Real Estate Analysis - Zillow Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Real-Estate-Analysis\n",
    "\n",
    "Analysis of Real Estate Trend in USA in last 10 years from Zillow.com.  Among the factors investigated were the percentage median sale price increases and pattern in the seasonality of number of houses sold during the year.\n",
    "\n",
    "[Plot1 : Median Sale Price growth over years in U.S](#median)<br/>\n",
    "[Plot2 : Top 10 states by percentage increase in Median Sale Price from Sept 2011](#plot2)<br/>\n",
    "[Plot3 : Top 10 metros by size](#plot3)<br/>\n",
    "[Plot4 : Median Sale Price increase for Cities in Bay area ](#plot4)<br/>\n",
    "[Plot5 : Home Sale Counts by state - US Map](#plot5)<br/>\n",
    "[Plot6 : Days On Market  - Seasonality Trend over the years](#plot6)<br/>\n",
    "[Plot7 :Days On Market trend - Heat Map](#plot7)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 798,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub data rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_data_rate_limit`.\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.ticker as tick\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from plotly import __version__\n",
    "from plotly.offline import init_notebook_mode,iplot, plot\n",
    "import plotly\n",
    "import plotly.plotly as py\n",
    "plotly.tools.set_credentials_file(username = 'singuava', api_key = 'Hd6ccbecmOGgaZbsHva2')\n",
    "\n",
    "init_notebook_mode()\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 684,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Format function to show numbers morethan 1000 in the ticks in K\n",
    "def fmt_x(x,y):\n",
    "    if x >= 1000000:        \n",
    "        val = int(x) / 1000000\n",
    "        return '{:.1f}M'.format(val)\n",
    "    elif x >= 1000:        \n",
    "        val = int(x) / 1000\n",
    "        return '{val:d}K'.format(val=int(val))\n",
    "    else:\n",
    "        return int(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 804,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sns.set_context(\"poster\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 673,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>2008-09</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102001</td>\n",
       "      <td>United States</td>\n",
       "      <td>0</td>\n",
       "      <td>188300.0</td>\n",
       "      <td>184800.0</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>177700.0</td>\n",
       "      <td>175800.0</td>\n",
       "      <td>174700.0</td>\n",
       "      <td>173700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>221000.0</td>\n",
       "      <td>224700.0</td>\n",
       "      <td>226600.0</td>\n",
       "      <td>230600.0</td>\n",
       "      <td>233800.0</td>\n",
       "      <td>236400.0</td>\n",
       "      <td>234900.0</td>\n",
       "      <td>230800.0</td>\n",
       "      <td>227700.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>394913</td>\n",
       "      <td>New York, NY</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>373800.0</td>\n",
       "      <td>380000.0</td>\n",
       "      <td>384100.0</td>\n",
       "      <td>385900.0</td>\n",
       "      <td>387100.0</td>\n",
       "      <td>389400.0</td>\n",
       "      <td>396500.0</td>\n",
       "      <td>399100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>753899</td>\n",
       "      <td>Los Angeles-Long Beach-Anaheim, CA</td>\n",
       "      <td>2</td>\n",
       "      <td>472800.0</td>\n",
       "      <td>461900.0</td>\n",
       "      <td>445100.0</td>\n",
       "      <td>435000.0</td>\n",
       "      <td>421000.0</td>\n",
       "      <td>408500.0</td>\n",
       "      <td>392400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>602300.0</td>\n",
       "      <td>612300.0</td>\n",
       "      <td>614300.0</td>\n",
       "      <td>618400.0</td>\n",
       "      <td>623700.0</td>\n",
       "      <td>627400.0</td>\n",
       "      <td>626700.0</td>\n",
       "      <td>621900.0</td>\n",
       "      <td>623500.0</td>\n",
       "      <td>626800.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 128 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID                          RegionName  SizeRank   2008-03   2008-04  \\\n",
       "0    102001                       United States         0  188300.0  184800.0   \n",
       "1    394913                        New York, NY         1       NaN       NaN   \n",
       "2    753899  Los Angeles-Long Beach-Anaheim, CA         2  472800.0  461900.0   \n",
       "\n",
       "    2008-05   2008-06   2008-07   2008-08   2008-09    ...      2017-10  \\\n",
       "0  181000.0  177700.0  175800.0  174700.0  173700.0    ...     221000.0   \n",
       "1       NaN       NaN       NaN       NaN       NaN    ...     373800.0   \n",
       "2  445100.0  435000.0  421000.0  408500.0  392400.0    ...     602300.0   \n",
       "\n",
       "    2017-11   2017-12   2018-01   2018-02   2018-03   2018-04   2018-05  \\\n",
       "0  224700.0  226600.0  230600.0  233800.0  236400.0  234900.0  230800.0   \n",
       "1  380000.0  384100.0  385900.0  387100.0  389400.0  396500.0  399100.0   \n",
       "2  612300.0  614300.0  618400.0  623700.0  627400.0  626700.0  621900.0   \n",
       "\n",
       "    2018-06   2018-07  \n",
       "0  227700.0       NaN  \n",
       "1       NaN       NaN  \n",
       "2  623500.0  626800.0  \n",
       "\n",
       "[3 rows x 128 columns]"
      ]
     },
     "execution_count": 673,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SalePrice = pd.read_csv(\"Median Price\\Sale_Prices_msa.CSV\")\n",
    "df_SalePrice.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Median Sale Price growth over years in U.S <a class=\"anchor\" id=\"median\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 674,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>2008-09</th>\n",
       "      <th>2008-10</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>0</td>\n",
       "      <td>188300.0</td>\n",
       "      <td>184800.0</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>177700.0</td>\n",
       "      <td>175800.0</td>\n",
       "      <td>174700.0</td>\n",
       "      <td>173700.0</td>\n",
       "      <td>172700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>221000.0</td>\n",
       "      <td>224700.0</td>\n",
       "      <td>226600.0</td>\n",
       "      <td>230600.0</td>\n",
       "      <td>233800.0</td>\n",
       "      <td>236400.0</td>\n",
       "      <td>234900.0</td>\n",
       "      <td>230800.0</td>\n",
       "      <td>227700.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 127 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      RegionName  SizeRank   2008-03   2008-04   2008-05   2008-06   2008-07  \\\n",
       "0  United States         0  188300.0  184800.0  181000.0  177700.0  175800.0   \n",
       "\n",
       "    2008-08   2008-09   2008-10   ...      2017-10   2017-11   2017-12  \\\n",
       "0  174700.0  173700.0  172700.0   ...     221000.0  224700.0  226600.0   \n",
       "\n",
       "    2018-01   2018-02   2018-03   2018-04   2018-05   2018-06  2018-07  \n",
       "0  230600.0  233800.0  236400.0  234900.0  230800.0  227700.0      NaN  \n",
       "\n",
       "[1 rows x 127 columns]"
      ]
     },
     "execution_count": 674,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Select USA\n",
    "df_US = df_SalePrice.iloc[0:2:2,1::1]\n",
    "df_US"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 675,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>Median_Sales_Price</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-03</td>\n",
       "      <td>188300.0</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008-04</td>\n",
       "      <td>184800.0</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008-05</td>\n",
       "      <td>181000.0</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  Median_Sales_Price  Year\n",
       "0   2008-03            188300.0  2008\n",
       "1   2008-04            184800.0  2008\n",
       "2   2008-05            181000.0  2008"
      ]
     },
     "execution_count": 675,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_US.drop(['SizeRank','RegionName'], axis=1, inplace = True)\n",
    "\n",
    "#transposing into columns\n",
    "df_US = df_US.transpose()\n",
    "\n",
    "#Reset index\n",
    "df_US.reset_index(level=0,inplace=True)\n",
    "\n",
    "##Name columns\n",
    "df_US.columns = ['YearMonth','Median_Sales_Price']\n",
    "\n",
    "##Make a new column Year from YearMonth\n",
    "df_US['Year']= (df_US['YearMonth'].str.split('-').str[0])\n",
    "df_US.head()\n",
    "\n",
    "\n",
    "#Convert median sales price & year to numeric\n",
    "df_US['Median_Sales_Price'] = df_US['Median_Sales_Price'].apply(pd.to_numeric)\n",
    "df_US['Year'] = df_US['Year'].apply(pd.to_numeric)\n",
    "\n",
    "df_US.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 676,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Median_Sales_Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>176660.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>157666.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>160258.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>152166.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>157133.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Median_Sales_Price\n",
       "0  2008       176660.000000\n",
       "1  2009       157666.666667\n",
       "2  2010       160258.333333\n",
       "3  2011       152166.666667\n",
       "4  2012       157133.333333"
      ]
     },
     "execution_count": 676,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Make a new dataframe groupby year\n",
    "df_US = df_US.groupby('Year', as_index=False).mean()\n",
    "df_US.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 821,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+MAAAI5CAYAAADKVustAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZLUZP8Pq3no5Glk2bgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b94671748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=df_US.plot(kind='line', x=\"Year\", figsize=(15,8), color='blue')\n",
    "ax.yaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"Year\", labelpad=20, fontsize = 40)\n",
    "plt.ylabel(\"Median Sale Price (in $)\", labelpad=20)\n",
    "plt.title(\"Median Sale Price growth over years (2008 - 2018) in U.S\")\n",
    "ax.legend_.remove()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Insights : Median Sale price of houses in U.S increased by 55% from its rock bottom in 2011. The decrease from 2008 to 2011 can be explained by the depression in the ecomony and hence the housing market. "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "But the prices seen on the y-axis, 140k - 230k, is a scale for prices unheard of in California. we see this discrepancy, due the inclusion of all states (with Housing prices high and low ranges). It could also be due the types of houses (condos, townhomes, single-family homes) and in all zipcodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Hence we like to investigate further to see how the various states fared in terms of the median house price increase."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Median Sale Price Increase By State <a class=\"anchor\" id=\"plot2\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 690,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>2008-09</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9</td>\n",
       "      <td>California</td>\n",
       "      <td>1</td>\n",
       "      <td>387800.0</td>\n",
       "      <td>370900.0</td>\n",
       "      <td>348000.0</td>\n",
       "      <td>332700.0</td>\n",
       "      <td>317800.0</td>\n",
       "      <td>305500.0</td>\n",
       "      <td>291500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>466200.0</td>\n",
       "      <td>471600.0</td>\n",
       "      <td>472600.0</td>\n",
       "      <td>475000.0</td>\n",
       "      <td>479100.0</td>\n",
       "      <td>483100.0</td>\n",
       "      <td>487800.0</td>\n",
       "      <td>487100.0</td>\n",
       "      <td>487200.0</td>\n",
       "      <td>485800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>54</td>\n",
       "      <td>Texas</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>213000.0</td>\n",
       "      <td>212400.0</td>\n",
       "      <td>211600.0</td>\n",
       "      <td>211300.0</td>\n",
       "      <td>213400.0</td>\n",
       "      <td>215200.0</td>\n",
       "      <td>216300.0</td>\n",
       "      <td>216900.0</td>\n",
       "      <td>218100.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>New York</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>286700.0</td>\n",
       "      <td>295300.0</td>\n",
       "      <td>303000.0</td>\n",
       "      <td>308000.0</td>\n",
       "      <td>305100.0</td>\n",
       "      <td>298600.0</td>\n",
       "      <td>295600.0</td>\n",
       "      <td>288100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 128 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID  RegionName  SizeRank   2008-03   2008-04   2008-05   2008-06  \\\n",
       "0         9  California         1  387800.0  370900.0  348000.0  332700.0   \n",
       "1        54       Texas         2       NaN       NaN       NaN       NaN   \n",
       "2        43    New York         3       NaN       NaN       NaN       NaN   \n",
       "\n",
       "    2008-07   2008-08   2008-09    ...      2017-10   2017-11   2017-12  \\\n",
       "0  317800.0  305500.0  291500.0    ...     466200.0  471600.0  472600.0   \n",
       "1       NaN       NaN       NaN    ...     213000.0  212400.0  211600.0   \n",
       "2       NaN       NaN       NaN    ...     286700.0  295300.0  303000.0   \n",
       "\n",
       "    2018-01   2018-02   2018-03   2018-04   2018-05   2018-06   2018-07  \n",
       "0  475000.0  479100.0  483100.0  487800.0  487100.0  487200.0  485800.0  \n",
       "1  211300.0  213400.0  215200.0  216300.0  216900.0  218100.0       NaN  \n",
       "2  308000.0  305100.0  298600.0  295600.0  288100.0       NaN       NaN  \n",
       "\n",
       "[3 rows x 128 columns]"
      ]
     },
     "execution_count": 690,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SalePrice_State = pd.read_csv(\"Median Price\\Sale_Prices_State.CSV\")\n",
    "df_SalePrice_State.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 807,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2009-01</th>\n",
       "      <th>2009-07</th>\n",
       "      <th>2010-01</th>\n",
       "      <th>2010-07</th>\n",
       "      <th>2011-01</th>\n",
       "      <th>2011-07</th>\n",
       "      <th>2012-01</th>\n",
       "      <th>2012-07</th>\n",
       "      <th>2013-01</th>\n",
       "      <th>...</th>\n",
       "      <th>2014-01</th>\n",
       "      <th>2014-07</th>\n",
       "      <th>2015-01</th>\n",
       "      <th>2015-07</th>\n",
       "      <th>2016-01</th>\n",
       "      <th>2016-07</th>\n",
       "      <th>2017-01</th>\n",
       "      <th>2017-07</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RegionName</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>California</th>\n",
       "      <td>317800.0</td>\n",
       "      <td>243000.0</td>\n",
       "      <td>230600.0</td>\n",
       "      <td>263000.0</td>\n",
       "      <td>266800.0</td>\n",
       "      <td>255400.0</td>\n",
       "      <td>243900.0</td>\n",
       "      <td>246600.0</td>\n",
       "      <td>271600.0</td>\n",
       "      <td>309600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>369200.0</td>\n",
       "      <td>379700.0</td>\n",
       "      <td>387000.0</td>\n",
       "      <td>401900.0</td>\n",
       "      <td>418900.0</td>\n",
       "      <td>422600.0</td>\n",
       "      <td>439100.0</td>\n",
       "      <td>459700.0</td>\n",
       "      <td>475000.0</td>\n",
       "      <td>485800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>173700.0</td>\n",
       "      <td>179800.0</td>\n",
       "      <td>186000.0</td>\n",
       "      <td>187200.0</td>\n",
       "      <td>194200.0</td>\n",
       "      <td>200400.0</td>\n",
       "      <td>204600.0</td>\n",
       "      <td>211300.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>246800.0</td>\n",
       "      <td>258000.0</td>\n",
       "      <td>226000.0</td>\n",
       "      <td>247600.0</td>\n",
       "      <td>252300.0</td>\n",
       "      <td>...</td>\n",
       "      <td>263800.0</td>\n",
       "      <td>261500.0</td>\n",
       "      <td>260100.0</td>\n",
       "      <td>262700.0</td>\n",
       "      <td>267900.0</td>\n",
       "      <td>280400.0</td>\n",
       "      <td>279300.0</td>\n",
       "      <td>291600.0</td>\n",
       "      <td>308000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>184300.0</td>\n",
       "      <td>150900.0</td>\n",
       "      <td>126100.0</td>\n",
       "      <td>130300.0</td>\n",
       "      <td>120600.0</td>\n",
       "      <td>115100.0</td>\n",
       "      <td>116000.0</td>\n",
       "      <td>120400.0</td>\n",
       "      <td>125700.0</td>\n",
       "      <td>135900.0</td>\n",
       "      <td>...</td>\n",
       "      <td>151600.0</td>\n",
       "      <td>154100.0</td>\n",
       "      <td>161800.0</td>\n",
       "      <td>171700.0</td>\n",
       "      <td>180200.0</td>\n",
       "      <td>187000.0</td>\n",
       "      <td>195600.0</td>\n",
       "      <td>203000.0</td>\n",
       "      <td>220500.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>181100.0</td>\n",
       "      <td>174200.0</td>\n",
       "      <td>152100.0</td>\n",
       "      <td>171500.0</td>\n",
       "      <td>158800.0</td>\n",
       "      <td>156200.0</td>\n",
       "      <td>141000.0</td>\n",
       "      <td>138700.0</td>\n",
       "      <td>140100.0</td>\n",
       "      <td>143800.0</td>\n",
       "      <td>...</td>\n",
       "      <td>169600.0</td>\n",
       "      <td>168500.0</td>\n",
       "      <td>176000.0</td>\n",
       "      <td>181800.0</td>\n",
       "      <td>178500.0</td>\n",
       "      <td>185400.0</td>\n",
       "      <td>190500.0</td>\n",
       "      <td>192400.0</td>\n",
       "      <td>194600.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             2008-07   2009-01   2009-07   2010-01   2010-07   2011-01  \\\n",
       "RegionName                                                               \n",
       "California  317800.0  243000.0  230600.0  263000.0  266800.0  255400.0   \n",
       "Texas            NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "New York         NaN       NaN       NaN       NaN       NaN  246800.0   \n",
       "Florida     184300.0  150900.0  126100.0  130300.0  120600.0  115100.0   \n",
       "Illinois    181100.0  174200.0  152100.0  171500.0  158800.0  156200.0   \n",
       "\n",
       "             2011-07   2012-01   2012-07   2013-01    ...      2014-01  \\\n",
       "RegionName                                            ...                \n",
       "California  243900.0  246600.0  271600.0  309600.0    ...     369200.0   \n",
       "Texas            NaN       NaN       NaN       NaN    ...          NaN   \n",
       "New York    258000.0  226000.0  247600.0  252300.0    ...     263800.0   \n",
       "Florida     116000.0  120400.0  125700.0  135900.0    ...     151600.0   \n",
       "Illinois    141000.0  138700.0  140100.0  143800.0    ...     169600.0   \n",
       "\n",
       "             2014-07   2015-01   2015-07   2016-01   2016-07   2017-01  \\\n",
       "RegionName                                                               \n",
       "California  379700.0  387000.0  401900.0  418900.0  422600.0  439100.0   \n",
       "Texas       173700.0  179800.0  186000.0  187200.0  194200.0  200400.0   \n",
       "New York    261500.0  260100.0  262700.0  267900.0  280400.0  279300.0   \n",
       "Florida     154100.0  161800.0  171700.0  180200.0  187000.0  195600.0   \n",
       "Illinois    168500.0  176000.0  181800.0  178500.0  185400.0  190500.0   \n",
       "\n",
       "             2017-07   2018-01   2018-07  \n",
       "RegionName                                \n",
       "California  459700.0  475000.0  485800.0  \n",
       "Texas       204600.0  211300.0       NaN  \n",
       "New York    291600.0  308000.0       NaN  \n",
       "Florida     203000.0  220500.0       NaN  \n",
       "Illinois    192400.0  194600.0       NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 807,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_state = df_SalePrice_State.iloc[0:,1::6]\n",
    "\n",
    "df_state.set_index('RegionName').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 808,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2009-01</th>\n",
       "      <th>2009-07</th>\n",
       "      <th>2010-01</th>\n",
       "      <th>2010-07</th>\n",
       "      <th>2011-01</th>\n",
       "      <th>2011-07</th>\n",
       "      <th>2012-01</th>\n",
       "      <th>2012-07</th>\n",
       "      <th>...</th>\n",
       "      <th>2016-01</th>\n",
       "      <th>2016-07</th>\n",
       "      <th>2017-01</th>\n",
       "      <th>2017-07</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-07</th>\n",
       "      <th>Min</th>\n",
       "      <th>Max</th>\n",
       "      <th>Diff</th>\n",
       "      <th>PctChange</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>297600.0</td>\n",
       "      <td>287700.0</td>\n",
       "      <td>291400.0</td>\n",
       "      <td>284300.0</td>\n",
       "      <td>306900.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>284300.0</td>\n",
       "      <td>306900.0</td>\n",
       "      <td>22600.0</td>\n",
       "      <td>7.949349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Connecticut</td>\n",
       "      <td>236300.0</td>\n",
       "      <td>231700.0</td>\n",
       "      <td>215600.0</td>\n",
       "      <td>238000.0</td>\n",
       "      <td>223800.0</td>\n",
       "      <td>253900.0</td>\n",
       "      <td>229200.0</td>\n",
       "      <td>224400.0</td>\n",
       "      <td>226400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>220200.0</td>\n",
       "      <td>221600.0</td>\n",
       "      <td>229100.0</td>\n",
       "      <td>225700.0</td>\n",
       "      <td>241100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>215600.0</td>\n",
       "      <td>253900.0</td>\n",
       "      <td>38300.0</td>\n",
       "      <td>17.764378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>New Jersey</td>\n",
       "      <td>305100.0</td>\n",
       "      <td>292000.0</td>\n",
       "      <td>273900.0</td>\n",
       "      <td>272100.0</td>\n",
       "      <td>274900.0</td>\n",
       "      <td>274600.0</td>\n",
       "      <td>269100.0</td>\n",
       "      <td>257000.0</td>\n",
       "      <td>266500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>276100.0</td>\n",
       "      <td>276000.0</td>\n",
       "      <td>280100.0</td>\n",
       "      <td>271600.0</td>\n",
       "      <td>276800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>257000.0</td>\n",
       "      <td>305100.0</td>\n",
       "      <td>48100.0</td>\n",
       "      <td>18.715953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>187200.0</td>\n",
       "      <td>194200.0</td>\n",
       "      <td>200400.0</td>\n",
       "      <td>204600.0</td>\n",
       "      <td>211300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>173700.0</td>\n",
       "      <td>211300.0</td>\n",
       "      <td>37600.0</td>\n",
       "      <td>21.646517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>232900.0</td>\n",
       "      <td>218200.0</td>\n",
       "      <td>215200.0</td>\n",
       "      <td>227600.0</td>\n",
       "      <td>220900.0</td>\n",
       "      <td>225600.0</td>\n",
       "      <td>213900.0</td>\n",
       "      <td>213200.0</td>\n",
       "      <td>230800.0</td>\n",
       "      <td>...</td>\n",
       "      <td>244200.0</td>\n",
       "      <td>248300.0</td>\n",
       "      <td>252700.0</td>\n",
       "      <td>257200.0</td>\n",
       "      <td>259700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213200.0</td>\n",
       "      <td>259700.0</td>\n",
       "      <td>46500.0</td>\n",
       "      <td>21.810507</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     RegionName   2008-07   2009-01   2009-07   2010-01   2010-07   2011-01  \\\n",
       "38       Alaska       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "28  Connecticut  236300.0  231700.0  215600.0  238000.0  223800.0  253900.0   \n",
       "10   New Jersey  305100.0  292000.0  273900.0  272100.0  274900.0  274600.0   \n",
       "1         Texas       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "11     Virginia  232900.0  218200.0  215200.0  227600.0  220900.0  225600.0   \n",
       "\n",
       "     2011-07   2012-01   2012-07    ...       2016-01   2016-07   2017-01  \\\n",
       "38       NaN       NaN       NaN    ...      297600.0  287700.0  291400.0   \n",
       "28  229200.0  224400.0  226400.0    ...      220200.0  221600.0  229100.0   \n",
       "10  269100.0  257000.0  266500.0    ...      276100.0  276000.0  280100.0   \n",
       "1        NaN       NaN       NaN    ...      187200.0  194200.0  200400.0   \n",
       "11  213900.0  213200.0  230800.0    ...      244200.0  248300.0  252700.0   \n",
       "\n",
       "     2017-07   2018-01  2018-07       Min       Max     Diff  PctChange  \n",
       "38  284300.0  306900.0      NaN  284300.0  306900.0  22600.0   7.949349  \n",
       "28  225700.0  241100.0      NaN  215600.0  253900.0  38300.0  17.764378  \n",
       "10  271600.0  276800.0      NaN  257000.0  305100.0  48100.0  18.715953  \n",
       "1   204600.0  211300.0      NaN  173700.0  211300.0  37600.0  21.646517  \n",
       "11  257200.0  259700.0      NaN  213200.0  259700.0  46500.0  21.810507  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 808,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Calculate Min and Max of the series\n",
    "df_state['Min'] = df_state.min(axis=1)\n",
    "df_state['Max'] = df_state.max(axis=1)\n",
    "\n",
    "##Calculate Diff of Min and Max\n",
    "df_state['Diff'] = df_state['Max'] - df_state['Min']\n",
    "\n",
    "##Calculate Percentage increase from the rock bottom in 2011\n",
    "df_state['PctChange'] = (df_state['Diff']/df_state['Min'])*100\n",
    "\n",
    "## Sort Values by percentage increase\n",
    "df_state.sort_values(by='PctChange').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 693,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:2: DeprecationWarning:\n",
      "\n",
      "\n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_top10 = df_state.sort_values(by='PctChange').tail(10)\n",
    "df_top10 = df_top10.ix[:, ['RegionName','PctChange']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 694,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PctChange</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RegionName</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>63.805970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>66.920566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>75.013492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>87.837838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>91.572546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>91.716621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>110.667823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>110.880829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>128.381963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>178.842975</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                PctChange\n",
       "RegionName               \n",
       "Tennessee       63.805970\n",
       "West Virginia   66.920566\n",
       "Oregon          75.013492\n",
       "Georgia         87.837838\n",
       "Florida         91.572546\n",
       "Colorado        91.716621\n",
       "California     110.667823\n",
       "Arizona        110.880829\n",
       "Nevada         128.381963\n",
       "Michigan       178.842975"
      ]
     },
     "execution_count": 694,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_top10.set_index('RegionName')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 696,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABEEAAAKWCAYAAACmiod5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b94677358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "ax = df_top10.plot(kind='barh',x='RegionName', figsize=(15, 10), rot=0, color='Teal')\n",
    "ax.xaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"Percentage increase\", labelpad=20)\n",
    "plt.ylabel(\"State\", labelpad=20)\n",
    "plt.title(\"Top 10 states by percentage increase in Median Sale Price from Sept 2011\")\n",
    "ax.legend_.remove()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "### Analysis2:  Michigan and Nevada had about 175% to 150% increase in Median Sale price in the last few years from Sept 2011. California came in 4th with 115% increase in meadian Sale price."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "I tried to delve in further more to see which metros have the high increase in median sale price, in the top 10 metros by size."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top 10 metros by size <a class=\"anchor\" id=\"plot3\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 697,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>StateName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6181.0</td>\n",
       "      <td>New York</td>\n",
       "      <td>New York</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>546500.0</td>\n",
       "      <td>546000.0</td>\n",
       "      <td>552100.0</td>\n",
       "      <td>565700.0</td>\n",
       "      <td>572600.0</td>\n",
       "      <td>574800.0</td>\n",
       "      <td>569500.0</td>\n",
       "      <td>567100.0</td>\n",
       "      <td>556200.0</td>\n",
       "      <td>552900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12447.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>2</td>\n",
       "      <td>508700.0</td>\n",
       "      <td>480000.0</td>\n",
       "      <td>459500.0</td>\n",
       "      <td>449200.0</td>\n",
       "      <td>432600.0</td>\n",
       "      <td>419400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>663500.0</td>\n",
       "      <td>672200.0</td>\n",
       "      <td>687000.0</td>\n",
       "      <td>696900.0</td>\n",
       "      <td>704600.0</td>\n",
       "      <td>695900.0</td>\n",
       "      <td>685900.0</td>\n",
       "      <td>688000.0</td>\n",
       "      <td>684800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17426.0</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>3</td>\n",
       "      <td>324300.0</td>\n",
       "      <td>313100.0</td>\n",
       "      <td>291700.0</td>\n",
       "      <td>282100.0</td>\n",
       "      <td>277400.0</td>\n",
       "      <td>273700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>267900.0</td>\n",
       "      <td>271400.0</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>280700.0</td>\n",
       "      <td>286400.0</td>\n",
       "      <td>299400.0</td>\n",
       "      <td>298500.0</td>\n",
       "      <td>293100.0</td>\n",
       "      <td>277800.0</td>\n",
       "      <td>272500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13271.0</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>4</td>\n",
       "      <td>113100.0</td>\n",
       "      <td>113200.0</td>\n",
       "      <td>113500.0</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>108600.0</td>\n",
       "      <td>112100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>143700.0</td>\n",
       "      <td>146500.0</td>\n",
       "      <td>149800.0</td>\n",
       "      <td>156700.0</td>\n",
       "      <td>154700.0</td>\n",
       "      <td>154900.0</td>\n",
       "      <td>152400.0</td>\n",
       "      <td>154600.0</td>\n",
       "      <td>153000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40326.0</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>5</td>\n",
       "      <td>220900.0</td>\n",
       "      <td>213000.0</td>\n",
       "      <td>206600.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>187700.0</td>\n",
       "      <td>177100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>223100.0</td>\n",
       "      <td>226000.0</td>\n",
       "      <td>230100.0</td>\n",
       "      <td>236800.0</td>\n",
       "      <td>239400.0</td>\n",
       "      <td>238200.0</td>\n",
       "      <td>235800.0</td>\n",
       "      <td>233700.0</td>\n",
       "      <td>237000.0</td>\n",
       "      <td>237900.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 129 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID    RegionName     StateName  SizeRank   2008-03   2008-04  \\\n",
       "0    6181.0      New York      New York         1       NaN       NaN   \n",
       "1   12447.0   Los Angeles    California         2  508700.0  480000.0   \n",
       "2   17426.0       Chicago      Illinois         3  324300.0  313100.0   \n",
       "3   13271.0  Philadelphia  Pennsylvania         4  113100.0  113200.0   \n",
       "4   40326.0       Phoenix       Arizona         5  220900.0  213000.0   \n",
       "\n",
       "    2008-05   2008-06   2008-07   2008-08    ...      2017-10   2017-11  \\\n",
       "0       NaN       NaN       NaN       NaN    ...     546500.0  546000.0   \n",
       "1  459500.0  449200.0  432600.0  419400.0    ...     647500.0  663500.0   \n",
       "2  291700.0  282100.0  277400.0  273700.0    ...     267900.0  271400.0   \n",
       "3  113500.0  110300.0  108600.0  112100.0    ...     143700.0  146500.0   \n",
       "4  206600.0  198300.0  187700.0  177100.0    ...     223100.0  226000.0   \n",
       "\n",
       "    2017-12   2018-01   2018-02   2018-03   2018-04   2018-05   2018-06  \\\n",
       "0  552100.0  565700.0  572600.0  574800.0  569500.0  567100.0  556200.0   \n",
       "1  672200.0  687000.0  696900.0  704600.0  695900.0  685900.0  688000.0   \n",
       "2  275000.0  280700.0  286400.0  299400.0  298500.0  293100.0  277800.0   \n",
       "3  149800.0  156700.0  154700.0  154900.0  152400.0  154600.0  153000.0   \n",
       "4  230100.0  236800.0  239400.0  238200.0  235800.0  233700.0  237000.0   \n",
       "\n",
       "    2018-07  \n",
       "0  552900.0  \n",
       "1  684800.0  \n",
