       "      <td>0</td>\n",
       "      <td>16.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-16.50</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1774</th>\n",
       "      <td>Kitchen</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-106.25</td>\n",
       "      <td>-106.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1775 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Product_Type  Net_Quantity  Gross_Sales  Discounts  Returns  \\\n",
       "0     Art & Sculpture            34      14935.0    -594.00 -1609.00   \n",
       "1              Basket            13       3744.0    -316.80     0.00   \n",
       "2              Basket            12       3825.0    -201.60  -288.00   \n",
       "3              Basket            17       3035.0     -63.25     0.00   \n",
       "4     Art & Sculpture            47       2696.8     -44.16     0.00   \n",
       "...               ...           ...          ...        ...      ...   \n",
       "1770          Kitchen             0         28.0      -2.81   -25.19   \n",
       "1771          Jewelry             0         28.0       0.00   -28.00   \n",
       "1772           Basket             0        116.0     -23.20   -92.80   \n",
       "1773          Kitchen             0         16.5       0.00   -16.50   \n",
       "1774          Kitchen            -1          0.0       0.00  -106.25   \n",
       "\n",
       "      Total_Net_Sales  \n",
       "0            12732.00  \n",
       "1             3427.20  \n",
       "2             3335.40  \n",
       "3             2971.75  \n",
       "4             2652.64  \n",
       "...               ...  \n",
       "1770             0.00  \n",
       "1771             0.00  \n",
       "1772             0.00  \n",
       "1773             0.00  \n",
       "1774          -106.25  \n",
       "\n",
       "[1775 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View data from business.retails.csv\n",
    "# There are 1774 product entries with net quatity sold, gross sales, discounts and returns\n",
    "\n",
    "# rename the columns to exlude spaces\n",
    "sales.columns = sales.columns.str.replace(' ', '_')\n",
    "\n",
    "# rename the product type values to exclude spaces\n",
    "sales['Product_Type'] = sales['Product_Type'].str.strip()\n",
    "sales"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kG2geEwM4Nck+gxNNXwMAm9s+BHp6X+D9o1wtZjnr3KAXLtvf5Ruceic2V7V+ajPs/9K+vB3wOuDbSc5L8oEkj0uyV/+bLWcdmotXgB8vsi8/Gig/KdemackFTYWy0OfU0//7Y9vYrkbzLPJHgQvaE81XJLn9hOPVOrLCeqZLz6bpc+DjVfX0tqXM79G0ltydpu+hx7dlr9b+/NpK3rCqzq+qV1XVA6rqQJo7VXcC/gx4D02Lrl2AlyR5YN+q/RdUS6lfu9af1Nu7sygWt+zvIWlWVdXlVXVeVb2bpi78YLvohb1kUpIbphl19ZM0SfT7Ajenebxub0ZcRLWtPR9H06fLDYGX0DzmfEGSzyT5mywyWmaS44A/bV8+q6q+sEDx3jG8Mwsfw714PYalyet951+n7Ut3tWzt+301Eigvokm0Q9Of3SnAljSjAb4tydGrnLi5dCVlktycpr/ND9Jc992T5kbhjWgG4RqaRGwbmPw1TaLqEOAVNF0h/CLN6M1PSTKqxey6YZJqMo6kuTMMzXPCW4ZMvTv2V6M5EHt6B99SsuHLWad30v+/g3f5RkyH969cVY+nSTb9Pc1jM5fTNM/8bZrHNk7PwBDFy1lnTBn4OSn9dx7vO+bn9JHeCu2dx4OBP6apaM9tt3lzmhPAz2TI8KvSmFZSz3SibUn4pPblVY8nVuNJNI/iBTg+yYtp+h6AbXfXJqKqfllVn66q46vqd2k6B/1Vu/jYvqL9dcpq36GcpP5Hin41slT3VvQ9JM26tjX4G9qX+wK/3t6A+C/gbjT1zr/TdER8S5pHbDbQDNowaptvbJc/i6bz9Ito7vrfgabfmK8mud8CYT2dJnEP8KIkt1ygbO8YfumYx/BzF9iWpOU5o/25Abhtl4GsRFWdT/NI8FE0/W/2HhM+gOZm5juA96cZ0GGqJLkWTYuo36A573oNzcBeN6e5sbAzC3S9UVV/25Z9MU2i7lKaG6p3pelL9StJbrd6ezD9TFJNxlIfrekv3+tjZNTzqsOsZJ1fW25WuqpOq6onV9VtaUau+02au3aX0Ixqt8OIe0tcpxfjDVjY9dufK31GedBP2XaidpPlbKC9GD6hbcFxPZo7m79P81xygOck2TSRaLXerKSe6crN2dY6aocRV6rq5TStw35F03rgCTTJ7DcPlp2kqvoU20bbPLBvUX+fT0upX/sfJ+zCjfp+/+Ey1u9PyK3mPqz4e0iaA/193V2DptXUoe3rh1TVQ6rq36vqK1X103H6nKmq71XVi6rqHu02fx14Is0AEHsBJ7aPXg/zWZq6+ts0fc+8P8kBI8r2juFlnSNJmoj+0cIf0lkUE9D2mXdqVT2qqm5K0wLpPjSjAEPTsOEJXcW3gIfT3Di+ArhHVR1bVf9RVV+rql+M6ANrO1X1jar666q6E009fRjNzYaft9t+3eqFP/1MUq1Qm0n93fblwxe6o0QzKhzAXfr6Z+r1Y3SjJIcynuWs0+u8bR+au3UrUk2Hbp+tqqcDL21nL9hB5hjr9Drou92QRwGBqzr3vNtA+YmoqsvY1rfLMRPa5g+r6i3AETSj4YRmmHVpbBOoZ5ajd2G0ksc1+pMfQ1tNVtW/s20o4F1ohi//0bCyC0mye/s5javX4qj/gvHzbNvvey9hW70+9PbuKPlyRPvzEpp96DfO37G/D8BrTyqoISb6PSTNqP7H735A87gHNJ0gn7TSjbcXfd+sqn9i2wAz+/S9z6B7VdU3aVrrnkdzo/ADSYZ1Ztw7hu+V5JrLCG8S3yvSulZVP2Rbv5l/kmRkS8tBSSbdVcpEVdNdw/ur6mHAx9rZg9eX01CP9OrTL9UEBsWq5rHwL1bVi4Ant7NvscTz2rlikmrlfo+mX5WLgf9YpOxJNBdGYduJw4fZdmfqpaOeLU5y/SS/sYJ1PkRzMgTwioVOLtr17tD3+hGLVGqXDfxc1jo0Qx9fStNMfbBD455H0zQDhWakv0k7sf15t2GdmvZLclTf7wcm+b0Fivc/gnPZyFLScCutZ5ajl7y5zQq28Q2axAnAE5JcbUS5X7AtoXVTmj63Rt31H2Vf4GtJHrRYHw1JbkZzdw76Ps9qBkDodXT5jBEXaSTZLcnd+2ad1f7ckyEDOiS5OktLeo2t7XusV1++taoG+08Y5+/47b7fjxhc2H6eDxycvwzL/h6S5kH7CHSvVcAXq+q7bKsj91qgjhzaAjvJvZIsdGxfNuL3q1TVhe3PM4HfoemH5hDgP7Pj4C9voKmrrwH880JJ+SS3TzLYMn4S3yuS4Jk0x/QeNOdMC96UbPu9ew/b+jbtXJInZsQI8K1h14owHfVIr97eZ4F6cOijmEkemGSh1qi9/S2apwvWJZNUK9d7pOZdVfXLhQpWVX9P/3/YzruY5jEXgPsB705yuzSjBeye5LAkfwt8E7j1Cta5lObEqGiadZ+W5PfbzpZJco0kd0/ySpoLrv7nYB8AnJXklUnu0V5wkeTaSf6Apl8ZaC6Ol71ONUOM/m378llJXppkv3a96yZ5Gts6Y39dVX1poc97mV7DthZar0nyL+3nuaGdbpzkT5J8gWa45p5rAW9L8vkkf5zk19q/xy5t/w5vpXns6WLg3asQt+bbiuqZZerdGXpYkvsl2SvJxvaiaKy7V22svWP2UOCzSe6b5Drt8XFIkuez7Xn8+9E8xnsvlpeouj5NnXJGkuckuXOSveGqOu6WSV4IfIrmePwKcPzANp5Bc5F2I+ATSX43ydXaeG+c5C9okm+P6Fvnw2zrYPQfkxzcvud12mT311l5k/ybJ/mzNoZd2unuNAM03Jimefhzh6y36N+xqs6j+UwA/rL9Lti53e/70vx9XrbC+Ff6PSTNpPbcYf8kDwU+A9yKpsPc3nnQB9rXuwBvSnLTvuPv8CTvohkRdZibA59L8q72wud6aezR1g+9+vcrVbXogBRV9VngwTQtFe4AvD1Nn1m95V8B/rl9+XCaEVqPaN8v7bnaMW3Mn2HHlpkr/l6RBNUMcPAnNN+nv07Tz+8Lktwqya5JdmqPx/sleQ3Nd+pCfdN14bk014rPTnLrNDcAd0qyX5o+fO/RlhtsYToN9ch725/7Aa9sY06Sq7fnuR9n9HnTXWhuqr6xjf/a0NzQTPK7wHG991jsnH+uVZXTMieaZ/KrnX5nzHUe1LfOnfrmP5PmpKC37Mp2qr7poQPbWs46j6C5mOovc8XA6wKO7VvnbUOWD67zUeDqK1mnXW9nmkTRQuudAlxtyGd7Yrv8I2P8HXrbeuSQZdel6Xx0MP7Bz/aHfescOmT54OtLgAd3/X/rNFvThOuZpRwjt6VJHA0eBwVcawnx70rTEfBCx9MXgZu05Q9jW8uq/wJ2H/N99gHOHBHvsDru/cDGEds6si+GUdt49cA6T1ig/Pk0JzQF1JD3e2677Owhy05k+GfX//n9HLjLSv6OwO3Z/ruhf/tX0Fwk914fPvAeh/ctO3CMv9WSv4ecnKZ56juGe9/1velXQ/6vz6fpe6p//b9Z4Hi4gqbF5w7HGNsuUhc6lr4PHDrwfo8cVR+1y/+ob/3XDyzbmaY/0cH3vXxIPXXIwLoT+V5xcnJqJpo+7X40Rj1QNDfY7tKut2Ad0JYZ+d3OAuctQ7Zzdlv2uQPzfzxG3P8wZHuL1iM0/Y0OPWcZtn8LxD7ycwJev0Dsl9KMJr3DujQNMhbb768CN+j6/6vT/+2uA5jlCXhe+490HrDLmOvsTnOCUsCrBpb9Bk2C5gyaE/hL2t+PB247YnvLWecGwAto7nL9jKZZ4S+A02g6Nb/NQPldaB71eFO77YvadX5Cc6H3CGCnla4zsP69aZJRP6Y5ydvSrvdgICPWObH9XD8yxt+hVwk8csTy0Iw28e80levFbYXzXZqTxYezY4LtIJoTzY+18V7W7vdXae48HtT1/6zT7E2TrGeWcoy05W9Pk1z5eXsc/oDmrv8OSeIxtnV/4NS2DrisPbbf19YFGwbK3pltSYyxE1Xtur/ZfmYfaI/dX9J8+V9A06LpdcDdx9jOvjTDI3++/Sx/RXOxdxLNIzE7D1nnaJo7fBe18X8ZeCFwPRY+0XkuiyepPgs8BvgITefol9I8pvePwL6T+DvSJAhPoRlE4tL28/tXmlHGDoThJ3wsMUnVrrOk7yEnp2me2D5JNThdStNFwydozhGGHq80Nxc+TXO+8Sualg//QtPyqv/4O3Bgvd+iOcf4v/YYurz9+Rmam5nXHPJeI+ujvjLP6XvPvx2y/NbAq4CvARe2x/C5NCNePQXYb8R2J/a94uTkVND0zfQomvOTs9rj8dL2XOET7XfqnQfWGacOGPndzmSSVNcGHkeTzPk+zTVs79zjrYPnGgPrLliPsDZJql4/sKe3cV9Cc575MpoW7kO3T/Mk25E01+9faf9el9Oce32E5qbnbl3/X3U9pf2wJEnSlElyIk0i76NVdXi30UiSJEmryz6pJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmfH6ZIkSZIkSeqcLakkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1LkNXQfQc+SRR9b73//+rsOQtLh0HcA0sg6TZor12BDWY9LMsA4bwXpMmhkj67GpaUl13nnndR2CJC2bdZikWWc9JmnWWY9Js29qklSSJEmSJElav0xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdW5D1wEsx2GbN09sW6efcsrEtiVJ4zhs82brHklzoXdOZp0maZaMcz1pvSZ1w5ZUkuZWkmskeUWSN/XNu06SU5P8IMkvk3wqye36lh+epJJc3jf9opMdkCRJkqR1xCSVpLmU5P7Az4DHDyzaE/hf4E7AdYC3A6cm6a8Pf1BVG/qma61FzJIkSZK0npmkkjSXqurUqtoAPH9g/ner6oVVdU5VXQq8GtgXuF4XcUqSJEmSGiapJK13dwDOA87tm3eDJJcmOTfJ25Js7Cg2SZIkSVo3TFJJWreS7E3Tkuq5VXVFO/s0mpZVVwNuB+wG/OuI9Y9NclqS07Zs2bIWIUvSVZIc0Pax94s2qf7aJHu2y45OclaSS5J8JsktuojxsM2bJzrgjSRJmm8mqSStS0muCbwf+EBVHd+bX1W/rKpzq+rKqjqH5nHB+wzbRlWdUFWbqmrTxo02tpK05t4GfBm4PnAY8GvAC5LsD5wIPAHYCLwHODlJuglTkiRpPCapJK07SW4AfAz4aFU9YZHie9E8DihJ0+aWwAer6uKq+iFN4v3GwFHt/PdW1YXAcTQtRG/VXaiSJEmLM0klaV1JchDwSeANVfXUIcv/NMl9klw9yX7AC4E3r3WckjSGlwFvTfLHSQ4BHgS8HDgYOKdXqH2c+ax2viRJ0tQySSVpLrWJpvOApwLHJDkvyR8BdwYOBF6a5PK+6TntqhfRXPj9GPgU8Dng2Wu/B5K0qP8CfgTckaau+inwJWAP4OKBshfRtAzdjn3rSZKkabKh6wAkaTVU1fuAfUYsPnGB9U5caLkkTYMk16Lpa+q2VfWdJH9OU3e9hma00l0HVtmNJlG1nao6ATgBYNOmTbWKIUuSJC3KllSSJEmz5yBg56r6DkBVXQC8gabfqTOAm/UKJtkZOAQ4s4M4JUmSxmaSSpIkafZ8DbgkyfOS7JlkX+BYms7TTwUObx973ovmsedzgdM7i1aSJGkMJqkkSZJmTFVtBe4D3JWmD70vAN8AnlFV5wCPBo6n6adqM3BMVfk4n6SpkORJSb6aZGvbb+jrk+zZt/zoJGcluSTJZ5Lcost4Ja0d+6SSJEmaQVX1BeDuI5adBJy0thFJ0th+ADyY5vHkfYD30STX/1+S/Wn62HsI8HHgL4CTk9zMZLs0/2xJJUmSJElaM1V1UlV9FbgcuBbN4A5fbBcfBXywqt5bVRcCxwH70vS5J2nO2ZJKkiRJktSFrcDOwOOr6mPtvIOBc3oFquqKJGe187+44yYkzROTVJIkSZKkNVdVV0tyU+A/klzQPqq8B01fe/0uAvZa8wAlrTkf95MkSZIkdaKqzqTpg+rB7aytwK4DxXajSVTtIMmxSU5LctqWLVtWLU5Ja8OWVJIkSZqowzZv7joESbPl6sCl7e9nAPfuLUiyM3AIcOawFavqBOAEgE2bNtmxujTjbEklSZIkSVozSf49yW2T7J7kTsAfA29rF58KHJ7kPkn2Ap4KnAuc3k20ktaSLakkSZIkSWvpUuCdwHVpOkl/RlW9G6CqzknyaOB44IY0yaljqspWUtI6YJJKkiRJkrRmqurhiyw/CThpjcKRNEV83E+SJEmSJEmdM0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJEmSJKlzy05SJblGklckedPA/LOTXJHk8r7p6JWHKkmSJEmSpHm1rCRVkvsDPwMeP6LIvatqQ9/0zmVHKEmSJEmSpLm3rCRVVZ1aVRuA5084HkmamAVafB6d5KwklyT5TJJb9C3bJcm/JPlFkvOTvDrJLmsfvSRJkiStL6vVJ9V7k1yY5HNJfnuV3kOSRhrV4jPJ/sCJwBOAjcB7gJOTpC3yZOA2wC2AmwOHAU9Zk6AlaUYdtnkzh23e3HUYkiRpxq1GkuquwJ7A9YETaC7+9htWMMmxSU5LctqWLVtWIRRJ69UCLT6PAj5YVe+tqguB44B9gVu1yx8EvLCqvl9V3wdeCjx4reKWJEmSpPVq4kmqqvpuVV1WVb+sqtcA3wHuMqLsCVW1qao2bdy4cdKhSNIwBwPn9F5U1RXAWe38HZYDZ/QtkyRJkiStktV63K/fXsB5a/A+kjSOPYCLB+ZdRFNXDVt+EbBH3+OAV7E1qCRJkiRNzkSTVEluneTJSfZLcrUkTwU2AJ+Y5PtI0gpsBXYdmLcbTTJq2PLdgIurqgY3ZGtQSZIkSZqcDctZKcl9gDfStDjYKcmRwNOA/wHuCzyz3fZngSOrautkwpWkFTsDuHfvRZKdgUOAM/uW3wz4avv60L5lkqQF2Hm6JElaiWUlqarqfcA+IxYfsfxwJGnVnQoc1ybbP04zyt+5wOnt8pOBpyb5NFDAXwFv7yBOSZIkSVpXlpWkkqRpN6rFZ1W9NsmjgeOBG9Ikp47pe5zv5cCvAV+nSVKdRDPCnyRJkiRpFZmkkjSXFmrxWVUn0SSfhi37FfDYdpIkSZIkrZG1GN1PkiRJqyDJ3ZJ8OMkFSbYm2budf3SSs5JckuQzSW7RdaySJEmLMUklSZI0g5IcAbwe+HtgX+AA4MIk+wMn0vS5txF4D3ByknQUqiRJ0lhMUkmSJM2mlwGPqar/rKqtVbWlqi4HjgI+WFXvraoLgeNokli36jJYSZKkxZikkiRJmjFJbgDcEjg2yU+S/DTJq5PsChwMnNMrW1VXAGe18yVJkqaWSSpJkqTZcwBwEc1IpfvRtJK6JfASmlFNLx4ofxGw1+BGkhyb5LQkp23ZsmV1I5YkSVqESSpJkqTZU8ClVfXxqvpVVf0AeDlwP2ArsOtA+d1oElXbb6TqhKraVFWbNm7cuOpBS5IkLcQklSRJ0uw5C7hOkuv1zdsA/BQ4A7hZb2aSnYFDgDPXNEJJkqQlMkklSZI0Y6pqC/Be4FVJ9m5H9Psr4E3AqcDhSe6TZC/gqcC5wOldxStJkjQOk1SSJEmz6RE0fU99G/gk8A7glVV1DvBomv6qfgpsBo6pquooTkmSpLFs6DoASZIkLV1V/Qx42IhlJwEnrW1EkiRJK2NLKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJ0ppJ8swkX0+yNcnZSZ4ysPzoJGcluSTJZ5LcoqtYJa0tk1SS1p0kByS5fMh0drv87CRXDCw7uuOwJUmS5kUBjwauDfwu8JQk9wFIsj9wIvAEYCPwHuDkJOkmVElrySSVpHWnqs6pqg39E/B44Ky+YvceKPPOjsKVJEmaK1V1XFV9uqouqaovAx8DDmsXHwV8sKreW1UXAscB+wK36iZaSWvJJJWkdS/J7sBzgOd3HYskSdJ6kmRnYBPwtXbWwcA5veVVdQXNjcSD1z46SWvNJJUkwZ8BX6+qj/bNe2+SC5N8LslvdxWYJEnSnHsJcC7NY30AewAXD5S5CNhr2MpJjk1yWpLTtmzZsnpRSloTJqkkrWtJrgE8HXh23+y7AnsC1wdOoOkHYb8h63pSJEmStExJng7cH9jctpgC2ArsOlB0N5pE1Q6q6oSq2lRVmzZu3Lh6wUpaEyapJK13fwV8pqo+05tRVd+tqsuq6pdV9RrgO8BdBlf0pEiSJGnp0ngJ8DDgrlX1477FZwA36yu7M3AIcObaRimpCxu6DkCSupLkusBfAHdbpOhewHmrH5EkSdK68GaaztDvWlW/GFh2KnBcO9rfx2lG+TsXOH0tA5TUDZNUktazv6YZPeb/ejOS3Bq4B3ASTWLqCTR15Sc6iVCSJGn+PBS4AjgvSW/e2VV1UFWdk+TRwPHADWmSU8dUVXUSqaQ1tezH/ZJcI8krkrxpYP7RSc5KckmSzyS5xcrDlKTJSnIA8FiaUf36nQ/cl+aE6MfAPYEjq2rrmgYoSZI0p6oqVbVhYDqob/lJVfVrVbVbVd2hqr7UZbyS1s6yWlIluT/wTpok11v65u8PnAg8hKZp5l/QdDh8MzPfkqZJVZ1DM3rM4PxvA0esfUSSJEmStL4tqyVVVZ1aVRuA5w8sOorm0Zn3VtWFwHE0zxrfamVhSpIkSZIkaZ5NenS/g4Fzei/aYUTPaudLkiRJkiRJQ006SbUHcPHAvItoRsbaQZJjk5yW5LQtW7ZMOBRJkiRJkiTNikknqbYCuw7M240mUbWDqjqhqjZV1aaNGzdOOBRJkiRJkiTNikknqc4AbtZ7kWRn4BDgzAm/jyRJkiRJkubIpJNUpwKHJ7lPkr2ApwLn0gzlLkmSJEmSJA21YTkrJbkP8EaaPqh2SnIk8LSqem2SRwPHAzekSU4dU1U1oXglSZLUSrI78AFg56q6czvvaODv2HYu9piq+kpnQUrSDDps8+ZFy5x+yimrHoe03iwrSVVV7wP2GbHsJOCklQQlSZKkhbXdKryNpv/Py9t5+wMnAg8BPg78BXBykpt501CSJE27ST/uJ0mSpLXxauCbwKv65h0FfLCq3ltVFwLHAfsCt+ogPkmSpCUxSSVJkjRjkrwE2Kmqnjaw6GDgnN6LqroCOKudL0mSNNVMUkmSJM2Qtv/PQ4DHDlm8B3DxwLyLgL1GbOvYJKclOW3Lli2TDVSSJGmJTFJJkiTNlpsDRwIXJbkEeA1wp/b3nYBdB8rvRpOo2kFVnVBVm6pq08aNG1czZkmSpEWZpJIkSZohVfXkqtq9N9G0qPpU+/sXgJv1yradqx8CnNlNtJIkSeMzSSVJkjQ/TgUOT3KfJHsBTwXOBU7vNCpJkqQxmKSSpA4ctnlz1yFImkNVdQ7waOB44KfAZuCYqqou45IkSRrHhq4DkCRJ0vJV1YnAiX2vTwJO6ioeSZKk5bIllSRJkiRJkjpnkkqSJEmSJEmdM0klad1J8twkVya5vG96V7vs6CRnJbkkyWeS3KLreCVJkiRpPTBJJWm9ektVbeibjkqyP02/Lk8ANgLvAU5Oki4DlSRJkqT1wCSVJG1zFPDBqnpvVV0IHAfsC9yq27AkSZIkaf6ZpJK0Xj2kfaTvu0le3LaWOhg4p1egqq4AzmrnS5IkSZJWkUkqSevRK4FrA3sBm4GjgScCewAXD5S9qC23gyTHJjktyWlbtmxZtWAladYdtnkzh23e3HUYkiRpypmkkrTuVNW5VXVBVV1eVV8AXg3cB9gK7DpQfDeaRNWw7ZxQVZuqatPGjRuXHIcXbJIkSZK0jUkqSWpaSp0HnAHcrDczyc7AIcCZHcUlSZIkSevGhq4D6NokWzKcfsopE9uWpNWT5G+Bk4EvA78BPA44tn19XJL7AB+nGeXvXOD0biKVJEmSpPVj3SepJK1LuwHvAK4LnA08u6reA5Dk0cDxwA1pklPHVFV1E6YkSZIkrR8mqSStO1X1JOBJI5adBJy0thFJkiRJkuyTSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJay7JNZK8IsmbBuYfneSsJJck+UySW3QVo6S15eh+68RhmzdPdHunn3LKRLcnSZIkaf1Icn/gnTQNJ97SN39/4ETgIcDHgb8ATk5ys6qqDkKVtIZsSSVJkiRJWlNVdWpVbQCeP7DoKOCDVfXeqroQOA7YF7jVWscoae2ZpJIkSZIkTYuDgXN6L6rqCuCsdr6kOTfxJFWS5ya5MsnlfdO7Jv0+kiRJkqS5swdw8cC8i4C9hhVOcmyS05KctmXLllUPTtLqWq2WVG+pqg1901Gr9D6SJEmSpPmxFdh1YN5uNImqHVTVCVW1qao2bdy4cdWDk7S6fNxPkiRJkjQtzgBu1nuRZGfgEODMziKStGZWK0n1kHa40O8meXGSrNL7SJIkaY0dtnnzxEcOlqTWqcDhSe6TZC/gqcC5wOmdRiVpTaxGkuqVwLVpnhneDBwNPHEV3keSJGldSvLMJF9PsjXJ2UmeMrD86CRntTcNP5PkFl3FKknDtEmo82iSUMckOS/JH1XVOcCjgeOBn9JcUx5TVdVdtJLWyoZJb7Cqzu17+YUkrwbuA/zDYNkkxwLHAuy///6TDmXNTfqO4umnnDLR7UmSpLlRNBdx/wfcFPhgkq9W1fuS7A+cCDwE+DjwF8DJSW7mRZ6kaVFV7wP2GbHsJOCktY1I0jRYiz6p9gLOG7bATu4kSZKWrqqOq6pPV9UlVfVl4GPAYe3io4APVtV7q+pC4DhgX+BW3UQrSZI0noknqZL8bZJNSXZLcnvgccBbJv0+kiRJuqpT4U3A19pZBwPn9JZX1RXAWe18SZKkqTXxx/1ohgd9B3Bd4Gzg2VX1nlV4H0mSJMFLaDoV7p1v7QH8eKDMRTSt2yVJkqbWavRJ9STgSZPeriRJkraX5OnA/YG7ti2mALYCuw4U3Y0mUTW4/lz1DypJ02acfovti1jaZi36pJIkSdIEpfES4GE0Car+llNnADfrK7szcAhw5uB27B9UkiRNE5NUktadMYZuPzvJFUku75uO7ipeSRrizcDt2DFBBXAqcHg7vPteNMO7nwucvrYhSpIkLc1q9EklSdNu5NDtfWXuXVUf6iQ6SVrcQ4ErgPOS9OadXVUHVdU5SR4NHA/ckCY5dUxVVSeRSpIkjckklaR1p6qO63v55SS9odvfN3wNSZouVZVFlp8EnLRG4UiSJE2Ej/tJWteGDN3e894kFyb5XJLf7iA0SZIkSVpXTFJJWu8Gh24HuCuwJ3B94ATg5CT7Da6Y5NgkpyU5bcuWLWsSrCRJkiTNK5NUktatvqHbN/cN3U5VfbeqLquqX1bVa4DvAHcZXN9RsSRJkiRpcuyTStK6k6aX4b8F7sPwkbEG7QWct+qBSZIkSdI6ZpJK0nr0ZmBfmgTVL/oXJLk1cA+aDofPA55AU1d+Yo1jlCRJkqR1xSSVpPVo5NDtwPnAfYFn0tSRnwWOrKqtXQQqSfPssM2br/r99FNO6SwOSZI0HUxSSVp3Fhq6vaq+DRyxhuFIkiRJkrDjdEmSJE2BwzZv3q5llSRJWn9sSSVJkiRJ0hKZWJcmz5ZUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkdchm4pIkSZLUMEklSVPAZJUkSZKk9c4klSRJkiRJkjpnkkqSJElr4rDNm1fccnQS25AkSdPJJJUkSZIkSZI6t6HrACRpvbNFgCRJ0vo1zrng6aecsupxSNPAllSSNCVMVkmSj/NJkrSemaSSpCnihZkkSZKk9crH/SRJkrSmTMhLkqRhbEklSZIkSZKkztmSaop5l1ELmeT/hx0xTpfDNm/2byJJrd73nfWiJEnzz5ZUkiRJ0jLYybskSZNlkkqSJEmSJEmd83E/SZpSPvYnaT0bbKE06vW49eSwFk+9dUdta3C+jx5KkrS6ViVJleSGwOuAuwI/A46rqlesxntJ0mqY9nrMBJakhUx7HSZJi7Ee295aPlo8iXPMceKdtnPZWYx5razlZ7NaLaleC3wb+D3gEOC9ST5fVZ9epfeTpEnrtB6zjxNJK7RuzsUG68vBVk/L2daoFlWjXq9k25JGWjf1mKRtJp6kSnJN4Ahgn6o6H/hskrcADwasUCRNvWmsx/oviEZd4Ni6ShJMZx22lpaSQBpVdrk3CiaRiBr30cNR6y3n/Ucl+pazjdX6HlrJ/k3Te416hHQ13muWrfd6TFrPVqPj9IOAC9vKpOcM4OBVeC9JWg1TVY8tdhHVP7rUUu72j3sRZqsuTTv/R3cwVXWYJC2D9Zi0Tq3G4357ABcPzLsI2GuwYJJjgWPbl79M8s1ViGct7QOc13UQKzTWPiRZg1CWbd38HSZliX/P91fVkasVy5QYqx5bQR029t932N+mf95iy0eVGWcZfXF6zE+EcU7WdnFaj21nLc7FZuX/ZNKG7vcE691Fy42z/krr7BHrT8054lp+JyVZlf/1cb6/FzDvdRisfj02T3XYxPdlrY6xgfeZib/JmJ/NTOzLmFZ03bKAkfXYaiSptgK7DszbjaZS2U5VnQCcsAoxdCLJaVW1qes4VsJ9mA7zsA8zbqx6bLl12Kz8fY1zsoxzsmYlzo6s+rnYev381+t+w/rd9/W631NgVeuxefq7zsu+zMt+gPuyUqvxuN+3gL2TbOybdyhw5iq8lyStBusxSbPMOkzSrLMek9apiSep2ueGPww8P8k1k2wCHga8fdLvJUmrwXpM0iyzDpM066zHpPVrNVpSATwGuCnwE+BU4HlV9YlVeq9pMg+PLroP02Ee9mHWrWY9Nit/X+OcLOOcrFmJsyurfS62Xj//9brfsH73fb3u9zTwXGw887Iv87If4L6sSKpqrd9TkiRJkiRJ2s5qtaSSJEmSJEmSxmaSSpIkSZIkSZ0zSSVJkiRJkqTObeg6AEmaZ0nuADwYOBjYC7iIZvjkt1fVp7qMTZLGYT0maZZZh0mzxY7T16kkOwNPYVuFvQdwMU2FfRLwd1V1eXcRLm7W92HW49fikvwp8DzgLcAZNCdFuwGHAg8FnltVx3cX4TZJ9gM2s+MJ3ClVdU6Hoc0kP0/Ni1mqxzQ567UOW6/7Pc+sw6TxTUsdaJJqGeYhuZDkX4BbAy9l+wr75jT79sWq+pPuIlzcrO/DrMevxSX5HvDAqvrfIcs20VT4N1r7yHaI5YHA64GPsOMJ3N2AR1fVOzoLsM+0fHkuZJY+z54k1wQOYttn+q2q+kWnQQ0xK3HOk1mpx1bLLNQ5kzaLddgkrNf9nnfzVIfNwzVov3mqX+dhX6apDjRJtQzzkFxI8nPg5lX1wyHLbgB8tar2XvvIxjfr+zDr8WtxSbYC16uqC4csuwbwk6q62tpHtkMsZwJ/XlXvG7Ls3sDxVXXQ2ke2QyxT8+W5kFn5POGquuZ1wBHA+Wz7TK8D/A/NZ/r97iJszEqc82hW6rHVMCt1zqTNUh02Set1v+fdPNVh83AN2jNP9eu87Ms01YEmqZZhHpIL7T4cWlU/GrLsBsDXq+qaax/Z+GZ9H2Y9fi0uyfuBbwFPr6pf9s2/DvAC4KZVda+u4uuL52Jgn6q6aMiyPYHzpuEEbpq+PBcyK58nXPU/+m3gOVV1Xt/8jcBzaf5Hf7uj8K4yK3HOo1mpx1bDrNQ5kzZLddgkrdf9nnfzVIfNwzVozzzVr/OyL9NUBzq63/ItlN2bhc/1bcA7k9wvyS2S3CTJzZIcDbwT+PeO4xvHrO/DrMevxT0auAnwsyTnJflekp8APwJuDDyq0+i2+T/gzwdnJgnwF8CX1jyi4W4EfGzEsk8AN1zDWBYyK58nwF1oTtzP659ZVVuAZwB37iSqHc1KnPNoVuqx1TArdc6kzVIdNknrdb/n3bzVYbN+DdozT/XrvOzL1NSBtqRahrap5WHAC4FzaJ4F3hW4GfBU4EtVdWxnAY4hyQaaZqHHsO2Z5q00TRRPBl5eVZd1F+HiZn0fZj1+ja9tTn4Q2/7G36qqC7qNapskh9L8z10H+B7b6rSbAj8GHlRVX+0uwkaSTwHvrqrjBuaHJlFxVFXdoZPgto9nJj5PuKqvjgdU1WlDlt2Opi+Fzk+uZiXOeTbt9dhqmJU6Z9JmqQ6bpPW63+vFPNRh83AN2jNP9eu87Ms01YEmqZbB5IKkeZTkljRfRFfVaVX1lW6j2maavjzHMe2fJ0CSx9OMenQiO57wPgz4m5qCUY9mJU7Nl1mrcyZtFuqw1bBe91vTb56uQeepfp2nfYHpqANNUq1z7T9h/ygEZ1TVTDVnnvV9mPX4pbU2DV+e8yTJbzL8hPcdVfXpLmPrNytxav5Y50jS6pin+nWe9qVrJqlWYJaTC0luTpPx3Rc4i22jEBwC/AQ4ZtoPqlnfh1mPX/Mjczakcdf8PCXNsvVah63X/dbsmeVrUE2vaaoDTVItwzwkF9pnZ/8TOK6qruybvxPwNOD+VXXHruIbx6zvw6zHr/mRGRnSeJq+PBcyK59nT5L9gM1sf8J7Jk0/T+d0GNp2ZiVOzY9ZqXMmbdbqsElZr/ut2TEP16A981S/zsu+TFMdaJJqGeYhuZBkK7BxGoaYXK5Z34dZj1/zIzMypPE0fXkuZFY+T4AkDwReD3yE7T/TQ4G7AY+uqnd0FmBrVuLUfJmVOmfSZqkOm6T1ut+aHfNwDdozT/XrvOzLNNWBJqmWYR6SC0m+BfxpVX1gyLJ7A6+sqpusfWTjm/V9mPX4NT/aL6VDq+pHQ5bdAPh6VV1z7SPbIZap+fJcyKx8ngBJzgT+vKreN2TZvYHjq+qgtY9sh1hmIk7Nl1mpcyZtluqwSVqv+63ZMQ/XoD3zVL/Oy75MUx24YS3eZA79ELgzsENyoZ2/wz/oFHoqcFKS/2L7kZKuuivdYWzjmvV9mPX4NT/eBrwzyaghjf+9w9gGLXRnZac1i2Jhs/R53gj42IhlnwBuuIaxLGRW4tT8mYU6Z9JmqQ6bpPW635od83AN2m+e6td52JepqQNtSbUMSY6meexgZHKhqk7uLsLxtP17HMWOIyWdWlXf7TK2cSXZH7g/M7oPQ+IP8H/MSPyaD7MypHHbnPowYNSX55eq6tjOAmzNyucJVz068O6qOm5gfoBnAEdV1R06CW77eGYiTs2XWalzJm2W6rBJWq/7rdkxL9egMF/167zsyzTVgSaplmkeEjyaPkm2VtUeXcchTaNp+vKcF0kOpfnsrgN8j20nVjcFfgw8qKq+2l2EjVmJU/PFOkfStBlyDXoRTZ307lm6Bp2n+nWe9mVamKRaBUkeVVWv7zqOxbT9eBwGfBX4z+r7Z0hyRlUd3FVs40hyNZpH4k6vqk8mOYZmVIVLgbdW1Xs7DXARSYY9uvJbwCd7L6rqrmsXkdarJJur6pS+1zcE7gJsAT5ZVZd0FdssmsXPsx3O+qb0nVhN4whBSW7BwAngNMYpzYP1Osz9et1vTb8k/1FVD+h7/UTgPjTnF28e1m+jtFTTUAeapFoFSc6tqut2HcdCkjyZJuP7MWATzbClm6vq3Hb5ZVW1S4chLirJa4Hb0NxNfznwJOBE4OrAHwNPq6p/6yzARST5KLAL8OrerPb3q5qDVtUbOghN60ySX1XVru3v96K56/Mdmi+nnYEjq+qbHYa4nWn48lzIrH2ekhY27XXOpM3TMPdLsV73W7Nj4PzihcDRwAk0ddPjgL+uqhO7i3Dp5qF+ncWbk8NMUx1okmoZkiyW+Dhm2h/ZSvJtmmFKv9IOW/pS4HeAu1TVlv5KcFolORe4JXBtmn6cbl5VZ7XL7gT8a1Ud2mGIC0qyG00Hdd+oqme083zcT2uuPymd5LPAa6rqX9vXTwXuUVVHdhljG8vUfHkuZFY+T4AkO9PcsHgw21ooXQycCZwE/F1VXd5dhI0kP6uqa7e/Xwf4V5q7x+cBbwKeU1W/6jBEzaFZqXMmLXM0zP1SrNf91uwYOL84m6aBwent69sDr6+qm3cX4fjmqX6dl5uT01QHmqRahiSvAP4EeMGIIn9VVXutYUhLluQiYO/+k/okTwceAtwV+OkMtKS6CLh6VV05mNxpE0A/q6o9u4twce1B32tJdSxwkUkqrbWBL9fzgetX1db29e7Aj6Zh6Nxp+vJcyKx8nnBVZ5+3prlRcQbbThJvTpO8+mJV/Ul3ETYGTszfShPj82lazr4A+GxVPa3DEDWHZqXOmbTM0TD3S7Fe91uzY+D8YiuwV69uSrIr8PNpv/bpmaf6dZZuTi5kmupAk1TLkOQaLJDESbKlqjaucVhLkuRrwKOq6rMD818C3Ba46wy0pPoKTWe5Xx+y7DbAO6rqxmsf2dIl+VuaOwf3NkmltZbkcuBeNEPk/iewZ1Vd0S67EfB/01CnTdOX50Jm5fMESPJzmlaoOwxbneQGwFenIaE2cGL+Y+B2VfW99vV+wCeq6oAuY9T8mZU6Z9KSfAv406raYZj7tj/TV1bVTdY+stW1XvdbsyPJFcCbaboI+T3g2lX1y3bZbWmufQ7sLsLxzVP9Oks3JxcyTXXghrV4k3lTVRekGQJ0lD9cs2CW743A4cB2SaqqelqStzAb/xv/SnO3f4ckFc1wn8M6Jp9KVfX0JI+iae4qrbXvA69rf/8RcP12HjSPgX2xi6CG+CFwZ2CHL892/g6Jlo7MyufZs9Ddqp3WLIrxXbOXoGr9nOaxb2nSZqXOmbSnAiclGTnMfYexrab1ut+aHc/v+/1FwO7AL9vXxwDvXPOIlm+e6tedktyd5pxpN5pBvHr2ATrvNmFMU1MH2pJKkjRSksOA86vqO1MQy9HA64GRX55VdXJ3ES5umj5PuOpxv8OAF7L9Z3ozmpOVL1XVsSM3sEaSXEmT6AtN0m/fqjqvXXYk8LKqukWHIWoOzUOds1zZcZj73nDqp9YMDXO/VEn2B+7POttvaa3NU/3a9g/Wn1S5S1V9v132l8B9q+qeXcS2VNNS95ukkiTNjCFfnhfRfHm+e1ouINqBKc4CnldVn+g6noUk2UDT99Qx7HhCcjLw8qq6rLsIG0nuNjDrc31N6R9P05+fo6Fq4qblhF2S5s16qF+n7ebkrDBJJUnqPWt+GPA14D3V9+WQ5IyqOrir2Pri+I+qekDf6yfSjPC2BXhzVb2vq9j6JbkMeDzwHJrP81lV9bluo5I0aUkeVVWv7zqO1dD3nfBV4D+n8Tth0pJcjeZxltOr6pNJjqF5RPtS4K1V9d5OA5TWkXmqX2dpX6al7jdJJUnrXJIn07Sm+RiwiWbo36Oqaku7/KpRS7o00DHlC4GjgRNohvh9HPDXVXVidxE2enG2o4w+gWaUmk/TJKu+1G10wyW5Jc2dzL1oW6dNY6xJrgecWwMnL0meVVUv7CgsrVNJzq2q63Ydx6SN+E7YXFXntsun4jth0pK8FrgNzSNHLweeBJxIM4roHwNPq6p/6yxAaR2Zp/p1VvZlmup+k1SStM61j6fdv6q+0g79+1Lgd2ieqd/Snxzq0sAQv2fTfHGe3r6+PfD6qrp5dxE2Bj+vJFen6d/pz2n6Xnh2VX2jq/j6Jbk5zWN9+9I8ongRTaefh9CcnBxTVV/pLsJGkk3AqTRxbgH+pqpe1bd8Kv5HNV+SLJaQOGYeR+Sdle+ESUtyLnBLmoEY/o9m5NOz2mV3Av61qg7tMERpbsxT/Tov+zJNdf8sjOAmSVpd16PpA4CquhJ4SpLzgA8muStNZ9XToP+uynWB/pY+pwMHrmUw46qqC4FnJ/ln4FnAaTQtlqbBa4A3Ace1f3sA2pOTp7XL79hRbP3+keZk6dXAbwKvSvLrVfXEdvm0/I9qvlwA/AnwghHLrxwxf9bNynfCpO0JbKmqnyS5spegan0eOKCjuKR5NE/167zsy9TU/bakkqR1LsnXgEdV1WcH5r8EuC1w12m4a57kCuDNNF+Svwdcu6p+2S67LfCOqjqwuwgbizWHTrL/tHQImmQrsLGqLhqybE/gvKq62tpHtkMsFwDX6XXinmRv4H3A/1TVM+b18SN1K8k1gJ+O+t9KsqWqNq5xWKtuVr4TJi3JV4AHVdXXhyy7Dc13zI3XPjJp/sxT/Tov+zJNdf9Oa/EmkqSp9kbg8MGZVfU04Fymp9Xt82keSfsW8CJg975lxwDv7CKoIW6y0MJpSVC1fgjcecSyO7fLp8EFNHf4AKiqnwP3Bu7TdqDvHTdNXFVdQNP33Sh/uFaxrLFZ+U6YtH8FRj0y/lSaflokTcA81a9ztC9TU/fbkkqSpHUqydHA62n6yjoHuJim0+BDgbsBj66qk7uLsJHkXcBnq+rFA/NvAHwCOKCqdu4kOEmSJE2MSSpJktaxJPsBR9GM7rcHsJWmT4JTp6XVV5JrA3tW1feGLLsJcOeqesPaRyZJkqRJMkklSZKGSvKoqnp913EsZlbilCRJ0sJMUkmSpKGSnFtV1+06jsXMSpySJEla2Lx2fChJkhaR5N8WKbLXmgSyiFmJU5IkSSvj6H6SJC1TkucmqSRndx3LMl0APIxm1MRh05UASXZP8jdJvprk4iSXJvlxkmOnKU5JkjRakj9M8skkFyS5PMnPk7y267imQZKPtOd0J3Ydy3pnkmpO9F0ojTs9t8NYz+46BmkWLeM4P3CF73dib1sT2oXB7S91f/qns1cjplmVZKck90/y6iRfSnJuksvak9AzkvxHkj9P8msDqz4TKOBRwHOBu1fV83oTcHGSXYAPtssPBXanaYl9PeAG7fv3/i6PXKVdfCZQ/bENxrlK76t1Yq3r17XWF/eJCyx75NpHJqlfktsmeUmSTyX5YZJLkmxN8r0k/5XkeUluP2LdBc/bkvwt8G/AnYCrAwGuBdykXT6xJE3f9d7g9Kskv0jytSQnJLnVSt9rliV55Gqea88qH/ebT5eOUebyVY9C0moa5zhf6RfeZWO+z3JdvsD2d+src8WQ5asZ10xJclfgBOCQgUVX0JyEXh24KbAZ+Mck/w38UVWdU1UXJDkaeBnNZ/qrgW38IU0Lpju32/tj4GSalk03AHZejX0a1BfnKH+4FnFo3ViL+nWt9fbpsk6jkDRUmpF2/xX47YFFl9OcE92one4FPCfJ14E/r6oP9ZUded6W5MbAX7UvjwdeDPwI2JvmptNquYLtrzt3Aa7ZTjcDHpXkkVX15lWMQTPGllTz55yq2n2M6YVdBypp2cY9zs9ZyZtU1WN725pU4APbf+Go2PuKPXZEmcGEzLqU5LHAf9MkqH4CPA24ObB7VW2gSVDdHvgb4Cs0d02PAG7c20ZVvbuqDmk/1+1Ojqvq/Ww7YT6lql5bVedX4wdV9d1V3sX+WN69wLL3r1UcmntrUr+utb64H9t1LJK2l+R2wOk037eXAv9Mc3Po6lW1C02S6mbAnwK9pNTN2jJXWeS87Z401/4/Af6iqn7Yfpf/rKq+vgq71TN4rrczcB3ggcAPaBrNHJ/kaqsYg2aMLakkSZpBSe4F/AtNa6YPA8dU1S/6y1TVL4HPAZ9L8gLgocDfLfGt9m1/nrGigCVJ0naS3AA4Fbg28F3gflX1lf4yVfUr4Bvt9Mokd6BJZC1F77v821U1rIX6mqmqnwHvTLIP8GqaVlWHAp/vMi5ND1tSiST3TvKGJP+b5LtpOsW9OMk5bT8mCz1iQZL7JHlnkh+0zxlfmOTLSV6T5HeS7NSWe2T7vO0B7ap/M+Q55cOHbP/IJO9on8v+VZKfJflYkse1faUMlj+