       "2  272500.0  \n",
       "3       NaN  \n",
       "4  237900.0  \n",
       "\n",
       "[5 rows x 129 columns]"
      ]
     },
     "execution_count": 697,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SalePrice_City = pd.read_csv(\"Median Price\\Sale_Prices_City.CSV\")\n",
    "df_SalePrice_City.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 698,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>StateName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12447.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>2</td>\n",
       "      <td>508700.0</td>\n",
       "      <td>480000.0</td>\n",
       "      <td>459500.0</td>\n",
       "      <td>449200.0</td>\n",
       "      <td>432600.0</td>\n",
       "      <td>419400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>663500.0</td>\n",
       "      <td>672200.0</td>\n",
       "      <td>687000.0</td>\n",
       "      <td>696900.0</td>\n",
       "      <td>704600.0</td>\n",
       "      <td>695900.0</td>\n",
       "      <td>685900.0</td>\n",
       "      <td>688000.0</td>\n",
       "      <td>684800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17426.0</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>3</td>\n",
       "      <td>324300.0</td>\n",
       "      <td>313100.0</td>\n",
       "      <td>291700.0</td>\n",
       "      <td>282100.0</td>\n",
       "      <td>277400.0</td>\n",
       "      <td>273700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>267900.0</td>\n",
       "      <td>271400.0</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>280700.0</td>\n",
       "      <td>286400.0</td>\n",
       "      <td>299400.0</td>\n",
       "      <td>298500.0</td>\n",
       "      <td>293100.0</td>\n",
       "      <td>277800.0</td>\n",
       "      <td>272500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40326.0</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>5</td>\n",
       "      <td>220900.0</td>\n",
       "      <td>213000.0</td>\n",
       "      <td>206600.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>187700.0</td>\n",
       "      <td>177100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>223100.0</td>\n",
       "      <td>226000.0</td>\n",
       "      <td>230100.0</td>\n",
       "      <td>236800.0</td>\n",
       "      <td>239400.0</td>\n",
       "      <td>238200.0</td>\n",
       "      <td>235800.0</td>\n",
       "      <td>233700.0</td>\n",
       "      <td>237000.0</td>\n",
       "      <td>237900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>54296.0</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>8</td>\n",
       "      <td>419800.0</td>\n",
       "      <td>408200.0</td>\n",
       "      <td>398800.0</td>\n",
       "      <td>380600.0</td>\n",
       "      <td>371300.0</td>\n",
       "      <td>356600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>553600.0</td>\n",
       "      <td>566300.0</td>\n",
       "      <td>574300.0</td>\n",
       "      <td>577800.0</td>\n",
       "      <td>572000.0</td>\n",
       "      <td>573200.0</td>\n",
       "      <td>577600.0</td>\n",
       "      <td>583200.0</td>\n",
       "      <td>584200.0</td>\n",
       "      <td>585000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>33839.0</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>California</td>\n",
       "      <td>10</td>\n",
       "      <td>615200.0</td>\n",
       "      <td>578200.0</td>\n",
       "      <td>560700.0</td>\n",
       "      <td>543300.0</td>\n",
       "      <td>529300.0</td>\n",
       "      <td>517700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>885300.0</td>\n",
       "      <td>922800.0</td>\n",
       "      <td>970900.0</td>\n",
       "      <td>1002300.0</td>\n",
       "      <td>1044300.0</td>\n",
       "      <td>1060800.0</td>\n",
       "      <td>1071700.0</td>\n",
       "      <td>1065200.0</td>\n",
       "      <td>1054600.0</td>\n",
       "      <td>1030600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 129 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID   RegionName   StateName  SizeRank   2008-03   2008-04   2008-05  \\\n",
       "1   12447.0  Los Angeles  California         2  508700.0  480000.0  459500.0   \n",
       "2   17426.0      Chicago    Illinois         3  324300.0  313100.0  291700.0   \n",
       "4   40326.0      Phoenix     Arizona         5  220900.0  213000.0  206600.0   \n",
       "7   54296.0    San Diego  California         8  419800.0  408200.0  398800.0   \n",
       "9   33839.0     San Jose  California        10  615200.0  578200.0  560700.0   \n",
       "\n",
       "    2008-06   2008-07   2008-08    ...       2017-10   2017-11   2017-12  \\\n",
       "1  449200.0  432600.0  419400.0    ...      647500.0  663500.0  672200.0   \n",
       "2  282100.0  277400.0  273700.0    ...      267900.0  271400.0  275000.0   \n",
       "4  198300.0  187700.0  177100.0    ...      223100.0  226000.0  230100.0   \n",
       "7  380600.0  371300.0  356600.0    ...      553600.0  566300.0  574300.0   \n",
       "9  543300.0  529300.0  517700.0    ...      885300.0  922800.0  970900.0   \n",
       "\n",
       "     2018-01    2018-02    2018-03    2018-04    2018-05    2018-06    2018-07  \n",
       "1   687000.0   696900.0   704600.0   695900.0   685900.0   688000.0   684800.0  \n",
       "2   280700.0   286400.0   299400.0   298500.0   293100.0   277800.0   272500.0  \n",
       "4   236800.0   239400.0   238200.0   235800.0   233700.0   237000.0   237900.0  \n",
       "7   577800.0   572000.0   573200.0   577600.0   583200.0   584200.0   585000.0  \n",
       "9  1002300.0  1044300.0  1060800.0  1071700.0  1065200.0  1054600.0  1030600.0  \n",
       "\n",
       "[5 rows x 129 columns]"
      ]
     },
     "execution_count": 698,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SalePrice_Cities = df_SalePrice_City.sort_values(by=\"SizeRank\").head(10)\n",
    "df_SalePrice_City.dropna(axis=0, inplace=True)\n",
    "df_SalePrice_City.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 700,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-12</th>\n",
       "      <th>2009-06</th>\n",
       "      <th>2009-12</th>\n",
       "      <th>2010-06</th>\n",
       "      <th>2010-12</th>\n",
       "      <th>2011-06</th>\n",
       "      <th>2011-12</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>...</th>\n",
       "      <th>2013-12</th>\n",
       "      <th>2014-06</th>\n",
       "      <th>2014-12</th>\n",
       "      <th>2015-06</th>\n",
       "      <th>2015-12</th>\n",
       "      <th>2016-06</th>\n",
       "      <th>2016-12</th>\n",
       "      <th>2017-06</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-06</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New York</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>449900.0</td>\n",
       "      <td>463500.0</td>\n",
       "      <td>438900.0</td>\n",
       "      <td>470600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>482800.0</td>\n",
       "      <td>491600.0</td>\n",
       "      <td>490700.0</td>\n",
       "      <td>524600.0</td>\n",
       "      <td>540400.0</td>\n",
       "      <td>540900.0</td>\n",
       "      <td>543900.0</td>\n",
       "      <td>544000.0</td>\n",
       "      <td>552100.0</td>\n",
       "      <td>556200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>449200.0</td>\n",
       "      <td>374700.0</td>\n",
       "      <td>323100.0</td>\n",
       "      <td>354400.0</td>\n",
       "      <td>347000.0</td>\n",
       "      <td>364500.0</td>\n",
       "      <td>343600.0</td>\n",
       "      <td>333200.0</td>\n",
       "      <td>341700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>484400.0</td>\n",
       "      <td>504400.0</td>\n",
       "      <td>510900.0</td>\n",
       "      <td>532300.0</td>\n",
       "      <td>563200.0</td>\n",
       "      <td>578400.0</td>\n",
       "      <td>605600.0</td>\n",
       "      <td>629700.0</td>\n",
       "      <td>672200.0</td>\n",
       "      <td>688000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chicago</td>\n",
       "      <td>282100.0</td>\n",
       "      <td>264000.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>242200.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>215200.0</td>\n",
       "      <td>194000.0</td>\n",
       "      <td>194600.0</td>\n",
       "      <td>196000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>251500.0</td>\n",
       "      <td>259300.0</td>\n",
       "      <td>268300.0</td>\n",
       "      <td>272200.0</td>\n",
       "      <td>257800.0</td>\n",
       "      <td>269800.0</td>\n",
       "      <td>281500.0</td>\n",
       "      <td>276400.0</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>277800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>113600.0</td>\n",
       "      <td>126400.0</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>105600.0</td>\n",
       "      <td>111300.0</td>\n",
       "      <td>103800.0</td>\n",
       "      <td>108200.0</td>\n",
       "      <td>...</td>\n",
       "      <td>117500.0</td>\n",
       "      <td>119200.0</td>\n",
       "      <td>119600.0</td>\n",
       "      <td>123400.0</td>\n",
       "      <td>124600.0</td>\n",
       "      <td>127900.0</td>\n",
       "      <td>131500.0</td>\n",
       "      <td>145900.0</td>\n",
       "      <td>149800.0</td>\n",
       "      <td>153000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Phoenix</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>122600.0</td>\n",
       "      <td>82300.0</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>105500.0</td>\n",
       "      <td>84600.0</td>\n",
       "      <td>82300.0</td>\n",
       "      <td>98800.0</td>\n",
       "      <td>122000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164400.0</td>\n",
       "      <td>162500.0</td>\n",
       "      <td>175100.0</td>\n",
       "      <td>190000.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>205100.0</td>\n",
       "      <td>212400.0</td>\n",
       "      <td>214700.0</td>\n",
       "      <td>230100.0</td>\n",
       "      <td>237000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     RegionName   2008-06   2008-12   2009-06   2009-12   2010-06   2010-12  \\\n",
       "0      New York       NaN       NaN       NaN       NaN       NaN  449900.0   \n",
       "1   Los Angeles  449200.0  374700.0  323100.0  354400.0  347000.0  364500.0   \n",
       "2       Chicago  282100.0  264000.0  231200.0  242200.0  231200.0  215200.0   \n",
       "3  Philadelphia  110300.0  110300.0  113600.0  126400.0  120000.0  105600.0   \n",
       "4       Phoenix  198300.0  122600.0   82300.0  105000.0  105500.0   84600.0   \n",
       "\n",
       "    2011-06   2011-12   2012-06    ...      2013-12   2014-06   2014-12  \\\n",
       "0  463500.0  438900.0  470600.0    ...     482800.0  491600.0  490700.0   \n",
       "1  343600.0  333200.0  341700.0    ...     484400.0  504400.0  510900.0   \n",
       "2  194000.0  194600.0  196000.0    ...     251500.0  259300.0  268300.0   \n",
       "3  111300.0  103800.0  108200.0    ...     117500.0  119200.0  119600.0   \n",
       "4   82300.0   98800.0  122000.0    ...     164400.0  162500.0  175100.0   \n",
       "\n",
       "    2015-06   2015-12   2016-06   2016-12   2017-06   2017-12   2018-06  \n",
       "0  524600.0  540400.0  540900.0  543900.0  544000.0  552100.0  556200.0  \n",
       "1  532300.0  563200.0  578400.0  605600.0  629700.0  672200.0  688000.0  \n",
       "2  272200.0  257800.0  269800.0  281500.0  276400.0  275000.0  277800.0  \n",
       "3  123400.0  124600.0  127900.0  131500.0  145900.0  149800.0  153000.0  \n",
       "4  190000.0  198300.0  205100.0  212400.0  214700.0  230100.0  237000.0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 700,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Select subset of columns\n",
    "df_Cities_6mon = df_SalePrice_Cities.iloc[0:,1::6]\n",
    "df_Cities_6mon.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 701,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-12</th>\n",
       "      <th>2009-06</th>\n",
       "      <th>2009-12</th>\n",
       "      <th>2010-06</th>\n",
       "      <th>2010-12</th>\n",
       "      <th>2011-06</th>\n",
       "      <th>2011-12</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>2012-12</th>\n",
       "      <th>...</th>\n",
       "      <th>2013-12</th>\n",
       "      <th>2014-06</th>\n",
       "      <th>2014-12</th>\n",
       "      <th>2015-06</th>\n",
       "      <th>2015-12</th>\n",
       "      <th>2016-06</th>\n",
       "      <th>2016-12</th>\n",
       "      <th>2017-06</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-06</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RegionName</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>New York</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>449900.0</td>\n",
       "      <td>463500.0</td>\n",
       "      <td>438900.0</td>\n",
       "      <td>470600.0</td>\n",
       "      <td>492300.0</td>\n",
       "      <td>...</td>\n",
       "      <td>482800.0</td>\n",
       "      <td>491600.0</td>\n",
       "      <td>490700.0</td>\n",
       "      <td>524600.0</td>\n",
       "      <td>540400.0</td>\n",
       "      <td>540900.0</td>\n",
       "      <td>543900.0</td>\n",
       "      <td>544000.0</td>\n",
       "      <td>552100.0</td>\n",
       "      <td>556200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Los Angeles</th>\n",
       "      <td>449200.0</td>\n",
       "      <td>374700.0</td>\n",
       "      <td>323100.0</td>\n",
       "      <td>354400.0</td>\n",
       "      <td>347000.0</td>\n",
       "      <td>364500.0</td>\n",
       "      <td>343600.0</td>\n",
       "      <td>333200.0</td>\n",
       "      <td>341700.0</td>\n",
       "      <td>400400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>484400.0</td>\n",
       "      <td>504400.0</td>\n",
       "      <td>510900.0</td>\n",
       "      <td>532300.0</td>\n",
       "      <td>563200.0</td>\n",
       "      <td>578400.0</td>\n",
       "      <td>605600.0</td>\n",
       "      <td>629700.0</td>\n",
       "      <td>672200.0</td>\n",
       "      <td>688000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chicago</th>\n",
       "      <td>282100.0</td>\n",
       "      <td>264000.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>242200.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>215200.0</td>\n",
       "      <td>194000.0</td>\n",
       "      <td>194600.0</td>\n",
       "      <td>196000.0</td>\n",
       "      <td>203800.0</td>\n",
       "      <td>...</td>\n",
       "      <td>251500.0</td>\n",
       "      <td>259300.0</td>\n",
       "      <td>268300.0</td>\n",
       "      <td>272200.0</td>\n",
       "      <td>257800.0</td>\n",
       "      <td>269800.0</td>\n",
       "      <td>281500.0</td>\n",
       "      <td>276400.0</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>277800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philadelphia</th>\n",
       "      <td>110300.0</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>113600.0</td>\n",
       "      <td>126400.0</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>105600.0</td>\n",
       "      <td>111300.0</td>\n",
       "      <td>103800.0</td>\n",
       "      <td>108200.0</td>\n",
       "      <td>111500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>117500.0</td>\n",
       "      <td>119200.0</td>\n",
       "      <td>119600.0</td>\n",
       "      <td>123400.0</td>\n",
       "      <td>124600.0</td>\n",
       "      <td>127900.0</td>\n",
       "      <td>131500.0</td>\n",
       "      <td>145900.0</td>\n",
       "      <td>149800.0</td>\n",
       "      <td>153000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phoenix</th>\n",
       "      <td>198300.0</td>\n",
       "      <td>122600.0</td>\n",
       "      <td>82300.0</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>105500.0</td>\n",
       "      <td>84600.0</td>\n",
       "      <td>82300.0</td>\n",
       "      <td>98800.0</td>\n",
       "      <td>122000.0</td>\n",
       "      <td>142800.0</td>\n",
       "      <td>...</td>\n",
       "      <td>164400.0</td>\n",
       "      <td>162500.0</td>\n",
       "      <td>175100.0</td>\n",
       "      <td>190000.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>205100.0</td>\n",
       "      <td>212400.0</td>\n",
       "      <td>214700.0</td>\n",
       "      <td>230100.0</td>\n",
       "      <td>237000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Las Vegas</th>\n",
       "      <td>230000.0</td>\n",
       "      <td>166100.0</td>\n",
       "      <td>120500.0</td>\n",
       "      <td>121500.0</td>\n",
       "      <td>128700.0</td>\n",
       "      <td>115500.0</td>\n",
       "      <td>108700.0</td>\n",
       "      <td>105700.0</td>\n",
       "      <td>116700.0</td>\n",
       "      <td>133200.0</td>\n",
       "      <td>...</td>\n",
       "      <td>166400.0</td>\n",
       "      <td>163800.0</td>\n",
       "      <td>178900.0</td>\n",
       "      <td>186800.0</td>\n",
       "      <td>192300.0</td>\n",
       "      <td>200100.0</td>\n",
       "      <td>207200.0</td>\n",
       "      <td>225400.0</td>\n",
       "      <td>237400.0</td>\n",
       "      <td>264000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>San Antonio</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>163100.0</td>\n",
       "      <td>165900.0</td>\n",
       "      <td>170800.0</td>\n",
       "      <td>177800.0</td>\n",
       "      <td>176100.0</td>\n",
       "      <td>181300.0</td>\n",
       "      <td>178600.0</td>\n",
       "      <td>199500.0</td>\n",
       "      <td>192000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>San Diego</th>\n",
       "      <td>380600.0</td>\n",
       "      <td>308200.0</td>\n",
       "      <td>308400.0</td>\n",
       "      <td>350200.0</td>\n",
       "      <td>343500.0</td>\n",
       "      <td>359200.0</td>\n",
       "      <td>336900.0</td>\n",
       "      <td>330100.0</td>\n",
       "      <td>355000.0</td>\n",
       "      <td>389800.0</td>\n",
       "      <td>...</td>\n",
       "      <td>435800.0</td>\n",
       "      <td>445600.0</td>\n",
       "      <td>464500.0</td>\n",
       "      <td>475900.0</td>\n",
       "      <td>489500.0</td>\n",
       "      <td>505300.0</td>\n",
       "      <td>522800.0</td>\n",
       "      <td>537400.0</td>\n",
       "      <td>574300.0</td>\n",
       "      <td>584200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dallas</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249700.0</td>\n",
       "      <td>250300.0</td>\n",
       "      <td>255400.0</td>\n",
       "      <td>258000.0</td>\n",
       "      <td>268400.0</td>\n",
       "      <td>275300.0</td>\n",
       "      <td>281200.0</td>\n",
       "      <td>281900.0</td>\n",
       "      <td>287700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>San Jose</th>\n",
       "      <td>543300.0</td>\n",
       "      <td>428300.0</td>\n",
       "      <td>366700.0</td>\n",
       "      <td>448600.0</td>\n",
       "      <td>446400.0</td>\n",
       "      <td>448600.0</td>\n",
       "      <td>422500.0</td>\n",
       "      <td>422600.0</td>\n",
       "      <td>450200.0</td>\n",
       "      <td>526900.0</td>\n",
       "      <td>...</td>\n",
       "      <td>616700.0</td>\n",
       "      <td>640200.0</td>\n",
       "      <td>669100.0</td>\n",
       "      <td>705300.0</td>\n",
       "      <td>738400.0</td>\n",
       "      <td>760300.0</td>\n",
       "      <td>785600.0</td>\n",
       "      <td>817400.0</td>\n",
       "      <td>970900.0</td>\n",
       "      <td>1054600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               2008-06   2008-12   2009-06   2009-12   2010-06   2010-12  \\\n",
       "RegionName                                                                 \n",
       "New York           NaN       NaN       NaN       NaN       NaN  449900.0   \n",
       "Los Angeles   449200.0  374700.0  323100.0  354400.0  347000.0  364500.0   \n",
       "Chicago       282100.0  264000.0  231200.0  242200.0  231200.0  215200.0   \n",
       "Philadelphia  110300.0  110300.0  113600.0  126400.0  120000.0  105600.0   \n",
       "Phoenix       198300.0  122600.0   82300.0  105000.0  105500.0   84600.0   \n",
       "Las Vegas     230000.0  166100.0  120500.0  121500.0  128700.0  115500.0   \n",
       "San Antonio        NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "San Diego     380600.0  308200.0  308400.0  350200.0  343500.0  359200.0   \n",
       "Dallas             NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "San Jose      543300.0  428300.0  366700.0  448600.0  446400.0  448600.0   \n",
       "\n",
       "               2011-06   2011-12   2012-06   2012-12    ...       2013-12  \\\n",
       "RegionName                                              ...                 \n",
       "New York      463500.0  438900.0  470600.0  492300.0    ...      482800.0   \n",
       "Los Angeles   343600.0  333200.0  341700.0  400400.0    ...      484400.0   \n",
       "Chicago       194000.0  194600.0  196000.0  203800.0    ...      251500.0   \n",
       "Philadelphia  111300.0  103800.0  108200.0  111500.0    ...      117500.0   \n",
       "Phoenix        82300.0   98800.0  122000.0  142800.0    ...      164400.0   \n",
       "Las Vegas     108700.0  105700.0  116700.0  133200.0    ...      166400.0   \n",
       "San Antonio        NaN       NaN       NaN       NaN    ...           NaN   \n",
       "San Diego     336900.0  330100.0  355000.0  389800.0    ...      435800.0   \n",
       "Dallas             NaN       NaN       NaN       NaN    ...           NaN   \n",
       "San Jose      422500.0  422600.0  450200.0  526900.0    ...      616700.0   \n",
       "\n",
       "               2014-06   2014-12   2015-06   2015-12   2016-06   2016-12  \\\n",
       "RegionName                                                                 \n",
       "New York      491600.0  490700.0  524600.0  540400.0  540900.0  543900.0   \n",
       "Los Angeles   504400.0  510900.0  532300.0  563200.0  578400.0  605600.0   \n",
       "Chicago       259300.0  268300.0  272200.0  257800.0  269800.0  281500.0   \n",
       "Philadelphia  119200.0  119600.0  123400.0  124600.0  127900.0  131500.0   \n",
       "Phoenix       162500.0  175100.0  190000.0  198300.0  205100.0  212400.0   \n",
       "Las Vegas     163800.0  178900.0  186800.0  192300.0  200100.0  207200.0   \n",
       "San Antonio   163100.0  165900.0  170800.0  177800.0  176100.0  181300.0   \n",
       "San Diego     445600.0  464500.0  475900.0  489500.0  505300.0  522800.0   \n",
       "Dallas        249700.0  250300.0  255400.0  258000.0  268400.0  275300.0   \n",
       "San Jose      640200.0  669100.0  705300.0  738400.0  760300.0  785600.0   \n",
       "\n",
       "               2017-06   2017-12    2018-06  \n",
       "RegionName                                   \n",
       "New York      544000.0  552100.0   556200.0  \n",
       "Los Angeles   629700.0  672200.0   688000.0  \n",
       "Chicago       276400.0  275000.0   277800.0  \n",
       "Philadelphia  145900.0  149800.0   153000.0  \n",
       "Phoenix       214700.0  230100.0   237000.0  \n",
       "Las Vegas     225400.0  237400.0   264000.0  \n",
       "San Antonio   178600.0  199500.0   192000.0  \n",
       "San Diego     537400.0  574300.0   584200.0  \n",
       "Dallas        281200.0  281900.0   287700.0  \n",
       "San Jose      817400.0  970900.0  1054600.0  \n",
       "\n",
       "[10 rows x 21 columns]"
      ]
     },
     "execution_count": 701,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_Cities_6mon.set_index('RegionName')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 702,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>RegionName</th>\n",
       "      <th>New York</th>\n",
       "      <th>Los Angeles</th>\n",
       "      <th>Chicago</th>\n",
       "      <th>Philadelphia</th>\n",
       "      <th>Phoenix</th>\n",
       "      <th>Las Vegas</th>\n",
       "      <th>San Antonio</th>\n",
       "      <th>San Diego</th>\n",
       "      <th>Dallas</th>\n",
       "      <th>San Jose</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>449200.0</td>\n",
       "      <td>282100.0</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>230000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>380600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>543300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>374700.0</td>\n",
       "      <td>264000.0</td>\n",
       "      <td>110300.0</td>\n",
       "      <td>122600.0</td>\n",
       "      <td>166100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>308200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>428300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>323100.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>113600.0</td>\n",
       "      <td>82300.0</td>\n",
       "      <td>120500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>308400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>366700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>354400.0</td>\n",
       "      <td>242200.0</td>\n",
       "      <td>126400.0</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>121500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>350200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>448600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>347000.0</td>\n",
       "      <td>231200.0</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>105500.0</td>\n",
       "      <td>128700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>343500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>446400.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "RegionName  New York  Los Angeles   Chicago  Philadelphia   Phoenix  \\\n",
       "2008-06          NaN     449200.0  282100.0      110300.0  198300.0   \n",
       "2008-12          NaN     374700.0  264000.0      110300.0  122600.0   \n",
       "2009-06          NaN     323100.0  231200.0      113600.0   82300.0   \n",
       "2009-12          NaN     354400.0  242200.0      126400.0  105000.0   \n",
       "2010-06          NaN     347000.0  231200.0      120000.0  105500.0   \n",
       "\n",
       "RegionName  Las Vegas  San Antonio  San Diego  Dallas  San Jose  \n",
       "2008-06      230000.0          NaN   380600.0     NaN  543300.0  \n",
       "2008-12      166100.0          NaN   308200.0     NaN  428300.0  \n",
       "2009-06      120500.0          NaN   308400.0     NaN  366700.0  \n",
       "2009-12      121500.0          NaN   350200.0     NaN  448600.0  \n",
       "2010-06      128700.0          NaN   343500.0     NaN  446400.0  "
      ]
     },
     "execution_count": 702,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Transpose\n",
    "df_cities_T = df_Cities_6mon.set_index('RegionName').T\n",
    "df_cities_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 709,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>RegionName</th>\n",
       "      <th>New York</th>\n",
       "      <th>Los Angeles</th>\n",
       "      <th>Chicago</th>\n",
       "      <th>Philadelphia</th>\n",
       "      <th>Phoenix</th>\n",
       "      <th>Las Vegas</th>\n",
       "      <th>San Antonio</th>\n",
       "      <th>San Diego</th>\n",
       "      <th>Dallas</th>\n",
       "      <th>San Jose</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-06</th>\n",
       "      <td>491600.0</td>\n",
       "      <td>504400.0</td>\n",
       "      <td>259300.0</td>\n",
       "      <td>119200.0</td>\n",
       "      <td>162500.0</td>\n",
       "      <td>163800.0</td>\n",
       "      <td>163100.0</td>\n",
       "      <td>445600.0</td>\n",
       "      <td>249700.0</td>\n",
       "      <td>640200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12</th>\n",
       "      <td>490700.0</td>\n",
       "      <td>510900.0</td>\n",
       "      <td>268300.0</td>\n",
       "      <td>119600.0</td>\n",
       "      <td>175100.0</td>\n",
       "      <td>178900.0</td>\n",
       "      <td>165900.0</td>\n",
       "      <td>464500.0</td>\n",
       "      <td>250300.0</td>\n",
       "      <td>669100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06</th>\n",
       "      <td>524600.0</td>\n",
       "      <td>532300.0</td>\n",
       "      <td>272200.0</td>\n",
       "      <td>123400.0</td>\n",
       "      <td>190000.0</td>\n",
       "      <td>186800.0</td>\n",
       "      <td>170800.0</td>\n",
       "      <td>475900.0</td>\n",
       "      <td>255400.0</td>\n",
       "      <td>705300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12</th>\n",
       "      <td>540400.0</td>\n",
       "      <td>563200.0</td>\n",
       "      <td>257800.0</td>\n",
       "      <td>124600.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>192300.0</td>\n",
       "      <td>177800.0</td>\n",
       "      <td>489500.0</td>\n",
       "      <td>258000.0</td>\n",
       "      <td>738400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06</th>\n",
       "      <td>540900.0</td>\n",
       "      <td>578400.0</td>\n",
       "      <td>269800.0</td>\n",
       "      <td>127900.0</td>\n",
       "      <td>205100.0</td>\n",
       "      <td>200100.0</td>\n",
       "      <td>176100.0</td>\n",
       "      <td>505300.0</td>\n",
       "      <td>268400.0</td>\n",
       "      <td>760300.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "RegionName  New York  Los Angeles   Chicago  Philadelphia   Phoenix  \\\n",
       "2014-06     491600.0     504400.0  259300.0      119200.0  162500.0   \n",
       "2014-12     490700.0     510900.0  268300.0      119600.0  175100.0   \n",
       "2015-06     524600.0     532300.0  272200.0      123400.0  190000.0   \n",
       "2015-12     540400.0     563200.0  257800.0      124600.0  198300.0   \n",
       "2016-06     540900.0     578400.0  269800.0      127900.0  205100.0   \n",
       "\n",
       "RegionName  Las Vegas  San Antonio  San Diego    Dallas  San Jose  \n",
       "2014-06      163800.0     163100.0   445600.0  249700.0  640200.0  \n",
       "2014-12      178900.0     165900.0   464500.0  250300.0  669100.0  \n",
       "2015-06      186800.0     170800.0   475900.0  255400.0  705300.0  \n",
       "2015-12      192300.0     177800.0   489500.0  258000.0  738400.0  \n",
       "2016-06      200100.0     176100.0   505300.0  268400.0  760300.0  "
      ]
     },
     "execution_count": 709,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cities_T = df_cities_T.dropna()\n",
    "df_cities_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 713,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Reset index\n",
    "df_cities_T.reset_index(level=0,inplace=True)\n",
    "\n",
    "##Name columns\n",
    "df_cities_T.columns = ['YearMonth','New York', 'Los Angeles', 'Chicago', 'Philadelphia', 'Phoenix','Las Vegas', 'San Antonio', 'San Diego', 'Dallas', 'San Jose']\n",
    "\n",
    "#Extract Month and Year into separate columns\n",
    "df_cities_T['Year']= (df_cities_T['YearMonth'].str.split('-').str[0])\n",
    "df_cities_T['Month']= (df_cities_T['YearMonth'].str.split('-').str[1])\n",
    "\n",
    "df_cities_T['MonthName']=df_cities_T['Month'].apply(lambda x: 'Jun' if x == '06' else 'Dec')\n",
    "df_cities_T['Yr']=df_cities_T['Year'].apply(lambda x: '\\''+x[-2:])\n",
    "df_cities_T['MonthYr']=df_cities_T['MonthName'] +' '+ df_cities_T['Yr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 715,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>New York</th>\n",
       "      <th>Los Angeles</th>\n",
       "      <th>Chicago</th>\n",
       "      <th>Philadelphia</th>\n",
       "      <th>Phoenix</th>\n",
       "      <th>Las Vegas</th>\n",
       "      <th>San Antonio</th>\n",
       "      <th>San Diego</th>\n",
       "      <th>Dallas</th>\n",
       "      <th>San Jose</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>MonthName</th>\n",
       "      <th>Yr</th>\n",
       "      <th>MonthYr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-06</td>\n",
       "      <td>491600.0</td>\n",
       "      <td>504400.0</td>\n",
       "      <td>259300.0</td>\n",
       "      <td>119200.0</td>\n",
       "      <td>162500.0</td>\n",
       "      <td>163800.0</td>\n",
       "      <td>163100.0</td>\n",
       "      <td>445600.0</td>\n",
       "      <td>249700.0</td>\n",
       "      <td>640200.0</td>\n",
       "      <td>2014</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'14</td>\n",
       "      <td>Jun '14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-12</td>\n",
       "      <td>490700.0</td>\n",
       "      <td>510900.0</td>\n",
       "      <td>268300.0</td>\n",
       "      <td>119600.0</td>\n",
       "      <td>175100.0</td>\n",
       "      <td>178900.0</td>\n",
       "      <td>165900.0</td>\n",
       "      <td>464500.0</td>\n",
       "      <td>250300.0</td>\n",
       "      <td>669100.0</td>\n",
       "      <td>2014</td>\n",
       "      <td>12</td>\n",
       "      <td>Dec</td>\n",
       "      <td>'14</td>\n",
       "      <td>Dec '14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-06</td>\n",
       "      <td>524600.0</td>\n",
       "      <td>532300.0</td>\n",
       "      <td>272200.0</td>\n",
       "      <td>123400.0</td>\n",
       "      <td>190000.0</td>\n",
       "      <td>186800.0</td>\n",
       "      <td>170800.0</td>\n",
       "      <td>475900.0</td>\n",
       "      <td>255400.0</td>\n",
       "      <td>705300.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'15</td>\n",
       "      <td>Jun '15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-12</td>\n",
       "      <td>540400.0</td>\n",
       "      <td>563200.0</td>\n",
       "      <td>257800.0</td>\n",
       "      <td>124600.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>192300.0</td>\n",
       "      <td>177800.0</td>\n",
       "      <td>489500.0</td>\n",
       "      <td>258000.0</td>\n",
       "      <td>738400.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>12</td>\n",
       "      <td>Dec</td>\n",
       "      <td>'15</td>\n",
       "      <td>Dec '15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-06</td>\n",
       "      <td>540900.0</td>\n",
       "      <td>578400.0</td>\n",
       "      <td>269800.0</td>\n",
       "      <td>127900.0</td>\n",
       "      <td>205100.0</td>\n",
       "      <td>200100.0</td>\n",
       "      <td>176100.0</td>\n",
       "      <td>505300.0</td>\n",
       "      <td>268400.0</td>\n",
       "      <td>760300.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'16</td>\n",
       "      <td>Jun '16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  New York  Los Angeles   Chicago  Philadelphia   Phoenix  \\\n",
       "0   2014-06  491600.0     504400.0  259300.0      119200.0  162500.0   \n",
       "1   2014-12  490700.0     510900.0  268300.0      119600.0  175100.0   \n",
       "2   2015-06  524600.0     532300.0  272200.0      123400.0  190000.0   \n",
       "3   2015-12  540400.0     563200.0  257800.0      124600.0  198300.0   \n",
       "4   2016-06  540900.0     578400.0  269800.0      127900.0  205100.0   \n",
       "\n",
       "   Las Vegas  San Antonio  San Diego    Dallas  San Jose  Year Month  \\\n",
       "0   163800.0     163100.0   445600.0  249700.0  640200.0  2014    06   \n",
       "1   178900.0     165900.0   464500.0  250300.0  669100.0  2014    12   \n",
       "2   186800.0     170800.0   475900.0  255400.0  705300.0  2015    06   \n",
       "3   192300.0     177800.0   489500.0  258000.0  738400.0  2015    12   \n",
       "4   200100.0     176100.0   505300.0  268400.0  760300.0  2016    06   \n",
       "\n",
       "  MonthName   Yr  MonthYr  \n",
       "0       Jun  '14  Jun '14  \n",
       "1       Dec  '14  Dec '14  \n",
       "2       Jun  '15  Jun '15  \n",
       "3       Dec  '15  Dec '15  \n",
       "4       Jun  '16  Jun '16  "
      ]
     },
     "execution_count": 715,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cities_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 716,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABQQAAAMDCAYAAAD0SxgZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd4VFX6wPHvGxJIgEAIoWQBARHsgqBSFFBhFTs2xI7d\nxcLyWzsWdMW6sshaUCygslJUBEUQVLAAFhQUBVyliUBoIbQQSDm/P865mcnkzmQmhSTwfp5nnknm\nnnPvuXXmvvcUMcaglFJKKaWUUkoppZQ6MMRVdgGUUkoppZRSSimllFL7jgYElVJKKaWUUkoppZQ6\ngGhAUCmllFJKKaWUUkqpA4gGBJVSSimllFJKKaWUOoBoQFAppZRSSimllFJKqQOIBgSVUkoppZRS\nSimllDqAaEBQKaWqGREZKiJGRMb4TDPu1WqfF6wKirStVNUmIgPcvptTAfPW40KpMhKRRe486lvZ\nZSkPItLBrU9WZZclWiIyzZX52Moui9r/iMhRIlIgIrMquyxKqYqhAUGl1AFPRMYEBdJyRaRxCen7\nBqU3IjJgHxV1vyMic0K2pXE/PrNE5FsReVBEUiu7nKp8uWDfUBHpUNllqWhBgc3SvAZUdvkjEZEG\nInK+iDwmIrNEJDOo7E2jnEe8iNwuIt+JyHb3+k5EbhORGqUsV+g1+toS0tcRkR1B6d8vzXIjzP8e\nd7xHtU1U2YnImSIySURWiUiO27+/ichnIvJPEelV2uOrqhCRHsCZwDRjzMKQaXVEpL/7ffOLiOxy\n22GViLwlIl2iXMbZIvKxiGwSkd0i8quIPBXN97KIHCQiLwbtgwwReU9ETowib1cRGefy7hGRbLfs\nl0Tk8GjKXt5EpKaInCsio0RkobtW7RWRtW69+kQ5n5Nc+gy3XVa67dQiQp7aInKWiDwkIh+KyIag\n61W0+/JIERntzoPdQct+U0Q6++UxxvwMTAF6i0jvaJajlKpe4iu7AEopVcXEA5cBIyKkuWoflaU0\nfnXvuZVaitjlANvc3zWANOB497pRRHoZY34NlzmCzdhtsr5cSqnKywCgJ7AKWFQJy9+Xx8VuYIPP\n595xDrAV2Bsmb1V2HvB6aTOLSBIwA+jhPspx78e51wUicoYxJscvfwyuAl6LMP1CoG4ZlxHJPUB9\n4H0gowKXc8ATkZrAW8DFQR/nutfBwCHAKcD9QGvsNciTg70ubN8XZS0HT7j3R32mzcGeQ54cIB9o\n6V6Xicg/jTEPhZu5iDwN3OH+zQeygXbAnS5/D2PMijB5uwHTgXruo+1AY+B84DwRuc0Y80KYvPcA\njwHiPsrGXi/budc1InKVMWZ8uLJXkHHARUH/78Vu179g1+t8EXkNuMEYU+A3AxG5Dfv7Mg4wwA6g\nFXAzcKmInG6M+cYn6wnAh6UtuIhcCbwKJLiP9mD3aSv3ulxE7jLG/Msn+6NAX+Bx4JPSlkEpVTVp\nDUGllAr4w72HDfi5p+JnATuBzH1RqFgYYw5zr7WVXZYYTTDGNHWvRtib58HYH63NgPEiIhHn4MMY\n85zbHveWc3lVNbYvjwtjTPCxXfjCBrs9F/ilMcZMqOjylYP1wAfAg8CgGPOOwAYDdwD9gDru1c99\ndjLwTBnKthcbgOshIi0jpPOu+avLsCxVNfwTGwwsAIYDbYFEY0wqUBvoCgwDin1HGmOWuevCCfuw\nvKUiIl2x67LYGPO1T5IEYAnwd6CtMSYJG/Q+HJiGDbY9KCKXhZn/pQSCgQ8D9Ywx9YBO2KBpM+B9\nv1qWIlIfmIwNBs5zy68PNARewt5/jvSr2eZqqj3uyjcFaGeMqQMkYQOc37h1e7USatwmYK8R9wNH\nY4+retgA61iX5lrsA4BiXM1ILxj4EtDQbZd22O1UH7tNk8MsfwvwMfb4vSLaQovIQcBoV/65QEcg\nyW3Xw4CPsNv7SfGptW+M+R774O44Eeke7XKVUtWDBgSVUipgPrAcOFZEjgyTpj9QE3iXql97p9oy\nxmw3xozA/vAF6ABE1SxGKbXPvGmM+Ysx5lxjzD+BL6LNKCKHANe5f281xkwyxhS41yTgNjftRhFp\nXcryGeC/2Jtd3xtoEWmGrTG2GXuzraopVzvwZvfv48aYfxhjfvdqaxlj9hhjvjbG3I+tFfVnJRW1\nPFzv3sPVkrsVOMoY86wx5ncAYy3D1vb6zqW7MzSjiMQR+O593Rgz1BiT7ebxA3AuNth+NLZFRajB\n2NqAm4Fzg5a/1RhzMzAbW+NvmE9eb37rgUuMMb8Flf174BwgDxvcjaqJbjl6EhvcHGaM+dkYY1zZ\n/jDGDMDWAAYYHKY5+jDsvfdsY8zNxpitLv9v2G26BWiKDeKG+tIYk2aM6eOO32kxlPtCoBa2lux5\nxpiFQWX/FVvrMcOVLVx/oG+79+vCTFdKVVMaEFRKqaLedO/hagl6n78RzcxE5BwRmeL6itkrIhtF\n5AMROb2EfIeKyNsu/W4RWeb6jqlVQj7fQUVEpIaInCIiz4rI967/mb0isk5EJovIqRHm6fXzN0BE\nksT2hfWrK9dGERkvIm2j2R6l8HbQ352CylQ4KISIxInIrWL7HMxyn3cITRdh/TqLyBsS6Odos4j8\nICKPi8ihYfK0EpH/uO2QLbZ/qu9F5G4RqVPalRWRI0RkQsh+f1hEEsOtiyuLERHj/u8iIu+IyHoR\nyReRESHp67l5/SgiO93rJ7ec+j5lesDNf6LPtOOCjrlizb9EpI+btsr9P8CVs6dL8roU7ettVYRt\nc46IzHb7eKeIfC22FkvMIh0XweeQ2D6wRovIn2L7sVopIv8SkXo+s61w7vh4XURWu/JsEdsn2hUi\n/jVoJWjgBxFpIiIvuPw5IvKHO47T/PKWxBiTX4bVuQQbFFiHbYoX6i1sUCDepS0t71p9ZZjpV2J/\nD79NFF0tiEg7sX2I/e7O0W0i8o2I/F1Crs8iMsId7955tTDkeH8/NK17jxeRO9x1aLv4X9O7ishE\nsddw77vlQxE5K0LZk0TkLrHXym0u33qx/aGNEJGOJa1/hHlHfWy59TIicn8J85wS7toSRksCTVQj\nNq80xuQZY/JCluc7qEjQvinp5dv3pIhcJCIfuX20VwJ96fX0S18SEamNrUULUOy67NbvKy/o4zMt\nj8A5d4yIhHYh1RXbnBrgaZ/8/8PW3gO43GcRXlDvNWPMFp/pXrPUU0TkLyHTmrj3JcaYPT7L3kSg\nNUepv2tLwxgz3xgT6Roxxr2nYY/FQmIfPHhdI/ht0y0EujUoFmQt47XW26Z/+O0PY8xubG1SCL9N\nvePsYhGpyO4VlFL7mAYElVKqKC8geLnYp+SFRKQd0BlYg+2fJywRSRCRt4Cp2Ce/TbA1ChsBZwMz\nROSpMHl7AD9gayM2wj6Jbw0MxT5Zr1mK9Toc+Ay4HdtcpL6bbzr2ifCnInJfCfOoh21u8hD2x65x\n5bsE+FpE2pSiXCUJbtblF4QR4D3gP9j18r0B8iPWk8DX2KBAS2wT5WTgWGyzn2JNSkXkAmAptgZG\nO/dxTbf8J4D5ItIkNF8U5ekNfI+90Qve7w9i93vEYLCbRz/gS2yNgCRsH0HB0w8BfsLuw2Ow20+w\nNT0eBH6S4sHdz927381rzzB/h37mzcPrT8+7qdru/vdem8Ks1wPYc8m7oaqDPRf/KyJ+tSnKQ3tg\nIbYmTj3sb6ZWwD+w50tC+KzlT2zwcxG2/8WDsNuyHrZ225vAe2JrSIXTDHt8/Q17w1oAtMAexwtD\nA077wCnu/VO/m1332afu37APLEpijPkRe8wfKv4d53uBwjd9phUhIlcDPwM3AW2w2zAJ27/Xv4Ev\nRCQlKIt3fHvXpS0UPd63+iwmHltT8WnseVls24jIHdgmhhdjaxTtwjbHPAv40AXmJCRPEvba8CS2\nuXoytuuLRtga2IOAG0vaBmHEemy94t4HRAhkN8EOmAGR+3+MVKbyEnqdCn35BolcAPZ9YBJwBnZb\n78b+HjgfmBPF966fbtjmvxu92nel4AWG4ih+P+idm38aY5aGye/Vpu0pQbXhRKQ5tpl2cJpQs7Hb\nTLDdAgRb5d6PCA2wu/k3wl7/wP5OqkqCg22hNQRPwa5vLnb9/Xjb6zCfQGlZrHLvB4lIw9CJIpII\nHOH+9d2mxphV2Ic3tYESB4VRSlUfGhBUSqkgroPsudibidCbUK924LhwHUYHeQr75HwV9mlvsusr\nJhl7M7kduFNCajiJSAPszUNt7A+zDi5fXeBqbJBiYClWba+b7znYG8gkY0xd7I3JA9ibzkfD3DB7\nHgYaYJvp1HFl6oFtdpWK7fenvB0U9HeWz/QLXHkGYvs4aoBdJ9+OzkPcAdzl/n4RaOW2dRKBTr5/\nC84gIsdjm2glYG+sW2K3RW1sk+ZvsDfxUdUgDZpvmptvIvAtcHTQfr8cOIpAU7hIXsXW3GhtjElx\n5RrhluE1dW+JDWqf5uZfF+iNrXVxEDA55EbsG2ygtLGIHBayPC9AtwN7A9cozPTPIdCfHjaYATAo\npM+84ymuPTaA+QC2z6UU7DH8jpv+uFTMSNRjsAG4o10/UXWxzaX2YPuyuqEClulLRI5x5UnAdtR/\nsNsO9bDN8/Kxgf3HIsxmGDZQ81fsutTBnjvrgObYfjr35e9C7wb0lwhpvForR0RIEw0v2FeklqCI\nHOfmvdQY812xXEXTnoINTBnstbCZ64OrNjbw/RM2MPiSl8cY86A73r1BKnqHHO/X+Czqamyw+xrs\n90YD7PfRRleOPgRqGI0B0l2a4Gvw34BbQuZ7A7aW9TZsE0GvX71E7GAb/4d90FEasR5b47CBsTZA\nuD7JrsQGRxcbYxZEWY4VBPr2fdQ9xCszbz/6vSg6eMn0kKwvYAfe+RX7XVXHXde9PnKzgWEickaM\nRfICMt/HvDIB3sOa/xljQgc08s63nyPk987NRAK1CYPzQphz29VIW+mTHuwgRXnYh5UT3EMs7wFe\nR2x/pfHAJGPM/AjlqwzeNt1J8f5IvfVcbsIPkrQk6O+yXvOCTcT+fkoApriasAK2NQr2d0FT7MNR\n3xqnjnceaj+CSu1PjDH60pe+9HVAv7A3VQYY7/6/0f3/RlAawQb3DHC4++xP9/+AkPm1xd6gb8Xe\nuPsts5/L+3PI5w+4zzcDaT75rnDTDTDGZ7o3rVWM28Bb7us+0+a4adnAIT7TL3TTc4CaMS53Trh1\ncdP/FbROnYI+Hxr0+Y0R5j/Ub/7Y2jS73LTHYijvVy7P4DDTG2BrNRrguBjm+7DLswFIiXC8+K1L\nq6BpXwFxYZZxpUuTi+1bKnT6kdjAsQGuDZn2ufv8pqDP4rA339uxNTQNcGHQ9NpB82sTZr8PiLBN\nBgSt1xCf6YnYIIkBrorxuPM9LkLOoZ+BWj7TvXX9LJZl+swneL+dXELad126H/3OMWxg27jt3TRk\n2iI3LQ9o75O3E/Z6ZYCzy7hOHYLWqWkJab1lXhkhzdVe2WMsR1+XL8f9n+7WfzOQEJRupEt3r/v/\nOff/+z7zXOymXRNmmU2xNYQKsAMhBE/Lcnk7RCjziKBt1y9Cuu9dmo8A8Zn+gpu+Kfj4xfalaLB9\n65V6H5fXsYUdhMH3O8dN/8VN/3uMZRoctB0LsA80hgOXUsL3YtDxmxXlsg4iUAP0ZZ91N9hm7+lh\n8nu/Nb6KcR2nuXxPlHK/tcN+XxvgHp/ps920VyPMo2XQdu4e9HnhOet3fEazDGzAemfQ/HcFlXcN\ndlCPGuV1HJfHC/ubYpMr4yif6a+7aZ9GmIcQxXXRpU0J2j5doihfdwLfl8ZtT+830Gbs4E21S5jH\nIy79rMre3vrSl77K76U1BJVSqriJ2B9LF0igP7ie2B/AC0z4JjSeq7DBkveNrXHo5z1sTaMjRSQ9\n6POL3PtoY8xmn3zjqJiRMD9w75Gagrxj/JsnTcX+SKwFHFLWgojt77CtiDxOoHPt+cZ2KB4quN+d\nWFyMDVhtxY5KGU252mC3z25glF8aYzsJ92qJ/DWG8lzg3l82xhSrCWmMmUh0tR6fMeFrr3rH1vvG\nmGI1P4wxvxCoddcvZLI3WETPoM+OxgZAv8I2Rw+d3hVbI2GtMWZ5FGUPJwdXyzGkvDkEmlgdVYb5\nhzPc+PRhRaDj+IpYZjGutubZ7t+nTPHaPADPEqgBEq5T+GnGNp8twp1XM9y/F4VOrwiuDzTvN2ik\nwZmy3XsN1+S1VIwx64FPCDSrxfWb1h8bNHqrhPJ2wu7vLQRGEw1dRgY2yCFAr9KWFXt9nxSmHK2x\nXRMADDPGGJ9k/8SuUxqBpp8QqKWYXixH2ZXm2PKaDRfrk8zVVD8CG+COuG98lvlvbPPnLOy+OAEb\nJPwvsFJEfhPbP2OJXTBE4o7h97GDZ3xF8RqZA9z7eHf8+XkbF9CJsV82bx/6/UaIyDUP/S/2+/pX\n7LUjlPe7J5pzE2yt0NC8OWGOz9D8xdbbGPMOtom1N+hLbQJdZtTGfu8kRpj3PuVq243BnnObsDXa\nQ5W4Td328moPlms/fcaYL7GtXrxaiLWw29L726sFH4l3vFXENUQpVUk0IKiUUiFcQOYD7A+4C93H\nsQwm0s29X+Q6Dy/2wv7Q9fogawGFTTq90Y0/x4f7wRj1SJ7BXH9Gg8UOErJRRHK9ztCxfaUBROq3\nxrdJnbGdbG90/zYoTdmAq4PKkgf8D9uHXw3sTUv/MPkWmJCO4aPkjVg829jmS9Hw9mtN7I1luH3r\nlbVFNDN1N6Ze86CvIiSNNM0TqQmVF0iYHSGNF9gLHVzArx/BnkHTvsDe2IabXhZLjDG7wkzz+pgs\n7XEXSbgmpBW5TD9HEeg31HffucDlXPdvuIEh5kRYhrePSj2oRIyC+42LFDQoT96127uWn4nt022O\nMWZNCXm9c78esC7Cue81/Yzq3A/j6wiBFG//5GCb9xXjgk9LQ9KDrVEI9lo7UUTODenvsCzmRJjm\ne2y5AMWv2O/Z0AcQ17r3qWEejEVkjBmJbap8GTbw+BP2ewXsQ6ungXllXP/XsH3N/oGtGR3aj6B3\nzFwb4XjxuqSoQeTv3lDeQC1+fVCG5QJXr2FrL+4C+of5/vPOz9Kcm2XJi9hBwv6N/U7ZhO3aIhVb\nA/cC7Dr/H/C5C8pWBY9jH9rkY2urb/BJU6btUlau39EfscG/C7DbMxW7fX/D9pU7P+QBdSjveCvV\nIFRKqaopdFQppZRS1hvYWmRXisgkbGAwl6Kj3obj/aDy+mcrifejNpVAR9TrIqRfG2GaL/cjbw6B\nQTDA3hBsxdYmqYH9kRdp1L4dEaZ5T7VLO9BCDrZvK1x5dmB/pE4DxhpjssPk8x2EIgqFo+7FkMfb\nrzWC8kcS7c1KAwIP6MLVJIHIx4Qn0vbw+veLdPx4NTIaiogEBSbmYY//v4jIIa6mqBfwm2OM2SIi\nvwBHi0iqMSaT8gsIVuRxV5rlesvcV7+hvP1WQOTjw9t3of04eiLtd29auLzlyhizS0QKsMd9pPPE\nm5YfQ+A+nMnYfXqW63Myloc83rmfQPme+36iOYczTORRR//EPlwq3J/GmKki8i9sMOVi9zLuvP0Q\n28yxtLXPS3tsvYrtb/caXE1vVxPUG1W6NLW/AXuMYb+v33bzTcbW2h6CDU52xA4E49ePY0RuIJBL\nsLXczjPGbPRJ5h0z9fAfECtULMeMV1vOr7ZwJM9hm07vxQYxF4VJtzOKMgVP2+nzd1LId0i4/DtD\nPv8btmXAaqCHMSZ4+mQR+Q7bnLwTtiZoVH0Xi8jrBAL2waYb/748oyIidwF3E+i+ZEaYpCVuUxew\n9Wo+hm6XUhM78vjT2FrCPY0xwefrLBGZj+0i42Bsdxo3hZmV991X6traSqmqR2sIKqWUvxnYWm+n\nYkdKrIf94RhNbQXv2jrIGCNRvObEWDbfURlLMAIbDFyBDW6mGmPqGmMaG9sxepeIuSveBBPoqP0v\nxphDjTFnG2NejBAMBJ8ROKNUmm3o7deFUe7XARVYFl8lBAk8MTeVc/vAa7Ld09249MDetHiff45d\nl+6uWZo3QE2parSqYoRS7LsY5r2vZbj3SDWjvGkZEdJExQUU38HWtrwZW6MnG9s/Y0m8c392lOd+\nWUa+rpBzGMAYcyd2xPkHsE2os7E1UO8BfhWR80sz3xJEOrbGYh80nCSB0c0vxA66sRaYWV6FMMbs\nMMa8h70ufeM+vtRdq6ImImcT6GbimghBNe+YuTrKYybcfPx4A6dEXcNRRJ7CDr6VD1xmjAk3AjAE\nHj5Fc25C0QcVXt4a2ObUJeUPfcgxyL2PDgkGAmCM+ZNAk/rzIsw/lDfgWOir1DW9ReQW7OBiAP9n\njIkUwI5mmzYluoeDsfK26cSQYCAAbjt7TfgjbVNvW22JkEYpVc1oQFAppXy4ZqjjsdfJYe7jN8Pn\nKMJrLhLrKHGZBG4GI/1ojKn/FtcU2fuRd7kx5j1j+7oLFk2tl/2JF2BoGUMeb7+2df2PlZdMbO0v\niLxvy9pvj1fzKNI6N3fvW3xqdgQ3Gz4CW6N0blCT7eDpnbFBi43GmGVlKrXy9psQuSmqt+/C1TCL\n5ppS2hq3peH1ZXVkhDTeNXRJhDSx8K7hQ7HH52S/oIMP79w/vJzKUVre/mnqruvhhD0WjDH/M8Y8\naoz5K/YG/3Rs8/hawKuuJl2sSnVsuZp1U92/A9y711x4bJQPOGLirldeP5C1iOE7wI2yPg77u+BR\nY/t2Dae0vwOi4T2YjCqYJSIPA3cSGDCqpCB4LOdmDkX7tw0+V33zu1qgrULTu2O6jft3ZYRle8tr\nFSFNEcaYvmECseH6XI1IRK7FDjAF8IAxplg/tyG89Tw4QhA6+Fgpr2seBK5b0WzTJhHK5x1vMTfj\nV0pVXRoQVEqp8LymZAnYprUfREgbzOvH7RwRibopo7GDBfzi/u3hlyaoZlYs0gjUKFkYJk3vGOdZ\n3Xn9b50cw2AF3n6ti+13p1y4/t+8H/8nRUgaaVo0fnDvp0RIc2pI2mDBA4v4NQcuaXowLwBaGTXT\nqpufCTQN9N13rh9Kb0Agv30HRft3DDctXN6K4PWHeKqI1Aid6D7zjsdPy2mZc7BNEb3rcjTNhSFw\n7jcVkW4RU/orr+Pd2z8CnOyXwHUPcXhIel/GmFxjzEzgXPdRA+xgQbEqy7Hl1Uy62g3cdDJu9OFS\nlCNawX2SRtXs1vU3OBXbWmAq8GAJWbxj5nz3vV2efnXvrUtKKCL3ECjrQGNMNMe8d262EJFDw6Tx\nvgPnmKCBrFwNNK9vxHADa52MralrKNovaj6Bc+SgCOXzgriRupOoMCJyGTAaW9YnjTGPRpFtDnZ9\naxL+fPG26TJjTDRdhETL2z/RbNNcYwfs8tPKvetDPqX2IxoQVEqpMIwdIXEo8Azwd+M/4qifsdgf\nYH8B7o2UUERCn/B7TWFucP1chepPDE/Fne0EOrIudrPnbiBvi3Ge1d0k7Gh/DSj5xg4AV9PNCyQ+\nKYERqItxA7jE0qxvsnu/QUTq+8zvQgI1J0rLG0H4DBE51mcZRxIYCdSv5stX2Bu2gwjU5pnjTXQd\nqf8KdCBQIzVcQNAb8bS8BjXYb7nrzofu3zvC1AwbhN2WuQRGQQ51toj4nf8dgD7uX9/RbSvIROzx\n1Azbr1moy7DX0Dz8j8eYuVqvd2Cv6U9gm81G4xsCQftnItXOE5FknwBnuRzvxpiVBJroh/tueQD7\n+34TQcGWEmoU5hD4jihNc+SyHFszsUHaZtjvTgG+MP4j2kfktn3nklMWHm+ZRNGPrNuf44G22Id2\nV0ToG8/jBTTbUcL3q8/vgJJ4AwgdV8J8byPQx94/jDGjopz/1wRqk93pM99DCIxmPs4n/3/d+3Vh\n1u0f7v0zEzQCs6sR+rP79yq/71ARaQh4Tdu/CZ1e0Vyz+rHYc2ykMeaeaPK5QKn30OwOn/mmEujP\n0m+bloU3AvgFbvuFLrsWcKX799sI8znevX9ZjmVTSlUyDQgqpVQExpiHjTF3RPlU3cuzFNtnH8DD\nIvK8iBzsTReRuiLyVxF5k+I3Sc9j+y5MAz4WkWNcngQRuQL7VHobMXBN4rxA1mvuJs0bza8Xgb7f\nDhjGmC3Aw+7fe0TkORE5CAq3y0Ei8n8iEhosvA3Yg+1360sR6e01H3b5jhSR+4HlxNbE9z/Ym9Mm\nwHQXnENE4kWkP/bmMqt0a1toAna0TYD3XdnFLacXdhTSBOwNb7EbEmPMdgI3Fsdja9ksCEn2Ofa3\nRceg//14NWEv8AuAqmIextZkaovtWL81FAaeBwGPuXTPGmPC9be3C/hQRE51eUVE/oqt+VwDe3M9\nPZZCuXmkeS+KBrxSg6eF1pJyAZ9X3b/Pi8iFEnARdgAEgJddIKxcGGPecdf0e4NrNpWQx2D7ks3H\n9rc6R0S6i0gc2ICRiLQXkUewTe9Cm916x/sVsdQaD+N+936yiLwuIk1cGeqLyGPYQRkAHg55iDVZ\nREaJyKnBDzPE9t33JvY7IIvIAYFwSn1suX3gBc+8Wq6lHUykPvC1iHwuIje4Goe4MtUSkW4i8iGB\nIOXzUTZLHoZtWp0JnGuMKbFmmjHmGwLrMUJEnhaRwib/IlJPRM4UkYkEaklGyxtx/vBwD6ZE5Brg\nWffv/caY4dHO3O2TIe7f60TkQXEj+rqHSVOxNd0W4z/Q2r+xv2MaAVO9/SAiKSLyAtALey7d75P3\nRW/dsMfUUe67NV5EugIfu/kaAk129wkROQ0bGI7H/haLta/Q+7EPi3uLyAviRrl2AdYp2PXKILDf\nQpdfeE3FDkLnqR9yrQ19IOFt00bY35Vd3faME5GjsA+cvFrFI8MsuxaBB8oaEFRqf2KM0Ze+9KWv\nA/oFjMH+uBwfY74/Xb4BPtNqAC+46d5rO4FRfb3PZvvk7Ynt7N1Lk0WgBsc87BN/A4zxyevlaRXy\neeeQee4M+n8LtkaXwd37huSdE249g9KscmlOjnEbzgm3LiXkGxpNvkjpsDfA/w7ZR1nYgJ+JkO8M\nl85Lswfbp87ekHm1jHGdTg/az6H7/aug/f5SSL5W4fadzzIOCdpXBnsjvyvo/9VAuwj5hwelnekz\n/bKg6ZvR69AxAAAgAElEQVQBCTOfw4K2cy52AIFVwFdBaQa46XPKehzEeFz4nkOl2d4llKFV0LJK\nPG+wtZpyg/JsDfl/ClDLJ98iN/0WAtesnSH7fQ3QuhTrkBJyzEd6pfjkT8IGjb002diau4XXRyCx\nFOXq6/LnxJjvOZfv/TDTLw7Zbt65nxuyrvVD8p0fNC0HWyttFTbY6aUZ4aaPiKKcdwbNr4BA/7Pe\nZy8Qcu4RuNYG5wn+TtgD9I1xe5XLsYXtG9Mr/zagdinPqfSQ7eCt1xaKfu8abHPx+JD8Hdy0rDDr\nmY0N2IR7vR6SrxY22Bq83G3Ya3tweSaXYl1/cHkvDDM9M2hfRypzBnBkmHk8HVTGPAKtDYzb320i\nlK+bW9fg7zNv3+Rjmy/75RNsIDV4m+2m6PdrHnBbaY6RsryCtrnB9hEZaZv2CTOP20K2Q/BviSyg\nc4TlB6eN9Orgk/fhkGNuL0WvtQZ4KsKyz3ZpftzX211f+tJXxb60hqBSSlUAY0y+MWYgtt+3t7CB\nlprYG+A/sE1ErybQ7CY47+fAsdgaXZuwNxWrsEGMU7E3OLGW5xugK7Y54VZsTbCNwEvYm6Afw+fe\nPxlrMLZPxgnYoFQS9ibmB2ytq2E++aZjm4E96tLlYAMj27EB2weBw40xq2Msz8fYJmDvYG9ga2Gb\nbT2ErVHh9XVY6pqCxtbKag88QqBpFu7vfwLHGGP+F2EWn4f52++zL40xJkw5lmH7l5qB3d5NsX0Y\nNfdLr8AY8zZ2343FBllqY4Mvc4CrsMGcSNeGtUAnbG2RTGwtlzXYINixphxr4UXL2JF/e2Fr2nyP\nvUHOw9Y8HQT0NuH7s9rnjDGTsOf+U9hr5h5srbSt2OaA9wKHGGO2heSbDFyOvT7swR7nLYk8Cmuk\ncjyNDbhMwgYm6mL36UfAOcaYgT7n3u3YWl+fYK8ridjavL9hvwfaG2PCNTcvSZmOLWPMGgK1jSeY\nyCPLR5rPeuy2vQnbbPUXAvtoF7bZ9+vAKcaYq0xgQKRoJeE/Uq3viLXGmD3GmCux17rx2G2S6F6r\nsPvvUgLNNWPh1a7tH2a6d48nJZS5CYE+NYswdlTqc7HNurNcut+Af2G/K5aHK5wxZh62RtlL2N8/\nSdjg+WSghzHmhTD5jDHmWuAs4D1s4DEOe21YgX2Ae4IxZp/WDnSC75sbE3mb+g7M4crdE/tbbDN2\nu6wGRmG3aYU0gzbGPAR0x/4eXYkNDgr2mJwInGqMuSvCLLzj7NUIaZRS1ZCE+a2ulFJKqSpERL7E\nBpivMcaMqeTiqGpCRBZhA4nnlyHgo1SFcf2nrcM+BOlqjPm6hCwHPNfc1AuWNTW2Swelyp1rLp6B\nDfQ3N8ZkVnKRlFLlSGsIKqWUUlWc6zvpJOxT/fIacVUppaqCa7DBwMUaDIyOMSYL2+VFEjCwkouj\n9m83YftFHanBQKX2PxoQVEoppaoAEblRRO4TkTZep+BiB6C5isAosxNd8zqllKr2ROQwwBupdUSk\ntKqYp7HNTgd7g34oVZ7cYCJ3YJuMP1nJxVFKVYD4yi6AUkoppQA4CNvH1zAgX0S2Yfsm9B7eLcJ2\nSK6UUtWaiHyEbcreFHuNW4gd6ENFyRiz3T0w6oz9/lhWyUVS+58W2BGVvzfGbK3swiilyp8GBJVS\nSqmqYTy2+VdPbMf4qdiBSpZgBxoZ5QZhUEqp6u4v7rUJO2jFHaUY5OOA5wa5ml7Z5VD7JzcQ2dDK\nLodSquLooCIHCBFZCLTGjkj4eyUXRymllFJKKaWUUmp/cAhQF1hpjDm2sgsTLQ0IHiBEJAuoX9nl\nUEoppZRSSimllNoPbTPGpFR2IaKlTYYPHDuB+vXr16dDhw6VXRZVxW3evBmAtLS0Si6Jqur0WFGx\n0ONFRUuPFRULPV5UtPRYUbHQ40VF67vvviM7Oxts3KXa0IDggeN3oFmHDh2YM2dOZZdFVXFTpkwB\n4LzzzqvkkqiqTo8VFQs9XlS09FhRsdDjRUVLjxUVCz1eVLSOOuoofvnlF6hm3bPFlZxEKaWUUkop\npZRSSim1v9CAoFJKKaWUUkoppZRSBxANCCqllFJKKaWUUkopdQDRgKBSSimllFJKKaWUUgcQDQgq\npZRSSimllFJKKXUA0YCgUkoppZRSSimllFIHEA0IKqWUUkoppZRSSil1AImv7AKoqmvnzp1s376d\n7Oxs8vLyMMZUdpHUPtK4cWMAli5dWsklqd5EhFq1apGcnExqaipxcfoMRimllFJKKaVU5dOAoCrG\nGMPGjRvJzMys7KKoSpKcnFzZRdgvGGPIyckhJyeHXbt20aJFCw0KKqWUUkoppZSqdBoQVMVs376d\nzMxMRISGDRuSnJxMzZo1NZBxAMnKygIgJSWlkktSvRUUFLBr1y4yMjLIzs4mMzOTtLS0yi6WUkop\npZRSSqkDnEZ4VDFbt24FoEmTJjRq1IjExEQNBipVCnFxcSQnJ9O0aVMAduzYUcklUkoppZRSSiml\nNCCofOTk5ABQr169Si6JUvuHOnXqALBnz55KLolSSimllFJKKaUBQeXDGzykRo0alVwSpfYPIgKg\nA/MopZRSSimllKoSNCColFIVzAsIKqWUUkoppZRSVYEGBJVSSimllFJKKaWUOoBoQFAppZRSSiml\nlFJKqQOIBgSVUkoppZRSSimllDqAaEBQqVJq1aoVIoKIMG3atLDpjjrqKESEOXPm7LvClUJubi7H\nHnssIsLTTz8dMe0bb7yBiNC8eXOysrIqtFzLli1DRDjssMMqdDlKKaWUUkoppdSBQgOCSpWDe++9\nl4KCgsouRpkkJCQwduxYatasydNPP83ixYt9061fv56///3vALzyyiukpKTsy2IqpZRSSimllFKq\njDQgqCqdMYaFf2xl4LjvOfyBGbS+ZxqHPzCDW8b9wKI1WRhjKruIEdWuXZvFixczbty4yi5KmR1z\nzDE8+OCD5ObmMnDgQHJzc4uluemmm9i6dSs33HADffr0qYRSKqWUUkoppZRSqiw0IKgqVW5+AbeP\nX8hlo79hxs8Z7M7NxwC7c/OZ/vN6Ln35a24fv5Dc/Kpb++72228H4KGHHmLv3r2VXJqyu+eee+jU\nqRM///wz//znP4tMe+ONN/jggw9o1aoVzzzzTCWVUCmllFJKKaWUUmWhAUFVaYwx/N/ERcxasoHd\nufkUhFQELDA2MDhryQb+b+KiKltT8MILL+SEE05g5cqVjBo1Kub8H3/8Meeeey5NmjShZs2apKen\nc+mllxZrsrt582bi4uJo2rRpsXmMHDmysD/DpUuXFpm2ZMkSRIT27dtHVZ4aNWrwwgsvkJiYyOOP\nP84PP/wAwLp16/j73/+OiPDaa6+RnJxcLO+OHTt4+OGHOeaYY6hTpw5169alY8eOPPXUU+zevbtY\n+hkzZiAi9OnTh507d3LvvffSrl07EhMT6dKlS4llzczMpHv37ogI/fr1Y8+ePVGto1JKKaWUUkop\nVVrGGH7Ytovrf17J7/GJlV2cUtGAoKo0i9Zk8cmSjeTkRq79l5NbwCdLNvLjn9v2Ucli98QTTwAw\nbNgwdu7cGXW+QYMG0adPH6ZPn06bNm3o27cv6enpjB8/nhNOOIGPPvqoMG1aWhrt27dnw4YNxYKF\nn376aeHfn3zyie+0Xr16RV2udu3aMWTIEPLy8rj66qvZs2dPYVPhW2+9lVNOOaVYnoyMDE444QSG\nDh3K2rVr6dOnD71792b58uXcfffd9OjRg23b/Pfhrl27OOmkk3j++edp164d5513Hi1btoxYxpUr\nV9KtWze++uorBg8ezIQJE6hVq1bU66iUUkoppZRSSsUqt8DwtyWruXDRcj7atI2q254xMg0Iqkrz\nypcr2ZOXH1XaPXn5vPLligouUemdcsopnHbaaWzcuDHqprSjRo1i5MiRHHnkkSxevJh58+YxceJE\nfvjhByZPnkxeXh6XX345W7duLczjBfWCA4D5+fl8/vnnHHHEEcTHx5dLQBBg4MCBnHTSSfz888+c\ncsopfPjhh7Rt27Yw+BnqxhtvZNmyZfTq1YuVK1fy7rvv8v7777N8+XKOP/54FixYUDgYSaivvvqK\nmjVrsmLFCj788EMmTJjAhAkTwpZtwYIFdO3ald9++40RI0YwfPhwRCSm9VNKKaWUUkoppWJhjOG2\npav5ePM2dhcUVNtgIEB8ZRdAVU+t7pm2T5dXYODDn9bz4U9lX+6qJ84qhxIV9/jjjzNr1iyeeeYZ\nBg4cSKNGjcKmzc/P55FHHgFg4sSJHHbYYUWm9+3bl5tuuonnn3+et956i9tuuw2wQb1nnnmGTz75\npDC4tmDBArZt28bAgQOZPXs2c+bMIT8/nxo1ahQGC+Pj4+nZs2dM6xMXF8eYMWNo37498+fPL/y/\ndu3axdL+9ttvfPDBB8THx/Pyyy9Tr169wmlpaWm89NJLdOzYkbfeeosnnniCJk2aFJvHiy++SFpa\nWonlmjZtGpdccgn5+flMmjSJCy64IKb1UkoppZRSSimlSmPh9mxmbt7O7tA+z6ohrSGoVDnp2LEj\n/fr1Y8eOHQwbNixi2kWLFrF+/XqOPPJIjjjiCN80XgBv/vz5hZ/16NGDhIQEvvjiC/Ly8oBADcDe\nvXvTu3dvtm/fzrfffgvA999/T1ZWFp07d6Zu3boxr1ObNm24+eabATj//PPp1q2bb7rPP/+8sHwH\nH3xwsenHHnssHTp0IC8vj6+++qrY9JYtW9KpU6cSy/PSSy9x3nnnkZiYyKeffqrBQKWUUkoppZRS\n+8yLazaRU1Cd6wUGaEBQqXL06KOPEh8fz6hRo1i9enXYdCtW2ObPv/zyS+FgIKGvfv36AbBp06bC\nfHXq1KFLly7s2LGDb775BrABwcTERE488UR69+4NBPoRLG1z4WBeIDFSQHHt2rUAtG7dOmyaNm3a\nFEkbrKT+AgGWL1/OzTffjDGGWbNmhQ1OKqWUUkoppZRSFeGTLdW3z8BQ2mRYlUp5NLu9ZdwPTP95\nfbHRhf3ECZx5dDrPXdaxzMutSIcccgjXX389o0aN4sEHH2Ts2LG+6fLzbd+JzZo1KwzihRPanLhX\nr158+eWXfPrpp3Tq1Il58+Zx0kknUatWLbp27Urt2rX55JNPeOCBB4rUHqxI3gjQkfrxizRKdFJS\nUonLaNasGW3atOGzzz5j0KBBTJs2zXekY6WUUkoppZRSqjztzMtn6qas/aKpsEcDgqrSXN+9NZ8t\n28ju3JIHFqkVX4PruxdviloVPfjgg7zxxhu89dZb3Hnnnb5pWrRoAUB6ejpjxoyJaf69e/dm6NCh\nfPLJJ5x44onk5OQUBvxq1qxJ9+7dmT17Nlu2bGHu3LmFtQorUvPmzYFAzUc/K1euBGxgrzQSExOZ\nNm0aF154IR999BG9e/dmxowZNGjQoFTzU0oppZRSSimlwjHG8PW2XYxfn8kHm7LIzt9f6gZa2mRY\nVZoOLVLofURjEhMiH4aJCXH0PqIx7ZvX30clK5v09HQGDRpEQUEB9913n2+aE044gYYNG7Jw4UJ+\n//33mObv9Qf49ddfM3XqVKBok+BevXqxd+9ennjiCXJycujevTsJCQmlX6EoeP0dfvHFF6xatarY\n9B9//JFFixYRHx/PSSedVOrlJCYm8v7773PhhRfy7bffcuqpp7J58+ZSz08ppZRSSimllAq2Lmcv\nI1Zl0PWbpZy/8HcmZGTud8FA0ICgqkQiwvB+HfjrEU1ISqhBXEhr0ziBpIQa/PWIJgzv1yFic9Sq\n5u677yY1NZUPPvigsGZcsISEBB544AHy8/Pp27dv4SAgwXbt2sXbb7/N0qVLi3weHx9Pjx49yM3N\n5eWXX6ZBgwZ07BhoSu3VFnzuueeK/F+R2rZty9lnn01eXh433XQTO3bsKJy2ZcsWbrrpJowxXHHF\nFb4jDMciISGBCRMmcMUVV7Bo0SJ69uxJRkZGWVdBKaWUUkoppdQBKie/gPc3bOXSH5fTaf4SnliZ\nwarde4ukaVc7keuapZEUGryoprTJsKpUCTXiGNn/WH78cxujv1jBZ8s2kpOXT2J8DXod3pgbuh9M\n+xYplV3MmNWvX5977rmHu+66i+zsbN80gwYNYvXq1fz73/+mc+fOHHPMMbRp04aCggLWrFnDsmXL\nyM7OZvr06Rx++OFF8vbu3ZuPPvqInJwczjzzTOLiArH9Dh06kJaWVlhzriwDisRi9OjRnHLKKcyc\nOZODDz6Ynj17UlBQwGeffca2bdvo1KkTI0aMKJdl1ahRg7Fjx5KUlMTo0aPp0aMHn376aWFTbKWU\nUkoppZRSKhJjDD/t3M349ZlM3rCVrLzi3ZnVi4+jb+MG9E9P5djk2gBsyc3j483bqn1/ghoQVJVO\nROjQIoXnL6/aA4bE6rbbbmPkyJH8+eefYdMMHz6cvn378uKLLzJ37lymTZtGUlIS6enpnHPOOZx7\n7rl07969WL7gIF9oDUAR4ZRTTmHSpEmkpaXRvn378lupCJo2bco333zD8OHDeffdd/noo48QEdq1\na0f//v25/fbboxo8JFpxcXG8/PLL1K5dm2effbYwKHjwwdWjr0mllFJKKaWUUvve5r15vLchk/Hr\nM1myK6fYdAG6N6hL//SGnJFWn6QaRRvX/ufwlty2dDUzN28np6D6NiXWgKBSpeTXV16wxMRE1qxZ\nU+J8evToQY8ePWJa9jHHHBNx1N6JEyfGNL9Ihg4dytChQ6NKW69evZjS9+nTJ+J6gB1lOVKaESNG\nlFvNQ6WUUkoppZRS+5+8AsNnmduZkJHJzM3byfW5xzwosSaXNE2lX3oqLRJrhp1XQpzw4hEtWbgj\nmxf/2MSbFVnwCqQBQaWUUkoppZRSSim13/ltVw7jMzKZlJHJxr15xaYnxQlnNUqhf3oq3VLqEhfl\n2AUiQsd6dRh9VB3m5+XwS3kXfB/QgKBSSimllFJKKaWU2i/syMtnysYsxq/fwoLt/n36H1evNv3T\nG3Ju4xTqxdfYxyWsGjQgqJRSSimllFJKKaWqrQJjmJe1k/HrM5m2Kct3wI/GNeO5uGkqlzRNpV2d\nxEooZdWiAUGllFJKKaWUUkopVe2sydnLxPWZTMjI5I+cvcWmxwucnlafS5qmcmpqPeLjomsSfCDQ\ngKBSSimllFJKKaWUqhZ25xcwffM2xq/fwpdbd+I3BOXhdRK5ND2VC5qkklZTQ19+dKsopZRSSiml\nlFJKqSrLGMPCHdmMX5/J+xu3sj2voFia+vE1uKBJA/qnp3JM3SQkygFCDlQaEFRKKaWUUkoppZRS\nVc6mvbm8k7GV8RmZ/Lorp9h0AU5OTeaSpqn0SatPYo24fV/IakoDgkoppZRSSimllFKqSsgtMHy6\nZTvjM7bwyZbt5Pm0CW6VVJP+TVO5uGkqzRJr7vtC7gc0IKiUUkoppZRSSimlKtWyXbsZvz6TdzK2\nsjk3r9j0pLg4zm2cQv/0VLrUr6NNgstIA4JKKaWUUkoppZRSap/blpvH+xuzGL8+k4U7sn3TdK5f\nh0vSUzm3UQp142vs4xLuvzQgqJRSSimllFJKKaX2iQJj+GrrTsZnZPLRpixyCoq3CW5aM4F+TRtw\nSXoqbWonVkIp938aEFRKKaWUUkoppZRSFWr17j1MyMhkYkYmf+bkFpteU4TT0+rTPz2Vk1OTqaFN\ngiuUBgSVUkoppZRSSimlVLnLzi9g2ibbJHhu1k7fNEfXTeKS9FQuaNKA1AQNU+0ruqWVUkoppZRS\nSimlVLkwxvD99mzGr8/k/Y1b2ZlfUCxNakINLmjSgP5NUzkquXYllFLFVXYBlKquWrVqhYgwZ86c\nyi5KqVx22WWICCLCokWLKrs4ZbZq1SpEhFatWlV2UZRSSimllFLqgLNhTy7Prd5Aj2+XcfYPv/HW\n+i1FgoFxQK/Ueow+shULux3Jo22bazCwEmkNQaUOQFlZWUyePLnw/9dee42RI0dWYomUUkoppZRS\nSlU3ewsKmLVlO+PXZ/JZ5nbyi48PQpukWvRPT+Wipg1Ir1Vz3xdS+dKAoKp8xsDa72HeSPhtJuTm\nQEIitD0dut0OzTqCdiZarv773/+Sk5NDs2bNWLt2LePGjePpp5+mVq1alV00pZRSSimllFJV3JKd\nuxm/PpN3NmSSmZtfbHqdGnGc1ziF/k1TOb5+HUTv6ascDQiqypWfC5Nvhl8/grwcMK46ce5uWDrV\nBggPPRPOHwU1Eiq3rPuR1157DYBhw4bxxBNPsGzZMqZMmUK/fv0quWRKKaWUUkoppaqirbl5TN6w\nlfEZmfy0Y7dvmq4pdejftCFnN65PnRo19nEJVSy0D0FVeYxxwcBpkJsdCAYWTi+wny+bZtMZn7rH\n1cyuXbsYNmwY7du3p27dutSpU4cOHTrw2GOPkZ2d7Ztn5syZnHXWWTRu3JiEhARSU1M57LDDuPba\na/nhhx9iLsPixYv5/vvvqVu3LhdddBHXXHMNEAgS+jn55JML+0v8/vvvOffcc2nYsCFJSUm0b9+e\nV199NWzejRs3MnDgQJo3b05iYiKHHHIIQ4YMYffu3UXmG8oYw/jx4znttNNIS0ujVq1aHHTQQdxw\nww2sWrUq5vXetWsXTz31FMcffzz16tUjKSmJI488kqFDh7JzZ/HRrvLz8xk1ahTdunWjfv361KxZ\nkyZNmtCxY0f+8Y9/sGnTppjLoJRSSimllFLVSb4xzN6ynZt+WUX7ub9w329riwUDm9VKYHDLJnzd\n5XAmH9uWS9JTNRhYDez3NQRF5FCgD3A8cBzQDhDgYmPMO2WY72XA34BjgBrAMuB14EVjQiNbICJz\ngJ7u3/HGmEsjzHsYcJ/7d7UxplVpy1mlrf3e1gzM9X+yUChvt0239gdo3mnflK0CbN68mVNPPZXF\nixfToEED/vrXvyIizJ49myFDhjBx4kQ+++wzUlNTC/OMGTOGa665hri4ODp37kzLli3ZuXMna9as\nYcyYMbRr146OHTvGVA4veHfxxRdTp04drrzySu677z5mzZrFmjVraNGiRdi8M2bMYPjw4Rx66KGc\ndtpp/PHHH8ybN4/rr7+erKws/vGPfxRJv27dOk488URWrVpF48aNOeecc9izZw8jR46MOBhLbm4u\n/fv357333iMpKYnjjjuOJk2a8PPPP/PKK6/w7rvvMnPmTI477rio1vnPP//k9NNPZ8mSJTRq1Iiu\nXbuSmJjId999x8MPP8zkyZOZM2cODRo0KMxz3XXXMXbsWJKSkjjppJNIS0tj8+bNLF++nOHDh3Px\nxRfTqFGjqJavlFJKKaWUUtXJyuw9TMjIZGJGJuv25BabXitOOCOtPv3TU+neIJka2iS42tnvA4LY\noN2g8pyhiDwPDARygE+BXKAX8BzQS0QuNsYUb0Qf0FdEUowxWT7zjgOuLM/yVlnz/mObCUcjLwfm\nPwcXv16xZapAAwcOZPHixXTv3p2pU6eSkpICwNatWzn77LOZN28et9xyC2+//XZhnkceeQSAL7/8\nkm7duhWZ359//sn27dtjKsPevXsZN24cQGHNwPT0dPr06cO0adMYO3Ys999/f9j8Tz75JK+++irX\nXntt4WdvvfUWV155JY888gh/+9vfqF07MErUwIEDWbVqFWeccQaTJk2iTp06AGRkZNCrVy+WLFni\nu5wHHniA9957jx49ejBu3DiaN29eOO25557jtttuo3///ixbtoz4+MiXMWMM/fr1Y8mSJdx66608\n+eSThWXcvXs3N954I2+99RaDBw9mzJgxAKxevZqxY8fSokULvvvuO5o0aVJknosWLeIvf/lLxOUq\npZRSSimlVHWyKy+fDzZlMX59Jl9v2+Wbpn1yEv3TG3J+4xRSEg6EkNL+60DYez8DTwMLgO+BVwnU\n1IuZiFyIDQZmAD2MMb+5z5sAs4HzgVuBZ8PMYgG2pmJ/YJTP9N5AC+A7bK3Gqmlo/X27PFMAv7xn\nX2U1dFvZ5xGj1atX88477xAXF8fLL79cGAwEaNCgAaNHj+boo49m4sSJPPXUU4W19DZs2EBKSkqx\nYCBQJEgWralTp7J582YOOeQQunfvXvj5tddey7Rp03j99dcZMmRI2PwXXnhhkWAgwBVXXMFjjz3G\n0qVLWbBgAT169Chc56lTpxIfH88LL7xQGAwEaNq0Kf/6178488wziy0jMzOTkSNHUrduXSZNmkTj\nxo2LTL/11luZMWMG06ZNY/r06ZxzzjkR13nGjBnMnz+fLl268OyzzxIXF+gpISkpiVGjRjFz5kzG\njRvHv//9bxo0aMDGjRsB6NixY7FgIECHDh0iLlMppZRSSimlqgNjDN9u28X4jEymbsxiV36xBo80\nTIjnoiYN6J+eyuF1kyqhlKoi7Pd9CBpjXjHG3GWMmWiMWV4Os7zXvd/tBQPdcjZgayMC3ONq+vl5\nE8gHBoSZ7n0+pkylVFXKl19+iTGGLl26cNhhhxWbfsQRR3DCCSdQUFDAF198Ufj5CSecQFZWFldd\ndRULFy7ElLEfRa+fwAEDBhT5/JxzziEtLY0VK1bw+eefh81/9tln+37urdO6desKP/viiy8wxtC1\na1datWpVLM8ZZ5xRpImuZ/bs2ezevZuePXsWCwZ6eva0Mf358+eHLavno48+AmwwMzgY6KlTpw7H\nHXcceXl5fPfdd4Xrk5yczLRp03jsscdYvXp1ictRSimllFJKqepi/Z69jFy9gRO/WcZ5C3/n7fWZ\nRYKBNQROa1iP145qxcJuR/Bw22YaDNzP7PcBwfIkIs2BTsBeYFLodGPM58BaoCnQJcxs1gEzgc4i\ncnjI/OtjaxguAb4tv5KryrZ27VoAWrduHTZNmzZtiqQFeOGFF2jdujVvvvkmHTt2pEGDBpx22mk8\n/fTTZGRkxFSGdevWMXPmTOLi4rjqqquKTEtISODyyy8HIg8uctBBB/l+Xq9ePQBycgJNwL31aNmy\nZa4lBQgAACAASURBVEzzW7FiBQDTpk1DRHxfd911F0BUA3t487vzzjvDzs8LGnrzS05O5rXXXiMp\nKYkhQ4bQqlUrmjdvzsUXX8yYMWOKrKdSSimllFJKVQd7CgqYujGLy35cTqd5S3hsxXpW7N5TJE3b\n2rV4oM1fWNj1SN445mDObJRCTZ+KFar6OxCaDJenY937L8aYcCNhfAc0c2nnhUnzOnAGtjbg3UGf\nXwokuulVW3k0u514NSydWnx0YT8SB0f0rbZ9CHo1+yRCR6t+tf8OP/xwfv31Vz7++GM+++wz5s6d\ny+zZs5k1axZDhw7l3XffpU+fPlGVYcyYMeTn51OrVi0uvbT4mDZbtmwB4N133+XRRx8tDPIF86th\nV5JI6+w3v/x82/3moYceSpcu4eLqVufOnUtcvje/nj17+tZUDBYcvLzooovo3bs3U6ZM4YsvvmDu\n3Lm88847vPPOOwwdOpQvv/wy4gAsSimllFJKKVUVLN6Rzfj1mby3YStb84oPd5BcI46+TRrQv2kq\nHevVjngPp/YfGhCMjVe9K1L7wT9C0vqZCmQCV4jIfUEDkAzANid+C4i9g7jqpttt8NtMyM0uOW18\nInS9teLLVEG8/v682mp+Vq5cCUCzZs2KfJ6QkMDZZ59d2Fx369atPPzwwzz77LNcd911RWoURuIN\nmLFnzx7mzp0bNl12djbvvfdesWbFsfIG3YjU3NZvmhdkO/roowvLXBbe/C6++GJuueWWmPKmpKRw\n9dVXc/XVVwOwfPlybrjhBmbPns3dd9/Nf//73zKXTymllFJKKaXKW2ZuHu9t2Mr49Zn8vNO/PtNJ\nKXXpn57KmY1SqF1DawEeaDQgGJu67t1/uB1rp3tPDpfAGLNHRN4GbgFOA6aLyGFAZ+BDY0yGa54c\nkYgMIHxfhKE6AGzevJkpU6ZETNi4cWOSk5PJyio2CHL5qtOG2q17k7BiJhJhtGETn0hu695k1zkY\nKrpMMSgosDUbd+7cWeK2OuaYYxARvv76axYsWMAhhxxSZPqvv/7KN998Q1xcHO3bt484PxFhyJAh\n/Oc//2HdunX8/vvvpKWlRVz+3Llz+e2330hOTmbZsmVFRgIO9sorr3DnnXcybtw4BgwYUFiOvLy8\niOu6d+9ewAYTvent27dHRJg3bx4//fRTsebBn376KZmZmcXme/zxx5OQkMCsWbNYvXo19etHN4CN\nN+JyQUFBkTL26NGDV155hbfffruwWXRpNWzYkEGDBjF79mwWLlwY0zmSn5/Pjh07Sjz/qqv9db1U\nxdDjRUVLjxUVCz1eVLT0WFGxqE7HSz6wJD6ReQl1+TG+Nvk+Nf0aFuTRNXcnXffuIm17HvwBs/Z9\nUVUVoCHg2HhnU9lGdrDGuPcB7v0a9x5Lm9hW2BGTo3nt42GBoyBC9unDyT34NEx8EiZkHBYjcZj4\nJHIPPo3s04dDNa62fNBBB3HuuedSUFDA4MGD2bYt0OR627ZtDB48mIKCAvr27VtYmzA7O5vnn3+e\nzZs3F5vfzJkzKSgoIDk5OaqA2bhx4wA7eEi4YCDABRdcQEJCAgsWLGDZsmWxrmYRLVu25LTTTiMv\nL48777yT7OxATdCNGzfywAMP+OZr3Lgx119/Pdu2bePSSy/lf//7X7E0WVlZvPHGG4WjAUdy1lln\n0aFDB+bOncvgwYPZunVrsTSrVq1i9OjRhf//9NNPvPfee+zeXfxJ2owZM4DSjfKslFJKKaWUUuVt\nQ1w8k2ulcF/dZjxXuwk/JNQpEgxMMAWcsHcnf9+1gUd3ruWcPdtIM3mVWGJVFWgNwdjscO91I6Tx\npu2IkAZjzAIRWQycJyKNgCuBLcCHMZRnFRB+SNiiOgD109LSOO+88yImXLp0KWCbS+4Tl74Ba3+A\neSNtE+K83RCfhLTrA91upWazTtTcNyWJidf/3V133eXb355n8uTJpKen88orr7B8+XK++uorOnbs\nyMknnwzYUXW3bt1K+/btGT16dJHtfv/99/PQQw9x9NFH07ZtW+Li4li+fDkLFiwA4KmnnqJRo0YR\ny7lz506mTp0KwHXXXRdxv6akpHDmmWcyZcoUxo0bx3/+8x8A4uPtpaJu3bq++WvWtHuodu3aRaa/\n8sornHjiicycOZOOHTvSo0cP9uzZw+zZsznyyCPp0qULX3/9NampqUXyPfvss2zZsoWJEyfSrVs3\nOnToQOvWrcnJyWHNmjUsXbqUvXv3snTp0sJ8Xm29uLi4YmX84IMPOPPMMxkzZgzvvvsu7du3p3nz\n5mzevJk//viD//3vfzRp0oQ777wTgMzMTK677jpq165Nx44dadGiBXv37mXhwoWsWLGC5ORkHn/8\n8ZjOkfXr15OSkkLXrl2jzlMdeE9MS7quKAV6vKjo6bGiYqHHi4qWHisqFlX9eNmZl8/UjVmMz8jk\n223+jRg71qtN/6apnNc4hfoJGv6pKEOGDKnsIpSKHhGxWeXeww+bCt4oA6sipPGMAZ4BXgPSgZHG\nmL3RFsYYM4ZATcOIRGQOtqZg1SMCzTtBv7GVXZJS8QKo4ezZY0dtSktLY/78+YwYMYKJEycyffp0\nANq2bcsdd9zBoEGDqFOnTmG+unXr8uKLLzJnzhwWLVrExx9/TG5uLs2aNeOyyy7j9ttvj2pQjQkT\nJrBr1y6aNWtWGISM5Morr2TKlClMmDCB4cOHk5CQUGKecJo3b863337LQw89xNSpU5kyZQrNmjXj\nb//P3n3HdVX3/x9/nA8bBAFRQRkOVFy5MsMuB7nq0uwyS00bjqvM0dfW1WWX2VTblpojs6L85bay\nMkcOXLnTNEUNB6IoioCibD7n9wf6UQIUVPwoPu+3Wzfjfc77nNfn+AHkyXsMGsTrr7/OHXfcAVBg\nyrOTkxOzZ8+mT58+fPnll2zatIkdO3bg6elJQEAAvXv35sEHH7TtzFzcOr744gvmzJnDzp072bhx\nIxUqVKBq1aq89NJLdOvWzXb+3XffzTvvvMOqVavYs2cPW7duxdnZmaCgIF588UWeffbZy+6eLCIi\nIiIicr2Zpsn6lHPMOn6Kn06cJt1acIPOis6OPFzZh14BFajj4WqHKuVWYRS2s2lZdkkw9ohpmvNK\n2DeIvE1DsgDvwnYaNgwjjrwNQf5hmua6S9oL3NcwjErAUS4Gs01N09x2/tid5O1YHGuaZrWS1FlE\n7VFAmzZt2hAVFXXZcy8EXHXr1r3W28ot6sJou9IcJXro0CFCQ0Px8PAgOTn5qnYwvpWU1c+rm/03\np3Jz0ftFikvvFSkJvV+kuPRekZK4md4vRzOymHM8idnHkziUXnAMkaMBHSqUp1eAL/f6euFkuXWX\n27oVNWjQgF27dgGsMk2zrZ3LKTaNECwB0zTjDMP4HWgKPAJ8c+lxwzDakBcGHgfWF+N6JwzDmEve\nxiLRF8JAkbLCNE22bt3KnXfema89Li6Oxx9/nNzcXJ544okyHwaKiIiIiIiUREaulcWJp5l1LIlV\nyamFbmRQx8OVR/196e7vQ0Xnq5/ZJbcnBYKFMAzjHaAb8L1pmq/87fA7wFzgPcMwfjNNM+Z8n0rA\npPPnvGuaZsGxu4UwTbP3dSpb5KaTm5tL8+bNCQ4OJiwsDB8fH+Li4vj999/JyMigQYMGjBo1yt5l\nioiIiIiI2J1pmvyRms6s40l8n5DM6ZzcAud4OVroVilvSnBjTzeMW3jzTbGvMh8IGobRlItBHUC9\n83+OMQzjpQuNpmnefck5AUCd83/mY5rmPMMwJgODgJ2GYSwDsoF2gBfwA/DpdX0RIrcoBwcHRowY\nwbJly9i2bRspKSm4uLhQr149HnroIYYNG0a5cpfbo0dERERERKRsS8zKYX5CErOOJRF9LqPAcQNo\n7eNJrwBf7vMrj5uDZljJtSvzgSB5IV1hOy/UutoLmqY52DCMtcAQ8tYFdAD2kLc5yOTijg4UKesM\nw2DUqFEaBSgiIiIiInKJHKvJiqQzzDqWxNJTp8kpZE5wiKszPQN86eHvS6Cr840vUsq0Mh8ImqYZ\nRV6gXpI+fYG+VzhnBjCjBNdsW8IatlDCukVERERERETk5rXvXAazjiUxNyGJk1k5BY67WSx0qVSe\nXv6+hHuXw6IpwVJKynwgKCIiIiIiIiJiL2dycllwIplZx5LYeiat0HOae3nQK8CXrpW88XR0uMEV\nyu1IgaCIiIiIiIiIyHVkNU1+SznLrGNJLDyZQrq14JzgSs6O9PD3pae/L7U8XO1QpdzOFAiKiIiI\niIiIiFwHcRlZzD6WxOzjScRlZBU47mQYdPTzope/LxG+XjhaNCVY7EOBoIiIiIiIiIjIVUrPtfLL\nyRRmHU9ibfJZCtkfhHoerjwaUIGHKvtQwVlRjNif3oUiIiIiIiIictszTZNtZ9KYFHeCpZ5BZGHw\n3Ko/aF+hPIOCK9LE0x3j/CYfpmmyLTWNWceS+OFEMmdyrAWu5+3owEOVfegV4EvDcm62viI3AwWC\nIiIiIiIiInJby7aaPBsdy5LEM2RarVgNCwDpVpOFJ1NYfuoMHf28eK1mFX44kcKsY0nsS8socB0D\naOvrSa8AXzpVKI+rg+UGvxKR4lEgKCIiIiIiIiK3LdO8EAaeLnTzDyuQZrXy44kUfjiRUug1qrs5\n08u/Ao/4+1DF1bmUKxa5dgoERUREREREROS2te1MGksTzxQaBl7q75OC3R0sdK3oTa8AX1qU99CU\nYLmlKBAUERERERERkdvW5LiTZFgLrgFYFF9HB0aGVqFrRW88HB1KsTKR0qPJ7CLXwS+//MLjjz9O\naGgo5cqVw9XVlcDAQDp37syUKVNITU21ndu3b18MwyAyMrJE93jjjTcwDIM33njj+hYvIiIiIiJy\nG1t26nSB0X+Xk241eTSggsJAuaVphKDINThx4gQ9evRg1apVANStW5eOHTvi7OzMkSNHWLZsGb/8\n8gsjR45ky5YthISE2LliERERERERuVTGFaYKFzy/JPGhyM1JgaDYnWma7EzcSeSuSNYcWUNmbiYu\nDi60DmxN3/p9aeDX4KZciyElJYV77rmHmJgYwsPDmTJlCnfccUe+c1JTU5k8eTKjR48mOTn5mgLB\noUOH0qtXL/z8/K61dBEREREREQGspomjYZBtFj8UdLVosqXc+hQIil1lW7MZsWYEK+NWkpWbhfX8\nQO2M3AyWxS5jzdE1tA1sy+hWo3GyONm52vyGDh1KTEwMd911FytWrMDV1bXAOZ6enrz88ss89NBD\neHh4XNP9/Pz8FAaKiIiIiIhcJ8cys3g+Oq5EYaAF6FDBq/SKErlBFGuL3ZimaQsDM3IzbGHgBVas\npOekszJuJSPWjMAswRfp0rZ//35mzpwJwJQpUwoNAy8VGhpKQEBAgfaYmBh69+5N5cqVcXFxISws\njPfeew9rIUPQr7SGYHR0NE8//TShoaG4ubnh4+PDHXfcwUsvvURsbGy+c+fPn0///v2pX78+3t7e\nuLq6EhoaypAhQ4iLiyvydZw4cYLBgwcTGBho6zNixAjS09Np27YthmEQFRVVoN+5c+cYPXo0jRo1\noly5cnh4eNC4cWPGjBlDWlraZZ+diIiIiIjI9fbjiRQiNu0lKjn1yidfwsVi8ExwxVKqSuTGUSAo\ndrMzcSdRR6LIyM247HkZuRlEHYniz8Q/b1BlV/bzzz9jtVpp2LAhTZo0uaprbN++nWbNmrFx40Yi\nIiJo2bIl+/fvZ/jw4QwbNqxE1/rmm29o3Lgxn3/+OaZp0qVLF9q0aYPVauWjjz5i5cqV+c7v2bMn\nc+bMwcPDg/bt29OhQwcyMzOZNGkSTZs2JSYmpsA94uPjadGiBZMnTyY7O5sHHniAevXqMX78eNq3\nb092dnahtSUmJhIeHs6rr75KXFwcHTp0oFOnTsTGxjJixAhatmxJUlJSiV6viIiIiIjI1TiTk8vQ\n3bE8vesQKTm5tvZQNxdcLZdfqsrNYtDJrzxNPN1Lu0yRUqcpw2I3X+/6msyczGKdm5mTyde7v+bD\nNh+WclXFs3XrVgCaN29+1dcYN24cr7/+Oq+99hqW82tQrF69moiICCZNmsTLL79MUFDQFa+zefNm\nBgwYgGmaTJs2jf79++dbczE6OrpAnxkzZtClSxfc3S9+I8vJyeHNN99k1KhRDB8+nHnz5uXrM3jw\nYA4dOsT999/P3LlzbVOgjx8/Trt27di9e3eh9Q0ePJidO3fSqlUrfvzxR7y9vQFITk6mS5cu/Pbb\nbwwZMsQ24lJERERERKQ0/JZ8lmejYzmaeXEwQ1UXJybUDaF5eQ+ejY5laeIZMqz5569ZyBsZ2Mmv\nPBPqhtyUa9yLlJQCQbkqDb9ueEPvZ8XKkkNLWHJoyTVfa+eTO6/5GidPngSgUqVKV32N5s2b8/rr\nr+f7ZtK6dWs6derEokWLWLlyJU888cQVrzN69GhycnL473//y4ABAwocr1u3boG2Hj16FGhzdHTk\n7bff5ssvv2TlypWkpqbawrvY2Fh+/PFHHB0dmTRpUr71EP39/fnwww/55z//WeCasbGxzJs3D4vF\nwtSpU23XA/Dx8eHzzz+nYcOGzJkzh/fff79YAaiIiIiIiEhJZFqtvHvgGFPiTnLpQlQPV/ZhTO1A\nvBwdAJhcL4RtqWlMPnySJSeSyMbA1cGBDhW8GBRciSZeGhkoZYcCQRE7+ec//1nob5bCwsJYtGgR\n8fHxV7xGbm4uy5YtA+Df//53ie6/b98+Fi9eTExMDGfPnrWtW5iTk4PVauXgwYO2gG716tWYpkl4\neDjVqlUrcK37778fHx8fkpOT87WvWbPG1i8sLKxAv3r16nHXXXexYcMGVq9eTZ8+fUr0GkRERERE\nRC4n+mw6g3fHEn3u4lJVPo4OvFcniK6VvPOdaxgGTb08+LyBBwsW/AHAgw8+eEPrFblRFAiKXIWK\nFfMWkT1x4sRVXyM4OLjQdi+vvB2rMjIuv7Yi5K3Pd+7cORwdHQkNDS3WfXNychg8eDDTpk277EYt\nqakXF9c9evQoACEhIUWeHxwcXCAQvNCvevXqRfarWbMmGzZssJ0rIiIiIiJyraymyWdxJ3nnwDGy\nLvm5p62PJ5/UDcbfxcmO1YnYnwJBuSrXY9rti1Evsix2WYHdhQtjwUKHah1umjUEmzVrxvTp09m8\nefNVX+PCuoE32rhx4/j888+pUqUKY8eOpWXLllSqVAkXFxcAWrZsyfr16wsNCy+3VkZhr+fCNS7X\n72baPVpERERERG59RzKy+L/ow/yWctbW5moxGFmzCv2r+mkNQBG0y7DY0ZP1n8TF0aVY5zo7OPNk\nvSdLuaLi69y5MxaLhZ07d7Jt2za71eHn54e7uzs5OTns37+/WH3mzp0LwGeffUbPnj0JCgqyhYFA\noTsMV6lSBchbE7AohR0LDAwE4MCBA0X2O3jwIABVq1YtRvUiIiIiIiKFM02T+ceTuHfznnxh4B2e\nbvx6Zx0GBFZUGChyngJBsZuGfg1pG9gWVwfXy57n6uBKRFAEDfwa3KDKriw0NJSePXsCMGjQIDIz\nL79b8v79+zl27Nh1r8PBwYH27dsDMG3atGL1SUpKAih0A49ff/3VtmHKpVq1aoVhGPz222+FBn9L\nliyxXbewfhs2bGDfvn0FjkdHR7Nx40YsFgutW7cuVv0iIiIiIiJ/l5ydw8DdsQyJPsyZnLxZaBbg\nuZDK/Ny0FrU8Lv9zp8jtRoGg2I1hGIxuNZqIoAjcHN2w/O3taMFiCwNHtxp90/0m59NPP6VGjRps\n3LiRe++9l507C06jPnfuHGPHjqVZs2YkJCSUSh0jRozAwcGBDz/8kMjIyALH9+zZw549e2wfX9jc\nY/LkybaNRCAvtHzmmWcKvUf16tXp3LkzOTk5DBkyhLS0NNuxhIQEXnrppUL7hYSE0L17d6xWKwMH\nDuT06dO2YykpKQwcOBCr1UqPHj20w7CIiIiIiFyVVUmpRGzay48nUmxtIa7OLGhai+E1AnC203JN\nIjczrSEoduVkceK91u/xZ+KfRO6KZM3RNWTkZODq6ErrwNb0rd/3phoZeClfX1/Wrl1Ljx49WLt2\nLXfccQf16tUjLCwMZ2dnjh49yqZNm8jMzKRy5cr4+vqWSh133XUXU6dOZeDAgfTr149Ro0bRrFkz\nMjMz2b9/P3/++SdfffWVLQh85ZVXWLx4MZ999hkrV66kSZMmJCUlsWrVKsLDw/H39+e3334rcJ/J\nkyezY8cOFi5cSI0aNWjdujWZmZmsXLmS+vXrc/fdd7NhwwacnZ0L9NuzZw9RUVHUqFGDtm3bArBy\n5UqSk5Np1KgREydOLJVnIyIiIiIiZVd6rpXRB+KZdiQxX3ufAF/eDK1KOUcHO1UmcvNTTC52ZxgG\nDSs25KO2H7GpzyZ2PLmDTX028WGbD2/aMPCCgIAA1qxZw08//UTv3r1JT09n8eLFfPfddxw4cID2\n7dszdepU9u/fX+SuwtdD//79+f333+nbty/Z2dn88MMPrF69GgcHB/7zn/9w77332s4NDw9n06ZN\ndO7cmdOnT7NgwQKOHDnCiBEjWLJkCU5Ohe+2FRgYyKZNmxg4cCAWi4UFCxawc+dOBg0axPLly21T\njf38/PL18/PzY/369bz99ttUrVqVRYsWsWjRIoKCghg9ejTr1q0rtbBURERERETKph2paXTcsjdf\nGFjByZHIBtX5KCxYYaDIFRja4fP2YBhGFNCmTZs2REVFXfbc6OhoAOrWrVvqdcnNKSUlb6i9t7d3\nsc4/dOgQoaGheHh4kJycbLcdlG9mZfXzasGCBQA8+OCDdq5EbgV6v0hx6b0iJaH3ixSX3itlQ65p\nMvHwCd4/eIycS+KMDhW8GBsWREXnwgc4lJTeL1JcDRo0YNeuXQCrTNNsa+dyik0/tYtIsZimyZYt\nWwq0x8XF8fjjj5Obm8sTTzyhMFBEREREREpFbHom3bbFMObAxTDQzWLhgzqBfNOw+nULA0VuB1pD\nUESKJTc3l+bNmxMcHExYWBg+Pj7ExcXx+++/k5GRQYMGDRg1apS9yxQRERERkTLGNE1mHU/i1b+O\nci734saITb3cmVg3hOruLnasTuTWpEBQRIrFwcGBESNGsGzZMrZt20ZKSgouLi7Uq1ePhx56iGHD\nhlGuXDl7lykiIiIiImVIYlYOL++N45fE07Y2BwNerObP/wVXxtFi2LE6kVuXAkERKRbDMBg1apRG\nAYqIiIiIyA2x7NQZnt9zmJNZOba2mm4ufFovhCZe7nasTOTWp0BQRERERERERG4a53JzeTMmnm/i\nT+Vr71vVj9dqVsHdQeuWi1wrBYIiIiIiIiIiclP4/cw5hu4+zIH0TFtbJWdHPg4Lpl0FLztWJlK2\nKBAUEREREREREbvKsZp8EpvAx7HHyTUvtneuWJ73awdRwVnxhcj1pM8oEREREREREbGbA2mZDNkd\ny7bUNFtbOQcLo2sF0sPfB8PQxiEi15sCQRERERERERG54UzTZHr8KV6PiSfdarW1tyjvwfi6wYS4\nudixOpGyTYGgiIiIiIiIiNxQJzKzeWFvHMtOnbG1ORkGL1f3Z3BwJRw0KlCkVCkQFBEREREREZEb\nZtHJFF7cG0dSdq6trba7KxPrBdPQ092OlYncPhQIioiIiIiIiEipO5uTy8iYo8w8lpSv/enAivyv\nRgCuDhY7VSZy+1EgKCIiIiIiIiKlalPKWYZGH+ZwRpatLcDFiXFhwbT29bRjZSK3JwWCIiIiIiIi\nIlIqsqxWPjqUwITYBKyXtD9YyZt3awfi46RYQsQeNB5X5CpVq1YNwzDy/efq6kr16tV54okn2L59\ne77z27Zti2EYREVFleg+ffv2xTAMIiMj87VHRkZiGAZ9+/a9thdSTFdbf2EOHTqEYRhUq1btmq91\nwYW/g5K68Pd46NCh61aLiIiIiIjAvnMZdNn6F+MuCQO9HC1MqhfCZ/WrKQwUsSN99olco06dOuHv\n7w9AUlISmzdvZvr06cycOZPp06fTq1cvO1coIiIiIiJy41hNky+PJjJqfzwZVtPWfo93OcbXDaaq\nq7MdqxMRUCAoNwHTNMnYsYNTX37F2VWrMDMzMVxcKNe2LRX698O1YcOrGvl1owwfPpy2bdvaPk5P\nT+epp57i22+/5emnn6Zjx474+vpe9fXfeecdhg8fTkBAwHWoVv5u+fLlZGdnU7VqVXuXIiIiIiJy\nyzuWmcVz0XGsSk61tblYDP5XI4CnAitiuYl/thO5nSgQFLsys7OJHz6c1BUrMTMzwZo3kNzMyCB1\n6VLOrlqF570RVHn3XQwnJztXWzxubm5MnjyZH374gdTUVJYsWcKjjz561dcLCAhQGFiKatasae8S\nRERERETKhAUnkvnv3iOk5OTa2up5uDKxXgh1y7nZsTIR+TutISh2Y5pmXhi4fAVmerotDLSxWjHT\n00ldvoL44cMxTbPwC92EPD09qV27NgCxsbEFjm/dupWuXbtSoUIF3NzcaNSoEV988UWh1ypqDcHL\nmT9/Pv3796d+/fp4e3vj6