wf3tJrpvkRe2zz5e2z3Y/eOWfnDT9kuyb5O+TfDjJN9t+AC5L8tO2v4NnJbnWiHVHdgre1+/BR9rX90vy7na7VyQ5fZX3a7tn+JPcMslr2z4bLk/TF9ON2mV/08b2lWzfV9OXkvy/JDdd5L12TfIXST6X5KJ2Hz+fpl+9G40R637t3+BrSX6Zpm+JbyT5pyT7L3P/dwb+H02C6pvA5sEE1aD2julbgFvQtKrq394O/VC09WcB92hnPWOgvj6x9z/St6nXD6nXD+zb5i5J/iTJ/7Sf42Vtnf7pNH1w3HY5n4fUhcF6aESZw4cdC8PWX6Qeu+oYTbJbkmPb4+jn7XnN15I8c9h5Ubv+Dv2BLuX4XWg/+ra33fnXQp9Dkhu3deBZbT1wUZI7Dqwz8bpTmkLPp0kgXQL8zmCCapiq+ixNv1LbjXybEedt7XH+/PblHQeO8bP7vu/v1pZ5xJC64JEr2svhzu37fYe+JbNG16jjSnL39v0ryZsG12/Pcf64rZvPa9/zR0neleTIIds7G3h93+vBz/wjA+UPaOvEr7R14qXt98W7kzwhyXWWsj/TzJZUAngQ8PC+11fSJDD3b6fNSd5YVf1lSBKaflAeM7DuXjQXQbdolx0DvIPmmeRL2dbXzOAzyr31e9vfDXgdTX8oPUXz7PRd2umhSY6sqq0j9u3hNM1Jr9H3njsDe4woL82bg4AnDcy7kuaO3R3b6dgkd1nm4ysbk/wXTR8JvW3vRNMR55pI8s80TeB3Yls/MVdn23fcs9m+76Qr2+W3bKfHJnlAVb1vyLb3Bd4HHNY3e3fgNu20WGwPAt4A9JqxF80jd4e00yOS/E5VfWLRHd3efdnWB9Uz2hZTY6mqn49Z9EqaOntXmpivZPv+bC5jW79iC/Uh1rsA3xv4AHC7gffYG/jNdnpqkn2q6qfj7o80D8aox3puAXyVtqNjttW5NwNeRFMvHTPm2459/E7YU4FH973vlTTnZb3Xq1l3SlMjybWBR7QvT6iqL4+7btsa6ttjFr+Upi7Zue91/7LFvu9heP+gK9VLTJ9Bc8Nt0Fpdoy4qTeu1U2nOAU8CHlFV/detNwLezfbni0WTgLw/cP8kL6+qp/Qtv5Sm3t3Q97rfVf2EJrl3G+uefduGbX2V/Q7N46K/O87+TDtbUgngezQd6N2Ppp+S3Wg6tTuU5gAH+MMkvzOw3u/THOBX0vR3ciOag+waNH2evBL4JU1lR1W9sX1GunchPKw/mo/1bf+VNAmqH7Tv09v+9dvXW2gSVS9dYN8eRdN09kE0z3VvADbSVCLSenAJzZfqsTRfyr2Lno3AI4ELgf2Aly9z+4cChwP/SHORtAvNSc4Ryw95yZ4A/CdN3wy9keduTNMhKMDHgWfQ9M20se0PYS/gSOBrNHXe6zLQAiFNa6WTaU44fg78EU3ybRea+ujhNH1IDNW2JHgrzefxSprP/2o0f4PfAj5K08T95CR7Dt/KSL07cufT/H0nrqo+1tbZvXr5jQP19WN7/Yr1rTasD7Fenf93NAmqnwN/QPNZ9kYJPAY4heb7JKuxP9KUW6we67ktsA/wHODX2nI3AE5slz8wyT3HecMlHr+T9Diax5CPpElO9fbh87Dqdac0TY5gW4Li3xYquBLtcd7rj3iw371Dxvi+372q3jiJWNI4MMmzgSfSnBM8bMQjiGtyjTpGzLeiuWG5F/BO4Pf7402yB9tuaP4vcB+aenoXmnr6xTRJvicnueomQtu/6mP7Xg9+5r/dbv8awFtoElT/Q3M+u3v7eRwKPJnmUdD5OX+qKqc5mGiGBq92umSM6VlL2PaH2u2+dmD+O9v5719g3X2BmwzMO7td77kLrHfHtswW4MYjyhzZt7979c0/sO+zeBWwoeu/j5PTJKYlHOefXcI2/6Bve7uMeL+zh6x3YrvsJ8BtV2Ffe/v5yBHLH9lX5g9X8D4H0Jw4FHCXgWUPa+dfDtxxkb/J2QPzA3y9XfZnI9bdg+YuaNFcHC4l7o+36314Qp/3R9rtnbiUZeP+vdoyP2vLPH2BMrcBrjbp/ycnp8Wm5dSv/fXQAts9vG+7Bw4sG7se6zsOTweuP2T5LjTnTAX885DlZzPi3GvM43fkfvSVObCvzOELrP8sICO2sap1p5PTNE3AC9r/40uBnSewvaHnJIst6yuz6Pf9EmLp1TmXD9ShvXOuomkp9KBR9cEY7zHpa9Qd9h84mOZct4B3MXCu3JZ5Rrv8k8BuI97vb3tlBuZf9T2wQKz37/vM9h1RZifgN7v+n57UZEuq+bTbGNNSHvX8bPtzvxHLr902q9xBVf24qs5awnv19LLKr6+q74wo81/AVpr9ud2IMm+rqsFHCqV5sNgxPq7e8b0bTeuqpfp6VXXa0WWt4O5eNa0Efty+HKzj/qj9+a6q+vQSN30X4NdpTmxeOeK9t9LUYzAwQs8Yev0OnLtgqek0ss+EqvpCVe3QL4W0xiZVv45tCfXY6VU12LqKqrqMbS07bzK4fMq8qdqrqiFWu+6Upknv+/Bn1XFn5qtoZ7avP/vzD7vQPDr3xSQHLWPbq3qNmuQAmkTYdWlaSj2orWsH9a5bX1RVg4/s9ZzS/rx9kl0Xet9FDD2Hqqorq+ozK9juVLFPqvlzTlUduNSVkuxF8wzrPWiaDe5D06x6r3aCptl1vw8BD6BJEP1XktcCH6uqHy4v9O3cpf35pCR/vkC53snivguUkebNko/zJHeieV79N2haD12dbcd4z0q+NKdae/JzNE19dVOaJt+9/e897rJrX/mdaDolhW0XQ0vRq8OuC2wdcY4E276Hl1uH7TxqQZJfsG3fBv12bf949Vr4EM0d0ye1/VOdBHymqi5Y4zikhSzrPGpK/Lz9Ocv9bq5V3SlNk4W+y0+l6WtomBdW1QtHLJsWz6uq5/ZetEmj3WgewfttmpaVtwQ+leRWVfXj/pW7ukZt+yT9EE0C7IPA0dWMsjhY7gY0jyIC/EdGD6TRq8w20CSadrjZsIBPAxfRPO73gbYPww8AX5nX5KZJKtGOjPAvNCcEg3pNC4edJbyGpnI5CrhnO5HkRzR9DbwDeOuIjPNibtD+3MB4/6ercmdTmnVJbgi8mW0jtgya65aGbT9T/4/mLtew1sOjvtyvzbYEz3L6ZOnVYb2TscUstQ7bQtMH2EIXaL3+CobpoiX1k4Fb0XR6/EftVEm+BXwCeEtVfaiDuKR50RtEZpb7JVntulOaJlvan3sn2XVYEoQmATPq/3zmruXbVpSXAN8CvpXkAzSDQWwE/pJmYAWg02vUa9Mkpg6iGXXw96vqkhFlb9j3+7g3e5dUb1XVliSPo9mvGwIvaaetSb5M08rr9VX13aVsd5r5uN86l+QuNHezr0vz2MiLaEbpOoimo/GdaJ6X3kFVXVZVm2ky2/9CU8FcSdOx+f1pRmX5dDtyxVL17ig8vqoyxnTiMt5DmmtJNtC0ArobzRf5vwMPobljtQ/Nyc1NOwtwbRwP/DHN992ngD+h6XDy+jT9BmxgeBKq/0RjOYm8Xh32v2PWYYcvcftfb3/edrDD955qOt286j3YdqevE1X1PZok1e8Db6PpEDU0/4OPAj6Y5HXdRShpCqx23SlNk953+QZGdF1SVUcO/t+zvJtnU6l95O7j7cu79+Z3fI36uzQDNlxBM2jDG0eda7F9K7hDx6y3zl7gIxmqfST8pjQtz/6HpmXVHsAdaPob+2qS+y11u9PKJJWeRHNwfRe4eVU9q6o+VFVn1ZhDmlfV/1TV46uqN3LY4TQVwpU0o9A8bxlx9fpZmfZ+FaRpdl+aptEAD6mqh1TVv1fVV6rqp/PaRLinPfl4VPvyX6rqt6rq1VX1ubYvgmF3LHt+0ff7Pst4+14d9muj+kNYod4jiHsAD16F7a+KqvpVVb2lqh5aVfvT3Dk9Gnh/W+RRSR7YXYTSklz1WEc7Gug863+EZTX3dbXrTmmafIjmegmaDrTXq16Lsmv0zev6GvWZNDfVCrg3zSjQw+qk/r5BV/W6taq+V1Uvqqp70HxWv04zQuIPaB59PDHJqG4eZopJKh3S/nxHVZ230o1V1daq+mhVPR54Uzt7sFPLXquEhZo69jrC27wOTvyk1dI7vn9eVSd1Gkk3bsK2pvCvWsqKbce8vUEbbr2M9+7VYfsw+lHLlfhPtt1JfeEyW6xOUi/hudQm7OdV1X/QDC/d+7ztCFmzor+T/66PwZUY5/hdq31d7bpTmhrttVfv/OwRSe7QZTyMd422GvZvf36/b14X16g976yq46rq32m6KoBmNOyXDin7HbYlqo5ZRmhXtdZPMvbnXk1H6d+sqn8C/rCdvQ/bPreZZpJKvedrhz3rS5uNvfmIZY9Lco1hy1qXDfzs6WXLb7PAuie2P29C04RxpCRHLuWgltaR3vG9V5KrjSizaa2C6UB//wGj6rheJ+rDvK/9+fvDPr923q1GrPshmjtbAK9Ics1RQSa5/lJPTKsZPeYp7csDgfcmuf5StjFhC9brSfZM8vi2Q/odVNWVbLtQXk4/hlIX+keGOmJwYTuC0/3XLpxlG+e87Nt9vw/b152ASbSCXNW6U5pCfw1cQDPS3buS3LHDWMapCyYqyd2A3j6/u29RF9eoPRf2fqmqfwBe3r58SpK/7C/Y9rH1b+3LP0hy71FvmmSnJL87MHtL3++jzqHulWShv8llI36fWSap9N7250PaA3pvgCTXS/Jo4BuMzgr/MfCdJC9Jcqcke6RxvSRPYFtWd7AFxyfbn0ckeUSSaya5VpK7JNkHoKr+E3hXW+5ZSU5Kcscku7UH+A2TPDzJR2guJEc9JyytZx+gadK8C/CmJDdNsnOSqyU5PMm7gLd3G+Kq+ipNM3GAf2zrqd2SbEhyyyR/35bZe8T6/wRcStNJ5buSHNrWcddK8vvtug8YtmKbRHoCTTPxmwOnJfn9Xh2X5BpJ7p7klTQXukP7olhIVZ0MPLt9eQfg60lenOT2SfZs3+eaSQ5J8ns0nWyull69/rAk90uyV5KN7YnVbjT/g8e3Mf5l+1nu0v4/3rT9HA6i+bxOXsU4pUk6naZvNYAXJLlNW0dcI8mDgS/RPLIy7RY7fnstPj7VlvvLtv7qfZ/cl2b0qZetNJC1qDulaVJV36ZJ8F4CXA/4eJJ/S3LvJHu3dcrVktw4zY35l7flVkOvLjg4yVOTXCfJ1ZPcLskBk3qT9sbVbyT5G5pr0Z2AM4BX9xXr4hp1lL8C3tr+/rL2HLDfcTQtqnYG3t2ei/16e826a/v7k4FvAn8zsO7ngF73E8e150RXS/JrSX6rnX9z4HNJ3pXkge1+pN2vu9M8wgjNaH9fG3OfpltVOc3BRNPaqDfKwSVjTM9q17sG8MW+dYvmbnbv93NpOrMr4CMD7/mZgfUG1y2ag3/DwHr7AT8bsm4Bh/WV27Ndf7H3uAzYo2+9A/uWHd7138bJaVJT33F+9hLW+ZsFjp8rgP/oe33guO9H09pxh3phgvvai+mRI5Y/sldmke38Nk2iqbe9K9up9/ojwE9HvRfNCHT95fs/v4uAzy/0NwEeQTPi1kJ1WAHHruCzOormQnmxurJompWfCuw3sI2PtMtPHLL9kcv6ytx24HPun65F0xfEZQPzB/8WVwBP6vo4c1qf03Lq13a9ze1xNey4u3SROnaseqwtO85xOLJeBs5ulz13yLIFj9++crcfqM8Gj9+3970+fOA9Dh/1OYzYl1WvO52cpmmi6UP002N+lxdNcuPwgW2MrMfGqeNorgu/PeL9Ni9xf3p1zuVsfw06bH8+x47nJV1co36E0edCuwIfbpf/CvjtgeU3GRLv4HlOAZ8asu2XjfjMT2mX/8kY+/N9mo7bO/9fnsRkS6r5tNsY0waAqrqA5nncl9JUJlfQnBR8hmYI0JvQHJDDHEFzEvGOdt1exfNDmlZQD6iqB1fVdiNjVTPC0x1p7pafR1N5nUtTMfysr9xFVfVgmpEe/o1mqNKt7Xv8iKaj3ccD16+m/xhJA6rqeTQda3+Gbcfot2n6aLo1s3GXf9mq6r9o6ptTgfNpThbOpam3freakaEuXGD919LUQR9o17+M5k7Y39N0WPnuUeu267+BpoXQC2n6Wvl5G8P5NAmulwK3raoTVrCP76IZue9BwOuAr9DUpb33+RpN/wuPAvatqvu39fDEVNXngbvQtGz9Bc3n9EOaDt4vraoLgQNo7kZ+EPgJTd1/KU3d/jpgUzXN6qWZUVWn0Axv/iGaR3YuA84E/pmmjvinzoIb02LHb1+5/wXuRHOO97O23DnAa4HDaI7vScW06nWnNE2q6mtVdUfgt4B/oPm/731X9vrJfBfNo/4HV9XtquojE46hd134epprrctpbuR9mm2tRpdqZ7a/Bg3N/pxNsz8PBX5z8Lyki2vUhVQz2M4DaBJRuwDvSLKpb/lZNF1oPJzm3PCHNHXkpTTn3W+jafl1jyGb/yvgL2jO3y6luQn6DZrPnap6VftZ/D+aFrzn0ySmzqf5P/lrms7l56MVFZA2OydJkiRJkiR1xpZUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTObeg6gJ4jjzyy3v/+93cdhqTFpesAppF1mDRTrMeGsB6TZoZ12AjWY9LMGFmPTU1LqvPOO6/rECRp2azDJM066zFJs856TJp9U5OkkiRJkiRJ0vo1dpIqyTWSvCLJmxYpd8MkH0hycZIfJPmzlYcpSZIkSZplXlNKWsxYSaok9wd+Bjx+jOKvBb4NXB84GnhekjsuO0JJkiRJ0kzzmlLSOMbqOL2qTgU2JHkucNCockmuCRwB7FNV5wOfTfIW4MHAp1ceriRJkiRp1nhNKWkck+6T6iDgwrYy6TkDOHjC7yNJkiRJmj9eU0rr2KSTVHsAFw/MuwjYa8LvI0mSJEmaP15TSuvYWI/7LcFWYNeBebvRVCo7SHIscCzA/vvvP/abHLZ58/KikzTU6aec0nUI68ok6jD/ZpI0nlk5b7Rel66y6teUs1IvSLNkUt9jk25J9S1g7yQb++YdCpw5rHBVnVBVm6pq08aNG4cVkaSxDRsxJsl1kpzajgzzyySfSnK7RbZzdpIrklzeNx29+nsgSZK07nlNKa1jK05SJflwb0jQ9rnhDwPPT3LNJJuAhwFvX+n7SNJCFhgxZk/gf4E7AdehqY9OTbJY/XfvqtrQN71z4kFLkiTJa0pJVxkrSZXkPknOA54KHJPkvCR/1C6+CbBPX/HHADcFfgKcCjyvqj4xwZglaQdVdWpVbQCePzD/u1X1wqo6p6ouBV4N7Atcr4s4JUmS1iOvKSWNY6w+qarqfWxfafQvO3Dg9feAe644MklaHXcAzgPOXaTce5NcCnwD+Ouq+q9Vj0ySJGlOeU0paRyT7pNKkqZWkr1pWlI9t6quWKDoXWkeE7w+cAJwcpL9hmzv2CSnJTlty5YtqxKzJEmSJK0XJqkkrQtJrgm8H/hAVR2/UNn2EcHLquqXVfUa4DvAXYaUs6NOSZIkSZoQk1SS5l6SGwAfAz5aVU9Yxib2onlEUJIkSZK0SkxSSZprSQ4CPgm8oaqeOmT57ZN8I8kN29e3TvLkJPsluVqSp9L032dnnZIkSZK0ikxSSZoLC4wYc2fgQOClSS7vm57TrroHcAiwS/v6fOC+wOnAj2k67Tyyqrau3d5IkiRJ0voz1uh+kjTtFhoxBjhxgfU+AqTv9beBIyYZmyRJkiRpcbakkiRJkiRJUudMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSdIcSnK3JB9OckGSrUn27jomSZKkhZikkiRJmjNJjgBeD/w9sC9wAHBhp0FJkiQtYkPXAUiSJGniXgY8pqr+u329tctgJEmSxmFLKkmSpDmS5AbALYFjk/wkyU+TvDrJrl3HJkmStBCTVJIkSfPlAOAi4HhgP+BWNEmrl3QZlCRJ0mJMUkmSJM2XAi6tqo9X1a+q6gfAy4H7DRZMcmyS05KctmXLljUPVJIkqZ9JKkmSpPlyFnCdJNfrm7cB+Olgwao6oao2VdWmjRs3rlmAkiRJw5ikkiRJmiNVtQV4L/CqJHsn2R/4K+BN3UYmSZK0MJNUkiRJ8+cRwMXAt4FPAu8AXtlpRJIkSYsYK0mV5IZJPpDk4iQ/SPJnC5Q9IMmpSX6R5Nwkr02y5+RCliRJ0kKq6mdV9bCq2ruq9quq46qquo5L0vrlNaWkcYzbkuq1NHfirg8cDTwvyR1HlH0b8OW27GHArwEvWFmYkiRJkqQZ5jWlpEUtmqRKck3gCODpVfWLqvos8BbgwSNWuSXwwaq6uKp+CLwfuPGkApYkSZIkzQ6vKSWNa5yWVAcBF1bV+X3zzgAOHlH+ZcBbk/xxkkOAB9EMeyxJkiRJWn+8ppQ0lnGSVHvQdLzZ7yJgrxHl/wv4EXBH4HM0wx1/aVjBJMcmOS3JaVu2bBkvYkkaIck1krwiyZsG5h+d5KwklyT5TJJbLLKdJZWXJEnSgrymlDSWcZJUW4FdB+btRlOpbCfJtYD3AA+sqkcCN2rLvWbYhqvqhKraVFWbNm7cuISwJWl7Se4P/Ax4/MD8/YETgScAG2nqqJOTZMR2llRekiRJi/KaUtJYxklSfQvYO0n/EX8ocOaQsgcBO1fVdwCq6gLgDcCtVhqoJC2kqk6tqg3A8wcWHUXTp8F7q+pC4DhgX0bXS0stL0mSpIV5TSlpLIsmqdrnhj8MPD/JNZNsAh4GvB0gyYf7hg/9GnBJkucl2TPJvsCxNB3dSVIXDgbO6b2oqiuAsxjdB8JSy0uSJGkBXlNKGtc4LakAHgPcFPgJcCrwvKr6RLvsJsA+AFW1FbgPcFfgx8AXgG8Az5hgzJK0FEvtA2Gp5SVJkrQ4ryklLWrDOIWq6nvAPUcsO3Dg9ReAu684MkmajLH7QFhq+STH0tzZY//9919ZlJIkSXPMa0pJ4xi3JZUkzaozgJv1XiTZGTiE4X0gLKm8HXVKkiRJ0uSYpJI0704FDk9ynyR7AU8FzgVOB0hy+yTfSHLDccpLkiRJklbHWI/7SdK0S3If4I00fUrtlORI4GlV9dokjwaOB25Ik2w6pqqqXXUPmpZSuwBU1TmLlJckSZIkrQKTVJLmQlW9j7bDzSHLTgJOGrHsI0DGLS9JkiRJWh0+7idJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXP2SSVJkqQlOWzz5q5DkCRJc8iWVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjo3VpIqyQ2TfCDJxUl+kOTPFil/tyQfTnJBkq1J9p5MuJIkSZKkWeM1paRxjNuS6rXAt4HrA0cDz0tyx2EFkxwBvB74e2Bf4ADgwpWHKkmSJEmaUV5TSlrUhsUKJLkmcASwT1WdD3w2yVuABwOfHrLKy4DHVNV/t6+3TipYSVLjsM2bV7T+6aecMpE4JEmSFuM1paRxjdOS6iDgwrYy6TkDOHiwYJIbALcEjk3ykyQ/TfLqJLtOJlxJkiRJ0ozxmlLSWMZJUu0BXDww7yJgryFlD2iXHQ/sB9yKpoJ5ybANJzk2yWlJTtuyZcvYQUvSUiQ5IMnlQ6azR5R/bpIrB8q+a43DlqQVS7J7ko8m+UTXsUha17ymlDSWcZJUW4HBrPVuNBXHoAIuraqPV9WvquoHwMuB+w3bcFWdUFWbqmrTxo0blxK3JI2tqs6pqg39E/B44KwFVnvLwDpHrVG4kjQRSXYG3kZz3iZJXfKaUtJYxklSfQvYO0n/EX8ocOaQsmcB10lyvb55G4CfLj9ESZqsJLsDzwGe33UskrSKXg18E3hV14FIWve8ppQ0lkWTVO1zwx8Gnp/kmkk2AQ8D3g7QDgv6Z23ZLcB7gVcl2TvJ/sBfAW9arR2QpGX4M+DrVfXRBco8JMklSb6b5MVJslbBSdJKJXkJsFNVPa3rWCTJa0pJ4xqnJRXAY4CbAj8BTgWeV1W9vg1uAuzTV/YRNM8bfxv4JPAO4JUTiVaSVijJNYCnA89eoNgrgWvT9JOwmWaY5CcO2ZZ9IEiaOkkeDRwCPLbrWCSpj9eUkha1YZxCVfU94J4jlh048PpnNFlxSZpGfwV8pqo+M6pAVZ3b9/ILSV4N3Af4h4FyJwAnAGzatKlWIVZJWo6bA0cCF7WNQHcGdk5yCXC9/tG1khwLHAuw//77dxCqpPXCa0pJ4xi3JZUkzbwk1wX+goVbUQ2zF3De5COSpMmrqidX1e69iaZF1afa1+cPlLXDYUmSNDVMUklaT/4a+GBV/V//zP5+ENrXf5tkU5LdktweeBzwljWOVZIkSZLWlbEe95OkWZfkAJrWBLcbsniwH4TdaPo+uC5wNvDsqnrPascoSZIkSeuZSSpJ60JVnQPsMWLZgQOvnwQ8aQ3CkqRVV1UnAid2HIYkSdKifNxPkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjo3VpIqyQ2TfCDJxUl+kOTPxlhn9yQfTfKJlYcpSZIkSZpVXlNKGse4LaleC3wbuD5wNPC8JHccVTjJzsDbgN1WHKEkSZIkadZ5TSlpUYsmqZJcEzgCeHpV/aKqPgu8BXjwAqu9Gvgm8KqJRClJK5DkuUmuTHJ53/SuEWWXfJdPkiRJo3lNKWlc47SkOgi4sKrO75t3BnDwsMJJXgLsVFVPm0B8kjQpb6mqDX3TUSPKLekunyRJkhblNaWksWwYo8wewMUD8y4C9hosmOTRwCHAA8d58yTHAscC7L///uOsIkmrpu8u3z7tSdRnk/Tu8n260+AkSZJml9eUksYyTkuqrcCuA/N2o6lUBt0cOBK4KMklwGuAOyW5pL34205VnVBVm6pq08aNG5cYuiQtyUPauui7SV6cJEPKLOkunyRJksbiNaWksYyTpPoWsHeS/iP+UODMwYJV9eSq2r03AY8FPtW+Pn+wvCStkVcC16a5W7eZ5jG+Jw4pN/ZdPmju3CU5LclpW7ZsmViwkiRJc8ZrSkljWTRJ1VYEHwaen+SaSTYBDwPeDpDkw3YsLGmaVdW5VXVBVV1eVV+g6YjzPkOKLuUun3fuJEmSxuA1paRxjdOSCuAxwE2BnwCnAs+rqk+0y24C7LMKsUnSatkLOG/I/LHv8kmSJGlJvKaUtKhxOk6nqr4H3HPEsgMXWO9E4MRlxCVJE5Pkb4GTgS8DvwE8jraDzSQfBv6jql5RVee3r5+f5Ok0J1IPA0aNBChJkqQxeE0paRxjJakkacbtBrwDuC5wNvDsqnpPu2zwzt1jgNfT3OX7Gdvf5ZMkSZIkrRKTVJLmXlU9CXjSiGUHDrweeZdPkiRJkrR6xu2TSpIkSZIkSVo1JqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSdIcSfLMJF9PsjXJ2Ume0nVMkiRJ43B0P0mSpPlSwKOB/wNuCnwwyVer6n3dhiVJkrQwW1JJkiTNkao6rqo+XVWXVNWXgY8Bh3UcliRJ0qJMUkmSJM2pJDsDm4CvdR2LJEnSYkxSSZIkza+XAOcC7+k6EEmSpMXYJ5UkSdIcSvJ04P7AXavqihFljgWOBdh///3XMDoNOmzz5q5DGNvpp5zSdQhj83OVpNliSypJkqQ5ksZLgIfRJKh+PKpsVZ1QVZuqatPGjRvXLkhJkqQhbEklSZI0X94M7EuToPpFx7FIkiSNzSSVJEnSfHkocAVwXpLevLOr6qDuQpIkSVqcSSpJkqQ5UlVZvJQkSdL0sU8qSZIkSZIkdc4klSRJkiRJkjpnkkqSJEmSJEmdGytJleSGST6Q5OIkP0jyZwuUfWaSryfZmuTsJE+ZXLiSJEmSpFnjNaWkcYzbkuq1wLeB6wNHA89LcscRZQt4NHBt4HeBpyS5z0oDlaTlWuqJTpLnJrkyyeV907vWKl5JkqQ55DWlpEUtOrpfkmsCRwD7VNX5wGeTvAV4MPDpwfJVdVzfyy8n+RhwGPC+iUQsSUvXO9H5P+CmwAeTfLWqFqqX3lJVf7Am0UmSJM0xrykljWucllQHARe2lUnPGcDBi62YZGdgE/C15YUnSStXVcdV1aer6pKq+jLQO9GRJEnS6vOaUtJYxklS7QFcPDDvImCvMdZ9CXAu8J5hC5Mcm+S0JKdt2bJljM1J0sos4UTnIUkuSfLdJC9OkjUIT5IkaR55TSlpLOMkqbYCuw7M242mUhkpydOB+wObq+qKYWWq6oSq2lRVmzZu3DhOvJK0Ugue6LReSdMHwl7AZpp+E544WMiTIkmSpLF4TSlpLOMkqb4F7J2k/4g/FDhzWOE0XgI8DLhrVf145WFK0sqNc6IDUFXnVtUFVXV5VX0BeDWwQ2ednhRJkiSNxWtKSWNZNEnVPjf8YeD5Sa6ZZBNNZfF2gCQfHhg+9M3A7bAykTQlJnCisxdw3uQjkyRJmn9eU0oa1zgtqQAeQzMi1k+AU4HnVdUn2mU3AfbpK/tQ4K7AeX1Dt39rUgFL0jIseKIzeGKU5G+TbEqyW5LbA48D3rJ24UqSJM0dryklLWrDOIWq6nvAPUcsO3DgtZ0LS5o2DwWuoDnR6c07u6oOan8fPDHaDXgHcF3gbODZVbVQH1aSJElagNeUksYxVpJKkmbZYic6Q06MngQ8aTVjkiRJkiRtzySVJK1Dh23e3HUInH7KKV2HIEmSJGmKjNsnlSRJkiRJkrRqTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMbug5AkqT17LDNm1e0/umnnDLzMaz0/ScRgyRJkrpnSypJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXNjJamS3DDJB5JcnOQHSf5sEmUlaa1Yj0laT6zHJE0bz8UkjWPcllSvBb4NXB84GnhekjtOoKwkrRXrMUnrifWYpGnjuZikRW1YrECSawJHAPtU1fnAZ5O8BXgw8OnllpWktWI9Jmk9sR6TNG08F5M0rnFaUh0EXNhWED1nAAevsKwkrRXrMUnrifWYpGnjuZiksYyTpNoDuHhg3kXAXissK0lrxXpM0npiPSZp2nguJmksiz7uB2wFdh2YtxtNRbGSsiQ5Fji2ffnLJN8cI57Vsg9wXofvvxSzEuusxAnrPNYkSyn+/qo6cpLvvwZWpR4bow6bpf+rcU1sn5b4f7eaZvrvtMDnuGb7tYZ/y5H7tA7qsaWYZD02abN0vM1SrDBbx/wsfbbT+LnOYh02bdeU/g+uDmOdvFmJkyRLiXVkPTZOkupbwN5JNlbVlnbeocCZKyxLVZ0AnDBGDKsuyWlVtanrOMYxK7HOSpxgrOvAqtRji9Vh8/i3cp9mxzzu1zzu0yqZWD02abP0N5ylWGG24jXWdWmqriln6e9qrKtjVmKdlThhcrEu+rhf+yzwh4HnJ7lmkk3Aw4C3t4F8uDck6GJlJakL1mOS1hPrMUnTxnMxSeMap08qgMcANwV+ApwKPK+qPtEuuwlNE7RxykpSV6zHJK0n1mOSpo3nYpIWNc7jflTV94B7jlh24Lhlp9xUPHY4plmJdVbiBGOdex3VY/P4t3KfZsc87tc87tOqmOLzsVn6G85SrDBb8RrrOjRl15Sz9Hc11tUxK7HOSpwwoVhTVZPYjiRJkiRJkrRs4z7uJ0mSJEmSJK0ak1SSJEmSJEnqnEkqSZIkSZIkdW6sjtPnTZJbAQcA76+qy5LcG7gV8KGq+r9uo9tRklsCBwN7ARcBZ1bVF7uNakdJrgecWwMdnSV5VlW9sKOwFpXkbVX1kK7jWEySWwP3Bn4KvKeqftRxSGoluQPwYAaOU+DtVfWpLmOTJEmSpElbrTzFuus4PckfAq8Evgf8EvhX4EXAx4HfAh5TVe/uLsJtktwcOBnYFziL5g+/G3AIzXCsx1TVV7qLsJFkE83QsPsCW4C/qapX9S3/VVXt2lV8/ZI8esjsfwH+BAhAVb1uTYMaIclbgD+vqvOSPAh4LfARmuTyJuB3qup/OwxRQJI/BZ4HvAU4g23H6aHAQ4HnVtXx3UWoniQ7A09hW0JxD+BimoTiScDfVdXl3UW4PPO4X/O4T+vVrNxo0+qYpWN5lmLV8sxSfeTN/9Uz7Tf+Z6FBzWrnKdZjkuprwOOr6iNJjqL5cG9bVV9Kcmfgn6vqNt1G2UjyKeA/geOq6sq++TsBTwPuX1V37Cq+vng+QfM5vhr4TeBVwPuq6ont8suqapfuItwmyQXAj4Ef9M2+K/Cx9veqqnuseWBDJLkY2KuqrkjydeCJVfWBdtn9gGdNw99/vUvyPeCBwxKGbQL3lKq60dpHtnLzdsKe5F+AWwMvZfuE4s1p9vOLVfUn3UW4PPO4X/O4T+vNrNxo65ml+m7GYp2ZY3mWYtXSzFJ95M3/yZulG/+z0qBmtfMU6zFJdRFw9aq6MsndaQ78w9tlG4BfVNVeXcbYk2QrsLGqLhqybE/gvKq62tpHtkMsFwDXqarL2td7A+8D/qeqnjFlSarbAW8A/rCqPt/O21pVe3Qb2Y6SfIOm0vxWkvOBa/XupiTZlebvf41Og1TvOL1eVV04ZNk1gJ9Mw3G6HPN2wp7k58DNq+qHQ5bdAPhqVe299pGtzDzu1zzu03ozKzfaemapvpuxWGfmWJ6lWLU0s1QfefN/8mbpxv+sNKhZ7TzFeuyT6tvA7YDPAs+gyVD23AHY4YupQz8E7gx8YMiyOzM9sV4AXA/4PkBV/bxtlvjRJD8BpiYTWlWfS/IA4B1J/ryq/rvrmBZwIvCSJL8HfB24EU1WHZq7p2d2FJe29zHguCRPr6qr6pMk1wFeAHyis8hW7iEMP2H/RpJPA1+luVs2Sxaqj2Z5MJF53K953Kf15DDgXv0XhADtTcJ/Bp7TSVSjzVJ9N0uxwmwdy7MUq8Z3GLNTH90KuHt78/9/kvwm8L4kx1XVMzqObdARNDf/nzJw8//u3Ya1g3OAGwPfAm4A/Fffsg8Cb+0iqBEOYFuS7wLgk1X1pfb1Z2haz06DVc1TrMck1XNpDvSf09x5eleS/wK+BjwMeH6HsQ16KnBSG985NE25d6Xp6+ZuwLAmll34PPBw4MW9GVV1fpL70lyg79xVYMNU1TeTHAmcmuS4ruNZwN8Br6E52fwlcHybXb8FzV2K+3YYm7Z5NE2z4Z+1d5R6x+newIeBR3UY2yTM0wn724B3Jnkh29epN6Opb/+9w9hWYh73ax73ab2ZlRtt/WapvpuVWGfpWJ6lWLU0s1QfefN/8k5kdm78z0qDmlXNU6y7x/0AktyM5gP8QFX9MskjgdsCH6mqd3Qa3IAk+wFHsa3Pga00TbtPrarvdhlbT5JrA3tW1feGLLsJcOeqesPaR7awNu530NyNvG7X8YyS5DdoElIH0HwxnQW8raq+32lg2k77aN9BbDtOv1VVF3Qb1cq0j5QcBow6Yf9SVR3bWYBL1D7S/RTgGHasU08GXt57bHmWzON+zeM+rTdJjgZeT3PHeugJbFWd3F2E25ul+m7GYp2ZY3mWYtXSzFJ9lORdwGer6sUD829Ac/P/gKqaqgYASW5E04/WccAbpq0blbYfv9fQ9On0S5rHE7e78V9VU/HkQ5IH0sR6VYMamuTUVQ1qquoV3UW4zWrmKdZlkkqStDhP2CWtxJAT2Ito6o93T8uNtp5Zqu9mKVZpWszCjX/w5v9qmpUb/7PUoGa1mKTqk+T6wC7TVFGNMiuxzkqcYKzSepEdh6A+o+95/5k1j/s1j/u0XiT5j6p6QN/rJwL3oRmt6s1V9b6uYtPam4VjOcnmqjql7/UNgbvQ/M9+sqou6So2SZoVk7hONUnVp+3t/+Bpa0I5zKzEOitxgrFKo8zCxcU4MkNDUC/FPO7XPO7TepO+YdLbPn6OBk6gqUceB/x1VZ3YXYTDzUJ9N0vJlFk6lgf+Z+9FE/d3aP4XdgaOrKpvdhiiVsEs3fg11smblThhdmKdxHWqSao+SW4H7FFVH+06lsXMSqyzEicYqzRoli4uxpEZGoJ6KeZxv+Zxn9ab9A2TnuRsYHNVnd6+vj3w+qq6eXcRbm+W6rtZSqbM0rE88D/7WeA1VfWv7eunAveoqiO7jFGTN0s3fo118mYlTpidWCdxnWqSSpI01CxdXIwjyVZgY1VdNGTZnsB5VXW1tY9sZeZxv+Zxn9abgUTKVmCvXj2SZFfg51W1Z5cx9pul+m6WkimzdCwP/M+eD1y/qra2r3cHflRVe3cZoyZvlm78GuvkzUqcMFuxrtQ0DVG7ZpJcoz3pIMnVk9w3yRFJpuJLciFJ3tZ1DOOYlTjBWKUFHAb8Y/8FG0D7+p/b5bOkNwT1MNM2BPVSzON+zeM+rTc7J/m3JG8ENtB0VNxzS5pH06bJYcxOfdd/h/nXgbf0vf5nmpGgpsUsHcs7Jbl7kiNoWtFd2rdsH+DybsLSaqqqz83KRb+xTt6sxAnTGWuSWyZ5YJJHJDmm7Zx+xTZMYiOzpO0d/1+BryZ5APAR4HyaJtIkmaYm0o8eMvsBSR4FBKCqXre2Ue1oVuIEY5WWqHdx8YEhy6bt4mIcTwVOSjJyCOoOY1uJedyvedyn9eb5fb+/CNidZuhvaEale+eaR7SwWarvdkpyd5qbzdOeTJmlY/n7QO+86kfA9dt5AA8GvthFUJqMJAF+E7gxTaL3HOB/q2qajhfAWFfDrMQJsxHrQo/IJ1nxI/Lr7nG/JN8A/oLmi+fpwHOq6qR22TOBu05RE+kLgB8DP+ibfVfgY+3vVVX3WPPABsxKnGCs0lIkORp4PTDy4qKqTu4uwqXLjAxBvVRJ9gfuzxzt15B9CvB/zPA+aXrNUn3X9vHVfwJ/l2qHUE/yl8B9q+qeXcQ2zDzUu0kOA86vqu90HYuWLsmvAe8Frg2cCVwPuAZwJfDMabrpa6yTNytxwuzEutqPyK/HJNXFVXW1JLvRfEnuWlVXtMv2AH5YVdfqMsae9rnTNwB/WFWfb+dtrao9Fl5zbc1KnGCs0lLNw8WF5oP1n1bbPNR3JlOkHSV5N/AN4GlVdWWSWwN/AzwR+A/ghVX1jg5DvIqxTt6sxAmzE+tq9ze4HpNU3wduXVVbkjykqt7Wt2w/4AtVtbG7CLeX5BDgHcCfV9V/T+tJ+qzECcYqTUqSR1XV67uOYymS3Jumb5mvAv9ZfV+CSc6oqoO7im252v4UHw2cXlWfTHIMzaMplwJvrar3dhrgMiT52JDZvwV8sveiqu66dhFpvZul+m7aYp2lercv1q8B75nmWDW+JD8HblBVF7evdwZ+UlX7JLkjTX90U9GXm7FO3qzECbMTa5JvAX9aVTs8It/Wo6+sqpssd/vrseP0TwO/DdCfoGo9GPjymke0gLZ/rCOBlyV5UNfxjDIrcYKxShP0kq4DWIokTwZOBG4D/BPwySTX7Sty4y7imoBXAI8BTmj7svsb4LM0fQS8NsnDuwxumYqm38zXttPraPrZeW3fJK2lWarvpibWWap3B2L9R5pY+29cT02sWrJz2f7v92vAZe3vpwG3WPOIRjPWyZuVOGF2Yu31N/j2JC9L8oIkL2lbgr2d5pG/ZVt3HacDf8To5NyZwFPWMJaxVNX/Z+++w2Ury/v/vz+cQ8cCcmwo2AuoX4xH/dqxg5Ug8adGjSGKJRo1KpZoRE1EjZrErxrFRmxRIgaxt4QYaySKxq4o2OUACsjhIOX+/bHWuIdhZp/dZtbMnvfrutY1M6vNvdaeefaz7nnW8/w0yb1oWtT8dnvrd2VW4gRjlZYiydu3s8oeEwlk7fw5cO+q+kZ7z/wrgM8kuUtVbeHyfbzMkgfSjJa2F02fTQdU1WkAbWfFbwa297ecNvcB3gPcrKqeC5Dk9VX1z92GpfVqlsq7WYqV2Sp3h8X6X1Maq5bnpcCHkxwL/A44koUfO64CnNNVYEMY69qblThhRmKtqvcn+TILt8hfleYW+Y/TtLBa1S3yc3e7nyRpaZK8FngC8JIRqzyrqqbpYmhRSS4A9qyq3/XNew7wMJpBCc6uqh27im+l2uO6Utt3weVuCW77XzynqnbvLsKVaS8S39i+PBK4wNudNS6zVN7NWKwzU+7OUqxaviQHA39M09/cfwH/r9cv8bQx1rU3K3HCbMU6LnOXpOrru+NrVfXZae67Y1ZinZU4wVil5UhyZRaplCfZMk19+G1Pkm8Bf1pVXxqY/3LgNjSju+7USXCrkOQbwB9V1beHLPsD4ISqmtnbVJK8DLgpcF+TVBqXWSrvZizWmSl3ZylWra1p68dtMca69mYlTpiuWMfZ3+A89knV67vjjTPQd8esxDorcYKxSktWVecBhy2yyqMmFcsaeQdw0ODMqno2TR8As3oL/JuBA0YsOwoY1gn5zKiq5wAnAa/vOhatX7NU3s1SrMxWuTtLsWptTU0/bktgrGtvVuKEKYl13P0NzmNLqjMZ3XfHHYE3V9X+HYb4e7MS66zECcYqSZIkzZMl9ON2+LS01DXWtTcrccLsxJrkh8CDBvrwewBwl6rakuR3q2l5Oo+/COwObKmqXyW5rHfR3/ofYL+O4hpmVmKdlTjBWCVJkqR5ch6L9+N22QRj2R5jXXuzEifMTqzXAL4HUFWXAc9MchbwySR3BbKanc9jS6qZ6btjVmKdlTjBWCVJkqR5MmP9uBnrGpuVOGF2Yh13H37z2CfVLPXdMSuxzkqcYKySJEnS3JilftyMde3NSpwwU7GOtQ+/uWtJJUmSJEmSpOkzjy2pJEmSJEmSNGVMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUnSmCQ5KEm10/W6jkeSBiU5vS2jju46FkkaJcnJbVl1XNexaLxMUi1TkqPbL8fpS1y/d3HymPFGNluSPKbv3PSmS5NsTfLzJJ9P8pok907i51RaJ5JsHvLdryTVdWyS1IWl1i2T7JzkU+265ya5TTv/OMtRSUs1zjKnb9nJ44le88CLf02Di9rpUmBX4FrAHYCnAJ8AvpnkLt2FJ2kNXcbCd/4i4JJuw5Gk6ZdkI/Be4J7ABcD9qup/2sUXs1CmStKqWeaoSyap1Lmq2qWddgI2AvsC9weOBS4EbgZ8OsljOwxT0hqoqq/0fed3AR7XdUySNM2SBHgb8GBgG/Cgqvpcb3lVPa6vTJWkVbHMUddMUmmqVNWlVfWTqvpIVT0euDnwZWBH4I1JDuoyPkmSpAl7LfBI4HfAQ6rq3zuOR9L6ZpmjTpmk6lgaD03y0SRnJvld2yfTCUnuuch2v+84LsmuSf4iyReSnN9OX0ryx33rXzvJK5J8M8kF7TqfTfKg7cS3Y5LHJ/mPJGe18f0iyQeSHLyW52KYqjoDuBvwbZrP6zuS7LrWsSa5UpKj2nN4TrvtT5O8P8nhSXYass0+SV6d5NvtOT0vyVfb+7yvMuJ9LteJcpLrJ/nHJKclubjdzx2Wf6ak9SnJ1ZK8uP1unZdkW5IfJnlLkv2HrP+h9vt1woj9ndAuf9mI5We0yx8/ZFmSPCzJR5L8qi0ntiT5RJKHt788LufYft83X/v6lu1x/STJJe3x7pfkwna9p25nf//YrvfN5cQhaXolOQZ4Ek2XCA+vqo8MWWe7/cu09Y03tGXctiQ/TlP3fCRNK/ZR26Ut3z7alnsXp+mb5n/S9B16tzU4TElTYqVlTntdU8CftLPuliv2P3r0kH3dIsmxSb6fpm/iC5J8I8k/JPk/i8S5Y1uP+lR77bYtybeSPC/Jjts5xtsneUdbHl7Ulmn/neTZSXYfsc3v+5lOcvX2HHy1jfe3afpTPnyx99UyVJXTMibgaKCA05e4frXTY4Ys2xU4sW+doikQ+l//P2CHIdue3C4/BfjhIts/F3gGzW1zw9a5jKYAGhb7dYCvDuzvsoHXr1zheXxMbx9LXP9Ofe/5uLWMFfgD4Cfb+TscP7DNfYHzF3mvnwH/Z8h7HdS3zutpmtAOvudBXX/OnZwmNS1WFtAkqM9e5Hu9DTh8YJu/bJf9csj+dgF+2y7//pDl1+zb900Gll0V+NR2ypjjGSivB77z1xt17MBr+sqAy/r2fT3g7e3zby9yHncFft2u96Su/65OTk5LnxhRtwSe3Vc/+OPlbt+3/FBg6yJlV286emC7nYEPD6wzWD8q4DZdn0MnJ6elT+Moc4D92npZf11m28D0/IH9PGegTBlWvtyvb/2T23lfBL61yHbvGxF3gL8bWHewPPwmcI0h2/aWfwQ4b5H3fnLXf9/1MNmSqlv/j+Ze34toLqyuXlUbaPpkOob2g05TYIxyG2DPdp192u2vB3yyXf5S4JU0SZPHAHvR/GJ2K+DrtF/WJBv6d5pkN+CjwIHAfwOHAHvT3HZ3g3a/lwLPmETWuJr7oE9rXz54rWJNcl3g4zRJru/TVOR2b7e9MXAUzbnbqW+bmwLvB/YA/oumk/cdaSpz96UpNK8NfCTJ1RY5rCfS3Mp4MLAbzd/l2sD/LLKNNBeS3Jzm4mgv4F+AzTTfzd2BW9N8B3cG/jnJvn2b9pqkXyPJjQZ2e+92e4AbJbnlwPJeK8afV9X3+mLZgSYBdU/gO8BDaRJaG4HrAs+i6VT0j2jK8pV4Cs3x3pkmmbYRuD7wC+Cf2nVultG3PD+cJpF2PvCOFcYgaUokeQLwMpq64OOr6l0r3M+tgPfQJLJ7dZadaOodtwReSJPAGuZZwP1o6qlPYaGeuhdN36HvpLkdaFmtSCVNn9WWOVV1RjV9VPXqIJ+pvj5I2+lvBt7vGJo7Zd5NUx7tSFM23Y2mT6yL6bsG63N7mmumv6a51utdQx3XLn9IknsN2e75wDNpftR7Jk09a0dgE00d7kfA/sBbFjnUQ4BfAUfQXG9ubGP/crv8ZRlxR42Woess2axNLGSOe7/ib2/qrfuYgf3csm/ZqJZML2iXbwX2Hlh2crvsVOBaQ7a9Yd/+3w7sMmSde/Wtc5uBZc9t538O2HlEfL2C7HMrOI+P6b33MrZ5Z7vNT9YqVhZaKPwM2DRi291p7sfuvT6h3ebrw96PpsD6ZbvOKwaWHdR3zp8PpOvPtJNTl9OosoAmeVyMbgG5A/D5dp2/7Zsf4Kx2/p8MbPPWdv6X28cXDix/eTv/nQPzH97O/x6w14h4ntCu89OB+f3f+euNOnbgUds5T6e2671nxPLeMb2267+pk5PT8iYGWiUAf8zCr/N/sdztB5Z9ol32lUXqSKczvCXVV9r5b1jkvW/EkFYHTk5O0zuNucw5rl128iLbXxU4t13v2EXW+z/03ZnC9q9/dwS2tOu8ZmDZvjRJ9QuB2454v1vQjDpdwI0HlvXqa+8YVpbS/IDaW+ewrv/Gsz7Zkmp1dl7CNMoj28fTqupfRqzzKppbU3YFRrVWOrWqfjE4s6pOo/llH+BTVbVtyLZf63t+g4FlvRG3/raqRg0vemL7eLsM6bNpDHrHuWlg/opibVtg/X/t/GOqasuwDavqgqo6od3mSiy05HrFsPerqrNobuUDePTow+Gd1ZZqkhYk2Q+4D80vaH8zbJ2qugw4qX155775Bfxn+/JOffvcADyA5vbBp7ezHzKw2//bPv7HwPxeGfMPVXXOiLBPbB/3SXL9EeuMVFXba/3Ua031h0mu3r8gyWaalmawUPZImkFp+go9jiYR/6mqes0q9nVdmhak0CTlVzpc/MhW4VX1g6r61Qr3K6lja1nmLMPhwJVpWmk+d9RKVfW1qvrakEWjrn8vpklgQdNgo99jaJJYH6yqLzNEVX0D+EH78s7D1gE+PaIsPZUmCTbsvbVMJqlW7oyqyvamRba/ffv4mVErVNVWFm79uv2o9RZxfvs46u98Xt/z3XpPklybpvkjwL+1HdFdYWLhQnAji1Rg1tAVzucqY93MQhPSjy8xhtsAvVsjR/7t+pZdo73glrR0vYrBjsAvF/lev6Rd75oD2//7wH56zzcBH6Bpdfkz4Ja9WwLbJNZt2nV/n6Rq5/duA/yHRWI5ve+9BuNZC++iKbN3omli3u+Jvbir6ltjeG9Jk7GJ5tbiXkfm90ry56vY313ax0uBT69g+0+1j4cnOT7Jg5PsvYp4JE2XtS5zluqO7eP/VNXZa7zvX7ePuw3M75WHh42qy7X1uZu06y2rLtf+SHruiPfWMpmk6s412sdfbme9Xpb4GouuNdyiv5gNZIH7E0D79D3fidGtxPpbTy3Wamyt9FoP9J+z1cTaX/j8eIkx9P8dFvvb9Wf3V/K3k+bZtfueL9ZSdWPfOv16SaqbJdmrfX5o+/j+tiLx/vb1Ye3jrWhu7f1xVf2wb1970fQRBQt9z22v5eyal4dV9VuaW54BjkyakQSTXBV4WDv/dWv9vpImajeaW00OYaE1wGuS/OEK99crS89qf/hcrr8FvtA+/yOaFqNbkpye5D1JDuuVRZJm0lqXOUvVuwZb6vXXcvTKusGyqVcebmDxulxvu5XU5Ua9t5bJJNX0y8DjJPR3or7/UlqMVdXpE4ir15qsv2Px1cTaf07X+ra7jHguaft63+szl/idvl7/xlX1bZokcli45e/BNC2Rei0DTmgfe0mq3q1+J4+IBZoRZpYSz+A+1krvlr/r0wzSAM1Qz7sBP6VpJSZpdl0M/GFVfYymw/LTaTsVTjLq1pPF9H6gu2QlwVTVuTStUB9McztQ7zaY/Wi6SzgB+NiEunyQtPbWusxZqt610SS7PenV516xxLrc0ROMTQNMUnXnzPbx2ouuBddqHyd5v/+Zfc+n4p7aJLdlofnl+/oWrSbW/m2vu4JtFvvbXavvuX01SKNtGDKv9z3bexUjpPRu2btTkgNpEjsf7mtB+l/t+9wuyXUY3R/V2TS3ykDH5WHbV8J/tS+fMPD4xqpa0YWopKnx86r6JEDb38p9aQaC2AU4qR31dDl6t73stdIWT1V1WVWdVFV/WlU3punw+BCaUVeh6T/wKSvZt6TOrXWZs1S9et5Sr7/W8j2n4tpWizNJ1Z3/bh8PGlVxSLIHC53h/vewdcbkRyx8kUd12D4x7S90b2hffo/LJ6lWE+v/sHDxed/FVhyxzd0XWa+37MwJtTKTZlUvCdU/uMOX2scdgJU2Oe/d8ncnFm7167We6nW8fiLNr3l/yIgkVdsJ51fbl52Xhyy0pnpAkkcCN6P5JfRN3YUkaRyq6ns0Az5sBfakabW0vR83+32zfdyVpqxYi5jOraqPVdUjWOh/c5wtLiRNyBqUObDQcnOx2+V6HZfftq9bhnHr1S3vvYofQDUhJqm68672cT/gT0es82ya2zi2cfnEzFi1/bW8vX35yCQjEzhJdkjywHHFkuQaNJ19/gHNhdgj24vGVcdaVecBH21fPjfJ0M7fk+yc5O5923yoXfTsdoTAYTH3OjJ+5+BySZfT68jytN6MqvomcEr78qXtCFVDJblK7/s5oJekui3wUJohhz86sE4vaXUEcGPgR1V1xpB9Hdc+3i3Jn42KpY3nwYstXwMn0CTmNwDHtvPe5+ha0vpUVV+iKcMuoRlC/aPLuMD6EtAbkfSxw1ZIcjMWfiwYXPa0JItdaF488Chpxq2yzAHojZZ+wCK3Ar+fpu/knRkxijNAkpskGRyBfqX+meb2wivT9Ls1snVpktutIDmnNWSSqiNVdSrNlwXgDUmOSrIJmiGDk7wCeH67/KVVdeaQ3YzTMTStlDYAH0zy0iQ3axM9O7XPnwF8F3jhWr1pkg1Jrp3kXkn+gab/gzvTFGR/OmLI0NXE+lyaXwuuA3w2yQOT7NrGcf0kTwW+Q9PvS8/zaC54bwp8Osmd2vV3SnIwzUiCe9P0ifPyNTkx0oxLcsckd2s7+ibJ1drv1wPaVd41sMlTaL731wK+nOTxSa7Vbrt7kv/blpOnA/cffL+28/MzaCpANwc+NqTj4P+guR3mQJoWVYO3+vW8iYXWrG9K8k9JDkyysZ2un+QJSb4CvGUp52Olqup3wFvbl7u2j3aYLq1jVfVhFm7tvRXNaMbb7Qeqvb35H9uXT0vy7CR7pXHjJC8DvkZzC98wRwOnJXlBklu3P9rt0NZTjwbu0a53/MqOTNI0WmmZ0/pc+3gl4BVJrtnW226VZP92/z8HXtGu98Qk/5zkgLZ82T3JHZK8DvhfmkTZWhzTN4DXtC8fDXwyyT2T7NaWiVdPcniSDwBfpBk4Rx3ZuP1VNEZPAq5Gc5H2cuDlSS7j8snDN9CMrjJRVXVOknvTZLpvRZPMeS4LHdz1Z5+/wCqkGe4TmuPeccgq3wAeV1VfXOtYq+obSR4CvIemKfxJ7aLBv8Mn+rb5VpLDaSpl/xf4bPte/e/zS+D+HSQXpWl1H9okcZJLuXxfVJ8EXt2/clV9McmhNMmra9CUhW8Ysi3A70a8538Aj2mfnzC4sKouTnISC0nooUmqqvpd2wrzvcBBNBW3XuVt8Lv/C8bvjcBRNGXUqVX1ue2sL2nGVdVb2l/2X0zTpcA/J3lE26J8MS+jabF6r/b5y7h8HecbND/UXXXItttoRlF+cTvBFetH/1BVE2vtL2kyVlHmfJSmFeftgae2U8/TgW+1z4+muQ5+Ek3S6NFcsXyB0XW8lXgGTZ3tL4B7thM0Xbn01y0LW4h2ypZUHWp/1X8Q8HCaJMhZNF+SX9L0lXKfqnpi23dKF/GdRtMn1qOBDwI/p/nCXgT8kCaxczgLv6StVG/Izw3ABTQXeZ8DXktzYXurUQmqtYi1HdHiZsBLga/QjAB2KfAz4F+BB9IUoP3bfKTd5h9pWmhta2P/OvASmpEGv7KssyCtb9+nqZj8hqaCcB7N9/wJwCF9HZr/XvvdvBHwHJq+T86iqTj8lubXtdcBdwX+asR79m75+x0Lt+kO6k9enTwq+DbhfA+a/q2Op2mltY2mnPkJTZn9JzQtLMftV8D57XNbUUlzoqpewkK/dA8DXrmEbX5HM2rXUTR9VF1EU358BngcTXcK547YfH+a+s+HaepEF9HcAnQGTb3q7lX19BUejqQpt8Iy51Ka67d/BH5MU2b8hqZf3+/2rXdZVf05cDfg3TQt4y+muVvlG8DfATerqs+vzdE0sVXVU2nKvTcC36apUxbNbYr/ATwL2K+qvjtyRxq7bD8ZKkmSpkWSx9H0R/UbYJ8htzFKkiRJM8mWVJIkzZa/aB/fZoJKkiRJ64lJKkmSZkTb/94taJqm/9N2VpckSZJmikkqSZJmx9Pax09U1fe7DESSJElaayapJEmaAUluDBzSvrTDdEmSJK07dpwuSZIkSZKkztmSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjpnkkqSJEmSJEmd29h1AD0HH3xwfexjH+s6DEnbl64DmEaWYdJMsRwbwnJMmhmWYSNYjkkzY2Q5NjUtqc4666yuQ5CkFbMMkzTrLMckzTrLMWn2TU2SSpIkSZIkSfPLJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnNnYdwEoceOihQ+efeuKJE41DktbKsHLNMk3StBpVF1sqyzdJ69lgGWmZJy2dLakkSZIkSZLUOZNUkiRJkiRJ6pxJKklzK8ndknw6yXlJtibZs51/WJLTkmxL8sUkt+g6VkmSpPUoyS5J/jPJZ/vmWReT5pRJKklzKck9gbcBrwauCewHnJ9kX+A44CnAJuBDwPuSpKNQJUmS1qUkG4D3ADv3zbMuJs0xk1SS5tUrgcdW1YeramtVbamqS4AHA5+sqo9U1fnAMTRJrFt1GawkSdI69Ebgu8Ab+uZZF5PmmEkqSXMnybWBWwJHJvlVkrOTvDHJTsBNgDN661bVpcBp7XxJkiStgSQvB3aoqmcPLLIuJs0xk1SS5tF+wAXA64Dr0vwyd0vg5cBuwIUD618A7DG4kyRHJjklySlbtmwZb8SSJEnrRJIjgJsCjxuyeMl1sXZf1sekdcQklaR5VMBFVfVfVfW7qvoZ8Crg/sBWYKeB9XemqRxdfidVx1bV5qravGnTprEHLUmStE4cABwMXJBkG/Am4I7t8x1YYl0MrI9J641JKknz6DTgakmu0TdvI3A28D3g5r2ZbYeeNwW+P9EIJWkRSZ6e5JvtyKRnJXlbkt37ljsylqSpVVXPqKpdehNNi6rPt8+/gnUxaW6ZpJI0d6pqC/AR4A1J9mxHkXkW8E7gJOCgJIck2QM4CjgTOLWreCVpiJ8BDwWuQnO78q2BI8CRsSTNPOti0hwzSSVpXv0JTX8HPwQ+B5wAvL6qzqC50HsdTcuqQ4HDq6o6ilOSrqCqjq+qbwKXAFeluRXma+1iR8aSNLOsi0nzbeNqNk6yC/BxYENV3bmddxjwd8A+NNnux1bVN1YZpyStqao6B3jEiGXHA8dPNiJJWpGtwAbgSVX1mXbeFUbGStIbGetrV9yFJHWrqo6jaQHae21dTJpTK25J1d4b/B6aX+5682xeLkmSNCFVtStNB8RPS/LQdrajlEqSpJm0mtv93gh8F3hD3zybl0uSJE1QVX2f5kfCXpLKUUolSdJMWlGSKsnLgR2q6tkDi67QvJxmFK2brDhCSZIkbc+VgIva545SKkmSZtKyk1RJjqCp6DxuyOIlNy9v92UTc0mSpGVK8t4kt0myS5I7Ao+n6YYBHBlLkiTNqJV0nH4AcDBwQdvV1AZgQ5JtwL+wxObl0DQxB44F2Lx5s6M1SJIkLc1FwPuBq9O0Yn9uVX0QmpGx2h8VX8fCQDaOjCVJkqbesltSVdUzqmqX3kTTourz7fOvYPNySZKksaqqR1fVflW1a1XdrKreNrD8+Kq6QVXtXFW3r6qvdxWrJEnSUq2m4/RhbF4uSZIkSZKkZVvJ7X4j2bxckiRJkiRJK7HqJFVVHUcz7HHv9fHA8avdryRJkiRJkubHWt/uJ0mSJEmSJC2bSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjpnkkqSJEmSJEmdM0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkqSJSfL0JN9MsjXJWUnelmT3vuWHJTktybYkX0xyiy7jlTQ5JqkkSZIkSZP0M+ChwFWAWwK3Bo4ASLIvcBzwFGAT8CHgfUnSSaSSJmpj1wFI0rw58NBDuw5BkiSpM1V1PECbeLoqsDPwtXbxg4FPVtVH2nWOAZ4J3KpvHUnrlEkqSZIkSVIXtgIbgCdV1WfaeTcBzuitUFWXJjmtnW+SSlrnvN1PkiRJkjRxVbUrcADwtCQPbWfvBlw4sOoFwB7D9pHkyCSnJDlly5Yt4wtW0kSYpJIkSZIkdaKqvk/TB1UvSbUV2GlgtZ1pElXDtj+2qjZX1eZNmzaNLU5Jk2GSSpIkSZLUpSsBF7XPvwfcvLcgyQbgpsD3O4hL0oStKEnlkKGSJEmSpJVI8t4kt0myS5I7Ao8H3tMuPgk4KMkhSfYAjgLOBE7tJlpJk7TSllQOGSpJkiRJWomLgPcDvwbeCjy3qj4IUFVn0Fxbvg44GzgUOLyqqptQJU3Sikb3c8hQSZIkSdJKVNWjt7P8eOD4CYUjaYqsKEnVxyFDJUmSJEmStGqr6jh9tUOGOlyoJEmSJEmSYA1G91vNkKEOFyqpa22Hnf+Z5LN98xz8QZIkSZImbNVJqpZDhkqaOW359B6aRHpvnoM/SJIkSVIHVpSkcshQSevEG4HvAm/om/f7wR+q6nzgGOCaNIM/SJIkSZLGZKUtqRwyVNJMS/JyYIeqevbAoisM/gD0Bn+QJEmSJI3JipJUVfXoqtqvqnatqptV1dsGlh9fVTeoqp2r6vZV9fW1CVeSVi/JETS3IT9uyGIHf5A09ZI8L8m3k2xNcnqSZw4st289SZI0c9aqTypJmiUHAAcDFyTZBrwJuGP7fAcc/EHS9Cualut7AQ8EnpnkELBvPUmSNLs2dh2AJE1aVT0DeEbvdZLHAI+tqjsneQpw375lDv4gaepU1TF9L/83yWeAA4GP0te3HkCSY4Bn0vSt97UJhypJc+/AQw+9wrxTTzxx4nFIs8CWVJJ0eQ7+IGmmtMn0zcC32ln2rSdJkmaSSSpJ6uPgD5Jm0Mtpkukfal/bt54kSZpJJqkkzb2qOq6q7tz32sEfJM2EJM8BHgQc2raYAtiKfetJkqQZZJ9UkiRJM6btBP1lwCHAXavql32Lv4d960nSVLOfKmk4W1JJkiTNnncBt+WKCSqwbz1JkjSjbEklSZI0ex4OXAqc1TSqAuD0qrpRVZ2RpNe33j40ySn71pMkSVPPJJUkSdKMqapsZ/nxwPETCkeS5taw2/YkrZy3+0mSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSZIkSZI6t65G9xs1ssKpJ5440TgkSZIkSZK0PLakkiRJkiRJUudMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkqSJSfK8JN9OsjXJ6UmeObD8sCSnJdmW5ItJbtFVrJImyySVJEmSJGmSCjgC2At4IPDMJIcAJNkXOA54CrAJ+BDwviTpJlRJk7SuRveTpPVkcMRSRyqVJEnrQVUd0/fyf5N8BjgQ+CjwYOCTVfURgCTHAM8EbgV8bcKhSpowW1JJkiRJkjqRZAOwGfhWO+smwBm95VV1KXBaO1/SOmeSSpIkSZLUlZcDZ9Lc1gewG3DhwDoXAHsM2zjJkUlOSXLKli1bxhelpIlY0e1+SZ4HPArYj6ZAeW1VvbJv+WHA3wH7AKcCj62qb6w62hUavGWmn7fPSJIkSdLkJXkO8CDgrm2LKYCtwE4Dq+5Mk6i6gqo6FjgWYPPmzTWmUCVNyEpbUtnRnSRJkiRp2dJ4OfAImgTVL/sWfw+4ed+6G4CbAt+fbJSSurCiJFVVHVNVX6iqbVX1v0Cvozvo6+iuqs4HjgGuSdPRnSRJkiRpvr0LuC1XTFABnAQclOSQJHsAR9HcvXPqZEOU1IVV90llR3eSJEmSpGV4OHBX4Kwkl7TTDwCq6gyau3ZeB5wNHAocXlXeyifNgRX1STVgWEd3g9nwoR3dJTkSOBJg3333XYNQJEmSJEnTrKoW7Qqmqo4Hjp9QOJKmyKpaUvV1dHfoSjq6q6pjq2pzVW3etGnTakKRJEmSJEnSDFtRksqO7iRJkiRJkrSWVtqSyo7uJEmSJEmStGZW2ifVw4FLaTq66807vapuVFVnJOl1dLcPTXLKju4kSZIkSZI00oqSVHZ0J0mSJEmSpLW0qo7TJUmSJEmSpLVgkkqSJEmSJEmdM0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6tzGrgOQJEmSJGneHXjooZd7feqJJ3YSh9QlW1JJmjtJnpfk20m2Jjk9yTMHlh+W5LQk25J8McktuopVkiRJkuaFSSpJ86iAI4C9gAcCz0xyCECSfYHjgKcAm4APAe9Lkm5ClSRJkqT5YJJK0typqmOq6gtVta2q/hf4DHBgu/jBwCer6iNVdT5wDHBN4FbdRCtJoyW5cpLXJnnnwHxbhEqSpJljkkrSXEuyAdgMfKuddRPgjN7yqroUOK2dL0lTI8mDgHOAJw3Mt0WoJEmaSSapJM27lwNn0lzEAewGXDiwzgXAHoMbJjkyySlJTtmyZct4o5SkAVV1UlVtBF48sMgWoZIkaSaZpJI0t5I8B3gQcGjbYgpgK7DTwKo70ySqLqeqjq2qzVW1edOmTeMNVpKWzhahkiRpJpmkkjR30ng58AjgrlX1y77F3wNu3rfuBuCmwPcnG6UkrdiSW4RKkiRNE5NUkubRu4DbcsUEFcBJwEFJDkmyB3AUze2Ap042RElasSW3CPW2ZUmSNE1MUkmaRw8H7gqcleSSdvoBQFWdARwBvA44GzgUOLyqqqtgJWmZltwi1NuWJUnSNNnYdQBdO/DQQ4fOP/XEEycah6TJqapFR7iqquOB4ycUjiSttZOAY5IcAvwXzSh/tgiVJElTb+6TVJIkSbOoTUK9g6YPqh2SHAw8u6rekqTXInQfmuSULUIlSdLUM0klSZI0g6rqo8DeI5bZIlSSJM0c+6SSJEmSJE1ckisneW2Sdw7MPyzJaUm2Jfliklt0FaOkyTJJJUmSJEmaqCQPAs4BnjQwf1/gOJr+9DYBHwLel2TRPkUlrQ8rTlKZ9ZYkSZIkrURVnVRVG4EXDyx6MPDJqvpIVZ0PHANcE7jVpGOUNHkr6pOqzXq/nybJ9e6++b2s98NoRpN5Kk3W++Z21ilJkiQYPbryJDmSszS1bgKc0XtRVZcmOa2d/7XOopI0EStKUlXVScDGJEcDN+pb9PusN0CSY4Bn0mS9LVAkaRWGXdR5kSVJktaZ3YBfDsy7ANhj2MpJjgSOBNh3333HG5mksVvrPqmukPUGellvSZIkSZIWsxXYaWDezjSJqiuoqmOranNVbd60adPYg5M0XmudpNoNuHBg3qJZ7ySnJDlly5YtaxyKJEmSJGnGfA+4ee9Fkg3ATYHvdxaRpIlZ6ySVWW9JkiRJ0kqdBByU5JAkewBHAWcCp3YalaSJWOsklVlvSZIkSdKi2iTUWTRJqMOTnJXkz6rqDOAI4HXA2cChwOEOxCXNhxV1nL6Ik4BjkhxCM7rfUzDrLUmSJEnqU1UfBfYesex44PjJRiRpGqwoSdUmod5B0wfVDkkOBp5dVW9J0st670OTnJrJrPdiQyM7mpYkSZIkSdLaWlGSyqy3JEmSJEnjM6zhhA0mtN6tdZ9UkiRJkiRJ0rKZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1LkVdZwuSZoOi41E2s9ONiVJkiRNO1tSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjrn6H6SJEmSJM2AYSM7O4qz1hOTVCswash3CwdJkiRJkqSV8XY/SZIkSZIkdc4klSRJkiRJkjrn7X6SJEnSCozqAmKpVttVxGrffy1ikCRpLZmkkiQBdsQpSZIkqVve7idJkiRJkqTO2ZJqBi3WtNtWD5IkSZI0v2wdr1lmkkqS5sBa9FsiSevJNJSL0xCDJEnTxNv9JEmSJEmS1DlbUkmSJmIpLQa6aIpuk3hJkiRpOpikWkP2FeU5kCRJkiRJK2OSSpI00rS2MlpKXNMauyRJkqThxpKkSrIP8FbgrsA5wDFV9dpxvJckjYPlmKRZZhmmpVoPnbdPww8Qa3Eep+E4ponlmDSfxtWS6i3AD4H/D7gp8JEk/1NVXxjT+2k7pvk2vJXEtpYVqq6PH0Yfz1rHNqn3WScsxyTNMsswSbNubOXYPLa2nnRCeqUt3Ffah+ngdvP495zkMY/z/dc8SZXkKsA9gb2r6lzgS0neDTwUsGIkaepZji1u0h2gT+uv/F1XDqbJOCuGS/37z+u5H8YyTNKssxyT5tcOY9jnjYDz28Kk53vATcbwXpI0DpZjkmaZZZikWWc5Js2pcdzutxtw4cC8C4A9BldMciRwZPvyt0m+u8h+9wbOWpMIO5BktbtY0vGv5H3WILaxvU+7zVj/9pM6/pWYxPH3vc9SfayqDh5XLFNiSeXYMsuwfjNdni3FSr9XSVZ8bpbynkuNaxXxr2i7JZipz8yEy9W9gbMsxy5nXHWxrs3S98BYx2NorFNal1v2eV3Gcaz3Mgw6KMdW+Tnq9Hu0wtg7v8ZaQdxL/p8/ReXCxD4ba3jMK4p5repi40hSbQV2Gpi3M02hcjlVdSxw7FJ2muSUqtq8+vBm0zwf/zwfO3j8HVlSObacMqyff9PRPDfDeV5G89wMNZa6WNdm6W9trONhrHNlpsqxWfx7G/NkGPPyjeN2vx8AeybZ1Ddvf+D7Y3gvSRoHyzFJs8wyTNKssxyT5tSaJ6na+4Y/Dbw4yVWSbAYeAfzrWr+XJI2D5ZikWWYZJmnWWY5J82scLakAHgvcGPgVcBLwoqr67Cr3ORNN0cdono9/no8dPP6ujKMc6/FvOprnZjjPy2iem+HGWYZ1ZZb+1sY6HsY6X2apHJvFv7cxT4YxL1Oqqsv3lyRJkiRJksbWkkqSJEmSJElaMpNUkiRJkiRJ6pxJKkmSJEmSJHVuY9cBDJPk9sBDgZsAewAX0Aw3+q9V9fkuY5Ok5bA8kyRJWh+s10njN3UtqZL8OfBhYEfg48DbgQ8BG4APtMslaepZnkmStHxJNiR5dpL/SXJ+kkuT/DbJV5M8N8nU/NA+S7FqdWa1XudndDI8z2tn6kb3S/IT4CFV9d9Dlm0GTqyq60w+sslIsgF4JgsZ+t2AC2ky9McDf1dVl3QX4fgluS5wKFf8heLEqjqjw9DGbp6PfT2a9/JsMZZ1i7MsGM7zMl+S3JKBv3VVfa3bqK5olsqzWYk1yT8BtwZeAXyP5u+/M3AATfxfq6ondBfhglmKVaszq/W6WfyMzkpZ1W8Wz3PPtNWvpjFJtRW4RlWdP2TZlYFfVdWuk49sMmb5w70WkjwEeBtwMpc//v2BuwFHVNUJnQU4RvN87OvVvJdni5n3sm4xlgXDeV7mR5IDgPcB1wROY+FvfVPgV8DhVfWN7iK8vFkqz2Yl1iS/Bg6oqp8PWXZt4JtVtefkI7uiWYpVqzOr9bpZ/IzOSlnVbxbPM0xn/Woak1QfA34APKeqfts3/2rAS4AbV9W9u4pv3Gb1w71Wknwf+Iuq+uiQZfcFXldVN5p8ZOM3z8e+Xs17ebaYeS/rFmNZMJznZX4k+TzNLTXHVNVlffN3AJ4NPKiq7tBVfINmqTyblVjbOPevql8MWXZt4NtVdZXJR3ZFsxSrVmdW63Wz+BmdlbKq3yyeZ5jO+tU03hd5BPAW4Jwk59E069sJ2BP4NPCnHcY2KYtlDqeuH7E1dh3gMyOWfRbYZ4KxTNo8H/t6ZXm2uHku6xZjWTCc52V+HAjcuz9BBVBVlyV5DfDXnUS1uFkqz2Yh1vcA70/yN8AZLPz/vDlwFPDeDmMbNEuxanVmtV43q5/RWSir+s3qeZ66+tXUtaTqaZtM3ojm/tOtwA+q6rxuoxq/tmnjgcCoD/fXq+rIzgIcs/bX0w9W1TED8wM8F3hwVd2+k+DGbJ6Pfb2b1/JsMfNe1i3GsmA4z8v8SPID4M+r6uNDlt0XeH1V3XDykQ03S+XZrMTadjD8TOBwFvqj2UpzK8r7gFdV1cXdRbhglmLV2pi1et0sfkZnpazqN4vnGaazfjW1Sap5Nasf7rWSZH+a47wa8BMWCqQbA78E/qiqvtldhOMzz8eu+TPvZd1iLAuG87zMjySH0fSP8Qkuf3HS3z/G+7qL8PJmqTybpVglzS/LqsmZxvqVSSpNpXZEnxvTVyBNUyep4zTPxy5pgWXBcJ6X+dCONPRgFi5OLqC5OPlgVf24y9g0OUNGePxeVX2926guL8mhVXVi3+t9gLsAW4DPVdW2rmKTwM/opMz6eZ6m+pVJqik1C/+UJWm1LOskDUryb1X1h32vnwYcQlPRf9ewzl2nwSyUZ7NyETVLIzwm+V1V7dQ+vzdN3D+i+RxsAA6uqu92GKLm3Cx/RmehXO2Z5fM8bUxSTZlZ+qc8Dkk20DTtfCgLv55eCHwfOB74u6q6pLsIx2eej13zZ97LusVYFgzneZkfAxX9vwEOA46lqeg/Efirqjquuwgvb5bKs1m5iJqlER6TXFxVO7bPvwS8qare3L4+CrhHVR3cZYyab7P4GZ2lcrVnFs8zTGf9yiTVlJmlf8rj0HaSd2vgFTTN+nsF0gE0X56vVdUTuotwfOb52DV/5r2sW4xlwXCel/kxUNE/HTi0qk5tX98OeFtVHdBdhJc3S+XZrFxEJdkKbKqqC4Ys2x04q6p2nXxkVzSQ+DsXuFZVbW1f7wL8oqr27DJGzbdZ/IzOUrnaM4vnGaazfmWSasrM0j/lcUjya+CAqvr5kGXXBr45jV/utTDPx675M+9l3WIsC4bzvMyPgYr+VmCP3kVKkp2AX1fV7l3G2G+WyrNZuYiapREek1wC3BvYgeaievequrRddh3gq1W1qcMQNedm8TM6S+VqzyyeZ5jO+tXGSb6ZluTnwJ2BK/xTbudf4cOzDi2WOd1hYlF0Y56PXfPFsm5xlgXDeV7mw4YkbwdCU1fdDfhtu+yWNP0nTZNZKs92SHJ3mu/LzsBFfcv2BqblltmjgOOTjBzhscPYBv0UeGv7/BfAtdp50Nw+87UugpL6zOJndJbK1Z5ZPM89U1W/Mkk1fWbpn/I4vAd4f9sHRf/x35zm3Ly3w9jGbZ6PXfNn3su6xVgWDOd5mR8v7nv+t8AuLCSpDgfeP/GIFjdL5dlMXERV1fuTfJmFER6vSjPa1MdpWlhNzQiPVXW9RRb/O/BvEwpFGmpGP6OzVK4CM3ueYQrrV97uN4XmedjlJBtp7n09nIXj30pz/O8DXlVVF3cX4fjM87FrPs1zWbcYy4LhPC+aZkPKs95n86RZKc+SHAicW1U/6joWSZq1emKSH9J08v6iqvps1/Es1TTWr0xSTZlZHXZZkpbDsk7SvEjyp1X1tq7jWIppirXte+pA4JvAh6vvoiXJ96rqJl3FNqgv1m8BH5rmWDWfZu0zOov1xCQXA08C/prmPD+/qr7cbVSzySTVlJm1YZfHJcktaTK5e9Bmzavq691GNV5JDq2qE/te7wPchaYw/lxVbesqNmmtWdZt3zyWg4uxjNSsSnJmVV296ziWYlpiTfIMml/2PwNsphly/tCqOrNd/vtRCrs2ItYHV9WWdvnUxKr5NIuf0VmsJ/ZiTrIz8BSaUQi/QJOsmvr62zTVO01STZlZG3Z5rSU5gKZZ4TVpmkv2hsC8KU2BenhVfaO7CMdnoDC+N815+BFNQbEBOLiqvtthiNKamfeybjHzXA4uxjJS06rt5H0xh1fVbhMJZjtmJdb2tpkHVdU32iHnXwE8ALhLVW3pLw+6Nkuxaj7N4md0FuuJg+cxyZVo+nT6C+ATwAuq6jtdxTfKNNY7TVJNmVkbdnmtJfk8zZCdx/SOu52/A002+kFVdYeu4hungcL4S8CbqurN7eujgHtU1cFdxiitlXkv6xYzz+XgYiwjNa2SvBZ4AvCSEas8q6r2mGBII81KrEkuAPasqt/1zXsO8DDgrsDZ09LyY5Zi1Xyaxc/oLNYTRyX7kmwCng/82TSUr4Omsd5pkmrKJLkUeBfNsMv/H7BXVf22XXYb4IRafOSAmdYWQpuq6oIhy3YHzqqqXScf2fgNFMbnAteqqq3t612AX1TVnl3GKK2VeS/rFjPP5eBiLCM1rZJcmUUu8pJsqapNEw5rqFmJNcm3gD+tqi8NzH85cBvgrtPS8mOWYtV8msXP6CzWE7d322SSfWs6O3yfunrnDpN8My3Ji2ma2f2AhWGXe6Zx2OW19nPgziOW3bldvl7tkOTuSe5J08Tyor5lewOXdBOWNBbzXtYtZp7LwcVYRmoqVdV5NP2ljPKoScWyPTMU6zuAgwZnVtWzgTOBjZMOaBGzFKvm0yx+RmexnnjDxRZOY4KqNXX1TltSaaokOQx4G819u2cAFwI7AfsDdwOOqKr3dRfh+LT3W/d/Ie9SVT9tl/0lcL+qulcXsUmanHkuBxdjGSlJkrS2prHeaZJKUyfJdYEH04wusBuwFfgecNIUZ6DHKsmBwLlV9aOuY5E0fpaDy2MZKUmStDLTVu80SaWZkuRPq+ptXcfRhXk+dkkLLAuG87xIkiStrS7qVyapNFOSnFlVV+86ji7M87FLWmBZMJznRZIkaW11Ub+axk7SNMeSvH07q0zdsJ1rZZ6PXdICy4LhPC+SJElraxrrVyapNG3OA54AvGTE8ssmGMukzfOxS1pgWTCc50WSJGltTV39ytv9NFWSXBk4u6p2HLF8S1VtmnBYEzHPxy5pgWXBcJ4XSZKktTWN9asdJvlm0vZU1XnAYYus8qhJxTJp83zskhZYFgzneZEkSVpb01i/siWVJEmSJEmSOmdLKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmaO0l2SfLCJN9McmGSi5L8MsmRXce2XiV5TJJKYmeY0hglOa79rp084fe9Xu87nuSgSb63pJVJcnT7nT2961ikHpNU61hfoVNJzk+y13bW3ynJz/q2OW5CoS4W09TEIs2CJFdK8uQkH0nykyTbkpyb5LtJ3pLk4K5j7FqSHYFPAkcD+wO7ABuBawDX7i6yxSU5vS0Pj97Oen/Q/s0ryaeS7NK3zDJVM2+gftM/XdiWex9L8vgkO3cdq1Yuye5t/bX39339Gu//ZMtDrQdJ9kvyN0m+kOScJBe3350zknwiyTFJ7pVk4xq/b69ecvJa7neFsVwnyV8l+Y/2evaiJL9N8oMk70/yxCTX6jpOLc2aflA11fYAngq8cJF1Hs30XaBd1D5e3GkU0gxI8gjgNcDV+mZfBuwMXBm4CXBEki8AD6+qMyYf5VR4BHBn4FLg8cD7gPNoyr8NHca1akluDnyc5u/9OeDBVbWtbxXLVK03F/U93wW4TjvdF3hCkvtV1S86iUyr9RCa+mvPw5I8rap+11VA0rRJ8jTgGJryr+cymu/OHsC+wL2B5wDfBG6xhm9/UTt19p1MshPN8T8Z2Klv0WXt6xu20x8C/5jk3VX1mEnHqeWxJdV8OLd9fEqSKw1bIckOwLPal7+ZRFBLUVW7tNPjuo5FmmZJngq8iyZBdQZN8mVfYEdgV2Az8I80yYk7AF9OcsNuou3cfdrHE6vqLVV1bjV+VlU/7jSyVUhyPZoWYnsDpwD3q6oL+texTNU6c0bfZ3oXmrLuFsA/AAUcCLyzu/C0So9uHz9M8/fcE3hgd+FI0yXJk4G/p0lQ/QfN9+MaNA1RrkRTHj4J+Pd2k6uu5ftX1U3b8vc+21977bWtZT8J/CVNQupTwIOAq1XVBpok3f8Bngn8gKZOfGgXsWp5TFLNh1NpflHfE/jzEev8IU0ri88CX5tMWJLWQpLNwCvblycDt6yqY6vqJ1V1WVVtq6r/qaqnAfcEzgc2AccnmemWQyt0zfbxe51GsYbaJuyfAvYBvg7ct6rO6zYqabLasu6bVfV04BXt7Hsk2b/LuLR8Sa4D3L19+Tc09VNYSFxJc629lf8l7cv3Afesqg9V1ZntD2+/bcvDf6qqe9Ikaz47coez6TXAXdvnT6+qe1fVB6vqHICquqCqvl5VrwJuBjwB+G1HsWoZTFLNj2Pax6cn2W3I8me3jy8dtYOl9Ieyvfv7kxzS3hf8syS/a++X/t8kb0rygLZF13Lf835JTui7//g3ST6f5LlJpu32RWkcXkzzq9mZwOFVdf6oFavqv4C/aF/+Ac3tFMAVO71tX78yybfavl7Obfs4uvvQnS/sZ8e2P5j/SHJW+13/RZIPrGWfWEk2JnlcW+6c3X7/f5zkHUluM2T9g9J02n2PdtZzB/qzOW4FMVwzyauTfDpNv1+/afuCOLsth56f5KqrO9LtxrAXzS+JNwS+C9y7V0Ebsu7IMrXvPDwmydXT9Pvz1SQXtP06fD7J4duJZYd2+8+0n5dzk3w9yStpfgiRJuW9fc9vPmqlJAe3dYift2XVOe3n94lp+q8btd0OSR6Rpv+/X7Xbnt2We09pv5ek6SOw2vLp6ovsb6ckZ7brPmvI8v2S/H2awR7Ob8vk77X1pzst8Zz07+/mSd6Ypr+WC9t9fi3J3ybZezvb3jVNXe7MJFuTfD/JO4GDlhvHIh5Jc53yg6r6Igst4g5JsmmR2C43QEOSW6bpj/EnSS5Jcl6SR7bL79Zu9ie5Yv9mj1nDY5HGYX8WWka9raoWHZSkTdY8bLlvkuTaSX7Yfi++nuRqfctGXvf11zeSXDnJM9L0mXVeW258NckTlhtP3/73Bx7bvnxtVf3DYutX1aVV9UbgtgP7uW+Sf07y32nqkBe20xlJ/i3JYYvE0H+MO7f/Nz7f1pkuTvKagfUnUj9eF6rKaZ1ONJ0CF3By+/rU9vVTB9a7Rzv/K+3rk9vXxw2sd3o7/+hF3nPUtgHe1C7rTZcOvC7gIUt9T2A3ml8OFtvnJcCVu/5bODmNawKu2/d5/6slbhOaZs8FfKJv/vX69vVvNP0MDPtuXULT19GwfV8H+OrA9/CygdevXIPjvhrw+UW+/5cBRw1sc1dgW188l7ave9ObVhDHnYeUY4Pl0I+B/dbgmK9QHtI05//vdv5pwD7L3Uffsl68H6Hpo2vU8Tx5xL73AD6xhHK+uv7eOM32xEL95vRF1rlp32fuAUOW70xzi/RiZdVngN2GbLt3u2yxz/qZ7bpXpvnlvoDnLBLvw9t1LqS5VaV/2aPbMmpUnAU8qW/94+ir/w15r6fSlOOj9vdT4GYjtj1mKd9x4KBV/o2/1e7nhe3rq/adg79YZLvH9MXwmr74Lus7zu39L9gGPKrrz7mT02ITTbKl91k/YhX7GVmetmVd77v4LeDqA8tPZsh1X7vs9F45BPxykTJjRXVC4LXt9luBvVdx/G9eQpn29hHb9o7xQ8D3+9bvla/H9a07kfrxeplsSTVfXtY+PitNJ3M9z2kfR7aiWgN/TJPtvoym8/br0LT8uDLN7Uevp6nEZRn7fCtNK5CLgRcA163m/uO9gMNo7r/egC0Gtb7dre/5vy1lg2r+W57YvrzTiNYChwLfAB5K8z3dEbgjTSJkA/CaDNwqmKaV5kdp+oH5b+AQmgrOjsANaMqYS4FnbK9FzmKSBHgPTd9avwaOoLmA2QjcmKZsCPDyJL//1bCqPlNNvzWfaWe9o/r6s6mV9dO0DTgJOJKm74crtXFsorlYOp8mkfiqFex7UWma+p9EU1H9CU1T/5+twa4PAX5Fc173pjmeWwJfbpe/LMlVhmz3JprOWbcBzwCuzsKoiQ+hqahKk3KzvuffH7L89TSDKPyMpn7Sq5dcq329BbgLC7cNAk0LTpqy9i403++n0Fy4baC5lfhRwP/QduBbzW2372o3P7Itv4Z5Yvv4nqo6u+/97keTdNqZJgl8+3bfO9N89/+B5iKtv143UpJHttv8jqZMvnG7rz1pOpv/Gs1tw8cPxprk8SzUGY9tt93YbntX4C1LiWEJMd6WhdZv7wSoqt/Q9E0FS7/l7yntNndmYRTX6wNf2s7/gl2q6h2rPxJprL5J8/8WmpbhN17Lnbf/5z9B8138HnCPqjpzBbu6G83139NofkjbQFMn/Gi7/C+TrKSl9T3bx3+vqrNWsH3PT4DXAfenKR92pqm37k9TzgE8KskDFtnH/WnqoU8HrlVVvT7BXgCTqx+vK11nyZzGN3HFllQbWMjyHtnO+4P29XeAHdp5JzMkK87qWlK9v53/sUW2vSZww6W8Jwutvwp4xCL7PJwhv4I6Oa2XCfjb9nuwrfcdXuJ2j+z7Dt2wnXe9vnkvG7Y/mv7reuv8wcCy57bzPwfsPOJ9X9ZbZxXH/EAWfoG604h13sJCi4AdB5YNLafG9Pfpnedtg3GsYF+/Lw9pKjYfbF//ArjxcvcxZFnv7/qOYX8/4NZ96xw2sOyOfcv+aMR7P6a3zrjPu9P6nthOS6r2+9FrafnZIcvv0C7bAlx/xD4O7vvu7tE3/wgWfim/y4htQ19LHJoLk9734+Ah6x/Qt3xz3/yNwA/b+R8FNox4v+v3x8KIllTA7sDZbdn5wBH7uibNADpFc+twb/4e7bYFvG7EttfrO46DVvH3/X8M+T/B5f//7D9i28f0rbNoaygm+L/AyWkcE01yo/d5v5imb8q/br8rN2YJ9cJh5WlbVny2nf8DRrTSXuw7xEJ945PAVYYs35uFFkd/uczj3sBCK6S/HvM5/lT7Pm9Z5Bi/wEArs4H1JlI/Xk+TLUzmSFVdysIvgs9pfw3s9UX1sqq6bAJh7DXqV8Sq+mVVnbbE/RzRPv5PVb171EpV9b6q2rrcIKUZslf7+Otlfof7f3W62pDlHxuxv//uez44OmCvJdLfVtVFDHdi+3i7gRady/HI9vHfq+pzI9Z5cfu4Dwu/tnXhS+3jzjStq9bCDsDbgd6ves+sqmEtRVbq0yP+fqeyMMz04N/+z9rHr1TVv65hLNKSpOkj6mpJ7kvTkvoONKMb/8WQ1Xtl1duq6kcjdvkJmhZKvRZLPb36x4nV9PF3BdV4R9/rU4Evti+H9cHSa0X131V1St/8g2gSUADPautxw97vR6NiGfAQmv8Zp1TVB0fs65d9sd65b9Efttv+juYieCzalr29FrCDrZk+DPT629tua6qyNZTWvxfQDJxzCU1S+57Ai2gaB3wPOL/t/+ipI1pAX0GaEfNOBO4E/Ai4e62ulfbnqurcwZnVtH7qlb/LHW36aizcfbNlFbEtRa8ed91F1vl4Ld7KbFL143XDJNX8+Weapu3XpynYHkIzXP27FttoDXyqfbwt8IkkD8vqOjW/Y/v48dWFJc2t/mRxLWO7X/c9//0gDO33uXcx9W9Jtg2bgP9s19lIX3IsySdGbZPkuwMx3L59/AwjVNUZNGVb//pLskgc25K8acQ2d0zy0iQfTvKNtsPNc2ia4/fsNLDNdxd5n08sEuKfs3ARB/CqJDdYzjGuRDU/9fUqmoMDcNylfVwsbmmt7ZeFTrIvpUm+f4wmufI1mltgvzJku97n9emLlFVbWficXxN+f6vf7dp5y61//FP7+IAk+/RmJtmd5hZBaG456der6/y8qr6xzPcbpnfct1msnKO5bRcWRkLt3/Yr1Xc74hjcn6aFxe+A4/sXVNXvgF4S/JEZGGxHmjfVdAb+LJpWUy+gSdD3/wi5G02y+x+A7ye5z2L7a8u49wL3oulP8x5V9ZO1j/z3enXKYYN6LdVy6rBDJdkjycPTDETxubZ+9vMk59G0goIl3lI9ZN+rqh/Pq41dB6DJqqrfJXk1Tf8ovV/C/q6qLh7zW78JuA/wYJqC714ASX5B08/JCcC/LCOOXsXpx2scpzRrehcLeyZJm0hYir36ni/5gqOqtvY1huxPdO3T93yp/8h3Hthm5yWsB00fR9B0xLmYXwD79a2/VKPigOY2ot9rLzbfxeX7But3yXbeZ9R7LXYO96JpMv4Kmgu2awAfS3LHWl2/DEvRa5k62CK296PDGUiT1f+r9I40P8CeRXNxNXSUSxY+rxtZWl249z3di4UyYLn1j+OBV9NcfDyO5hYbaPrsvDJNzO8d2Gat6zq9496Bxcu5nv51JvUd77WQ+g9gh1xxpMGPAI9noZXsJ8ccjzT1qup04G/aiTQjYN4auA1NP72baVpzvz/J/lU1rEzZgeZW4Qe3r5/U7necRtUptuccmuRUWGUr9TSj9/0TTT+ag3q3Ui43vn6rrR/PJX+BmE9vZOGi9FesUUeXi6mqi6vqUJq+pP6JpnXBZTQdlD6IpoXXF9IO2bwEvcJi1dlzacZ9p33cmUWGWR/iwPbxAppOI1ervxP1/asqS5hO721QVQctst71VhhTBh6XZDsxP+b3O29+cfwETYKqaC4wH0bTyXivw/GRHZlW1fUWeZ+DFgnxa8D9q+ok4E/b974x8KG2c84u9CpeiyXlpLV2RvV1dk3T8ffFNN+/Exa5ZaJXXj1piWXVce36K22BSlVto7kABHhsFgae6N3+9+Yht4GsdV2n957HL/G4H9O37di/420d8P7ty/vS3MYzOH2gb5OldqAuzZWq2lJVn6iqY6rqtsAz20W70yTGh7luu6x3W/E/9bf6nCZVdQkLtwr+35XuJ8ldaH5AuDpwJk0/r/cGbgRcqap2AF6yumhXVz+eVyap5lBVXUDTKSXAq9uK05I2bR83LLrW4u/9H1X1pKrqjYJ1EE3S6jKabP+Llrir3n2/i90fLM2Dk/ue/+FSNmj7hev9UvbZNWpJ2X8v/nL7Fljpe23vluFrtY+/GlMc96MZ/QXgYVX1sKp6b1V9o6rOHtV/zBo4sde/QzV98j2rnX97mhG5VlxGr0Kvyf5gqwdpYqrqUywkfQ4CjhvRD2avDFluWXUOCxdwK6l/vIGmLrUP8MAk/5emtcNl7bJRca5VXWelxw2T+Y4/jOXdUvOHSfYYVzDSOvJqmh8loRngYJSTaK7HzqEpdz6W5KpjjWzlPt0+3j3JsFZQS/F0muvaHwMHVNXzq+pTVXVaVf12TaKcbP143TBJNb9eQpMkeuUytrmwfVxqa6dFVdXWqvrPqnoS7RDDXL6TzsX0hkK/71rEIs2qqvopC32jPCXJUu5j/2MWWvgM7WNpBX7Ewj/icQ+f2+u8/e6jVmj7aNp3YP21dtP28ddVdfyia45RVb2KpgIKTSuEYRe749bre+vWHby39HtV9VaaEa8AHk4zYtKgXke4hy4nqdsm9E9tXy67/lFVP2Dh9rQnsJBQ+1Dbj96gXl3nOkn2H7J8uXrHfesky71Y6n3HDxw1AM4a6LWMeutirQyAm7Xr7U7Tt+pK9VqFzf2tNZo9STYt80ep3g+Sozoa/xVweFV9jWYU5QuBWwAnJdll5ZGOzVvbx11pWkAtSZL+vvZ69bgTxthdwiTrx+uGSao5VVWXVdVva3mjgfVG3hs6UlaSW9M0jxy27IlJrrzIvi8eeNyef2kfb5vkoaNWSnLIEvcnzbK/pqlsXwN4X5IrjVoxyZ1Z6Jz3f4B/W4sA2r6w3t6+fGSaEbZGxbBDkgeu4u16Az3cNcmokfuObh9/ycLADWut1wp1jyS7jlhn85jee9AzWSgXH5vk6Am9b89H28cHDFQAAWgr0reZbEiaY88H3tM+PyrJkwaWH9c+3pCFsmKoJAenGe2qp/c9OyzJHYdt09tuxKJeB+r3YWEAhMEO03s+zcLFzStGdRSe5FpJ/s+oWPr8K00fMDsAxy5yOyRJbjKQGOt9x6/Bwsiig5Y1SMXg+/Vtv+hgPlX1XaA3CuKfrPQ9WbhY/4NV7EPqyv2BzydZSj3jT4Crts9PHLHOtl7L+qr6PE2S/1KaQRP+paNW2iNV1RdpRjGEpt7znMXWT+NRLCTrYaEeN7QlVpucO2CVcU6yfrxumKTScpzUPt40yYuSXLn9Mu2f5DU0v/iNunf58cCPkrw8zShYu7WFxTWSPIWFkW2W2hrh/SyMgvCOJM/r3TedZK8kD0zyQZoONqV1rar+m4Vbvg4CvpHk8Umu235Hd07yB0n+gWbklyvTXPg8dJmJ6u05huYXow3AB9OMdnezNoad2ufPAL4LvHAV73MSC7c5vj/J45JcpS1Tbpzkn1koU46qZkSocfg4zW06OwLvbN97Q5JdkxyU5AMsjEQ1Vm0l6DEsNH9/YZLHjd5izb2Fpq/D3YAPJ7ld+3ffPcmDaBKiT55gPJpjfd+Hz7WzXtN+DnvLP8xC30bPT3J8kju0ZeUOSfZJ8ugkJ9MkZ/oHTPgnmr4ANwAfaX+E2xsgydXTjF78X4xu0fhB4Kc0/U3tDHyfEZ1/V9WFLIwsdX+acvW2bTmzS5IDk7yMpkzdbivGaoZI/6v25T1oLnAf1PsRsa0/3T/JO2haTt2gb9sv03RmDvDWJA9pY9gxye2TnMBCYnAlesmmn3P529hH6SWyDkqy76Jrjtb7fNwkyVFJrpbkSu053m+F+5Qm6XbAl5P8V5KnJLlV+383SfZOcuckb2Wh/+E3V9Upi+zv96rqAzSjCQMcCrx+zaNfvT8F/rd9fkyS/2zLpl6ZvFuSA5I8tV3v7cBV+rbvXSc+rC3L92y3u0aSI2jK+rVo/TSp+vH6UVVO63Si+XWwgJOXud3J7XbHDczfEfgCCyMd9IZ87j3/H5rK1rBtvziw3eC2RZOg2jiw3entsqOHxLk38Nnt7POirv8OTk6Tmmhu4ztnO9+JovkVab8h21+vb52DFnmf3jqPGbLshjQde/e/32Xt1D/v86s81k3tcYw61suA543YdmgZt8I4XrhIDJfStFTrvb7eKt9rZHnYt86VgK+2610CPGCp+1js77rE7Q+mGWlt2Lm4mL7/H11/V5xme2KhfnP6dtbbm4V6yQXA7fuW7U5T79he3eRiYLeB/d6AJomz2HbfXSSuv+5b72lLON7nDSnfBsvUh/etfxyL1P+A57Tlw/b+V9xnYLv9aPpuGSzfe88/0/f8oGX8PUMzamABr1ziNtfsO4bn9c1/zFLLGZofbH445LgLOLTrz7mT02ITTaL57BGf38Hv8yU0I7tvGLKfRctTmi5ievs5emDZyYyoT7G0OsvI7ZdxHq5Ek7QeLBMHy7iiqaO8uW/bK3PFOmv/uTsT+K9R5elSjrFv3YnUj9fLZEsqLVk1TUDvDbyc5p/6xcBvaG6l+WOabP7PRmx+T5pfyU6g+UJvoykEfk7za+YfVtVDqxmtYanxnEUzqtajaH7p/BXNF/084PPAXzK6ZZe07lTVu4DrA8+gGXXu5zT/pH8L/AB4B/Dgqrp9De//ZC1iOI3mFrdH07