upKaGgoQ4YMIS4ursh+iYmJDB06lPr161O5cmVq1KjBK6+8Qlpa2mXv\nZ5oms2bNomPHjvj5+eHi4kJwcDBPPfVUidfmu3QtwKlTp9KkSRPc3d2pUKECDz30EH/++ecVrzF7\n9mzCw8MpV64cnp6etGvXjrVr1xZ6blFrCMbGxvLOO+8QERFBUFAQLi4u+Pr6EhERwYwZM0r0mkRE\nREREyrLT2TkM3R3LwF2xtjDQAIYEV2LRnbUVBorchBQIit1k7NiRNzIwI+Oy55kZGaSuWEnGzp03\nqLLr48yZMwC4uLjka1+8eDHh4eEcPHiQjh070rRpU3bs2MG///1vPvroo+ty7549ezJnzhw8PDxo\n3749HTp0IDMzk0mTJtG0aVP27dtXoM/x48dp0aIFEydOJCsri/vvv5/69eszYcIE2rVrR1ZWtp1k\n4AAAIABJREFUVqH3ys7O5uGHH+bRRx9l7dq11KtXj65du+Lh4cG0adNo2rQpW7ZsKfFreP755xk0\naBDly5fnwQcfxM/Pj++//54WLVoUGe4BvPbaa/Tu3RtnZ2c6d+5MYGAgK1asoF27dqxfv77Y958+\nfTr/+9//iIuLIywsjG7dulGvXj3WrFlDnz59GDZsWIlfk4iIiIhIWbMuOZV7N+9lXkKyra2qixPz\nG4cysmYVXCyKHURuRvrMFLs59VVk3jThYjAzMzn11VelXNH1s337dg4ePAhA48aN8x177733mDJl\nCjt37mTmzJmsW7eO6dOnA/DWW29dcTReccyYMYMTJ06wadMm5s2bx08//cTBgwd59dVXSUxMLDTM\nGjJkCAcOHKB9+/b8/vvvREZG8tNPP7F3716SkpKKDNNGjhzJd999R+vWrdm3bx+rV69m7ty5REdH\nM2HCBJKTk+nVqxc5OTkleg1Tp05l5cqVREVFMXPmTPbs2cPw4cNJS0ujd+/eZBQRJE+cOJFNmzax\natUqZs+eza5du3jqqafIysritddeK/b9O3XqxJ9//klMTAy//vors2bNYu3atURHRxMUFMT48ePZ\nuHFjiV6TiIiIiEhZkWm18kbMUR7evp+jmdm29kf8fVh5VxgtfcrZsToRuRKtIShXJTqs7o29odVK\n6qLFRC9afM2Xqrsn+joUVLjk5GTWrFnDc889h9VqpXHjxrRp0ybfOd27d6d///752h577DHGjBlD\ndHQ0W7ZsoXXr1tdUR48ePQq0OTo68vbbb/Pll1+ydOlSUlNT8fT0BODw4cN8//33ODg4MGXKFFs7\nQNWqVfnwww/p2rVrgWsmJSUxfvx4ypUrx9y5c6lUqVK+40OHDmXx4sUsXLiQRYsW8cADDxT7NQwa\nNCjfczAMg1GjRjFnzhwOHDjA/Pnz6dOnT4F+b775Js2aNbN9bLFYGDVqFJ9//jlr1qwhOzsbp2Ks\nR9m8efNC22vVqsXIkSN5+umnmTdvHi1atCj2axIRERERKQt2n01nyO5Yos9d/CW9j6MD79cJ4oFK\n3nasTESKS4GgyDWKiIgotL1p06Z89913WP42RL5Lly6Fnh8WFkZ0dDTx8fHXpa59+/axePFiYmJi\nOHv2LNbzazTm5ORgtVqJiYmhSZMmAKxevRrTNLn77rupWbMmKSkp+a71wAMP4O3tXaB95cqVpKen\n07lz5wJh4AVt2rRh4cKFrF+/vkSB4GOPPVagzcHBgUcffZTRo0cTFRVVaCBY2POtVKkSPj4+JCcn\nc+rUKfz9/YtVQ0ZGBkuWLGHz5s2cPHmSzPMjWo8dOwZQ6NRrEREREZGyymqaTIk7ybsHjpF1yRrv\nEb6efBwWjL/LrbERpIgoEBS5Zp06dbIFTC4uLlSpUoVWrVoRERFh2xzjUsHBwYVex8vLC6DIqbDF\nlZOTw+DBg5k2bdplN2K5sMYhwJEjRwCoXr16keeHhIQUCAQPHDgAwMKFCwt9rZc6efLkFWu/VFG1\nVKtWDbhY899d7vkmJycX+/muX7+eHj16FHkfyP8MRURERETKsriMLIZFH+a3lLO2NleLwWs1q9Cv\nqt8Vfx4QkZuLAkG5Ktdj2u2R554ndenSgrsLF8ZiwbNTRwI//via73u9DR8+nLZt2xb7/L+PGLze\nxo0bx+eff06VKlUYO3YsLVu2pFKlSrbNTVq2bMn69euvy67Nubl5O4jVqVOHu++++7LnXu+ptUX9\ng+N6PN+0tDS6detGQkICAwYMYNCgQYSGhuLp6YnFYmHp0qV06tTpltr5WkRERETkapimyfyEZF7Z\nd4TU3Is/u93h6cbEuiHU8nC1Y3UicrUUCIrdVOjXl7OrVmGmp1/xXMPFmQr9+t2Aqm59c+fOBeCz\nzz4rdPpsTExMgbaqVasCcOjQoSKvGxsbW6AtKCgIgIYNGxIZGXkV1Rbt0KFDNGrUqNB2gCpVqlzX\n+11q9erVJCQk0KxZM6ZNm1bgeGHPUERERESkrEnOzuHlvUf46eTFmUIWYFhIZV6o5o+TRaMCRW5V\n2mVY7Mb1jjvwvDcCw/Xyv1EyXF3xvPdeXBs2vEGV3dqSkpKAi2HdpX799ddCp+62bt0awzBYv369\nbRrwpRYuXFhgujBA+/btcXJyYtmyZYUevxbffvttgbbc3Fxmz54NUKJRmSV1uWcIebs4i4iIiIiU\nZauSUonYtDdfGFjNzZkfm9bivzUCFAaK3OIUCIrdGIZBlXffxbPdvRhubvD3qZ4WC4abK57t7qXK\nu+9qTYpiCgsLA2Dy5Mm2jUQA9u/fzzPPPFNon5CQELp27Upubi6DBg3i3LlztmPx8fG89NJLhfar\nXLkyQ4YMISUlha5du7Jnz54C5yQnJzNt2jQSEhJK9DomTZrE2rVrbR+bpsnrr79OTEwMVatWpXv3\n7iW6XklceIYrVqzI95qsVitvvfUW69atK7V7i4iIiIjYU3qulRH7jtDzj/0cz8q2tfcJ8GX5nXW4\ns7yHHasTketFU4bFrgwnJ6p8+CEZO3dy6suv8qYQZ2RguLpSrm0bKvTvj5tGBpbIK6+8wuLFi/ns\ns89YuXIlTZo0ISkpiVWrVhEeHo6/vz+//fZbgX6TJk3ijz/+YOnSpTRu3Jh77rkHq9XKihUraNCg\nAeHh4axfv75Av/fff5/4+HjmzJlDgwYNaNy4MdWrVycjI4O4uDiio6PJysoiOjqaypUrF/t1PPXU\nU7Rp04bWrVsTEBDA77//zt69e3Fzc+Pbb7/Fzc3tmp7T5TRt2pQHHniAn376icaNGxMREUH58uXZ\nvHkzhw8f5uWXX+b9998vtfuLiIiIiNjDjtQ0huyO5a+0TFtbBSdHxoYF0cmvvB0rE5HrTSMExe4M\nw8DtjjsI/ORjwrb9Tt3o3YRt+53Ajz9WGHgVwsPD2bRpE507d+b06dMsWLCAI0eOMGLECJYsWYKT\nk1Oh/apUqcKmTZsYNGgQTk5OLFq0iJ07dzJ48GCWL1+Os7Nzof2cnJyYPXs2CxYsoEuXLsTHx7Ng\nwQJ+++03cnJy6N27N99//z01a9Ys0esYO3YsEyZMICkpiR9++IETJ07wr3/9i40bN9KmTZsSP5eS\nmjdvHu+++y6hoaFERUWxfPly6tevz9q1a7n//vtL/f4iIiIiIjdKrmky7lAC/9y6L18Y2KGCF1F3\n1VEYKFIGGdol8/ZgGEYU0KZNmzZERUVd9tzo6LwdhOvWrVvqdcnN6cJ6gN7e3jf83hemhpe1r01l\n9fNqwYIFADz44IN2rkRuBXq/SHHpvSIlofeLFJfeK4WLTc9k6O7DbD5zcdkgdwcLb4VWpU+A7227\ndJPeL1JcDRo0YNeuXQCrTNNsa+dyik1ThkVERERERERuM6ZpMvN4EiP/Osq53ItrjzfzcufTuiFU\nd3exY3UiUtoUCIqIiIiIiIjcRhKzcvjP3jgWJZ62tTkY8GI1f/4vuDKO2kFYpMxTICgiIiIiIiJy\nm/g18TTP74kjMTvH1hbq7sKEuiE08XK3Y2UiciMpEBSRm0pZWztQRERERORmcC43lzdj4vkm/lS+\n9n5V/RhZswruDtpzVOR2okBQREREREREpAz7/fQ5hkTHcjA9y9ZWydmRT8KCubeClx0rExF7USAo\nIiIiIiIiUgZlW00+iT3OJ7EJ5F4yEadzxfK8XzuICs6KBERuV/rsFxERERERESlj9qdlMGT3Yban\nptnayjlYGF0rkB7+PhiGNg4RuZ0pEBQREREREREpI0zT5Ov4U7wZc5R068VhgXeX92B83WCC3Vzs\nWJ2I3CwUCIqIiIiIiIiUAScys3luz2FWJKXa2pwMg/9W92dQcCUcNCpQRM5TICgiIiIiIiJyi/vl\nZAov7Y0jKTvX1lbHw5WJdYNp4Olux8pE5GakQFBERERERETkFpWak8vIv44y63hSvvaBgRV5pUYA\nrg4WO1UmIjczBYIiIiIiIiIit6CNKWcZGn2YuIwsW1sVFyfGhQXTytfTjpWJyM1OgaCIiIiIiIjI\nLSTLauWDg8f59PAJzEvau1Xy5p3agXg76Ud9Ebk8fZUQERERERERuUXsOZfO0N2H+fNsuq2tvKMD\n79YOpFtlHztWJiK3Ei0mIHKVqlWrhmEY+f5zdXWlevXqPPHEE2zfvj3f+W3btsUwDKKiouxTcCnq\n27cvhmEQGRlp71JERERERMokq2nyedxJOm3Zly8M/Id3OVY0r6MwUERKRCMERa5Rp06d8Pf3ByAp\nKYnNmzczffp0Zs6cyfTp0+nVq5edKxQRERERkVvZscwshkUfZnXyWVubi8VgRI0A/h1YEYth2LE6\nEbkVKRAUuzNNk4RDZ9j+62Fi/zxFTpYVR2cLIQ38aNIhmErVPDFu4m9ww4cPp23btraP09PTeeqp\np/j22295+umn6dixI76+vvYr8AZ45513GD58OAEBAfYuRURERESkTPkhIZnh+46QkpNra6tfzpVP\n64ZQt5ybHSsTkVuZAkGxq9xcK8u/2s3BHYnkZlsxz6+Im5Nl5cC2E8T+mUj1O/xo168eDg63xgx3\nNzc3Jk+ezA8//EBqaipLlizh0UcftXdZpSogIEBhoIiIiIjIdXQ6O4f//XWU+QnJtjYDGBJcif9U\n98fFcmv8fCQiNyd9BRG7MU0zLwz8I5GcrIth4MXjecHgwT8SWf7Vbsy/n3AT8/T0pHbt2gDExsYW\nOL5161a6du1KhQoVcHNzo1GjRnzxxRdFXu/cuXOMHj2aRo0aUa5cOTw8PGjcuDFjxowhLS2tyH5x\ncXEMGzaMOnXq4ObmhpeXF/fccw+RkZGFPs8L6xyuXbuW7du3F7vGwtYQ3LdvH15eXjg6OrJ69eoC\nfXbv3o2HhwdOTk6sX7++yNcgIiIiInK7WZucyr2b9+YLAwNdnfi+SSiv1qyiMFBErpm+iojdJBw6\nw8EdieRkWy97Xk62lYM7EjlxKPUGVXZ9nDlzBgAXF5d87YsXLyY8PJyDBw/SsWNHmjZtyo4dO/j3\nv//NRx99VOA6iYmJhIeH8+qrrxIXF0eHDh3o1KkTsbGxjBgxgpYtW5KUlFSg38qVK2nYsCHjx4/H\narVy33330aJFC3bs2EG/fv148skni6x92bJldOzYsdg1FqZ27dp89tln5Obm0rt3bxITE23H0tLS\neOSRR0hLS2PMmDGEh4cX65oiIiIiImVZRq6VN2KO8sj2/RzNzLa19/D3YWXzMO72LmfH6kSkLFEg\nKHaz/dc4cq8QBl6Qm21l+7LDpVzR9bN9+3YOHjwIQOPGjfMde++995gyZQo7d+5k5syZrFu3junT\npwPw1ltvFRjxN3jwYHbu3EmrVq04cOAA33//Pd999x0HDhygZcuW/PHHHwwZMiRfn2PHjtG9e3fO\nnj1LZGQk+/bt4/vvv+fXX39l9+7dNG7cmOnTpxe5K/C4ceMYO3ZssWssyqOPPsrTTz/N0aNHeeKJ\nJ2yjEocMGcLu3bv55z//yUsvvVSsa4mIiIiIlGW7z6Zz/9Z9TIk7yYW5PL5ODkyrX43xdUPwdHSw\na30iUrZoDUG5KhOfWXFD72eaELP1BDFbr/2+Q6bcex0qKlxycjJr1qzhueeew2q10rhxY9q0aZPv\nnO7du9O/f/98bY899hhjxowhOjqaLVu20Lp1ayBvuvG8efOwWCxMnToVb29vWx8fHx8+//xzGjZs\nyJw5c3j//fcJCgoC4JNPPiE5OZmXX365wEjAoKAgPv/8c5o3b86ECRPo27dvgdfRtWtXHnvssWLV\neCXjxo1jw4YNLFq0iA8++AB/f38iIyMJDAzkm2++uak3jBERERERKW25psmUuJO8d+AYWZcs6xPh\n68knYcFUdnGyY3UiUlYpEBS5RhEREYW2N23alO+++w7L39b36NKlS6Hnh4WFER0dTXx8vK1tzZo1\nmKZJeHg4YWFhBfrUq1ePu+66iw0bNrB69Wr69OkDwC+//ALAI488Uui9mjVrRrly5di+fTsZGRm4\nurrmO96pU6di13glrq6uzJ07l2bNmjFixAicnZ1xcHBg5syZVKhQodjXEREREREpa+Iysvi/6FjW\np5yztblZDF4LrUrfKhX0y3MRKTUKBEWuUadOnfD39wfy1gusUqUKrVq1IiIiotBv4MHBwYVex8vL\nC4CMjAxb29GjRwGoXr16kfevWbMmGzZssJ0LcODAAQCaN29+xfpPnTpF1apV87UFBgYWu8biqF27\nNu+//z6DBw8mJyeHN998k3/84x8luoaIiIiISFlhmibzEpL5374jpOZeXEapkacbE+uFEOruepne\nIiLXToGgXJXrMe128dQ/ObDtRIHdhQtjGFCzaSU6PdXgmu97vQ0fPpy2bdsW+/y/jxi8nAtr7l3u\nN4OF7Racm5sLQM+ePQuM/vu7v296UtIaiyM3N5dZs2bZPt68eTOmaeo3niIiIiJy20nKzuG/e4/w\n08kUW5sFGBZSmReq+eNk0b+RRaT0KRAUu2ncIYjYPxPJybryxiIOThYaty98ZF1ZdmGk3oURf4W5\nsHnJpaP8goKCiImJYeTIkdSvX790iyyGN954g9WrV3PXXXdx7tw5fv75Z8aOHcuLL75o79JERERE\nRG6YqKQzDIs+TEJWjq2tmpszE+uG0Ky8hx0rE5HbjXYZFrupXM2L6nf44eh0+beho5OF6nf4Uama\n5w2q7ObRqlUrDMNgw4YN7Nu3r8Dx6OhoNm7ciMViybfJx/333w/A3Llzb1itRVm+fDljxozB29ub\n2bNnM3v2bNzd3XnllVfYtGmTvcsTERERESl1ablW/rfvCL3+OJAvDHy8SgWW31lHYaCI3HAKBMVu\nDMOgXb96VG/kh6Ozhb/PHjUMcHS2UL2RH+361bstp5eGhITQvXt3rFYrAwcO5PTp07ZjKSkpDBw4\nEKvVSo8ePWw7DAP85z//wcvLizFjxjBx4kRycnIKXHvDhg2lHhgmJCTQp08frFYrX3zxBdWqVaN+\n/fqMHz+e7OxsevbsSUpKypUvJCIiIiJyi/ojNY1OW/by5dFEW5ufkyPfNKzOB3WC8HB0sGN1InK7\n0pRhsSsHBwsdBtTnxKFUtv16OG8KcbYVRycL1Rr60bhDMJWredm7TLuaPHkye/bsISoqiho1atjW\nK1y5ciXJyck0atSIiRMn5usTFBTEDz/8wMMPP8zQoUMZPXo09evXp0KFCsTHx7N//37i4+Pp2bNn\nkTsRXyur1UqfPn1ISEhgyJAhPPTQQ7ZjAwYMYMWKFcyYMYMBAwYwf/78UqlBRERERMRecqwmnx5O\n4MNDx8m5ZNnvTn5efFgniIrOTvYrTkRuewoExe4Mw6BydS/ue/rm2zDkZuDn58f69ev55JNPmDNn\nDosWLQKgVq1avPTSSwwbNgwPj4JTDCIiIti1axcTJkxg4cKFbNiwgezsbPz9/alVqxbPPvtsqYWB\nAKNHj2b58uU0btyYjz76qMDxzz77jM2bN/Pdd9/x6aefMnTo0FKrRURERETkRjqUnsmzuw+z+cw5\nW5u7g4W3Q6vSO8D3tpz9JCI3F6OwHUql7DEMIwpo06ZNG6Kioi57bnR0NAB169Yt9brk5nRhGq+3\nt7edKyk7yurn1YIFCwB48MEH7VyJ3Ar0fpHi0ntFSkLvFymuG/FeMU2TmceSGBlzlHO5FzdPbObl\nzqd1Q6ju7lJq95brS19bpLgaNGjArl27AFaZptnWzuUUm0YIioiIiIiIiFyjk1nZ/GdvHIsTz9ja\nHA14sZo/zwZXxtGiUYEicvNQICgiIiIiIiJyDZYmnuaFPXEkZl/czC/U3YVP64bQ2MvdjpWJiBRO\ngaCIiIiIiIjIVTiXk8sb++OZHn8qX3u/qn6MrFkFdweLnSoTEbk8BYIiIiIiIiIiJbT19DmGRsdy\nMD3L1lbZ2ZGPw4K5t4KXHSsTEbkyBYIiIiIiIiIixZRtNfk49jjjYhPIvWSPzs4Vy/NBnSB8nfRj\ntojc/PSVSkRERERERKQYYtIyGLr7MNtT02xt5RwsjKkdyCOVfTAMbRwiIrcGBYIiIiIiIiIil2Ga\nJl/Hn+LNmKOkWy8OC7y7vAfj6wYT7OZix+pEREpOgaCIiIiIiIhIERIys3l+z2FWJKXa2pwMg/9W\n92dQcCUcNCpQRG5BCgRFRERERERECrHwZAr/2RtHUnaura2OhyuT6oVQv5ybHSsTEbk2CgRFRERE\nRERELpGak8urfx1l9vGkfO0DgyrySvUAXB0sdqpMROT6UCAoIiIiIiIict6GlLM8G32YuIwsW1sV\nFyfG1w3mHz6edqxMROT6USAoIiIiIiIit70sq5UPDh7n08MnMC9pf6iyD2NqVcXbST8+i0jZoa9o\nIiIiIiIiclvbcy6dobsP8+fZdFtbeUcH3qsdyL8q+9ixMhGR0qFAUERERERERMok0zTZdiaNSXEn\nWOoZRBYGz636g/YVyjMouCKNyrnxxdFERh84Rqb14rjAVj7lGBcWTBVXZztWLyJSerQSqshVqlat\nGoZhEBUVZe9SLmvatGkYhkGNGjUwTfOK58+dOxcfHx9q165Ndnb2DahQREREROT6y7aaDNodS/ft\n+/nl5GmyDAsYBulWk4UnU3hoWwyNf9vFazHxtjDQxWLwdmhVZjeqqTBQRMo0BYIiZVzPnj3x8PDg\n4MGDrFq16ornR0ZG2vo5OTmVcnUiIiIiItefaZo8Gx3LksTTpFutWP923ApkWE1OZufa2hqUc2PJ\nnbV5KqgiFsO4ofWKiNxomjIsdmeaJsdj9rHlp+84sG0LOdlZODo5U6Npc+58oBv+NWtj6BvyVfP0\n9OThhx/m66+/5quvvqJt27ZFnnvs2DGWLFkCQJ8+fW5QhSIiIiIi19e2M2ksTTxDuvXKM2QAHqns\nw0dhQThbNGZGRG4P+mondpWbk8Mv4z9gztv/469Nv5GTlQmmSU5WJn9tXMect/7HL+M/IDcnx96l\n3tL69+8PwPz58zl79myR533zzTfk5uZy5513EhYWdqPKExERERG5ribHnSTD+vdxgYUzgEyrqTBQ\nRG4r+oondmOaJosnjiVmy0ZyMjMLrG9nmiY5mZnEbNnA4olji7X+3c0sNjaWd955h4iICIKCgnBx\nccHX15eIiAhmzJhRZL+lS5fSuXNnKlWqhJOTE76+voSFhdG/f39+//33Yt27devW1KpVi3PnzjFn\nzpwiz7swXbiw0YGmaTJjxgw6dOhAhQoVcHZ2JiQkhIEDB3L48OEirzlnzhzCw8Px8PDA19eX++67\nj3Xr1rFs2TIMw6B9+/YF+sydO5d+/fpRr149vL29cXV1pVatWgwdOpSjR48Wep/k5GSGDx9OvXr1\ncHNzw83NjcDAQCIiInj//fev8IRERERE5FZlmiYnMrPZkHKWGcdOMXp/PL+cTCkwTbjI/sCvp86U\nZokiIjcdTRkWuzkes4+YrRvzRgVeRk5WFjFbN3J8/z4CQuvcoOquv+nTpzNy5Ehq1qxJWFgY99xz\nD0eOHGHNmjVERUWxceNGxo0bl69PZGQk/fr1w2Kx0KJFC0JCQjh79ixxcXFERkZSu3ZtmjZtWqz7\n9+3blxEjRhAZGWkbMXip9evXs2fPHtzd3XnooYfyHcvOzuaRRx5hwYIFuLu706xZMypXrszOnTuZ\nOnUq8+bNY9myZTRp0iRfv7feeovXX38dwzC45557CAwMZNeuXbRp04Znn322yFp79OhBuXLlqFev\nHh06dCA9PZ3t27czceJE5syZw/r166lZs6bt/LNnzxIeHs7evXupXLkyHTt2xN3dnfj4eP788082\nb97Myy+/XKznJCIiIiI3H9M0OZWdy8H0TA6kZeb9mZ7JwfP/fza3uPFf4Yo7mlBEpKxQICh2s+Xn\n78nNyirWublZWWz5+QceeO6/pVxV6enUqRPdunWjfv36+dr/+usv2rVrx/jx4+nduzctWrSwHXvr\nrbcAWLNmDS1btszX78iRI5w5U/zfZPbt25fXXnuNNWvWsH///nyBGlwcHdi9e3e8vLzyHXvllVdY\nsGABERER/L//9/+oUqWK7di4ceN47rnn6NWrF7t378bBwQGATZs28cYbb+Ds7MzPP/9Mhw4dbH0+\n/vhjXnjhhSJrnTVrFl27dsXNzc3WlpOTw8iRI3n33Xd57rnn+Omnn2zH5syZw969e+natSvz58/H\n0dExX7/Vq1cX+zmJiIiIiP2kZOfYgr4D6ZkcTM9if1oGh9KzOJ2Te+ULXCVXTRcWkduMAkG5Kh/1\n7HJD72eaJvvWr+Gj9Wuu+Vovzv75OlRUcs2bNy+0vVatWowcOZKnn36aefPm5QsEExIS8Pb2LhAG\nAgQGBpbo/lWqVKFjx44sWrSIyMhI3n77bdux9PR0Zs+eDVBg9ODJkyf59NNP8fLyYs6cOfj5+eU7\nPmzYMBYtWsSSJUtYunQp999/PwCffvoppmnSr1+/fGEgwPPPP8+3337L1q1bC621Z8+eBdocHR0Z\nM2YMX331FYsWLeLcuXN4eHgAec8JoEOHDvnCwAv97r333is+HxERERG5MVJzcvOFfhdG/B1MzyQp\n++pCP08HC9XdXajh5kJ1Nxeiks6wPTWd4iw6ZAE6VPC64nkiImVJmQ4EDcMIBP4LdASCyVsvNg5Y\nDrxvmuaBIvr1BgYBdwAOwB7gK2CyaZpFjiU3DOM+4AXgTsAVOADMBD40TbPAvFjDMCKBJ4E3TdN8\no5Dj5YGFwD3na+hgmuaRYrx0uUllZGSwZMkSNm/ezMmTJ8nMzHtbHDt2DIB9+/blO/+uu+4iKiqK\nJ554gueff57GjRtf047L/fv3Z9GiRXz99de8+eabWM7/JvS7777j9OnT1KhRgzZt2nD69GlbnxUr\nVpCZmcl9991XIAy8oE2bNixZsoT169fbAsFVq1YB0Lt370L7PProo0UGggB79+5lyZL5LfbdAAAg\nAElEQVQlxMTEcPbsWaznp3FYrVZyc3M5cOAADRs2BPKeE8A777yDj48PnTt3xtvbuySPRkRERESu\no3M556f3pmddMtovL/xLzL66DQPdHSy2wK+GuwvV3ZzzPnZ3wc/JMd+/kztU8OLh7ftJK8ZUYBeL\nwTPBFa+qJhGRW1WZDQQNw2gCrAC8gSPAkvOH7gQGAn0Mw+hkmuZvf+s3ERgMZJAXHGYD7YBPgXaG\nYTximmaBX1sZhvEy8B6QC0QByUAbYBTQxTCMdqZpppWg/orna24C/A50Mk0zsbj95eazfv16evTo\nwZEjRWe6f58CPGnSJDp37sz06dOZPn065cuX56677qJDhw48/vjj+Pv7l6iGrl274ufnR1xcHCtW\nrLBt6PHVV18B0K9fvwKB44EDebn5ggULrhhGnjx50vb/8fHxAISEhBR6blHt2dnZDBo0iC+++OKy\n97r0WbVr144XXniBTz75hMceewyLxUKdOnVo1aoV3bt3p2PHjpe9loiIiIiUXFquldj0/KP8LvyZ\nkHV1oZ+bxaCaLfBzsQV+NdxcqOTsWOxfjjfxcqejnxdLEk+Tbi16nKCbxaCTX3maeLpfVb0iIreq\nMhsIAhPJCwM/B4aYppkNYBiGEzAF6A9MBhpd6GAYRnfywsDjQGvTNP86314ZWAl0A4YC+XZ+MAzj\nTuBdIA241zTNjefby5E3wq81MBp4vjiFG4YRBPwK1AHWAF1M07yptr26HtNuf/r4Xf7auK5Yuwcb\nhkGtu/9xy64hmJaWRrdu3UhISGDAgAEMGjSI0NBQPD09sVgsLF26lE6dOhV4FnXr1rWNlFuxYgXr\n1q1j5cqV/Prrr7zxxhvMnz+f++67r9h1ODs706dPH8aNG8dXX31F+/btOXz4MCtWrMBisfDkk08W\n6JObm5d/h4WF5ZvOXJgLI/UuVdQ/2ixFrNMyduxYvvjiC6pWrcrYsWMJDw+nUqVKuLi42O6xefPm\nAs/qo48+YvDgwfz444+sXbuWdevWMXXqVKZOncr999/PTz/9ZFvfUERERESKJyPXSmxGwVF+B9Mz\nic/MvqprulgMQlxdqOHufMlov7zQz9/FCcs1zIi5wDAMJtQN4dnoWJYmniHDas2367DlfB2d/Moz\noW7INc3CERG5FZXJQNAwDFcg/PyHr10IAwFM08w2DGMkeYHgHYZhuF8ycu+V83/+90IYeL5PgmEY\ng8gb+TfcMIwJf5s6PJy86cjvXQgDz/c7axhGP+AvYLBhGG+applyhdprkRcGhgCLgO6maaaX9Bnc\nCu7s0o0D2zaTk3n5XYYBHJydubPLv25AVaVj9erVJCQk0KxZM6ZNm1bgeExMTJF9nZyc6NKlC126\n5K3bmJyczJtvvsm4ceMYMGAAR48eLVEtAwYMYNy4cXz//fecPn2ayMhITNOkY8eOBAUFFTj/Qlvj\nxo1tG48UR0BAAHFxccTGxhIcHFzg+KFDhwrtN3fuXACmTZtWaNh5uWdVs2ZNnn/+eZ5//nlM02TN\nmjU8+uijtmnShe2uLCIiInK7y7JaOZyRVWCU34H0TI5mZBdrHb6/czIMQtycC4zyq+7uQhUXJxxu\nQADnZDGYXC+EbalpTD58kiUnksjGwNXBgQ4VvBgUXIkmXhoZKCK3p6sKBA3DqAT8A2gBBAB+gBtw\nCkgkb727NcC2y625V4pygRzyXl9h32kufE87B6SDbb3BZkAWMLdAB9NcZRjGUaAqcDfw2/l+zsD9\n50/7tpB+BwzDWE/eOoD/BGYUVbRhGHcAS4HKwBzgsUvDzLLGP7Q2oc1aELNlAzmX2W3Y0dmZ0GYt\n8K9Z+wZWd30lJSUBFBq4AcyYUeTbogAfHx8++OADJkyYQHx8PCdPnqRixeKvedKwYUOaNWvG1q1b\nmTVrFl9//TVQcDORCy5s1LF06VLOnDlTYAfiorRu3Zpvv/2WmTNn0qpVqwLHZ82aVWi/yz2rRYsW\nkZycXKz7G4ZB69ateeKJJ3j33Xf5448/itVPREREpCzKsZrEZWQVGOV3IC2TuIwsruaHNgcDgl0L\njvKr4e5CVRdnHC32H3VnGAZNvTz4vIEHCxbk/XvwwQcftHNVIiL2V+xA0DAMX+AxoB95m23YDv3t\n1Et/gXTOMIx5wJemaa696ipL6PwowOVAJ+BNwzD+PmV41PlTvzAvzjtscv7PXZcZkbeZvECwCecD\nQfKm9boDSaZp7r9Mv3vO9ys0+TEM427gF8CHvGnOz9gpTL1hDMPgviEvsHjiWGK2biQ3KyvfNFDD\nMHA4HwbeN+SFW3oYf1hYGJC3QceePXtsH1utVkaNGsW6desK9ElLS2PKlCk8/vjjBQK/hQsXYrVa\n8fLyuqrNM/r378/WrVsZOXIkJ0+exNfXt8h/GFWpUoVnnnmGTz/9lK5duzJ16lRq184fziYlJTFv\n3jy6detmq3Xo0KHMmDGDL7/8kocffjjfTr/jx49n8+bNhd4vLCyMgwcPMnnyZCZMmGD7e//rr78Y\nPHhwoX3m/3/27js+qir///jrTDIzSSAJJYQAoYOUYKHIAgYCiI2yrAW7INhwFRT7b9UV2WJZdVlR\n0MWCfF3bwiICCggCghEEgiAQeguhJCGQBCaZds/vjymkJzMJJITP8/HIY5I799x7Jgxi3vmc85k7\nl6ZNm3LVVVcVeZ/YbDZ++OEHoOw9C4UQQggh6gq31hwucBQL/DxfHyqw4wqi1M8ExIdZSlT5tQu3\n0jLMgrkWhH5CCCECV2EgqJRqDrwEjAYsnA0ADwGb8VQEnsTThKOh96MNcAVQH7gXGKOU2gFM1lqX\nqL47R/4ILAYeAG5QSm3wHr/SO8d/AU8XOr+t9/FgOdc8VOzcwp8fomyljSssEXgKqIenI/HTZZxX\n54SEhjJ04tMc27uLDQvmeZYQOxyEWiy069GbK4ffSFyH2l0Z+Mc//rHcqrl58+bRo0cPRowYwYIF\nC7jiiisYNGgQ0dHRrF+/nkOHDvHMM8/w+uuvFxnncDh48skneeaZZ7j00kvp2LEjJpOJvXv3smGD\n5+382muvYTabA57znXfeyZNPPulvAnLXXXf59+grzZtvvsnRo0eZO3cuCQkJXHHFFbRt2xabzUZa\nWhqpqak4nU4GDx7sDwT79OnDiy++yJQpUxgyZAj9+/enRYsWbNu2jW3btjFx4kTefvttLBZLkXv9\n6U9/YtmyZbz77rssW7aMK664ghMnTvDjjz+SmJhI06ZNWbduXZExK1as4N1336VJkyb06NGDmJgY\ncnJy+Omnnzh58iRdu3bl/vvvD/j7JIQQQghR2xhac8Tu9O/pty/fzn5v+Hcw34GjEvtzF6eA5lZz\niSq/tuFWWoVbsJax97MQQogLV7mBoFLqNTxNNMLxLK/9H56lrD9V1PFWKRUCXAoMB24HugJfeLvx\njtdab6z69MvmXarbD5iNZ0lvfKGnNwA/FluOW9/7eKacy572PkZWw7jCrvY+/hJIGKiUuhdP4FoZ\nVwBkZWUxf/78ck+MjY0lMjKSU6fK3e6wWoXHNKX/2PH0Hzu+xHPncx6BMAxPAWdqamq552VmZhIe\nHs4HH3zA9OnT+fLLL1m5ciX16tXjyiuv5P3336egoIDXX38dl8vlf70ul4s333yTNWvWsHXrVhYv\nXozL5aJZs2bccsstPPTQQ/Tq1Svo78/w4cOZM2cOAKNGjSr1OoWPffDBB9x00018+umnpKSksHnz\nZiIjI2natCm33norQ4cOpUGDBkXGTJo0iVatWvHee++xfv16fv31V3r06MH8+fM5eNCTvUdFRRUZ\n061bN77//nv+9re/sXnzZr755htat27N008/zcSJE/n9738PQF5enn/cqFGjCAkJYe3atWzZsoUT\nJ07QoEED2rdvz80338zdd9+NYRg1+l5yu93k5eVV+PfvQlVXX5c4N+T9IipL3isiEHXp/aKBUyqE\nDFMoGSZzkcdMUyhOFVxA18BwEWu4iDWcxBoumnofYwwXlmI7BeYD270fdU1deq+Ic0/eL6KuqqhC\n8GlgD54Oup8H0txCa+0GfvV+/FUp1c17vTuAYcA5DQS9YeD/gFxgJPATnl9+XQW8CcxVSr2ktZ7i\nG+KbeqC3CnJcYT8DvYDeSqm3tdYTKzmuDZBUhfuKKtiyZUtA51ssFh5//HEef/zxUp8vvjdeaGgo\n48aNO2eNMGbOnMnMmTMDGjN06FCGDh0a0Jibb76Zm2++ucTxTz/9FPA0Kynu8ssv56uvvir1eosX\nLy71/Msvv7yUs4UQQgghaicN5CpTicDP9+gIMvSL8oZ+TQsFf7GGkyaGC2uVfmQRQghRl1QUCN4N\nfFEde9lprbfiWTr8Ep59+M4ZpVQD4Gs8S3D7aa33FXp6vlJqG7AFeFEp9bm3o3Ce9/n6lM33XF6h\nY8GOK2wp8AbwBTBBKaW11o+Vcz2fA8CqSpwHngrB6JiYmAo30fVVvAWzN52oG3yVdFV9D+zcuZO4\nuDiio6P9x7TWfPjhh3z55ZeEhYVx7733XhTvtaNHj9KgQQP69u1b8ckXEN9vTGVzblEZ8n4RlSXv\nFRGI2vx+0Vpzwuku0bnXt9z3jDu4H7Mam0O9e/kV29sv3Er90JBqfhV1R21+r4jaR94vorKef/75\nmp5CUMoNBLXWlW99Wkla6wN4gqxzaRjQBPihWBjom8MepdQ6YKD3Y3ehOZXXecDX9vRAoWO+z1sF\nOK74nP6nlLodTyg4USlFRaGg1noWMKu8c3yUUiuRakJxnn388cf885//pEePHrRs2RKbzcb27dvZ\nv38/JpOJd999l7i4uJqephBCCCFElZx0ukrs6efr5pvrCi70axgaUiTo8+3p1zbcQrS50r0hhRBC\niFLV1X9JfOFcTjnn+DYTa+R93OR9TFBKhZexPPrKYucC7MCzxUYjpVT7MjoN9y5lXAmlhIJaa136\n+lIhLgDDhw/nwIEDrFu3jq1bt2K322nSpAmjRo1i0qRJda5aTgghhBDnh9aaTbk2pqdlsDSyJQ4U\nj6/azJDG0TzcqgndIyNQqnq73+a63IU69xat9jvpcgd1zahQk7+Jhy/8833eUEI/IYQQ51Bd/Vfm\niPexp1LKXKx5CEopM9DT++V+AK11mlIqBegBjMLTjKTwmCQ8jUmO4dnzD+84h1LqO+Am4C5gSrFx\n7YC+gANYVNHEi4WCj3krBSUUFBekxMREEhMTa3oaQgghhKhDnIZmQupBlmTlYjcMDO9ee/mGZlHm\nKZafyOXamCimdWmN2RRYKHja5S6xrHe/zcG+fDsnnK6g5lsvxFRiWa+v2q+xOaTag0shhBCiMqo1\nEFRKRQMj8ARnGcBirfWR8kedE98BNjyVgv9USj2ptbZ752gFpuJZxnsSWFJo3CvAf4HXlFLJWus9\n3jGxwHTvOa+Wsqfiq8CNwLNKqcVa61+84+oDHwEmYLrWulItTksJBbXWelJg3wIhhBBCCCHqFq19\nYWAO+UbJBhkGYDMMlmTlMCH1IDO6ti4RuNncBgfK2NMvwxFc6BduMtE23HI29CtU7dfEEiqhnxBC\niFqn0oGgUqojnrAvT2tdojWpUioRmMfZJbgADqXUE1rrGVWeaQC01hlKqT8CHwKPADcqpTbi6Qjc\nE2gG2IFxWuucQuPmKKVmAA8DvymllgFO4GogCk+jkndKud96pdRzwGtAslLqBzxLkpOAWGAdENAu\nk8VCwce9lYISCgohhBBCiIvWplwbS7NySw0DC8s3NIuzcph+KAOUKrKn31G7s9yxZbGaFG3Ci1f5\nWWgXYSXOYpbQTwghxAUlkArBscCzwEzvh59SKgqYCzQGjgM/AZcA3YBpSqltWusfq2XGlaS1/kQp\n9RvwONAfuNb7VDqeoPAtrfX2Usb9USm1Bk+QmASE4Nkn8CNgRlkdl7XWryultgBP4tlrMAzYB7wN\nvOGrUAzwNUgoKIQQQgghhNeMtEwKjMo16SgwNH/ZdzSg65uVok24xdO8o9iefs2tZkwS+gkhhKgj\nAgkEB3gfPyrluQfwdPXdC/xOa50NoJSaCdwHTALOayAIoLVOAUYHMe4zIOAOy1rrxcDiAM6/F7i3\ngnP+B1gCnYsQQgghhBAXqjNuN0cKnByxO0m3O0gvcHDE7mRR5imC69l7VqiCVmG+Kj9LkT394sMs\nhEjoJ4QQ4iIQSCDYCnABG0t57g+ABv7uCwO9ngbGAH2CnqEQQgghhBCiznAammMOJ0cKHKTbnf6w\nr/BjsF17SzOuRYw/8GvnDf0CbTYihBBC1DXlBoJKqcLVdU3x7Lt3Vyn7Y/g69jYpNgY8S4ibFjv+\nq9Z6SxDzFUIIIYQQQtRSWmuynK4iAd9h76MvADxud1a5yq+ywk0m/n5J/Hm6mxBCCHHhqKhCcGyh\nz82Au9gxgIZ49svLA24o5RoRePbhKzzuY0ACQSGEEEIIIS4gp13uElV9niW9To7YHRy1OymooOFH\nZZiVornVTPMwMy2sFlqEWWhuNTP3+EnW55yhMncwAdc0jqryXIQQQoi6qNxAUGs9yPe5UioHCAeG\naq3zCx1/BJgGLNZa31b8Gkqpn4DLC19LCCGEEEIIUbs4DIOjdqc/3EsvcBYJ+47YneRUw1JeBcRa\nQmlutdDCG/g1L/QYb7UQYwkttYHHpfXDueXXvdgq0VjEalKMb9WkyvMVQggh6qJA9hDcAfTC0yTk\nnULH78Wzf+DSMsZ1xNPZVwghhBBCCFEDDK3JdLhItzs44g36jhQ4OVzo60yHq1KVdxWJDg2hudXs\nr+qL9z76AsBmVjMWkymoa3ePiuDamCiWZOWQX04lYrhJcV1MNN0jI4J9GUIIIUSdFkgg+DlwJfCW\nUqojsBP4PZ79A7OBL4sPUEpdDsQAy6s+VSGEEEIIIURxWmtyXW5vR97Sl/MetTtx6qrHfVaTZylv\n4aq+FmEWWljNNPc+1g8NqYZXVTqlFNO6tGZC6kGWZuVSYBhF9iM0eed4XUw007q0ppS9z4UQQghB\nYIHgNGAoMAR41HtM4dlX8CGt9elSxozHUz24qCqTFKK22rFjB1OnTmXFihWkpaWhtaZJkybEx8fT\nt29frr/+eq655pqanmal/Pvf/+ahhx4C4O9//zsPP/xwDc/o3Fu5ciWDBg0iKSmJlStX1vR0hBBC\niFIVuL1LeQst3y2+nPe0u+ptOkxAU6u5SLhXOOxrbjUTYw6t8ZDNbFLM6NqaTXk2ZhzKZElGNk4U\nYSEhXNM4iodbxdI9SioDhRBCiPJUOhDUWruVUjcAd+NpHtIQ2A/M1FpvLH6+UioaaAf8AMytnukK\nUXt8+eWXjB49GofDQYsWLRg4cCANGzYkMzOTlJQUfv75Z1atWnXBBIIfffSR//NPP/30nASCs2bN\nYuzYsYwZM4ZZs2ZV+/WFEEKIC41bazIczpL79RVazpvldFXLvRqZQ2hutZS6nLdFmIWmFjNm04VR\nUaeUokdUPWZ2q8f8+ZsBGDlyZA3PSgghhLhwBFIhiNbaDXzi/ajo3BzguiDnJS4iWmscaXmcXn2Y\ngh0n0U4DZTYR1rkRkQPiMcfXr/HfRBd37Ngxxo0bh8Ph4K233mLixImEhJxdHmMYBmvWrGHNmjU1\nOMvKS01NZd26ddSrV4/Q0FC2b9/Opk2bGDSobvcC6t27N6mpqURESBWBEEKI6qe15pTL7V/Ce7jQ\nUt4j3oq/Y3YnrmrYuC/cZCrSoKO5v7rv7L599ULO3VJeIYQQQlxYAgoEhahu2m2Q/dUuCrafQLsM\nfDtZa6dB/tYsCnZkE9a1MY1uvQQVEtzm0+fCwoULsdls9O3bl0mTJpV43mQyMWDAAAYMGFADswvc\nhx9+CMCoUaOwWq28//77fPrpp3U+EIyIiKBz5841PQ0hhBAXKJvbKFHNV7hpR3qBk/xKdMOtSIiC\nOEvRar7mxZbzNgwNqXW/QBVCCCFE7VV7EhZx0dFanw0DnWfDwLMneILBgu0nyP5qF7oaNsKuLhkZ\nGQDExsYGPHbdunU8/fTT9OrVi6ZNm2KxWGjevDm33HILa9euLXXM5MmTUUoxefJkjh8/zkMPPUR8\nfDxWq5W2bdvy3HPPUVBQENRrcblcfPrppwCMHTuWcePGATB37twyrxnMfNq0acPYsWMB+OSTT1BK\n+T/uvffeIudmZWXx7LPP0rlzZ8LDw4mKiqJPnz5Mnz4dl6vksqlZs2b5r5OXl8fTTz9N27ZtsVqt\ntGjRgocffpjs7OwS41auXIlSioEDB5b6Ordt28bo0aNp2bIlVquVmJgYhg4dynfffVfu91QIIUTg\ntNak5Jzh/q37mRDZkociW9F21WYe2HqAlNwz5/3/A1yG5nCBg19OnWbe8ZO8c/A4/2/XYcb8to8h\n63fSdc1vtPtxC4nrdnDr5r08sSONNw4c4/Oj2aw6mccem73SYWBjcyiXRYZzQ0w098fH8Of2zXk/\noTULe3QkpW9XDiVdzsZ+Cczv0ZEZCW14oX1zxsU34bqYaLpFRtCoFuzrJ4QQQogLi1QIihrjSMs7\nGwaWwxcKOg+fxtIy8jzNrnytWrUCYPny5WzdupVu3bpVeuzzzz/PypUrSUhIoHfv3litVnbu3Mnc\nuXP5+uuv+fzzzxk1alSpY9PS0ujZsydaa/r160dubi5r1qzhtddeY/v27XzzzTcBv5aFCxdy/Phx\n2rVrR//+/VFK0blzZ3bs2MH//vc/7rzzzjLHBjIfX+D5008/0b59exITE/3PFf58z549DB48mLS0\nNOLi4hgxYgQ2m40VK1bwyCOPMG/ePBYuXIjVai0xn5ycHK666irS09MZMGAA3bp1Y82aNbz33nv8\n8ssvrF27FrPZXKnvyzfffMOtt96K3W4nISGB/v37c/jwYZYsWcJ3333HCy+8wF/+8pdKXUsIIUT5\nnIZmQupBlmTlYjcMDOX5nXW+oVmUeYrlJ3K5NiaKaV1aV8sed1prTjjd3mo+R4nOvEfsTo7ZnVS9\ntg/qhZj8y3aLduY109xqoZnVTHgtWgUhhBBCiIuDBIKixpxene5ZJlwJ2mWQt/owje/sco5nVTkj\nR46kefPmHDlyhO7du3PttdeSlJREz5496dWrF9HR0WWOfeqpp/jPf/5D06ZNixxfsGABN998M+PH\nj2fYsGGl7mv30Ucfcf/99/Puu+9isVgAz/5/vXv3ZsGCBfz0009cddVVAb0WXzORe++9119dcOed\nd/LnP/+Zjz76qNxAMJD5vPHGG8yaNYuffvqJxMTEMpuK3HnnnaSlpTFq1Chmz55NWFgY4AkfhwwZ\nwrJly5g8eTKvvPJKibFff/01Q4cOJTk5mfr16wNw5MgR+vTpQ0pKCl999RV33XVXhd+TY8eOcc89\n92C323nzzTd54okn/M+tXLmSYcOG8de//pXExESuu062ShVCiKrQ2hcG5pBvlKwCNACbYbAkK4cJ\nqQeZ0bV1hdVwp11u0u3OMsO+I3YHBaXcK1BmpWhmNZdozlH46yhZyiuEEEKIWkgCQRGUw8+tPr83\n1JC/JYvDW6p+3/hX+1f5GpGRkSxbtozRo0ezYcMGvv32W7799lvAs39gnz59mDhxIrfddluJsddf\nf32p1xwxYgSjRo3is88+Y8WKFQwbNqzEOS1btuTtt9/2h28AXbp04Z577mHGjBksX748oEDw+PHj\nfPfddyilGDNmjP/4bbfdxpQpU/jhhx84cOAAbdq0KXV8dc9n9erVrF+/nsjISN577z1/GOi719Sp\nUxk6dCjvvvsuL730UpHnAerXr8+HH37oDwMBmjdvzqOPPsqzzz7L8uXLKxUIzpw5k9zcXPr161ck\nDAQYOHAgjz76KK+//jpvvPGGBIJCCFFFm3JtLM3KLTUMLCzf0CzNymV9zhmaWs1FAj5fsw5fAJjj\nclfL3GItoTQvVN3nq+rzfd3EEopJwj4hhBBCXIAkEBQiSF26dGH9+vUkJyezaNEi1q1bR0pKCidP\nniQ5OZnk5GS+++67UivhsrKyWLhwIVu3buXUqVP+ffG2bt0KwK5du0oNBAcPHkx4eHiJ477GGEeO\nHAnoNXzyySe4XC6GDBniXwYNnr0Rr7nmGv/8J0+eXOr46p7PqlWrAE842qhRoxLP33DDDTRr1oyj\nR4+ycePGEmFjz549iYuLq/J8fPMovrehz7hx43j99ddZs2YNbre7SIdpIYQQgZmRlklBJffasxkG\nv9+0p1ruGxXqWcrbvIzlvHFWM1aTLOUVQgghRN0kgaAQVdSvXz/69esHgGEYrF27lpdffpmlS5fy\nySefMGzYsCJ7Ar7//vs88cQT2Gy2Mq+Zm5tb6vHCoV1hUVFRAAE3FvGFlb5mH4Xddddd/kDwpZde\nKnW5U3XPJz09HYC2bduWeU67du04evSo/9xzMZ+K5tG2bVtMJhMFBQWcOHEiqOYyQghxMbEbBsft\nTjIcLo7ZnRx3ODlud3Lc4WJR5qlq2auvMKtJ0dxqLjXs8z1Ghsovc4QQQghx8ZJAUASlOpbdnvhP\nKvlbs0p2Fy6NgvBLY2rNHoJlMZlM9OvXj2+//ZbevXuTkpLC119/7Q8EN2zYwMMPP0xoaCj/+Mc/\nGDFiBPHx8URERKCU4k9/+hOvvPJKmZ0UTdVYqZCcnExqaioA//znP5k+fbr/OZfLhdvtWW518OBB\nli9fzpAhQ87pfAD/6y5vr6XyukxW13wqMw8hhBBQ4DY47igt6HNy3O7yf32ympbw+vj27Su+X58v\nAIyRrrtCCCGEEOWSQFDUmPr9W1CwI7vCLsMAKtREZP/48zCr6hESEsLgwYNJSUkhMzPTf3zOnDlo\nrZk4cSJPPfVUiXF79lTPMqjK8DUTAU9QWdG5pQWC1S0+3vNnvG/fvjLP2b9/PwAtWrQ4p/PYuXMn\n+/bt4+qrry7x/IEDBzAMg7CwsFKXNgshxIUu322Q4Q3zjjlcZDicJSr7jtudnOs8r/IAACAASURB\nVKrmoK8ywk2KTf0Szvt9hRBCCCHqEgkERY2xtIwkrGtjCrafKDcUVGYTYV0bY46vX+Y555vWusLK\ng0OHDgFnQy6A7OxswNMgo7jMzEy+//77apxl2c6cOcNXX30FeBp5JCYmFnn+1KlTgGfPvYSEBObN\nm8epU6do0KBBle7raz7i2zOxuKSkJMDTcfnkyZM0bNiwyPNLlizh6NGj1K9fn549e1ZpLuVJSkpi\n+fLlzJ49mwceeKDE8x9//DEAiYmJhIbKf0aFEBcOmzfoKy3cO+49nuFwVVtTDp8QBbEWM7GWUOKs\nZppavB9WM18dPcH6XFulFgyYgGsaR1fr3IQQQgghLkZB/ySrlGoADAe6AQ0Bczmna631fcHeS9RN\nSika3XoJ2V/t8oSCLqPo8mHlqQwM69qYRrdeUquW/kyfPt2//Ld3795FnnO5XHz88cfMmTMHoEin\nYV9zi9mzZ3Pffff5u+Hm5eUxbtw4fxB3rv33v/8lLy+Ptm3bltsFuGvXrvTo0YOUlBQ+++wz/vjH\nP1bpvr6qPt9S5eL69+/PlVdeyfr163nkkUf4+OOPsVqtgGdfv8cffxyARx99tESH4er0wAMP8I9/\n/IM1a9bw9ttvM3HiRP9zP/74I9OmTQPgySefPGdzEEKIQJxxu8mwuzhWxpLd4w7PR66renfrC/UG\nfZ5wL9Qf8sVZzMRazTT1BoCNzKGElPHveNd6Ydzy615slWgsYjUpxrdqUq2vQQghhBDiYhRUIKiU\nmgi8Avh+Iq8oqdGABIKiBBViotHtnXAePk3ej4c9S4hdhicI7NKIyP7xWFpG1vQ0S3A6ncyaNYtZ\ns2YRFxfHFVdcQaNGjcjOzmbLli3+brbPPPMM1113nX/c2LFjmTp1KikpKbRr147ExES01vz4449Y\nLBbGjRtXZCnvueK7x913311h0HrPPfeQkpLCRx99VOVAsE+fPsTFxZGSkkKvXr1ISEjAbDZz1VVX\n+RubfPbZZwwaNIjPP/+cVatWkZiYiM1mY8WKFZw5c4arr766zK7H1SUuLo7/+7//47bbbuOxxx7j\ngw8+oFu3bhw5coTVq1djGAYvvPAC119//TmdhxBCnHG5vSHf2XDvmHfPvuOFqvzy3NUb9JmVItYS\nSlPr2Uq+poW+jrN6qv0am0MxVfEXdt2jIrg2JoolWTnkG2XXCYabFNfFRNM9MqJK9xNCCCGEEEEE\ngkqp24Gp3i8zgSVAOhBYO1EhvJRSWFpG0viu2t0wpLD77ruPNm3asGzZMn755Rd+++03MjIyMJvN\nxMfHM2bMGO6///4SS3EbNmzIhg0bePHFF/n+++9ZtGgRsbGx3HTTTUyZMoX333//nM997969rF69\nGvAEghW54447ePrpp9m4cSNbtmzhsssuC/reVquVxYsX8/zzz/Pzzz+zadMmDMPA5XL5A8EOHTqw\nadMmXn/9debPn8/8+fMxm80kJCQwevRoHnzwQczm8gqSq8fIkSPZsGEDr732Gj/88ANz5swhMjKS\na6+9lgkTJjB06NBzPgchRN112h/0nV2ye8zhJMP/6Kn2O3OOgr64coM+M43MIVUO+ipLKcW0Lq2Z\nkHqQpVm5FBhGka7DJjyVgdfFRDOtS+tatWJACCGEEOJCpcrr2FnqAKV+Bn4H/BcYrbW2n4uJieql\nlFoJJCUlJbFy5cpyz/Ut5+zS5cIJ6ET18i1druqegeKsuvr3av78+YAnQBWiInX9/aK1Js9tFKnc\nO+ZwkVFsf75jDie2ag76LEqVWcVXOPxrGBpSawM1rTWb8mzMOJTJkoxsnCjCQkK4pnEUD7eKpXuU\nVAaK0tX1/7aI6iPvFREIeb+IyurWrRvbtm0DWKW1HljD06m0YJYMd8OzBPhRCQOFEEIIUddprcl1\nuUttvlG4qu+43UV+JfbBC4TVpAo14AgtUsVXOPBrUIuDvspSStEjqh4zu9Vj/vzNgPwQJoQQQghx\nrgQTCLqAHK11ZnVPRgghhBB1i9aaTbk2pqdlsDSyJQ4Uj6/azJDG0TzcqgndIyNqLMjSWpNTatDn\n5Jjd5e/Gm+Fwlru3XTDCfEGftayGHKHEWcxE14GgTwghhBBC1D7BBIK/AolKqSitdW51T0gIIYQQ\ndYPT0ExIPciSrFzshoGhTADkG5pFmadYfiKXa2OimNalNWZT9YVeWmtOudxnq/j8IV/R7rsZDicF\n1Rz0hZtUkS67cZaSy3abWkKJkqBPCCGEEELUoGACwbeAJOARPJ2GhRBCCCGK0NoXBpbeOdYAbIbB\nkqwcJqQeZEbXiptFaK056XKXXLZbaM++4w5PZZ+92oM+E3ElqvjMxBXrxBsZYpKgTwghhBBC1HoB\nB4Ja6wVKqT8DLyulNPAvrXV+9U9NCCGEEBeqTbk2lmblVrjUNt/QLMnKYWV2Hk2tZn+45+uyW7iy\nL8PuwhFgM7SK1AsxFVmiG1tGQ476EvQJIYQQQog6JOBAUCn1g/fT08DfgBeVUtuBvHKGaa311UHM\nTwghhBAXoBlpmRRUssFGvqG5Y8u+ar1//RBTyeYbpezZVz80pFrvK4QQQgghxIUgmCXDA4t9HQ70\nrGBM9f46XwghhBC1SoHbYH++nb02O/vy7XybeYrq7bfrEVla0Fdkfz7PHn31JOgTQgghhBCiTMEE\ngmOrfRZCCCGEqPUMrUm3O9lns7PHVsA+mycA3Jtv53CBo8q//esYYS3RfKNpkSW8ZiJCTNXyWoQQ\nQgghhLiYBbOH4CfnYiJCCCGEqB1OOV3+oG+vzc5eWwF7bXb259urvSuvT7jJxOrfdTkn1xZCCCGE\nEEIUFUyFoBBCCCEucHbD4EC+wx/2+Zb67rEVkO10B3w9E9Aq3EK7cCsdIsL4+dRptp7Or1TVoAm4\npnFUwPcUQgghhBBCBEcCQSGEEKKOMrTmqG+Jb76dfbYC9tjs7LPZSStwBLXHX2NzKB0irLSLsNI+\n3Er7CCvtI8JoHW7Bajq7nDcl5wy3/LoXWyUai1hNivGtmgQxGyGEEEIIIUQwyg0ElVIDvJ/atNYb\nih0LiNb6x2DGCSGEEKJ8uS53iT399toK2GdzkF/JTr+FhZsUbcM9QZ8n8POEf+0irDQwV+53id2j\nIrg2JoolWTnkl7PMONykuC4mmu6REQHPUwghhBBCCBGciv6vfiWeDsE7ga7FjgVCV+JeQgghhCiD\nwzA4mO8oFvjZ2WOzk+V0BXw9BcSHWTzVfoUq/dpHWGluNWNSqkrzVUoxrUtrJqQeZGlWLgWGUaQi\n0YSnMvC6mGimdWmNquL9hBBCCCGEEJVXUUh3CE+Yd6SUY0IIIYSoRlprjjtcpVb7HSpw4A7iX99G\n5hBv4He22q9duJW24VbCznHHXrNJMaNrazbl2ZhxKJMlGdk4UYSFhHBN4ygebhVL9yipDBRCCCGE\nEOJ8KzcQ1Fq3qcwxIS5WO3bsYOrUqaxYsYK0tDS01jRp0oT4+Hj69u3L9ddfzzXXXFPT0yzVrFmz\nGDt2bJFjZrOZ6OhomjRpwqWXXsrQoUMZNWoUERGl/8A+efJkXn75ZV566SUmT558HmYtRN1w2uUu\n0cF3nzf8O+MOfImv1b/E9+zS3g4RYbSLsNKokkt8zxWlFD2i6jGzWz3mz98MwMiRI2t0TkIIIYQQ\nQlzsZBmvEEH68ssvGT16NA6HgxYtWjBw4EAaNmxIZmYmKSkp/Pzzz6xatarWBoI+TZs25frrrwfA\nMAxycnLYuXMn//3vf/nqq6+YNGkS06ZN46677qrhmQpxYXEamkMF9hIdfPfZ7Bx3BL7EF6CF1ewP\n+toXaurRIsxCiCy5FUIIIYQQQlSSBIKixmmtSU9PJzk5md27d+N0OjGbzXTs2JF+/frRokWLWre3\n1LFjxxg3bhwOh4O33nqLiRMnEhIS4n/eMAzWrFnDmjVranCWldO5c2dmzZpV5NipU6dIT0/nvffe\n45133uHuu+8mOzubCRMmFDnv0Ucf5fbbbycmJuY8zliI2kNrTabD5encWyjw22uzc7DAjiuIJb7R\noSFFGnn4lvq2CbcScY6X+AohhBBCCCEuDhIIihrldruZN28eO3fuxOVyobXnp2en00lqaiq7d++m\nU6dO3HjjjUUCt5q2cOFCbDYbffv2ZdKkSSWeN5lMDBgwgAEDgmrKXSu0aNGCadOmcckllzBx4kQm\nTZrEDTfcQIcOHfznxMTESBgoLgpnXG725Z+t9ivc1CMviCW+FqVo42/k4V3iG26lXUQYjc0hte6X\nIEIIIYQQQoi6pdxSA6XUCqXUoOq6mVKqoVJqilJqYnVdU1y4tNb+MNDpdPrDwMLPO51OduzYwbx5\n80o8X5MyMjIAiI2NDXjsunXrePrpp+nVqxdNmzbFYrHQvHlzbrnlFtauXVvqmMmTJ6OUYvLkyRw/\nfpyHHnqI+Ph4rFYrbdu25bnnnqOgoKBKr6ksEyZMoFevXrjdbqZOnVrmvEqTmprKfffdR9u2bQkL\nC6Nhw4YMGTKEb775psz77d+/n7vvvpvY2FjCw8NJSEjgjTfewO1206ZNG5RSHDhwoMS4rKwsnn32\nWTp37kx4eDhRUVH06dOH6dOn43IFtzxTXFxchma/zc6yE7m8n5bBMzvTuHnTHronb6P96t+4ZsMu\nxm8/yD8OHON/x0+yOS+/wjCwudVM/4b1GdO8MX/p0IL/XNaOdX26sD/pMn78XWc+vrQtL7Rvzp3N\nGtO7QX1iLKESBgohhBBCCCHOuYoqBPsDy5RSa4F/A/O01rmB3kQp1Re4A7gXqAe8GOg1RN2Tnp7u\nDwPL43K52LlzJ+np6cTHx5+n2ZWvVatWACxfvpytW7fSrVu3So99/vnnWblyJQkJCfTu3Rur1crO\nnTuZO3cuX3/9NZ9//jmjRo0qdWxaWho9e/ZEa02/fv3Izc1lzZo1vPbaa2zfvr3coK0q7r77bjZs\n2MD3339f6TFffPEFY8aMweFwkJCQwPDhw8nMzGT16tUsX76cF198kSlTphQZs3XrVpKSksjOzqZV\nq1YMHjyYU6dO8cILL/DLL7+Uea89e/YwePBg0tLSiIuLY8SIEdhsNlasWMEjjzzCvHnzWLhwIVar\nNejvgagbtNZkOV3+Jh6epb6eph4H8h04g/jFQ2SIifYRYXTwVvr5lvq2jbBSrxZVNgshhBBCCCGE\nT0WBYDfg78AfgD7Ae0qp74GfgI3AFuCE1trtG6CUqg+0BXoBVwI3AK0ABRwDngFmVu/LEBei5OTk\nSlduuVwufv755zKDsvNt5MiRNG/enCNHjtC9e3euvfZakpKS6NmzJ7169SI6OrrMsU899RT/+c9/\naNq0aZHjCxYs4Oabb2b8+PEMGzas1M6+H330Effffz/vvvsuFosF8FTh9e7dmwULFvDTTz9x1VVX\nVe+LBXr27AnArl27/Hs8lmfLli2MGTMGi8XC119/zQ033OB/btu2bdxwww385S9/YdCgQQwa5ClC\n1lpzzz33kJ2dzbhx43jvvff899m5cyeDBg3i6NGjpd7vzjvvJC0tjVGjRjF79mzCwsIAT4A6ZMgQ\nli1bxuTJk3nllVeq/L0QFwab22B/sS6+vsYeOS53xRcoxqwUbcItnsAvPOzsHn8RVmLMUtUnhBBC\nCCGEuLCUGwhqrXcANymlfgc8AfweGA4MK3yeUuo04ACigcLlEL6fkHbhCQFnaK1t1TN1UZPKWiJ6\nrmit2bZtG9u2bavytapj7pGRkSxbtozRo0ezYcMGvv32W7799lvAs39gnz59mDhxIrfddluJsb6O\nvsWNGDGCUaNG8dlnn7FixQqGDRtW4pyWLVvy9ttv+8NAgC5dunDPPfcwY8YMli9ffk4CwSZNmvg/\nz87OLhFmFve3v/0Nh8PB1KlTi4SBAAkJCbz11luMGjWKd955xx8Irl69ml9//ZWGDRsyderUIqFj\np06dePHFF/njH/9Y4l6rV69m/fr1REZG8t577/nDQPB8v6ZOncrQoUN59913eemll4o8Ly5sbq05\nXOAo1MHXzj5v+JduL7/yuCxxFnORsK9duJUOEWG0DLMQapLQTwghhBBCCFE3VKqpiNZ6HXCbUqoR\ncBdwLdAXaOQ9JbLYEAPYCqwBvtRar66e6QpRe3Tp0oX169eTnJzMokWLWLduHSkpKZw8eZLk5GSS\nk5P57rvvSnTwBc9+dwsXLmTr1q2cOnXKXym5detWwFOJV1ogOHjwYMLDw0sc79y5MwBHjhypxld4\nlmGc3SfNZCq/y6lhGCxevBilFLfcckup5yQlJQHw888/+4+tWrUKgOHDhxMZWfw/KZ4qwNICQd+4\nESNG0KhRoxLP33DDDTRr1oyjR4+ycePGcxKYXmy01mzKtTE9LYOlkS1xoHh81WaGNI7m4VZN6B4Z\nUa0VcyccrhIdfPfm2zmQb8duBL7Et16IqUQHX1/4Vz9UlvgKIYQQQggh6r6AugxrrbOBad4PlFId\ngGZADGAFsoEsYLfWOq96pypE7dSvXz/69esHeMKwtWvX8vLLL7N06VI++eQThg0bVmSp8/vvv88T\nTzyBzVZ2sWxubulbdfr2LiwuKioK4Jw1FsnKygJAKUXDhg3LPffEiRP++VfUdCUzM9P/eXp6OgCt\nW7cu9dzo6Giio6PJyckpctw3rm3btmXep127dhw9etR/rgie09BMSD3Ikqxc7IaBoTwBcb6hWZR5\niuUncrk2JoppXVpjDqCiLt9tcKBIF98C/z5/J4NY4huioHVYoQ6+har9YqVxhxBCCCGEEOIiF1Ag\nWJzWeg+wp5rmIi4g1bHs9quvviI1NbVS3YOVUnTt2rXW7CFYFpPJRL9+/fj222/p3bs3KSkpfP31\n1/55b9iwgYcffpjQ0FD+8Y9/MGLECOLj44mI8FRU/elPf+KVV14p83tSUXXeubJx40bAU4kYGlr+\nfzbcbk94ExISwt133x3wvcoLakp7/b7vVXnjalOH6guZ1r4wMIf8UirzDMBmGCzJymFC6kFmdG1d\n5M/F0Jp0u7Ponn42O3vyC0gvcBLMn1KsJdQf9PmDvwgrrcOsAQWSQgghhBBCCHExqVIgKERV9OvX\nj927d1fYZRggNDSUvn37nodZVY+QkBAGDx5MSkpKkSq4OXPmoLVm4sSJPPXUUyXG7dlTO/P1Tz/9\nFIBrrrmmwnNjYmIIDw8nPz+fd955h/r161fqHs2bNwfg4MGDpT6fm5vLyZMnSxz3dZ7et29fmdfe\nv38/AC1atKjUXETpNuXaWJqVW2oYWFi+ofkuK4d/7D+GG/xLfffn2ykIYolvRIiJ9uFFO/i29waA\nUbLEVwghhBBCCCECJoGgqDEtWrSgU6dO7Nixo9xuw6GhoXTq1KlWhTla6wqXHB46dAg4G1iBpyEH\neJpdFJeZmcn3339fjbOsHtOmTWPjxo2YzWYef/zxCs8PDQ1lyJAhLFiwgDlz5nDvvfdW6j4DBgwA\nYOHChZw+fbpEkPj555+XOs63H+GCBQs4efJkiSXNS5Ys4ejRo9SvX9/fLVkEZ0ZaJgWF9pMsj93Q\nvHXweKWvbQJahVtKdPBtH2ElzmKWJb5CCCGEEEIIUY1qZv2hEHiWeN5444107twZs7nkD/xKKcxm\nM507d+bGG2+sVYHA9OnTGTt2LL/88kuJ51wuFzNnzmTOnDkARToN+5p/zJ49m9OnT/uP5+XlMW7c\nOE6dOnWOZ155R44cYeLEiTz22GMA/Otf/yp3n77C/vznP2M2m3nsscf44osvSizZNQyD5cuXs3jx\nYv+xpKQkLrvsMrKzs3niiSeKhMS7d+9mypQppd6rf//+XHnlleTl5fHII49gt9v9z6Wnp/tDzEcf\nfVQ6DAfBaWh2nylgUeYpvss6ReXiwLLFmEP5XXQ97mzWiBfaNWNWt7b82LszB5IuY22frvzn8nZM\n6diCMS1iSGwYSTOrpVb93RdCCCGEEEKIukAqBEWNCgkJ4eabbyY9PZ3k5GR2796Ny+UiNDSUSy65\nhH79+tWqykAfp9PJrFmzmDVrFnFxcVxxxRU0atSI7OxstmzZ4u/2+8wzz3Ddddf5x40dO5apU6eS\nkpJCu3btSExMRGvNjz/+iMViYdy4cXz00Ufn9bXs2LHDX8VnGAa5ubns3LmTnTt3orWmcePGTJs2\njTvuuKPS1+zVqxezZ89m3Lhx3HHHHTz33HN07dqVyMhIDh8+zK5du8jKyuLZZ5/l+uuvBzwB8OzZ\nsxk0aBAzZ85k6dKl9O3bl1OnTrFixQqGDx/O+vXrOXToEBaLpcj9PvvsMwYNGsTnn3/OqlWrSExM\nxGazsWLFCs6cOcPVV19dLfte1mUOw2Bfvp1dZ+zsPJPPrjN2dnmX+jqrsAfjpNZN/Ut924VbaWCW\nf3aEEEIIIYQQoqbJT2aiximliI+P59Zbb63pqVTafffdR5s2bVi2bBm//PILv/32GxkZGZjNZuLj\n4xkzZgz3338/iYmJRcY1bNiQDRs28OKLL/L999+zaNEiYmNjuemmm5gyZQrvv//+eX8tx48f55NP\nPgHAbDYTFRVFbGwso0aN8ndIDg8PD/i6t99+O1deeSVvv/0233//PatWrQIgLi6OHj16MGzYMG65\n5ZYiYy6//HLWr1/Pn//8Z5YuXcq8efNo27YtL730Ek888QRRUVGYTCYaNWpUZFyHDh3YtGkTr7/+\nOvPnz2f+/PmYzWYSEhIYPXo0Dz74IGazOcjvUN1S4DbYm29n15kCz4fN87gv3467mnuvhJtMPNuu\nWfVeVAghhBBCCCFElSnpvnlxUEqtBJKSkpJYuXJlueempqYC0KVLl3M+L1E7+ZYuN2jQoIZnctbq\n1asZMGAA3bp147fffqvp6QTsfP+9srkN9njDvrPBn50D+faAl/22sJq5pF4YB/Pt7M93VKobsAkY\n3qQB/+7WJvDJizpr/vz5AIwcObKGZyJqO3mviEDI+0VUlrxXRCDk/SIqq1u3bmzbtg1gldZ6YA1P\np9KkQlAIUWucPn2atLS0EqFZamoqDz74IEClm5RcLE673Oy2eSr+dhaq+EsrqFxwV1jLMAuXRITR\nqV4Yl9Szckm9MDpGhBHp7eSbknOGW37di60SjUWsJsX4Vk2CeEVCCCGEEEIIIc41CQSFELXGsWPH\n6Nq1Kx07dqRjx47Ur1+fAwcOsHHjRtxuN4MHD2bixIk1Pc0akety+6v9dhaq/Eu3OwO6jgLahFu4\npF4Yl0SEeR7rhdEhwkq9kJByx3aPiuDamCiWZOWQb5QdN4abFNfFRNM9MiKguQkhhBBCCCGEOD8k\nEBRC1BqxsbE88cQT/PDDD6xbt46cnBzq1avH7373O26//XbGjx9f5/cCPOl0Fdnbz9fc42iAwV+I\ngrbh1iKh3yURVtpHhBEeElyDeaUU07q0ZkLqQZZm5VJgGEWWH5vwVAZeFxPNtC6tpTuwEEIIIYQQ\nom7SGtI3QvLbND69s6ZnE5SgA0Hl+UnvRuAaoCUQrrW+utDz9YCegNZar67qRIUQdV9UVBRvvvlm\nTU/jvMhyFA3+fMt9Mx2ugK4TqqBduGeJbyd/8BdGuwgrVlNwwV95zCbFjK6t2ZRnY8ahTJZkZONE\nERYSwjWNo3i4VSzdo6QyUAghhBBCCFFHuZ0wbzzs/BZcBaiAN2uqHYIKBJVSHYH/AV3xrEADSnwH\nCoAPgPZKqSu11ilBz1IIIS5AWmtcWlNgeB6P2Z38v5Td7LIVkO10B3Qti1J0iLAWqvbzPLYNt2I2\nnd9KPKUUPaLqMbNbPebP3wzIZstCCCGEEEKIi4DW3jBwETjza3o2VRJwIKiUaggsw1MVuBmYAzwN\nRBY+T2vtVkpNB94CbgYkEBRC1Elaa5xaYzc0BYZBgdvzaDcM3N5flbgMzQmni7VnzpR7rTCTomNE\n4dDPEwK2DrMSep6DPyGEEEIIIYQQhaRv9FQGXuBhIARXIfgknjDwO2Ck1tqllHqUYoGg1wI8geAQ\n4PmgZymEELWAL/grMDQFbsMb+nnCv3J6bJQqIsRER1/Fn7ezb6d6YcSHWQiRvfeEEEIIIYQQonbR\nGtZMBVdBTc+kWgQTCI7Eszz4Ka11uZtdaa33KqXsQIdgJieEEDVBa41D+0I/jd04+xho8GdSEGYy\nYVPQ3GrmP+3bcEm9MFpYzZgk+BNCCCGEEEKI88+ZD7ZsyD/p/fB+XuTYyZLH3Paannm1CSYQbAvk\na61TK3n+aSA6iPsIIcQ5pb3LfH2BX+GKPx1g8BeiwGoyEWYyERaiCDOZsJoUZqVQSpFqMtHEYqJL\n46hz82KEEEIIIYQQ4mLjLCgn0Cv0ua3YsTpS5VcVwQSCurLjlFIWPGFgbhD3EUKIamFojcO3v58/\nAPSEf8EEf57QzxP4hZlMhJkUod7gTwghhBBCCCFEgFz2Uiryskuv0it8zHXh7+VXU4IJBPcDCUqp\njlrr3RWcO9R7j8pWEwohRNCMQo09/FV/bgO71iX7oFcg1KSKBH6eij/Tee/oK4QQQgghhBAXDJej\nWHBXTuWerdB5zvKbL1Y7kxkiGkF4Iwhv6PmI8D4WOdao6LGvH4bUb0Ab53e+50AwgeAioBue5iLj\nyzpJKdUEeAPPj+Hzg5qdEEKUwhP8FVrm6+vqG0TwZy4W/PmW/UpHXyGEEEIIIcRFy+2E/FOVWIpb\nrHLPcfr8ztMUejasKxLeNSh2rGHR88wREMwKr34TYPdScNqq/7WcZ8EEgm8CDwIPKKVswD8LP6mU\nigVuAl4AmgPpwIwqzlMIcRFyFwr+7O6zAaAj0M4eeIK/woGf73MJ/oQQQgghhBCAp4ts+kZIfpth\nqd8Roh2wNRw6Xgf9JkKLHsGFSDXJ7YKCU5VYiltsvz1H3vmdpym0ZHDnD/QalAz0fM9b6p/fP5MW\nPaHTUNix6IJfrhxwIKi1zlJKjQQWAI95PwBQSmUBDX1fAtnAH7TW57n2gA3DTAAAIABJREFUUwhx\nIXFr7/5+7qKVf84ggj+LP/RT/gYfVpOJkAvtH24hhBBCCCHE+eN2wrzxsPNbcBUQ6lsS6sz3LBHd\nvdQTBN34HoSYz//8DLe3Yq+8Cr3i1XynwJ5zfuepQgoFe6VV6DUovWrPGnlhhK1Ked4Dhd4rF6pg\nKgTRWq9RSl0O/B24BbB4n2rkfXQBc4HntNYHqzxLIWqhNm3acPDg2be3Uor69esTHR1Np06duPLK\nK7njjju47LLLqu2ekydP5uWXX+all15i8uTJ/uMrV65k0KBBJCUlsXLlyqCurbXG5jbIdLrINZnR\nKA7l2YgKDaGJJZQIk6nKTTNcJTr6ej4PNvjzV/qFnK34k+BPCCGEEEIIERCtvQHPIk8AWOJ5w7NE\ndMciz3k3fxB8eGW4oSCn/ECvtMq9gvMd7JkgrIzwrsixYuGfJRJMpvM71/MtxOx5D6SnQPLbaPVZ\nTc8oKEEFggBa60PA3Uqp+4FeQDPABBwHNmitz/PCcSFqxnXXXUdcXBwANpuNzMxMNmzYwPLly3n1\n1VcZMWIE//73v/3n1EaG1qQVOMhxub1ddz3/uGkNOU43eS43UaEhtAyzYKrEP3wuf0dfw9/ko8DQ\nuAIN/hRYlSrW0dfzeWXmIYQQQgghhBAVSt/oqfYqLQwszJXvOS89BZp391Tf2bIrqNwrdqwgh4A3\nPq8SVXLJbWnNMoo31bBG1f1gryqUgviecOsnnJiyEdhW0zMKWNCBoI/WugBYUw1zERcprTW5uZs5\ndOgDsk6sxDAKMJnCiIkZRKtW9xMVeVmVK9POpeeee46BAwcWOWYYBgsWLOCJJ55gwYIFJCUlkZyc\nTOPGjWtmkuXQJcLAkgwNOS43FDhoFWZBKYXWGlehrr6FG3y4yrpQGZQqWvHn6+grwZ8QQgghhBDi\nnEueVvmln04bfHw9GK7z3GlWQVh0BYFeKZV7YQ0k2BOlqnIgKERVGIaT7dufIjNrOYZhBwzv8Xwy\nMhaTlbWCJjFX07XrG5hMNbBPQ5BMJhMjR45kwIAB9O7dm127dvHkk08ya9asmp5aCTa3QW45YaCP\n9oaCB/MduLx7/rkDLfhTlKj0CzOZsEjwJ4QQQgghhDjfCnLg2G+epcCBhHtuR9Xua40uWo1X5n57\nhY6FRYMppGr3FaKQgANBpVQP4A1go9b66QrO/RdwKTBJa705uCmKukpr7Q0Dl2EYpf02xsAw8snM\nWsb27U+RkDC1VlcKlqZhw4ZMnTqV4cOH8+mnn/Lqq6/6lw4vW7aMefPmsWbNGg4fPszp06eJi4tj\n4MCBPPfcc3Tp0qVa5lDRfcLbtKP4Sl57QQH/mf4OS+f9j4N79+ByOolu2JDmrVrTO2kgDzz9LNaw\nsDLvqRRFOvmGFQr+LrQ/QyGEEEIIIUQdcDoDjm6BY5vh6GbP5yf3V+2a1ijvctzS9tYr41hYNIRI\nbZaoecG8C8cAScDMSpy7FZgAjAaeDOJeog7Lzd3srQwsvzTbMArIzFpObt4WoqMuP0+zqz5Dhw6l\nUaNGZGdns2LFCu644w4Axo8fz+HDh0lISKB///4opdi6dSuzZ89mzpw5LFmyhMTExCrfv/B9rkpM\nRCvFtq3bmD17Nv+dM4fp/5tP9779/OcbhsGEUTfxy4+rqB8dTc+rEqkfFUV2RgYH9uzmgzde5/YH\nH8IaFodJUSTws5o8+/1ZlAR/QgghhBBCiBqgNeSknQ39jm6GY1sg72j13SM0HP5fWs10GxaimgQT\nCA7yPv5QiXMXAO8Dg4O4j6jjDqV96F0mXDHDsHPo0Idc2u3tczyr6qeUonv37ixfvpxt285uNPrG\nG28wcOBAGjRo4D+mtebf//4348eP58EHH2Tbtm0BBWsaOONy49Aah6FxGAZP/e3vXHFVf8Kjo/17\n12qtmfvxR/x10kT+8tgE5q7b4L/Ppp+T+eXHVXS5/Ao++m4p4fXqFZnfr+vWktC0CY3qh2GW4E8I\nIYQQQghRUww3nNjrCfyO/no2ACw4VbnxplCI7eJZOnwqjUo1+1Am6HSDhIHighdMINgSyNdaH6/o\nRK31MaVUvneMqEOW/9D+PN/RICNjEct/WFTlK109eG81zCcwTZo0AeDEiRP+Y3/4wx9KnKeU4qGH\nHmL27NkkJyezfft2EhIS/M9r70Z/drdBpsPpDf00h/I9weoZt8EeW9GQte8Nw72Di97nlnH3seCL\nz9i8bi17d6TSoUtXzxwzMgDo3q9fkTDQN65H377ERUYE820QQgghhBBCiOC4HJCZWrTq79hWcJ6p\n3PjQcIjrBs0uh7jLPI+xXSDUCoc3wCcjPA1DKrxOGPR9tGqvRYhaIJhA0Iyv80PluAFJD8RFzTA8\nf2VMxbo7HT58mEWLFrFjxw5yc3Nxu90YWnP02DEA1m3bTmS7DtgNjUNrjjtcAJx0uTlS4PRfx1F8\nE8Bijqens3rJYg7u2UV+Xh4Ybkwocrzh36E9e/yBYJfLryAkJISv/282rdt3ZMjIkTSObeq/VlSo\nbGQrhBBCCCGEOIccZzxh3zFv+Hd0M2SkguGseCx49unzhX6+j8Ydym7K0aIndBrqaS7iyi/7uqHh\nnvNa9Aj8NQlRywQTCKYDHZRSnbTWO8s7USnVCagPVHGnTiEubFlZWQA0atQIl6FxaIOXX5rMW6+9\nisvlKnNcevZJTjrdlb6PAsJCFBblaeBhMSne/MsU3ny1/Pucycv1f96yXTueeuU13nrhT7zy1CRe\neWoS8W3acvnvfsegYcN54LZRlZ6PEEIIIYQQQpQr/2TRqr+jmyFrN5VavgtQPw6aXVYoALwMGrT2\ndDqsLKXgxvdg3njY+S24Cop2HVYmT2Vgp6Ge82TbJFEHBBMIrgA6Ai8Dt1dw7hQ8f4tXBHEfUYtV\nx7Lb37ZOICNjMZUrODURG3vDBbGHoKE1Tm9Fn90wsLsNNm7aBEB0h0vYdjqfZfO/5vW//ZV6kZH8\n6W+v0ntAEjFxcYSFhwPw3H33snjOf/1LhIuzmBSNzKH+0O9omGf/inohJjrVC/efN3fuXF7761+J\njIzkrbfeYvDgwTRr1oxw733uvPNOPv/8c8JMCqU8++8C3PHQw1zzhxtZsXAhm9Yms2ntzyz68gsW\nffkFn771BqtWrSIqKuocfQeFEEIIIYQQdY7WkPf/2bvz+CjLe///r2uWZCZ7IAlIEhAUUOsK1Urq\nVrW11VrMQahf+23dPVqXbnq09Xcs9nuOrafWWm2LVqvgae2jagtoQQtuuMRaETckoSiyRSAJ2ZOZ\nzHJfvz/ueyYzk5lktqx8no/HPO6Ze73uMGR5z+e6rn3RVX/73of2Xcmfo2RGf+h3yPFmCFg4Zejj\nkmF3wqKHoXET1N1HoGEtdsOPcrphzpeh5nqzklCICSKdQPBe4ApgsVLKD/yH1jpquh6l1CHAz4HF\nmF2G7820oWLimV59BS0tL2EYg5RkW2y2XKZPv2IEWjU0rTUBrcOfV7X6Auzy9IUn8vDHdN995bln\n6Whrw+FwMP+UUwFYv2olADfcvpR/u+TSqP3tCho/2Q6Y3XOrXDnh4G9KjvlfdpLTQbU7J3yMyx6/\n9P3JJ58E4M477+TKK68csP2jjz4Kn6/YYaczECTU/LIpU1l8xZUsvuJKlILGLR9yy1VX8O677/Kz\nn/2MO++8M8mvmBBCCCGEEOKgojW07Yiu+tv7PvQ0JXe8skHZnOiqv6nHgLt0WJuNUlA1H5asYM3q\n1QAsXLhweK8pxChJORDUWjcopb4P/Aq4GPi6Uuo9IBTrzwCOBUIJxc1a683ZaKyYWIqKjqO87Cya\nW57HMLwJ97PZXJSXnUVR4bEj1rZgxCy9/TP2avq0gc/QaA1+q5yu1R9I2K23s62Nn//wFgDO/z/f\nYFJ5BUpBV3sbAIfPmM40l5Mcpcixmd18/9XQQP177wFQ4nQwOaf/v2mqM/q2trYCUF09cF6f+vp6\n3rEqF21KMd2VQ69h0OwL0OkPoDGrBoscdipyHBz7uRP59Dvf4corr+Q9q31CCCGEEEKIg1wwAAe2\n9Yd++943l30dyR1vz4GKo6yqv+Ng6nEw5TOQI1MRCDGc0qkQRGt9v1JqH3APUAnMtx6RGoEfaK2f\nyKyJYqJSSnHUUXezZctNNLe8gGH0Ed192IbNlkt52VkcddTdKYdhg9Fa49fanKzDGtMvFPr5DLMC\nMBN2NK8/9yw//eEt7N6+ndlzj+C+X9zNlAIXDqWY/5mjqHvxBVauWM43F36NHKfZ5bepqYlLLrlk\n0PH+UnHEEUewfv16HnroIb7yla+Qk5OT8DpKKfLtdt58YwMtLS2ceeaZlJWVhbcHg0HWrl0LwIwZ\nM7LSPiGEEEIIIcQ44vdC05boqr/9m80x95LhzI8Y788KAMvmgiNn6GOFEFmVViAIoLV+Uim1EjgL\nOBmYgjmnwT7gH8ALWuvspBpiwrLZnHzmM/fS2fU+u3Y9bHUh9mKzuSgrO5MZ06+kqCj1ykCtNUFN\nOOjrM0IBoPnarzWZZH42BaH5gv/4q3t4/s+PY0fh6/PS2tLCpk2baG9vB+CCCy7gwQcfpKK8P1z7\n7ne/y2OPPcaaNWs4/PDD+dznPofH42HDhg1UV1dzwQUXsGrVqvQbmMF13n//fb73ve9RVFTE/Pnz\nOeSQQ+jt7eXNN99k7969TJ06lVtuuSXjtgkhhBBCCCHGsL4u2PdB9IQfzQ1gJPlnvntSRNWfNebf\npFlgsw19rBBi2KUdCAJYgd/frYcQaVFKUVx0HMccfX9Kxxmhrrza6tobnsjDfG1kUuSnsLrxKnJt\ntvDzHJs5g69dgcOqWHx5/frwfeTn51NSUsL8+fM56aSTuPjiizn66KMHnH7WrFls2rSJ2267jdde\ne41nnnmGyspKrr76am6//Xa+853vZND4zK5z/vnns2/fPurq6vjoo4+oq6ujoKCA6dOnc80113Dt\ntddSXl6elfYJIYQQQgghxoCeA7Dvvf6qv73vQet2kp7pt6gyuupv6rFQXCWz8QoxhmUUCAoxnEKT\nd5hj90WM6WcFf7GTd6TKYVMDgr5c67lTqSG7KO/YsSOj68+aNYs//elPcbctX76c5cuXD1i/dOlS\nli5dOmD9GWeckXBG4lSvc9hhh3HrrbcCUFJSkvgGhBBCCCGEEOOL1tDZGF31t/d96NyT/DkmzYqo\n+jvOfOSXDX2cEGJMkUBQjKrIyTv6wtV+/ZN5ZNKtVynMCj9liwj9+ifvsMunVUIIIYQQQoiJyjCg\n7RPY+250ANh7ILnjlR3Kj4iu+pt6DLiKhrfdQogRMWggqJR60Xq6U2t9Wcy6VGit9VlpHCey7B/t\n3Vy1eQfXTi/nhMK8rE7UEY/WOmqW3lDQF+rWG8ysyA+nFfTlRgR9oao/RxJVfkIIIYQQQggx7gX9\n0Lw1ourvPdi3GXxdyR3vcJkz+4ar/o41Z/51uoe33UKIUTNUheAZ1rIhzrpUZBj7iGwxgDXN7bxw\noJMvlRVx/5EzcNrSD81Ck3f0Rc3Sa/SHgFpn9K9vVwwI+kJj+jltCpsEfkIIIYQQQoiDid8D+z+0\nxvuzAsD9WyDYl9zxuUUDx/srmwN26UAoxMFkqP/xl1nLjjjrxDhlAL2Gwd9bOrihfifLjpoxaCWd\nEdmtN7LazwoBMxnKT0VM3pETZ/IORwZhpRBCCCGEEEKMa552c6bfUNXf3vehZStoI7nj88r6x/kL\nBYAlh8pMv0KIwQNBrfWKZNaJ8cljaNa1dLKps5dDcp3s9PrY5fFR0ednktPOth4vPq0JZGnyjtyI\noC8nhck7hBBCCCGEEGLC626yxvp7tz8AbNuR/PHF083QL7Lbb+EhMtOvECKulGuClVJfs57Waa1b\nstweMcJ6DYOvbtoW1av33vwgRQ47vcHkPnWyWZN3RAZ9kWP6SbdeIYQQQgghhLBoDe27oqv+9r4H\n3fuSPIGCyYdHV/1NPRbyJg1rs4UQE0s6gwSsAgKAfLeZIIas/4vs1hs5eUeoW69CqvyEEEIIIYQQ\nIpYRhAMfmaHfvvf6A0Bve3LH25xQcYQV+lkB4JSjIbdgeNsthJjw0gkEWwG01t1ZbosYRZOcdqa7\ncpnhzqHC30mOTXFoXm64W69U+QkhhBBCCCHEIAI+aK6Prvrbvxn8vckd73DD1GOiq/4qjgRH7vC2\nWwhxUEonEPwQqFFKFWmtO7PdIDHy3DbFllOOCb+ur68HoNBhH60mCSGEEEIIIUTmtIbGt6HuPs6r\nfxa79sFmN8w+B2puhMp56Y2x5+uBfZutWX6tALCpHgx/cse7ivtDv9CkH5MPB5v8DSaEGBnpBIK/\nA04FbgD+O7vNESPNBnxxcvFoN0MIIYQQQgghsivoh5XXwNa1EPDiCM3M6/dA/dOwbR3MPRdqHwC7\nM/F5elut8f6sqr9970PLNpIYfMlUMDW66u+Q46Bkukz2IYQYVSkHglrrPyqlTgLuUEq5gF9qrVuz\n3zQxEnJtimuml492M4QQQgghhBAie7S2wsA1ZgA4YLthduVtWGPut+hhc33Xvv7QL9T1t2NX8tct\nPTS66m/qsVA4JSu3JIQQ2ZTOLMMvWk97gR8BtyilPgKagWCCw7TW+qz0miiGi9umOKesmBMK80a7\nKUIIIYQQQgiRPY1vm5WB8cLASAEPbFkF7TuhbQf0NCd3fmWDsjnRVX9TjwF3ScZNF0KIkZBOl+Ez\n4pzjCOuRSJK11GIk2DArA88pK+b+I2fIDMFCCCGEEEKIiaXufgh4k9vXCMCetxJvt+dAxVFW1d+x\n5my/Uz4DOVJYIYQYv9IJBC/LeivEiLGh+Gp5CddOr+CEIvkBJoQQQgghhBiHjKBZzdfZCJ2fWo9G\n6LBe73qDtOpScgrMSr9wt99jofyIwccYFEKIcSidMQRXDEdDxMg4uSSf3x196Gg3Y8JoaGjg3nvv\n5aWXXmL37t1orSkvL6eqqooFCxbw5S9/mS9+8Yuj3cy4Xn75Zb7whS8wY8YMduzYMdrNEUIIIYQQ\nwhQMQPe+/pAvMvALPe/aa1b2ZY2C6zfCpFlgs2XxvEIIMTalUyEohAD+/Oc/861vfQufz0dlZSVn\nnHEGpaWlNDc3s2nTJt544w02bNgwZgNBIYQQQgghRlygzwzzBoR8EWFf935z0o+R5HRD2eEje00h\nhBhFSQeCSqlc4AJgPlAEtANvAs9orbP50Yw4yGiteaezl9/ubuKFA514DY3Lpjh7cjHXTi/nhMK8\nMTfO4b59+7j88svx+Xzcc8893Hjjjdjt9vB2wzB47bXXeO2110axlUIIIYQQQowgvyci6PsUOvcM\nDP6SnbQjGXmToWgaFFVay4jnr98P219MLlhUNpjz5ey1SwghxoGkAkGlVA3wJDA1zuYdSqkLtNYf\nZLVl4qDgNzQ31O/k7y2d9BkGoR/XHkOzprmdFw508qWyIu4/cgZO29gJBf/2t7/R29vLggUL+N73\nvjdgu81m47TTTuO0004bhdYJIYQQQgiRZX3dg3fh7WwET2v2rpdfER3wFVdGB3+Fh5hVfYnkFMCu\nOvD3Dn0thwsWXJ+9tgshxDgwZCColKoE/gYUAwowgBag3Ho9E1irlDpaa90xjG0VE4zWoTCwA48x\ncMBfA+g1DP7e0sEN9TtZdtTYmRG5qakJgIqKipSPffPNN3nqqafC4w62tbVRVlZGTU0NN910Eyef\nfPKAY5YuXcodd9zBj3/8Y6699lpuv/121qxZQ3NzM9OmTePrX/86S5cuxeVyZXxvIbt27eJHP/oR\nzz33HI2NjeTl5XH88cdz1VVXcfHFFw/YPxgM8tBDD/HYY4/x4Ycf4vF4KC0tpbKyki984Qvceuut\nlJeXRx3T09PDb37zG5588km2bt2K3+9n1qxZLF68mJtuuomCgoKs3Y8QQgghhIhDa/B2DN6Ft/NT\n6MvSn3rKBgVTB1b0RT4vPAQcOZldp3I+zD0XGtZAwJN4P4fb3K9yXmbXE0KIcSaZCsHvACVAm/X8\nCa21TynlAq4E7gKmAVcA9wxXQ8XE805nL+taOuOGgZE8hmZdSyfvdPUyryh/hFo3uOnTpwPwwgsv\nsHnzZo4++uikj73tttt4+eWX+cxnPsNJJ51Ebm4uW7du5S9/+QurVq3iT3/6E4sXL4577O7du5k/\nfz5aa2pqaujs7OS1117jrrvuYsuWLTz99NNZub+NGzdy4YUX0tHRwcyZM6mtreXAgQNs2LCBl19+\nmeeee44VK1ZEBbRXXHEFK1aswO12c8opp1BWVkZLSwsff/wx99xzD4sXL44KBPfs2cM555zDli1b\nKC8vZ8GCBbhcLt566y3uuOMOVq5cycsvv0xpaWlW7kkIIYQQ4qCjNfS2Jgj5Ip77e7JzPZsDCqdF\nBHyRgZ+1LJgC9hEYyl4pqH0AVl4DW9dCwBvdfVjZzMrAueea+42RwgMhhBgpyXwn/iLmfO03aq3/\nGFqptfYCv7aCwf8BvoQEgiIFy3Y34zWSGyzYaxg8sKuZ3x09NgLBhQsXMm3aND799FNOOOEEvvSl\nL3H66aczf/58PvvZz1JcXJzw2Jtuuok//vGPTJkyJWr9M888w6JFi7jmmms477zzyMvLG3DsI488\nwpVXXslvfvMbcnLMT03r6+s56aSTeOaZZ3j99df5/Oc/n9G9eb1eLr30Ujo6Ovjud7/L3XffHR4f\ncfPmzZx11ln87//+L5///Of593//dwB27tzJihUrqK6u5q233hpwb++++y7Tpk0Lv9Zas2TJErZs\n2cL111/PXXfdFb5fj8fD1VdfzR/+8Ae+973vsXz58ozuRwghhBBiQjIM6G1JHPJ17DEn7wh4s3M9\ne27iir7Q8/zysTVDr90Jix6Gxk1Qdx+BhrXYDT/K6TbHDKy53qwkFEKIg1AygeAszEDwLwm2P4kZ\nCM7KVqPE2Df1pXdH9HoG8HRzO09n4br7vnB8xucoLCzk+eef51vf+hYbN25k7dq1rF27FjDHDzz5\n5JO58cYb+frXvz7g2C9/Of6Axeeffz6LFy/m8ccf56WXXuK8884bsE91dTX33XdfOAwEOPLII/nm\nN7/JsmXLeOGFFzIOBJ988kkaGxuprq7mf/7nf6ImSzn66KNZunQp3/72t7n77rvDgWCoC/W8efMG\nhIEAxx8f/TV/7rnneOONNzj55JP51a9+hS3iF0e3280DDzzAunXr+OMf/8gvf/lLqRIUQgghxMHF\nCJoz7SbswtsInXvB8Gfnes68wbvwFlWaE3iMxyo6paBqPixZwZrVqwHzw30hhDjYJRMIFgL7rYrA\nAbTWO61ug2OjdEuIEXLkkUfy1ltvUVdXx5o1a3jzzTfZtGkTbW1t1NXVUVdXx7PPPhu3wq2lpYW/\n/e1vbN68mfb2dgIBc6LuzZs3A/Cvf/0rbiB45pln4nYPHDz5iCOOAODTTz/N+L42bNgAwOLFi3E6\nnQO2X3bZZVx33XV89NFHNDY2UllZyRFHHEFhYSFr1qzhzjvv5Bvf+AYzZsxIeI1QeLpo0aKoMDAk\nPz+fz372s6xdu5a33nqLL33pSxnflxBCCCHEmBD0m5V7g3Xh7doHOpid6+UWDd6Ft2gauErGZ9gn\nhBAibckO3jD4IG8m+QkiDko1NTXU1NQAYBgG//jHP7jjjjtYt24dK1as4LzzzosaE/DBBx/k+9//\nPr29iWc86+zsjLs+NHZhrKKiIsDs7pupxsZGgISBnsvlYtq0aTQ2NoYDwcLCQh555BEuv/xybrvt\nNm677TYqKytZsGAB5513HhdddFHUhCfbt28H4Oabb+bmm28etD3Nzc0Z35MQQgghJhitofFtqLuP\n8+qfxa59sNkNs8+BmhvNCSJGI+Dye2PCvjiBX3cTyf15lQR36eBdeAsPAVdRdq4lhBBiQhmB0VzF\nRJSNbrdXbd7BmuZ2khlF0AZ8tbyE3x19aMbXHU42m42amhrWrl3LSSedxKZNm1i1alU4ENy4cSPX\nXnstDoeDn//855x//vlUVVWRl5eHUoof/ehH/PSnP0Xr+L8kxqumy7bQtQeb0Tle+y688ELOPvts\nVq9ezSuvvMLrr7/OU089xVNPPcXSpUt59dVXqa6uBswZiQFOP/10Dj300EHbM1iloRBCCCEOQkF/\n1EQRjtBEEX4P1D8N29b1TxRhH9jbIW2+HrOb7mATdPS2ZO96eWWDd+EtmgY5A8ecFkIIIZKRbCA4\nSSn1Ygb7aK31WSm0K2uUUm7gBmAxMBvIAfYDG4F7tdavx+xvA64FLgOOAILA+8BvtdZ/GuJaF1vH\nHgvYgQbgUWCZ1npA7qWUehk4HbhMa708zvYqYL3VjteAr2qtO5K89THv2upyXjjQSW8SE4vk2hTX\nTC8fcr+xwm63c+aZZ7Jp06aoCrennnoKrTU33ngjN91004DjPvroo5FsZlxVVVUA7NixI+52r9fL\n3r17AaisrIzaVlJSwiWXXMIll1wCwMcff8xVV13FSy+9xC233MLjjz8OEA4GFy9ezHXXXTcctyGE\nEEKIiUhrKwxcYwaAA7Yb4O+FhjXmfoseTq5S0Ns5eBfezkbwtmfpJpQ50+5gXXgLDwGna+hTCSGE\nEGlKNhDMAc7IYJ8s1cSnRik1E1gHHA40ARuAPuBQYCHwHvB6xP524K/A14BO69hc4CzgcaXUAq31\njQmu9Rvg24AXeAHwW8f9GjhLKbVY6+QHAlFKHQ48D8wA/g78m9Y6cR/TceiEojy+VFbE31s68BiJ\n3yJum+KcsmJOKBw7n4BqrQetoAPYtWsX0B+wAbS2tgL9gVik5uZm1q9fn8VWpuf000/n97//PX/5\ny1+46667cDiiv02sWLECrTWHH374gEAw1mGHHcZtt93GSy+9xHvvvRde/5WvfIWHH36YJ598UgJB\nIYQQQiSv8W2zMjBeGBgp4DH3a3wbJs1KHPKFnvu6stM+ZTfDvMFSKJsrAAAgAElEQVQm6Cicmt3K\nRSGEECINyQSCK4a9FcNAKZWPWV13GPD/gP+ntfZHbJ8MTI457LuYYeAW4Eyt9X5r39nAq8ANSqkX\ntNarY661CDMM3AecprXeZq2fArwE1ALXA79Ksu3HYIaRU4GngG9orX3J3/34oJTi/iNncEP9Tta1\ndOI1jKjuwzbMysBzyoq5/8gZQwZwI+m3v/1tuPvvSSedFLUtEAjw6KOP8tRTTwFEzTQcmvzjscce\n44orrqCgoACArq4uLr/8ctrbs/XJc/oWL17MD3/4Q3bu3MkPf/hD7rrrrnBX5S1btvDjH/8YIKrC\n8Z133uFf//oXX/va1wZMevLMM88A0V1/L7jgAubPn8+GDRu45ppruPPOO5k0aVLUcdu3b+fZZ5+V\nwFAIIYQQ/eruh0CSYyb7e+H3X8re5Bw2JxQdYgV7sVV91rKgAmz27FxPCCGEGEZDBoJa68tGoiHD\n4P/DDAMf01rfHrtRa30AOBB6bVUH/of18tpQGGjtu00pdQuwHLgNiAoEgR9ay1tCYaB13H6l1LXA\ny8CtSqn743UdjqSU+hzwLFAK/B64eqhjxjOnTbHsqBm809XLsl3NPH/ADAZdNhtfnFzEtdMrOKFo\n7FQGhvj9fpYvX87y5cuZOnUqxx9/PJMmTaK1tZX3338/PNvvf/zHf3DOOeeEj7vsssu499572bRp\nE7NmzeKUU05Ba80rr7xCTk4Ol19+OY888siI3kvsuIQul4tHH32UxYsXc/fdd7Ny5UpOPPFEWltb\nefnll/H5fHzzm9/k6quvDh+zc+dOLrroIvLy8pg3bx7V1dX4fD7eeecdtm/fTmFhIT/5yU+irrlq\n1SrOPfdcHnzwQR5//HGOO+44qqqqaGlpYdeuXfzrX/9iypQpEggKIYQQByutobcV2ndCx25o3wUN\nfzO7BSd9jiTDQIdrkPH6rOd5ZTAC4zkLIYQQI2FCTiqilMoBrrJe/izJwxYAFcAerfUrcbY/CTwE\nnKiUqtRaN1rXqgLmAz5rnyha6w1KqUagEjgZqBuk3Wdiho0FwD1a6x8k2fZxTSnFvKJ8Hjo6f7Sb\nkrQrrriCQw89lOeff55//vOffPDBBzQ1NeF0OqmqquKSSy7hyiuv5JRTTok6rrS0lI0bN/Kf//mf\nrF+/njVr1lBRUcG//du/8ZOf/IQHH3xwxO7B4zG72uTnD/y6n3jiibzyyissW7aM5557jr/+9a+4\n3W5OPvlkrr76ai6++OKois2TTz6Zn/70p2zYsIGGhgbefvttcnJyqK6u5gc/+AE33HDDgMlBqqqq\n+Oc//8nvf/97nnjiCT744APefPNNJk+eTGVlJTfddBO1tbXD+0UQQgghxOjRGnqazaAv8hEK/9p3\ng78n8+s486E4zjh9kdV97tLRmZVYCCGEGCUTMhDEDOgmA7u11vVKqRrgq9a6fcBzWus3Yo45wVq+\nFe+EWutepdSHwPHWozHmuA+11okGM3kLMxA8gQSBoFLqa8ATmGMW/lhr/ZN4+4mxobCwkAsuuIAL\nLrgg5WMrKioSBn9Lly5l6dKlSa8PufTSS7n00ktTakdoApNEs/xOnz6dZcuWJXWuqVOncuutt3Lr\nrbem1AaXy8V1110nVYBCCCHERGQY0L0/IuDbaYZ8kcFfst1/0+V0w48aJewTQgghYkzUQPAYa7lN\nKbUcuCRm++1Kqb8A34wI8WZay52DnHcXZhg4M2JdssdF7hvrQuAczJmJb9Ra3z/IuYTIWHt7e7hr\n8tlnnz3KrRFCCCHEuGQEoWtfRMAXWem32wz8ghkOg51TACXT+x87XoemLSQ1Z6GywZyvSBgohBBC\nxDFRA8HQ7ASnYYZsdwMPYI4ZeBrwW2AR5kzCl1v7FljLwfoldFvLwoh16R4X6Txr+UQqYaBS6lLg\n0iR3Px6gpaWF1atjh0CMVlFRQWFh4ZiY4EJk15NPPsmqVavYuHEjTU1NzJo1iwsvvDDhv7W8B7In\nGAzS1dU15P+/8Wqi3pcYHvJ+EcmS98roUjqIy99GXl8Leb5m3L4D5PmayfO1kOc7gNt3ABuZTdjh\ns+fhySmjN+IR+dpvz+8P9PxQWnIINS0/xWEMHTQGcPC6/xja5X0kYsj3FpEKeb+IiWqiBoKh0X4d\nwMNa65sjtj2tlPoU+CdwiVLqv7TW24HQR4dJfNwYJd3jIr2CGVQuUUr9U2v9iySPOxQ4PYPrioPM\npk2bWLduHVOnTuWyyy7j1ltvjTuGoBBCCCEmPmUEcPtbrYCvBbevxQr8DpDna8Hla8VGZnPb+ez5\n9OaUWwHfZDw55fTmltHrNF8HHKn9HtKWN4t9RfOY2rEJh04cCgZUDvuK59GeNyuj9gshhBAT1UQN\nBLsinj8Uu1FrvVEp9TbwWeAMYHvEMQWx+0cIbYs8f7rHRXoUeAq4D7hbKaW11vcMcr6QHcCGJPYD\ns0KwuKysjIULFw66Y319PQAlJSVJnlqMF8uWLUtqXMBQZaC8B7Jn7969lJSUsGDBgtFuSlaFPjEd\n6vuKECDvF5E8ea9kSaAPOvbEH7uvfRd0fkpmn2ljzrxbMh1Kqq3lDCiuDq/LyS0kB8jqbxTB82Dl\nNbB1rTkGYeSsw8oGDheOuedSVfsAVXZnNq8sxjn53iJSIe8XkazbbrtttJuQlokaCO6IeP5Jgn0+\nwQwEp8YcMyPu3qbqOOdP97goWuv7rVlb7wN+oZRiqFBQa70cWD7YPiFKqZeRakIhhBBCiInD7+kP\n+joixu4LBX/d+zK/RsEUM9wLh3wRj+IqyBmFngZ2Jyx6GBo3Qd19BBrWYjf8KKcb5nwZaq6Hyvkj\n3y4hhBBiHJmogeCmiOeTgeY4+5RZy9D4fqFjTox3QqVUHnC09fKdiE2h559RSrkTzDR8Ysy+ccUJ\nBbXW+peDHSOEEEIIISaovm6rmm+3VeUXUd3Xvgt64v2KmwoFhYdEVPdFBn8zzMDP6crKrWSdUlA1\nH5asYI1U8QghhBApm5CBoNa6USn1JvA54CygIXK7UqoUmGe93Ggt3wCagCql1Gla61diTrsYcAJv\naa0bI661Wym1yTrfYuCxmGudDlQB+6xrDNX2yFDwHqtSUEJBIcYxrTPsjiWEEGJi8nZGB3yRj47d\n0Hsgs/MrGxRVxlT3VfcHf8VV4MjNzr0IIYQQBxGtNY2NjdTV1dHd3T30AWNQxoGgMtOryUCe1npX\n5k3Kmv8GngZuV0q9rrV+F0Ap5QKWAcXA21ghndY6qJT6OfBzYJlS6gta6ybrmNnAzyLOG+unwJPA\nXUqpOq31R9ZxFZgzGgP8TGud1KjMcUJBrbW+N7XbT58VQmIYBjabbegDhBCDCgWCKjRLohBCiIlP\na/C2xx+7L/Twtmd2DWWH4kqzmm9At95qMwyUMfSEEEKIrAoGg6xcuZKtW7cSCARGuzlpSzsQVEot\nAH4IfAHIwxyR2BGxvQT4hbX+Oq11X2ZNTY3W+hml1N3ATcCbVsXgAeAkYBrQCPwfHV2680vM2X7P\nB7YppV7ArAo8G3AB92utB8w5rrV+Sim1DLgW+EAp9Tzgx6xOLAJWAb9Osf2RoeAvrZBuREJBp9OJ\nz+fD6/WSl5c3EpcUYkLz+cxZEB2OCVmULYQQByetwdPW35U3XvDX15nZNWxOs4ovXNkXE/wVHgJ2\n+dkihBBCjBStdTgM9Pv9o92cjKT1G4RS6jrgXsCeaB+tdbtSajJmuPY3zFBsRGmtb1ZK1QE3ACdg\nBpe7gHswK/aaY/YPKqUuAL4NXAacAwQxKwl/q7V+fJBrfVsp9RpwHebkHXbMrsqPAMuSrQ6MOeeo\nhIKFhYUcOHCAtrY23G63VDUJkaGuLnOCcQnYhRBiHNEaelqskG9nTHWf9dzfk9k17LnRXXhDY/eF\n1hVMAVvCX7eFEEIIMcIaGxsnRBgIaQSCSqmTgF8BAcwKwT9hjsNXEWf3R4GvAYsYhUAQQGu9EliZ\nwv4GZjVfShV91rGPAwlDwzj7n5HEPvcD96falkwUFRXR2tpKZ6f5qXZpaSkulwullISDQiQp1O2+\ns7OTAwfMMaCKiopGuVVCCDGGaQ2Nb0PdfZxX/yx27YPNbph9DtTcCJXzzIkkssUwoKcp/th9odAv\nEG+uuBQ43PHH7gtV+uWXgwzPIoQQQowJWmsCgQA+nw+/34/P5ws/Qq/r6uomRBgI6VUIfh9QwI+1\n1nfDoONibbCWJ6VxHTFKXC4XVVVV7Nmzh87OznAwKA4ewWAQgL17945ySyaOSZMmUVBQMNrNEEKI\nsSnoh5XXwNa1EPDiCHWs8Hug/mnYtg7mngu1DyQ/Jp4RhK59ESHfzphuvXsgmOGINjkF8cfuC1X6\n5U3ObogphBBCCLTWUYFdovBusHWJXh9ME0KmEwieai2XDbWj1W24E3OWXTGOFBQUMHPmTDo6Oujq\n6sLv9x9U/zEOdqEuriUlJaPckvFNKYXL5aK0tFSqA4UQIhGtrTBwjRkADthugL8XGtaY+y162AzZ\nggHo+jQm5Ius9GsEI8NP8HOLIoK+2OBvOrhLJfATQogJJHLm2Pr6erTWbN68mdmzZ1NTU0NlZaX0\nmkuBYRhZDesiX4vMpRMIlgGdWutky8Y0IH0hxqHc3FwqKiqoqIjXG1xMZKtXm3PnLFiwYJRbIoQQ\nYsJrfNusDIwXBkYKeODDldCyDbxtZuCng5ld210af+y+0Dq3fDAmhBAHi9iZY0MFMX6/n/r6erZt\n28bcuXOpra3Fbp9Y47sGg8GshnWh5+NxBl673Y7T6SQnJyf8iHy9ZcuWCVMslU4g2AFMUkrlDjVz\nsFJqKlAM7EmncUIIIYQQYpwL+MDbbs7I62kDT+TzNvjgKbMCMBk6CPveS/7aeZNjqvtm9HfrLa4G\nl1RvCyGEGHrm2FAX1YaGBlauXMmiRYtGvFJQax0O7rIR1kW+Dg0ZNZ44HI4BYV28AC/V10OFvU88\n8US4enS8SycQfA84EzgD+PsQ+15jLd9M4zpCCCGEEGIs0Br6uvpDvEQBn7c94rW1zHQm3sHkV8SZ\ntCPidU7+8F1bCCHEhJHszLGBQICtW7fS2NhIVVX8kdFC4WG2wrrI14ZhDMftD6tMwrnBXttGaVKu\nmpoatm3bNiG6LacTCD4GnAX8VCn1D611R7ydlFL/F7gNs8vwI+k3UQghhBBCZEW4Wi82xEsU7kWs\nz7R7btYouP4tKK4Cp3u0GyOEEGICqKurS7p7q9/v589//jMVFRUJA7zxRimVlbAudp3D4Ri14G64\nVFZWMnfuXBoaGsZll+hI6QSCfwC+hRkKvq2UWgG4AJRSXwWOAhYBn8WcjXil1vrZ7DRXCCGEEOIg\npzX4uhN3wR0Q8LX3r/d1j3x7ld0ci89dCi5r6S7tX/fqPalN/uF0Q9ns4WuvEEKIg0IgEKC1tZWm\npiYaGhpS6gLa1dUVnohxJNlstrTDucFeOxwOmSwlSUopamtro8abHK9SDgS11lopVQv8L7AQWBqx\nebW1DL2T/ooZHgohhBBCiEhBf3RYl0yVXmidMQq/fDrzo4M8d0n8gC82+MstHHwm3uatUP+0OZvw\nUJQN5nw5e/ckhBBiwgsGgxw4cIDm5maam5tpamqiubmZAwcODFsXXLvdntVx7UKvHY50arpEttnt\ndhYtWhSekXq8hqlpvZu01t1ArVLqLOBSYAFwCOZswvuBN4DlWuuhxhgUQgghxESmtTmLbN19nFf/\nLHbtg81umH0O1NwIlfMGD4vGunC1XipdcK2qPd/IVxagbIlDvEQVfKH1jpzhaVPNDbBtXXITizhc\nsOD64WmHEEKIcS0YDNLa2hoV+jU1NQ1L8Ge327nooovihndOp3PCzUIsBlJKUVVVxZIlS/jJT34y\n2s1JS0bxstb6BeCFLLVFCCGEEBNJ0A8rr4GtayHgxRGqAPN7zIqwbetg7rlQ+wDYnaPc1kBMYBcv\n3EuwbVSq9fJiQrySwav0QutzCmGsjeVTOd98HzSsgYAn8X4Ot7lf5byRa5sQQogxxzCMhMFfqrPl\nFhcXU1FRQWtrKwcOHEjqGKUURxxxBLNny/AVYnyTelMhhBBCZJ/WVhi4xgwAB2w3zIqwhjXmfose\nzrxSUGvw9SQX4sWOrzeq1XpDhHgDtpWAI3fk2ztclDJD4YjwOKr7sLKZlYGh8Hg8V5QKIYRImmEY\ntLW1RYV+zc3NtLS0pBz8FRUVUVFRQXl5eXhZXl5Obq7583TPnj2sWLEiqZljHQ4HCxYsSOuehBhL\nJBAUQgghRPY1vm2GO/HCwEgBj7lf4yaomm+uCwbA25H6LLiettQmp8gWZ16cIG+QSTRC63OLxl61\n3mixO81QuHET1N1HoGEtdsOPcrrNMQNrrjcrCYUQQkw4hmHQ3t4eN/hLdcKGoqKiAaFfeXk5Lpdr\n0OOSnTnW4XAwd+5cKisrU2qXEGPRoIGgUiprE4JorR/L1rmEEEIIMcbV3W9WeiXD3wt/qAVXsRns\n9XUOb9viUsmFeJEVe6FJNZyD/5EhkqSUGQovWcGa1eY8dQsXLhzlRgkhhMiWUPAXO7lHc3NzysFf\nYWFhVPAXWg4V/CUSb+bYyFmHlVLhMLC2tnbcTiIhRKShKgSXA8nPvT04CQSFEEKIiaqvG9o+gdbt\n5qPhmeRmjQ3xdpiPTDncCYK8IcbYk2o9IYQQIisMw6Cjo2PAGH8tLS1JdcmNVFBQEDf4c7vdWW93\n7MyxDQ0NGIaB0+lkzpw51NTUSGWgCNNa8+7udh56dTsfd43PgHioQPAVshcICiGEEGI887RHh36t\nEc+792fxQsqsFhyySi/OGHtSrSeEEEKMCK113OCvubk55eAvPz8/7hh/eXl5w9T6+CJnjl0t1eoi\nAX/Q4PtPvMvzW5roCwTR4zQ1GzQQ1FqfMULtEEIIIcRo0xp6W/tDvqjwbzv0Jjf7XlocLvj2G1a1\nXrFU6wkhhBBjhNaazs7OAaFfc3MzPp8vpXPl5eUNCP4qKipGPPhLJLLqa/2HdvwG3LrxOc48ooKr\nTpvFcVXF0l34IKe15vtPvMv6Lfvx+lPoDTMGyaQiQgghxMFEa+huig76Iiv++tLstmtzQumhMGmW\n+dj5Ouz7gKQ6GiibOYPspFnpXVsIIYQQGdNa09XVFTf46+vrS+lceXl5A6r9KioqyM/PH6bWZy62\n6svQZvDn8Qd5dvNeXmxo4uyjKrhnyfE47fLB5cHq3d3tPL+ladyHgSCBoBBCCDHxGAZ07Y0f+LVu\nB39Peud1uKB0phX6zewP/ybNguIqsNn7992zEVacb04Yksx5F1yfXpuEEEIIkZJQ8Bc7uUdTU1PK\nwZ/b7Y47xl9BQcEwtX54DFX1ZWgzGFy/ZT/ff+Jd7rvoBKkUzDLD0PgNg0BQmw/DIGBo/EFrnWGt\nC1rrjIj9rHVBQ+M3NIGYY/xBa13EMVHrwufQBA0j6hx+w1pn7f9xczcef3C0v1xZIYGgEEIIMR4Z\nQejYHRP2fdLf1TfZGX5jOfPjB36TZkHhIcl35a2cb1b9NayBgCfxfg63uV/lvPTaK4QQQoi4tNZ0\nd3fHHePP603t9wSXy5Uw+JsIwViyVV9ev8HzW5p4b08Hx1eXjFDromkdCq4iA7T+sCu8LmLpD+q4\n64JGZLgW5xzhwCwmmAv2h3XmOYYK5iLOHT4m+nrjdRy+8SztQFApVQVcBnwemAbkA4m+E2it9WHp\nXksIIYQ4KAX90L4rfvfetp1gpDZgd1huMUy2Qr7SmOCvoAKy8Yu9UlD7AKy8BrauNQPKyFmHlc2s\nDJx7rrnfBPhjQgghhBgtiYI/j2eQD+XiyM3NjTvG30QJ/iJprekLGHj9Qe5/8SO8geSqvrz+ILet\nfJ/aE6rC4Zg/Kmyz1hnxq9KCUeHa4MFcvO1BQ5IzkR1pBYJKqW8AvwNcDBICRmyTd6wQQggRj98L\n7Tvjh37tu0Gn2SUhb/LACr/Qw106MgGc3QmLHobGTVB3H4GGtdgNP8rphjlfhprrzUpCIYRIkQz8\nL5I10d4rPT09ccf46+1NYoiOCDk5OXGDv8LCwlH9ehhGf0jn8QcjlgZ9Ec9D2/ofRtT+ff7Yc0Qe\nb+7vTXN2WA18+GkXH35an/X7P9g57QqHzYbDrnDabdhtCqdN4bCb6xw2c7vTbq6z21T4mNDSbu8/\nxmlX2GOOcdoU9vA1+q/niFhnt9miruu09V/rGw+/SV9g/I8fCGkEgkqpecCj1rGPAM8AK4FWYAkw\nBTgbuBjoAr4LNGapvUIIIcT44+vp784bVeW3Azr2kPbnZgVTIoK+iEq/0pngHp1uLAMoBVXzYckK\n1qxeDcDChQtHuVFCiPFMBv4XyRrP75Xe3t4BwV9TU1NawV+8yT2KioqSDv4MQ+MNBPH4gngDhrmM\nDNaigrbYwM6wArrggHXx9p8oQctwM0MuMzQLh1k2FQ7SHDZlBVj9gZbDHrHO1h+4RW53xIRgUesi\njokb3MUL1xKcI946m2JchPNnHzmFZzfvZSIUaqZTIfh967hfaq1/AOF/NJ/W+kVrnz8ppe4F1gH/\nBcjAQEIIISY2b2f8CTxat0P3vvTPW1RlhX0xXXtLZ0Lu+BqwW4jBTLQqHjE8ZOB/kazx8l7p7e2N\nO7lHT09qE4A5HE4KSyeRXzwJV2EpzvwSbHnFGA43fUGDfb4gO3oNPB8F8dbvoS8U8MUJ58Lhn/Xa\nF5y4IV2O3Uau00aXN5DScXab4pIFh0YFW06bsqrTrMDLCruGCu4cMeFaqArOPIdVnRYTrsn3tdFz\n5akzebGhaUJMLJJOIHgKZinDL2PWR70jtdYfKKWuA54CbrUeQgghxPjV2xq/0q91O/S2pHdOZYPi\n6vhde0tngNOd3XsYYRLyiGSM5yoeMbLG08D/YnSNxnvFH4wI13xmsOb1m+FaV6+HtpZmOtsP0N3e\niqezDV93O4YvtTH+AtpGh3bTpl20G27atfno9uZAt4LdAH6g2XqMP7kOGy6nHZfThttpt56br11O\n+4B17pjnuVH7DDxH5Gu7zfx5c90fNyVd9WVT8JWjp3L7+UcN81dCjEXHV5dw9lEVCT9sGE/SCQSn\nAF6t9Z6IdUEg3l8sTwM+4AIkEBRCCDHWaQ09zXECPysE9Land16bA0pmxA/9SqaDIye79zFGSMgj\nkjFeqnjE6NLaHEj/wVc+pi/Zgf8DQX794jb+u/aYIccJ00MM3TD08UNsT2Kgskxn2BzuezTPMVQb\nhrjGkMdn2oL+c/xy/b9SmiTiP1dtpvaESivEM8IVc5HdZPsCQSLHtAutC+0TNDROApQoLyU2DyXK\netg85KvUJgILaBvt2mUGfpHBn84h8TD+wycySAuFbgPXRQZ2sUHc0AGf22kn12HDZhv5+0ul6ivX\nYefKU2eNQKvEWKSU4p4lx0f9jjtepRMIdmNOJhKpAyhVSuVprcODGmitA0qpPqA6gzYKIYQQ2WMY\nZhfeeFV+rZ+Arzu989pzofTQ+GP6FVeDPa15vMYtCXlEsqTiyxyfK2gFXsHQ82DMOusRMDSGNmef\nNLQOzzgZ9dCaoGEQNAgvA4Yx4DjDiDk+metax0UeE3kuI6aN8c7V38ZE92ZgaKvN4ban/nXVGp6v\nb+L5+hey/48mxhFNmerhM459VNs6sGMQxMZuo5gPA1Np0floFB80dvBBY0fSZ3USpER5KLV5mKk8\nlNg9lDjTCf4UHdpthn9RwV8uepDgTykGhHGJK+WGCuds4fXuqKW5Ptdhm/A/o5Ot+nI5bZx9VAXH\nVRWPYOvEWOO027jvohN4b08HD72ynUfH6X+PdP46aQSOUUqVaq3brHVbgZOBGuD50I5KqcOAQqAz\n04YKIYQQSTOC0NmYYEy/TyCQWvecMGfewLAv9CicBjapcgs5mEIerXW4IkVHrAu97t9mrdORxw7c\nFu8c4X1T3F8T3bDB2qMjzxETvkSeK+7+MfcD8b4mcc6h4RfrUqviuXPNFv799MPiBkvxAqnBQ7M4\ngVSc8CsQGa7pUMg28Hyh6w0WsMW7RqaVYUKI+BQGpzo+odrejh2DUOGZA4MZtjaqcjrYHSzh1cBM\nNPF/hjus4K+/4s+s/itQvpTaYmAjkFOAzi1CuYtw5JeQW1hCYUER03IcKXd7zbFP/JBuJMWr+or8\nIMKmzMrAUM8G+doLpRTHV5fwm2/MY8NPNR+OdoPSkE4g+BZwDHAssMFa9xywALhTKbVZa71PKVUG\nPIT5e+A/stFYIYQQIizoh/Zd8cf0a98JwdR+UQ/LKYTJcbr2TpplzuorvwCGBQ1Np8dPu8dPe6+P\n9l4/7R5z+cc3dyU92LLHH+TrD75BsdsZEywlH0BpHdEZLk44N2D/OIEVg2yLF/CJkaeBf+5o4587\nNo52U8QosCnSqhSsKMwFhv72rYbohjn08UNsz8LPjyHbMMz3aJ5jqDYMcY0ML5DMV1EpxcdNXZzq\n+ITp9jYcauAbx6bAhsF0exunAm8ah/J/jinF4e/C1teF8nQS6G0n6E1tcg+73c7kyZPDs/qGlqWl\npdjt9pTOJUZWbNXX+g8/xW+Ay+ngrCMruOrUWRw3Tj+8FCKedALBVcAVwDfpDwR/DVwHzAd2KaWa\nMccatGGOL/jfmTdVCCHEmKA1NL4NdfdxXv2z2LUPNrth9jlQcyNUzsteaBbog7ad8bv3tu8CneaY\nHe7S+IHfpFmQN/mgC/0MQ9PlDdDW64sO93p9tPX66fD0P2/3+Omwnnd6/VkLx/oCBk1dfdk5mRDj\nkMOmsFmzUdqVOVOlXSnstjiPiPWRx9mUOSOlTVnniXiE1oWvEXUuG3Yb0cuYc9lirjVo26y2h/ZP\ntt1D3a9SKuWB/8895hB+ffG84f8HFGPOd37/AgW72uOGgZEcSjPT3sosRytshWTnmrXZbJSVlVFe\nXh4V/E2aNEmCv3Essupr9erdACxc+NVRbpUQwyOdQHAdcPFjlSwAACAASURBVD7mWIIAaK3blFJn\nAo8CJwKHWJv2ADdqrV/NtKFCCCHGgKAfVl4DW9dCwItDW91B/R6ofxq2rYO550LtA2B3JndOXy+0\n7Yg/nl/HbpIZQDyu/IqYsG9m/9Jdmt45xzjD0HT1Bejo9ccJ98x1keFeh6d/nVS9ZU6p/sqVUIWM\nitpmvYpYqPBzFd6vf1v0OYh3/iGuSdzzDrxm7Dmi7imJ/SMuFXdbovsE2LqvK6X/5TYFZ8ytSBg+\nDQiaQoFYzLoBwVic0CoqvIoKyGzYbOCICdDiHjfUOa19RHJk4H8BYBgGfX19eDwevF5v3GVl+wf0\nkNwMoIN9Dmiz2Zg8eXJU6FdRUSHBnxBi3Es5ENRa+4E1cdZvAT6nlKoGqjAnGqnXyUypJYQQYuzT\n2goD15gB4IDtBvh7oWGNud+ih/t/w/Z2Qlts117rddfe9NtUOC3BmH4zIbcw/fOOMq37g732BOFe\ne+w6jxnwBdPpT5eBQpeD0rwcSvKcFLud4eePv7mLQAptcTltbLj5C0BsADZ0UBY3bEty/8g/AlMJ\n58ygTEKcbJCKL5EKGfh/4jAMA6/XmzDQG2zp9XqTukaq36ZDFX+xwZ/DcXBNDCaEODhk/Tub1no3\nsDvb5xVCCDHKGt82KwPjhYGRAh7Yshr6OsHbYYZ+Pc1pXlSZM/TGm8Sj9FDIyUvzvCNDa02PL0hb\nT6gyLyLc6wkFev3hXluvzwwBRyPYy3VQnOeMG+6V5OVQ4nb2P89zUuI293HY4w/CfqDbl1LIc/aR\nU5hS5MryXYnxQCq+RCpk4P+xJRgMphzqhZ739Y29YSKuv/760W6CEEKMGPmoQwghxOCMIPQegBf/\na+gwMHyM3+w+nAxlh9IZcQK/meZ6R276bc8SrTW9vqAZ2lnhXptVmddhrYsN90KVe6lUyWVDQa6D\nYiu8K83LodgK7wYL94rdTpwJgr10ScgjkiUVXyJVMvB/doVCvVSr9DweDz5fmhN4ZUFubi4ulwuX\ny4Xb7R6w3LBhA8Fg8mMNO51JDnUihBATRNYCQaXU+cDlwBzAB7wL/Fpr/Xa2riGEECKLAn3QvR+6\nm6BrH3Tvg679A5c9zelP3hFizzEr+uKN6Vdcnfx4gxnSWuPxBwd0u40f7kV0xe314wsmNw5RtuTl\n2M1AL0G4F1nNZwZ85r45juwGe+mSkEckSyq+RDpk4P9owWAwrUDP6/WOeqgXL8wbapmbmzvk+H37\n9u2jvr6eZEawUkoxZ86cbN2WEEKMC0MGgkqpo4A/AL3AWVrrAbXdSqmfA98PvbSWxwL/Vyl1mdb6\nD1lqrxBCiKH0dVmBXpxwL3LpaRvmhij41ioz9CuqBFt2B972+oPhIC+yq234ebyx9zx+fIGRDfbc\nTnvCyrzSPCcl7oHhXnGek1zH+B6oXEIekQqp+BKp0lrT2NhIXV1dOPTZvHkzs2fPpqamhsrKynH3\nfSUQCKRdqef3+0et3YNV6Q22dLlc2GzD9yFWTU0N27ZtS+pr43A4WLBgwbC1RQghxqJkKgTPBo4H\nViQIA78C/MB62Qu8BvQAZwLFwINKqVe01ruy02QhhDgIaQ29rWaQ170/ccjXtR/8Pdm/vrsU7WlH\npTAXqHa6UbPOGHI/rz8Y1QU3MrwLhXtRFXzW874RDvZcThsl7lC3W2fE8/5wr9idE67mC3XFdTnH\nd7CXCQl5RCqk4kskKxgMsnLlSrZu3UogEAhXgPn9furr69m2bRtz586ltrZ2xGeB9fv9aYd6gUBg\nRNsaKZ1AL1SpN5yhXiYqKyuZO3cuDQ0Ng35tHQ4Hc+fOpbKycgRbJ4QQoy+ZQPB0QANPJdh+s7U8\nANRorbcBKKWmAK8ChwFXArdn1lQhhJiAggHoCXXZ3T9I2LffHJcvm5QN8iugcAoUTIWCCiicCgVT\nrOVUa9sUcOTSvvxiij5Zi10NHQoGteKTks/z9lu7wuFee0Q1X2S4N1h30uGQ47DFVOZZ4V5+f8gX\nL9w7mIO9TEjII4TIJq11OAyMV/mltcbv99PQ0MDKlStZtGhRypWCfr8/7e63oxXqKaUSVuENFeyN\n5VAvE0opamtr44bHoe2hMLC2tnbcVZQKIUSmkgkEQ4MpvB67QSlVDJyGGRj+VygMBNBa71dK3QH8\nL3AWEggKIQ4mfk9/yNe1zxynL15FX08LpFB1lxR7bn/IFw77pgxcl1+WUjfe3wXO5QaeJ4+hZwXs\nw8kP9pzKe7s/yOROBuW0K0rycgaGe+GutwOr+UrzcnA5bfJLvxBCjFONjY0Jw8BIgUCAhoYGPvjg\nA4qLi1MK9lKZiCKblFJpVemFQj352TaQ3W5n0aJF4e7lDQ0NGIaB0+lkzpw54e7lQghxMEomEJwK\ndGmt2+NsOxmwYf41+5c425+2lrPTa54QQowhWoO3IyLk2x/9vCuiO29fR/avn1sUUb0XWlZEh3yF\nU8BVAhn8UdDh8bO9uZuPm3usZTfbm3vY1lTCEY55fNH+Nnkq8QDkvTqH9cH5vKcPS+p6DptK0O02\nQbhnhYBup13++BFCiAnOMAz6+vro6emht7eX9evXJz1eXiAQ4K9//eswtzCazWZLu/ttTk6O/Fwb\nBkopqqqqWLJkCatXrwZg4cKFo9wqIYQYfckEgkWQsBzkRGu5U2u9J3aj1rpLKdWFOZagEEKMTYYB\nvS0xwd6+iNl3I8K+gDf7188riwn5EoR9OXlZu2TQ0Oxp6w2HfR9HBIAt3YnCPsUPAtfyC5bxRfsm\ncvFFdR8OakUfTtYH5/ODwLWAYtG8KivYc1IcUc0XGe7l50iwJ4QQBwu/309vb2844It9xFufzCyx\n2WSz2dKu1JNQTwghxHiRTCDYAUxWSpXEqRL8nLV8e5DjFTA6dfdCiINbwBdTxRcxHl9UlV8T6Cx/\nm7I5zGBvQMg3Jbr7bkEF2J3ZvXaEULVfKPQLLXce6MUXTH3svgAOvhO4nuOCH3OVYw1n2t7FhQ8v\nObwQPIGHgufxvlUZ6Hba+cWS47J9S0IIIcYIwzDweDyDhnmx60djNtzq6uqUZsJ1Op0S6gkhhJjw\nkgkEN2NOLLIYeCi0UilVAJyB2V341XgHKqVKgQJgR4btFEIMN62h8W2ou4/z6p/Frn2w2Q2zz4Ga\nG6FyXkbdULOqrztOyBenos/Tmv1rO/Pih3xRYd9UcE+CERqgO1TtF1vp93FzDy3dQ4/3FyvHYWNW\nWT6zyvM5rLwgvPz1ix/xfP1+DK14Tx/O9f7vJDyHTcFZR1ZkcltCCCFGkNYan8+XVMVeaL3H4xmR\ntuXm5pKXl0deXh6ffvppShWDTqeTK664YhhbJ4QQQoxPyQSCqzCDv6VKqY1a63eUUjnAfUA+ZvVf\nosE5Pm8tt2TaUCHEMAr6YeU1sHUtBLw4tFU55vdA/dOwbR3MPRdqHxi+ajatwdM2MOSLF/b5urN/\nfVdJ4pAvMuzLLRy1YLTT6zdDv6Zutrf0V/vtONCLL5B6tV9FYW5E6FfAYdbzaSVu7LaB93jtGYfx\n6rYWPP6hqylzHXauPHVWym0SQgiRHcFgMG6QN1jINxIz5NpsNvLy8sjPzw+HfJGPeOsdjv4/WZ54\n4gnq6+uTCgWVUsyZM2fI/YQQQoiDUTKB4EPAjcAsYKNSaj8wCXBiVgf+Id74gZYl1j6vZaGtQojh\noLUVBq4xA8AB2w3w90LDGnO/RQ+nFogFA9DTHD/ki+y+270fgoknqkiLskF++SAhnzU+X34FOF3Z\nvXaagoamsc3Dxy3dVvDXE142d6VX7Tdzcj6HVeQzq6y/2m9meT5FrtTC3eOrSzj7qArWb9mP1584\ngHQ5bZx9VAXHVcnwsUIIkQ1aa/r6+lIae8/rHYYxb+NwuVyDhnmx6zKdDbempoZt27Yl1fXY4XCw\nYMGCtK8lhBBCTGRDBoJaa49S6suYlYJHYc46HLIBuCHecUqpKcCF1stnM2ynEGK4NL5tVgbGCwMj\nBTzmfo2boGo++L2DhHwRYV9PM+bnAllkz40Yhy8m3Itc5peBzZ7da2dJV6jaL2Z8v08O9KRV7Vde\nmMussnwOqygILw8rK6CyNH61XzqUUtyz5Hi+/8S7PL+lib5AECPin9amzMrAs4+q4J4lx8v4S0II\nkUAgEEi6W27ouWGk/rMhVXa7fUCAN1jI53a7sdtH9udsZWUlc+fOpaGhYdCKRofDwdy5c6msrBzB\n1gkhhBDjRzIVgmitP1JKHQecDRxjrd6otX55kMPKgJsBv9b6vYxaKbJnZx08ccnYGxNOjA6t4fVf\nJT9zrr8XHvuaGbJ5O7LfntyigTPrxlu6SsbFezdoaD5t9/BRVOhnPm9Kp9rPbuPQsryocf1mWc9T\nrfZLl9Nu476LTuC9PR089Mp21n/4KX4DXE4HZx1ZwVWnzuK46pIRaYsQYmLRWtPY2EhdXV24S+jm\nzZuZPXs2NTU1VFZWjskPGgzDwOv1JtUtN7TO58tyRXwC8brkDhbyjYfJNJRS1NbWsnLlSrZu3Uog\nEIjqPqyUCoeBtbW1Y/5+hBBCiNGSVCAIoLUOAn+3Hsns/yHwYZrtEsNFGyM3JpxITGswAmYQF/CZ\ny2AfBCIe4dfeOOsitgV9CfaJPLcvwbXS6E6Uzvh9eWVWFd9gYd8UyMlP/dxjQKjaL3JcP/N1etV+\nZQW5HFaeHzWu32Hl2a32y4RSiuOrS/jNN+axevVuABYu/Ooot0oIMZ4Fg8G4AY/f76e+vp5t27aF\nA57hrkjz+/2DhnnxHqlMcpEup9OZdLfcUPWebYQmtxppdrudRYsWhQPkhoYGDMPA6XQyZ86ccIAs\nhBBCiMSSDgTFBJLpmHDjXTAQE6x544dtwZgwbsA+ccK4hKFdnHPr4e/6M6xsjv6JNsLdd+OEfQUV\nEyJ0NgxNY7tnQBffj5u7M6r2m1VWEB7f77CKAmaW5VPsHv9fLyGESJbWOhwGxhsXTmuN3++noaGB\nlStXsmjRoqSrvgzDwOPxDFmxF/lIZmy6TCmlku6WG3o4nfKzIZJSiqqqKpYsWcLq1asBWLhw4Si3\nSgghhBg/JBA8mMWOCTfcjGCcIM0XE8gNUtU26D7xgrzY46yHHnqGVDEIhwu+9yG4J8EErDzo7guE\nu/VGhn6ftPT8/+zde5wbV33///eZi6S9eJ3Ya5NgJ4Fc7OIkJOHSEFNybwuU1nX9SNpCC7TQfikE\nWu7QlLbfXxtKf998KaWF9tcLt5bQBh64LqWkxGCTNKGBBELi2Js4ccjFSWxvHHu9u7rNzPn9MZJ2\npJV2Ja12tbt6PR/oIc3MmZmjtXCs937OOcq3We13ZqXKb6Dyev3J/Yui2g8Auu3gwYMNw8CkIAj0\n4IMPamRkRENDQ02FfNnsLPPjdkg6nW56WG55YY3lWr0HAACWBgLBXlfMSjv/SHrVe2YYZlqvIq6N\nNlHjiZ97knHjcM1Lxc9u6dlLlx7JfYljbjrRprw9U5t61060+cpvxsPIm6lYNE481HxgeP5/PvOo\nXO03tYLvVPB3aKy9ar8zVvdXzetXHvJLtR8ATFeedy+bzWrnzp1NV+UVi0X967/+67z2zXGcpofl\nlh+exz+pAQDA0sK/XnqelX58e/zoFcaZJWyrF9I102aGkK62jZuW3EXyf7/N74znlCxOzt7Wy0iX\nXDf/feqQiXxQmdvvkcPjeqQUAP742Qnliu1U+6VqhvjGz+tP7pPnUukBoPckg73ko1yd12h/LtfG\nHLZtymQyLc29l06nWYgCAAAse4skkUBvMDUhWU2lW70Arpmqucr2DEGemzyfj32VdS+Nq/5Gvh4P\nI2/E64vbrXvJwvWtCVFk9dTx7LQhvgeOTOiZsda/cPqu0RmrBxKLepRW9B0e1Mp+qv0ALE9RFCmf\nz88a6tXb1w2nnHJKw4q95P6+vr55X4QEAABgKSIZQVwx98JLZwnSZhh+mgzbZqyI83tr8ZKlwph4\ntentb4vnlAxy1cOHyxWV5VWpu/RnOJEP9OhoHPY9kgj9Hh0db6vab/VAairsSzxT7QdgKbPWVoK9\nZgO9yclJ5XK5BVkpN6k8796xY8daurfv+3rb2942jz0DAABY/ggEe51xpE2/KF3z2W73BN3k+vFq\n0wd/IN35SQUj/yk3Ksr4fdKGV0ubr4srCedZFFk9PZaL5/U7Mh7P8VcK/p4+3n6135nDAzpr7WDl\nmWo/AItdMthrZShuNpvtSrDX19dXeZQr82ofyf2ZTKZSuXfzzTdr3759TfXbGKMNGzbM91sCAABY\n9ggEe90SmxMO88dKujc6U39ffJduzV2jYiT1hZ6uLKzVb0Vn6gJrOzan0mQhqDvE98Acqv3OXDNQ\nM7/foE6j2g9Al1lrVSgU2hqKG0Wt/304F6lUasZQr1HQN9chuZs3b9b+/fubWljE8zxdcsklc7of\nAAAACAR7Wt6k5W94jZxFNiccFl4xjPSem+/Vzr2HlQ9CRTYO/rLFUN/Y87S+PXJYV29aq49fe6H8\nJgO2KLJ6Ziw3LfR75Mh4W9V+nmNKK/kOVg3xPWvNgE7qT7V8PQALw1qrgwcP6s4776xUge3Zs0fn\nnHOONm/erHXr1i2JBRystSoWiy0FeuX9Cx3s+b7fUqDX39+vTCbTtZVy161bp40bN2pkZERBEDRs\n53meNm7cqHXr1i1g7wAAAJanOf3LzxjjSTpb0smSZhx/Z629bS73QueE1igvX9+OXqpbi2/TJyQt\n/q9imC/WWr3n5nt1695DdavzIhsHg7fuPaT33HyvPvkrF1V9eS9X+x0oreB7YHQiHu57ZELZYthy\nf1YNpOKhvTXz+522qr/pMBLA4hCGobZv364HH3xQQRBUhoQWi0Xt27dP+/fv18aNG7V169YFXfih\ntmKv2cq9MGz977S58H2/qVCvdl+3gr12GWO0devWup+V8vFyGLh169YlESADAAAsdm39i9EY80JJ\nfybpFySlmzjFtnsvdFYkR/8ZXqy/D39O99mz1LfvqH705HFdeNpJ3e4auuTeJ45p597Dsw7VzRUj\nffOBQ/rof+5TIYgqAeBTbVb7nb66f1ql35nDgzp5gGo/YDmw1lYCnnpDQcsVdyMjI9q+fbu2bdvW\nctBTrthrdSjuTFVo88HzvJbm1ys/fL935jp1XVfbtm2rVJOOjIwoiiL5vq8NGzZUqkkBAADQGS2H\ndMaYsyV9V9IqxYVlVtJhSa2nAlhw34s26p3Buyrb2WKoa/72Tq3I+DIqLyBrZIwq26ZqO/6y5jjT\n95dOrdpOnq/a/aVjTmnHVPvp56tef+pc26lzfsP3M+3a1X1wTPlY4/Ob+VkZE19r6n0nf1aNz5eZ\n/jOsusYM50/7WSt5TvW1/+V7jyvXZCVfPoj097c/2lRbSTq536+p9Itfn061H7DsHTx4sGEYmBQE\ngR588EHt379fK1eubGko7kIHe67rtjS/XnlfLwV7c2GM0fr163Xttddqx44dkqQtW7Z0uVcAAADL\nUztVe38iabWkJyX9nqR/t9Yu7L/I0VHF0OroRKHb3cASVa72Ky/ocdZwHPqduWZQq6j2A3pCudov\nl8tVHrfeemtTi0RIcaXfTTfdNM+9nOI4zrQAr5nKPd/3Ga4KAACAZaGdQPBKxVWBv2qtvaPD/QGw\nBHzoNT8Rz/O3dpBqP2AZsNYqn88rn89XhXozPWrbLvTCGVIc7LU6v15fX59SqRTBHgAAAHpaO4Hg\nCklZwsDlI+M7+u8PXilrJSur0v8q27ayHb9W6Vhk7dT+0j5VtU+cn3itOteOKteuOT9x7Vn7Fp8u\nK6soUvN9K7Wb1q9E3zStffW2kv2s6vP0a0d1fx5NXrvhz6f++ZVrNzhfsrr57icVRlOTt8+mz3f1\ntsvOaro9gPkXRVHdMK/ZgC+fz1ct4tAtw8PDLa2MS7AHAAAAtKedQPBxSacbY4xdDN8eMCeOka5+\n0fM0PNjM2jBYjsaygb6x52k1kwk6RrrqRWvnv1NAjwnDsKXwrt6+bnNdV5lMpvJ46qmnWgoZfd/X\nddddN489BAAAAFDWTiD4L5I+IukqSTs72x0stLTn6q2vOrPb3UAXvfVVL9S3Rw4r28TCInxegPqC\nIGi7Oi+XyzU919588n2/KtBLp9NV2zM90un0tIUzbr75Zu3bt6+pUNAYow0bNszXWwMAAABQo51A\n8GOSfkHS/2eMudpa2/ySo1hUMr6jqzet1QXrV3a7K+iiC087SVdvWqtb9x5Srth4DjA+Lyiz1urg\nwYO68847K4HPnj17dM4552jz5s1at27dkhrGaa2tG+i1EvAt9Gq39aRSqaaCu0bHXNftaH82b96s\n/fv3NxV2ep6nSy65pKP3BwAAANBYO4HgtZI+K+l/S7rfGPMVSd+XdGKmk6y1X2jjXpgHjokrva7e\ntFYfv/bCJfXFHZ1njNHHr71Q77n5Xu3ce1j5IKwaPsznBUlhGGr79u168MEHFQRBpfqrWCxq3759\n2r9/vzZu3KitW7d2PGBqxFqrQqHQVmVeuW0Yzl4hO9/mUp2XTqcX7OfdrHXr1mnjxo0aGRmZMTD1\nPE8bN27UunXrFrB3AAAAQG9rJxD8nOI1CcqpwK+XHrMhEFwEHGP02vNP1W+96kxdcNpJ3e4OFgnf\ndfTJX7lIP3ryuP7+tgO69YGnVIykjO/pqhet5fMCSXHwVg4D61V9WWtVLBY1MjKi7du3a9u2bU0F\nyFEUVQV67Qy97faUtsaYOVXnpVIpOc7yWq3bGKOtW7fWDZDLx8th4NatW/llAwAAALCA2gkEb1Np\n8VMsPT/5wlX669e/pNvdwCJkjNGFp52kT73hJdqx4wlJ0pYtr+tyr7CYHDx4sGEYmBQEgfbt26dd\nu3apr6+vqZCv2xzHUV9fX1vVeeVAj0BrOtd1tW3btsoQ85GREUVRJN/3tWHDhsoQcwAAAAALq+VA\n0Fp7+Tz0AwCwgMqr2ubzeRUKhWmv6+179NFHm178IgxD3XbbbfP8LqZ4ntd2dV4mk5HneQR688QY\no/Xr1+vaa6/Vjh07JElbtmzpcq8AAACA3tZOhSAAYIGVF75oNcRrdHwxzJmXVF4Qo53qvHKgBwAA\nAABoDt+gAGCeRFGkYrHYcnDXqG2358lrx8UXXzxryLcYF8QAAAAAgOWMQBCApLgCrTzP1759+2St\n1Z49e3TOOedU5vnqhSGVYRi2VX1Xr22hUOj222nIGKN0Oq1UKlX13Oh1KpXS1772tZYqC33f12te\n85p5fBcAAAAAgHa0HQgaY14u6W2SXinp+ZIGZmhurbWEj8AiFYZh3ZVAi8Wi9u3bp/3791dWAl1s\nlVzlobRzHUJbfh0EQbffUkOu67Yc4jU67vt+ywHvQw89VAmLZ2OM0YYNG9p9qwAAAACAedRWSGeM\n+ZCkP5XkNHtKO/cBMP+stZUwsN6CEdZaFYtFjYyMaPv27dq2bducKwWttSoUCnMeQlt+HUXRnPoz\nn3zf71iI1+158jZv3qz9+/c3tbCI53m65JJLFqBXAAAAAIBWtfzt0hhzhaSPSgol/aGk/5D0A0lH\nJF0i6XmSrpb0ztIpb5F0Xyc6C6DzDh482DAMTAqCQA8++KAeeughnXzyyW0Fd+XXhUJhUc+H10pI\nN9txx2n29yaL37p167Rx40aNjIzMWEnpeZ42btyodevWLWDvAAAAAADNaqfc5J2SrKQ/stZ+VFK5\nWii01h6QdEDSd40x/yBpt6R/lHRRR3oLYM6stcrn85qYmNDExIRuvfXWpiq+pHgI8Ze+9KV57mHr\nHMfpWIjXzlDaXmGM0datW+sOLy8fL4eBW7du5ecIAAAAAItUO4HgxaXnv6vZX1UGY6192hjzdkm3\nSvp9Se9o414AmhAEQSXga+bRysIQ88XzvI6FeN0eSttLXNfVtm3bKgvQjIyMKIoi+b6vDRs2VBag\nAQAAAAAsXu18ix6WNGGtHU3sCyT112n7bUlZSSwzCbQgiiJls9mmA758Pr+g/RseHp5TiJdKpRbd\n4iRonjFG69ev17XXXqsdO3ZIkrZs2dLlXgEAAAAAmtVOIPicpKE6+4aNMSuttcfLO6211hgTSTp1\nDn0ElrzyIhrNBnyTk5PzOsee53kaHBzUwMCAnnrqqZbu5fu+rrvuunnrGwAAAAAAmF/tBIJPSrrI\nGLPGWnuktG+vpEslXS5pR7mhMeYCSQOSjs6xn8CiEwSBJicnmw75ZlqEYa6MMRoYGGj6kUqlKufe\nfPPN2rdvX1OhoDFGGzZsmLf3AQAAAAAA5l87geAdihcJeZmkb5T2/bukyyTdaIx5StK9ks6X9BnF\nC5B8Z+5dBeZXFEXK5XJNB3y5XG5e+5PJZJoO+DKZTNur2W7evFn79+9vamERz/N0ySWXtHUfAAAA\nAACwOLQTCG5XvNLwmzQVCP6NpLdJOkfS/yTaGkmTkv64/S4C7WtlmO7ExMS8D9NtNuDr7+9fsIUy\n1q1bp40bN2pkZGTGKsby6rEsGAEAAAAAwNLWTuJwm+Lqv0J5h7U2Z4y5TNJfSvoFSWnFlYHflfRu\na+39HegroDAMWxqm20zVW7uMMerv729pmK4xZt760y5jjLZu3art27frwQcfVBAEVcGoMaYSBm7d\nunVRvgcAAAAAANC8lgNBa20k6YE6+5+R9MvGGF/xSsRj1tqJuXcRnfTYY4/p5ptv1ubNm7Vu3bqu\nhzvW2paG6Waz2XntTzqdbjrg6+vra3uY7mLjuq62bdumgwcP6s4779TIyIiiKJLv+9qwYUPl8wIA\nAAAAAJa+jo9JtNYWJT3d6euiM6y12rdvn/bv31+p+HJdt6P3KBaLLQ3TjaKoo/dPcl23pcU2FmqY\n7mJkjNH69et17bXXaseOeG2gLVu2dLlXAAAAAACg03o3/ehh1loVi0WNjIxo+/bt2rZt24yVgmEY\nKpvNNh3wFQqFhtfqhFaG6abT6a5XQQIAAAAAACwmjXBsBgAAIABJREFUMwaCxpjTSy+L1tqna/a1\nxFr7eDvnYf4EQaCRkRHdcccdymQyDQO+ycnJee1HKpVqabGN5TJMFwAAAAAAoBtmqxB8tPQ8Iunc\nmn2tsE3cC10QBIF27tzZ0Ws6jtPSMF3f9zt6fwAAAAAAADQ2W0hXHmvp1NnXCsZsLnF9fX1NB3yZ\nTIZhugAAAAAAAIvUjIGgtXba2Mx6+7D0XXTRRTMO0+30wiMAAAAAAADoDobxQr7vs5osAAAAAABA\nj6Dar8cZY7Rhw4ZudwMAAAAAAAALhECwx3mep0suuaTb3QAAAAAAAMACmXHIsDHmMx26j7XWvqVD\n10KHeJ6njRs3at26dd3uCgAAAAAAABbIbHMIvlmSVf1Vgm3ide3x2mNWEoHgImGMqYSBW7duZUVg\nAAAAAACAHjJbIPi/G+xPSXq7pJWSHpN0m6SDisO/UyVdKukFko5J+ltJ+Q70FR1gjNGmTZu0efNm\nKgMBAAAAAAB60IyBoLV2WiBojElJ2lU699ettV+sd64x5lcl/Z2kV0m6au5dRSecccYZuuaaa7rd\nDQAAAAAAAHRJO4uKfEjSKyT9TqMwUJKstV+S9DuSXinpA+11DwAAAAAAAEAntRMI/qqkgqQvNdH2\nXxQPF359G/cBAAAAAAAA0GHtBIJnSMpZa8PZGlprA0m50jkAAAAAAAAAuqydQPCEpCFjzHmzNTTG\nnK944ZETbdwHAAAAAAAAQIe1Ewh+W/Fqwp8xxpzcqJEx5iRJ/yjJls4BAAAAAAAA0GUzrjLcwB9J\n+nlJL5X0oDHm7yTdJump0vHnS7pU0m9JWiNpsnQOAAAAAAAAgC5rORC01j5kjHmtpC8rDvw+XHrU\nMpIOS7rWWrt/Tr0EAAAAAAAA0BHtDBmWtfY2SRsVV/7dLylSHACa0uv7JX1E0k+U2gIAAAAAAABY\nBNoZMixJstYek/Qnkv7EGONLWlU6dNRaW+xE5wAAAAAAAAB0VtuBYFIpADzUiWsBAAAAAAAAmD9z\nDgSNMc+TdJqkfoYHAwAAAAAAAItb24GgMeaXJV0v6dzSLpu8njHmJMULjxhJW621J+bQTwAAAAAA\nAAAd0NaiIsaYj0m6SdJ5kgqKw0CTbFOaY/AZSVdI+oW5dRMAAAAAAABAJ7QcCBpjfkbSBySNSbpW\n0qCkIw2af16lCsF2O9gpxpiPGmNs6fG+Gdq93hhzuzHmuDFm3BhztzHmHcaYGX9WxphXG2O+aYw5\naoyZNMbsMcZcb4xJN2j/uVJf/rjB8ZXGmP8utdlnjFnf0hsGAAAAAAAA6minQvA6xRWB77fWfsVa\nG87Q9rulti9pp3OdYox5ueIQ087S7lOSvijpZZJul3SrpA2S/lrSV4wxboPzPiDpG5KulPQDSV+X\ntFbSn0rabYzpb7G/ayTtkvTK0vVeZa19spVrAAAAAAAAAPW0EwheXHq+abaG1toJScclndLGfTqi\nVKH3OcWrIO+Yod02SW9XPMz5xdba11lrt0o6R9I+xVWO19U572WSPiZpUtIrrbVXW2uvkXSmpNsk\nvULSDS309zTFYeRFpecrrLWjzZ4PAAAAAAAAzKSdQPAkSWPW2skm29etqltA/4+kTZLepjicbOTD\npecPWmv3l3daaw9J+p3S5ofqDB3+kOJh0X9urb0rcd64pN+QFEl6e2mRlRkZY85RHAJuVFxx+LPW\n2rHZzgMAAAAAAACa1U4geFTSUDPDYI0xL5S0QnHV3YIzxlws6b2SbrLWfm2GduslvVTxAilfrj1u\nrf2OpIOKKx1fkTgvJek1pc0v1jnvgOJh0ylJr52lry9WHAaeIelmSVustdmZzgEAAAAAAABa1U4g\n+L3S8+uaaPve0vPtbdxnTowxGcWLmhyV9LuzNL+o9PzADCHc92vaSnElX7+ko9baR1o4r7avr5C0\nW9LzJP29pF+11hZn6TMAAAAAAADQsnYCwX9QPET2o8aYM+o1MMa4xpg/UDwnn5X0t+13sW03KA7s\n3tnEHHwvLD0/NkObx2vaJl8/rsbqnZf0U5J2SjpZ0o3W2t+21kYzXA8AAAAAAABom9fqCdbarxlj\nbpL0ekk/MMb8m6QBSTLGXKd4vr6fl/T80il/Y639bof62xRjzGZJvyfp36y1/9rEKYOl54kZ2oyX\nnld04Lykq0rP37PWvn+G60xjjHmzpDc32fxCSRodHdWOHQ3XVgGq8FlBs/isoBV8XtAsPitoBZ8X\nNIvPClrB5wXLVcuBYMmbJR2R9E7FC2dIcSXgX5ZeG8WLaXxc0gfn0L+WGWP6JH1W0pjiCsWmTis9\n21Zv1+Z5Sd+V9DJJP2mM+aS19l0tnPsCSZfN4d4AAAAAAADoMW0FgtbaQNK7jTGfkvQmSZdIOlXx\nEORDikOuz1trRzrV0RZ8VNIGSb9prX26yXNOlJ4HZ2hTPnYisa/d85K+KelGSf8i6Z3GGGutnW3O\nw7IfS/pOk20vlLRyeHhYW7ZsafIU9Kryb8H4rGA2fFbQCj4vaBafFbSCzwuaxWcFreDzgmZdf/31\n3e5CW9qtEJQkWWsflvSRDvWlU7Yqrk58kzHmTTXHfqL0/DvGmNdJetha+1bFwZoUr/DbyGml5x8n\n9pVfn97ieVWstV81xvyK4lDwXcYYNRMKWms/J+lzs7WTJGPMblFNCAAAAAAA0PPmFAguYo5mDr/O\nLD1OKm3/sPR8rjGmr8FKwy+vaStJI5KyklYZY85qsNLwT9Y5b5o6oaC11v7eTOcAAAAAAAAArWpn\nleFFzVr7AmutqfeQ9PlSs/eX9l1YOucJST+QlJJ0Te01jTGXSVov6RnFw6HL9ypI+kZp8w11zjtT\n8XDqgqSvN9H3r0r6FUlFSb9rjPlEs+8bAAAAAAAAaMasFYLGmDd24kbW2i904jrz6M8kfVnSnxtj\n7iwNh5YxZq2kT5fafMxaG9Wc9zHFw5Q/aIy5xVr7vdJ5g5I+ozh0/bS19lgznaipFPzdUqXgu+f6\n5gAAAAAAAACpuSHDn9PcVtFV6fxFHQhaa79ijPkbSb8j6X5jzE7FlXpXSRqS9G+S/rrOed83xnxI\n0p9LutMY821JxxQPWV4r6S5JLc0wWRMK/l5pTkFCQQAAAAAAAMxZK3MIPqd4vrxly1r7dmPMf0t6\nh+JAz1U8T+BnJP1NnerA8nn/rzHmPknvVTzXYEbSAUmflHSjtTbfRl8IBQEAAAAAANBxrQSCvqR/\nl/QFa+3u+enO/LLWvlnSm2dpc5Okm9q49i2SbulwX76qeF5DAAAAAAAAoCOaWVTklxQPl00rDrC+\nZYx51Bjzp8aYDfPZOQAAAAAAAACdNWsgaK39N2vtNkmnSrpO0vclnSHp9yXtM8bcZYx5uzFm1fx2\nFQAAAAAAAMBcNVMhKEmy1j5nrf20tfYVkjZK+qikxxXPmfdXkp4yxnzVGPNLxhh/froLAAAAAAAA\nYC6aDgSTrLX7rbV/YK19oaQrJH1eUk7SL0r6sqSnjTG/1rluAgAAAAAAAOiEtgLBJGvtd6y1vynp\nFEkfkBRIOlnSi+d6bQAAAAAAAACd1coqw3UZY/okbZP065KulOSWDp2Y67UBAAAAAAAAdFbbgaAx\n5kpJb1S8CvGAJCPpsKR/kfQFa+0POtJDAAAAAAAAAB3TUiBojHmR4hDwDZLWKQ4Bc5K+IukLkm6x\n1oad7iQAAAAAAACAzpg1EDTGDEt6veIg8CLFIaAk3aE4BLzZWnt83noIAAAAAAAAoGOaqRB8SvG8\ngEbSI4pDwH+21j46nx0DAAAAAAAA0HnNBIKeJCvpMUnfl/QiSTcYY2Y8qYa11r6h9e4BAAAAAAAA\n6KRm5xA0ks6QdHpiuxVW8byDAAAAAAAAALqomUDw8/PeCwAAAAAAAAALYtZA0Fr7GwvREQAAAAAA\nAADzz+l2BwAAAAAAAAAsHAJBAAAAAAAAoIcQCAIAAAAAAAA9hEAQAAAAAAAA6CEEggAAAAAAAEAP\nIRAEAAAAAAAAegiBIAAAAAAAANBDCAQBAAAAAACAHkIgCAAAAAAAAPQQAkEAAAAAAACghxAIAgAA\nAAAAAD2EQBAAAAAAAADoIQSCAAAAAAAAQA8hEAQAAAAAAAB6CIEgAAAAAAAA0EMIBAEAAAAAAIAe\nQiAIAAAAAAAA9BACQQAAAAAAAKCHEAgCAAAAAAAAPYRAEAAAAAAAAOghBIIAAAAAAABADyEQBAAA\nAAAAAHoIgSAAAAAAAADQQwgEAQAAAAAAgB5CIAgAAAAAAAD0EAJBAAAAAAAAoIcQCAIAAAAAAAA9\nhEAQAAAAAAAA6CEEggAAAAAAAEAPIRAEAAAAAAAAegiBIAAAAAAAANBDCAQBAAAAAACAHkIgCAAA\nAAAAAPQQAkEAAAAAAACghxAIAgAAAAAAAD2EQBAAAAAAAADoIQSCAAAAAAAAQA8hEAQAAAAAAAB6\nCIEgAAAAAAAA0EMIBAEAAAAAAIAeQiAIAAAAAAAA9BACQQAAAAAAAKCHeN3uAAAAAAAAALBUWGs1\nNvYjPf74P8h1D3S7O20hEAQAAAAAAACaEEVF7d37Ph0Z/ZaiKC8Z2+0utYVAEAAAAAAAAJiFtbYU\nBu5UFOW63Z05YQ5BAAAAAAAAYBZjYz8qVQYu7TBQokIQAAAAwBJjrdX9o/frcw98TruP7VZRRf3p\nP/+pLl1/qd587pt13vB5MsZ0u5tYBJLzfA0M7pRU1K7d12t4+AqdfvpbNbTixXxWUMHnZfmx1sra\ngqKoqCgqKLIF2ah6O4rK+5Lbtcfj7UOH/0NRlO322+oIAkEAAAAAS0YxKur626/Xrid2qRAWFCmS\nJOXCnHY+tlO3H7xdl6+/XDe86gb5jt/l3qKbauf5MiYq7c/q8OFbNDq6S2uGr9KmTTfK4bPS8/i8\nzE0cvJVCtErwNrU9dSxfs11uX5wK5aZt5xWV2ttKSNfkti10+0ezaBEIAgAAAFgSrLWVMDAXTh+u\nFSlSNshq1xO7dP3t1+vPL/1zqnl61OzzfEWKoqyOjO7U3r3v07nnfoLPSg9bSp+XZPA2c6iWrxuy\nVVfD1W5PtbWJ401tE7wtOQSCAAAAAJaE+0fv1+4nd9cNA5NyYU67n9ytPaN7dP6a8xeod1hMmp3n\nK4pyOjL6LY2duE8rhy5YoN5hsWnt87JTzxz6dw30v7CmGq4cphVrhqHWbFeFbsXWtkuv0RpjfDlO\nqvJceRhfZsbt1LTjP37sb2Rt0O231BEEggAAAAC6zlqrbJDVZDCp8cK4JoIJTRQmNF4c10RxQhPF\nCd384M3KBllJVmekIl2+oqhzM5F8IxWt9EDW0a5xX48XHGWDrD5w2wd06fpL5Tu+fNePn8uPxLbn\neFX7a7erzquzz3Xcbv/4lqWpub+SgUhNRdS0MCbefvLJLzQ96X8UZfXAA+/WqlWvkmTLd5eslZWt\nvK70a9q+ZDtVrpFsZ5PXjd9czb7adnX6MG2fGvQhef8651TdT3X21d5PM/QhcQVrp65T/hkk91k1\n6EOjn03ivdnqe1Xvq20nNexDZZ+q9lkbqllRlNPeve9pun0vMcYrBW/lEM2vCdZ8OaVjJhG6TW1P\nHY/31WwbX46TrtmuPZ7cjq9pTOfW052YeFjPHPnGslihl0AQAAAAQFustSpEBY0XxjVZnKwK72pf\n1zteuy+y0az3dGT1hlUFndcXyjeSUxq1lzLSBf2RNvXltSfr6otHU3py/EndNHLTPP8UJMc48ow3\nY+hYCR7rtGnm3EahZu25je5RCS+NW3eoo7XRjAGbnRbC1Q5FTFY15acPLZxhsv7qIYjdmfsrm31M\nBw8+tmD3A+ZiKnibIRAzpUCtHKBVtmuP19k2qdJ5pYq5RMBXu+046XkJ3harwtDlCg59Q6ll8FYJ\nBAEALWFlRwBY+ophMQ7hgom4Gq8UyNUGec2Ee0G0kEOn4jDw/L6w7pcxx0hpI53fF+oNqwr6p6Mp\nSfP/36TIRirYggpNDuVzZOUZxQ9JrkluJ14byTNWrqq3PSWOJa7jmerrVh2vubZvTOW+ruJ2AJq3\nYsV5NSFcOXibbRiqP606rlIhlwj0arfj4K089HUZpFEdZq1VZCNFNlJoQ0U2UmADRdHUdmjD+HU0\n9brqWBRWnx8FVdthFOqze7brxZHb8L9DSwmBIACgaazsCGC+8MuG2YVRWBlGWy+4m227sr8w3nRw\ntdDSbloD/kDVY9AfVL/fr0F/UHc/9mWd18SXsJQjndcX6sy0o2vOf4+CMKcgyimMcgrCvMIwX6pQ\ny9cdjipblI0CyQaSLUoKZGwo2UBGoRwbyVEoo/i5HKpVhXaVUC4RzJW2nUXxUbazN1kEAiuF1iiQ\nFNnkT91RJEdWjiLjysqVjCsrTzKeTrVPtBRyhtbouRVXy8iRkSn9fRM/GzmSMfF+OfGx5LYkGSPH\nOKVzyteIP6jxfiduWT7POIl2U/dwyvcypfaqvq5TOqd8v0p/Su2S905ey8jIMe7U/RLnxvs1df3K\nsdJxTe1zzNT9yu9lSnJf+aHE3921+6Ye1X+/1147eT9VrjF1nqmzb+b7lf7IKtu7vnOBZPPNf2BM\nWj/58h3Nt29BbQBVLL8Oiopsvm5IVRtqNQrAKiFZ+fxEMFbv/HqhWHk7ef1kkJa8VhTV3K+mv3Wv\n1aBfs10rbGHY91zdr1RVpfpSZaxdGv8hwNwYY3ZLuuyyyy7T7t27u9wbLEZVX8Qei7+IZdwMX8RQ\nYa3VB2/7YMOVHcsybkZXnHYFKztimh074n84b9mypcs9wWJTjIq6/rbf18OHduqVAxPalAkrc8Lt\nzbq6Izugs9derRsu/eiS+2VDZCNNFiebrrabKciL585bfDzjaTA1OD3I8wY06Pdp0M9ohZdWv5fS\ngJtSn+erz/HU53lKG0dp11HKGKWMkVEQr4wZ5RWWV8lMPA48/XVlbFbN/OfFWjXVDlOKNg7g4odR\nqOrtwEqBEscr2ybRTgpUOpbYrrpuzXWm2pXCv9J2KMm2WeH5plU5XdAfNRW+Rla6d9LVF46m27pX\nLzLlALIUwDlV4aapBIfl104iHK09p9F1nFJgWfU6ccwxjmQ09bp8/Zr2tX2pel263pnZW7UxNdn0\n52Vfvl97vEuaC7IaVJo1qkyzSySsh9XpqUhXDBb1hT94Uvffl5Ok71hrL+9yx5pGhSAAqr7QFFZ2\nBDAfrLX6g9s+rOeNf12Xry5MmxPuxf2hXtQ3pn3j/6E/uM3qY5f9n3n/ZcO0xS3amROvEA/HnShO\nzGtfZ3knciT5lSGitvQspYzRCj+jFV5GA15aA15K/Z6vPtdTn+sr47jKOI7SjiPficO6eKiqlWus\nXEUy5aq58rxvYV5RNKYwyiuKcoqivJS3Up2im0DSidKjFX1S0yOAF3cY6NSsdJmYUH/aypaN5/+a\ncajhtMn6420rV9a4Cq1RKFMJ4YqRVWADFaOiilFRQVR6HRYr+2q3G7Vp5txiVJQTFWXCohQVZaO4\nKjOKijJRIIXFOa3kuXvc16a+vNJNfA6KVto9zlfjVljZqYqsZZBfnZEKdeYaNf15+a/joR4vfHf+\nO4aWGBm5xpVjHLmOO/XauHKdqdeOceQ5XtW2a0rtnanX5WOOE88T6xhH33nyO6X5bo0eL7j6/FFX\nB/JLc+wwf+sBPc5aWwkD6wU9kSJlg6x2PbFL199+PVVf88BaqyAKFNggfo4ChTasvK7aLrUJo8Rx\nO/M5tfsDmzg/eb1G9y/tf+joQ01Xp2SDrP74u3+sN7zoDRpKDWlFaoWGUkMaSg9pKDWkAX+g8ptc\nAL3tviP3ae3E17UpU5hxTrhNmYI08XXdf+SNevHaF09rV29xi2YXsqgX5DWzuEUzynPF+aVho5Vw\nrmp/dVjXqJ1vpIzrKuO4SjuuUo5RyjGVczzFQV08kDIoDW+d6Zt6nb/TreK0rg4rqVh6LCXTV71s\nvCJldRBXP1BrtPpldbupifxr7xvfk69hzShXVjUdTCb2f+j2D2pPNph1nq9CJO3JunqqmNJvnvem\nyjxkVlPPyX3WWkWK4hWQy21Kr8vHIhtJVlOvS+9lpnMb3ivxutwuec3K9Wa7Tk2/atvX9qVy/TrX\nW44eKzjak519Xrjy5+Xxwvz+O3bGIMt4VaFV5VgitGo6FEtcqyoUS5xbCcXqhGjl7eT1GwVslfs1\nG9DVuVbynGS75Hnz7b2736udj+2sFNEsZfyXCOhxS6HqqxxWhVGoYlScCrpqQ60Wgq/aa5XPL0bF\nyjm1odhMIdy0vrXQl0596VxsHnruIf3RnX9U95hjHA36g5WQsBIYJkLD5GNFakVl/4rUCnl8kQKW\njR0P/IVelq4fBialHOlF6YJuvOMdGlhxXt0gL6hTTWRkq0M31Q/h+o3VSiN5KclPl/arJpwzyXCu\nTqCn6YFe5xdqmCGtW4RMIhiLn9NyS8+Vh5ue1qZR25EHPyJrm48kHadPV1y+Zx7fIeaTYxyl3JRS\nbir+P2QL/uvH/6UvPXartCo3bUVqKR72WbRxuPOloxld9YKr9e6Xvruzb2CZahRoVoWfzQaeiUCz\n/DpSKbhMBp4116gXrs56/xmC2A/f/mF98ajqrmAeX3Pq8/LFoymlnLQ+eeUnmw+yairPZgrxpuZp\nxGL0pnPfpNsP3q5sMavh4ymde2BIE889pUc12e2utYxvVECPsdYqF+aUDbLKBTl9+t5PKxfMHAaW\n5YKcPnLHR3Tl6Ve2FXyV988UnCX3l8O55fqbyF4W2UhjhTGNFcak8dbP7/f6q4LD2grE8vbK9Mpp\nx9Mu8wMBc5WsxksOpR0vjE+9Tuyr2i6OK18cVyE4oSCc0C+sGJOfae6+vpFeN/CUnsgdikM3T/L8\nUghXG/yVwrpeXzk1ro5rPnBznFQioJutbbqqbb1rGeN29P08e/Q2HT58i9RUZYaj4eErO3p/LB3l\nL+3/dDSqzPO1qS+qzE/6QNbVrnFPTxRcZdy03rTpTd3u8pKRnINvufjmj7+pnY/t1D8dTc36eXHk\n6IrTr9Ar172y291GF5w/fL4uP/Uy5b72Az3/UFpuaGSW6NdVAkFgkQmioBLWZYNs5ZELc8oWs5Uw\nr7I/yFXa1jtW9Vw63i4rq0eOP6JH7n+kg+8YUjwhu+u48hxPromfPceTZ+Ln8rHKdqlN7f565087\n13Er+33Hr75e8tzktvH0zm+/s6VVKV3j6ufO/DmdKJyohH9j+fh5rhPjTwaTmgwm9czEMy2fm3bT\nM4aI9aoWV6ZXakVqhfq9fn5jiyUtsvE0EMmQrl5wVxlyWzihbHBC+cKYisEJFYNxheGkwmhSngKl\njZQ2VilHyhirtCOljI33l16faqS0E+9LOVbpPsnrb6//jpFWe9Jqb+FWEpw7R66bmTGUqx+opRqE\nbrNcy526TjxUdXn9c//0096i0dFdiqLZ/zviOGmdfvpbFqBXWIzOHz5fl6+/XLue2KXHCzl9/mj9\ncLq8GNp5w+ctcA+xmFSqvoJsZV64RlJuigC5x73q/tUaOdwvJ1yiSWDJ8voXAmZ1z6F79N7d72XV\n2DZZa5UP89WBXZitBHXTQrxmg7ogF18nyCqI2p88ebkyMnUDrobBV4PgzHf8hsFXM8FZbQjnG3/2\nvtRcq17Y5hp3Sfx/8fLTLm96vgxHjq4+42rd8FM31D1ejIpxUFgKCCuhYe12Yl/5MV4Yn1PVaD7M\n60j2iI5kj7R8rme8yvDlFf6K6VWKM2wP+oNync5WyqB3BFEwFeAVxqsWu5gK9E5osnBMueJx5Ytj\nKpQDvGBCYTQpG2ZlbV5pY+NHObxzVNoXD8sdMlZrSiFeqlxhly49liQjpxSiuVUBW+NgbqptMpTL\n1Dk+e8i33AK5bhsaukBrhq/SkdGdiqLGIxwcJ6M1w1dpaMX0+SbRG4wxuuFVN+j626/X7id3Kx/k\nq/4N4ygejnzFaVfohlfdsCT+LYb5kwyQZ5pKiQAZzzz8kA7c8305wdIOAyXJWLv03wRmZ4zZLemy\n/o39OvvDZyvtpZflqrFBFMQVc6VqunLIVhvAzVR116iqrrxvOQxfTbtpZbyM+rw+HZo41NJ78oyn\n/3XB/2q6eq1eCOc7flXYNtu1CFEWh/uO3Ke3fvOtTVX3ZdyMPvOzn5mX+SYjG2m8OF4VFCbDxYbb\npXCx3hxjC8HIxPMm1lYkNjH0eSg9tGT/ro6iSD984qva+8gnNBw9XRl6M+o8X+ee9Xu68LStcpzl\nM+QoacZhtYUxTRaOabLwnHLF48oVj6tYPKFCeEJBMKEwnJSNsrJhTsbm5SqoVOJNhXdTlXhpE4d3\nzpL5PuvKdfvlegPK559pdtFYSVIoRxec95cNwrnpwZwxHl/0l5koKmrv3vfpyOi34pWMq35R5chx\n0lozfJU2bbpRzhL9uxOdY63VntE9+twDn9Oux3YpUKCMl9Gl6y+tFEkAUvwL62YD5KX67zLM3df+\n4s+0/647lczSPr3ruzpw5Kgkfcdae3m3+tYqAsEekQwEz/zwmZKmfruxUKvGlr8YlQO4yWCycVBX\nDvUaHGtUdVeMltq6d9M5xlGf16eMm6mEduVHeTvjNtjvxef0e/2VNslj/V6/0m66KmBrZZUkR45+\n+gU/rRsvu3E+fwRYpKy1+uBtH9SuJ76t57mTunxFUedmknOrONo17utw2K8rTrtyUa5Iba1VNshO\nqz6srUhstD3b4jvzqc/rm3nxldrFWRJVihk305U/i3wwqS/f9hqtjp6UV2dy7sBKzzrrdc2l31C6\n3TGk86B2WO2JwnGN55/VZOGoJvPPKVs8rnzxuAqlKrxygBdFWdkoK0V5ObYgR0X5iqoCu3QixFsy\njCfj9Mlx+uS6/fK8QaW8QfneCrnugFyvPw733IHSc7+8xOu4zUDVPsdJVS5/+92/rtzxO5sKMyMr\n9Z30Sv3US78wj28YS4G1VmMn7tPjj/+DDh3oPiCdAAAgAElEQVTaKako181oePhKnXH6WzU0RGUg\nptuxY4ckacuWLV3uCRYrAmREUajxo0c1NnpYJ44c1tjoEY0dOayx0cMaO3JYR596cto5BIJY1OoF\nglL8BfMff+Yfdf6a8xVG4cxDWxNDY2cN6upU3eXC3LJYTTXlpGYO6vzqwC4ZyPV5fepzG+wvPXzH\nX9Av7oul6gtLw2wBT9FKRxdhwNMphbBQdyjzTBWJ5e3xYhurp3SI7/iNhzU3WHylvD3oD7b1d1IU\nRbpp9xVaHT054+qxhSgOBV9/+a45VwoWo6LG88d1Ij+qE7lRTRaOaqJwVLnCceWKx1QonigFeOMK\nwklF4aRslJNsTiYqyLEFuQrkKaypxJtTtxZUJE9y0jJOphTgDcjzBuR7g0r5Q0p7Q/K9wWkBnusN\nJIK8gcTxvnmvsDp27Ie66we/LE+zzwsYyNUrXnqzVq68cF77hKWFkAfN4rOCVvB5WZ6CQiEO+UoB\n34lnk4HfEY0fHVUUtjZX8VINBJnUpMdlg6ze+I03yjFOS4sFLFZGZlrIVhvSzRbmJQO72rZpNy1v\nmc0FxHwZaJa1VvtHPqx1zmjdelLHSGkjrXNGtX/kwzr33E8sugrBuUq5KQ33DWu4b7jlc4Mo0Hhh\nvBIQHi8cn7UiMRkwzuUXKsWoqGdzz+rZ3LMtn+sYpxIUzrTwSm3F4mOHd2vVLGGgFIdtq6MnddvI\n/9WpJ50fB3jF48oVjsVVeMG4isEJhWGpCi8sB3h5GVssBXiBfEVKOfEqs7X80qP+Gyw9d2FmglCe\nIuNLJi05GTlun1ynX67XL99boZS3Qml/pTKlh+cNTA/ySoFfebvTK7ouhJUrL9Spa1+tpw/fMmMo\nGMjVqWtfraGhCxawdwAAYCnJT05UVfTVVvhNHj/W7S4uGssr2UBbAhtooabF8x1/eiDXRFDX8Fhy\neKzfp5STWnYBxHxjwmU0a2zsR6X5mmYeNhtFOR0Z/ZbGTtynlT34xd3aSNaGsjaSFFZeWxuqz4TK\npFNamzpZ1g5NHVMoVc4LZRVJifMiGypXnNBEcVyTxROaDCaULUxoMhhXNphUNphQrjipXBA/8mFO\n+SCrfJBVIczJ2lDGxNmXozi8NbKJ1/HCEabh8awcHZYjyRQkpyA5E3GbnKSCkZ5NnOtIWuNF6m+y\nsi7lSOEzf6snaxaNTpUedS1g1Z61cRgVGk+RUrJOSjJpOW6fnFIQ57uD8v0VSntDyvgnqS+1Uv3p\nVUr7Q3Folxw+W6q8M2YJlR7OI2OMztv0f2VkdPjIrYpsvuqPN5LkmLTWrflpbdp0I/8dAgCgR1lr\nNXn82FTQVwn9pob35icn5nyf/pUnaWh4jYaG12rFmrUaGl6roTVrNTS8Rnd++SYduOcuLYfRtgSC\nPeasdKQ3rspp17ivxwuOlJjG28hMr6xrMLS13tDYhsNj/alQb7lV1y0XvuPrY6/6mO59Yrv2PvIJ\nrY6eqswL96zzfJ179rt14Wlb+RLWg6y1sjaQtUX9+LG/nTUMLIuinB7e/zGdccZvTwu36gVeVvGz\nEgGZteU2DfYpEbxV7Qsq11XivHrXr+yrvZYSfW20T8n3NBX+LaT+0qNKOfXr0bmuIysVrBMHePIU\nGk/WpKeG0brxMFrfHagEeGl/pfpSJ6nfP1n9mVUaSK1SyltRmveuX47Tx99/88xxfJ137ifqzgm3\nljnhAADoCVEY6sSzo1VB39iROPg7MRoHfmFxbusGGMfRitXDccg3vEZDa9ZqRSn8K7/2U+mG51/8\ni9fosft/qCCfn1M/FgPSmR5jjHRBf6RNfXntybr64tGUUm6fbv+V25V203zh6VHl1fqOj35Lpypf\nqbxJGelUPaNjB/5QD4x9h9X6OiQO2YqKomLNc0GRLcpGxcbPUaFyTvWx2nMDRbZQ2U7eo/a68bFC\nTX+Cyv4236WOHf+ejt33vY7+7LB8WSs9E6YVGV+RiSvwyvPgOV5cged5g0r7Q8p4K5VJrVRf6mQN\npE/WYGpYg+nVGkivltulBVQwd8YYrRy6QOef91c68AjzNgEAsNwU8zmNjR6ZWqyjJvgbP/ps6Rft\n7fP8VKmqb02pqm+qum9ozVoNnrxajtv+FCunnL1BZ7/0Yj189/8oKCztadcIBHtQeZ6v8/tC/dqq\ngg6t+FllvEy3u4UusdZq79736cjozgbVX5GiKKsjozu1d+/7Fu28cHGlVnXIVnndVKhWE5SVX9cG\nZw1Cu+Q1m3nG8hbP4+bKGEfGuKWhocltV0aOZGr2GVdGrpQ4r3q7wT7Fryv7KtuJ69fuS/Sndp9q\nrlvZJ0fG8WrOrX+t/7n72rrz+TVStNKv/cze+fojAQAAwDyy1io3MV4zhHeqwm9s9IiyY8fnfJ/M\nwGBc0VcO+2qCv76hlfP6fdUYo1e/4z265VMf18P33KVwCYeCBII9LOVI5/aFuuqFm7vdFXRRa/PC\n7dSRIzs1OHh2dfBWt0KtfKwQD+GMZmlbW6GWCOSm76+tZosr2jA/jPFkjK8omn0l6mqOVq/6qalw\naVqQVQ6SZtk3Y5BVblMvoEqGW078PjQVotUGWQ33JUKxSj9q900L/3DEPF+n2KeqVqJuJLLSs866\n+e8UAAAA2mKjSBPHnmu4WMfY6BEVc61+X5hu4ORVlfn7aiv8VgyvVbp/2oQ5C871PL32Xe/XM488\npLu/tl1m13e73aW2EAj2uJQjZQ/+lfZN3i1JspXVRWw8fquyN7m/9FxpXzpma9qV9k1rl7h2vfbV\n++rtL193tj7Uu1d1H2yy3Ux9KB+a8X0krmZr2pX7Wtlvpy4x7V71rzl9f+01k++lzr1kayY+jV+H\nYVaqu2bsdFGU0/173tZUW8zMGF+O48sYX8Z4chxfjknJOFP7p55TcowfH6t6TskxXs126byqtqnK\ndvKa8T4vca9U3I+a+5cDrvv3vFOHD9+i5j4vjtaufY3OP++T8/pzxOK16azf1eH9H1SqiUAwsNKm\ns393/jsFAACAusKgqBOjjebvO6ITzx5RGMytCMNx3an5+9as1YrhtRpak5i/b/Uaef7SmKLKGKNT\nz96on3/3h/Thf/xn6fCz3e5SywgEe5yRlMs9oaeefqLbXQHmrDpE86cHXbWhmpNKtPGmQrW6wZs/\nQ6hWDvVS00K76nskQ7bFN+x6Nqef9haNju5qqlLQcdI6/fS3LECvsFhddNov6aZH/kqroyeVmqFo\nshBJzzrr9bOnbV24zgEAAPSYQi47LehLDu8dP/ZcoiioPX46UzVf34pkld/wGg2cfLIcp/35+9BZ\nBIIAWtbXd0bdoKschNVuJyvUqkK12sq3VkK1ZDVc6dylGLItJUNDF2jN8FUzzDcZc5yM1gxfpaEV\nrAjayxzH0TWXfkNfvu01Wh09Kc+oavhwZOPKwGed9brm0m/IcRhqDQAA0A5rrbInxqYCvqrhvHH4\nlxs/Mef7ZFYM1RnOO7WdGVzBd7IlhEAQMsbXxg1/JMlIxsio/H9gU3qUDtXuL/0f3STbxRes3m+m\nzqu6hlHN+aZyfvW9VLM/eY3kvVS1v/77MNVtm23X8P3W60Oj91FqZ2rfm6nZV2//7H0wyXZV96q+\ndu01b//vi2edPzDJcfq0+ZJvN90ey4cxRps23VhahOZbiqK8qocPO3KctNYMX6VNm27kHwNQ2uvX\n6y/fpXuf2K4HHvmEVkdPyTflIHCdzj3n3XrN6VQGAgAAzCSKQo0fPZpYrKNm/r5njyjI5+d2E2M0\nuGr19IU6Eq/9DIuRLicEgj3P0Zo1P6N163612x1BlwwPX9nSvHDDw1fOd5ewiDmOr3PP/YTGTtyn\nxx//Bx06tFNSUa6b0fDwlTrj9LdqaIjKQExxHEcvOWObXnLGNu3YsUNFSVu2bOl2twAAAKax1uqZ\nhx/S3V/7qh65+y7ZMNBffuULOvMlL9fLfn6rTjlrw7z80jsoFHTi2SOJFXmr5/EbPzqqKAzndA/X\n8+LVeess1jG0Zq0GVw3L9YiImmWt1aEfj+neWx9X4bmlOQyaP+0exzxfYF44tMoYo5VDF+j88/5K\nBx7ZIYmABwAAAEtbGAS65VMf18P33KWwUKgsyBgU8tp/1x068MPv6+yXXqxXv+M9LQdn+cmJaSvy\nJrcnjx+bc/9Tff1Vq/FWVfmtWauBlSfJMEVLR4RhpG99dq8evW9UYTGStUtzZBSBYA9jni9IzAsH\nAAAAoLdZa+Mw8O67FBSmD7211irI5/Xw3f+jWz71cb32Xe+vVApaazV5/FjDxTrGRo8oPzkx5z72\nrzypMn/fijoVfpmBwTnfA7Oz1sZh4I9GFRSbGWW3eBEI9iTm+cIU5oUDAAAA0MueefghPXxP/TAw\nKSgU9NBdd6jwf/IKCnmdGI0Dv7BYnNP9jeNMzd9XZ7GOFcNr5KfSc7oHOuPQj8f06H1LPwyUCAR7\njpGjtWtfwzxfqMK8cAAAAACWoygKVchmVchOqjA5qXz5dXZS+cn4ec+ubza9KEcUhjpwz10t9cHz\nU6WqvjX15+87ebUcd2nOQ7ccRJFVGEQKi/EjKD2HQfl1GD8HkX7wX48pKCz9MFAiEOw5J530cp1/\n3ie73Q0sQswLBwAAAGCxCIrFRIg3WQnxGoV6U9tZFXJTAWAx33hapE5JDwxUV/fVBH99QysZaTUD\nWwrkyqFb/VCutD8I4+dCvWM1oV6QCPNqr5V4HYW22z+CriAQBAAAAAAAc2atVTGfqw7xJuNwLp8I\n9MqB3VSYl60+np1UGATdfjsz+sUP/GEl9Ev393e7O3NirW0iiIsUFqYCuWToNnsoV3vdsKp9FPRm\nINdtBIIAAAAAgGXJWqtnHn5Id3/tq3rk7rtkw0B/+ZUv6MyXvFwv+/mtOuWsDVRuKR4GW0hW3c1W\ngVdpVw7wspVgz9pFNpzSGKX7+pXq61eqr0+p/n6lMn3xvv54/w9v+Q/ZKGz6kq6f1lkv/cmOddFa\nqyiwlTCtEpiVw7bCTEFb2DjAazK4C4NF9me20IzkeY5cP354viPXS7z2HbmeK8939Oh9R7TYPuLt\nIhAEAAAAACw7YRDEK8fec5fCQkHWxlVIQSGv/XfdoQM//L7OfunFevU73iPXW5pfjec0rDYR6jU7\nf95CclxXqf4Bpfv6SmFev9L9iWCvr78q1KuEfv3Vx/xUWsZxZrzXw3cf0NjhPZKaqVQzSg+crT23\nHZwhiAvrV8jNUIXX6xoHcQ1e+24lxPNSM5/nlQK9Rscd1zT9i4Fb/m6PDvzwsOwyKGpcmn/rAQAA\nAADQgLU2DgPvrr9yrLVWQT6vh+/+H93yqY/rte96/4JVCjY7rHYq4EsMr03MjbdYh9V66XSiIq9f\n6f6pQK861OuPw77Edqqvr3Ku6/tz+jMJg0j5yUDjz2WVnygqNxnEzxNF5SeD+Lm0P5c7T9I+Sc38\nPF0F4Yv1nZsebLtvi5GbrJCrUy03FcTVHnebC/OmtXEr13K85gO5brvwp0/TY3tGl8XCIgSCAAAA\nAIBl5ZmHH9LD99QPA5OCQkEP33OXnnnkIZ169sYZ2yaH1eYToVxtcLdchtUmQ72piry+OhV5/VXn\ndnK1XGutgkJUCfHiAK+o/EQp0JssKjcxtX/qdaAg3/wQYOOcIsc/S1HxEc0cCnpy/LNk3FPm/N5q\nOZ6ZHrTNFrB5tdVxbsN2Mw6HdR0ZZ2kEct32vBcM6YUvHtajPxpVsMQrOwkEAQAAAADLyt3/sV1h\nodBU2yCf1y2f/oROP++CJTis1isFcvM/rHYubGRVyAVxYDdZrA74JoJSyFdMHJ8K+RZiwQljjPyB\nV6s4cUspFAxVPXzYSHLl+GfJH3i1HNfRizafWrf6rTqIc2eZl25qP4Hc0mCM0VW/sUnf+uxePXrf\n6JIe7k0gCAAAAABYUoq5nCbHjmly7LiyY2Ol5+OV5/133VmZM7AZRw8+oaMHn5jHHleby7DaZMDn\n+f6C9VmSojCaGm6bHHZbDvISIV8l+Cu9Xug514xjlBnwlO73le73lBnwlR7wlOn3lR7wK8cyA75+\neOtjOvjQMfkDr5UNn1GQu0dR8YDiakFPjn+mvMzL5HinyBjprIvW6Ipf+4mFfUNYNFzX0U+/5Vwd\n/vEJ/fDWx2X+fWlOKEggCAAAAADoGmutirmsJsfGNHn8mLInjjcM+sr7ZxsKPC9mGVZbG+ol58Ob\nz2G17QiK4bRht+XwrlytVy/4K+SaH4bbKa7nxOHdQDLY85Xp90rB3tT+5Gs/4zY9L116wNOOv/ih\ngkIk452q1ODrGvfHd3Th1ad36u1hiTLG6HkvHNKrf/s8pT4ZSk91u0etIxAEgP+fvTuPk6ys78X/\n+Z6lurqnuwdnhkUYdmQzIAKiSVQQRBRJ0BiNN5obwNwbl8SL5mck92eiuZqf6CUSo0azqGQxcUlM\niEsQZQRXEJBVRZZxkAFHGBim16o6y/f3x/OcqlOnlj7V09W1nM+bV7/OqbP1Uz2H092f/j7PQ0RE\nRERrRlVRW15qhHh7G4GeCfts8Dc3h6V5sz0KgoG22XFdnPlbr+verXaiPFQTH5jJSaJMkNdmbL2k\ne25q2yDGPvPLrq3Os6HeVLpizwZ6mf3lDR68Uv/D07zjwnm+gyNP3oIDjpjpe5uI+o2BIBERERER\nEXWkqqguLjYCvvm9WN6bqdqbT0I+s97v2W9d38fk7EZM2Q+zPovJGbP+gxu+hkfuvQd5+qmKCI45\n45dw6kt+ta9t7iSOFbV0NV7LeHrNlXvJ9upiiDhe7364MBV4bbrdduuWO7HBg+v2b4zCfdVuXLj0\nrSNiKgOPPHkLzrn4xKEKholWi4EgERERERGNFFXFz3fM4fav/hQP3z4NjYG/vu56HP4LW/DMcw/D\nAUfM8Bf2LjSOUVlcaFTtzc21HY8vHfbFUX+7inqlCUzOzjYFfJP19WT7fvXgzy9Pdv033nLo4fj0\nO/8IqjkqD8XDaS992T6/hyiMc3W7bYyzl1Tu9Tc8bcdxpd7ttrULrpep3kttm/TGdvKL7Lhw2+/4\nOTQCvJKLI07aglPOPQwHHjE76GYSrRkGgkRERERENDKiKM5U8ZhwIqzF2H7bo3jw7t31Kp5hrkha\nS3EcobKwkBlrLz0e31xLwKdxf7uM+hPlRtVePcybTVXzJUHffpia3Qi/XF7Tzy/eQXBKRyOq3A8z\nMUQnHpzS0XDcgwCYsDmsxbm63Vaa1kOE1fUfX88rOU3dazuNrdc0/t6UB38i//h6RZIeF+7qqx8A\nAFx44YUDbhVRfzAQJCIiIiKikaCqJgzsMM6XqgkGf3LHblz3yR/i3Nc9fSRDjziKsDw/Vw/2GpNs\nmPH46t12bTVfZX4eqv0N+EqTkybImzFB3uTsRkxt3A9TM7OpgK8R9HmlCWisUAU0VtO1VU33WFWF\nxrBLRWUJWF5Ybj4mdW76eHOMIo4z+1Lrcay4/Ws/hVc+Dxop4uABABGAdPdaAeDC8Y+GVz4P//mX\nt8MvuagsBYjD9Z8xtDTppbrfJsFe63h66e0TUx48f7CTkxDR6GIgSEREREREI+HnO+bwkzt3I6hF\n0GgXwsotiIOfwFSAeXD8o+CVT0OgB+End+7Grp/M4YDDZ0xYlAqgktAoG0xlg6fsOdnjYs0EVx0C\nsCgKUVtcQGVpDrXFOVSXF1Bbmkd1aR615cZHUFlArbKAsLqE5vBq7Yk7AdfbANebguNtgONO2Y8N\nEHcSjjMFcacgMgVxJqFwAQWqoaKyW/HEY9n3vIBY54F4J2LVfjc/33sUF/6G8+29civiYDua75XT\n4XimMjCoRAj2cQZdcaTRtbbLeHrp7eUNPkqTLpyCVLMS0fBgIEhEREREA8cx4caHqiIKYoRBXF+G\nQdSyLUpvr8WIwhhhLbLLGGEYI6olx0YIgxi7H5pHUA0QLF7TpuorRBzch1qwHY5/NIAX4/Pvv7VP\n7zECdBkaL0N1CdAlu74MxEtQXYbGS+YYXQK02pd2NJEJiEwBMglxJs26XYozCcgUxO6DTEKk8aug\nAogUiEJ06F3bccfQExGI91SUpi/IfY7rOY1qPNvFtlNX3PS6X2Y3XCIaHQwEiYiIiGigOCZcf2is\nTaFaayjXOaQLA3teGCOqRY3rhHHHAC+97Nt7Uk2Fge0CKoUJBh9AsHgN/A3n5wpoVMPmgC8J9doG\nfMvrFPCVITIJODbIqwd8kxBnqk3AN3xdR0VsIOcIxGm/7oiprDOv08eIOd8ROKn1luMEZn/6GEfw\nkzseQy+9qF3fwWv/zy+ivMGDVxq+ryUR0Voby0BQRHwAzwdwPoBfBnA4gM0AHgPwXQAfVtXru5z/\nmwDeAOBkAC6AewB8EsBHtcvgHCLyYgBvBXA6gDKA7QD+BcAVqq0/NYjIVQB+G8Cfquq72uzfCOBL\n9j3cA+BcVd3Z9c0TERERjZAijAkXx9qhGi5GFEamGq4plItsgNehmq7T60yAN4hx0PpNo11dwsA0\nEwpGtR/CdTdAsQzoUlPop7EJ+eJoCdBan1sucP0peBMb4Jem4U1Mw5+Yhl+ehj+xAX55Bn55GqVJ\ns5yYnIbjum0DMMcRoF0Iljqu4zHpkK0lWLOvU+tO2wCu+fNkz6mv2zBwUK75m7ux/bZHoTn+NxAB\njjx5C6afMtH/hhERDYmxDAQBnAngq3Z9F4BbASwCOBHAKwC8QkTerap/kj1RRD4C4I0AKgCuAxAA\nOAfAhwGcIyKvVNWWwSVE5A8BvA+m38L1APbYdrwHwAUico6qLuV9AyKyP4CvAHgmgO8DOE9Vd+c9\nn4iIiGgU9Dom3KM75nHgkbOr+lxx1C5k6xK0ZarewlqUOqdbgNd8vTgav2BuJa7nwPUdeH526cL1\nHbiewnFiOF4ERyKIE0MkhjgRREIIYph7IIIiADSCaog7v/ZV5O+6GiJc+kpfOrqKOGZijZnUrLkb\nN2JyJj25RmPijfL0NByHVWfr6ZRzD8WDd+9GWFu5TND1HZzywsPWoVVERMNjXAPBGMC/Afigqn4z\nvUNEfgPApwD8sYh8XVW/ntr3CpgwcBeA56vqfXb7gQC+DuDlAH4PwAcz1zwdwOUAlgCcrao32e3T\nMBV+zwfwZwDekqfxInIoTKB5HIBvArhAVed6+QIQERERDaM4VkS222kUxLj5izsQ1PKPCXfd3/8Q\nh/3C5uburE3hXufusBoXMJhrCeVceHbdcRWOG8NxIziOQpwIjhMBYkI6SAjUg7kQ0AhACI3th4aI\nowAam2UUBoijAHEYIAxqCGsBoqCGYKGG5VoNYRAgqtUQBjVo3N8ZcXsljtMc5M00Qr76drttcnYW\nk9MzEIfd14fZgUfM4siTt3SsPk54voMjT96CA46YWcfW0bBSVdQemsfCN3filB88BU4MPHzLt1E+\nfhNmnr8V/tbpkatSJ+pkLANBVd0GYFuHfZ8RkXMBvA7Aa2GCvsQf2eXbkzDQnvNzEXkDTOXfZSLy\noUzX4ctg5q1/XxIG2vMWRORiAPcBeKOI/KmqPtmt7SLyNJgw8HAA/wXgFaq6nOd9ExERDRtOFDFc\nkplTo0yVXBTaCrggbt4XZo+z4VuYXCOqjynX+Zzma2er5XodE+6Jn52PPbtyd7oYGp7vwC058DwH\nbqk5lHO9GOLEJpxzIohEtlIuhogJ4YAIggjQAIoI0BBxJphrfISIQxPGhYFdVmpYmhvuUK5fDjvp\nFBvqzWJqxlTsTSbVezbsK09tYMA3ZkQE51x8YmZ80vR+E5gn45PyexFpFOOJz96Lyg8fh4YxXDue\nrQYxlu/ejco9T6B84mZsetWxEI5nS2NgLAPBHG6zy63JBhHZCuA0ADUAn8ueoKo3iMjDAA4B8BwA\n37HnlQC8xB72qTbnbReR78KMA3g+gH/u1CgRORnAtQAOBPBZAK9V1aDXN0dERDQMOFFEK1VtDszC\nRmi2chjX5riWMC5VFRcqoqRKLnVcnvG01lOvY8JptAviPXV1n0xggzi3qXLO9WylnKdwJDIVcxJD\n3NiEcE5olhJBbKWcIgS0US0X15emQi4J56IgQBTWEAWmaq66VMxQLkvEgVcqwSuV4JZK8Hwfnm9f\n15c+vNJEfZ9b8nHHtV9GHLWM3tORNzGBV77jPX18JzTMXNfBua97Oh7dMY/bvvpTbL/j59AI8Eou\njjhpC0459zAceMTqhiCg8aKqjTCwXUWpmmCw8sPH8cRn78WmVx/HEJlGXlEDwafZ5c9S255plz/o\nUpF3M0wg+EzYQBCmW+8UgCdU9YEu5/2yPa9tICgizwHwZQBPAfC3AF7fbQITIiKiYTasE0Vku6um\nw7b0WHDpMC4OGwFd9zCuQ7iXOq6fs6+OknoY5zl48pFbYboJ5xEiWL4ex//SuWZW2CSU00alXNJ9\ntaVaLkxVyy0HqOytMZTLEcrV19P77LGuX4K/QoCXvE5fz/NLcNzVjae3uGcP7rvp29AcybaI4KhT\nz1jV56HxISI48MhZvPh//gKuvtr8unbhhRcOuFU0bGoPzXcOA1OSUDDYuYDSoexmTqOtcIGgiBwE\n4CL78t9Su460ywe7nP7TzLHp9Z+is3bnpT0XwP8DYAPMjMRv63KtOhG5CI33spJTAGD37t24+uqr\nc55CRcd7hfLivUJZ1Scd7L5tCnGIFSeKuO/7P8fuyoPwNig0NsOUaSzQGIBdprdpLPZ1en+yr7G/\n3blQ/jUfonYmULOE21gXN9kHIOmq6gRIuqxCAoiG9eo4IIRqYL/IAVSjpqo51RCII2iUbDPrQTVC\ndTGERiHioLeRUTT8GX70jX9Y8y/LwIhAXA/iunZWWRfieWbpuna7V183H/a1Y8/J7G86PnO9puNz\ndpGNYbrQtJ2HNwAQ1IClfs/Sa1RmNwOOC0Q5pgpxXCzNbOL3KGrBe4IAAAq4ocAPHBy6fQozgQfB\nyj8nxEGEBz9+C/ZsCRA7CnUUsQPEjpfXROUAACAASURBVNrXdl3QZj+gjpofR/gjyWhTYGrBxYGP\nlDE97w+6NatSqEBQRDwA/wRgI4DrVPULqd3TdrnY5RILdpn+U8Bqz0s7xy6/lzcMtI6AmcmYiIho\n1VRtnhOlwrUotYylZX8coXVf6nUw7yAOIwSLX1lxogh/w4ux5+7JAX4F1pkopCmEM+tIQrr0PhvS\nQRSQGEAASGi6rSbVcUgFdLFdj1PdWbURxiEyyzgKoZFdVpPXdlto1oeub3E/rXsol95XjO7ya2Vi\n8/7YsPVwLO7cAe3SdVhcFxu2Ho6JzfuvY+uIaBhIDPg1B34g8GsOvMCBHzjwa2KXZp8XOHBW8YdC\ngWCy4mFy5+rjFEUjHIxTgWEjTEzvbxM2Ou3Cxjb7pfnaDCHXSAwcef8GbNxTghObH9NGUaECQQAf\ngwnfHoKZUCQt+V+j13/K1Z6X9l0ApwM4Q0T+UlXfnPO8HQBuyHnsKQA2btmyhSXytKLkr6a8V6id\n9CQR229/FBqbsXg4ScTaUlXEoSKomTHgglqEsGZmTg1rMcJOr+2Mq03Lrsf1pxurmSjiK7knivA3\nnL8+943ATOqQnnXVczLjybl2u9jj3JZzHFfMJBBiq+Rgq+nUVMyphtAogMYB4jgwlXBRDVEy0UMt\n+aiaZWDWg1oNYbXaur9WA0cSMcRxcMJzz1qx++pKXV3XovsqDUZ0wQW45iMfwP233oSoVmvqPiwi\ncEslHHPas/HiN70Vrle0X3eoG/6MO7o0VsTLIeL5GiL7YdaD1Lp5rZUcFcQDJhC4tqfDuvIE4rkQ\n3zEfntN93XMgvttxP1qOtcd70jjPGa/fC1QVT3z6x6jMPT7yQ44U5jukiHwQZmbhXQDOUdVdmUPm\n7XIanSX75lPbVnte2rUArgDwaQC/LyKqqv+ry/UAAKp6FYCrVjoOAETkerCakIj2ESeJMGPQtQ3Z\nVgrfanGboK4RyqXPDWoxolo00gVaq5ko4uDjj4frNYd0ru+0CfCyE0I4cDyYSR9gKuIESXVcYCd6\nqCGOQ0RBDVFQaRu4pdeXF8x6UN+WPs4EeCP9D5RDenw5rzSRWm9+7ZcmMvtXXk+f87WPfxTbb70p\n95hwT3v2L+Mlb3rrOnwFaFi5nofz3/w27HrgXtzyhX/HfTffCI1CeBMTOOrUM/CsC16Og445dtDN\nJKIcNIjahHo1xHZbtFBDPFdDtBAA8dp/35UJF+5MCeHjy72V+LiCmbMOhYYxEMTQIIaGMTSIzHr9\ndZtlEPflveQSKjQMoZV1/JyOdAgaMyGj73YPGpuO7R5WwpW+/aE573iTo6AQgaCI/DmANwN4DCYM\nvK/NYTvs8vAulzo0c2x6/bAez2uiqp8XkVfDhIJvFhHkCQWJiNZLMknE9tsfQ1B5pOOYcNtvV2Ad\nJ4lI2pZU060uqOt8XhLOhbZKLw7HMARKZl4tufBKZgZWr+TAL9ngreTCLzlwSy58+9pN7ffteSbE\nAxxH8W+XX42eJopY+hoOOdq3lXKNAK620FgPqqlwLnNcFAT9/AoNBcd1m4M1v3NQ509MNF77+YI6\nc05ju+N66/L/8LNf9ko8eNdtCKvVFY91SyWcfsHL+t4mGn4igqcecxx+5S2XseqLaMhorIiXAkTz\nQZuKPlPFFy/UEM3VoNX8s4bn5gjcaR/OTAmu/XBm/NS6XU77cEqmQvzxT/0Iy3fvzhcKCjD59M3Y\neG636KA7jbQRIKaCwnR4iOy2pvWobdDYeT0CBvUzbKzQatSff+tOBB0qGt2cQWOy7kL8VFWl52Du\nup+af58xMPaBoIi8H8BbATwO4FxV/WGHQ2+zy6eLyGSHmYaflTkWAO4BsAxgk4gc3WGm4WR6s9va\n7KtrEwqqql7a7RwiovXy8x1z2H7Hz7H85Je7jgkXVo7G9jvOx6M7DsP+h8+078raLbRbsetrEtQl\nXWnN630auGFIOZ7Uw7mkGs4rCVxX4fqA58UQN4bjAq6rECeG68a2K2tsxqWTCCIxgMbSzrhhurVq\nBI0jRGGAOAwRBmYZhSGiMEC4HKI6FyAK7UytQVDfFyXH2XPCMFh11ZxGj+Fbnx6tiSJcz1u5Gi4T\n2mVDt6Z1v0M1nT1nXLu1HnTMsTjmtGfj/ltuRFjrPDGFZ7uBHnQ0K7+IiAYhrkXNoV427FuwlX4L\nNTMb0RqTstsS6rkzPpzpEtzZVMg35ffcTXX6eYegcs8Tuaq+xHMw87ytq30b5hquQFwXmFi/7+0a\nKxDlCw81ULvMGTqGMZBUR2b2D+RndEWjGpM6GutAUEQuB/A2AHtgwsA7Oh2rqg+JyPcBnArglQCa\nfisRkTMBbIXpcvzd1Hk1EfkvAL8G4DUA/k/mvKMA/CLMxGxfWqnNmVDwf9lKQYaCRLSu4ihGdTlE\ndTFEZSlAdSnETf/5AJb3fDnXmHDLe76Mz70PuWZqGyamy6KiEZqZD7UBGjQCJILrxnA8mKWr5sOx\nQZyjcJwIcBSShHAS2+6sybXMFLmmS2uEOJl9NQ4RRyHiyAZ0UYigGqKyBoFbEbi+b7ui5uu26qWO\n9Xs+pwTHGc+Abr2JCF78prfmHhOOY5QSEa0djRXxYtA8Jl+9m25z992+VfPNZKv5TNDnTpfgzJbg\nTpvX4vfv+27p0BmUT9y8YldQ8R2UT9wMf2u3EcOGkzgCOG5fv45ZqgrUqyHbdaFeIXRMKiXTlZFd\njq2fE/Hn5TzGNhAUkXcDeDuAJ2HCwK7VedZ7AXwOwPtE5Duqer+91gEA/soec7m2jup9OYCXA3i7\niFyjqt+z500D+AQAB8BfqeqTedreJhRUVX1LnnOJiBIaK2qVENUl81FZDOx6kFoPUV0MULHbq4tm\nWau0/sAXhz/rbUy4cBfEe2pzm/IEbnafIkK6mq2+LXWe2Wb2iRNBRBvLVGUcYAI5c2yjKs4sQxvE\nmZlWx7LUcB2JOHB9H2Ft5e6faY7r4rSXvmz1QZ1f4mytI4xjwlGvVBW1h+ax8M2dOOUHT4ETAw/f\n8m2Uj9+Emedvhb91muExFVpctdV8tmtuvYJvzlTw1Sv7FoK+/Ogjk16bUC9Z9+vBnzPpDcWkEyKC\nTa86Fk989l4TCmYr22wX1PKJm7HpVcfy+ZKTiNiJTBygvH6ft7lLtrYGiS1BY44u2XZZe3BubH5d\nGMtAUER+FcA77Mv7YSbqaHfoPap6efJCVf9VRD4K4A0A7hKRrwEIYGYmngXwHwA+nL2Iqt4sIpcB\neB+A74jINpgg8kwABwC4CcD/28t7yISCl9pKQYaCRAWjqgiqUVN4V12yVXs2vKu/zoR7taWwbTGZ\nCeXMbKjJBAxN6wjMaw2hqePC6g+xchiYCFGb/xwgZYjE9rqxvRbtExF4ng/X9+F4Hlzfh+t5cN3U\nul06ng/Xa95mPsy5XnKNdsfV93mZfX6Ha9hzbNXcF668HPfd9O3cE0Ucc8Yv4fmvubjfXz0aYhwT\njvLSKG76pd21E1xpEGP57t2o3PNE45f2MZ3giopJY0W8kJ1sIzUBR6rKT2t9qOZzpVHBN+3DnS2Z\n7rrZcfqmS2a8thEjroNNrz4Owc4FzH9jJxZ+8BicGHB8F+UTNmHmeVtROnRm0M2kHPrZJbun8SaH\n3FgGggA2pdZPtx/t3ABT3Venqm8UkW8BeBNMoOfCjBP4CQAfbVMdmJz3fhG5E8AfwIw1WAawHcBf\nArhCVXsrlQBDQVpfqopd99+LW77weTxwy03QKMQH//UfcNSpz8Lpv/JyHHQ0/xK2L8LAhnqpLrhJ\nRd7yYg2VhQqW55dQXaigsrSMykIFteVl1CpVxFH7gM5UujUCvPq+FY7LP9HDPr9rQBdGr4frOgVu\nTddOhWzpbemgLRu4DbvTL3g5tt92M8JqFZsmnorjZs/AwVNHwxUPkYZ4ZOl+/HjvzXii9jNOFEFE\nualqIwxs163PjhtV+eHjeOKz92LTq4/jzy8FN+zVpKoKrZmZdpu76dZaZt+NF/tTzedMeY1x+LpM\nxiGT6zPZ1CCJCEqHzmDza07At66+FwD/OEXNehlvctiNZSCoqlcBuGofzv9nAP+8ivOuAXBND8df\nBOCiFY75PIBSr20h6kUUhm3HbgprVdx307ex/bab62M3ud5YPjaaqKoduy2Z0dTMZFqrVLA8t4zl\n+SUszy+jsriM6mIF1aUKqksmvAsqVXteMvNpDVFYs2PFpcK7VFiXv+puTDBwK4SDjjkWx5z6HDxl\n+344uHwUHPHgiKkW8MTH1g3H4eCpo/FIZTv2HPUkJ4ogolxqD82vOMYX0AgFg50LrOgpsEFWk2qk\niBdbQ712Y/X1JViw1XxNY/I1TcZhw77pkunOSUS55B1vchSM/2/2RNSVqpow8Jab2o75paoIq1Xc\nf8uNuOYjH8D5b37bQP4yGIVhPZhLL4NaKrSrVpoCvOb9dlmtorpcqQd3jdCvamZPjWqIwwBjUQPe\nhev7LTOhtp/9tPH61i9dDY3zVxe6fgmX/MVfM3ArsGfv/1Is7XoUDlr/zR1x4EgJW6eehmP3P2AA\nraNhM+xVPDQYGisQKzSKoaFifttDZuynPOeGMfZ+7UE85VePBhwBHDFjlUkyuL4AIhAHgKT201jo\nRzWpqkKrUccKvvoEHAt9ruZrNwFHOuyb9gtRzUc0CG3HmxxRDASJCm7X/ffi/lvbh4FpYa2G+2+9\nCbseuBdPPeY4xFGUCudSwVsSsAWpfamKuUY4lwR2teZ9ybFB49igWoXGo/ugzUMcF65Xguub8M0v\nTcAvT8CfMMtsUGfCOxPkJfvq27qEen5pAm5pdaHc3GM/x703fgf5froVHH36GZjdsn/Pn4fGQ+2h\neVTv2dM2DExz4KJ6zx5W8RQcx4RbfxorEMX1gdcRqVmP4saMkE37GksNtbEe2euE6WNar9PxmDBz\nnUjt9e22eB8SFQWqP96DXf/3lt7OswGh2MAQzgoBYvr4dOBYPwapc83+xrkCkcx+e7zY8+GgsZ4O\nM+vHZD5/+vjU9dPvp+Vct0P7Ws7NvH8B0HRu6vMPWK/VpJV7noA7U2qaVbcp7FsIEM/3qZrPy1bz\n2a672ck4Nvis5iMaAtnxJnXwj7xVYSBIVCAax6guL6GysIDq4gKWF+bxnc/8E8JqviEuw2oV//In\nfwiB2NlYx5kDwAPEfIhdd1wfjlcyXV6TIK40AX+iBL9cxsRUGROTZUxsMB/l6SlMzkyiPDUJbyIV\nzGWq8Uahau70C34N22+7Jdf94pVKOP2Cl69Dq2hYLXzz4Z6qeOa/uRObf/OEPreKhtE4jQmnmlSz\nKZAEalG74C3OHJOEZ5ngLe916kFdKmxrOSYJ5Mz6mBfC75sYAOzXyuKXq0eC9gFiS5iaDUTtflfa\nh6DtqjubwtTGMZX7n8wd3mkQ4/G//+GafxmcDT7cmcaYfI6dcMOd9RuTccyWIBPu0D7XiKi99HiT\nC+8NBt2cVWEgSDSCgloV1YUFVBbmUVlYQGXRri8uNL2uLjYfU11cRId5cXLTKBrQD8WCdgEd4EMk\nWc/sa1r3AXgQ8eCVSiiVyyhNTWBiahLlKRvezZjwbnJmClMzZUxMeZiY8lDe4GNiykOp7BW6K9FB\nxxyLY057Nu6/5UbMyuaOk0TM4XEcc/qzOSbckNLYBgWhCQ80yCxDGxoEKx3TeI3suWGM4OGFHhoF\nLN+5Gw//+DupXwhhfikUALC/MCavk1/4ktd2X9Mxkj1Gmo9zZIXz2pzT8dodPp/T/tw87cy2seUY\noPGLdJ732+7zOXnOy/He0ObfYcWvb+NZ2nMVz31PonTQhi7VaUmQ1iV4y1S5NW/rEsClq906BHnU\nB66tYHMd6HLvf5B095sAVKExgCS0jdUEf2rX1b6mtaFofK0zm0ed+E5zFV+HCTicaZ8VzUQ01BgI\nEg1IHEeoLi42wrx0kLewgMriPCoLi3aZCvUWFhAGtUE337AhWxK0JaFc54DOTwV5dl+H41quA6fp\nF0iv5GBiym8K7CamPExs8FGe8sy+DV7jmOT1pAeHP5ytiojgvNdfisPe+0XMLO0HR9w2k0Qcg/mp\nJ3HC6y/gX7o7qFcQtQRtNrRYKXzL7guagzgNInOtTucPcWChVTNG5fC2kNZUEhD20CVUgxiPf+Lu\n/rWpaDyBuE49bBNXTHdEG8CJa9e91DFeantyTLvruAJ4TvN16scm11z5OvVKMevxT/0Iy3fvzjt6\nBSZP2pK7+lhVzXVtQNguQEye4YgVmj42apzbOKbD8fVjkDq38/HpwLJlvd7W1Oevb08f3+b9NF0/\ne27meIUJvzWzP/35k+NH+CHuH7TBdtPNTsDRCP5YzUdE44KBINE+SCbcWG5Tjdeo2JtHZXHR7kuO\nW0B1aXEgbRZnAo5bhkgZKhOIqg+ht5/cPEzs90YA+/7DkOMJJqayAZ4N7+y2cirUm9jQCPdcn6He\nelNV7P38djwlOhBwWssozCQRDjZFB2Lv57cPd7e+ZOysIBWktQnj8lTIIVQbwqVDue5B3ij/skS0\nZpIKonHjoCkAaw7G0kFXm3AtE5K1C9TEk+ZrdwryvBWCuSEZ561X0887BJV7nsjVFVQ8BzPP25r7\n2vUqWNsbYPS+OsOhKexMAskoE6C2hImpADOz3hSCpsPWdNjZErYqnvzC9p7+CCa+gwMvPbVPXxUi\nouHDQJAIZgbb6lIjtKt3vV3IdL1dbGxL1gczlp4DccoAyoCUzbqUITIBkWS9DDjJ60mITAAyAZHm\nseo0/iLi4D4Aik0TT+3YDfSJ2s8ACBz/KFvVZ4igKbArpyr12oV65dR2r+SM5C8jRZV060PObn0r\nTRKRdMNLKtq6Vr+ltrWvomutuEPY5jrJviGuklsXnmOCB99+eDaISG/3HMB32m6X1HZkz7f79n5l\nB6r3P5m7iqd84mZseuWxjV/skioTu25yo+YKlHo1T/11+rw2x8St59Sv3e285NrxSsesdO32n6/+\nust7y/X5Wr52K723NsfEba6NzOePO18/z9dyLQLxelc8T1oDsw4BXCMwS0K1TEjmrdF1Cjy0xHoo\nHTqD8ombV+xmLr6D8omb4W+dXsfWEWCDVRcAZKChavWBvT1Vk5ZP2NT3NhERDRMGggWz80c/wBeu\nvByn/8rLcdDRx45VGKOqqC0v1yfLSFfjtVTsZcbZqy0vD6bR2QAvee1kXtv9SfBnutOuzb+dVz4N\nQbADz97/PBwydQwc8dp0Az0aDy/dj5se+wpKG56FV/3vZ9VDv9KEy19+hljLLJJxaqyrNuvtxs5K\nxtZa+N6ungbnfuyTd8PbVO4wzlxc7LGaHBug+Y0gDR0Ct+4BnbQGdNnzM9fMdr/rl9lzD8fuHXO5\nq3hmzzoUTpk/lhRBNpB85E+/29OsneI7OPgdz+lb+2i4iQg2verYplmpmwIfMc+U+qzUY/SzLvWm\nn9WkRETjgD95F8yWiUOw+YHNuPbPPojNzzgCL/m9t8L1hus2CIOgEeQtzNsx9LpPlpGEfRoPImFw\nUxV5NriTRsVecwVfOuSbgMi+dXsVAUqTZrKL0qSH0qTb9Hpi0oVfNuPmme12vz1mYtLDtn/8Ifb7\nkeDg8kHwHL/lc5huoCUcMvU0POfAGcw9/enY/7DOVV/jrClci9qsh7arSno9GYA+bh7AvmlWyNR6\nvv2dj83uH2TXVF0KESz1MLHEemtT1dYUnHWpihNPulfRZba1HOOO/y+orOKhTurdMs0rlI/fxCoe\n6om4Dja9+jgEOxcw/42dWPjBY3BiwPFdlE/YhJnnbe1aoU7FwO9DRETdDVcSRH0nEGzdcCwOnjoK\nD9//AL78oQ/ggkvftuZ/PdU4RnV5KdO9tk3FXpuZccNqdU3bko9kqvHaBXlJ2DeRqeBrDdHycH3H\nhnbZoK41tGu3vTTpwl+DQY2f+cwDUN2xF94K1/EcHwdPbsWRpxywT58vYcK1TuFXh0AsqXDrFL6l\nZ42M4+YZJjsGas3r7QO/wYdrY0nQputp54DOhHQC8d2mQG5V3VzZra/vWMVDebGKh1ZDRFA6dAab\nX3MCvnX1vQCACy+8cMCtomHC70NERN0xECygRsXXMcAD9+OR+36MQ449vu2xQa1qZrxtO1lGc7CX\nDvuqi4tQHUS1nm+DvGxX3HQF30RmezK2Xs4fAgT1QG4iXZ3XEti1qdBLVfC5XqM6MD0uU+fZ49AY\nLDmMgL0hQkV9Zrr6DHFNM8ClrpGd9c5e1/nez+DmfO+uCHD9T/HEjr3mfFv91mm9WzUdw7V1IsgM\nPt9hBsfMessMk65g8eaf9zQbKDzBAb/7DIifqrZLB3mc7XnssYqH8mAVDxH1C78PERF1xkCwwDzH\nxyFTR+NbH7oKG084yHbNTQd/C4iCWs/XFZiJIlzxIRCIOKml2Wf+cyDiwIHYbcl+FyIlODasc2TC\nzIwrJYj9SNYdpwQRH474EPj2c5iutILMhwCuI3A9B54n8DwHrmvWXVfgug4cV+A6Asd+uA7MughE\nzKRzIpIK7mDXY2AxAhaq9eAuG74FqghixUJ2VrVkIPkByvv3UAEQ7aliac+j/WzO8OoQrrWGZyuH\na00zPXbdnxnI3kkNfG/X4TqQ9Hr6vDWsgouXwp669U2euJk/ZBOreGhFrOIhon7i9yEiovYYCBac\nKz5Om3gBFu7dA0cObgR1UwKZchpBXT2wawR8ThL02f1OZvbaoRYrUIsARCseqrmOolXxBOIkszSa\n9fqMkfX1TAiWNzxbcb9d90zSK53Wk/He1jhcG0Xs1kdE/cIqHiIiIqL1xUCw4EQEZW8KZW9q0E2h\npIzREYiTXhfAsZWJTmqbILXfvG6s22vUj7Xn2Qo3s9+cs3T7o71VKLqCp/za01boatqhK2pS4eY6\njfdEI4Pd+oion1jFQ0RERLR+GAjS2rNBVTqMEhepUMqGQ8lx0gi96vtzhmDS8rnQGoI5rZ+neb/9\n3JIK11LXbhzb/Lp+3XSbBSb8ygRwTfubPkfmvQ6ABnFv3UCfvhkbTjuw7+2i4cNufURERERERGYe\ngMqdd+LxT3wSkz/ZMejmrAoDQUKkEfS8o1Aqe/AnPfhlD/6UB2/CheNmQ7JUoJYNxpJAjUYKu4FS\nL9itj4iIiIiIikyDAI9cdhnmt30dWq1CBjKh6r5jIFhwscZ4ciLGM84+bNBNoQFhN1DqFbv1ERER\nEdE4Sld9HbNtGyQIcM8734Xps87C5ksuRvmkk9gLpuBU1YSB122DViqDbs4+YSBYcLHGOOD8Ewbd\nDBogdgMlIiIiIqKiy1Z9ObEpltBKBfPXXouFG27AzNkvwMGXXw7x/QG3lgalcued5h4Z8TAQYCBY\naGEcYmGmjMPO4HhwRcduoEREREREVFQrVn3FMXR5GfPXbcMjl12Gg6+4goUSY0DjGAhDaBxDwwiI\nwsa2KDLb4qhp36N/8cGxCAMBBoKFFGuMGMDi7CSO/8PT4TjOoJtEQ4DdQImIiIho3LALKOWRt+pL\nKxXMb/s6KnfdhcmTT16n1q0NVa2HX/XAK4qAZNlum11qGNr12ARj6f1JWBbF0ChsbLNBmtkW2+ND\nsy2OgDDzOaLQbEvvq18jarQ9uUb23OTzt+xr8x7t1wCaZ2bN8cVAsGAUwPz0BDaddwSOOOOgQTeH\niIiIiIioL9gFlAAbhNlQS8PQhEJJMBSEQBTisQ99OHfVl1Yq2PVn/x82/eZ/awRe6QqzJNSKsoFY\nEnilQ61MWNYx1EodZ9veLixr+hyZgA/xaE58Qf3DQLBgykdtxNP/+DmDbgYREREREVHfsAtofvXw\nqN5NMoQGQWuIlgrQzPakcsy+DkIbSDX2ZV8jSo6LoGFgwqv65w6BoNGGjscmr9PHZtqffo0wXOMv\nmKJyxx145I471va6NBieB3FdiOsCydJug+tAXK9pX/W++8amspCBIBEREREREY2VteoCWq8uawnD\n2leaNYKy5kCt3uUyCJtDtPSxNlAz184Eat2CsfSxqZCs+7EREAS20oyVY4WRCbzEcVLhl9sIxjwv\nsy8VjHkuxLHLTFgmngs4duma/fVzk31u+lwHyFzXnJvsc5vP9TLtzOyrb0uu67mA40Dq78Psa3qP\nPdp56Vswf+21Y/H/DQNBIiIiIiIiGkkahojm5xHPzSGam0O0dw7x3F7s/ruP5+8CuryMB3/rv8OZ\nnm5baUZjoB5YeSYISgIi34O4HoKdO3ur+nJdzL70/ObAKxuM5Qi18gderaEW7PvJHeo5TmGrYNfS\n5osvwsINN0CXlwfdlH3GQJCIiIiIiIgGJq5WmwK9aG4v4vn5xvreOUTz8431uTlE83OI984hXlxc\nkzZotYqoWl2Ta42kJCSrB2V+KkBzIZ7fNlAT3752vdZjfc+GVunX9ty2++xrz34e1xxXD7c67GsJ\n+dLvxbPXXaESrKeqL8fBzIvOxSHvf/8affFplJRPPhkzZ7+g83AEI4SBIBEREREREa2aqkKXlkxQ\nNzeHaG8m0JubQzTXPtCL5uagwx7EOU7nkCwdjLnpQK1DSFYPw5LAym0TqNnXTSFZ5tj6vkzwlQ7N\nsiFfp7DNdQtfOdZL1ZdMlLD54ovXoVU0jEQEB19+edOERaOKgSAREREREVHBaRybEM+GenGnar16\nuDeHeO9eG+7ND65rrQicmRm4MzNwNs7Cnd0Id3YW89ddZ2ZWzXuZchnHfPXa5uq3JFRbxThjNFry\nVn1JuYyZs89G+aST1rF1NGzE93HwFVegctddePwTn4T+7d8OukmrwkCQiIiIiIhoDGgQNAd6yZh6\n80m4l4R684112x03np8f3MyZngd3Zgbu7CycjSbQc2dn4MzagG/jrAn9kvXZWXvMLJzpaVPlltFr\nF9DpF5wFb//9+/DmaBS0rfpK3zuOA5koYebss3Hw5ZcXvqKSzD0zefLJ2PoXV2L5a18FfvCDQTep\nZwwEiYiIiIhopKgqKnfeicc/25nbrQAAIABJREFU8Ukcs20bJAhwzzvfhemzzsLmSy5G+aSTRvIX\ndlWFViqI5uYRz+3tKdCL5uagS0sDa7tMTNhAz4Z4mYo9Z7YR6JnXjVBPpqbW/N+LXUCpV9mqr73X\nXQcJQzjlMqbPOhObL7kEk6wMpDHCQJCIiIiIiEaGBkFTFY9jq3i0UsH8tddi4YYbMHP2C0wVj++v\nf/tUES8uNrrT7rXj5aW74HYI9OK9e6FBsO5tTjgbNuQP9GZmm8I9Z2JiYO1uh11AaTXSVV+3Xn01\nAODCCy8ccKuI+oOBIBEREREN3LhWfNHaUlUTBnYKeeIYuryM+eu24ZHLLsPBV1yxqvtGo6i5223T\nmHrNFXumki81pt78fL5uqv3gODbIM4Ge6V6b7oJr1ze2BnruzIwZM29MsAsoEVF34/PEJyIiIqKR\nNOwVXzQ8Knfeae6TLhVfgL13tm3D4je+Af/QQ82stznCvaR6L15YWKd31Ep8vxHopbvgdhlTr16l\nt2EDJ8BIYRdQIqLOGAgSERFR37Dqi1ayXhVftG80joEwhIYhNIqgYQhEETSK2m8PI2gYNNajZHvY\nfEyyPQhTx9jtYZg5N8L8tm25xoQDAF2u4KHffX2fvzLtydRUa6CXc0w9KZd5j68hdgElImqPgSAR\nEfWEAQ/lxaovyqO3iq+vo3LXXZg8+eR1al2bdqiakDIJwpIQrL4eAZFdD8LGepgOxKLu21sCsdT2\nMEwds8L2IGw+JrIhXfbc7PbU+0peD2z22QFy0oHezGzXaj13xnbHtetSKg26+URERF0xECQiotwY\n8FBerPoab+1CsaRarG3YFcVtArAIiCM89pG/WjEMrH/eSgWPvOOPMfvi81pDrdBWmLUJxNLb08HX\nittTgZgm1XADnPCBVqd0+OGNGW03JuPlpdbrAV+qWm96GuK6g246ERFR3zAQJCIArPqilTHgoV6M\nWtVXXvVuk3Hcc/DV0p0ySnW5bOlWac/JbDPrcZuulfY6ceu2pnOygVfyfrLhWP2cTBhm3zvCcED/\nAIravfdi9733DubzF53vQ1zXBGWeZ9Y9D/BciOvZ7S7E8xvrdrv4HpA+ptt2z4N4btvtj155ZU/3\nn0xO4uivXNPHLwoREdFoYiBYMEu33IKdl76FAQ81YdUX5TGuAc8oUFXTXc9WZUEVCtTXEce2N19q\nfzKTYvqcWM0x6W2Zaze9Tq6jADRObUv2Z7alPv+jH/pQT1Vfu979Huz3qlc2wrCk6iuO2gdfUdQS\nYpkgrkPwtZpzmsKy4nabpA583wRXbQOyZL0RarXdngm+xEuuk3O77wGu27zds5/Lfk5xs58rtd3z\nMse4rdvT73EILN91F+avvTbfLL6Og+mzzux/o4iIiEYQA8GiiWMGPNSEVV/jQ1Wbx7AKgzZjW4Ut\nr+vryYDu6UHcw0ZXvD2f+XT+gGd5GY/84dsxfeaZANIBkgmRTHfDVOiUBEst29AIvdLXiWPzOn1O\nHEPrYVfmc6WuU79ut1AMzW3p3OZU+9LXqYd2ze1rG+ShuS3trjP2VFG56y7suuuuQbeEeuE4Nkhy\nW4OjesjkpCrHUvvrx7lYuul7+cKdhOdh8++8zlShJQGXmw672mxvCtMa201wlgnKMkEYXBeSrYzj\nLK4Ds/nii7Bwww25JhaRiRI2X3zxOrSKiIho9DAQLCIGPJRShKovVW0esL0elDWHZisGZe1Cs/SY\nVWH3QG3lfan1IN3lMHNckKpYClKhXxQN+kvdpLZjB57YsWPQzSBae22DL7dNpZgLODnCsmwlmOO2\nCbo8iOu02ZbznEwVGBynfWVY/ZxMtZjb+Bz197tGodjOS9/SU8XXzLkvxAGXXromn5tGT/nkkzFz\n9gs6/yHTknIZM2efjfJJJ61j64iIiEYHA8ECG+WAZ1A0qdRJV+xkt2WW2um4buc0TurhnEwVUY7P\np6p47GMf66lb36MfuBL7v+mN9UBNw6B9UBYlAVsqyOo5UEsN8t4uDAuDDtcY7qCMaNUcBxABRMwf\nckS6bpP0OY4DCCBIneOIeZ0+J7lG+hxxVtgmzdcVwfJtt/VW9eW62PjylzWqyZKALTuOmNNmW7sQ\nq6kazF198JUN8lgZtuZY8UW9EBEcfPnlTUOdND1rHAcyUcLM2WebnjD8ozcREVFbDAQLTpeX8eBv\nXwRv8+Y2QVY6SELTvs7hlzYfn+OcluBsNef0OaAjSxVLN96IB2+8cdAtoU7qIYrXOgZUEmwkA7i3\nG0PK91oHerfjTj35+X/vLVz1fRzwlreYsKgeMqWCqKZtMEGLCIBU6NS0zZ7jOACk+Tr1balz6oFV\ndhsa57QL0pBpX8drZ6/j2KauENJlAzcIxGne1hTkpa8zQnqu+nrRuTj4Pe/pf8No6LDii3olvo+D\nr7gClbvuwuOf+CT2XncdJAzhlMuYPutMbL7kEkzyPiEiIuqKgSBBl5cR7Nw56GYQ9Vc2KGsTmqVn\nOmwN1BqzJmaDsvqYVdlrZI9LjWHVGLeqddyr+j4/1Z3PbzcofZvQr4+hUTS/0FvA88JzsPkSVvIU\nFau+KC9WfNFqiAgmTz4ZW//iStx69dUAgAsvvHDArSIiIhodDASJViv9C0my3mEpnY5br3O6nBvt\n3t3u3XUmgslTT+0elKVnPswTlLULw7ruaw3NugZlazjWVZEx4KFesOqLesGKLyIiIqL1xUCQIBMT\nOOqLX7AvkuBIml+mX3QMm6R50UNg1jisl3Mybex3QDemFQk9d+s770XYeuWV/W8YDR0GPNQLVn1R\nr1jxRURERLR+GAgWneNg+uwXoHTooYNuCQ0Iq74oLwY81CtWfRERERERDScGggXHgIdY9UW9YMBD\nvWLVFxERERHR8GEgWGAMeAhg1Rf1jgEPERERERHRaGMgWEQMeCiDVV9ERERERERExcFAsGgcFzPn\nvYgBD7Vg1RcRERERERFRMTAQLJip00/jDLFERERERERERAXmDLoBREREREREREREtH4YCBIRERER\nERERERUIA0EiIiIiIiIiIqICYSBIRERERERERERUIAwEiYiIiIiIiIiICoSBIBERERERERERUYEw\nECQiIiIiIiIiIioQBoJEREREREREREQFwkCQiIiIiIiIiIioQBgIEhERERERERERFQgDQSIiIiIi\nIiIiogJhIEhERERERERERFQgDASJiIiIiIiIiIgKhIEgERERERERERFRgTAQJCIiIiIiIiIiKhAG\ngkRERERERERERAXCQJCIiIiIiIiIiKhAGAgSEREREREREREVCANBIiIiIiIiIiKiAmEgSERERERE\nREREVCCiqoNuA60DEdkJ4JCNGzfilFNOGXRzaMjt3r0bALBly5YBt4SGHe8V6gXvF8qL9wr1gvcL\n5cV7hXrB+4Xyuvnmm7G0tAQAD6vq1kG3Jy8GggUhIksAJgfdDiIiIiIiIiKiMbSsqlODbkRe3qAb\nQOsmsssagO8OsiE0Ek4BsBHAXgC3D7gtNNx4r1AveL9QXrxXqBe8Xygv3ivUC94vlNcvAiihkbuM\nBAaCxXErgDMBfFdVzxpwW2jIicj1MPfL7bxfqBveK9QL3i+UF+8V6gXvF8qL9wr1gvcL5ZW6V24d\ncFN6wklFiIiIiIiIiIiICoSBIBERERERERERUYEwECQiIiIiIiIiIioQBoJEREREREREREQFwkCQ\niIiIiIiIiIioQBgIEhERERERERERFQgDQSIiIiIiIiIiogJhIEhERERERERERFQgDASJiIiIiIiI\niIgKxBt0A2jdXAXgegA7BtoKGhVXgfcL5XMVeK9QfleB9wvlcxV4r1B+V4H3C+VzFXivUH5XgfcL\n5XMVRvBeEVUddBuIiIiIiIiIiIhonbDLMBERERERERERUYEwECQiIiIiIiIiIioQBoJ9JiLXi4iK\nyEWDbks7InKRbd+72ux7qYi8W0SuEZHd9riFVXyOKRG5z56vIrJlTRo/4kRkR+proiISi8iciDwk\nIl8TkfeKyMmDbmc3vH8Gq4jPl8z/M+0+LuvLmxkhfLZ0vCbvnZyK+GxJnX+8iPytiPxERCoiskdE\nbheRD4nI9Jq+kRHDZ8uK1+a900XRnisiclWO7zsqItv69qZGBJ8tba/H+yenoj1bUue+WES+ICK7\nRCQQkb0icqOIXCoipbzt46Qi1M2nAGxcg+tcDuDoNbjOuPoKgF12fQrA/gBOB3AOgMtE5AsA/qeq\n7upw/rDi/UPd7Ov98fcdtt+1D9ccN3y2tMd7Z7yt+v4QkUsAfAyAD+AOADcBmAVwHIDfA/A+AD3/\nYWsM8dmSwXtn7K3m3vjWCvt/E+Z++fqqWjSe+Gxp4P1TDKv6vmPDxXfal9+DmcxkC4DnAXg2gFeJ\nyNmqWlnpWgwEqZt/A/BjALcCeBzAbb1eQETOhPlB6K8AvGlNWzc+LlfV69MbRMQB8CsAPmCXN4jI\nL6nq4wNo32rx/qFu9un+UNWL+tCmccNnSxu8d8bequ4PEXkJgL8DsBvAK1T1m5n9zwDwxNo2dWTx\n2ZLCe6cQer43VPXvYO6LFiJyBoDfBhDDzExKBp8tFu+fwuj53hCR4wH8CYAAwEtV9aupfUcA+CaA\nXwTwBgBXrnQ9BoLUkaq+Llm3N1dPRGQDgE8A+CmAy8BAJzdVjQFcLSLfgEn9jwXw5wAuGmS7esH7\nh7rZ1/uDVofPFhp3q7k/RMQH8NcABMBvZAMde9071qiJY6mozxbeO8XQh+87yfWuVdWH1uB6Y6uo\nz5YV8P4ZE6u8N86E+Z6zLR0G2uvtEJGPAvgzmFBwxUCQYwgOQGpMgIs67H9Xu37m6e0icqCI/LWI\n7BSRqpjxSi4XkfJ6vIec3g/gKJjSbnaTWAVV3QPgUvvytSJyUPYYEdksIu8RkbtEZEFEFkXk+yLy\nFvuDalsicp6IfF5EHhGRmh1/4Nsi8nYRmezXe+oB759VKNDzhfZBwZ8ttApj/mz5VQCHAvieqrL7\n1T4o4LOF984+GPPnSlv2Xv0N+/Ljg2zLKCngs6Ut3j/5jPmzpZrzuN15DmKF4Gg6FKasVAB8B2aM\nkucCeDuAE2F+OBkoETkbpkz1k6p67aDbM+K+DNPVZBOAFwD4l2SHiJwE4BoABwPYCTN+gAMzdsAH\nALxURM5X1VrqHIHpgvt6u+kWADfY658AM2bfZwDs6ON76or3z0AN/fMFAETkDwAcAyAC8ACAL6nq\nvYNt1cgp3LMF4L0zQMP8bHmRXX7F/rL1SphxqxwA9wD41xEcs2qQivRs4b0zWMP8XOnk12HGDNsN\n4D8H3JZRU6RnSye8f9bHMD9bvg6gBuBsETk302X4cJjfoWOYnnYrYiA4mi6BGVPgTclDTUROgCmj\n/hUR+WVV/XaeC6nqVVjjsQfEzKT2cZhBYd+6ltcuIlVVEbkNZkDdpyfb7Q+eV8N84/vfAP6vqoZ2\n3yaYb2AvtPvelbrkpTDf+H4O4GWqemPqmgLgLAB7crbtKvD+GTdD/XxJuSLz+s9F5OMAfj/PALpU\nvGdLCu+dwRjmZ8tJyaVhJpfJTmT1fhF5o/28tIKCPVt47wzWMD9XOrnELv8xHU7Rygr2bOmE98/6\nGNpni6o+KCJvgJnI6loR+R6An6AxqcjDMPfzLXmuxy7Do+khAG9OPwRU9UcA/tG+PGcgrWq4AsAR\nAN6gqk8OuC3j4jG73JzadhGAIwF8VlXfm3zjAwBVfQJmsNkAwJvsNzWIiAfzzRAALkp/47Pnqap+\nXVX39udt5ML7Z7CG/fnyKZi/yh0OYBLA8TB/rVsA8DvoMAAzdVSkZwvvncEa5mfLJrv83wCmYSow\nNsH8f/BnACYAfFxEzhpI60ZTUZ4tvHcGa5ifKy1E5CiY8b+AnNU71KIoz5YWvH/W1VA/W1T1EwBe\nAhNmnwHTjfwcmIK/bQB+lPdaDARH0zZVXW6z/R67PHg9G5MmIi8E8LsAPqOqVw+qHWMo+X81Tm07\n3y4/1+4EVX0EwH0wfy14mt18un29U1Wv6UM79wnvn6EwtM8XAFDV16rqF1T1p6paUdUfq+r7Yf6K\nGwJ4jYicPsg2jphCPFsA3jtDYJifLcn/Bx6AX1fVf1PVPaq6Q1XfAdOlzAHwzoG1cPQU5dnCe2ew\nhvm50s4lMF0Qv6eqdw+6MSOqKM+Wdnj/rJ+hfraIyLsBfBWm+/AzAGyAqVB/N4D/DuAmETklz7UY\nCI6mn3bYPmeXAxnoUkRmYLp67gbw+4NowxjbYpdPpLYdZZefs4OftnzAjHEAAPvb5eF2+eM+t7dn\nvH+GxlA+X1aiqt8H8AX78vxux1KTsX+2rIT3zroZ5mfLvF3+SFW/1Wb/x+zyuSIysU5tGnVFebbw\n3hmsYX6uNBERB6ZSDeBkEPuiKM+WJrx/1t3QPltE5DUA3gHgK6r631T1TlVdUtXtqvoumG7xmwB8\nMM/1OIbgcFopqI1X2D8opwE4DMDPYB7InY67WkQCAB9W1X9dr8aNKlva/kz78q7ULtcuv4SVZxF6\nfK3b1Qe8f9bHqD5f8kj+anfIQFsxIgr0bMmD986+G+Vnyw4Ap8KMwdNOst2D6ab2yDq0aWQV7Nmy\nA7x3+mmUnytZLwKwFcASgE8PuC0jqWDPlizeP2trlJ8tF9nlP3fY/ymYISueKyJlXWF8bAaCg5H0\nRZ/usP/wDttHxVPtRye/ZJf/sQ5tGQcvBfAUmC5t16e2PwTgOAAfVdUv5bzWg3Z53Jq1bu3x/tk3\n4/586SYZT2ZhoK0YHUV7tnTDe2dl4/xsuRXAr6F5TKq0Lal13iMrK9KzhffOvhnn50pWMhnE51R1\nruuR1EmRni1ZvH96M87PlsPsstP4lskY/A7MjNRdA0F2GR6Mh+3y+OwOO0vSWevamjWiqterqnT6\nSB26v932FwNr7IgQkacAuNK+/HtVfTS1+7/s8pU9XPJWmL+cbRWR89agiWuG98+aGcvny0rse7vA\nvrx5kG0ZBUV6tqyE905u4/xs+Xe7PElEDmiz/4V2eR9/EeuugM8W3jv7ZpyfK3UishnAhfYlu3uu\nQgGfLXW8f1ZlnJ8tSaX5czrs/0W7XMDKFbMMBAfkOrv8LRGp/1XC3pwfRSP1pYISEUdEfhXml9Nj\nYLqzvS1z2N/A/EXst0XkT0Vkqs11fkFELk5eq2oA4L325SdF5IzM8SIiZ4nIxjV8O7S+xvb5IiKv\nEZFj22w/FMDnYQb43YHGL2iUUdRnC++dNTG2zxY7c+DnAUwB+JiIbEj2icgvwAzSDQAfGkDzRkJR\nny28d/bZ2D5XMl4LoAQTDH9z0I0ZJUV9tmTw/undOD9bkiGz3iJmQs46ETkGwF/al59T1Wili7HL\n8Pqp90NX1W+JyBdhKhK+LyLfhCl9Pt0e90kAF7e9yjoSkT+GKc0GgGQg5EkRSU/L/iVVfTdoX1wm\nIhfZ9TLMYLenAtjPbvsPAL+rqnvSJ6nqgoi8FMAXAfwJgN8TkTsB7AJwIIAjARwB4CaYeypxJYAT\nAPwOgBtF5BYA98MMPnoigEPtuZ3KkHPh/bOuivJ8eSWAfxKRB2DCm90w39CfCfP/ziMALlTVaj/b\nPkL4bGngvbM6RXm2AGaG+xMBvBzAAyJyE4BZmL/AlwF8BsCH+9bw0cJnSzPeO70p0nMlkbwHVnd1\nx2dLe7x/8inKs+Vv7DkvAfBVEfk+zH17EMz3nRKAHwD4wzxtYCDYf5N2uZjZ/koA7wTwagBnw/xy\n8iWYGWN+d91a193RAJ6d2eZktt0D2ldJmbrC3CdPwpSxfw/AP3ebVl5V7xKRkwG8EaaU/FSYb6CP\nwfyl7B/R+CtCco4C+B8icjWA1wM4A8ApMLN13QfzV+xda/C+eP/0X9GeL38P815PgQlyZu3rO2Bm\nif2r7A+JBcdnSwPvnd4U7dkCVd0tIs+C+QH6VTD//9QA3ALg7wD8g73Hic+WJrx3civccwUAROQ0\nAM8AEAH4h760bnzw2ZLB+yeXQj1bVDUQkQtgJhd5Dcz98QyYCWfugKla/0tVXcrTAOH3p/4REQHw\nKMyAwqer6q0DbhIRjQk+X4ioH/hsIaK1xucKEfUDny37jmMI9tdvw9ycj8GktUREa4XPFyLqBz5b\niGit8blCRP3AZ8s+YpfhNWYHMf1rmPLPZIaXP1bVcHCtIqJxwOcLEfUDny1EtNb4XCGifuCzZW2x\ny/AaE5H9AOwBMA/gTgAfVNXPDbZVRDQO+Hwhon7gs4WI1hqfK0TUD3y2rC0GgkRERERERERERAXC\nMQSJiIiIiIiIiIgKhIEgERERERERERFRgTAQJCIiIiIiIiIiKhAGgkRERERERERERAXCQJCIiIiI\niIiIiKhAGAgSEREREREREREVCANBIiIiIiIiIiKiAmEgSEREREREREREVCAMBImIiIiIiIiIiAqE\ngSAREREREREREVGBMBAkIiIiIiIiIiIqEAaCREREREREREREBcJAkIiIiIiIiIiIqEAYCBIRERER\nERERERUIA0EiIiIiIiIiIqICYSBIRERERERERERUIAwEiYiIiIiIiIiICoSBIBERERERERERUYEw\nECQiIiIiIiIiIioQBoJEREREROtIRE4RERWRJwfdFiIiIiomBoJEREREQ0BEvmpDoptFxF3h2NNE\nJLTHv2a92tgvIrKffS/Jxz/kOOf61PFDE6yJyItF5F0i8uJBt4WIiIioEwaCRERERMPhfwBYAHA6\ngD/odJCIeAA+DsAF8EVV/dT6NG9d/ZqIbOi0U0QOB/D8dWxPL14M4J12SURERDSUGAgSERERDQFV\n3QHgj+zLPxWRYzscehmAZwDYC+D169C09fZTABsAvKLLMb8FQAA8uC4tIiIiIhozDASJiIiIhsdH\nAHwTQBnAx0VE0jtF5AQA77Av/0BVH17n9q2Hf7LL3+pyTLLvn7ocQ0REREQdMBAkIiIiGhKqqgBe\nB2AZwHMB/F6yT0QcmK7CEwC+qqofz54vIq6IXCIi20Rkt4jURGSniHxKRJ7Z7nOKiCci54rIR0Tk\nNhF5VESqIvKwiHxORJ7bqb0icosdw+/XRWSLiHxARO4TkWUR2bnKL8N/AXgMwNkickibz/kcAMcC\nuBvA7StdTEROFJFPisiD9n09br8+r80Grqlzbrfv62UiMiMi7xWR+0WkIiI/E5H/v737D9WzrOM4\n/v7mnHnm1LnUuS3bgiDUcsT+6ccfrmWiBE1niBVTFhUEbQhaIbNU/EFGphBSrD+cs2Vgs1/MyNBp\nhZSSYZsoqxSKtrXM3HRNd+a3P67rbmfP7uc5P3Xn+LxfcHOf576v6/7xnH8On3Nd13ddnbY8tM+i\niEhgdT20umNdxIyIE7vcb3FEbKzf/b6I2BoRVw23lqQkSdJYGQhKkiRNIpm5Dfhq/XhzRCyoP38R\neD9lncHPdvaLiFnAZkpouAQ4iRIszgM+Cfw+Ila23HIx8EvgC8AiYCYwCMwFLgYeiYhVwzz2POAJ\n4Apgfu0/VoPAPZS/Uz/dcn5F3Y+k8MillNDwcuB0yvdxPOX7WQ9sjIjpPS7xNuAxyjTtuUACc+oz\nPBoRc4e03Q/sBPbWz3vr56Hbay3PuBz4LXAhML1uZwC3UH6XkiRJE85AUJIkafL5FvA7ylp6ayNi\nIXBjPfeVzDxk7bw60u2HlFGFjwMfBQYy8wRKqHUdZc2970bE+zrutQ/YAFwAnJKZx2bmDEoAdkNt\nc2tEvKfH894AvAIsrfedCZwz6rc+qAn7Dpk2XMO7SyjBWs9iKhHxXuBO4GjKqMN3ZuaJlEDwCuAA\nsAy4qcdlvlH3Syi/i+Mo3+0/gdOAa5uGmbk1M+cAa+uhtZk5p2Pb3XH9AWBdfZf59flO4ODv+rKI\n+ECv95QkSRoLA0FJkqRJJjMPACuBV4GPUNYVnAE8AtzR0uXjwLnA08CHM/OBzNxXr/V8Zl5LCb6m\nAV/quNcfM/NTmXl/Zu4acnx7Zl5DCcWOAj7X45GnAedl5oN12jOZ+efRv/n/7/048BRwZkeA+THK\nyMdfZeY/hrnM1yij7Z4ElmXms/Xa/83M24Cra7tVETGnyzUCWJqZm7M4kJkPDOl78ahf7lBHA/dn\n5spmPcjM3JOZa4DfTNA9JEmSDmMgKEmSNAll5lPA9fXjPMp01880gVuHy+r+e5m5p8slN9T9uaN8\nlJ/V/Qd7tNmYmX8Z5XWHs77uVww5NqLpwhFxDCU8BLglM19taXY78B9KKLesy6Xu6lK45cd1P6tj\n2vBY3NzleHOPs8Z5fUmSpMMYCEqSJE1eX6cU2AD4To9Rd8200jURsaNtAx6ubU6KiIGhnSPiuFrE\n4tcRsSsi9jeFMCijE6FMIe7m0TG823DupkwNvrQWPplNmda8B7hvmL5nUUYHAjzU1iAzX6Gs3QfQ\nOY268ViXvs9TploDzBrmWXoZpHthlCaIHM/1JUmSWk070g8gSZKkdpk5GBFNkYrO9eeAUlkYOLl+\nbK1i22KAWvyiVsvdDCwYcv6lej4pfy/OpkxZ7mZXtxMR8QxlXbxO12Tm2pbjAGTm3yPiIcq6hOcB\nCymj+b6fmXu79aua7+M1YHuPdk0l5JO7nO822hLKmolvrc80Vi9n5mGFRqomcBzP9SVJkloZCEqS\nJE1tb6GsdQdlvbsHR9n/DkoY+DTwZeDhzHyxORkRZ1NGsUVr7+JAj3On0h4I9goYG3dRAsEVlECw\nOTZSARzDwXBNkiRJGAhKkiRNaZm5PyL+TSm2cQYw4kAwImZSRt8BfCIzt7Q0O3WczzfSUYttNlIC\nywspI+X+RhnNOJxmxGIAbwe2dWk3v6O9JElSX3ANQUmSpKmvWcPvolH2O41SQXiwSxgIpcrxEZGZ\nL1HWC2ymzd7dpahKpy2UCs0AS9oa1MIjTaGUP4znOTs0U4B7jaiUJEk6ogwEJUmSpr47635JRCzv\n1TAihhapaKYGT4uId7d/w23MAAAB8ElEQVS0XQB8fgKebzxuBb5Zt65rDg5VC4b8vH68MiKmtzRb\nTVlzcT8HK/pOhGatx/GMjJQkSXpdGQhKkiRNfT8CflF/3hARV0fEKc3JiJgdEcsjYhNwfXM8M3cC\nf6of10fEmbX9URFxPqVC7/435A26yMwnMvPKuj07iq7XUUYJvgu4LyIWAkTEsRGxGriptrs9M3dM\n4CNvrfulEXH6BF5XkiRpwhgISpIkTXF1Gu0llFBwOnAjsDMiXoiI3cC/gHuB81u6r6IEZ4uBLRGx\nh1JleBOlGvGRHiE4Jpn5JHA5MAhcAPw1Il6gjOC7jTJV+qfAmgm+9SZKZeN5wHMRsSMinqvb8RN8\nL0mSpDExEJQkSXoTyMzdlODrIuAnlFBqBiX42gasB5YBV3X02wx8iDLF9kXKen3bgW8Di4Bn3pAX\neB1k5g+As4F1lIIkA5SwczOlcvGyOr14Iu/5MnAOcA+wA5gNvKNu/u0tSZImhRjZusySJEmSJEmS\n3gz8L6UkSZIkSZLURwwEJUmSJEmSpD5iIChJkiRJkiT1EQNBSZIkSZIkqY8YCEqSJEmSJEl9xEBQ\nkiRJkiRJ6iMGgpIkSZIkSVIfMRCUJEmSJEmS+oiBoCRJkiRJktRHDAQlSZIkSZKkPmIgKEmSJEmS\nJPWR/wHob/56nhPcXAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b9479e128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=df_cities_T.plot(kind='line', x='MonthYr', figsize=(20,12), grid=True, style='o-')\n",
    "ax.yaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"Year-Month\", labelpad=20)\n",
    "plt.ylabel(\"Median Sale Price (in $)\", labelpad=20)\n",
    "plt.title(\"Median Price growth in Top 10 Metros by Size (2008 - 2018)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "##Analysis 3 : Among the Top metros by size, San Jose saw the highest percentage increase in median sale price(150%)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Median Sale Price increase for Cities in Bay area (San Jose, San Francisco & Santa Clara)<a class=\"anchor\" id=\"plot4\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 753,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>StateName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12447.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>2</td>\n",
       "      <td>508700.0</td>\n",
       "      <td>480000.0</td>\n",
       "      <td>459500.0</td>\n",
       "      <td>449200.0</td>\n",
       "      <td>432600.0</td>\n",
       "      <td>419400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>663500.0</td>\n",
       "      <td>672200.0</td>\n",
       "      <td>687000.0</td>\n",
       "      <td>696900.0</td>\n",
       "      <td>704600.0</td>\n",
       "      <td>695900.0</td>\n",
       "      <td>685900.0</td>\n",
       "      <td>688000.0</td>\n",
       "      <td>684800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17426.0</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>3</td>\n",
       "      <td>324300.0</td>\n",
       "      <td>313100.0</td>\n",
       "      <td>291700.0</td>\n",
       "      <td>282100.0</td>\n",
       "      <td>277400.0</td>\n",
       "      <td>273700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>267900.0</td>\n",
       "      <td>271400.0</td>\n",
       "      <td>275000.0</td>\n",
       "      <td>280700.0</td>\n",
       "      <td>286400.0</td>\n",
       "      <td>299400.0</td>\n",
       "      <td>298500.0</td>\n",
       "      <td>293100.0</td>\n",
       "      <td>277800.0</td>\n",
       "      <td>272500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40326.0</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>5</td>\n",
       "      <td>220900.0</td>\n",
       "      <td>213000.0</td>\n",
       "      <td>206600.0</td>\n",
       "      <td>198300.0</td>\n",
       "      <td>187700.0</td>\n",
       "      <td>177100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>223100.0</td>\n",
       "      <td>226000.0</td>\n",
       "      <td>230100.0</td>\n",
       "      <td>236800.0</td>\n",
       "      <td>239400.0</td>\n",
       "      <td>238200.0</td>\n",
       "      <td>235800.0</td>\n",
       "      <td>233700.0</td>\n",
       "      <td>237000.0</td>\n",
       "      <td>237900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>54296.0</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>8</td>\n",
       "      <td>419800.0</td>\n",
       "      <td>408200.0</td>\n",
       "      <td>398800.0</td>\n",
       "      <td>380600.0</td>\n",
       "      <td>371300.0</td>\n",
       "      <td>356600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>553600.0</td>\n",
       "      <td>566300.0</td>\n",
       "      <td>574300.0</td>\n",
       "      <td>577800.0</td>\n",
       "      <td>572000.0</td>\n",
       "      <td>573200.0</td>\n",
       "      <td>577600.0</td>\n",
       "      <td>583200.0</td>\n",
       "      <td>584200.0</td>\n",
       "      <td>585000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>33839.0</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>California</td>\n",
       "      <td>10</td>\n",
       "      <td>615200.0</td>\n",
       "      <td>578200.0</td>\n",
       "      <td>560700.0</td>\n",
       "      <td>543300.0</td>\n",
       "      <td>529300.0</td>\n",
       "      <td>517700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>885300.0</td>\n",
       "      <td>922800.0</td>\n",
       "      <td>970900.0</td>\n",
       "      <td>1002300.0</td>\n",
       "      <td>1044300.0</td>\n",
       "      <td>1060800.0</td>\n",
       "      <td>1071700.0</td>\n",
       "      <td>1065200.0</td>\n",
       "      <td>1054600.0</td>\n",
       "      <td>1030600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 129 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID   RegionName   StateName  SizeRank   2008-03   2008-04   2008-05  \\\n",
       "1   12447.0  Los Angeles  California         2  508700.0  480000.0  459500.0   \n",
       "2   17426.0      Chicago    Illinois         3  324300.0  313100.0  291700.0   \n",
       "4   40326.0      Phoenix     Arizona         5  220900.0  213000.0  206600.0   \n",
       "7   54296.0    San Diego  California         8  419800.0  408200.0  398800.0   \n",
       "9   33839.0     San Jose  California        10  615200.0  578200.0  560700.0   \n",
       "\n",
       "    2008-06   2008-07   2008-08    ...       2017-10   2017-11   2017-12  \\\n",
       "1  449200.0  432600.0  419400.0    ...      647500.0  663500.0  672200.0   \n",
       "2  282100.0  277400.0  273700.0    ...      267900.0  271400.0  275000.0   \n",
       "4  198300.0  187700.0  177100.0    ...      223100.0  226000.0  230100.0   \n",
       "7  380600.0  371300.0  356600.0    ...      553600.0  566300.0  574300.0   \n",
       "9  543300.0  529300.0  517700.0    ...      885300.0  922800.0  970900.0   \n",
       "\n",
       "     2018-01    2018-02    2018-03    2018-04    2018-05    2018-06    2018-07  \n",
       "1   687000.0   696900.0   704600.0   695900.0   685900.0   688000.0   684800.0  \n",
       "2   280700.0   286400.0   299400.0   298500.0   293100.0   277800.0   272500.0  \n",
       "4   236800.0   239400.0   238200.0   235800.0   233700.0   237000.0   237900.0  \n",
       "7   577800.0   572000.0   573200.0   577600.0   583200.0   584200.0   585000.0  \n",
       "9  1002300.0  1044300.0  1060800.0  1071700.0  1065200.0  1054600.0  1030600.0  \n",
       "\n",
       "[5 rows x 129 columns]"
      ]
     },
     "execution_count": 753,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SalePrice_City.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 812,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_SalePrice_City1 = pd.read_csv(\"Median Price\\Sale_Prices_City.CSV\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 813,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>StateName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>33839.0</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>California</td>\n",
       "      <td>10</td>\n",
       "      <td>615200.0</td>\n",
       "      <td>578200.0</td>\n",
       "      <td>560700.0</td>\n",
       "      <td>543300.0</td>\n",
       "      <td>529300.0</td>\n",
       "      <td>517700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>885300.0</td>\n",
       "      <td>922800.0</td>\n",
       "      <td>970900.0</td>\n",
       "      <td>1002300.0</td>\n",
       "      <td>1044300.0</td>\n",
       "      <td>1060800.0</td>\n",
       "      <td>1071700.0</td>\n",
       "      <td>1065200.0</td>\n",
       "      <td>1054600.0</td>\n",
       "      <td>1030600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20330.0</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>12</td>\n",
       "      <td>792500.0</td>\n",
       "      <td>784400.0</td>\n",
       "      <td>782400.0</td>\n",
       "      <td>779000.0</td>\n",
       "      <td>787300.0</td>\n",
       "      <td>793600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1282800.0</td>\n",
       "      <td>1290600.0</td>\n",
       "      <td>1287900.0</td>\n",
       "      <td>1291100.0</td>\n",
       "      <td>1288100.0</td>\n",
       "      <td>1307000.0</td>\n",
       "      <td>1318200.0</td>\n",
       "      <td>1327100.0</td>\n",
       "      <td>1316400.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>13713.0</td>\n",
       "      <td>Santa Clara</td>\n",
       "      <td>California</td>\n",
       "      <td>171</td>\n",
       "      <td>586300.0</td>\n",
       "      <td>581300.0</td>\n",
       "      <td>575200.0</td>\n",
       "      <td>600700.0</td>\n",
       "      <td>611200.0</td>\n",
       "      <td>620700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1166700.0</td>\n",
       "      <td>1211000.0</td>\n",
       "      <td>1255200.0</td>\n",
       "      <td>1300200.0</td>\n",
       "      <td>1352900.0</td>\n",
       "      <td>1355300.0</td>\n",
       "      <td>1382300.0</td>\n",
       "      <td>1324100.0</td>\n",
       "      <td>1304400.0</td>\n",
       "      <td>1307000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 129 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     RegionID     RegionName   StateName  SizeRank   2008-03   2008-04  \\\n",
       "9     33839.0       San Jose  California        10  615200.0  578200.0   \n",
       "11    20330.0  San Francisco  California        12  792500.0  784400.0   \n",
       "170   13713.0    Santa Clara  California       171  586300.0  581300.0   \n",
       "\n",
       "      2008-05   2008-06   2008-07   2008-08    ...        2017-10    2017-11  \\\n",
       "9    560700.0  543300.0  529300.0  517700.0    ...       885300.0   922800.0   \n",
       "11   782400.0  779000.0  787300.0  793600.0    ...      1282800.0  1290600.0   \n",
       "170  575200.0  600700.0  611200.0  620700.0    ...      1166700.0  1211000.0   \n",
       "\n",
       "       2017-12    2018-01    2018-02    2018-03    2018-04    2018-05  \\\n",
       "9     970900.0  1002300.0  1044300.0  1060800.0  1071700.0  1065200.0   \n",
       "11   1287900.0  1291100.0  1288100.0  1307000.0  1318200.0  1327100.0   \n",
       "170  1255200.0  1300200.0  1352900.0  1355300.0  1382300.0  1324100.0   \n",
       "\n",
       "       2018-06    2018-07  \n",
       "9    1054600.0  1030600.0  \n",
       "11   1316400.0        NaN  \n",
       "170  1304400.0  1307000.0  \n",
       "\n",
       "[3 rows x 129 columns]"
      ]
     },
     "execution_count": 813,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_BayArea = df_SalePrice_City1[(df_SalePrice_City['RegionName']=='Santa Clara') | (df_SalePrice_City1['RegionName']=='San Jose') | (df_SalePrice_City1['RegionName']=='San Francisco')]\n",
    "df_BayArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 814,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-12</th>\n",
       "      <th>2009-06</th>\n",
       "      <th>2009-12</th>\n",
       "      <th>2010-06</th>\n",
       "      <th>2010-12</th>\n",
       "      <th>2011-06</th>\n",
       "      <th>2011-12</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>...</th>\n",
       "      <th>2013-12</th>\n",
       "      <th>2014-06</th>\n",
       "      <th>2014-12</th>\n",
       "      <th>2015-06</th>\n",
       "      <th>2015-12</th>\n",
       "      <th>2016-06</th>\n",
       "      <th>2016-12</th>\n",
       "      <th>2017-06</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-06</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>San Jose</td>\n",
       "      <td>543300.0</td>\n",
       "      <td>428300.0</td>\n",
       "      <td>366700.0</td>\n",
       "      <td>448600.0</td>\n",
       "      <td>446400.0</td>\n",
       "      <td>448600.0</td>\n",
       "      <td>422500.0</td>\n",
       "      <td>422600.0</td>\n",
       "      <td>450200.0</td>\n",
       "      <td>...</td>\n",
       "      <td>616700.0</td>\n",
       "      <td>640200.0</td>\n",
       "      <td>669100.0</td>\n",
       "      <td>705300.0</td>\n",
       "      <td>738400.0</td>\n",
       "      <td>760300.0</td>\n",
       "      <td>785600.0</td>\n",
       "      <td>817400.0</td>\n",
       "      <td>970900.0</td>\n",
       "      <td>1054600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>779000.0</td>\n",
       "      <td>704300.0</td>\n",
       "      <td>666400.0</td>\n",
       "      <td>713700.0</td>\n",
       "      <td>670000.0</td>\n",
       "      <td>686300.0</td>\n",
       "      <td>660700.0</td>\n",
       "      <td>654700.0</td>\n",
       "      <td>695700.0</td>\n",
       "      <td>...</td>\n",
       "      <td>869400.0</td>\n",
       "      <td>929000.0</td>\n",
       "      <td>1026100.0</td>\n",
       "      <td>1135600.0</td>\n",
       "      <td>1150800.0</td>\n",
       "      <td>1157100.0</td>\n",
       "      <td>1206500.0</td>\n",
       "      <td>1203100.0</td>\n",
       "      <td>1287900.0</td>\n",
       "      <td>1316400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>Santa Clara</td>\n",
       "      <td>600700.0</td>\n",
       "      <td>539800.0</td>\n",
       "      <td>495800.0</td>\n",
       "      <td>579900.0</td>\n",
       "      <td>519200.0</td>\n",
       "      <td>549700.0</td>\n",
       "      <td>508300.0</td>\n",
       "      <td>536100.0</td>\n",
       "      <td>564600.0</td>\n",
       "      <td>...</td>\n",
       "      <td>700500.0</td>\n",
       "      <td>696900.0</td>\n",
       "      <td>753500.0</td>\n",
       "      <td>845700.0</td>\n",
       "      <td>904800.0</td>\n",
       "      <td>926500.0</td>\n",
       "      <td>968800.0</td>\n",
       "      <td>1042900.0</td>\n",
       "      <td>1255200.0</td>\n",
       "      <td>1304400.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        RegionName   2008-06   2008-12   2009-06   2009-12   2010-06  \\\n",
       "9         San Jose  543300.0  428300.0  366700.0  448600.0  446400.0   \n",
       "11   San Francisco  779000.0  704300.0  666400.0  713700.0  670000.0   \n",
       "170    Santa Clara  600700.0  539800.0  495800.0  579900.0  519200.0   \n",
       "\n",
       "      2010-12   2011-06   2011-12   2012-06    ...       2013-12   2014-06  \\\n",
       "9    448600.0  422500.0  422600.0  450200.0    ...      616700.0  640200.0   \n",
       "11   686300.0  660700.0  654700.0  695700.0    ...      869400.0  929000.0   \n",
       "170  549700.0  508300.0  536100.0  564600.0    ...      700500.0  696900.0   \n",
       "\n",
       "       2014-12    2015-06    2015-12    2016-06    2016-12    2017-06  \\\n",
       "9     669100.0   705300.0   738400.0   760300.0   785600.0   817400.0   \n",
       "11   1026100.0  1135600.0  1150800.0  1157100.0  1206500.0  1203100.0   \n",
       "170   753500.0   845700.0   904800.0   926500.0   968800.0  1042900.0   \n",
       "\n",
       "       2017-12    2018-06  \n",
       "9     970900.0  1054600.0  \n",
       "11   1287900.0  1316400.0  \n",
       "170  1255200.0  1304400.0  \n",
       "\n",
       "[3 rows x 22 columns]"
      ]
     },
     "execution_count": 814,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Subset columns\n",
    "df_BayArea = df_BayArea.iloc[0:,1::6]\n",
    "df_BayArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 815,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>RegionName</th>\n",
       "      <th>San Jose</th>\n",
       "      <th>San Francisco</th>\n",
       "      <th>Santa Clara</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-06</th>\n",
       "      <td>543300.0</td>\n",
       "      <td>779000.0</td>\n",
       "      <td>600700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12</th>\n",
       "      <td>428300.0</td>\n",
       "      <td>704300.0</td>\n",
       "      <td>539800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-06</th>\n",
       "      <td>366700.0</td>\n",
       "      <td>666400.0</td>\n",
       "      <td>495800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12</th>\n",
       "      <td>448600.0</td>\n",
       "      <td>713700.0</td>\n",
       "      <td>579900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-06</th>\n",
       "      <td>446400.0</td>\n",
       "      <td>670000.0</td>\n",
       "      <td>519200.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "RegionName  San Jose  San Francisco  Santa Clara\n",
       "2008-06     543300.0       779000.0     600700.0\n",
       "2008-12     428300.0       704300.0     539800.0\n",
       "2009-06     366700.0       666400.0     495800.0\n",
       "2009-12     448600.0       713700.0     579900.0\n",
       "2010-06     446400.0       670000.0     519200.0"
      ]
     },
     "execution_count": 815,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_BayArea_T = df_BayArea.set_index('RegionName').T\n",
    "df_BayArea_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 816,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##Reset index\n",
    "df_BayArea_T.reset_index(level=0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 817,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Name columns\n",
    "df_BayArea_T.columns = ['YearMonth','San Jose', 'San Francisco', 'Santa Clara']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 818,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_BayArea_T['Year']= (df_BayArea_T['YearMonth'].str.split('-').str[0])\n",
    "df_BayArea_T['Month']= (df_BayArea_T['YearMonth'].str.split('-').str[1])\n",
    "\n",
    "df_BayArea_T['MonthName']=df_BayArea_T['Month'].apply(lambda x: 'Jun' if x == '06' else 'Dec')\n",
    "df_BayArea_T['Yr']=df_BayArea_T['Year'].apply(lambda x: '\\''+x[-2:])\n",
    "df_BayArea_T['MonthYr']=df_BayArea_T['MonthName'] +' '+ df_BayArea_T['Yr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 819,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>San Jose</th>\n",
       "      <th>San Francisco</th>\n",
       "      <th>Santa Clara</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>MonthName</th>\n",
       "      <th>Yr</th>\n",
       "      <th>MonthYr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-06</td>\n",
       "      <td>543300.0</td>\n",
       "      <td>779000.0</td>\n",
       "      <td>600700.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'08</td>\n",
       "      <td>Jun '08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008-12</td>\n",
       "      <td>428300.0</td>\n",
       "      <td>704300.0</td>\n",
       "      <td>539800.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>12</td>\n",
       "      <td>Dec</td>\n",
       "      <td>'08</td>\n",
       "      <td>Dec '08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-06</td>\n",
       "      <td>366700.0</td>\n",
       "      <td>666400.0</td>\n",
       "      <td>495800.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'09</td>\n",
       "      <td>Jun '09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-12</td>\n",
       "      <td>448600.0</td>\n",
       "      <td>713700.0</td>\n",
       "      <td>579900.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>12</td>\n",
       "      <td>Dec</td>\n",
       "      <td>'09</td>\n",
       "      <td>Dec '09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-06</td>\n",
       "      <td>446400.0</td>\n",
       "      <td>670000.0</td>\n",
       "      <td>519200.0</td>\n",
       "      <td>2010</td>\n",
       "      <td>06</td>\n",
       "      <td>Jun</td>\n",
       "      <td>'10</td>\n",
       "      <td>Jun '10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  San Jose  San Francisco  Santa Clara  Year Month MonthName   Yr  \\\n",
       "0   2008-06  543300.0       779000.0     600700.0  2008    06       Jun  '08   \n",
       "1   2008-12  428300.0       704300.0     539800.0  2008    12       Dec  '08   \n",
       "2   2009-06  366700.0       666400.0     495800.0  2009    06       Jun  '09   \n",
       "3   2009-12  448600.0       713700.0     579900.0  2009    12       Dec  '09   \n",
       "4   2010-06  446400.0       670000.0     519200.0  2010    06       Jun  '10   \n",
       "\n",
       "   MonthYr  \n",
       "0  Jun '08  \n",
       "1  Dec '08  \n",
       "2  Jun '09  \n",
       "3  Dec '09  \n",
       "4  Jun '10  "
      ]
     },
     "execution_count": 819,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_BayArea_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 820,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABQQAAAMDCAYAAAD0SxgZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b947b9fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "ax=df_BayArea_T.plot(kind='line', x='MonthYr', figsize=(20,12), grid=True, style='o-')\n",
    "ax.yaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"Year-Month\", labelpad=20)\n",
    "plt.ylabel(\"Median Sale Price (in $)\", labelpad=20)\n",
    "plt.title(\"Median Price growth in Top Metros of Bay Area - Sept 2011 to Jun 2018\")    \n",
    "plt.show()    "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Analysis : Bay area cities a much higher percentage increase in their Median Sale price as compared to Nation increase \n",
    "           San Jose - 150%\n",
    "           Santa Clara - 156%\n",
    "           San Francisco - 101%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Home Sale Counts by state - US Map <a class=\"anchor\" id=\"plot5\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 748,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionID</th>\n",
       "      <th>RegionName</th>\n",
       "      <th>SizeRank</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>2008-09</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9</td>\n",
       "      <td>California</td>\n",
       "      <td>1</td>\n",
       "      <td>23518.0</td>\n",
       "      <td>28536.0</td>\n",
       "      <td>31373.0</td>\n",
       "      <td>33071.0</td>\n",
       "      <td>36669.0</td>\n",
       "      <td>35316.0</td>\n",
       "      <td>36477.0</td>\n",
       "      <td>...</td>\n",
       "      <td>41189</td>\n",
       "      <td>37759</td>\n",
       "      <td>36593</td>\n",
       "      <td>29333</td>\n",
       "      <td>29312</td>\n",
       "      <td>39767</td>\n",
       "      <td>40783</td>\n",
       "      <td>44718</td>\n",
       "      <td>44630.0</td>\n",
       "      <td>43208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>54</td>\n",
       "      <td>Texas</td>\n",
       "      <td>2</td>\n",
       "      <td>23774.0</td>\n",
       "      <td>25876.0</td>\n",
       "      <td>26542.0</td>\n",
       "      <td>27791.0</td>\n",
       "      <td>28239.0</td>\n",
       "      <td>25213.0</td>\n",
       "      <td>21392.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32804</td>\n",
       "      <td>28839</td>\n",
       "      <td>29941</td>\n",
       "      <td>24783</td>\n",
       "      <td>25329</td>\n",
       "      <td>31152</td>\n",
       "      <td>32593</td>\n",
       "      <td>38935</td>\n",
       "      <td>39184.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>New York</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>19289</td>\n",
       "      <td>17409</td>\n",
       "      <td>17860</td>\n",
       "      <td>16239</td>\n",
       "      <td>13335</td>\n",
       "      <td>14014</td>\n",
       "      <td>14461</td>\n",
       "      <td>17680</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>Florida</td>\n",
       "      <td>4</td>\n",
       "      <td>17429.0</td>\n",
       "      <td>19501.0</td>\n",
       "      <td>19766.0</td>\n",
       "      <td>20462.0</td>\n",
       "      <td>20923.0</td>\n",
       "      <td>17640.0</td>\n",
       "      <td>17759.0</td>\n",
       "      <td>...</td>\n",
       "      <td>38908</td>\n",
       "      <td>36071</td>\n",
       "      <td>40928</td>\n",
       "      <td>36048</td>\n",
       "      <td>34492</td>\n",
       "      <td>45172</td>\n",
       "      <td>46433</td>\n",
       "      <td>49560</td>\n",
       "      <td>48507.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>5</td>\n",
       "      <td>11823.0</td>\n",
       "      <td>13158.0</td>\n",
       "      <td>13967.0</td>\n",
       "      <td>15312.0</td>\n",
       "      <td>16499.0</td>\n",
       "      <td>15070.0</td>\n",
       "      <td>14189.0</td>\n",
       "      <td>...</td>\n",
       "      <td>19981</td>\n",
       "      <td>18048</td>\n",
       "      <td>17525</td>\n",
       "      <td>14702</td>\n",
       "      <td>12155</td>\n",
       "      <td>17074</td>\n",
       "      <td>19639</td>\n",
       "      <td>23725</td>\n",
       "      <td>27333.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 128 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionID  RegionName  SizeRank  2008-03  2008-04  2008-05  2008-06  \\\n",
       "0         9  California         1  23518.0  28536.0  31373.0  33071.0   \n",
       "1        54       Texas         2  23774.0  25876.0  26542.0  27791.0   \n",
       "2        43    New York         3      NaN      NaN      NaN      NaN   \n",
       "3        14     Florida         4  17429.0  19501.0  19766.0  20462.0   \n",
       "4        21    Illinois         5  11823.0  13158.0  13967.0  15312.0   \n",
       "\n",
       "   2008-07  2008-08  2008-09   ...     2017-10  2017-11  2017-12  2018-01  \\\n",
       "0  36669.0  35316.0  36477.0   ...       41189    37759    36593    29333   \n",
       "1  28239.0  25213.0  21392.0   ...       32804    28839    29941    24783   \n",
       "2      NaN      NaN      NaN   ...       19289    17409    17860    16239   \n",
       "3  20923.0  17640.0  17759.0   ...       38908    36071    40928    36048   \n",
       "4  16499.0  15070.0  14189.0   ...       19981    18048    17525    14702   \n",
       "\n",
       "   2018-02  2018-03  2018-04  2018-05  2018-06  2018-07  \n",
       "0    29312    39767    40783    44718  44630.0  43208.0  \n",
       "1    25329    31152    32593    38935  39184.0      NaN  \n",
       "2    13335    14014    14461    17680      NaN      NaN  \n",
       "3    34492    45172    46433    49560  48507.0      NaN  \n",
       "4    12155    17074    19639    23725  27333.0      NaN  \n",
       "\n",
       "[5 rows x 128 columns]"
      ]
     },
     "execution_count": 748,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_Counts_State = pd.read_csv(\"Home Sale Counts\\Sale_Counts_State.CSV\")\n",
    "df_Counts_State.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 749,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>2008-03</th>\n",
       "      <th>2008-04</th>\n",
       "      <th>2008-05</th>\n",
       "      <th>2008-06</th>\n",
       "      <th>2008-07</th>\n",