QY+DlNWXERTbnxHppfpe6xyvfZAtyJpk+Xz9CURZfQtFB4N83F6EtH7mCNVNWLgIfSJOJ75doPaVpR3JqmU86JqarzgUNY+MXuvUlWfAvOMt/7YzT/B95PU3Hujb5zLM2Ih2+cRBxST1tPuB8Lrfw+mORG7bILquqhNH3bvZ2mjNxK8x3+BfAx4EnAtapq68B+f0hz++qTaVoXnU1T/ziHprXqkSx+q+8P2scLgLct4TheSnNL2ptpkm7bgN+1z18PbK6qfxm9hyvs72U0o8H+PU0fW+f2xf95movWm1bVJwa2O4PmuF9HMyrsxTS3zP0bTR9dKx1t7yAW+hBc9Fa/vlh+SXOuWen7VtV5NH2hvo3mb34Jzd/yC6zNqLfS2FTVv9MMEPNAmgGxPkfTxcGFNMmOX9PcFvtKmk7Bn1ErGNClql7AQv9PL0zyhMXWn7SqOr+q/pimnvFKmvrYFhauCb9PM/ry44F9quqxfdv2yoBX0FyfXkrzf+CLwFE0iaVeC/XVxjmR+vF6kTazJ0mSJGnMknwOuCNwbFU9vut4JEmaJiapJEmSpAloOznujdp3YDUjaUmSpJa3+0mSJEmT0bsF+LMmqCRJuiKTVJIkSdKYJbk28Efty9d1GYskSdPKJJUkSZI0fk+iGSn5lzQDyUiSpAH2SSVJkiRJkqTO2ZJKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkqQpkeTKSV6b5J19866W5KQkP0vy2ySfT3Lb7ezn9CSXJrmkbzps/EcgSZK0ciapJEmSpkCSBwHnAE8aWLQ78N/AHYGrAf8KnJRke/W4+1bVxr7p/WsetCRJ0hpKVXUdgyRJklpJjgZuVFWPHLF8N+AC4NpV9YsR65wOPLaqPjWuOCVJktba1LSkOvjggwtwcnKa/klDWIY5Oc3UNOtuD5wFnLmd9T6S5PwkX05yn+3t1HLMyWlmJo1gOebkNDPTSBsXWzhJZ511VtchSNKKWYZJmoQkewJvBI6uqksXWfWuwC+AnYGHA+9LckBV/WRgf0cCRwLsu+++4wlakibE+pg0+6amJZUkSZJGS3IV4GPAx6vqdYutW1U/rqqLq+q3VfUm4EfAXYasd2xVba6qzZs2bRpP4JIkSUtkkkqShkiyXzua1m+SnJnkLUl27zouSfMpybWBzwD/WVVPWcEu9qC5RVCSJGlqmaSSpOHeA/wvcC3gQOAGwEu6DEjSfEpyI+BzwD9X1VFDlt8uyXeS7NO+vnWSZyS5bpJdkxxF08XDZycbuSRJ0vKYpJKk4W4JfLKqLqyqn9PcYnP9jmOStI4lOSTJWcBRwOFJzkryZ8CdgesBr0hySd/01+2muwE3BXZsX58L3A84FfglcC/g4KraOrmjkSRJWr6p6ThdkqbMK4F/aYeCPxn4I+BpHcYjaZ2rqo8Ce49YfNwi250MpO/1D4F7rmVskiRJk2BLKkka7hM0I2PdAfgycDbw9U4jkiRJkqR1bCZbUh146KFdh/B7p554YtchSFpjSa4KfAi4TVX9KMlf0LRieBPw//Wtt6Kh26epDNseyzhJwyy1HLMMkTSNuqyLWS5Ki7MllSRd0Y2ADVX1I4CqOg/4Z+BW/Ss5dLskSZIkrR2TVJJ0Rd8CtiV5UZLdk1yTpsXUxzqOS5IkSZLWLZNUkjSgHQHrEOCuNCNjfQX4DvDcLuOSJEmSpPVsJvukkqRxq6qvAHfvOg5JkiRJmhe2pJIkSZIkSVLnTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0zSSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSpKmT5G5JPp3kvCRbk+zZdUySxssklSRJkiRpqiS5J/A24NXANYH9gPM7DUrS2G3sOgBJkiRJkga8EnhsVf17+3prl8FImgxbUkmSJEmSpkaSawO3BI5M8qskZyd5Y5Kduo5N0nitOEmV5MpJXpvknQPzT09yaZJL+qbDVh+qJEnS+rZI/eqwJKcl2Zbki0lusZ39LGt9SZoy+wEXAK8DrgvciiZp9fIug5I0fitKUiV5EHAO8KQRq9y3qjb2Te9fcYSSJElzYFT9Ksm+wHHAU4BNwIeA9yXJiP0sa31JmkIFXFRV/1VVv6uqnwGvAu4/uGKSI5OckuSULVu2TDxQSWtrRUmqqjqpqjYCL17jeCRJkubSIvWrBwOfrKqPVNX5wDE0nQjfasSulru+JE2b04CrJblG37yNwNmDK1bVsVW1uao2b9q0aWIBShqPcfVJ9ZEk5yf5cpL7jOk9JEmS5sFNgDN6L6rqUpoLuJus0fqSNFWqagvwEeANSfZsW4g+C3jn4ltKmnXjSFLdFdgduBZwLE3z8usOW9GmmZIkSdu1G3DhwLwLgD1Wu751MUlT7E9oyrIfAp8DTgBe32lEksZuzZNUVfXjqrq4qn5bVW8CfgTcZcS6Ns2UJEla3FZgcESrnWkST6ta37qYpGlVVedU1SOqas+qum5VHVNV1XVcksZrXLf79dsDOGsC7yNJkrQefQ+4ee9Fkg3ATYHvr9H6kiRJU2FNk1RJbp3kGUmum2TXJEfRdHD32bV8H0mSpDlyEnBQkkOS7AEcBZwJnAqQ5HZJvpNkn6WsL0mSNK1WlKRqKz1n0VR6Dk9yVpI/A84F7kdTCfolcC/g4KraukbxSpIkrUuj6ldVdQZwBPA6mpGtDgUO77vtZTeallI7AixhfUmSpKm0cSUbVdVHgb1HLL7nysORJEmaT4vVr6rqeOD4EctOBrLU9SVJkqbVJPqkkiRJkiRJkhZlkkqSJEmSJEmdM0klSSMkuVuSTyc5L8nWJHt2HZMkSZIkrVcmqSRpiCT3BN4GvBq4JrAfcH6nQUmSJEnSOraijtMlaQ68EnhsVf17+9pRSiVJkiRpjGxJJUkDklwbuCVwZJJfJTk7yRuT7NR1bJIkSZK0XpmkkqQr2g+4AHgdcF3gVjRJq5f3r5TkyCSnJDlly5Ytk49SkiRJktYRk1SSdEUFXFRV/1VVv6uqnwGvAu5/uZWqjq2qzVW1edOmTZ0EKkmSJEnrhUkqSbqi04CrJblG37yNwNkdxSNJkiRJ655JKkkaUFVbgI8Ab0iyZ5J9gWcB7+w2MkmSJElav0xSSdJwfwJcCPwQ+BxwAvD6TiOSJEmSpHVsY9cBSNI0qqpzgEd0HYckSZIkzQtbUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkSZIkSVLnTFJJkiRNsST7JblkyHT6iPWPTnLZwLofmHDYkiRJy2aSSpIkaYpV1RlVtbF/Ap4EnLbIZu8e2ObBEwpXkiRpxTZ2HYAkSZKWLskuwF8Df9x1LJIkSWvJllSSJEmz5cnAt6vqPxdZ52FJtiX5cZKXJsmkgpMkSVopk1SSJEkzIsmVgecAL1hktdcDewF7AIcChwFPG3dskiRJq2WSSpIkaXY8C/hiVX1x1ApVdWZVnVdVl1TVV4A3AocMWzfJkUlOSXLKli1bxhSyJEnS0pikkiRJmgFJrg48lcVbUQ2zB3DWsAVVdWxVba6qzZs2bVptiJIkSatikkqSJGk2/BXwyar6av/MJJ9O8uS+1y9LsjnJzkluBzwRePeEY5UkSVo2R/eTJEmackn2Ax4H3HbI4hsCe/e93hk4Abg6cDrwgqr60LhjlKRxaEc0/Tiwoaru3HU8ksbLJJUkSdKUq6ozgN1GLLvewOunA0+fQFiSNFZJNgDvoUm+X9JxOJImwNv9JEmSJEnT6I3Ad4E3dB2IpMlYcZIqyZWTvDbJOwfmH5bktCTbknwxyS1WH6YkSZIkaV4keTmwQ1U9u+tYJE3OipJUSR4EnAM8aWD+vsBxwFOATcCHgPclyerClCRJkiTNgyRHADel6YtP0hxZUZKqqk6qqo3AiwcWPZhm1JmPVNX5wDHANYFbrS5MSZIkSdKcOAA4GLggyTbgTcAd27t1rtK/YpIjk5yS5JQtW7Z0EaukNbTWfVLdBDij96KqLgVOa+dLkiRJkrSoqnpGVe3Sm2haVH2+fX3uwLrHVtXmqtq8adOmbgKWtGbWOkm1G3DhwLwLgD2GrWzWW5IkSZIkSbD2SaqtwE4D83amSVRdgVlvSZIkSZIkwdonqb4H3Lz3IskGmg7vvr/G7yNJkiRJmgNVdVxV3bnrOCSN31onqU4CDkpySJI9gKOAM4FT1/h9JEmSJEmStI6sKEnVJqHOoklCHZ7krCR/VlVnAEcArwPOBg4FDq+qWquAJWlSkuyS5D+TfLbrWCRJkiRpvdu4ko2q6qPA3iOWHQ8cv5qgJKlr7e3K76HpV++SjsORJEmSpHVvrW/3k6T14o3Ad4E3dB2IJEmSJM0Dk1SSNCDJy4EdqurZXcciSZIkSfPCJJUk9UlyBM2opI9bwrpHJjklySlbtmwZf3CSJEmStI6tqE8qSVrHDgAOBi5IArAB2JBkG3CNqjq3t2JVHQscC7B582YHiJAkSZKkVbAllST1qapnVNUuvYmmRdXn29fnbm97SZIkSdLKmKSSJEmSJElS50xSSZIkSZIkqXMmqSRpEVV1XFXdues4JEmSJGm9M0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJE25JEcnuSzJJX3TB0asu0+Sjye5MMnPkjx50vFKkiSthEkqSZKk2fDuqtrYNz14xHpvAX4IXAs4DHhRkjtMLEpJkqQV2th1AJIkSVobSa4C3BPYu6rOBb6U5N3AQ4EvdBqcJEnSdtiSSpIkaTY8LMm2JD9O8tIkGbLOjYDz2wRVz/eAm0wmREmSpJWzJZUkSdL0ez3wamArcCvg3cAW4O8H1tsNuHBg3gXAHsN2muRI4EiAfffddw3DbRx46KFLWu/UE09c8/eWJEmzx5ZUkiRJU66qzqyq86rqkqr6CvBG4JAhq24FdhqYtzNNomrYfo+tqs1VtXnTpk1rG7QkSdIymaSSJEmaPXsAZw2Z/wNgzyT9Gaf9ge9PJCpJkqRVMEklSZI05ZK8LMnmJDsnuR3wRJpb/kjy6SRPBmj7ovo08OIkV0myGXgE8K9dxS5JkrRU9kklSZI0/XYGTgCuDpwOvKCqPtQuuyGwd9+6jwXeBvwKOAd4UVV9dnKhSpIkrYxJKkmSpClXVU8Hnj5i2fUGXv8EuNcEwpIkSVpTJqkkSSMtdWSuaeDoYJIkSdJss08qSZIkSZIkdc4klSRJkiRJkjpnkkqSJEmSJEmdM0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEnS1EjyvCTfTrI1yelJntl1TJImY82TVEmOTnJZkkv6pg+s9ftIkiRJktalAo4A9gIeCDwzySHdhiRpEjaOab/vrqpHjmnfkiRJkqR1qqqO6Xv5v0k+AxwIfLSbiCRNirf7SZIkSZKmUpINwGbgW13HImn8xpWkeliSbUl+nOSlSTKm95EkSZIkrV8vB84EPtR1IJLGbxy3+70eeDWwFbgV8G5gC/D3Y3gvSZIkSdI6lOQ5wIOAu1bVpSPWORI4EmDfffedYHQrc+Chh3byvqeeeGIn7yst15onqarqzL6XX0nyRuAQhiSpZq1AGaarQmYUCx9p9ZI8D3gUsB/NL3evrapXdhuVJEnSfGjvxHkZzXXkXavql6PWrapjgWMBNm/eXJOJUNK4TKJPqj2As4YtqKpjq2pzVW3etGnTBEKRpCVxRBlJkqTuvAu4LdtJUElaf9Y8SZXkZUk2J9k5ye2AJ9Lc8idJM6GqjqmqL1TVtqr6X6A3oowkSZLG7+HAXYGzklzSTj/oOihJ4zeOPql2Bk4Arg6cDrygquzkTtJM6htR5l1dxyJJkjQPqsqBt6Q5NY4+qZ4OPH2t9ytJHRk5osx66FdPkqbBUvv4tO9NSZLWt0n0SSVJM6lvRJlDh40oY796kiRJkrR2TFJJ0oA0Xg48AjvslNSxJM9L8u0kW5OcnuSZ21n/6CSX9fXjckmSD0wqXkmSpJUaR59UkjTr3gVckyZB9ZuOY5Gk3oijXwVuDHwyyTer6qOLbPPuqnrkRKKTJElaIyapJOmKHg5cSjOiTG/e6VV1o+5CkjSvquqYvpf/m6Q34uhiSSpJkqSZ4+1+kjSgqlJVGwcmE1SSOtc34ui3trPqw5JsS/LjJC9NX8ZdkiRpWpmkkiRJmh0jRxzt83pgL2AP4FDgMOBpw1ZMcmSSU5KcsmXLlrWNVJIkaZlMUkmSJM2A7Y042lNVZ1bVeVV1SVV9BXgjcMiIdR2lVJIkTQ37pJIkSZpi7a16L6NJNK1kxNE9gLPWPDBJkqQ1ZksqSZKk6fYu4LaMSFAl+XSSJ/e9flmSzUl2TnI74InAuycXriRJ0srYkkqSJGm6bW/E0RsCe/etvzNwAnB14HTgBVW1WB9WkiRJU8EklSRJ0hSrqkVH5quq6w28fjrw9HHGJEmSNA4mqSRJkjQTDjz00CWtd+qJJ441DkmSNB72SSVJkiRJkqTOmaSSJEmSJElS50xSSZIkSZIkqXP2SSVJkiRJksZiqf0JjsM89lHY1fleq3NtSypJkiRJkiR1zpZUkiRpqC5/+VyuefylVJIkab2xJZUkSZIkSZI6Z0sqjc0s/QI/72yBIEmSJEnqmi2pJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1zj6pJEmSJGkMltNHq32ESpItqSRJkiRJkjQFTFJJkiRJkiSpcyapJEmSJEmS1DmTVJIkSZIkSeqcSSpJkiRJkiR1ziSVJEmSJEmSOmeSSpIkSZIkSZ0bS5IqyT5JPp7kwiQ/S/LkcbyPJI2L5ZikabKcMsnyS9J6YFkmzadxtaR6C/BD4FrAYcCLktxhTO8lSeNgOSZpmiynTLL8krQeWJZJc2jjWu8wyVWAewJ7V9W5wJeSvBt4KPCFtX4/SVprlmOSpslyyiTLL0nrgWWZNL/G0ZLqRsD5bWHS8z3gJmN4L0kaB8sxSdNkOWWS5Zek9cCyTJpTa96SCtgNuHBg3gXAHoMrJjkSOLJ9+dsk3x1DPLNub+Cspa6cZIyhTKVlnZ85s+Rzs8zPzceq6uAVRTQ7llSOWYYtycS+o+uk/LNMW7rLnat1Xo4tuW61zHWXW47NzOezg/JgZs5NBzw3o620HJu1MmwlxnFNOaufxTWJe8Ll4tSc62Ue99TEvUxTEfda1cXGkaTaCuw0MG9nmkLlcqrqWODYMcSwbiQ5pao2dx3HtPL8jOa5WZUllWOWYdvn53B5PF9LN2fnasl1q2Wuu6xybM7O+bJ4bkbz3IzmuVnUml9Tzur5nsW4ZzFmMO5pMY7b/X4A7JlkU9+8/YHvj+G9JGkcLMckTZPllEmWX5LWA8syaU6teZKqvW/408CLk1wlyWbgEcC/rvV7SdI4WI5JmibbK5OSfLo3NLvll6T1wLJMml/jaEkF8FjgxsCvgJOAF1XVZ8f0XuudtxItzvMzmudmdSzH1oafw+XxfC3dvJ2rxcqkG9L0R7GUdVdj3s75cnhuRvPcjOa5Wdxal2Wzer5nMe5ZjBmMeyqkqrqOQZIkSZIkSXNuXC2pJEmSJEmSpCUzSSVJkiRJkqTOmaSSJEmSJElS5zZ2HYAkSZKmS5LbAw8FbgLsAVxAM/T7v1bV57uMTZK2xzJMml22pJIkSdLvJflz4MPAjsDHgbcDHwI2AB9ol0vSVLIMk2abo/tpJiTZADyThV9EdgMupPlF5Hjg76rqku4i7I7nRtPAz+HyeL6WznM1eUl+Ajykqv57yLLNwIlVdZ3JR6ZZkOS6wKFcsQXLiVV1Roehdc5zMxmzWob5/25yZvlcz0M5YpJqiszyl2XckvwTcGvgFcD3aL6MOwMH0Jyzr1XVE7qLsDueG00DP4fL4/laOs/V5CXZClyjqs4fsuzKwK+qatfJR9Y962qLS/IQ4G3AyVz++7o/cDfgiKo6obMAO+S5mZxZLcNm9f/dLJaLM3yu56IcMUk1RWb1yzIJSX4NHFBVPx+y7NrAN6tqz8lH1j3PjaaBn8Pl8Xwtnedq8pJ8DPgB8Jyq+m3f/KsBLwFuXFX37iq+LllXW1yS7wN/UVUfHbLsvsDrqupGk4+se56byZnVMmxW/9/NYrk4w+d6LsoRO06fLg9j+JflO0m+AHwTmKov+IQtllGd9/7VPDeaBn4Ol8fztXSeq8k6AngLcE6S82h+Ed8J2BP4NPCnHcbWNetqi7sO8JkRyz4L7DPBWKaN52ZyZrkMm8X/d7NaLs7iuZ6LcsQk1fSZxS/LJLwHeH+SvwHOYOGfzc2Bo4D3dhhb1zw3mgZ+DpfH87V0nqsJay80Dmlvi7kRza0bW4EfVNV5nQY3HayrjfZV4C+AY/pnJgnwVODrXQQ1JTw3EzLDZdgs/7+btXJxVs/1XJQj3u43RdqmkgcCo74sX6+qIzsLsENJNtI0Fz2chXudt9I0KX0f8Kqquri7CLvjudE08HO4PJ6vpfNcaZpYV1tckv1pvpdXA37Cwvm5MfBL4I+q6pvdRdgdz422Z1b/381iuTjD53ouyhGTVFNkVr8skiRJ88C62tIkuSXNRdPvz09VfaPbqKaD50brjeXi5K33csQklWZK+4XsH27ze1W1Lpo1rpbnRtPAz+HyeL6WznMlSVrPkhxaVSf2vd4HuAuwBfhcVW3rKrb1xnM93UxSTSEr4leU5ACaTPw1gdNYGDXipsCvgMPXU/Z4OTw3mgZ+DpfH87V0nitNI+tqw83iUPST4rnR9iT5XVXt1D6/N83/vh/RlDMbgIOr6rsdhrioWSoXZ/Vcz0s5YpJqilgRHy3J54EPA8dU1WV983cAng08qKru0FV8XfLcaBr4OVwez9fSea40TayrLW4Wh6KfFM+NtifJxVW1Y/v8S8CbqurN7eujgHtU1cFdxjjMLJaLM3yu56IcMUk1RayIj5ZkK7Cpqi4Ysmx34Kyq2nXykXXPc6Np4OdweTxfS+e50jSxrra4JL9m+FD0JLk28M2q2nPykXXPc6PtGWjdcy5wrara2r7eBfjFNH5GZrFcnOFzPRflyDQOBznPDgT+of/LDdC+fk27fF79HLjziGV3bpfPK8+NpoGfw+XxfC2d50rT5ECsq23PrA1FP0meGy1mhyR3T3JPmtYxF/Ut2xuY1tu4DmT2ysVZPdcwB+XIxq4D0OX0KuIfH7Js3iviRwHHJ/kElx/adH/gbsARHcbWNc+NpoGfw+XxfC2d50rTxLra4t4DvD/JqKHo39thbF3z3Gh7fgq8tX3+C+Ba7Txo+iD6WhdBLcEslouzeq7nohzxdr8pkuQw4G3AyIp4Vb2vuwi7leS6wIO54tCmJ1XVj7uMrWtJ9gUehOdGHfI7ujx+b5duyLkK8FU8V5ow62qLcyj60Tw3Wo0kBwLnVtWPuo5l0HorF6f8XM9FOWKSasp4kSdJ0uKSbK2q3bqOQ/NpSF3tApq62getq0maR7NWLib5IU0n7y+qqs92HY8uzyTVDEnyp1X1tq7j6EqS+9Lc0/xN4MPV9+FN8r2quklXsXUpya40t7ucWlWfS3I4TTPVi4B/qaqPdBqg5obf0aXze7t0ST4zZPadgM/1XlTVXScXkeZZkn+rqj/se/004BBgC/CuqvpoV7FNk1kain5SkhxaVSf2vd4HuAvNZ+dzVbWtq9g0PfrqUt8CPjQLdalZLBeTXAw8CfhrmnP9/Kr6crdRLd16L2NNUs2QJGdW1dW7jqMLSZ5B07TxM8BmmuFMD62qM9vlvx9GdN4keQvwBzTNal8FPB04DrgS8Hjg2VX19s4C1FzwO7o8fm+XLsl/AjsCb+zNap8f2Vunqv65g9A0hwZGhPob4DDgWJoLhScCf1VVx3UXYbdmcSj6SRn47Nyb5jz9iOazswE4uKq+22GI6tiIutSDq2pLu3wq61KzWC72Yk6yM/AUmlEIv0CTrJraZM+8lLEmqaZIku1dkBw+r7c3tE0yH1RV32iHM30F8ADgLlW1pb9wnDdJzgRuCexF00fLAVV1WrvsjsCbq2r/DkPUHPA7ujx+b5eurUC+B/hOVT23neftfupE/0ViktNpkvGntq9vB7ytqg7oLsJuzeJQ9JMy8Nn5EvCmqnpz+/oo4B5VdXCXMapbs1qXmsVycfBcJrkSTcfjf0HTt9YLquo7XcU3yryUsSappkiS1wJPAF4yYpVnVdUeEwxpaiS5ANizqn7XN+85wMOAuwJnT+MvC5PQnpsrVdVlgxdu7cXdOVW1e3cRah74HV0ev7fL01a+ei2pjgQuMEmlLgy0GNgK7NG7UEiyE/Dref7utudkU1VdMGTZ7sBZVbXr5CPr3sBn51zgWlW1tX29C/CLqtqzyxjVrVmtS81iuTgq4ZdkE/B84M+m8bp7XsrYjV0HoMt5HvD4qnrRsIVJnjzheKbJGcCtgS/1ZlTVy5LsCbwfmOds649omnh+e8hF2wHAmZMPSXPI7+jy+L1dhray+7gkL6P5PEld2dC2fA9NPXo34LftslvS9MEyz2ZxKPpJ2SHJ3YEdaG7Puahv2d7AJZ1EpWkyq3WpWSwXM2xme2vlU5O8asLxLNVclLEmqaZIVZ3XDuE5yqMmFsz0eQdwEH2FNkBVPTvJu5nvz/KbaS5qvz1k2VE097VL4+Z3dHn83q5AVT0nyZ/S9MMgdeHFfc//FtiFhYuxwzGJehRwfJKRQ9F3GFvXfgq8tX3+C+Ba7TxoBs74WhdBaarMal1qFsvFGy62sKZwRMLWXJSx3u4nSZIkaU0MGYp+K81Q9CdN8YVfp5IcCJxbVT/qOhZJ020eyliTVJIkSZLGLsmfVtXbuo5jGnluJK3WeilHTFJJkiRJGrskZ1bV1buOYxp5biSt1nopR6b1vlZJkiRJM6TtPHkxUzda1qR4biSt1ryUIyapJEmSJK2F84AnAC8ZsfyyCcYybTw3klZrLsoRb/eTJEmStGpJrgycXVU7jli+pao2TTisqeC5kbRa81KO7NB1AJIkSZJmX1WdBxy2yCqPmlQs08ZzI2m15qUcsSWVJEmSJEmSOmdLKkmSJEmSJHXOJJUkSZIkSZI6Z5JKkiRJkiRJnTNJJUmSJEmSpM6ZpJIkaY0lOS5JJTm561gkSZKkWWGSakKS7Jfkb5J8Ick5SS5Ocn6SM5J8IskxSe6VZGPXsXYlyentRd3RXcciae203+uVTo/pIN7H9N5/O+sdt5T1JEmSJC3N3CZEJinJ04BjgF36Zl8G7NFO+wL3Bp4DfBO4xYRDlKRxumjE/I3Ahu2sc+nah7NmLmZ03JIkSZKWyZZUY5bkycDf0ySo/gN4IHANmouzK9EkpJ4E/Hu7yVUnH6UkjU9V7TJsAv6mXeWMUetU1Tu6jH0xVfW4vmORJEmStEq2pBqjJLsAL2lfvg94aFX13xbyW5qWU98E/inJrYDnTTZKSZIkSZKk7tmSarz2Z6Fl1NsGElRXUFVfr6qHDVuW5LZJ3pnkx0kuSnJ2kv9I8tgkG0Zsc80kr07y6STfTfKbti+ss5N8Psnzk1x1xLZHt32tnN6+PizJR5OclWRbu78XJdl11PEkOSTJ+5P8LMnv2j64/jfJm5I8IMkO7XqPaft02a/d9IVD+qU5aGDfG5M8LsnJ7fFc1J6bdyS5zSIx/b7fqyRXTvKMtp+w85JsTfLVJE8YtX3ffg5OckKSn7fHdk6SzyR5YpIdt7e9pOVZzncuyZ3bsq6S/Msi+3xUu85lSR7YzjsdeFvfOoNl0cl9yy5XTq7gmG6e5I1JfpDkwraM/FqSv02y9yLbLalslSRJkmaNLanGqz95dM2V7iTJX9G0yEo76zJgL+CgdvqTJA+qql8PbHoj4OkD83rb3qGdjkxyl6o6Y8TbXyXJ59t1e9vvANwE+GvgvknuWVUX9MUb4FjgsQPvuwfN7Y23aJcdDpxA0+fMRcDO7bqXApcMibu3/6sBH+yLqbf8usAjgT9O8pyqesWIY4LmvD2B5tbL/uM6kKZV242q6pmDGyXZGXgr8Ii+2QXsCdylnR6e5OCq2rrI+0tagpV856rqs0meD7wMeFiST1bVWwf2eyPg9e3Ll1bVB9vnF9GUPxv7Xvf73Rod11OBV7Hwf6Jobgu/VTv9SZJ7VdV3+rZZbtkqSZIkzRR/bR2vbwLb2ufPTXLj5e4gySNp+m3pXZzciObi6ao0FyPnAncG3t1ewPTbBpwEHElz8XKldttNwGOA82kSO69aJISr0lwwvZymZdiONEmu59BcVN0eeMHANn/cxnYZ8ELgOu37Xhm4J82F4W/bY6Kq3tH26dJLlP3NkH5pPtOejwDvoUlQ/Ro4oo1xI3BjmovZAC9PMrRVWutubXxPA/apqg3ADYCPtsv/MslNhmz3epqL5Z+1x9g7tmu1r7fQXDQvliCTtHQr/c69Avhw+/w1SW7aW5BkJ5pyZA/gUzQJdwCq6qbA4/peD5ZF91ntAbXl+j/QJLxeSlN27UyTeLsv8DVgH+D4gXJ9WWWrJEmSNHOqymmME80FSLXTxSxcEP0hzYXJDotsuxPw83bbN45Y5640FywF3G+ZsT2y3W4bsOPAsqPbZb8GbjBi+1e36/wG2KVv/vvb+R9b5L2vCdxwYN7p7XZHL7LdA9t1LgPuNGKdt7Tr/HTIcfXe45PAVYZsuzdNK4oC/nJg2R3a+VuA649474P7zukeXX/+nJymeeorZ04fsXxV3zngasCP2+VfAXZq57+qnfdjYO8h+3xMr9xeafzAce2ykwfm7w6c3ZZhDxyx32u25WoB9+6bv6Ky1cnJycnJycnJyWlWJltSjd8LgFeycPvIPYEX0VxsfA84P03fUk9NcpWBbe9J01oAFkbBupxqWhid3L589DJj+1L7uDNN66phzq2qH45Y9qb28SrA/x2yfK8hrbsAqKpfVtVpS450wSPbx3+vqs+NWOfF7eM+NOdwmM9V1blD4joL+FH78oYDi3utK95WVT9iuE8AW2nO6W1HrCNpaVb1nauqs4GH0ZS/t6ZpYXkwzW3QvwMOb7/zk/QQmtaop9TCLYaXU1W/BL7YvrzzkFXGUbZKkiRJnTNJNWZVdWlVPYum1dQLgH8H+i+KdqPpH+kfgO8n6b+V5Pbt44+q6ieLvM1nBta/nCR3TPLSJB9O8o0kZyQ5h+Z2xJ6dlnpMfb4DXNg+v3nf/E+1j7cFPpHkYUmuvYL9D9M7xs+MWqGa/rV6tw4OPSfb0evba7eB+XdpH5+epvP4K0w0F8u97VbcD5kkYA2+c1X1eeC57cun0tzmF+CpVfXfY45/mN4x3WbUMbXHde92vf5jGmfZKkmSJHXOjtMnpKpOp2kN9TcASTbR/LJ/G+AwYDNNa6b3J9m/qn7MQqfev9zO7n/RPl6jf2aSfYB30fS/NMxg5+TLUlWV5NfArjR9qfS8CbgP8GDgXu1Ekl8AX6bp0PdfquriFbztcs7JfgyckyXqdXg+2FKhdzG4kaV9d3be/iqSFrFW37lX0ZSDD6Bp+fmuqnrD6sNbkd4x7cDSyoj+dcZZtkqSJEmdsyVVR6pqS1V9oqqOqarbAr2R5Han6Rx3OTLwSJKNNLfB3I2mD5P30tz2ckuafpd6HY2vVu/C8fcjXlXVxVV1KHAP4J9oWmxdRnPr4oOAfwa+kGSvNXj/Ua5wTtZAbxSuJ1VVljAdt4bvLc2jNfnOVVVx+VH5rteWkV3oHdPxSzymx/Q2nJKyVZIkSRobk1TT49XABe3z67WPZ7aP27udo9dv1a/65t2PZjQ+gIdV1cOq6r1V9Y2qOruqLl1twEl2pemYGJoO3i+nqv6jqp5UVb2RBQ+iubC6jKYF2YtW8LarOSer1Xvvwb6qJI3HmnznkvwlTYvVs2mSVXeiGdSiC6s+pjGVrZIkSVLnTFKNUZJNSTZsf83f692isaV97PWXsl+S6y+y3d0H1gfoDbf+66o6fhkxLMfdWGgVMKoTcwCqamtV/WdVPQl4Zzt7sEPg3u2Hi90C0zvGu49aIckNgH0H1l8LvY7mD13m31XSyqz6O5fkjsDL2pePBp7XPn9mkgeM2Oz3t0InWevbdnvHdOskq054L7FslSRJkmaCSarxuj/w+SSbl7DunwBXbZ+f2D5+ioWWQEN/GU9yTxY64n1H36Jt7eMebYunYZYS11BJdgRe2L78j7az8t6yJya58iKbXzzw2NNLzv3BItu+q328a3vswxzdPv6ShY6G18Jx7eMN+95jqCQHj+HiVpo3x7WPK/rOJdmb5lbnHYF/rKqP0LRa/TjNrcD/nGTfK+xsoSyCxcujlfhXmn7vdgCOTTJy0IokN0myf9/rlZatkiRJ0kwwSTV+twO+nOS/kjwlya2S7J7G3knunOStwFva9d9cVacAVNVFwHPa+Y9KclySG7fbXiXJ44B/a5d/CvhQ3/t+nObWjx2Bd7bbbUiya5KDknyA5mJpe66e5LlJbpZk5yQ7JLkt8DHg/9LcOvPMgW0eD/woycvbkQV3a2O+RpKnAI9q1xts4dVrjXXPJH/SHuNVk9ylvdgEOAk4uX3+/iSPa9dLe4z/3Lf/o6qqvx+aVamqDwMfaF8+P8nxSe7Qd172SfLoJCcDH6U595JWaDXfuSQ70CS1rwOcCjy73WfR/ChwJrAXcHybdO/3ZRb6sDqmLVt2TXKDJHda5TGdCfxV+/IeND9kPKiXfEqyV5L7J3kHTZ9TN+jbfKVlqyRJkjQbqsppTBPNBcjZNB2XD06XDry+hGYEqg1D9vPC7Wz7eeBqy9zuUpoEV+/19Qa2PXoJcW8DDh/yvl9cwvEeD2wc2O66wDkj3vfAvvU20dwyM2r/lwHPG/E3Ob1d5+hF/m4nt+scN2TZ7m3s2zu+i4Hduv4MOjlN89RXzpy+yDor+s71lX8XADcbst/79W376iHLXzmiLDpxKfHTtAIr4OQRx/UcmnJ/sWMq4D5926yobHVycnJycnJycnKalcmWVGNUVf9O04H3A4H/R9NS6JfAhTQXE78GTqG5GDqgqp5RQzo0r6oX0bRaejfwU5qLkt8An6H5Zf2uVXX2iO0eSnNhs63d7ofAG4BbA09fwmH8FHg4Tcupn9BcVP0UeCtwi6p635Bt7knTUuEEmqRQ771/TtMq4g+r6qFVdUn/RlX1E+AOwPuAs9r3OpMmaXRO33pbaDo+fkJ7Dn7TF9e7gdtX1Vg6Ra6qC6rqoTR9Yr0d+AHNrTuXAr+gOU9PAq5VVVvHEYM0T1bynUtyL+Cv2108taq+M2S/HwH+sX359CSHDqzyLOCpwDeAi2iSXd8BvrBGx/Uy4ObA39O09DqXJsF+Ds0PD0cDN62qT/RttqKyVZIkSZoVqaquY9AUSnI0TUuEM6rqet1GI0mSJEmS1jtbUkmSJEmSJKlzJqkkSZIkSZLUOZNUkiRJkiRJ6pxJKkmSJEmSJHXOjtMlSZIkSZLUOVtSSZIkSZIkqXMmqSRJkiRJktQ5k1SSJEmSJEnqnEkqSZIkSZIkdc4klSRJkiRJkjpnkkqSJEmSJEmdM0klSZIkSZKkzpmkkiRJkiRJUudMUkmSJEmSJKlzG7sOoOfggw+uj33sY12HIWn70nUA0+j/b+/uYy256/OAP192scFsTKG+QEqzTSSwBQ5oCbepkhIXNVXBVWO2xqVJ1FbCSTcJDVJRLBtSVWqctMap0lYVScsmCCcBShyHbMyLS1H+iEUgaZ2yIbwkBqc2VSLwbmnxy9oUzLd/nLvy3et77fXdOXfOnPP5SCvtmTk788zdMz/tefY3M8YwmBTjGADAAlqYmVQnT54cOwLArhnDAAAAzs3ClFQAAAAArC4lFcAOquppVfU7VfXRsbMAAAAsOyUVwDaqal+S9yY5f+wsAAAAq0BJBbC9tyf5kyT/aewgAAAAq0BJBbBFVd2Y5Cndfd3YWQAAAFbF/rED7Mahw4fPeRvHjx07520Ay6eqrk5ySZLXnsV7jyQ5kiQHDx6cc7KdPZkx0dgHAAAsqkmWVABzdGmSVyd5sKqSZF+SfVX1cJLndvdXTr+xu48mOZok6+vrPUJWAACApeFyP4BNuvsnuvtpp38l+SdJPrbx+itP9OcBAADYHSUVAAAAAKNTUgEAAAAwOiUVwOPo7pu6+xVj5wAAAFh2SioAAAAARqekAgAAAGB0SioAAAAARqekAgAAAGB0SioAAAAARqekAgAAAGB0SioAAAAARqekAgAAAGB0SioAAAAARrerkqqqfrKqPltVp6rq7qq6Zsv6K6vqrqp6uKp+r6q+fZi4AAAAACyj3c6k6iRXJ3l2ku9Lck1VXZ4kVXUwyU1J3phkLckHktxSVXXOaQEAAABYSrsqqbr7hu7+eHc/3N1/lOT2JIc2Vr8myUe6+0PdfX+SG5I8L8lLhwgMAAAAwPI553tSVdW+JOtJPrOx6OIk95xe392PJLlrYzkAAAAAPMYQN06/Mcm9mV3WlyQXJHloy3seTHJg6x+sqiNVdUdV3XHixIkBogAAAAAwRedUUlXVm5NckeTwxoypJDmV5Lwtbz0/s6LqDN19tLvXu3t9bW3tXKIAAAAAMGG7fbpfVdWNSX4wyWXd/cVNq+9M8qJN792X5JIknzuXoAAAAAAsr93OpHp3kr+axxZUSXJrkldW1eVVdSDJtZldDnh81ykBAAAAWGr7d/nnfiDJI0lOVtXpZXd39wu6+56qujrJzyd5fmbl1FXd3ecaFgAAAIDltKuSqrvrCdbfnOTmXSUCAAAAYOUM8XQ/AAAAADgnSioAAAAARqekAgAAAGB0SioAAAAARqekAgAAAGB0SioAAAAARqekAgAAAGB0+8cOMJZDhw8Psp3jx44Nsh1gcVTVm5L8cJJvS3IqyfuT/Hh3PzhqMAAAgCVmJhXAY/1ZktcleWaSlyR5WZKrR00EAACw5FZ2JhXATrr75iSpqkryF5Kcn+QPx8wEAACw7JRUADs7lWRfkjd09+1jhwEAAFhmSiqAHXT306vqhUl+s6ruOz3DCgAAgOEpqQAeR3d/rqpuyuweVWeUVFV1JMmRJDl48ODeh9uFs31ohIdCAAAAe82N0wGe2Dcl+erWhd19tLvXu3t9bW1thFgAAADLQ0kFsEVV/VpVvbyqnlZV353kR5K8d+xcAAAAy8zlfgCP9dUk70vynCT3JHlLd79/3EgAAADLTUkFsEV3/+OxMwAAAKwal/sBAAAAMDolFQAAAACjU1IBAAAAMDolFQAAAACjU1IBAAAAMLpdl1RVdWFVva2q3rVl+d1V9UhVfX3TCvycLQAADv9JREFUryvPPSoAAAAAy2pXJVVVXZHky0nesMNbXtXd+zf9et+uEwIAAACw9HZVUnX3rd29P8n1A+cBAAAAYAXN655UH6qq+6vqv1fV357TPgAAAABYEvMoqS5L8owk35zkaJJbqupbtntjVR2pqjuq6o4TJ07MIQoAAAAAUzB4SdXdX+jur3X3A939i0n+Z5Lv2eG9R7t7vbvX19bWho4CAAAAwETM63K/zQ4kObkH+wEAAABgovYPubGqelmSv5nk5syKqTdu7OOjQ+4HAAAAgOWyq5lUVXV5VZ1Mcm2Sq6rqZFX9UJKvJPk7SY4n+WKSv5Xk1d19aqC8AAAAACyhXc2k6u7bkly0w+rv3X0cAAAAAFbRXtyTCgAAAAAel5IKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQC2qKqfrKrPVtWpqrq7qq4ZOxMAAMCy2z92AIAF1EmuTvKJJC9M8pGq+nR33zZuLAAAgOVlJhXAFt19Q3d/vLsf7u4/SnJ7kkMjxwIAAFhqSiqAx1FV+5KsJ/nM2FkAAACWmcv9AB7fjUnuTfKBrSuq6kiSI0ly8ODBs97gocOHz+p9x48dO+ttAgAATJ2ZVAA7qKo3J7kiyeHufmTr+u4+2t3r3b2+tra29wEBAACWiJlUAFtUVSV5a5LLk1zW3V8cORIAAMDSU1IBPNa7kzwvs4Lq/46cBQAAYCUoqQAe6weSPJLk5GxSVZLk7u5+wXiRAAAAlpuSCmCL7q4nfhcAAABD2vWN06vqwqp6W1W9a8vyK6vqrqp6uKp+r6q+/dxjAgAAALDMdlVSVdUVSb6c5A1blh9MclOSNyZZy+yR7bfUputlAAAAAGCrXZVU3X1rd+9Pcv2WVa9J8pHu/lB335/khsxuPvzSc4sJAAAAwDLb9eV+O7g4yT2nX3T3I0nu2lgOAAAAANsauqS6IMlDW5Y9mOTAdm+uqiNVdUdV3XHixImBowAAAAAwFUOXVKeSnLdl2fmZFVWP0d1Hu3u9u9fX1tYGjgIAAADAVAxdUt2Z5EWnX1TVviSXJPncwPsBAAAAYIkMXVLdmuSVVXV5VR1Icm2Se5McH3g/AAAAACyR/bv5Q1V1eZJfzeweVE+pqlcnua6731FVVyf5+STPz6ycuqq7e6C8AAAAACyhXZVU3X1bkot2WHdzkpvPJRQAAAAAq2VXJRWPOnT48CDbOX7s2CDbAQAAAJiioe9JBQAAAABPmpIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQB2UFUXVtXbqupdY2cBAABYdkoqgG1U1RVJvpzkDWNnAQAAWAVKKoBtdPet3b0/yfVjZwEAAFgFSioAAAAARrd/7AAAU1VVR5IcSZKDBw8Ovv1Dhw8Pvs2h93382LFRtjemZTqWKfDzBgBYHYPPpKqqf1lV36iqr2/69VtD7wdgbN19tLvXu3t9bW1t7DgAAACTNq+ZVO/p7n84p20DAAAAsGTckwoAAACA0c2rpPr+qnq4qr5QVf+6qmpO+wGYi6q6vKpOJrk2yVVVdbKqfmjsXAAAAMtqHpf7/UKSf5vkVJKXJnlPkhNJ/t3WN877psOraKgbLbsBLauuu29LctHYOQAAAFbF4DOpuvve7r6vu7/e3f8jyduTXL7De910GAAAAIA9uSfVgSQn92A/AAAAAEzU4CVVVb21qtar6vyq+s4kP5bZJX8AAAAAsK153JPq/CS/keQ5Se5O8i+6+wNz2A8AAAAAS2Lwkqq735TkTUNvFwAAAIDlNY+ZVOzCUE/lWySeNAgAAACcrb24cToAAAAAPC4lFQAAAACjU1IBAAAAMDolFQAAAACjU1IBAAAAMDolFQAAAACjU1IBAAAAMDolFQAAAACjU1IBAAAAMDolFQAAAACjU1IBAAAAMDolFQAAAACj2z92ABbTocOHx44AAAAArBAzqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNEpqQAAAAAYnZIKAAAAgNHtHzsATM2hw4cH2c7xY8fOeRuLlAUAAADOhZlUAAAAAIxuLiVVVT2/qj5cVQ9V1Z9V1Y/PYz8A82IcAwAA2Fvzmkn1jiR/muSbk1yZ5Keq6rvmtC+AeTCOAQAA7KHB70lVVc9M8r1JLururyT5/ap6T5LXJfn40PsDGJpxDAAAYO/NYybVC5Lcv/HF7rQ7k1w8h30BzINxDAAAYI/N4+l+FyR5aMuyB5Mc2PrGqjqS5MjGyweq6k/Och8XJTm564TTskrHmmxzvFU1UpT5qqqF+bt9kj/j/9Ldr55XlgVxVuPYko9hZ5Vx6PPzSW5voX+OG8ey0Bk3mULOx81oHAMAmL55lFSnkpy3Zdn5mX3BO0N3H01y9MnuoKru6O713cWbllU61mS1jneVjnWCzmocW+YxTMZhTCFjMo2cU8gIAMC5mcflfp9P8qyqWtu07MVJPjeHfQHMg3EMAABgjw1eUm3cw+W3k1xfVc+sqvUkP5jk14feF8A8GMcAAAD23jxmUiXJDyd5YZIvJbk1yU9190cH3P6TvrxmwlbpWJPVOt5VOtYpmuc4NoW/exmHMYWMyTRyTiEjAADnoLp77AwAAAAArLh5zaQCAAAAgLOmpAIAAABgdEoqAAAAAEa3f+wAj6eq/lqS1yW5OMmBJA9m9gj4X+/uj42ZDeBsGMcAAADOzsLOpKqqf5rkg0memuTDSX4lyQeS7EvyWxvrmaiq2ldV11XVH1TV/VX1SFU9UFWfqKq3VNVCF6hPxiodK2cyjg1jCueQjAAAcO4W9ul+VfW/kry2u//bNuvWkxzr7r+898nmp6r2Jbkmj866uCDJQ5nNurg5yb/p7q+Pl3A4VfUfk7wsyc8muTOz2SXnJ7k0s5/BH3b3j46XcDirdKycaSrj2KKPPVM4h2QczqJ/HgEAmJ9FLqlOJXlud9+/zboLk3ypu5++98nmZypfIIZQVf8nyaXd/efbrPtLST7d3c/a+2TDW6Vj5UxTGccWfeyZwjkk43AW/fMIAMD8LPLU/tuT3FBVb+7uB04vrKq/mOSnk3x0tGTz8/3Z/gvEH1fVx5N8Osky/cP88RrShb0UdZdW6Vh51FTGsSmMPVM4h2QcxhQ+jwAAzMEil1RXJ3lHki9X1X2ZTfU/L8mzkvx2ktePmG2epvAFYgjvTfK+qvqZJPfk0b/fFyW5NsmvjZhtaKt0rJxpSuPYIo89UziHZBzWIn8eAQCYk4W93O+0jUtiXpDZPSlOJfl8d983bqr52LjE4VCSnb5AfLK7j4wWcEAbN+i9JslVefSeI6cyu7TjliQ/191fGy/hcFbpWNneoo9jiz72TOEcknE4i/55BABgfha+pFolU/kCASwXYw+LxOcRAGB1KakYVVW9JLMvIQcyuznund39yXFTzccqHSvMwxTOIRkBAGD3lFQLaBW+QFTVpZn9j/jzktyVR5/edEmSLyW5qrs/NV7C4azSsTJtizr2TOEcknF4i/p5BABgfpRUC2RqXyDORVV9LMkHk9zQ3d/YtPwpSa5LckV3f9dY+Ya0SsfKNC362DOFc0jG4Sz65xEAgPlRUi2QqXyBGEJVnUqy1t0PbrPuGUlOdvfT9z7Z8FbpWJmmRR97pnAOyTicRf88AgAwPx7jvFgOJfn3m/9RniQbr//Dxvpl8edJXrHDuldsrF8Wq3SsTNOhLPbYM4VzSMbhHMpifx4BAJiT/WMH4Aynv0B8eJt1i/QFYgjXJrm5qv5rznzE+IuT/I0kV4+YbWirdKxM06KPPVM4h2QczqJ/HgEAmBOX+y2QqroyyTuT7PgFortvGS/hsKrqW5K8Jo99xPit3f2FMbMNraoOJrkiK3CsTM8Uxp4pjBdTOM+3yVhJPpHFyrjwn0cAAOZDSbVgpvBFDFg+xp7VVFWnuvuCsXNstc3n8cHMPo/v93kEAFheSqoJqarXd/c7x84xlKp6VWb3Fvl0kg/2pg9jVd3Z3RePlW1IVfX0zC6jOd7dv1tVVyV5XZKvJvnP3f2hUQPCE1iEsWfRx4spnOdVdfs2i/96kt89/aK7L9u7RNurqt/s7r+36fU/S3J5khNJ3t3dt42VDQCA+VJSTUhV3dvdzxk7xxCq6ieSXJPk9iTrmT1W/HB337ux/mvd/dQRIw6mqt6R5Dsyu1zl55K8KclNSb4pyY8kua67f2W0gPAExh57pjBeTOE8r6rfSfLUJG8/vWjj90dOv6e7f3mEaGeoqv/X3edt/P5nklyZ5GiSA0l+LMk/7+6bxksIAMC8KKkWSFU90ReYqxbxsozdqKo/zewx4p/aeKz4zyb5u0m+p7tPbP6SMnVVdW+SlyR5dmb3frm0u+/aWPfdSX6pu188YkRW3KKPPVMYL6ZwnlfV+Unem+SPu/stG8sW7nK/zaVjVd2dWSF5fOP1dyZ5Z3dfOl5CAADmxdP9Fst9SX40yU/vsP4bOyyfoudmdn+R048Vv6aqTib5SFVdltn/8C+LZyQ50d1fqqpvnP7iuuEPkvyVkXLBaYs+9kxhvFj487y7v1pVr03y9qr6xWyaQbVgNv/v2XOSfHLT6+NJvnUvwwAAsHfMpFogVXVhkv+902UrVXWiu9f2ONZcVNVnkry+u39/y/Ibk7w8yWVjz4wYSlV9Ksnf7+7PbrPuO5L8Rnd/294ng5lFH3umMF5M7TyvqrcmuSTJqxZwJtUjSd6dWfn4D5I8u7sf2Fj38sx+lt86XkIAAOblKWMH4FHdfV9m997YyT/aqyx74FeTvHLrwu6+Lsm9Wa5Zfr+UZKdLU67N7D47MJoJjD1TGC8mdZ5395uT3JrkF8bOso3rk9yV5PNJ/lWSp21ad1WS940RCgCA+TOTCgAAAIDRmUkFAAAAwOiUVAAAAACMTkkFAAAAwOiUVAAAAACMTkkFAAAAwOj+PyBgLY65a4ZpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x1440 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot histograms of total net sales for each product\n",
    "plot = sales['Total_Net_Sales'].hist(by=sales['Product_Type'], bins='auto', grid=False, figsize=(20,20))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at Easter and Gift Basket Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Product_Type</th>\n",
       "      <th>Net_Quantity</th>\n",
       "      <th>Gross_Sales</th>\n",
       "      <th>Discounts</th>\n",
       "      <th>Returns</th>\n",
       "      <th>Total_Net_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1482</th>\n",
       "      <td>Easter</td>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>-3.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Product_Type  Net_Quantity  Gross_Sales  Discounts  Returns  \\\n",
       "1482       Easter             1         38.0       -3.8      0.0   \n",
       "\n",
       "      Total_Net_Sales  \n",
       "1482             34.2  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check out Easter \n",
    "sales.loc[sales['Product_Type'] == 'Easter'] # only one entry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product_Type</th>\n",
       "      <th>Net_Quantity</th>\n",
       "      <th>Gross_Sales</th>\n",
       "      <th>Discounts</th>\n",
       "      <th>Returns</th>\n",
       "      <th>Total_Net_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1690</th>\n",
       "      <td>Gift Baskets</td>\n",
       "      <td>1</td>\n",
       "      <td>19.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Product_Type  Net_Quantity  Gross_Sales  Discounts  Returns  \\\n",
       "1690  Gift Baskets             1         19.5        0.0      0.0   \n",
       "\n",
       "      Total_Net_Sales  \n",
       "1690             19.5  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check out gift baskets\n",
    "sales.loc[sales['Product_Type'] == 'Gift Baskets'] # only one entry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Table of Mean, SD, Min and Max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Returns</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Total_Net_Sales</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Net_Quantity</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Gross_Sales</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Discounts</th>\n",
       "      <th colspan=\"3\" halign=\"left\">Returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Product_Type</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Art &amp; Sculpture</th>\n",
       "      <td>0.0</td>\n",
       "      <td>251.0</td>\n",
       "      <td>749.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12732.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>268.0</td>\n",
       "      <td>866.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14935.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>-594.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>-1609.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basket</th>\n",
       "      <td>0.0</td>\n",
       "      <td>245.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3427.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>261.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>3825.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-317.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>-376.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skin Care</th>\n",
       "      <td>0.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1189.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>237.0</td>\n",
       "      <td>364.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1216.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christmas</th>\n",
       "      <td>0.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2114.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>212.0</td>\n",
       "      <td>323.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2160.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>-46.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>-380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Home Decor</th>\n",
       "      <td>0.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1701.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>207.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1748.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>-74.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>-68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>One-of-a-Kind</th>\n",
       "      <td>0.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>182.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Recycled Art</th>\n",
       "      <td>0.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>165.0</td>\n",
       "      <td>311.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1554.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jewelry</th>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1517.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>96</td>\n",
       "      <td>148.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1584.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>-84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Textiles</th>\n",
       "      <td>0.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>135.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>564.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>-58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Furniture</th>\n",
       "      <td>0.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>127.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>-11.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>-70.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories</th>\n",
       "      <td>0.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>100.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>472.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kitchen</th>\n",
       "      <td>0.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>-106.0</td>\n",
       "      <td>1078.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>69</td>\n",
       "      <td>100.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>-106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Music</th>\n",
       "      <td>0.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>91.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>328.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>-110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fair Trade Gifts</th>\n",
       "      <td>0.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>412.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>81.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Soapstone</th>\n",
       "      <td>0.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>72.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kids</th>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>61.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Easter</th>\n",
       "      <td>0.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gift Baskets</th>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Returns Total_Net_Sales                        Net_Quantity  \\\n",
       "                    amax            mean    std   amin     amax         mean   \n",
       "Product_Type                                                                   \n",
       "Art & Sculpture      0.0           251.0  749.0   13.0  12732.0          4.0   \n",
       "Basket               0.0           245.0  366.0    0.0   3427.0          3.0   \n",
       "Skin Care            0.0           234.0  357.0   17.0   1189.0          9.0   \n",
       "Christmas            0.0           198.0  313.0    0.0   2114.0          8.0   \n",
       "Home Decor           0.0           196.0  275.0   18.0   1701.0          3.0   \n",
       "One-of-a-Kind        0.0           176.0   79.0  122.0    405.0          1.0   \n",
       "Recycled Art         0.0           161.0  305.0   21.0   1525.0          4.0   \n",
       "Jewelry              0.0           141.0  217.0    0.0   1517.0          5.0   \n",
       "Textiles             0.0           120.0  134.0    0.0    520.0          3.0   \n",
       "Furniture            0.0           117.0   72.0   34.0    280.0          2.0   \n",
       "Accessories          0.0            97.0   81.0   22.0    458.0          2.0   \n",
       "Kitchen              0.0            95.0  136.0 -106.0   1078.0          5.0   \n",
       "Music                0.0            83.0   89.0   16.0    315.0          3.0   \n",
       "Fair Trade Gifts     0.0            79.0   98.0   12.0    412.0          4.0   \n",
       "Soapstone            0.0            69.0   68.0    0.0    359.0          3.0   \n",
       "Kids                 0.0            59.0   50.0   16.0    264.0          2.0   \n",
       "Easter               0.0            34.0    NaN   34.0     34.0          1.0   \n",
       "Gift Baskets         0.0            20.0    NaN   20.0     20.0          1.0   \n",
       "\n",
       "                                 Gross_Sales                        Discounts  \\\n",
       "                   std amin amax        mean    std   amin     amax      mean   \n",
       "Product_Type                                                                    \n",
       "Art & Sculpture    7.0    1   59       268.0  866.0   13.0  14935.0      -9.0   \n",
       "Basket             3.0    0   30       261.0  392.0   24.0   3825.0      -8.0   \n",
       "Skin Care         12.0    1   32       237.0  364.0   18.0   1216.0      -3.0   \n",
       "Christmas         13.0    0   90       212.0  323.0   18.0   2160.0      -5.0   \n",
       "Home Decor         3.0    1   19       207.0  284.0   18.0   1748.0      -8.0   \n",
       "One-of-a-Kind      0.0    1    1       182.0   90.0  125.0    450.0      -6.0   \n",
       "Recycled Art       8.0    1   37       165.0  311.0   25.0   1554.0      -4.0   \n",
       "Jewelry            9.0    0   96       148.0  230.0   12.0   1584.0      -5.0   \n",
       "Textiles           2.0    0    8       135.0  147.0    1.0    564.0      -8.0   \n",
       "Furniture          1.0    1    3       127.0   86.0   38.0    350.0     -11.0   \n",
       "Accessories        4.0    1   25       100.0   84.0   22.0    472.0      -3.0   \n",
       "Kitchen            8.0   -1   69       100.0  138.0    0.0   1104.0      -3.0   \n",
       "Music              4.0    1   16        91.0   96.0   16.0    328.0      -3.0   \n",
       "Fair Trade Gifts   6.0    1   22        81.0  101.0   12.0    432.0      -2.0   \n",
       "Soapstone          3.0    0   13        72.0   69.0   12.0    359.0      -1.0   \n",
       "Kids               2.0    1   12        61.0   51.0   16.0    264.0      -2.0   \n",
       "Easter             NaN    1    1        38.0    NaN   38.0     38.0      -4.0   \n",
       "Gift Baskets       NaN    1    1        20.0    NaN   20.0     20.0       0.0   \n",
       "\n",
       "                                   Returns                \n",
       "                   std   amin amax    mean   std    amin  \n",
       "Product_Type                                              \n",
       "Art & Sculpture   37.0 -594.0  0.0    -9.0  92.0 -1609.0  \n",
       "Basket            20.0 -317.0  0.0    -8.0  37.0  -376.0  \n",
       "Skin Care          8.0  -27.0  0.0     0.0   0.0     0.0  \n",
       "Christmas          9.0  -46.0  0.0    -9.0  49.0  -380.0  \n",
       "Home Decor        13.0  -74.0  0.0    -3.0  13.0   -68.0  \n",
       "One-of-a-Kind     13.0  -45.0  0.0     0.0   0.0     0.0  \n",
       "Recycled Art       7.0  -29.0  0.0     0.0   0.0     0.0  \n",
       "Jewelry           10.0  -77.0  0.0    -2.0  11.0   -84.0  \n",
       "Textiles          12.0  -44.0  0.0    -7.0  18.0   -58.0  \n",
       "Furniture         18.0  -70.0  0.0     0.0   0.0     0.0  \n",
       "Accessories        5.0  -14.0  0.0     0.0   0.0     0.0  \n",
       "Kitchen            4.0  -26.0  0.0    -2.0  11.0  -106.0  \n",
       "Music              5.0  -22.0  0.0    -5.0  21.0  -110.0  \n",
       "Fair Trade Gifts   4.0  -20.0  0.0     0.0   0.0     0.0  \n",
       "Soapstone          3.0  -20.0  0.0    -1.0   6.0   -44.0  \n",
       "Kids               3.0  -14.0  0.0     0.0   0.0     0.0  \n",
       "Easter             NaN   -4.0 -4.0     0.0   NaN     0.0  \n",
       "Gift Baskets       NaN    0.0  0.0     0.0   NaN     0.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create table \n",
    "total_sales = sales.groupby('Product_Type').agg([np.mean, np.std, np.min, np.max])\n",
    "\n",
    "# Round all values\n",
    "total_sales = total_sales.round()\n",
    "\n",
    "# rearange columns so that total net sales is first\n",
    "cols = total_sales.columns.tolist()\n",
    "cols = cols[-5:] + cols[:-5]\n",
    "total_sales = total_sales[cols]\n",
    "\n",
    "# rearange rows from highest to lowest for total net sales\n",
    "total_sales = total_sales.sort_values([('Total_Net_Sales','mean')], ascending=False)\n",
    "total_sales"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stacked Bar Chart of Net Sales, Discounts and Returns for all Products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get only the mean columns \n",
    "df = total_sales.iloc[:, total_sales.columns.get_level_values(1)=='mean'].copy(deep=True)\n",
    "\n",
    "# collapse hierachical dataframe\n",
    "df.columns = ['_'.join(col).strip() for col in df.columns.values]\n",
    "\n",
    "# make all values in table positive\n",
    "df[['Discounts_mean', 'Returns_mean']] =  df.loc[:, ('Discounts_mean', 'Returns_mean')].abs()\n",
    "\n",
    "# Remove Net quantity and gross sales\n",
    "df.drop(df.columns[[1,2]], axis = 1, inplace=True)\n",
    "\n",
    "# Stacked bar chart\n",
    "df.plot(kind='bar', stacked=True)\n",
    "plt.grid(False)\n",
    "\n",
    "# labels\n",
    "plt.title('Mean Product Net Sales, Discounts and Returns')\n",
    "plt.xlabel('Products')\n",
    "plt.ylabel('US $')\n",
    "\n",
    "# legend\n",
    "plt.legend(['Mean Net Sales','Mean Discounts','Mean Returns']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NAMxe85/m57zT+yU5I4Y5uUirNW9GL0t/hnLpPhnaREitgW93D7hVXX9sfr6pvw2a0nGtUnJ/bFt1Y/NznSEOXuz0VNvvCw1z3z8zpfvDcMpKTm7Nj4jRnvb9UOBRysnMpwfYrvU5se10nJi0X52Y7ucTEWMjYsFh7NLX/1R7CcbvTm8sfWi9Pi+h9EufIZn5fGZel5mHAns1i9cc5vOXBmVCLo2CzHyxuXQ7nEGB51L6ab8EOKGjlvlUImLljpnmWq3wffUfb+8rXUXT5/Lh5u7ag20fZcbQzpkRW7MJLtds9u9+tpnYx0P+IyI+3Dl7YR/HXZwprdoXDOnJTfsYL4mI/ZhScecbmdlXTJ3WaX7eMj3H7ZLW4OSNI2LTfrY5qPl5L6XUZkurlv1iQH+18F/bz3KAW9t+n+bYzf/L1n3tmGUmydbx94uIhfvaLiLmjoj2k432BHLdAWKbYc2JdOsEfh+mHtDY7pTm5yuY8lr3KcpMnu2Jd6usKszY81kc+HtEbN9cCRoohtUoVU9g6v+p9iuH/X1uDTrra6fMvBG4prl7WFN/vr/YFmj/e0fEuwZpDGm12id1ul5pFmZCLvWIzLwP+HxzdxPKKP+tm4FPRMRCUaY0P43S2rhC2+6t0mk7Rpk2+2XNPotFxK6UOujbdeWJ9K/VcrXJELZ9kpI8TM+tr4GjC1Ba4e6IMh33ZhGxSBTzNCc4n6O0pC5GadE/uI/HmUbzGAtExKsi4tPA9ZT+pwH8iCkT4QymlbRcPeBWdV1IqaMPcH5E7N4894iIlSLiVMrgRCizdU4uQZmZfwIub+5+v0l+xkbEXBHx2oj4EWXSof5cSxloC/DliFi3Oe78EbED8DdK163+7Ed5Xy0N/DYi3h4RL42IOSLi5RHxKcr/yQfb9vkTU1p3D2+e40sjYoWI2JCR91VKN58F6OcqQGZeAvykuXtARJwTERs0JxMviYilIuIDzYnpz5hSlak1qPmvzd1PRMRGzft/iYgY7oRUS1DGrdwcEV9oHqv1uTN/RKwVEYdQ6n2/FLiBMnFZy5VM6cp2UkS8snkvjImI10TEyZTXf3p8gtL3ewngT83J+BJNbPNGxOsi4ihKrfet2vZ7A+VE47Tms3ahZp/5opQObV3p+mmPdAXUrCR7oBi6N28z440+JvoY4n4T6WNioLb1+zJlEp7Wra/pmzdv22d+yqDB/va5j/IF2N/EObc36w6a3riH8Lw/3ez/twp/q2v7eP36e13/CKzYz+O0tnmOKVOOd05ZnpSuB/sCMcT4lmt7nHVm8P14+3Tse8pQ38uUeup/GOB1fBHYf4DneUfHvu2v3xVtv0/oY/9tO/432o/7DKUFtnV/+T7234IpE2v19x44vmOfo/t57/x4Ov8+A77GwMc6jrNzH9vMS0mGB3s/PwfM07Hv2/t5zz48jOeyCFMmQRvK/9TP6WMyJso09e2xdMZ1fn/vBwaZtKn5Wz/Y8Xidn6sJHNa2zxFDeD43AkvOyOeRN2993Wwhl3pMllH+qwFfoySSj1C+qB6itDYdRKnB/cu2fR6l1N9ttfq8QGkNvJpy+fsVTBlYVcs5lARhrYh4fTcPnJnrULrK7EeZUvtWymx8SRlEeSuldXZb4HWZ+a9BHnJOSh/cuSktqA9RWsbPpUzcslxmHpGZOcQQP0xpUb8xM68d6vOqIUv3ow2Bj1AS6Icpic5dwJnAazPzsH72nUQpMXkspbX7OUq3kAsofbs/MMixf0yZ/fQyyknPc5TE8JvAqpTZVwfa/+fNdodRJq95lPK/cjflb/d2SkLcbm9KGcwbKEn/E5SW9KsGOtYMOJFSprJfWSYw2oHSl/8HzfZPUp7LPZQE+GPAEpn5ZMe+F1Hq8F9BaaF+hnKSNOT67Jn5QGauRJk19GDKRESTmDIg+THKa3QysElmbpF9lArMzJMpf89fNfu+QHkfnQa8ITP7K4c4lBh/TqkytS/luT5A+X9/nPK/eiylcsrn23bbn1Km8XuUxPvxZp+HgN9QJhNbNzP/gzTCYujfF5I0YyLiREpZtwszc5va8fSCKIPDbqV0UXhvZp5VNyJJUreZkEvqmohYltKiOYbSAvbbyiFVFxHHUCqy/B1YK2d8dlBJ0kzGLiuSuiYz76B0L4AykOulNeOpLSI2YkqJu31MxiVp9mRCLqnbPk+pZrIycHLEdNWknuk15djOpXwOfytL9QxJ0mzILiuSui4iVqQMqpuPkox+snJIXdXUO/8N5aTkWspA0meqBiVJqsaEXJIkSarILiuSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFc9YOoLYtttgif/7zn9cOQ5IkSbO26G/FbN9C/sADD9QOQZIkSbOx2T4hlyRJkmoyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqmrN2AJIkScOxzrbbdv2Y1/74x10/pobuoIMO4vTTT+df//pX7VCmiy3kkiRJI2znnXcmIvjkJz85zbr999+fiGC33XarENm0br/9diKCiOCss86aat0hhxzC8ssvP6zHW3755TnkkEOGtO0///lPdtppJ5ZddlnGjh3L0ksvzcYbb8xhhx3Gc889N6zjzsxMyCVJkkbBoosuyoknnsi99947edkjjzzCcccdx6KLLloxsr5tvPHGfP7zn+fZZ5/tyvFuvfVWXv3qV3Pvvfdyyimn8Le//Y2zzz6bzTffnOOPP54nnniiK3H0AhNySZKkUbDWWmux0UYbcdRRR01eduyxx7Lhhhuy2mqrTbP9N7/5TVZeeWXGjh3LKquswre+9S0yc/L6HXbYgaWXXpq5556b8ePHs/XWW/PPf/5z8vpTTjmFOeeck3POOYcNNtiA+eabjzXWWIPLL798SPF+7nOf47HHHuO4444bcLtLL72UDTbYgJe+9KUss8wy/N///R+PP/44ABMmTGDSpEkceOCBk1vdJ06c2OfjnH/++Tz++OOcc845bLLJJqy88spstNFGHHDAAfzjH/9gvvnmA+Dee+/lta99LePHj2fuuedm6aWX5iMf+cjkY/bnrLPOYu2112bs2LGssMIKfOELX5iq1f2SSy7hda97HfPNNx+LLbYYm2yyCX/605+G9FqNNBNySZKkUXLggQdy/PHHc9999/HUU0/xjW98gwMOOGCa7Q466CCOPvpoDj/8cP76179y4IEHst9++3H66adP3mbVVVflhBNO4G9/+xsXXHAB999/P+9617umepwXXniBb37zm3zpS1/i97//Pauuuio77rgjzzzzzKCxzj///BxwwAEccsghPProo31u8+tf/5qtt96aHXfckWuuuYaTTz6ZX/3qV3zqU58C4Oyzz2appZZir7324t///jf//ve/ed3rXtfnYy299NIAXHzxxdOsm2eeeZhjjjkAyEze8pa38KMf/Yjrr7+e73znO5x//vl87nOf6/e5nHLKKXzsYx/jM5/5DH/961/52te+xoknnsgRRxwBwE033cS2227LNttsw5/+9CfOOOMM1llnHW688cZBX6fR4KBOSZKkUbLxxhuz3nrrcfTRR7P00kuz9tprT5OgPvnkkxx11FH86Ec/YssttwRgtdVW46qrruIHP/gBO+20EwAHH3zw5H1WWWUV9t13X7bddlsefvhhFlxwQQDmmGMOrrzySiICKK3e559/PrfccgtrrrnmoPF+9KMf5Rvf+AZHHnkkhx566DTrDz74YD75yU9OTsDXWGMNDj74YHbaaSdOPPFEFl98ceacc04WXHDBQfueb7/99px77rl84AMf4HOf+xzrrbcea665JptssgmbbLLJ5IR8iSWWmOq5r7zyyrzvfe8bsOX/oIMO4rDDDmPnnXcGyut58803c8IJJ3DggQdy/fXX8/zzz/PBD36QJZdcklVXXZXNNtts0NdntJiQS5IkjaIDDjiAd73rXSywwAKceeaZ06y/8cYbeeqpp3jHO94x1fIXXnhhqqR24sSJnHjiiVx77bU89NBDPPLIIwA8/vjjkxNyYHIyDjB+/HgAHn744SHFOmbMGA499FB22203Pv7xj0+z/k9/+hO///3v+cY3vjF5WWby7LPPcs8997DUUksN6TgAc845J+effz7XX389v/71r7n++uu59NJLOfLII1l//fX59a9/zbhx43jxxRf5wQ9+wHnnncc///lPHn30UR5++GGWXXbZPh/3/vvvZ9KkSXz6059mzz33nLz8xRdfnNwFaNNNN+UVr3gFa6yxBm9+85t5zWtew9ve9jZWXXXVIcc/kkzIJUmSRtHmm2/O6quvztixY9l4442nWf/iiy8C8MMf/pBVVlllqnVzzTUXUPo7v/3tb+c973kPhx56KEsssQR///vf2XXXXQc8dntyPlQ77rgjRx99NF/84hdZbrnlpol17733ntxq3256B6qutdZarLXWWpPvX3rppWy++eaceeaZ7LHHHuy7774ce+yxfPKTn+QTn/gEiyyyCN///vf5xS9+0efjtV7Pr33ta2yyySZ9bvOyl72MG264gQsvvJArr7ySM888k3333ZczzzyTHXbYYbqex4wwIZckSRpl55xzzuQuGJ1WW201xowZw2233cY222zT5zaXXHIJ6667LmecccbkZU899dSoxBoRHHXUUbzlLW/h3e9+91Tr1llnHW644YYBW5Jf+tKX8uSTTw56nJtvvpmVVlppmpOGV77ylQCT+71ffPHFfPSjH+Xwww+fvM1FF13U7+MuuuiiLLHEEtx000187GMf63Ob5557jrFjx7LDDjtMTsC33HJLzj77bBNySZKkWVFnS3O7+eefn7322osDDjiAF198kTe/+c1kJhMnTuSOO+7gmGOOYfXVV+f000/nkksu4eUvfzl/+9vf+MpXvjJq8W666aZsttlmnH322SyzzDKTl3/xi19kq6224iMf+Qi77LILCyywAH/5y184++yzufDCC4HS4n3uueeyzTbb8Nxzz7Hiiiuy+OKLT3OM73znO0ycOJEPfehDbLDBBsw///z861//4pBDDmGFFVbgve99LwCrr746l112GVdffTVjx47liiuu4IQTTmCeeebpM/aI4KCDDuKjH/0o8803H+94xzsYO3YsV111FVdeeSWnnnoqxx13HL/97W/ZfffdWX755bntttu47rrr+qwb3w0m5JIkaaYyK86aeeihh7LUUkvx3e9+l/33359x48ax1lprTR48+ZGPfGTyJDrPP/88G264ITvssAN/+ctfRi2mI488kksvvXSqZVtssQU///nPOfTQQ9l0000BWHHFFadqVT788MPZeeedmTBhAvPNNx8/+9nP+kzIWxMjnXDCCRx00EE8+uijLL744rzjHe9g//33Z+GFFwZKOcjddtuNTTfdlHHjxrHVVlux1VZbDTioc4899mD++efnq1/9Kscccwxjxoxh1VVXnXzMCRMmcPnll7PLLrvwwAMPsPTSS/PhD3+Yvffee8ZetOkU7fUtZ0frr79+XnPNNbXDkCRJ0qyt3w791iGXJEmSKqqSkEfE/BHx7Yg4vWP5OyPi1oh4OiKujog129bNFRHHRcTDEfFIRBwfEXO1rV8jIq5q9r01Irbr5nOSJEmSpkfXE/KI2Bp4CPhYx/JlgVOATwDjgYuB82LK0Nu9gHWBNYE1gHWAzzb7BnAecEmz7yeAkyOi/xEUkiRJUg/oekKemRdm5pzAwR2rtgEuzcyfZuZjwOHA4sDazfrtgUMy867MvAs4CmiNIFgTWAQ4NDMfy8yfAhOBbUf1yUiSJEkzqJf6kK8MTGrdycwXgFub5dOsB27uWHdnTj1CtX29JEmS1JN6KSGfB+iscP8EMK6f9U8A8zTdVQbbdyoRsUdEXBMR19x///0zHPiECROYMGHCDD+OJEmSZj+9lJA/CYzpWDY3JbHua/3cwFNNq/hg+04lM0/IzPUzc/3x48fPcOCSJEnS9OqlhPxmYLXWnYiYA1gFuKWv9cDqHetWavbpa70kSZLUk3opIb8QmBARW0bEOGAf4D7g2mb9ecA+EbFURCwJ7A2c26y7AbgX2C8ixkXEW4AJwI+7F74kSZI0fDXKHm4ZEQ9QEu7tIuKBiPhQZk4CdgWOBR6kVEjZrm2g5jHAdcA/mtv1lEorNNtsD2zd7Hsc8KHM/HfXnpgkSZI0Hebs9gEz82eUEoV9rTsHOKefdc8Cuze3vtZfD7xmhMKUJEmSuqKXuqxIkiRJsx0TckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpop5LyCNiuYi4MCIejoj7IuKkiJi3WffOiLg1Ip6OiKsjYs22/eaKiOOa/R6JiOMjYq56z0SSJEkaXM8l5MDZwPXAEsA6wArAlyNiWeAU4BPAeOBi4LyIiGa/vYB1gTWBNZp9P9vFuCVJkqRh68WEfC3g0sx8KjP/A/wceDmwTbP8p5n5GHA4sDiwdrPf9sAhmXlXZt4FHAXs0P3wJUmSpKHrxYT8aOCsiPhwRKxCSbSPAVYGJrU2yswXgFub5XSuB25uWydJkiT1pF5MyH8J3ANsAPwJeBD4GzAP8FTHtk8A45rfO9c/AczT1qVlsojYIyKuiYhr7r///hEOX5IkSRq6nkrII2JBSt/wd2XmzsDSlMT6ROBJYEzHLnM36+lj/dzAU5mZncfJzBMyc/3MXH/8+PEj+hwkSZKk4eiphBxYEZgjM/8NkJmPAqdS+onfDKzW2jAi5gBWAW5pFk21Hli9bZ0kSZLUk3otIf878HREfCki5o2IxYE9KAM7LwQmRMSWETEO2Ae4D7i22fc8YJ+IWCoilgT2Bs7t+jOQJEmShqGnEvLMfBLYEtgYuBf4C/BPYL/MnATsChxL6Ve+LbBdW5eUY4DrgH80t+splVYkSZKknjVn7QA6ZeZfgDf1s+4c4Jx+1j0L7N7cJEmSpJlCT7WQS5IkSbMbE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqaKeTMgj4o0R8auIeDQinoyIlzXL3xkRt0bE0xFxdUSs2bbPXBFxXEQ8HBGPRMTxETFXvWdR34QJE5gwYULtMCRJkjSAnkvII2JT4GTgq8DiwHLAYxGxLHAK8AlgPHAxcF5ERLPrXsC6wJrAGsA6wGe7GbskSZI0XD2XkANHA7tl5iWZ+WRm3p+ZzwPbAJdm5k8z8zHgcErCvnaz3/bAIZl5V2beBRwF7FDjCUiSJElD1VMJeUQsCawF7BER/42IB5uuJ2OAlYFJrW0z8wXg1mY5neuBm9vWSZIkST2ppxJySveUJ4BjgWUord9rAUcC8wBPdWz/BDCu+b1z/RPAPG1dWiaLiD0i4pqIuOb+++8f2WcgSZIkDUOvJeQJPJOZV2bms5l5N3AMsBXwJDCmY/u5KYk3fayfG3gqM3Oag2SekJnrZ+b648ePH/EnIUmSJA1VryXktwILR8RibcvmBB6kdEFZrbUwIuYAVgFuaRZNtR5YvW2dJEmS1JN6KiHPzPuBnwLfjYiXNZVV9gZOBy4EJkTElhExDtgHuA+4ttn9PGCfiFiq6Yu+N3But5+DJEmSNBw9lZA3PkjpC34b8DvgR8B3MnMSsCulf/mDwLbAdm1dUo4BrgP+0dyup1RaUQ+xNrokSdLU5hxsg4h4E7AJcHBmPtcs2xb4EhDACZn57ZEKKDMfAt7bz7pzgHP6WfcssHtzkyRJkmYKQ2khPxBYrC0ZXwY4G/gPMBE4IiLeN2oRSpIkSbOwQVvIKTNetnf92Ba4B9gqM1+MiLuAjwNnjHh0kiRJ0iyu34Q8Ii6nlCFcEDgkIvahdFFZERgLXNaU+F4YWDUift2sz8zcZJTjliRJkmYJA7WQ70xJsP8MfB24srl/OfAN4LRmu7dQBlTuMlpBSpIkSbOqfhPypqpJq6V8J+AyYDNgWeDMtvULA3e17kuSJEkauqH0If8cZfDm3c3972fmbQDNtPTva9ZLkiRJGqZBE/LMvDUi1gQ2Bh7OzCvbVi8GnAhcMkrxSZIkSbO0obSQk5mPABf1sfxeSn9ySZIkSdOhF2fqlCRJkmYbJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRdOVkEfEYhHx6ohYcITjkSRJkmYr/SbkEfHWiPhLRGzZsfwQ4C7gauCeiPi/UY5RkiRJmmUN1EL+PmBMZv6stSAiNgT2B34HbA0cAXw1It48qlFKkiRJs6iBJgZ6FXB6x7KdgAQ+mJmTgEsiYnHgC8CloxOiJEmSNOsaqIV8KeCGjmWvA+5okvGWXwGvHOnAJEmSpNnBQAn5c8AcrTsRMTewOvDnju2eHuRxJEmSJPVjoET6RmCTtvubUbq4XNGx3RrAPSMclyRJkjRbGKgP+VeB8yPiWWASsBfwGPDDju12ZNquLZIkSZKGoN+EPDN/EhEHUqqqzAPcDbw7M//b2iYidqH0H//KaAcqSZIkzYoGaiEnMw+LiKOB+TPzgT42+S2lGss/RiM4SZIkaVY3YEIOkJnPAn0l42TmLSMekSRJkjQb6Tchj4jvD7DfM5SBnBMzs3OQpyRJkqQhGqiFfK0B1s0BLAF8MSJ+DWydmU+NaGSSJEnSbGCgQZ2vHmzniNgcOA04GNh7BOOSJEmSZgszNKFPZv4S+Dqw/YhEI0mSJM1mRmKGzRsp3VckSZIkDdNIJOQvBx4cgceRJEmSZjszlJBHxErAp4BLRiYcqfsmTJjAhAkTaochSZJmUwOVPTxngP1eQumm8hrgJmC/EY5LkiRJmi0MVPZw/ADrngVuBU4FfpCZT49oVJIkSdJsYqCyh2/qZiCSJEnS7GgkBnVKkiRJmk4m5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuRSD5owYQITJkyoHYYkSeoCE3JJkiSpIhNySTM1ryZIkmZ2JuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFJuSSJElSRSbkkiRJUkUm5JIkSVJFPZmQR8TYiPhNRPy2bdk7I+LWiHg6Iq6OiDXb1s0VEcdFxMMR8UhEHB8Rc9WJXpIkSRq6nkvII2IO4Gxg7rZlywKnAJ8AxgMXA+dFRDSb7AWsC6wJrAGsA3y2a0FLkiRJ06nnEnLgeOAm4Ltty7YBLs3Mn2bmY8DhwOLA2s367YFDMvOuzLwLOArYoYsxS5IkSdOlpxLyiDgSeElmfq5j1crApNadzHwBuLVZPs164Oa2dZIkSVLP6pmEPCJ2BVYBdu9j9TzAUx3LngDG9bP+CWCeti4tncfaIyKuiYhr7r///hkLXJIkSZoBPZOQU/p+bwE8ERFPAycCr29+fwkwpmP7uSmJN8CTHevnBp7KzOzrQJl5Qmaun5nrjx8/fiSfgyRJkjQsPZOQZ+ZemTm2daO0lP+++f0vwGqtbZuBn6sAtzSLbm5fD6zetk6SJEnqWT2TkA/iQmBCRGwZEeOAfYD7gGub9ecB+0TEUhGxJLA3cG6VSCVJkqRhmLN2AEORmZOaPubHAktREvHt2rqkHAOsAPwDSOAcSqUVSZIkqaf1bEKemadQao+37p9DSbT72vZZSheXvgaESpIkST1rZumyIkmSJM2STMglSZKkikzIJUmSpIpMyCVJkqSKTMglSZKkikzIJUmSpIpMyCVJkqSKTMglSZKkikzIJUmSpIpMyCVJkqSKTMglSZKkikzIJWmETZgwgQkTJtQOQ5I0kzAhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZc0JBMmTGDChAm1w9B08u8nSb1rztoBzAzW2XbbAdf/64YbhrQdwLU//vGMByRJkqRZhi3kkiRJUkUm5JIkSVJFdlmZSQ2le8xQu9LYjUaSJKkeW8glSZKkikzIJUmSpIpMyCVJkqSK7EOuEWO/dkmSpOGzhVySpB7mpE7SrM+EXJIkSarIhFySJEmqyIRckiRJqsiEXJIkSarIhFySJEmqyIRckiRJqsiEXJIkSarIhFySJEmqqKcS8ojYPyL+ERFPRsTtEfHZjvXvjIhbI+LpiLg6ItZsWzdXRBwXEQ9HxCMRcXxEzNX9ZyFJkiQNXU8l5EACuwILAW8HPhsRWwJExLLAKcAngPHAxcB5ERHNvnsB6wJrAmsA6wBTJfSSJElSr+mphDwzD8/MqzLz6cy8HriCklgDbANcmpk/zczHgMOBxYG1m/XbA4dk5l2ZeRdwFLBDd5+BJEmSNDw9lZC3i4g5gPWBvzeLVgYmtdZn5gvArc3yadYDN7et63zsPSLimoi45v777x/p0CVJkqQhm7N2AAM4EriP0jUFYB7g3o5tngDGta1/qmPdPBERmZntO2XmCcAJAOuvv/5U6zTrWWfbbQdc/68bbhjSdtf++McjE5AkSVKbnkzII2JfYGtg46YlHOBJYEzHpnNTEu++1s8NPNWZjEu9wJMESZLU0lNdVqI4EngvJRlvbxG/GVitbds5gFWAW/paD6zetk6SJEnqST2VkANnAK9m2mQc4EJgQkRsGRHjgH0oXVqubdafB+wTEUtFxJLA3sC53QlbkiRJmj691mXlPcALwANTqhlye2aumJmTImJX4FhgKUoivl1bl5RjgBWAf1DKJ55DqbQiSepBEyZMAGDixIlV45Ck2noqIc/MGGT9OZREu691zwK7NzdJkiRpptBrXVYkSZKk2YoJuSRJklSRCbkkSY0JEyZM7tsuSd3SU33IJdUzUrXRwfrokupwoLBmVraQS5IkSRWZkEuSpGGze480ckzIJUmSpIpMyCVJkqSKTMglSZKkiqyyIqlnDaWiy1Crv1j5RZLUq2whlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqMiGXJEmSKjIhlyRJkiqyDrkkDYO10SVJI80WckmSpFEyYcIEJkyYUDsM9TgTckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSLrkEvSLGCwmufWRpek3mVCLkkaFZ4kSNLQ2GVFkiRJqsiEXJIkSarIhFySJGk2MmHCBCZMmFA7DLUxIZckSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqsg65pCFZcaONaocgzbCRqo0O1keXNHJMyCVJqsiTBEl2WZEkSZIqMiGXJEmSKjIhlyRJkioyIZckSZIqclCnJEmaylAGkA51sKkDTaXBmZBLkqSZwkhVpPEkQb3GLiuSJElSRSbkkiRJUkUm5JIkSVJF9iGXJEmaTvZr10iwhVySJEmqyIRckiRJqsiEXJIkSarIPuSSJEmzkJHq1w72be8WW8glSZKkikzIJUmSpIpMyCVJkqSKTMglSZKkikzIJUmSpIqssiJJqmLFjTaqHYIk9QRbyCVJkqSKTMglSZKkikzIJUmSpIrsQy5JkqRRNZRZQYdqVpw91BZySZIkqSITckmSJKkiE3JJkiSpIhNySZIkqSITckmSJKkiq6xIkiRpttNLlV9MyCVJaqy40Ua1Q5A0G7LLiiRJklSRCbkkSZJU0SyVkEfEUhHxi4h4KiLujoj/qx2TJElSL1lxo43sntVjZqmEHDgJuA1YAngn8KWI2KBuSJIkSVL/ZplBnRGxALApsEhmPgL8ISLOBHYArqoanCRJktSPWSYhB1YEHmuS8ZabgS0qxSNJkmZzdg3RUERm1o5hRETEG4CzM3OptmW7Ah/MzDd2bLsHsEdzdxXgphEIYRHggRF4nJHWi3EZ09AY09D1YlzGNDTGNDS9GBP0ZlzGNDTGNHQjFdcDmdlnQ/Gs1EL+JDCmY9ncwBOdG2bmCcAJI3nwiLgmM9cfycccCb0YlzENjTENXS/GZUxDY0xD04sxQW/GZUxDY0xD1424ZqVBnf8CXhYR49uWrQ7cUikeSZIkaVCzTELe9B3/FXBwRCwQEesD7wXOrRuZJEmS1L9ZJiFv7AasBPwXuBD4Umb+tkvHHtEuMCOoF+MypqExpqHrxbiMaWiMaWh6MSbozbiMaWiMaehGPa5ZZlCnJEmSNDOa1VrIJUmSpJmKCbmkmUpErNTHsrkjYtka8UiSNKNMyKdTRLwuIg6OiO82998QEa+vHZdmThFxfETMXTuOmcSNfSwbB/yl24H0soh4b0S8v/l9vYi4OiJ+GhHL1Y5NkmYWETEuIka9TLgJ+XSIiI8DPwYWBnZuLQaOqBRSz2oq3nw3Iu6MiKeaZR+MiP1rx9YuIlaNiCUrhrAd8GLF489Moo9lywJzdTuQlohYqNaxB/B54N/N718D/gRcA3ynWkQzgR74LOhpETFXRMxbO46WiNgzIj7a/P6WiPhvRPw9Il7ZA7HtGBE/iIifN/ffGhFb146r10TE67uR8A5VRBwVEZ9tfn8/8BDwQES8aVSP66DO4YuI24BtMvP6iHgqM18aEfMBd2bmgpVj2y0zv9ex7GXAZpnZ9RKQEXEW5cTvGOA3zWu1KvCTzFyl2/G0xXU6cHNmHhwRnwGOBJ4Gdq30Op0GnJOZF3X72H1pZrkdUGZ+vxuxtETEnUACSwF3t68CFgOOzswqJ3oR8SRwMfB94BfZAx+sEfEEpdHgBeBRymv0NHBf7c+pXtJrnwV9iYjF6Zj4LjPvqBTLmcBtmXlA27LPAytm5i4V4rkF2D4zr42IPwE/oiRQ78/MjbsdT1tcB1MaWk4GDm6++14DfDszX1MxrvcCL8nM0yNiPeBYyuv10cycVCmmJ4FxmdkTjVIRMQnYPDNviogbKI2t9wOHjubkQCbk0yEiHgSWysynI+LJzJynSXr/kZmLV47t2cwc07FsHHBvZo6rEM+DwHKZ+XjbazUX8L8a8bTF9R/g9Zl5e0T8C9gDeBA4MzPXqBDPL4C1gMs612XmByrEc3nz68qU1+XBttWrA/dk5jpdjumNlOT7MmDTtlUvUE6Gq3yZAETEEsAHgA8C8wGnAidn5q0VY/on8B5gGeCIzFw9IpYG/pqZ4wfee1TjGgN8BtgKWCQzV4uI7YH5M/OkCvH01GdBR2zbA8cDCzD1laHMzDkqxXQvsG5m/qdt2cLAjTW+/5oTz4UoDT//AxYEnqN8x8zf7Xja4roL2DAzJ7U13L0U+G/luG4E9sjM30XEFcB1lNdtvczcqlJMVwMfyMybaxy/U0Q8DixCme39XspnegKPjGbe0jOXCGYylwN7A19uW7YX8Js64UBErDDl13g5Uz68A9iC0kJWw/+AlwGPty1bmalbOGuYF/hvM7PrEpS/6ZzA8pXi+X1z6wmZ+SaApnXgLZl5T2tdRLwd2KFCTL9pjv994OrMfKbbMfSneX2OBI6MiNdSurJdExHXUVrNz83Mp7oc1qHAlcBY4GPNsh2BP3c5jk5fB9YAvgn8oFl2M3Aa0PWEnN77LGj3NeDTlFbfp+uGMpXHOu4/T7184mbgjcAKwA1NQ9kKwBOV4mmZkykNGa2WzwWAR+qEM9nywJ+bhrFXA2+juXJWMaaJwNcj4ujOFZn56+6Hw3XA+4HlgD9l5vMRsTrlSsKosYV8OjT9Cy+kXA5eFrgNeArYKjPvrBTTi5R/+s7+tS8CdwB7Z+aPKsT1OeAdwL7Az4DNKN1Xzs/Mo7odT1tcvwCuApamXO3Ysrl8d25mrjDw3rOPiHgUGN+e/DatPHdm5iKVYnoAWCIzn6tx/IE0rb/bUhLyNwGXUlpXXgX8MDM/3OV4lgXGtlqeIuJ1lBa6fw+856jGdB+wemY+0NZyOAZ4qNJVvJ79LIiIe4BXZOaTNeNoFxEnU75XPpmZTzT9yb9B6XKwY4V4tqDMyD0X8J7MvCAiDgVWycztuh1PW1wnUVrqP0VpmBoHnAi8kJl7VIyr566cRUR/n0dZ438wykzvZwHzUN5TV0TEd4B5M/ODo3VcW8inQ2b+JyJeTTm7XI7S2vvHzHy+YkwvAYiIyzJzs1px9OEo4BnKQLIXKa2FJwPTnAl32ceA71Jax1ofjh8AzqsVUERsTOny0OojfUpmXlkrnsbVwD5MfTVoG6buwtJtP6Nc9emJ/vYAEbEB5W/3bsoJ8A+AXTLzv836VYDdK4W3UURsl5mHURoOxgy2wyh7mikthq2fS1Gvha7nPgvanA+8Ezi9diBtPkOJ5+GIeIjSXeQ3wPsqxfMrSveCuTKzdSX2RKa+KlvDnpTPgUco/3OPU16n99YMih68cpaZL6917H48kpmd5XU/R3mfjRpbyKdDlGohL8vMXrqEOJXmkt0STT+xeShn5V2/xN8MIDkvM5/t9rFnJhGxC3AY8D3gTkrrxW7Avpl5asW4Xg5cQBkQOAkYT2nx3bHSpcSe628Pk1vtzwROzczaXUIAiIh3UU6Afwtsmpljm9bET2fmFhXjOprSbe2TwN+BlSgJ8Y2ZuW+tuHpR0+VpWeD6znU1ByzC5HETSwN3tXdpqxBHX+OmlgD+nJnVq+VExKI0DXft/e5r6tErZ/MCrwUWy8yzImIZ4JnM7PqJej/vqYWBm0bzyrAJ+XSIiJspgzXurx1Lp6af03mUhG6u5kt4Z8oX8k4V4nkcmC978I0WEdtRBihOdaUoM79QIZabKEnuX9uWrQucnZkrdzuedhERlKtBywMPUPpvV7uEHhFf7G9dZn6pm7G0RMQXgKN66SS9uTS9e2Ze2dY1ZCFKRZEq3Y2auMZQrpztRrkk/BSlJXHPGq9f2yDTt1K6Z1UdZNoRW7+Xx7t9oh4Ry9TqkjmQiHguM+fqWLY8pT95tcIBbbH0RIWciBi0zHVWqnLSXB0+j1LJZMXMnLtpUHhfZr6zQjx9vadeBUzMzAVG7bg9mCf1vIjYk9JS+Hk6+mzXekO3RMRvKQOAvg482XwJLwNclZlLV4jnV8Bn2xPNXtC00k0A1gbOaBZvQfkQf3OFeP4HLNk+8K9pMbgrM1/W7XhmRhExtlZCHBEPAwvV/v9v18Q0PjOfiykVjsYBt1dOyF9PGSj1XDOQ8oGaJ+xN39A1gG8DP2g+M18JnJaZa9eKq9e0Wg3bxitNtZouV36JiCubODYEftcRy2rAJaPZ33cwvVYhp5+/21RqxAUQEX+llBQ8r63xYDHgb5m5WBfjqFpa14R8OjRvbJj6zd31D6S+NIPwFsnMZ9u+hMdQvvS6XmopIo4F1gNO6FyXXa5j3S5KqbO1gZuAxZvkYGvKGfm7K8RzAWUSl/0y85lm4OQRwLKZ+Y5ux9MW18bAt4BVmDLxTk+812Fyq8/mlP6rW49m68UgcfwEOCYzr6hx/L5ExC+BszLz5LbPgo8Db8vMLSvG1Ws1h3tqkGlHbD1TIjIils3MO2KAmV6zi6VHm6sHQenm96G2Va0yqNWqnsHksof700eFnMx8oUI8y1Fer9Mo3SP/3loFfLSEVafLWD95y1hKed2uNUhF5dK6DuqcPr02AKHdrZQE+Kq2ZRtTEs8aVqdcku7sLpOU/q21LNh8Ad9L6YpxC3AJ5cOqho9S+iA/1jZQ6krqDZRqOYlSU/sCeqjsWjOI8n3A9pSWjIspFXxqeQI4MSJ+2LmiRheoxieBXzaJy5iIuJTy/7h5pXha/gasSClX1wt6bZBpu6/TIyUi27pZPAiMycyHYHKVk4cy84/djIdSyegtlEaLauNsBjAHZfxUT1TIaSWTEbE28Mv2k4KI+AolZ6g1huN6yuf3T9uWvZ0+xk6MpraTuCq5sS3ks5iI2IqS6B4H7AccTPli3i17ZBbIXhARd1AGkBxAqZO+ByVR+UZmLlMxrqVoLpdlZu1a7a3Bikv3Qt/oiFiDkoS/h1K55weU+QDWqD1YKkopuD5lhdkLW5oB3W9jSjWoSzKzah3kiDiCcnWqJ2oO9/Ig015svW+uBk3MzK81f8vdKSc1h2XmsV2M4wlgfuCpzgF4vaC5OnxVZvZShRyizGz6gcy8qm3ZcsBfMnPhSjG9jtKocjHlM/4USrnkbTLzdwPsOlrxLECZV6J1ZeqlTcPGUlmqVY3OcU3Ihy/KxCR9ysxBpxwfbc1gwN2Y8iV8cvs/X4V4gjLItHPw5G11IoKI+BClXNbzlFrRqwAPAx+sceISEfsBc2bml9uWfRSYIzO/3e142mI4nTKw9OJaMbTF8iLlKsK3M/PqZtn9wCtrJ+Qauui9msM9Nci0I7Y7gFdl5oNtl/JfDvyqxmvVxHQfsE6W8r93UVoyHwYuy8xXdDGO31EqP+1A6YIxjYpXp3q2Qk5EvI9y5eX7lG6S4yllPi/IzH0qxrUkUybjuZvS3a5K1ZeIOIsy8+sxwG+ahHxV4CeZucqoHdeEfPgi4st9LH4ncH1WmBihXUQskX2UoIqITTPzVxXi2RI4mzIpQmtgS0K9ASR9iVKa6sEaffua499K6QN9Y9uyFYGf5bT1ULsZ12WUk5XLO9dll0sMNn2iX03pPvP9zPxte3LQzVjaYho0Ker2iWfbYLd+1UwIelkvDDJt14ut902XuuUpgxVvzMz5I2JuSqv9vF2MYznKLKafZEp3nqlUvjrVMxVyOkWZR2VnSvfbByjdNc+p9b6PiC9n5oEdy8YDO2XmVyvE8yCwXGY+3nYiPBfwv9G8MmVCPkIi4g2UmtFbVY7jVmCz9jPLKDWuv5aZC1aI5zrKB+ZFlH7bL0bEkcDDmXl4t+PpiG0hynTLnSWpuj6FfUQ8Qqm/+nTbsrmB+2oNVGxi6KkSg82J07spk2uMp3TveWtmTnPC0KV4+psht6Xrg18HSgRaaicEvSAi3pClJOSy/W2TFcrTtRug9f4z2VaRqcsxnUeZeXIJ4OnM3K75/vveaLYeDhDPTplZa+yPRkD0Xfd7HOX7b54K8fwLeFNm3tmWkK9BmWHcFvJe1yRP/62R9HbEsRvwBWCLzPx705q/O/COGt1WIuLxzBzXXHpdt+kLuSBwbWYu3+142uL6LOUy5yNMPVgxM7PfL+hRjOcyytTqJ7Yt253SQmBrZh+a1un3UWaZm5/SP/ojdaPSYJouK31+8XSzG0ZMW8av86Sq6ydTA+mV1vuIWAQ4nDKz6T6ZeVdEHEJpIe9aa+ZMckL1AaadfbnKyUNEnJiZu0eZM6FPmXlwl2PapPn1F5QxXK3/waAM8tyhm92g2uL6HKUP+76UmaE3o3RfOT8zjxq145qQD1/bm6hlbsrAqQ0zc53uRzS1iNgGOBa4hnK5c6uKfbHup1wWOw24ODNPalo5b83M+WrE1BbXtjUGjPQlItYEfkmZpfN2ymu2PLBlVpj5MSLen5mnRyl72KfsrRJ/rwLeU7MPZBNH9RlyI+KAzDykSQb6lJl9XuLvhojYtI/FnwBuycy9ux1Pr2sS4BWZ9kpez/z/1dDrJ1QRsS+lb/YxlM/1ZSklLE8ZzaRugHi+l5m7DTAAfUxmdrWqV9t4kuUo4wFaXqC8Zgdm5m+7GVMTVwCfohR7WA64CzgZ+Mpodms1IZ8OfQxKehb4J7B/ex/gmiJiI+DHlITuTxXjuIRSi3VZ4CzKmfBawOWZ+eGKcd0GrJeZ/6sVQ6fmEt3bKANg7wJ+Xiu+iLglM1fqtQF4vaq5nHkuPTBDbkRclpmbRUR/3XgyMzsbFaqKiJUog7jWr3Dsp4CXZQ9UEuoUEZ8CvkKPXMlrYuqZFtZe1nx2bto+hqQZF3RZjavDEfH1zPx0P+sWorT+TuhqUFOO/73M3K3GsfsSEXP0lXhHxJKjOV7JhHwWEVNmmGq3YPPzYYBaH+AtUWpHv4FSK/38mpdem0usT2fmIbVi6EsvtLBq+KLHZshtYporM5/rY/mcmfl8jZj6ExHzUUp91pi87GbK1c37u33swTSDlnfIzIm1Y2mJiL66XLwJ+Ed2cZbjpn/9Uq2rv1Gqz7S3kt+Vmc92K55OzVXYV2Tmo23LFqRcCRpfIZ6rKPNt7JJT1yBfkTKo85bMfFu342piWBZ4aWbeFGVCoJ0pRRbOrRTPxcA7298/EbEWpVvkqOVRJuTTISLu6PyjRCnZc1FmrlcppjcOtk12ceayKPW0N6G0ej3ftjwotT3/UPMLMCLeBlxIj8y22kstrE0878zM8wdYf0RWrtHcS6LHZshtYuproNQSwJ8zc8kaMTUxdLaizk2ZFe/eGglBROxJGSD8eTq6PWTl2UQjYhKwdlauHT+Y5vP0fZn5ni4e89OUgXfbNPefo5SqC8rn+qeybsnYkykDcfen9B9fhjJu6fGsUP0lyuzP51Fem+0y8+m2K+nnAP9X6/0eZdKyM7PMKnw85QTvKeDC7Ki+0qV4TqP8vbbKzCci4i2UanEHZ+bXRu24JuTDFxHPZeZcHcvGA3dk5ksrhdWnphvE091uEYuIr1Gmx969j3XfAF7MzD27GVNHDHdRWjN/xrTTGt9aIZ6eamGNMoPpAZn5vY7lcwOnA+tnZi/PWNtVEfFX4GOZeVVbQr4ZcHhmvrpSTH19Ti0P3JAVp4Tvow9rq8vfiZn5eIV4WklIT5yct4uIgyiDJb9ZM47BNJ8L/8kuTiwTpbznF7KpsBTNxEnN728B9qvVBaOJYT7KDKvvAeaivM/PBD6dmY9VimkO4HuU8pmnA1+lvIbTTNLV5bgeAlbOUvThPmAjypX9v1S8wng08EbK3+yLlMmULhzNY1aZHnRmFRE/mPJrtA+KCkp95Cql19pFxFGUUkFHR8T7KcX/n4yId2R3S8NtBWzbz7rvUGbkqpaQUwZIfSd7ZFpjysyFm2RmRkQrMfgvpXpIDW8EfhYRi2TmETD5pPMiypTQG1SKq1cdAPw4Io4D5oiIz9PMkNvtQGJKHfKXRET7wL8AVqOc+NV0WGbe0r6gSegWA7qekFMGUPeUti6IcwELRakKNZWKfcg7x47MDWxNKYXYTatRChf05XfN+pqezsxdImJXyhWY+5vP92p5V9NVZZeIOJxS+GGnzDyzVjxtngMyIlYGXpKZN0fEvJRa91Vk5mcjYi9K2dFNMvPK0T6mCfnwtFpOo+13KCOCL6Nc9qnt3ZTyQVBK9uwK3E8ZGNTNAVNLUVq9+nIL5XJQTT8CtqEMNO0FtwLrAe2lKTcGbqoRTNOXb0Pgp00i/n3KSdTfKNVMun4iEz084U1mXhJlEqzdKJ8Fy1Gq+NSYIfd7lM+o1wMntS1/Abizm13X+nEjHRVDKBOH/QVYpNvBZOYkgIh4CbAopUGjalcVyoyFvepfHfefo3zWd3uW6pdSWp1b2ruBJOU9VdMTlMolCdwHU7qMAV3vMtacGLTcAvwB+HDTZxuAzOx3FvJRdjGlvv6iwE+aZRtTZhLtmqarSud3zL3ANyLiBhjdCfHssjIdImLj7NGSUxHxOOVLbW7KG2k+yhvskW5epo6I/wCvyz7qwDaXzf+QmYt1K54+YuipaY0jYitK0nscsB9wME0La2Ze1O142uJagNLHcEPKlY09aw3GjSkT3nwC+DnlS6VlR+CezOx2UtCzImLZvv7/auunK82rgIlZYRKsplvftyg17eekJJinU/og12ixb49tJWB8tk1WFqVE6sOZeVe9yOqLiL9Q+j1PM5Fb013sa5m5VvcjmxxDT3UZi/6rLrVkVqq+1JwU7EWpbf+VzPxfc1Xonsw8o4tx9DsRXkuO4oR4JuTToWlJeT+wBbAQ5Szue1mhXnSniPgdpV7mcsAbM3PjiFidUkKva5c4I+JESoWQaSZqafqQzlljsGJbDD03rXFErEtpYV2OMgjo5EotrJ2XpcdSWl1/SzlhCOj+lPAtTf/2ZTtGwK8MnJ6Zr6kU04PAlcAVwG+Av9ZuZW0GSr23ffB000J3emb2VQt8tONpdcNoTZIyeRWlu8rRmbl/hbi+T0kE9mdKvejW4LuqJ3hRJgw7PTNPaVu2I/DBzNyyy7EMenLX5e+Y/6O0ym+emQ+0LV+CMqfDKZl5TLfiaTt+60rehpSuM5NXUbrRXJKZg86mq9mPCfl0iIhvU7qFnAI8QOmDuAtlOuOq/bEiYn1KN4x5gR0z84qI+A4wbzc/BCJiMcqH0Z1NPHdQ+tHtTnm9Xp+Zd3Yrnj7i2ywzL+tYNh+wZq0kuJfE1JNt9NSkGxHxX0oN+bvals1HKXNWpc9hc0Lw6rbbK4C/Ar9p9cGvENOXKeXDPpCZl0fE2ylXYX7c12DrLsTzRsr76DJKVZWWVleaSX3uOPpx3QesmD1Snq5dRPwPWK4jtrGUijQLdjmW/1AGwH+VPq4sQtcreQVwKvB2yuD8uyknU1s293escTWvaewJSiPGh9pW9UqXsZ4TEQsDXwJWp6MrdaUr1u+l9GU/PSLWo/S3fwj46Gh+TpmQT4emNeyVHQnBaylle7o+zetgImIuSmt1V1vsmi+1vShfvotQ3tCXUy4l3tfNWDpF3yXhFgAmVfiim4vSDWNrSh+6eyl93L+bozgr2MwqIo6glMX6ImVW0/HApynlIreuF1kRpd7+dpSTz39l5roVY3k95YrZ7ZQJuT5cswtUL4qI2ymDttoncFmJMoHLctUCK3HcSil9envbspdTTvS6Oqiz+Zx6H2UGw3soXQt6oZDBxpSr1YtQGsgu7ZG4erLLWC+KiAso33s7A62r6h8DrsvMPSrEcyOwR5b5QK4ArqMMWl4vM7cateOakA9fRPydUv/0v23L5qSUp6pVFWOyppW8rzPNWgM2ekbT3SgoLT1jmNLyG8BbKd1EujawLEpt2InAM5QrLvcAiwMfpPz9Nk0nBppKlNJdn6F8eL+c8iV8CWWm3Fozm25JqSr0Vsqgtx9TWqKrtPq2NN2gzqAMcLuNMiB31GaaGySWEzNz9+ixmR6jTHG+E/A1ygy5yzBlivMjux1PR2wHUAafH0iZWnx5SkvipZn5+YpxbUZ5jRYFPtlXP+7ZXZT69k9n5nFRyjCeSmmUek9mXlc3ut7SNHIuRXmPr5Cl9vfalEpoG1WI5wlgYcpVjUcpXeqepgz4XnC0jmuVlelzIbBfRLTXhl0D+Gu0zRZWo49tROxNaW1dktKnFUr1jlspl6tnd88zZRR1Z232Z4FpyouNsj0p5bCmmhAlIk6hvM8+RSm7VF1E3JyZK9eOo7lq8JXm1iu+T5kE5EuURO6hyvEQpfTi54CDKMnmp4A/R8RnMrNGdaHWyW9PlRnMzCMi4h7KuKBW//bDM/MHA+/ZFYdRTta/TjlRuJNyglWlGxRMPiFeAliaqaucaGofA7Zvfj+E8jd8iDKAuEo1qB42hjKY+t/AmpQKMH8HXlUpnjsp/f2XAf6dmY9GxNJNjKPGFvLpEFMmkhhIlT62zeXXN1DK043PzOejzPj4+hqXfnpNRCxH//1Y/5t9TDU+yvFcD3wkM3/Xx7rXA8fXrBTQrq+qAbU0A9veCiyamVtExFspA4VHdeKGQWJ6LfA2Sh/Wxyit5BdmM7V3hXj+QRnU+de2ZetSZs9dpUZMGp6IWCn7qdne7e4QETEPpRvWpynJ0jGZ+etuxjAzaVpZF6LMHvo/YEFKQve/XriS3ksi4ibKZ+d7KFeEDgImUApTdLNccyuenSgFDMZSJnw7oan6sllmbjFqxzUhn7XElFkCb6a8ee5o+v7d082uGDObiFgVeLTbl/OjlKlcLDOf6GPdPJTW83m7GVN/eiUhjzL1+naUvtEHZ5nV9DXAt2tVWWkXEWtR5gP4FDBPxcGv82Qf9eIjYt6+3m/dFBHrAKvSUY+8Rqt0R9eCzSn1kHuia0E/Y10WBm7q9ud5RDwAPEJp6b2xr21M0KeIMnvv54AVKOVr12+qV/0uM5eoG11vaT4PJgFPAd+gNCr+C9ir84S0izEtC4zNzJub+6+jNNqNWgOLCfksphkJvzalm8PDmfmZJlm5ODMXrRtd74iI04GbM/PgiPgMcCSlj9iumXluF+OY5gt3OOu7KSIuy8zNeiCOu4ANM3NSNNNlN33x/1ur5SkivkSZvfQ1lCmff9O6ZeatA+w62nH14pWEo4D/oyR1T7etykoVFW4Bts/MayPiT5QB1Q8B768RT0dsPVOzvbn6OlDCkJnZOYvnbCsitgDOpcy2+p7MvCAiDgVWyczt6kbXGyLib5m5dtv9v2bmq/pb3+XYgtJlpXMs3qh1RTYhH4bo4ZkCW5oBU2dTPgQmUrpnzAN8OjNPqBTTIsCKTNsaVm1ypebE5fWZeXtE/AvYA3iQUilnjS7G8QKlT2ifqykf5I71aBOlDvmKmfl42xWhxYE/ZWaVGWCbPv8TKQl4lS4qnXr1SkJEPEQ5ofpHrRja9WLXgujRmu29KCLGUAaYbgUskpmrRcT2wPyZedLAe496bHNTqj893txfnjJJX5XB572m84Sz1cDS3/ouxrUlJY8ax5SxLwkwmlc8TciHIQaYTKYlK00q05eI+CSlHNQZ2cXZrjpi+BRl8N0jTNsa1tWyXe0i4hFKNZNxlJJw4yhnwg93s4tIVJ4ZbCh6rWpPRJxESZg+RUmgxgGtiaiqjpNoqi0tlpl3D7rx6MfSc1cSmrhuppwMPzDoxl3Qi10LokdrtveiKPNsrAF8G/hB8z5/JXBardbVtthaJRlbEwiekbP5DKvtOq8AtxpY+lvfxbiuo8yUfRGwYGa+GBFHUvKDw0ftuCbks4aIWJEytfkyQCth2RW4FHgHcERmnlghrvuAHTJzYrePPZCI+AVwFaVSwFKZuWWUCQDO9bLrFANV7Wm/tNjlmOan9PPdgnLV5WlK95D31mp5ioilKJVWNqWcGMwdEXtQJpr6ZKWYeu5KQhPX3sB8lDryU004lRVmN7Vrwcyt+Y5ZPTMfaDvxHEMpQ9z1Kerb4voC5bPzAqZMIPgWyvfhZQPtO7vo4YT88cwcF2V22nWb99aCwLWZufyoHdeEfPgi4gP9rasxKAkmd6e5DvgppYb1VsA6mfmviHg1ZfrlrldWiIhJwNqZ+Ui3jz2QiHgF8F3KjKZ7ZOYNEfEN4JnM3KdudL0jerhqT5TZYJcF7s5KtbXbYvkZ8A9KObpJTVKwAvCrzKxS5q9XryTElCpV7V8+Qd3ZX3uqa0H0aM32XtQkTa/KzAfbTjxfTvnfq9a4EmVG4U0z84a2ZVtQuhutWSuuXhIRzwNvZsqJ+U8pVapa939RqcvK/ZQTqNMo4+9OiohFKQ1R843acU3Ih69JfjutBdyemet0ORygnFlSBm49HmXGyYdaX27N4ISnM3PuCnEdQimm/81BN1bPiR6q2hNlUqcB1WhhBYiIh4HFM/Ppttes1QWqq610EfH+LFM+99yVhCa+fme/rNEVI8okN2Mz8+LmJOowyqDO/TPz4W7H08T0vczcLSJO7meTMZn5vq4G1aMi4mhgZUoXg78DK1EaW27MzH0rxvUv4NXt/2u1PhN61RAGClOjQSMiLgH2pzT4nAX8gpLjXZ6ZHx6145qQj4yIeD+lv+ZHKx2/Vy/93Au8DPhv57oafcgj4oDMPKQXr3L0opi6as//MnOvqFS1p2lZ7e8Dq3YL69+B7TLz720J+WuAk7LLdeT7+CxYFFiOHriS0MTzC2CbzHx60I27ICL+DOyXmb+MiJ8CT1Jm55snM3esFNPXM/PT/axbCDg/Myd0Nage1XRPOQrYjVLA4CnKieieNd9jEXEQ8ARwTNvitSiTdG0KkycQrNKIoKGJiA0oV4lvpfzfjVrSbEI+QqLUjL4tMxevdPxevfTzxv7WZeZvuhkLMLl0X0Rc3s8mmZmbdDWoHhb9V+35VLfHJAzUstpSa7BbROwK7AccSmmd+xBlcovDs8uDX6NH6sX3J8qsmCtk5lO1Y4HSX5QyBfzTlER8eUoidWe3rwK1xXQVcAuwS5aZaVvLVwQuAW7Jjtl9BRExHnhgNJOmYcTSX9es1rKqjQgamihzlKwJ/CEz7xzVY/XA+3am08el87mBbYGvZObS3Y+ody/99Koos2D+Kbs8M+dAokxEsBml68NhEbE2pU/7TZVDAyAi5qVUM5iUmdNc8ehiHK+jdM+6sG3ZxpRLwX+rGNc2wIcprdF3ASdn5tkV4ug8OZ9GVpzAJSK+CVzTK1eiIuLflNdrCeDUzFyhSexuysyFKsX0UuA8ymf6dk1XqI0os7+eA/zf7N6y2nQvGlCOYs3owQylAQHqNSJoWhExFtiT0lXldGABSpeVWyhVmLbJzL66LI/M8U3Ih6+fS+cPU6ZA79qkMr2s1wclNX3ux/XKl1pEvItSpeO3lIFAY5sBQJ/OUZyqdzhafZN7II7fUQZGXdC2bAtKn9+uzgPQtIz35Tng+sy8tovhAJM/n26n/4Q8Kw92+yvly22aWTC7/fdr4tmL8iU8H3BUZh4aEbtTJgbq9wpfF+KaA/gepU/06cBXgS9k5tG1YuolfXwPt7/fR71mtGY9EXEGZTDnbykVceahlEL9TUTsQLkyvOGoHd+EfPj6OPN9Fri3Fy6T9YohDEoiM3fpZkztIuJq4APZTItbW0T8E9g9M6+MKaW7FqLMJlrlsnmnWuMQ+ojjUcpVhCfbls1JGcjc1fraTVLQV9eruSiXOb/Q7QHNvfJ36k8MMJ9DVprHISI2BObNzF8297em9Ln/c4142kXE4cA+wE6ZeWbteHpNREwEPp6ZN7Yt+xSwUGYOOs/DKMa1MPAl+p7DoeoEgupblPlJVs3Me6JUWrqVMoD6hWaswsPtY/NG/PjmkMMXEW+jzAh2StuybYBHM7O/vslqExHjsikxVun4R1AGK07T2lTjcn5TpWN8Zj7XNihwHKVyjwn51HH8kzLV+fVty9amDLhZscux9NtfOyLWAH6eXa753St/p5lJ0x3rtZQTvTOb7mNPZ+Z9leLpvPKyG+Wqy+QTlm6PTehVEfEYZfKW9r728wM31Cgc0BbDBcC9wM7AR5rFHwOuy8olY9W3PgbEd84cOqqfrU7JPX0OBj7bsex+4BvAq7sfTu+KiOOzo0xQRCxJGXS6TpWginc3PzunVk7K5fRu+yPwfso05y0fBP5UIZb+9Nsnucu+Bvy4KXd2O2UQ3mcpM/V127EDrLsJGN+tQNr0yt+pT71W4agZf3Ae5TN8ReBMyuf4+4B3djuexk4d95/pWJ6ULm4qM2C+hfKd0rI8pdRnTRsDS1HeQ+dl5hNNd63v1A1LA4mIoHyGBpAd90f32LaQD19zRr5IZj7TtmxOSlm4USsaPzOKiMuA+yiXW19oWjJ/CvwoMz9VN7re0Yzk/iVwG7ARcDnlUufm7ZdiuxjPhyitcdEa+BoRG2fmFd2OpS8RsT2lkskylAGUp2fmaXWjmlpELE3psmJrWJvosXkcmiTp0Mw8r6272GLA3zJzsW7Ho+GJiDdTBrr+kpKcjwe2AQ7LzK9WjOsxYEHgd5S+x39o8oRHMnPeWnGpf/2MS8j230dzXIIJ+XSIiGspo9x/27ZsI+D4zFyjWmA9KMokMmdQBkecRGnVOTAza7Rm9rSmdObbaGpGA5dkpRlO27rN9Fz3h4hYKDMfqh2HRk5UnMehGZOwSGY+2/a+H0uZ/Opl3Y5HwxcRywA7UgbkPUCZJ+GPlWO6ifJ5/h7KCcJBwATgjZm5fr3I1J+hVMYZzao4JuTTISK2pYx+P4kpl8w/RDkLPqNaYD2queTzDeDjwLaZeVHlkFqXqb8FrEIZgAfWhZ0synTUH6WUWVuZPi7X1Sop1lTIuZjy//dLB1PP/KLiPA5N1Z5DM/OnbQn59sAnHHyn6RUR6wCTKBMVfYMpk8vs1SvFBNRbTMinU5RZ+HZlyiXzM3rlcn4viIjOkoZB6RN9PfBngMzstyTiaIuIWyhdMi6gTAgyWWbeWiGeNSljE1amo+9jZq5cIZ6dKF8iC9B337lqJy4RsQTwAcr7aT7K3/HkGn83DV/02DwOUeraX9zc3gecQun3u3Vm/q7b8Wh4rGaiWYUJuUbFQOUOG5mZ/dVwHnUR8QCwdPbO9N3XA1dQ+td3niD8qkpQMHlm01rHH0xEvJZSxWBHSl3r7wPnZo/MAqlp9dFPE8o8Dh/OzPO6H9HkgebvZ0p3sbMy8981YtHw9HI1k2YA8wcpgzvvBk7ptbEu6h0m5MMQEZsB62bmUc39RYETKFU5zgO+7OXzmUNE/AA4JzMvrh0LQET8D1iiV04QOjV9NJcC7srMu2rHA9DUhd2W8kX8JuBSSov5q4Afdlb3UV0RcVZmvqetn+a8lCnqq87jED0686uGJiIepHw2TQJWaKqZrA18JzM3qhjXvpQreccAd1Jmf/wMJSk/qlZc6l2dlw41sL2Bx9ruf40yino/Sv+wPSvE1JMiYqGmDnP7sm0j4jMRsUrFuE5rkvHFgOMi4gedt0qhXUkpk9VTImKxiPg18C/gfODWiPhVU4WiVkwbRMTxwH+BzwO/ApbPzK0z802UetKPDfQYquJdUAZFNQOjrml+v6dyQ8YxQGf3q3moU0ZTwzeGUqP935TJuAD+Tjkxr+nDwNsy86TM/GVmfg/YmtJ6rx7WNL52LpsvIjYY1ePaoDt0EXEX8JrM/E8zUPExyj/cxIhYCfhZtycm6VURcRLwfKuVMiL2BL4AXAZsCGyXmb+vENcXKZfL+60pmplf6l5ERTMm4VzK6zNVbJW79pxPaXnaLzOfjoiXAocDy2XmOyrF9AClVvSp2QMzKWpoOidR6px0o5booZlfNXy9Ws0kIu4HXpGZj7YtWxC4JTNrzE+gIeqrulhELABMyswFR+u4Tgw0PC8D7ml+XwkYS5nQBUoLYtcHJPWwNzBl8h2ATwKfzsxTI2Ir4BBgkwpx3QTsQanv/XxrYXOCdRbwwwoxARxB6Qf5EB19yCubQFtf+8x8KiIOAO6oGNNqwPztgzib7mNPZsXZXzWoztafXmkN+g/wCsqA85bVKfMnqPe9m1Lq8ChK15UjKd/H760ZFGWQ8IkRsT+l//gywGHNcvWgZsB5lF8nTwhE83Nj4Pn+9h0JJuTDcxdlJrdbgA2Am9taVZYA/lcrsB60BPA3gIhYhNJ/7rJm3aXUS3x3A05sT8ahjDCNiHMppf4uqBDXayh9yHutq8UDlMov17YtW7lZXsv3gImULmMt76Kc4G1fIyANyUsi4k1M+ZLrvE9m/rpCXL0086uG70hgm6bRoJfGjXwS+CZwI6W07rOUK3ufrhiTBvY8U66gdybfzzLtDO0jyi4rwxARewE7UCa62RM4ITMPb1v31szctGKIPSMi7gVWzsxHI2JzSlnI8c26eSiTbixQIa5pLiO2rRsH3FljMpCI+A1lsqnrB924iyJiF0qrzkmUE9JlKOU+98vMUyrF9CDlvfVg27JxlJkeF6kRkwYXEbczcKt4ZuYKXQpnKjETzPyqvkXEPZTBnD1RWSkiFqI0rtzY3H8JsB2lgs9FmfnPmvGpfxGxFvA4pdGwPZd7AfhvNrNWjxZbyIchM49pSnZtRimv1qq2MhewZbNMxWXAZ5tWpw9TpjVueSOlX3IN81AGAPXlRUpN5Br+CXynr3KRmVntfZWZJ0fEbZSScOtSLr2+u3LN/SeYdkD6vPT/d1UPyMzla8fQl+YK3l8y89y2ZYtGxDi7QM0UzqVcGas1IL/TVyitq63W+k8CX6R8J+4ZEVXGT2lIrgDGA1eN5oyc/bGFXKMiIpYCLgHWpsxOtnmrrm9EXA1ckZn7VIjrD8CXMvOnfazbBjgoM7s+Oj8iLu9nVWZmjb72PSsivkbpNrMX5cRueeBo4I6sMPW6Zm4R8RNgYmZ+rW3ZR4FNMtMuUD0uIv5KKT18Xee6GhMDRcTNlEaLvzb3/035XmmNn9rLz/Te1AzwXgp4sHNQZ1eOb0Ku0RQRC2XmQ2335wTWoHQveKRCPO+mtGC8v72VNyI2AU4DDsjMwSY1mi1FxKWZ+eYeiGMspVTdLpSB1U8BZ1MGDfdaH3z1uKZqzyp2gZq5RMSJmbl7RHywv20y89RuxgQQEY8BC2bmC83Vl/8Cy2bm3c3cCQ9l5rhux6XBRcSZlPFcLwf6nKV3NE/yTMg124mIT1GqvDxGqRYyHlgcOCwzD60Y14LA25kyq9tFmflwrXg69VUKqqZmFPwiwANOyKXpFRF3AOtl5v1tyxYDrs3MJepFpoH02udRS6+On9Lgmu7HbwV+RBlTMo3RPMkzIddsKSLmB15HSegeAq6umfw2dch/CvyDMqvbMsCqlIHCf6oVV7te+gKMMrviWykzLH4kIjYCXrRvpoarny5Qx1C6QH1kgF1VUWdd+14REacDt1G60Z0MPJ2Z72vWbQkcmZlrVwxRg4iIZTOz66V9TchHUESsnpl/rx2HZj5Nv/qvZuY5bct2BPbMzNfWi2yKiLglM1fqgTg+DhxI04qRmWOjTHV+SI0+o5q59dMF6ixKFygHdfaoiHgBGPCKZmZ+oUvhTNar46c0uIg4IDMPiYgP9LdNZo7a4GET8hESEetQZur0EqeGrRlMMj4zn2lbNpZSasnLm22aqi/bZOb1rdkeI2I+SsnKBSuHp5lUWxeoRSiTyuzYCyeg6luTkA+UHGXWneW4p8ZPaXARcVlmblaryIJlD6dTU5HjDErR/4soE8p8vGpQmpn9nTLt8zlty95BKYdYVR/dQ94AvFCxe8gClMm5YEpd6znprRlONROJiCUpU6+/jzKG4+fA/lWD0mBeyMxdagfRn/ZkvLn/PH1UglHvyMzNmp9vqnF8W8iHKSJWBZ4E7geWpPRDPgn4K7Bp28yd0pBFxGsplzn/SZmYZFlgJSr3Ie/F7iERcR5wXWZ+OSKezMx5IuIQYKXMfHeNmDTzaQZRb09JwteivMd3BFbLzLsrhqYh6NU+5Jp5NSfmm2Tm6c39nZl6zoufZeY9o3Z8E/Khi4h9gYMpCfmXKa2ZVwL7AotSSmfZSq7p0iQIWzGlysoltaus9GL3kIhYgnJVamHKicttlH6/W2XmnTVi0swnIp4GfkMZePfjzHy6mcn3lZn5n7rRaTCt7gW149CsIyIOB+bOzM80959lSvnDJYHzMvPzo3Z8E/Khi4j/AptTuqmcRGkd/1ZmfjsiFgButW6tZiXNNPVLNclKqzX6ZcA/MnPxinEF8GrKdNR3A38ExniFSkMVETcBcwGnAKdk5h0RcR+wjgm5NPuJiOuAD2Tmdc39JzNznub39YATMnO90Tq+fciH7+7MfD4ingR+m5nfbpYvWDEmzaQi4kqm9IPuU+XKIZcDe1OuCLXsRWlZrKapO/7H5kZErAX8EFi9ZlyaeWTmKs2X7HuB3zUzLM4DzA+YkEuzn5cz9bitaPv9emDF0Ty4Cfnw/JDywf0fykj8/zRTLN9LSVourBmcZkrfa/s9gOOBPSrF0pdPABdFxK7A3BFxC033kG4H0nSV+SqlS8+PM/OEZvlHmuWndTsmzdwy88/AnyPis8AE4P3AlU3r+cWZeUTN+CR11QuU0qetamevaFs36tXO7LIyDBHxEspI/IWA0ymXO78KvBK4GtgrMx+tF6Fmdu2XyHpF0z3kNZT+2ncDf2wqBnQ7jh9QZlS9EPggpVb0BpREarfM/Em3Y9Ksp5nefCvgPZm5Q+14JHVHRFxG6ZZyTh/rdgF2zsw3jtrxTcil3tGLCXmviIiHgFUz876IWJlyafEXwC6ZeW/d6CTVEBFPAS/LTMueaoZExFuAUyn9yH/Ztnxr4PvArpk5aj0hTMilHtJrCXlT4vBbwCqUK0JQutZkZs7R5Viezcwxbfefycy5uxmDpN7S9P3fMDPvrx2LZn4R8SHKzL1PUq4ILwu8FNg3M78zqsc2IZfqiYjOWb9+CmxJ22CSzPx1V4Nq0/QZPxW4gI6JdzLz1i7H8jzwZqa8Nj31WknqvojYExgPfJ6pB+GRmS9WCUoztYiYF9iQMlbwAeCqzHxs1I9rQi7VExH/HmSTzMwVuhJMHyLiAWDpXrgcHBG3M3BFmqqvlaTui4hW0t3+2VDlKp40I6yyMh0iYq7MfK6P5XPWGOymmVdmvrx2DIP4ObAZcHHtQDJz+doxSOo5vf4ZKg2JLeTTobMva7NsCeDPmblkpbCkEdeMOl+FUo98Kpn5ge5HJEnSrMcW8ukTfSybmzKhhDQrubK5SVLPiIhLM/PNEXEy/XRly8xduxyWNN1MyIehbVbFl0TEFe2rgNWAH1UJTBoFETGWMunVBErt/QcoZQZPSy+tSaqr9R18e80gpJFil5VhiIgPUpLv7wEfalv1AnBnZladTlwaKRGxKDCxuXs+cA+wJPAOSjmot2Tmg3WikyRp1mJCPh0i4gvAkZn5zKAbSzOhiDgJGEeZrfDFtuVzAGcCj2bm7rXik6SWiNgOWJ2Oq/6Z+YU6EUnDZ0I+HSLiYWAha5xqVhUR91Am27itj3WvAH6XmYt3PzJJmiIijqZ0q1sbOKNZvAVwQ2a+uVZc0nC9pHYAM6nfABvVDkIaRS8D/tPPuruBBboYiyT1572UBPwxYI/M3AX4MPBQ1aikYXJQ5/R5AjgxIn7YucJLZJpF/At4PdDXzJdvAKZpOZekChbMzAci4l5geeAW4BLgtKpRScNkC/n0eQb4PbBMHzdpVnAccFJEbNC+sLl/PHBslagkaWoPNPOATAS+FBHjgG2AR6tGJQ2Tfcgl9SkiDgL2plz6vQdYApgPODQzv1IxNEkCICI+BPwKeB64lDKR2cPABzPzooqhScNiQj4CImJVSj+292TmSrXjkUZKRCwAbAAsDDwIXJWZj9SNStLsLiLOysz3tN1/aWY+1ZRsfTAzX6gYnjRsJuTTKSKWBN4DvA9YijJhykWZeW7VwCRJmsVFxLOZOabt/pOZOU/NmKQZ4aDOYYiIBYHtKUn4WpSZOVcEVsvMuyuGJknS7CQGuS/NVBzUOTz3AtsB3wWWysw9KAM8vcwgSVL3dH7v+j2smZot5MMzCVgJWBlYFLgDPwQkSeq2l0TEm5jSMt55n8zsq2yr1JPsQz5MEbEeZQDnDsDNwGuB9TPzn1UDkyRpNhERtzNwg1hm5gpdCkeaYSbk0ykigjJd7/uBrYGbgIsz84iacUmSJGnmYkI+AiJiDLAVpezhDrXjkSRJ0szDhFySJEmqyCorkiRJUkUm5JIkSVJFJuSSNBOKiIMiIpvbixHxQEScFRGrj+Ixz4uIiSP8mMs3z2XRkXxcSZqZmJBL0szrUeDNlEHlBwLrAb+PiGWqRjU8ywNfpMztIEmzJScGkqSZ13OZeVnrTkT8ArgV2AU4uFpUkqRhsYVckmYRmXkb8ACweNMN5IGI2DQifhsRz0TEdwEi4mURcVKz/smI+HVErNP+WBExZ0QcFhH3RsRjEXEFsHrHNqdExDUdy9ZsutFMaFs2T0QcHRF3Nce7PiIOiIjlgcubza5vdcFp9hkTEQdHxK3NPjdHxLcjYoERfdEkqQeYkEvSLCIilgAWoswiTPP7qcBZwDbAaRExB3AJ8Bbg85TW9AB+ExEvb3u4Y4E9gW9TZif+CTD/dMQUwI+BDwFfA94NXATsB9wLfLbZdHdK95s3N/cPBT4OHANsD3wPeBswM3XHkaQhscuKJM3EImIs5bN8DeDrwIPAacAngCeAV2Xm/W3bvx3YAHhNZv6pWXYB8G9gH+CjEbECJUHeIzO/17bvBsAiwwxxc5pEu617zUURcVxmPh0Rf26WXZ2ZN7TttwVwXmZ+p7l/SUR8HRuSJM2CTMglaea1MPBU2/3rgC0z88HSMM0z7cl44w3Ava1kHCAzn42InwEbN4s2pbSanz0CMW4CPNDe17055p2D7PdPYPuI+DtwGfCPzHx2BOKRpJ5jQi5JM69HKC3Jz1OS7LuGsM9CQGeSTrNsoeb38cBjmfn4CMS4MKVrynB9FPgmcCQwN/BwRBwLHJhOMS1pFmNCLkkzr+cz8+ph7vMQfZcYXLRZByU5nzci5szM5wd4rBcZ/HvkIWDxAdb3mVxn5gPAeyNibuCVwI6UPu9/Ac4f5JiSNFOxL54kzV6uBBaLiNe3FjRJ75bAFc2iv1G+H97Yse98HffvBZaKiPbvks5k/0pgkYh4c/vCiGi1xj/S/FykY/0qAJn5TGb+EdgLeBpYbsBnJ0kzIRNySZq9/BT4I/CjiPhIRLwb+CUwDvgKQGb+AfgDcHJE7BwR746IX1EGaLb7OSWR/lZEvDUiDgUu7tjmEuAq4JyI2Csi3h4RBwB/b9bfDDwMHBwR74qIPZvlv4+IHzTHfhtwfLP8FyPyKkhSDzEhl6TZSGa+QGkN/zlwGHAKpevJhKaOecu7gZsoifAxwERKct3+WFdQyhZuA5xDqVO+U8c2LzbH+yGwd7Pduyn9w8nMJ4EPAksAZ1JKHQIcALwCOA44HVgZ2CIz/44kzWLCsTGSJElSPbaQS5IkSRWZkEuSJEkVmZBLkiRJFZmQS5IkSRWZkEuSJEkVmZBLkiRJFZmQS5IkSRWZkEuSJEkVmZBLkiRJFf0/ntCt6aHIVRYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get only the mean and standard deviation columns for total net sales\n",