       "      <th>2008-08</th>\n",
       "      <th>2008-09</th>\n",
       "      <th>2008-10</th>\n",
       "      <th>2008-11</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "      <th>Avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>California</td>\n",
       "      <td>23518.0</td>\n",
       "      <td>28536.0</td>\n",
       "      <td>31373.0</td>\n",
       "      <td>33071.0</td>\n",
       "      <td>36669.0</td>\n",
       "      <td>35316.0</td>\n",
       "      <td>36477.0</td>\n",
       "      <td>38863.0</td>\n",
       "      <td>29342.0</td>\n",
       "      <td>...</td>\n",
       "      <td>37759</td>\n",
       "      <td>36593</td>\n",
       "      <td>29333</td>\n",
       "      <td>29312</td>\n",
       "      <td>39767</td>\n",
       "      <td>40783</td>\n",
       "      <td>44718</td>\n",
       "      <td>44630.0</td>\n",
       "      <td>43208.0</td>\n",
       "      <td>36122.296000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>23774.0</td>\n",
       "      <td>25876.0</td>\n",
       "      <td>26542.0</td>\n",
       "      <td>27791.0</td>\n",
       "      <td>28239.0</td>\n",
       "      <td>25213.0</td>\n",
       "      <td>21392.0</td>\n",
       "      <td>21819.0</td>\n",
       "      <td>15415.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28839</td>\n",
       "      <td>29941</td>\n",
       "      <td>24783</td>\n",
       "      <td>25329</td>\n",
       "      <td>31152</td>\n",
       "      <td>32593</td>\n",
       "      <td>38935</td>\n",
       "      <td>39184.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25739.443548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New York</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>17409</td>\n",
       "      <td>17860</td>\n",
       "      <td>16239</td>\n",
       "      <td>13335</td>\n",
       "      <td>14014</td>\n",
       "      <td>14461</td>\n",
       "      <td>17680</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13604.477778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Florida</td>\n",
       "      <td>17429.0</td>\n",
       "      <td>19501.0</td>\n",
       "      <td>19766.0</td>\n",
       "      <td>20462.0</td>\n",
       "      <td>20923.0</td>\n",
       "      <td>17640.0</td>\n",
       "      <td>17759.0</td>\n",
       "      <td>18072.0</td>\n",
       "      <td>13673.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36071</td>\n",
       "      <td>40928</td>\n",
       "      <td>36048</td>\n",
       "      <td>34492</td>\n",
       "      <td>45172</td>\n",
       "      <td>46433</td>\n",
       "      <td>49560</td>\n",
       "      <td>48507.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31568.653226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Illinois</td>\n",
       "      <td>11823.0</td>\n",
       "      <td>13158.0</td>\n",
       "      <td>13967.0</td>\n",
       "      <td>15312.0</td>\n",
       "      <td>16499.0</td>\n",
       "      <td>15070.0</td>\n",
       "      <td>14189.0</td>\n",
       "      <td>13581.0</td>\n",
       "      <td>9376.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18048</td>\n",
       "      <td>17525</td>\n",
       "      <td>14702</td>\n",
       "      <td>12155</td>\n",
       "      <td>17074</td>\n",
       "      <td>19639</td>\n",
       "      <td>23725</td>\n",
       "      <td>27333.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15204.161290</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 127 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionName  2008-03  2008-04  2008-05  2008-06  2008-07  2008-08  2008-09  \\\n",
       "0  California  23518.0  28536.0  31373.0  33071.0  36669.0  35316.0  36477.0   \n",
       "1       Texas  23774.0  25876.0  26542.0  27791.0  28239.0  25213.0  21392.0   \n",
       "2    New York      NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "3     Florida  17429.0  19501.0  19766.0  20462.0  20923.0  17640.0  17759.0   \n",
       "4    Illinois  11823.0  13158.0  13967.0  15312.0  16499.0  15070.0  14189.0   \n",
       "\n",
       "   2008-10  2008-11      ...       2017-11  2017-12  2018-01  2018-02  \\\n",
       "0  38863.0  29342.0      ...         37759    36593    29333    29312   \n",
       "1  21819.0  15415.0      ...         28839    29941    24783    25329   \n",
       "2      NaN      NaN      ...         17409    17860    16239    13335   \n",
       "3  18072.0  13673.0      ...         36071    40928    36048    34492   \n",
       "4  13581.0   9376.0      ...         18048    17525    14702    12155   \n",
       "\n",
       "   2018-03  2018-04  2018-05  2018-06  2018-07           Avg  \n",
       "0    39767    40783    44718  44630.0  43208.0  36122.296000  \n",
       "1    31152    32593    38935  39184.0      NaN  25739.443548  \n",
       "2    14014    14461    17680      NaN      NaN  13604.477778  \n",
       "3    45172    46433    49560  48507.0      NaN  31568.653226  \n",
       "4    17074    19639    23725  27333.0      NaN  15204.161290  \n",
       "\n",
       "[5 rows x 127 columns]"
      ]
     },
     "execution_count": 749,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_Counts_State = df_Counts_State.drop(['RegionID','SizeRank'], axis=1)\n",
    "df_Counts_State['Avg'] = df_Counts_State.mean(axis=1)\n",
    "df_Counts_State.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 765,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_state_MeanCount = df_Counts_State.ix[:, ['RegionName','Avg']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 766,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>Avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>California</td>\n",
       "      <td>36122.296000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Texas</td>\n",
       "      <td>25739.443548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New York</td>\n",
       "      <td>13604.477778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Florida</td>\n",
       "      <td>31568.653226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Illinois</td>\n",
       "      <td>15204.161290</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RegionName           Avg\n",
       "0  California  36122.296000\n",
       "1       Texas  25739.443548\n",
       "2    New York  13604.477778\n",
       "3     Florida  31568.653226\n",
       "4    Illinois  15204.161290"
      ]
     },
     "execution_count": 766,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_state_MeanCount.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 823,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.plotly as py\n",
    "import plotly as ply\n",
    "import pandas as pd\n",
    "\n",
    "#for col in df_persqft_state.columns:\n",
    " #   df_persqft_state['Increase'] = df_persqft_state['Diff'].astype(str)\n",
    "\n",
    "scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\\\n",
    "            [0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]\n",
    "\n",
    "\n",
    "df_state_MeanCount['text'] = df_state_MeanCount['RegionName'] + '<br>' +\\\n",
    "    'Avg Count: '+df_state_MeanCount['Avg'].astype(str)\n",
    "    \n",
    "data = [ dict(\n",
    "        type='choropleth',\n",
    "        colorscale = scl,\n",
    "        autocolorscale = False,\n",
    "        locations = df_state_MeanCount['RegionName'],\n",
    "        z = df_state_MeanCount['Avg'].astype(float),\n",
    "        locationmode = 'USA-states',\n",
    "        text = df_state_MeanCount['text'],\n",
    "        marker = dict(\n",
    "            line = dict (\n",
    "                color = 'rgb(255,255,255)',\n",
    "                width = 2\n",
    "            ) ),\n",
    "        colorbar = dict(\n",
    "            title = \"Avg Count\")\n",
    "        ) ]\n",
    "\n",
    "\n",
    "layout = dict(\n",
    "        title = 'Avg Count of Houses Sold Monthly (2010 - 2018)',\n",
    "        geo = dict(\n",
    "            scope='usa',\n",
    "            projection=dict( type='albers usa' ),\n",
    "            showlakes = True,\n",
    "            lakecolor = 'rgb(255, 255, 255)'),\n",
    "             )\n",
    "#ply.tools.set_credentials_file(username='singuava', api_key='k4gITYpzzdFXRtcEcahg')\n",
    " \n",
    "#Click anywhere on the image below to be taken to plotly page with this plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <a href=\"https://plot.ly/~singuava/8/?share_key=t42budrsWYDdGzeUXaF7fS\" target=\"_blank\" title=\"Avg HousesSold - 2\" style=\"display: block; text-align: center;\"><img src=\"https://plot.ly/~singuava/8.png?share_key=t42budrsWYDdGzeUXaF7fS\" alt=\"Avg HousesSold - 2\" style=\"max-width: 100%;width: 600px;\"  width=\"600\" onerror=\"this.onerror=null;this.src='https://plot.ly/404.png';\" /></a>\n",
    "    <script data-plotly=\"singuava:8\" sharekey-plotly=\"t42budrsWYDdGzeUXaF7fS\" src=\"https://plot.ly/embed.js\" async></script>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Analysis  : California, Texas, Florida are 3 popular states in terms of Avg. houses sold per month. They all range from 25000 to 36000 avg. number of houses sold per month."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Days On Market  - Seasonality Trend over the years  <a class=\"anchor\" id=\"plot6\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 768,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>RegionType</th>\n",
       "      <th>StateFullName</th>\n",
       "      <th>DataTypeDescription</th>\n",
       "      <th>2012-01</th>\n",
       "      <th>2012-02</th>\n",
       "      <th>2012-03</th>\n",
       "      <th>2012-04</th>\n",
       "      <th>2012-05</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>Country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All Homes</td>\n",
       "      <td>119</td>\n",
       "      <td>114</td>\n",
       "      <td>102</td>\n",
       "      <td>84</td>\n",
       "      <td>78</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>85</td>\n",
       "      <td>92</td>\n",
       "      <td>98</td>\n",
       "      <td>91</td>\n",
       "      <td>67</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "      <td>58</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New York, NY</td>\n",
       "      <td>Msa</td>\n",
       "      <td>New York</td>\n",
       "      <td>All Homes</td>\n",
       "      <td>136</td>\n",
       "      <td>126</td>\n",
       "      <td>112</td>\n",
       "      <td>86</td>\n",
       "      <td>81</td>\n",
       "      <td>86</td>\n",
       "      <td>...</td>\n",
       "      <td>82</td>\n",
       "      <td>84</td>\n",
       "      <td>92</td>\n",
       "      <td>99</td>\n",
       "      <td>78</td>\n",
       "      <td>51</td>\n",
       "      <td>55</td>\n",
       "      <td>53</td>\n",
       "      <td>58</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chicago, IL</td>\n",
       "      <td>Msa</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>All Homes</td>\n",
       "      <td>140</td>\n",
       "      <td>135</td>\n",
       "      <td>122</td>\n",
       "      <td>98</td>\n",
       "      <td>88</td>\n",
       "      <td>88</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>86</td>\n",
       "      <td>98</td>\n",
       "      <td>105</td>\n",
       "      <td>88</td>\n",
       "      <td>50</td>\n",
       "      <td>46</td>\n",
       "      <td>50</td>\n",
       "      <td>54</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      RegionName RegionType StateFullName DataTypeDescription  2012-01  \\\n",
       "0  United States    Country           NaN           All Homes      119   \n",
       "1   New York, NY        Msa      New York           All Homes      136   \n",
       "2    Chicago, IL        Msa      Illinois           All Homes      140   \n",
       "\n",
       "   2012-02  2012-03  2012-04  2012-05  2012-06   ...     2017-10  2017-11  \\\n",
       "0      114      102       84       78       80   ...          81       85   \n",
       "1      126      112       86       81       86   ...          82       84   \n",
       "2      135      122       98       88       88   ...          78       86   \n",
       "\n",
       "   2017-12  2018-01  2018-02  2018-03  2018-04  2018-05  2018-06  2018-07  \n",
       "0       92       98       91       67       60       57       58       62  \n",
       "1       92       99       78       51       55       53       58       66  \n",
       "2       98      105       88       50       46       50       54       60  \n",
       "\n",
       "[3 rows x 83 columns]"
      ]
     },
     "execution_count": 768,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age = pd.read_csv(\"Inventory\\AgeOfInventory_Metro_Public.CSV\")\n",
    "df_age.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 769,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_age = df_age[(df_age['RegionName']=='San Francisco, CA')  | (df_age['RegionName']=='United States')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 770,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>RegionType</th>\n",
       "      <th>StateFullName</th>\n",
       "      <th>DataTypeDescription</th>\n",
       "      <th>2012-01</th>\n",
       "      <th>2012-02</th>\n",
       "      <th>2012-03</th>\n",
       "      <th>2012-04</th>\n",
       "      <th>2012-05</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>Country</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All Homes</td>\n",
       "      <td>119</td>\n",
       "      <td>114</td>\n",
       "      <td>102</td>\n",
       "      <td>84</td>\n",
       "      <td>78</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>85</td>\n",
       "      <td>92</td>\n",
       "      <td>98</td>\n",
       "      <td>91</td>\n",
       "      <td>67</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "      <td>58</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>San Francisco, CA</td>\n",
       "      <td>Msa</td>\n",
       "      <td>California</td>\n",
       "      <td>All Homes</td>\n",
       "      <td>82</td>\n",
       "      <td>60</td>\n",
       "      <td>42</td>\n",
       "      <td>39</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>46</td>\n",
       "      <td>26</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           RegionName RegionType StateFullName DataTypeDescription  2012-01  \\\n",
       "0       United States    Country           NaN           All Homes      119   \n",
       "10  San Francisco, CA        Msa    California           All Homes       82   \n",
       "\n",
       "    2012-02  2012-03  2012-04  2012-05  2012-06   ...     2017-10  2017-11  \\\n",
       "0       114      102       84       78       80   ...          81       85   \n",
       "10       60       42       39       35       40   ...          25       34   \n",
       "\n",
       "    2017-12  2018-01  2018-02  2018-03  2018-04  2018-05  2018-06  2018-07  \n",
       "0        92       98       91       67       60       57       58       62  \n",
       "10       46       26       15       14       14       15       20       24  \n",
       "\n",
       "[2 rows x 83 columns]"
      ]
     },
     "execution_count": 770,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 771,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RegionName</th>\n",
       "      <th>2012-01</th>\n",
       "      <th>2012-02</th>\n",
       "      <th>2012-03</th>\n",
       "      <th>2012-04</th>\n",
       "      <th>2012-05</th>\n",
       "      <th>2012-06</th>\n",
       "      <th>2012-07</th>\n",
       "      <th>2012-08</th>\n",
       "      <th>2012-09</th>\n",
       "      <th>...</th>\n",
       "      <th>2017-10</th>\n",
       "      <th>2017-11</th>\n",
       "      <th>2017-12</th>\n",
       "      <th>2018-01</th>\n",
       "      <th>2018-02</th>\n",
       "      <th>2018-03</th>\n",
       "      <th>2018-04</th>\n",
       "      <th>2018-05</th>\n",
       "      <th>2018-06</th>\n",
       "      <th>2018-07</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>119</td>\n",
       "      <td>114</td>\n",
       "      <td>102</td>\n",
       "      <td>84</td>\n",
       "      <td>78</td>\n",
       "      <td>80</td>\n",
       "      <td>86</td>\n",
       "      <td>91</td>\n",
       "      <td>94</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>85</td>\n",
       "      <td>92</td>\n",
       "      <td>98</td>\n",
       "      <td>91</td>\n",
       "      <td>67</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "      <td>58</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>San Francisco, CA</td>\n",
       "      <td>82</td>\n",
       "      <td>60</td>\n",
       "      <td>42</td>\n",
       "      <td>39</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "      <td>36</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>46</td>\n",
       "      <td>26</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           RegionName  2012-01  2012-02  2012-03  2012-04  2012-05  2012-06  \\\n",
       "0       United States      119      114      102       84       78       80   \n",
       "10  San Francisco, CA       82       60       42       39       35       40   \n",
       "\n",
       "    2012-07  2012-08  2012-09   ...     2017-10  2017-11  2017-12  2018-01  \\\n",
       "0        86       91       94   ...          81       85       92       98   \n",
       "10       38       40       36   ...          25       34       46       26   \n",
       "\n",
       "    2018-02  2018-03  2018-04  2018-05  2018-06  2018-07  \n",
       "0        91       67       60       57       58       62  \n",
       "10       15       14       14       15       20       24  \n",
       "\n",
       "[2 rows x 80 columns]"
      ]
     },
     "execution_count": 771,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age = df_age.drop(['RegionType','StateFullName','DataTypeDescription'], axis=1)\n",
    "df_age.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 772,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>RegionName</th>\n",
       "      <th>index</th>\n",
       "      <th>United States</th>\n",
       "      <th>San Francisco, CA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01</td>\n",
       "      <td>119</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-02</td>\n",
       "      <td>114</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-03</td>\n",
       "      <td>102</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-04</td>\n",
       "      <td>84</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-05</td>\n",
       "      <td>78</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "RegionName    index  United States  San Francisco, CA\n",
       "0           2012-01            119                 82\n",
       "1           2012-02            114                 60\n",
       "2           2012-03            102                 42\n",
       "3           2012-04             84                 39\n",
       "4           2012-05             78                 35"
      ]
     },
     "execution_count": 772,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age_T = df_age.set_index('RegionName').T\n",
    "df_age_T.reset_index(level=0,inplace=True)\n",
    "df_age_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 773,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##Name columns\n",
    "df_age_T.columns = ['YearMonth','United States', 'San Francisco, CA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 775,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>United States</th>\n",
       "      <th>San Francisco, CA</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01</td>\n",
       "      <td>119</td>\n",
       "      <td>82</td>\n",
       "      <td>2012</td>\n",
       "      <td>01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-02</td>\n",
       "      <td>114</td>\n",
       "      <td>60</td>\n",
       "      <td>2012</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-03</td>\n",
       "      <td>102</td>\n",
       "      <td>42</td>\n",
       "      <td>2012</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-04</td>\n",
       "      <td>84</td>\n",
       "      <td>39</td>\n",
       "      <td>2012</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-05</td>\n",
       "      <td>78</td>\n",
       "      <td>35</td>\n",
       "      <td>2012</td>\n",
       "      <td>05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  United States  San Francisco, CA  Year Month\n",
       "0   2012-01            119                 82  2012    01\n",
       "1   2012-02            114                 60  2012    02\n",
       "2   2012-03            102                 42  2012    03\n",
       "3   2012-04             84                 39  2012    04\n",
       "4   2012-05             78                 35  2012    05"
      ]
     },
     "execution_count": 775,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Make a new column Year from YearMonth\n",
    "df_age_T['Year']= (df_age_T['YearMonth'].str.split('-').str[0])\n",
    "df_age_T['Month']= (df_age_T['YearMonth'].str.split('-').str[1])\n",
    "df_age_T.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 776,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>United States</th>\n",
       "      <th>San Francisco, CA</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01</td>\n",
       "      <td>119</td>\n",
       "      <td>82</td>\n",
       "      <td>2012</td>\n",
       "      <td>01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-02</td>\n",
       "      <td>114</td>\n",
       "      <td>60</td>\n",
       "      <td>2012</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-03</td>\n",
       "      <td>102</td>\n",
       "      <td>42</td>\n",
       "      <td>2012</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-04</td>\n",
       "      <td>84</td>\n",
       "      <td>39</td>\n",
       "      <td>2012</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-05</td>\n",
       "      <td>78</td>\n",
       "      <td>35</td>\n",
       "      <td>2012</td>\n",
       "      <td>05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  United States  San Francisco, CA  Year Month\n",
       "0   2012-01            119                 82  2012    01\n",
       "1   2012-02            114                 60  2012    02\n",
       "2   2012-03            102                 42  2012    03\n",
       "3   2012-04             84                 39  2012    04\n",
       "4   2012-05             78                 35  2012    05"
      ]
     },
     "execution_count": 776,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age_T_2017 = df_age_T[(df_age_T['Year'].astype(int) < 2018)]\n",
    "df_age_T_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 777,
   "metadata": {},
   "outputs": [],
   "source": [
    "Month_to_MonthName = { '01' : 'Jan', \n",
    "                  '02' : 'Feb', \n",
    "                  '03' : 'Mar', \n",
    "                  '04' : 'Apr', \n",
    "                  '05' : 'May',\n",
    "                  '06' : 'Jun', \n",
    "                  '07' : 'Jul', \n",
    "                  '08' : 'Aug', \n",
    "                  '09' : 'Sep', \n",
    "                  '10' : 'Oct',\n",
    "                  '11' : 'Nov', \n",
    "                  '12' : 'Dec'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 778,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "\n",
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "\n",
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_age_T_2017['MonthName'] = df_age_T_2017['Month'].map(Month_to_MonthName)\n",
    "df_age_T_2017['Yr']=df_age_T_2017['Year'].apply(lambda x: '\\''+x[-2:])\n",
    "df_age_T_2017['MonthYr']=df_age_T_2017['MonthName'] +' '+ df_age_T_2017['Yr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 779,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>United States</th>\n",
       "      <th>San Francisco, CA</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>MonthName</th>\n",
       "      <th>Yr</th>\n",
       "      <th>MonthYr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01</td>\n",
       "      <td>119</td>\n",
       "      <td>82</td>\n",
       "      <td>2012</td>\n",
       "      <td>01</td>\n",
       "      <td>Jan</td>\n",
       "      <td>'12</td>\n",
       "      <td>Jan '12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-02</td>\n",
       "      <td>114</td>\n",
       "      <td>60</td>\n",
       "      <td>2012</td>\n",
       "      <td>02</td>\n",
       "      <td>Feb</td>\n",
       "      <td>'12</td>\n",
       "      <td>Feb '12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-03</td>\n",
       "      <td>102</td>\n",
       "      <td>42</td>\n",
       "      <td>2012</td>\n",
       "      <td>03</td>\n",
       "      <td>Mar</td>\n",
       "      <td>'12</td>\n",
       "      <td>Mar '12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-04</td>\n",
       "      <td>84</td>\n",
       "      <td>39</td>\n",
       "      <td>2012</td>\n",
       "      <td>04</td>\n",
       "      <td>Apr</td>\n",
       "      <td>'12</td>\n",
       "      <td>Apr '12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-05</td>\n",
       "      <td>78</td>\n",
       "      <td>35</td>\n",
       "      <td>2012</td>\n",
       "      <td>05</td>\n",
       "      <td>May</td>\n",
       "      <td>'12</td>\n",
       "      <td>May '12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearMonth  United States  San Francisco, CA  Year Month MonthName   Yr  \\\n",
       "0   2012-01            119                 82  2012    01       Jan  '12   \n",
       "1   2012-02            114                 60  2012    02       Feb  '12   \n",
       "2   2012-03            102                 42  2012    03       Mar  '12   \n",
       "3   2012-04             84                 39  2012    04       Apr  '12   \n",
       "4   2012-05             78                 35  2012    05       May  '12   \n",
       "\n",
       "   MonthYr  \n",
       "0  Jan '12  \n",
       "1  Feb '12  \n",
       "2  Mar '12  \n",
       "3  Apr '12  \n",
       "4  May '12  "
      ]
     },
     "execution_count": 779,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age_T_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 780,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABOoAAAMDCAYAAAAc7vobAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b8e1b9e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "ax=df_age_T_2017.plot(kind='line', x='MonthYr', figsize=(20,12), grid=True)\n",
    "ax.yaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"[Mon 'Yr]\", labelpad=20)\n",
    "plt.ylabel(\"Number Of Days On Market\", labelpad=20)\n",
    "plt.title(\"Inventory Trend - Avg. Days On Market Trend(2010 - 2018)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Analysis : A clear pattern seasonality pattern can be observed between SF and USA over the years. Winter months (Nov - Feb) are periods of low house buying and hence the 'Days On Market' a property has been 'Active' in market are in the peak. Where as in summer properties tend to get sold faster. Hence the avg. days on market in these months is low."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 781,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_age_T_2yrs = df_age_T[(df_age_T['Year']=='2017')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 782,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_age_T_2yrs['MonthName'] =[\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 783,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearMonth</th>\n",
       "      <th>United States</th>\n",
       "      <th>San Francisco, CA</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>MonthName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2017-01</td>\n",
       "      <td>104</td>\n",
       "      <td>47</td>\n",
       "      <td>2017</td>\n",
       "      <td>01</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2017-02</td>\n",
       "      <td>102</td>\n",
       "      <td>26</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "      <td>Feb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2017-03</td>\n",
       "      <td>86</td>\n",
       "      <td>21</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2017-04</td>\n",
       "      <td>68</td>\n",
       "      <td>20</td>\n",
       "      <td>2017</td>\n",
       "      <td>04</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2017-05</td>\n",
       "      <td>62</td>\n",
       "      <td>19</td>\n",
       "      <td>2017</td>\n",
       "      <td>05</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YearMonth  United States  San Francisco, CA  Year Month MonthName\n",
       "60   2017-01            104                 47  2017    01       Jan\n",
       "61   2017-02            102                 26  2017    02       Feb\n",
       "62   2017-03             86                 21  2017    03       Mar\n",
       "63   2017-04             68                 20  2017    04       Apr\n",
       "64   2017-05             62                 19  2017    05       May"
      ]
     },
     "execution_count": 783,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_age_T_2yrs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 784,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMUAAALwCAYAAACXycJFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b94610710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"talk\")\n",
    "ax=df_age_T_2yrs.plot(kind='line', figsize=(20,12),x='MonthName', grid=True, style='o-')\n",
    "ax.yaxis.set_major_formatter(tick.FuncFormatter(fmt_x))\n",
    "plt.xlabel(\"Month\", labelpad=20)\n",
    "plt.ylabel(\"Days on Market\", labelpad=20)\n",
    "plt.title(\"Days on Market for Inventory - USA(whole) and SF in 2017\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Analysis : Observing the same seasonality trend seen before by zooming in into a single year(2017)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 785,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files (x86)\\Microsoft Visual Studio\\Shared\\Anaconda3_64\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning:\n",
      "\n",
      "\n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_DOM_US = df_age_T.ix[:, ['Year', 'Month','United States']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 786,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>United States</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>01</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012</td>\n",
       "      <td>02</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>03</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012</td>\n",
       "      <td>04</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>05</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year Month  United States\n",
       "0  2012    01            119\n",
       "1  2012    02            114\n",
       "2  2012    03            102\n",
       "3  2012    04             84\n",
       "4  2012    05             78"
      ]
     },
     "execution_count": 786,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_DOM_US.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 796,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"6\" halign=\"left\">United States</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>119</td>\n",
       "      <td>109</td>\n",
       "      <td>103</td>\n",
       "      <td>106</td>\n",
       "      <td>102</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>114</td>\n",
       "      <td>100</td>\n",
       "      <td>102</td>\n",
       "      <td>102</td>\n",
       "      <td>98</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>102</td>\n",
       "      <td>86</td>\n",
       "      <td>90</td>\n",
       "      <td>86</td>\n",
       "      <td>72</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>84</td>\n",
       "      <td>76</td>\n",
       "      <td>71</td>\n",
       "      <td>65</td>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>78</td>\n",
       "      <td>74</td>\n",
       "      <td>66</td>\n",
       "      <td>60</td>\n",
       "      <td>64</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      United States                         \n",
       "Year           2012 2013 2014 2015 2016 2017\n",
       "Month                                       \n",
       "01              119  109  103  106  102  104\n",
       "02              114  100  102  102   98  102\n",
       "03              102   86   90   86   72   86\n",
       "04               84   76   71   65   68   68\n",
       "05               78   74   66   60   64   62"
      ]
     },
     "execution_count": 796,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_DOM_US_2017 = df_DOM_US[(df_DOM_US['Year'].astype(int) < 2018)]\n",
    "df_DOM_US_idx = df_DOM_US_2017.set_index(['Year','Month'])\n",
    "dfDOMbyYrMon = df_DOM_US_idx.unstack(level=0)\n",
    "dfDOMbyYrMon.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 788,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "month_short_names = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sept', 'Oct', 'Nov', 'Dec']\n",
    "year_short_names = ['2012', '2013', '2014', '2015', '2016', '2017']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Days On Market trend - Heat Map <a class=\"anchor\" id=\"plot7\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 795,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJUAAAN4CAYAAAB6SdkMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkiRJklSw/x+bByMBVXgkegAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12b946ac9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\")\n",
    "f, ax = plt.subplots(figsize=(20,14))\n",
    "ax = sns.heatmap(dfDOMbyYrMon, annot=True, linewidths=.9, ax=ax,fmt=\"0.0f\", yticklabels=month_short_names, xticklabels=year_short_names, cmap=\"Purples\")\n",
    "ax.axes.set_title(\"Inventory Trend - Avg Days On Market by Month and Year (US) - (2012 - 2017)\", fontsize=20, y=1.01)\n",
    "ax.set(xlabel='Year', ylabel='Month');\n",
    "# This sets the yticks \"upright\" with 0, as opposed to sideways with 90.\n",
    "plt.yticks(rotation=0)\n",
    "ax.xaxis.labelpad = 25\n",
    "ax.yaxis.labelpad = 25\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Insights : Usually May and June are the best months to Buy/sell houses, since both buyers and sellers are active during summer and houses tend to get sold faster."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}