    "# collapse hierachical dataframe\n",
    "df2 = total_sales.copy()\n",
    "df2.columns = ['_'.join(col).strip() for col in df2.columns.values]\n",
    "\n",
    "# Remove everything but net sales mean and net sales standard deviation\n",
    "df2 = df2[['Total_Net_Sales_mean','Total_Net_Sales_std']]\n",
    "\n",
    "# make product type into a data column instead of an index\n",
    "df2.reset_index(inplace=True)\n",
    "\n",
    "# plot standard deviation and mean of total net sales for each product\n",
    "df2.plot.bar(x='Product_Type', y='Total_Net_Sales_mean', yerr='Total_Net_Sales_std')\n",
    "plt.grid(False)\n",
    "plt.ylim(0,1100)\n",
    "error_kw=dict(lw=5, capsize=5, capthick=3)\n",
    "\n",
    "# labels\n",
    "plt.title('Mean (\\u00B1SD) Product Net Sales')\n",
    "plt.xlabel('Products')\n",
    "plt.ylabel('US $')\n",
    "\n",
    "# legend\n",
    "plt.legend(['Mean Net Sales']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Total Orders</th>\n",
       "      <th>Gross Sales</th>\n",
       "      <th>Discounts</th>\n",
       "      <th>Returns</th>\n",
       "      <th>Net Sales</th>\n",
       "      <th>Shipping</th>\n",
       "      <th>Total Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>January</td>\n",
       "      <td>2017</td>\n",
       "      <td>73</td>\n",
       "      <td>8861.50</td>\n",
       "      <td>-129.40</td>\n",
       "      <td>-448.45</td>\n",
       "      <td>8283.65</td>\n",
       "      <td>1088.30</td>\n",
       "      <td>9371.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>February</td>\n",
       "      <td>2017</td>\n",
       "      <td>56</td>\n",
       "      <td>6908.50</td>\n",
       "      <td>-104.70</td>\n",
       "      <td>-416.20</td>\n",
       "      <td>6387.60</td>\n",
       "      <td>892.45</td>\n",
       "      <td>7280.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>March</td>\n",
       "      <td>2017</td>\n",
       "      <td>60</td>\n",
       "      <td>5778.50</td>\n",
       "      <td>-172.20</td>\n",
       "      <td>-1017.20</td>\n",
       "      <td>4589.10</td>\n",
       "      <td>707.43</td>\n",
       "      <td>5296.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>April</td>\n",
       "      <td>2017</td>\n",
       "      <td>70</td>\n",
       "      <td>8814.00</td>\n",
       "      <td>-281.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8532.60</td>\n",
       "      <td>1068.30</td>\n",
       "      <td>9600.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>May</td>\n",
       "      <td>2017</td>\n",
       "      <td>54</td>\n",
       "      <td>6677.00</td>\n",
       "      <td>-185.75</td>\n",
       "      <td>-253.80</td>\n",
       "      <td>6237.45</td>\n",
       "      <td>866.46</td>\n",
       "      <td>7103.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>June</td>\n",
       "      <td>2017</td>\n",
       "      <td>68</td>\n",
       "      <td>9621.50</td>\n",
       "      <td>-234.45</td>\n",
       "      <td>-17.50</td>\n",
       "      <td>9369.55</td>\n",
       "      <td>1204.32</td>\n",
       "      <td>10573.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>July</td>\n",
       "      <td>2017</td>\n",
       "      <td>66</td>\n",
       "      <td>6480.00</td>\n",
       "      <td>-51.50</td>\n",
       "      <td>-469.20</td>\n",
       "      <td>5959.30</td>\n",
       "      <td>807.36</td>\n",
       "      <td>6766.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>August</td>\n",
       "      <td>2017</td>\n",
       "      <td>55</td>\n",
       "      <td>8025.00</td>\n",
       "      <td>-258.90</td>\n",
       "      <td>-26.00</td>\n",
       "      <td>7740.10</td>\n",
       "      <td>843.46</td>\n",
       "      <td>8583.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>September</td>\n",
       "      <td>2017</td>\n",
       "      <td>68</td>\n",
       "      <td>7075.00</td>\n",
       "      <td>-61.70</td>\n",
       "      <td>-281.00</td>\n",
       "      <td>6732.30</td>\n",
       "      <td>907.32</td>\n",
       "      <td>7639.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>October</td>\n",
       "      <td>2017</td>\n",
       "      <td>59</td>\n",
       "      <td>5720.00</td>\n",
       "      <td>-88.00</td>\n",
       "      <td>-305.00</td>\n",
       "      <td>5327.00</td>\n",
       "      <td>695.42</td>\n",
       "      <td>6022.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>91</td>\n",
       "      <td>13025.00</td>\n",
       "      <td>-131.30</td>\n",
       "      <td>-323.85</td>\n",
       "      <td>12569.85</td>\n",
       "      <td>1555.10</td>\n",
       "      <td>14124.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>December</td>\n",
       "      <td>2017</td>\n",
       "      <td>116</td>\n",
       "      <td>10356.05</td>\n",
       "      <td>-149.85</td>\n",
       "      <td>-414.20</td>\n",
       "      <td>9792.00</td>\n",
       "      <td>1340.85</td>\n",
       "      <td>11132.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>January</td>\n",
       "      <td>2018</td>\n",
       "      <td>83</td>\n",
       "      <td>8923.00</td>\n",
       "      <td>-217.10</td>\n",
       "      <td>-26.25</td>\n",
       "      <td>8679.65</td>\n",
       "      <td>1180.18</td>\n",
       "      <td>9859.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>February</td>\n",
       "      <td>2018</td>\n",
       "      <td>69</td>\n",
       "      <td>6529.20</td>\n",
       "      <td>-161.35</td>\n",
       "      <td>-118.15</td>\n",
       "      <td>6249.70</td>\n",
       "      <td>908.91</td>\n",
       "      <td>7158.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>March</td>\n",
       "      <td>2018</td>\n",
       "      <td>64</td>\n",
       "      <td>7442.70</td>\n",
       "      <td>-226.82</td>\n",
       "      <td>-8.80</td>\n",
       "      <td>7207.08</td>\n",
       "      <td>1226.92</td>\n",
       "      <td>8434.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>April</td>\n",
       "      <td>2018</td>\n",
       "      <td>81</td>\n",
       "      <td>9406.35</td>\n",
       "      <td>-232.28</td>\n",
       "      <td>-40.00</td>\n",
       "      <td>9134.07</td>\n",
       "      <td>1387.56</td>\n",
       "      <td>10521.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>May</td>\n",
       "      <td>2018</td>\n",
       "      <td>82</td>\n",
       "      <td>7493.90</td>\n",
       "      <td>-221.25</td>\n",
       "      <td>-1448.02</td>\n",
       "      <td>5824.63</td>\n",
       "      <td>1234.95</td>\n",
       "      <td>7059.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>June</td>\n",
       "      <td>2018</td>\n",
       "      <td>124</td>\n",
       "      <td>13260.80</td>\n",
       "      <td>-335.40</td>\n",
       "      <td>-1506.53</td>\n",
       "      <td>11418.87</td>\n",
       "      <td>2124.49</td>\n",
       "      <td>13543.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>July</td>\n",
       "      <td>2018</td>\n",
       "      <td>102</td>\n",
       "      <td>9274.95</td>\n",
       "      <td>-237.87</td>\n",
       "      <td>-689.98</td>\n",
       "      <td>8347.10</td>\n",
       "      <td>1627.03</td>\n",
       "      <td>9974.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>August</td>\n",
       "      <td>2018</td>\n",
       "      <td>82</td>\n",
       "      <td>7698.70</td>\n",
       "      <td>-140.57</td>\n",
       "      <td>-197.35</td>\n",
       "      <td>7360.78</td>\n",
       "      <td>1404.03</td>\n",
       "      <td>8764.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>September</td>\n",
       "      <td>2018</td>\n",
       "      <td>79</td>\n",
       "      <td>10582.85</td>\n",
       "      <td>-276.15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10306.70</td>\n",
       "      <td>1634.33</td>\n",
       "      <td>11941.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>October</td>\n",
       "      <td>2018</td>\n",
       "      <td>71</td>\n",
       "      <td>7014.50</td>\n",
       "      <td>-277.95</td>\n",
       "      <td>-294.75</td>\n",
       "      <td>6441.80</td>\n",
       "      <td>1262.45</td>\n",
       "      <td>7704.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>November</td>\n",
       "      <td>2018</td>\n",
       "      <td>140</td>\n",
       "      <td>12002.70</td>\n",
       "      <td>-414.45</td>\n",
       "      <td>-154.40</td>\n",
       "      <td>11433.85</td>\n",
       "      <td>2237.05</td>\n",
       "      <td>13670.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>December</td>\n",
       "      <td>2018</td>\n",
       "      <td>164</td>\n",
       "      <td>13683.50</td>\n",
       "      <td>-371.20</td>\n",
       "      <td>-928.35</td>\n",
       "      <td>12383.95</td>\n",
       "      <td>2552.20</td>\n",
       "      <td>14936.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>January</td>\n",
       "      <td>2019</td>\n",
       "      <td>87</td>\n",
       "      <td>7811.75</td>\n",
       "      <td>-261.97</td>\n",
       "      <td>-1250.35</td>\n",
       "      <td>6299.43</td>\n",
       "      <td>1313.78</td>\n",
       "      <td>7615.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>February</td>\n",
       "      <td>2019</td>\n",
       "      <td>63</td>\n",
       "      <td>6523.70</td>\n",
       "      <td>-288.70</td>\n",
       "      <td>-38.70</td>\n",
       "      <td>6196.30</td>\n",
       "      <td>1121.85</td>\n",
       "      <td>7318.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>March</td>\n",
       "      <td>2019</td>\n",
       "      <td>99</td>\n",
       "      <td>13075.50</td>\n",
       "      <td>-439.85</td>\n",
       "      <td>-981.00</td>\n",
       "      <td>11654.65</td>\n",
       "      <td>2115.10</td>\n",
       "      <td>13769.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>April</td>\n",
       "      <td>2019</td>\n",
       "      <td>92</td>\n",
       "      <td>6977.00</td>\n",
       "      <td>-285.40</td>\n",
       "      <td>-10.00</td>\n",
       "      <td>6681.60</td>\n",
       "      <td>1342.45</td>\n",
       "      <td>8024.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>May</td>\n",
       "      <td>2019</td>\n",
       "      <td>96</td>\n",
       "      <td>10082.25</td>\n",
       "      <td>-460.90</td>\n",
       "      <td>-173.35</td>\n",
       "      <td>9448.00</td>\n",
       "      <td>1768.20</td>\n",
       "      <td>11216.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>June</td>\n",
       "      <td>2019</td>\n",
       "      <td>85</td>\n",
       "      <td>7321.75</td>\n",
       "      <td>-186.02</td>\n",
       "      <td>-165.40</td>\n",
       "      <td>6970.33</td>\n",
       "      <td>1356.80</td>\n",
       "      <td>8327.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>July</td>\n",
       "      <td>2019</td>\n",
       "      <td>94</td>\n",
       "      <td>9739.20</td>\n",
       "      <td>-447.07</td>\n",
       "      <td>-908.75</td>\n",
       "      <td>8383.38</td>\n",
       "      <td>1631.40</td>\n",
       "      <td>10014.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>August</td>\n",
       "      <td>2019</td>\n",
       "      <td>105</td>\n",
       "      <td>8839.50</td>\n",
       "      <td>-201.67</td>\n",
       "      <td>-84.37</td>\n",
       "      <td>8553.46</td>\n",
       "      <td>1724.75</td>\n",
       "      <td>10278.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>September</td>\n",
       "      <td>2019</td>\n",
       "      <td>88</td>\n",
       "      <td>9077.45</td>\n",
       "      <td>-354.89</td>\n",
       "      <td>-853.35</td>\n",
       "      <td>7869.21</td>\n",
       "      <td>1567.65</td>\n",
       "      <td>9436.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>October</td>\n",
       "      <td>2019</td>\n",
       "      <td>97</td>\n",
       "      <td>9132.25</td>\n",
       "      <td>-279.42</td>\n",
       "      <td>-1572.55</td>\n",
       "      <td>7280.28</td>\n",
       "      <td>1631.25</td>\n",
       "      <td>8911.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>November</td>\n",
       "      <td>2019</td>\n",
       "      <td>272</td>\n",
       "      <td>23997.90</td>\n",
       "      <td>-776.84</td>\n",
       "      <td>-364.51</td>\n",
       "      <td>22856.55</td>\n",
       "      <td>4824.75</td>\n",
       "      <td>27681.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>December</td>\n",
       "      <td>2019</td>\n",
       "      <td>342</td>\n",
       "      <td>31183.90</td>\n",
       "      <td>-2269.51</td>\n",
       "      <td>-1311.18</td>\n",
       "      <td>27603.21</td>\n",
       "      <td>5703.25</td>\n",
       "      <td>33306.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Month  Year  Total Orders  Gross Sales  Discounts  Returns  Net Sales  \\\n",
       "0     January  2017            73      8861.50    -129.40  -448.45    8283.65   \n",
       "1    February  2017            56      6908.50    -104.70  -416.20    6387.60   \n",
       "2       March  2017            60      5778.50    -172.20 -1017.20    4589.10   \n",
       "3       April  2017            70      8814.00    -281.40     0.00    8532.60   \n",
       "4         May  2017            54      6677.00    -185.75  -253.80    6237.45   \n",
       "5        June  2017            68      9621.50    -234.45   -17.50    9369.55   \n",
       "6        July  2017            66      6480.00     -51.50  -469.20    5959.30   \n",
       "7      August  2017            55      8025.00    -258.90   -26.00    7740.10   \n",
       "8   September  2017            68      7075.00     -61.70  -281.00    6732.30   \n",
       "9     October  2017            59      5720.00     -88.00  -305.00    5327.00   \n",
       "10   November  2017            91     13025.00    -131.30  -323.85   12569.85   \n",
       "11   December  2017           116     10356.05    -149.85  -414.20    9792.00   \n",
       "12    January  2018            83      8923.00    -217.10   -26.25    8679.65   \n",
       "13   February  2018            69      6529.20    -161.35  -118.15    6249.70   \n",
       "14      March  2018            64      7442.70    -226.82    -8.80    7207.08   \n",
       "15      April  2018            81      9406.35    -232.28   -40.00    9134.07   \n",
       "16        May  2018            82      7493.90    -221.25 -1448.02    5824.63   \n",
       "17       June  2018           124     13260.80    -335.40 -1506.53   11418.87   \n",
       "18       July  2018           102      9274.95    -237.87  -689.98    8347.10   \n",
       "19     August  2018            82      7698.70    -140.57  -197.35    7360.78   \n",
       "20  September  2018            79     10582.85    -276.15     0.00   10306.70   \n",
       "21    October  2018            71      7014.50    -277.95  -294.75    6441.80   \n",
       "22   November  2018           140     12002.70    -414.45  -154.40   11433.85   \n",
       "23   December  2018           164     13683.50    -371.20  -928.35   12383.95   \n",
       "24    January  2019            87      7811.75    -261.97 -1250.35    6299.43   \n",
       "25   February  2019            63      6523.70    -288.70   -38.70    6196.30   \n",
       "26      March  2019            99     13075.50    -439.85  -981.00   11654.65   \n",
       "27      April  2019            92      6977.00    -285.40   -10.00    6681.60   \n",
       "28        May  2019            96     10082.25    -460.90  -173.35    9448.00   \n",
       "29       June  2019            85      7321.75    -186.02  -165.40    6970.33   \n",
       "30       July  2019            94      9739.20    -447.07  -908.75    8383.38   \n",
       "31     August  2019           105      8839.50    -201.67   -84.37    8553.46   \n",
       "32  September  2019            88      9077.45    -354.89  -853.35    7869.21   \n",
       "33    October  2019            97      9132.25    -279.42 -1572.55    7280.28   \n",
       "34   November  2019           272     23997.90    -776.84  -364.51   22856.55   \n",
       "35   December  2019           342     31183.90   -2269.51 -1311.18   27603.21   \n",
       "\n",
       "    Shipping  Total Sales  \n",
       "0    1088.30      9371.95  \n",
       "1     892.45      7280.05  \n",
       "2     707.43      5296.53  \n",
       "3    1068.30      9600.90  \n",
       "4     866.46      7103.91  \n",
       "5    1204.32     10573.87  \n",
       "6     807.36      6766.66  \n",
       "7     843.46      8583.56  \n",
       "8     907.32      7639.62  \n",
       "9     695.42      6022.42  \n",
       "10   1555.10     14124.95  \n",
       "11   1340.85     11132.85  \n",
       "12   1180.18      9859.83  \n",
       "13    908.91      7158.61  \n",
       "14   1226.92      8434.00  \n",
       "15   1387.56     10521.63  \n",
       "16   1234.95      7059.58  \n",
       "17   2124.49     13543.36  \n",
       "18   1627.03      9974.13  \n",
       "19   1404.03      8764.81  \n",
       "20   1634.33     11941.03  \n",
       "21   1262.45      7704.25  \n",
       "22   2237.05     13670.90  \n",
       "23   2552.20     14936.15  \n",
       "24   1313.78      7615.91  \n",
       "25   1121.85      7318.15  \n",
       "26   2115.10     13769.75  \n",
       "27   1342.45      8024.05  \n",
       "28   1768.20     11216.20  \n",
       "29   1356.80      8327.13  \n",
       "30   1631.40     10014.78  \n",
       "31   1724.75     10278.21  \n",
       "32   1567.65      9436.86  \n",
       "33   1631.25      8911.53  \n",
       "34   4824.75     27681.30  \n",
       "35   5703.25     33306.46  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View data from business.retails2.csv\n",
    "sales2\n",
    "# There are 35 datapoints showing orders, gross sales, net sales, discounts and returns from Janury 2017 through to december 2019"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Graphs Time Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a column where month names are converted to integers\n",
    "Date = []\n",
    "for i in range(len(sales2['Month'])):\n",
    "    Date.append(datetime.datetime.strptime(sales2['Month'][i], '%B').month)\n",
    "sales2['month'] = Date\n",
    "\n",
    "\n",
    "# Convert month and year columns to datetime\n",
    "sales2['Date'] = pd.to_datetime(sales2[['Year','month']].assign(DAY=1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Net Sales Time Series Plot\n",
    "plt.plot(sales2['Date'], sales2['Net Sales'])\n",
    "plt.grid(False)\n",
    "plt.title('Time Series of Net Sales')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('US $');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Total Orders Time Series Plot\n",
    "plt.plot(sales2['Date'], sales2['Total Orders'])\n",
    "plt.title('Time Series of Total Order')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Number of Items');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time Series Stacked Bar Graph - Discounts, Returns, Net Sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Stacked bar chart\n",
    "# Subset dataset to have only net sales, date, discounts and returns\n",
    "df3 = sales2[['Date','Net Sales', 'Returns', 'Discounts']].copy()\n",
    "\n",
    "# Make discounts and returns positive numbers\n",
    "# df3[['Discounts', 'Returns']] = df3[['Discounts', 'Returns']].abs()\n",
    "df3.loc[:, ('Discounts', 'Returns')] = df3[['Discounts', 'Returns']].abs()\n",
    "\n",
    "# Set index as date\n",
    "df3 = df3.set_index('Date')\n",
    "\n",
    "# Fix X axis tick labels \n",
    "x_label = sales2['Month']\n",
    "x = np.arange(len(x_label))\n",
    "\n",
    "# Plot\n",
    "df3.plot(kind='bar', stacked=True, zorder=4)\n",
    "\n",
    "# Background\n",
    "plt.axvspan(-1, 11.5, facecolor=facecolor)\n",
    "plt.axvspan(23.5, 40, facecolor=facecolor)\n",
    "plt.grid(False)\n",
    "\n",
    "# labels\n",
    "plt.title('Time Series of Total Sales From 2017 to 2020')\n",
    "plt.xticks(ticks = x, labels = x_label)\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('US $');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Total Sales</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Total Orders</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Gross Sales</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Shipping</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Discounts</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>...</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</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",
       "      <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>2017</th>\n",
       "      <td>8625.0</td>\n",
       "      <td>2491.0</td>\n",
       "      <td>5297.0</td>\n",
       "      <td>14125.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>54</td>\n",
       "      <td>116</td>\n",
       "      <td>8112.0</td>\n",
       "      <td>2152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>695.0</td>\n",
       "      <td>1555.0</td>\n",
       "      <td>-154.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>-281.0</td>\n",
       "      <td>-52.0</td>\n",
       "      <td>-331.0</td>\n",
       "      <td>274.0</td>\n",
       "      <td>-1017.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>10297.0</td>\n",
       "      <td>2686.0</td>\n",
       "      <td>7060.0</td>\n",
       "      <td>14936.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>64</td>\n",
       "      <td>164</td>\n",
       "      <td>9443.0</td>\n",
       "      <td>2448.0</td>\n",
       "      <td>...</td>\n",
       "      <td>909.0</td>\n",
       "      <td>2552.0</td>\n",
       "      <td>-259.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>-414.0</td>\n",
       "      <td>-141.0</td>\n",
       "      <td>-451.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>-1507.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>12992.0</td>\n",
       "      <td>8449.0</td>\n",
       "      <td>7318.0</td>\n",
       "      <td>33306.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>63</td>\n",
       "      <td>342</td>\n",
       "      <td>11980.0</td>\n",
       "      <td>7647.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>5703.0</td>\n",
       "      <td>-521.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>-2270.0</td>\n",
       "      <td>-186.0</td>\n",
       "      <td>-643.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>-1573.0</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Total Sales                          Total Orders                  \\\n",
       "            mean     std    amin     amax         mean   std amin amax   \n",
       "Year                                                                     \n",
       "2017      8625.0  2491.0  5297.0  14125.0         70.0  18.0   54  116   \n",
       "2018     10297.0  2686.0  7060.0  14936.0         95.0  31.0   64  164   \n",
       "2019     12992.0  8449.0  7318.0  33306.0        127.0  86.0   63  342   \n",
       "\n",
       "     Gross Sales          ... Shipping         Discounts                 \\\n",
       "            mean     std  ...     amin    amax      mean    std    amin   \n",
       "Year                      ...                                             \n",
       "2017      8112.0  2152.0  ...    695.0  1555.0    -154.0   75.0  -281.0   \n",
       "2018      9443.0  2448.0  ...    909.0  2552.0    -259.0   81.0  -414.0   \n",
       "2019     11980.0  7647.0  ...   1122.0  5703.0    -521.0  573.0 -2270.0   \n",
       "\n",
       "            Returns                       \n",
       "       amax    mean    std    amin  amax  \n",
       "Year                                      \n",
       "2017  -52.0  -331.0  274.0 -1017.0   0.0  \n",
       "2018 -141.0  -451.0  558.0 -1507.0   0.0  \n",
       "2019 -186.0  -643.0  565.0 -1573.0 -10.0  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make stacked bar graph for net sales, returns and discounts per year\n",
    "\n",
    "# create a table \n",
    "variables = ['Total Orders', 'Gross Sales', 'Shipping', 'Year', 'Discounts', 'Returns', 'Total Sales']\n",
    "total_sales3 = sales2[variables].groupby('Year').agg([np.mean, np.std, np.min, np.max])\n",
    "\n",
    "total_sales3 = total_sales3.round()\n",
    "\n",
    "# rearange columns so that total net sales is first\n",
    "cols = total_sales3.columns.tolist()\n",
    "cols = cols[-4:] + cols[:-4]\n",
    "total_sales3 = total_sales3[cols]\n",
    "\n",
    "# rearange rows from highest to lowest for total net sales\n",
    "total_sales3 = total_sales3.sort_values([('Total Sales','mean')], ascending=True)\n",
    "total_sales3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get only the mean and standard deviation columns for total net sales\n",
    "# collapse hierachical dataframe\n",
    "df6 = total_sales3.copy()\n",
    "df6.columns = ['_'.join(col).strip() for col in df6.columns.values]\n",
    "\n",
    "# Remove everything but net sales mean and net sales standard deviation\n",
    "df6 = df6[['Total Sales_mean','Total Sales_std']]\n",
    "\n",
    "# make product type into a data column instead of an index\n",
    "df6.reset_index(inplace=True)\n",
    "\n",
    "# plot standard deviation and mean of total net sales for each product\n",
    "df6.plot.bar(x='Year', y='Total Sales_mean', yerr='Total Sales_std')\n",
    "plt.grid(False)\n",
    "# plt.ylim(0,1100)\n",
    "error_kw=dict(lw=5, capsize=5, capthick=3)\n",
    "\n",
    "# labels\n",
    "plt.title('Mean (\\u00B1SD) Product Net Sales')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('US $')\n",
    "\n",
    "# legend\n",
    "plt.legend(['Mean Net Sales'], loc = 'upper left');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get only the mean columns \n",
    "df5 = total_sales3.iloc[:, total_sales3.columns.get_level_values(1)=='mean'].copy(deep=True)\n",
    "\n",
    "# collapse hierachical dataframe\n",
    "df5.columns = ['_'.join(col).strip() for col in df5.columns.values]\n",
    "\n",
    "# make all values in table positive\n",
    "df5[['Discounts_mean', 'Returns_mean']] =  df5.loc[:, ('Discounts_mean', 'Returns_mean')].abs()\n",
    "\n",
    "# Remove Net quantity and gross sales\n",
    "df5.drop(df5.columns[[1,2,3]], axis = 1, inplace=True)\n",
    "\n",
    "# Stacked bar chart\n",
    "df5.plot(kind='bar', stacked=True)\n",
    "plt.grid(False)\n",
    "\n",
    "# labels\n",
    "plt.title('Mean Product Net Sales, Discounts and Returns \\n From 2017 to 2020')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('US $')\n",
    "\n",
    "# legend\n",
    "plt.legend(['Mean Net Sales','Mean Discounts','Mean Returns']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Total Sales</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Total Orders</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Gross Sales</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Shipping</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Discounts</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>...</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>amin</th>\n",
       "      <th>amax</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</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",
       "      <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>December</th>\n",
       "      <td>19792.0</td>\n",
       "      <td>11858.0</td>\n",
       "      <td>11133.0</td>\n",
       "      <td>33306.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>116</td>\n",
       "      <td>342</td>\n",
       "      <td>18408.0</td>\n",
       "      <td>11189.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1341.0</td>\n",
       "      <td>5703.0</td>\n",
       "      <td>-930.0</td>\n",
       "      <td>1165.0</td>\n",
       "      <td>-2270.0</td>\n",
       "      <td>-150.0</td>\n",
       "      <td>-885.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>-1311.0</td>\n",
       "      <td>-414.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>November</th>\n",
       "      <td>18492.0</td>\n",
       "      <td>7961.0</td>\n",
       "      <td>13671.0</td>\n",
       "      <td>27681.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>91</td>\n",
       "      <td>272</td>\n",
       "      <td>16342.0</td>\n",
       "      <td>6650.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1555.0</td>\n",
       "      <td>4825.0</td>\n",
       "      <td>-441.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>-777.0</td>\n",
       "      <td>-131.0</td>\n",
       "      <td>-281.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>-365.0</td>\n",
       "      <td>-154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>June</th>\n",
       "      <td>10815.0</td>\n",
       "      <td>2616.0</td>\n",
       "      <td>8327.0</td>\n",
       "      <td>13543.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>68</td>\n",
       "      <td>124</td>\n",
       "      <td>10068.0</td>\n",
       "      <td>2995.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1204.0</td>\n",
       "      <td>2124.0</td>\n",
       "      <td>-252.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>-335.0</td>\n",
       "      <td>-186.0</td>\n",
       "      <td>-563.0</td>\n",
       "      <td>820.0</td>\n",
       "      <td>-1507.0</td>\n",
       "      <td>-18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>September</th>\n",
       "      <td>9673.0</td>\n",
       "      <td>2160.0</td>\n",
       "      <td>7640.0</td>\n",
       "      <td>11941.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>68</td>\n",
       "      <td>88</td>\n",
       "      <td>8912.0</td>\n",
       "      <td>1760.0</td>\n",
       "      <td>...</td>\n",
       "      <td>907.0</td>\n",
       "      <td>1634.0</td>\n",
       "      <td>-231.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>-355.0</td>\n",
       "      <td>-62.0</td>\n",
       "      <td>-378.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>-853.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>April</th>\n",
       "      <td>9382.0</td>\n",
       "      <td>1263.0</td>\n",
       "      <td>8024.0</td>\n",
       "      <td>10522.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>92</td>\n",
       "      <td>8399.0</td>\n",
       "      <td>1267.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1388.0</td>\n",
       "      <td>-266.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>-285.0</td>\n",
       "      <td>-232.0</td>\n",
       "      <td>-17.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>-40.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>August</th>\n",
       "      <td>9209.0</td>\n",
       "      <td>931.0</td>\n",
       "      <td>8584.0</td>\n",
       "      <td>10278.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>55</td>\n",
       "      <td>105</td>\n",
       "      <td>8188.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>...</td>\n",
       "      <td>843.0</td>\n",
       "      <td>1725.0</td>\n",
       "      <td>-200.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>-259.0</td>\n",
       "      <td>-141.0</td>\n",
       "      <td>-103.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>-197.0</td>\n",
       "      <td>-26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>March</th>\n",
       "      <td>9167.0</td>\n",
       "      <td>4284.0</td>\n",
       "      <td>5297.0</td>\n",
       "      <td>13770.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>60</td>\n",
       "      <td>99</td>\n",
       "      <td>8766.0</td>\n",
       "      <td>3824.0</td>\n",
       "      <td>...</td>\n",
       "      <td>707.0</td>\n",
       "      <td>2115.0</td>\n",
       "      <td>-280.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>-440.0</td>\n",
       "      <td>-172.0</td>\n",
       "      <td>-669.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>-1017.0</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>January</th>\n",
       "      <td>8949.0</td>\n",
       "      <td>1180.0</td>\n",
       "      <td>7616.0</td>\n",
       "      <td>9860.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>73</td>\n",
       "      <td>87</td>\n",
       "      <td>8532.0</td>\n",
       "      <td>625.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1088.0</td>\n",
       "      <td>1314.0</td>\n",
       "      <td>-203.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>-262.0</td>\n",
       "      <td>-129.0</td>\n",
       "      <td>-575.0</td>\n",
       "      <td>622.0</td>\n",
       "      <td>-1250.0</td>\n",
       "      <td>-26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>July</th>\n",
       "      <td>8919.0</td>\n",
       "      <td>1864.0</td>\n",
       "      <td>6767.0</td>\n",
       "      <td>10015.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>66</td>\n",
       "      <td>102</td>\n",
       "      <td>8498.0</td>\n",
       "      <td>1763.0</td>\n",
       "      <td>...</td>\n",
       "      <td>807.0</td>\n",
       "      <td>1631.0</td>\n",
       "      <td>-245.0</td>\n",
       "      <td>198.0</td>\n",
       "      <td>-447.0</td>\n",
       "      <td>-52.0</td>\n",
       "      <td>-689.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>-909.0</td>\n",
       "      <td>-469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>May</th>\n",
       "      <td>8460.0</td>\n",
       "      <td>2387.0</td>\n",
       "      <td>7060.0</td>\n",
       "      <td>11216.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>54</td>\n",
       "      <td>96</td>\n",
       "      <td>8084.0</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>...</td>\n",
       "      <td>866.0</td>\n",
       "      <td>1768.0</td>\n",
       "      <td>-289.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>-461.0</td>\n",
       "      <td>-186.0</td>\n",
       "      <td>-625.0</td>\n",
       "      <td>714.0</td>\n",
       "      <td>-1448.0</td>\n",
       "      <td>-173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>October</th>\n",
       "      <td>7546.0</td>\n",
       "      <td>1451.0</td>\n",
       "      <td>6022.0</td>\n",
       "      <td>8912.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>59</td>\n",
       "      <td>97</td>\n",
       "      <td>7289.0</td>\n",
       "      <td>1723.0</td>\n",
       "      <td>...</td>\n",
       "      <td>695.0</td>\n",
       "      <td>1631.0</td>\n",
       "      <td>-215.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>-279.0</td>\n",
       "      <td>-88.0</td>\n",
       "      <td>-724.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>-1573.0</td>\n",
       "      <td>-295.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>February</th>\n",
       "      <td>7252.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>7159.0</td>\n",
       "      <td>7318.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>56</td>\n",
       "      <td>69</td>\n",
       "      <td>6654.0</td>\n",
       "      <td>221.0</td>\n",
       "      <td>...</td>\n",
       "      <td>892.0</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>-185.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>-289.0</td>\n",
       "      <td>-105.0</td>\n",
       "      <td>-191.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>-416.0</td>\n",
       "      <td>-39.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Total Sales                            Total Orders              \\\n",
       "                 mean      std     amin     amax         mean    std amin   \n",
       "Month                                                                       \n",
       "December      19792.0  11858.0  11133.0  33306.0        207.0  119.0  116   \n",
       "November      18492.0   7961.0  13671.0  27681.0        168.0   94.0   91   \n",
       "June          10815.0   2616.0   8327.0  13543.0         92.0   29.0   68   \n",
       "September      9673.0   2160.0   7640.0  11941.0         78.0   10.0   68   \n",
       "April          9382.0   1263.0   8024.0  10522.0         81.0   11.0   70   \n",
       "August         9209.0    931.0   8584.0  10278.0         81.0   25.0   55   \n",
       "March          9167.0   4284.0   5297.0  13770.0         74.0   21.0   60   \n",
       "January        8949.0   1180.0   7616.0   9860.0         81.0    7.0   73   \n",
       "July           8919.0   1864.0   6767.0  10015.0         87.0   19.0   66   \n",
       "May            8460.0   2387.0   7060.0  11216.0         77.0   21.0   54   \n",
       "October        7546.0   1451.0   6022.0   8912.0         76.0   19.0   59   \n",
       "February       7252.0     83.0   7159.0   7318.0         63.0    7.0   56   \n",
       "\n",
       "               Gross Sales           ... Shipping         Discounts          \\\n",
       "          amax        mean      std  ...     amin    amax      mean     std   \n",
       "Month                                ...                                      \n",
       "December   342     18408.0  11189.0  ...   1341.0  5703.0    -930.0  1165.0   \n",
       "November   272     16342.0   6650.0  ...   1555.0  4825.0    -441.0   324.0   \n",
       "June       124     10068.0   2995.0  ...   1204.0  2124.0    -252.0    76.0   \n",
       "September   88      8912.0   1760.0  ...    907.0  1634.0    -231.0   152.0   \n",
       "April       92      8399.0   1267.0  ...   1068.0  1388.0    -266.0    30.0   \n",
       "August     105      8188.0    588.0  ...    843.0  1725.0    -200.0    59.0   \n",
       "March       99      8766.0   3824.0  ...    707.0  2115.0    -280.0   141.0   \n",
       "January     87      8532.0    625.0  ...   1088.0  1314.0    -203.0    67.0   \n",
       "July       102      8498.0   1763.0  ...    807.0  1631.0    -245.0   198.0   \n",
       "May         96      8084.0   1778.0  ...    866.0  1768.0    -289.0   150.0   \n",
       "October     97      7289.0   1723.0  ...    695.0  1631.0    -215.0   110.0   \n",
       "February    69      6654.0    221.0  ...    892.0  1122.0    -185.0    94.0   \n",
       "\n",
       "                         Returns                        \n",
       "             amin   amax    mean    std    amin   amax  \n",
       "Month                                                   \n",
       "December  -2270.0 -150.0  -885.0  450.0 -1311.0 -414.0  \n",
       "November   -777.0 -131.0  -281.0  111.0  -365.0 -154.0  \n",
       "June       -335.0 -186.0  -563.0  820.0 -1507.0  -18.0  \n",
       "September  -355.0  -62.0  -378.0  435.0  -853.0    0.0  \n",
       "April      -285.0 -232.0   -17.0   21.0   -40.0    0.0  \n",
       "August     -259.0 -141.0  -103.0   87.0  -197.0  -26.0  \n",
       "March      -440.0 -172.0  -669.0  572.0 -1017.0   -9.0  \n",
       "January    -262.0 -129.0  -575.0  622.0 -1250.0  -26.0  \n",
       "July       -447.0  -52.0  -689.0  220.0  -909.0 -469.0  \n",
       "May        -461.0 -186.0  -625.0  714.0 -1448.0 -173.0  \n",
       "October    -279.0  -88.0  -724.0  735.0 -1573.0 -295.0  \n",
       "February   -289.0 -105.0  -191.0  199.0  -416.0  -39.0  \n",
       "\n",
       "[12 rows x 24 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create table \n",
    "variables = ['Total Orders', 'Gross Sales', 'Shipping', 'Month', 'Discounts', 'Returns', 'Total Sales']\n",
    "total_sales2 = sales2[variables].groupby('Month').agg([np.mean, np.std, np.min, np.max])\n",
    "\n",
    "# Round all values\n",
    "total_sales2 = total_sales2.round()\n",
    "\n",
    "# rearange columns so that total net sales is first\n",
    "cols = total_sales2.columns.tolist()\n",
    "cols = cols[-4:] + cols[:-4]\n",
    "total_sales2 = total_sales2[cols]\n",
    "\n",
    "# # rearange rows from highest to lowest for total net sales\n",
    "total_sales2 = total_sales2.sort_values([('Total Sales','mean')], ascending=False)\n",
    "total_sales2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get only the mean and standard deviation columns for total net sales\n",
    "# collapse hierachical dataframe\n",
    "df4 = total_sales2.copy()\n",
    "df4.columns = ['_'.join(col).strip() for col in df4.columns.values]\n",
    "\n",
    "# Remove everything but net sales mean and net sales standard deviation\n",
    "df4 = df4[['Total Sales_mean','Total Sales_std']]\n",
    "\n",
    "# make product type into a data column instead of an index\n",
    "df4.reset_index(inplace=True)\n",
    "\n",
    "# plot standard deviation and mean of total net sales for each product\n",
    "df4.plot.bar(x='Month', y='Total Sales_mean', yerr='Total Sales_std')\n",
    "plt.grid(False)\n",
    "# plt.ylim(0,1100)\n",
    "error_kw=dict(lw=5, capsize=5, capthick=3)\n",
    "\n",
    "# labels\n",
    "plt.title('Mean (\\u00B1SD) Monthly Net Sales')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('US $')\n",
    "\n",
    "# legend\n",
    "plt.legend(['Mean Net Sales']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get only the mean and standard deviation columns for total net sales over the three years\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Projections for Q4 of 2020 (oct-dec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List of sales per item for Q4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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