{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2016 Election Campaign Contributions\n",
    "##### SmirkyGraphs -  [Website](https://smirkygraphs.github.io/) - [Github](https://github.com/SmirkyGraphs/Python-Notebooks)\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For data\n",
    "import pandas as pd\n",
    "from pandas import Series,DataFrame\n",
    "import numpy as np\n",
    "\n",
    "# For visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('darkgrid')\n",
    "%matplotlib inline\n",
    "\n",
    "from __future__ import division\n",
    "import datetime\n",
    "\n",
    "#use to get info from web\n",
    "import requests\n",
    "\n",
    "#stringIO to work with csv\n",
    "from StringIO import StringIO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "doner_df = pd.read_csv('Election_Doner_Data.csv', index_col=False, dtype={\n",
    "'cmte_id': object, 'cand_id': object, 'cand_nm': object, 'contbr_nm': object, 'contbr_city': object, 'contbr_st': object, \n",
    "'contbr_zip': object, 'contbr_employer': object, 'contbr_occupation': object, 'contb_receipt_amt': float, \n",
    "'contb_receipt_dt': object, 'receipt_desc': object,'memo_cd': object, 'memo_text': object, 'form_tp': object, \n",
    "'file_num': int, 'tran_id': object, 'election_tp': object})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7440252 entries, 0 to 7440251\n",
      "Data columns (total 18 columns):\n",
      "cmte_id              object\n",
      "cand_id              object\n",
      "cand_nm              object\n",
      "contbr_nm            object\n",
      "contbr_city          object\n",
      "contbr_st            object\n",
      "contbr_zip           object\n",
      "contbr_employer      object\n",
      "contbr_occupation    object\n",
      "contb_receipt_amt    float64\n",
      "contb_receipt_dt     object\n",
      "receipt_desc         object\n",
      "memo_cd              object\n",
      "memo_text            object\n",
      "form_tp              object\n",
      "file_num             int32\n",
      "tran_id              object\n",
      "election_tp          object\n",
      "dtypes: float64(1), int32(1), object(16)\n",
      "memory usage: 993.4+ MB\n"
     ]
    }
   ],
   "source": [
    "doner_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmte_id</th>\n",
       "      <th>cand_id</th>\n",
       "      <th>cand_nm</th>\n",
       "      <th>contbr_nm</th>\n",
       "      <th>contbr_city</th>\n",
       "      <th>contbr_st</th>\n",
       "      <th>contbr_zip</th>\n",
       "      <th>contbr_employer</th>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th>contb_receipt_amt</th>\n",
       "      <th>contb_receipt_dt</th>\n",
       "      <th>receipt_desc</th>\n",
       "      <th>memo_cd</th>\n",
       "      <th>memo_text</th>\n",
       "      <th>form_tp</th>\n",
       "      <th>file_num</th>\n",
       "      <th>tran_id</th>\n",
       "      <th>election_tp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>BLUM, MAUREEN</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>20</td>\n",
       "      <td>DC</td>\n",
       "      <td>STRATEGIC COALITIONS &amp; INITIATIVES LL</td>\n",
       "      <td>OUTREACH DIRECTOR</td>\n",
       "      <td>175.0</td>\n",
       "      <td>15-MAR-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1082559</td>\n",
       "      <td>SA17.1152124</td>\n",
       "      <td>P2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>DODSON, MARK B. MR.</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>30</td>\n",
       "      <td>GA</td>\n",
       "      <td>MORTGAGE CAPITAL ADVISORS</td>\n",
       "      <td>PRIVATE MORTGAGE BANKING</td>\n",
       "      <td>25.0</td>\n",
       "      <td>16-MAR-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEBT RETIREMENT</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1082559</td>\n",
       "      <td>SA17.1153048</td>\n",
       "      <td>P2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>CHILDERS, WILLIAM</td>\n",
       "      <td>DPO</td>\n",
       "      <td>AE</td>\n",
       "      <td>098309998</td>\n",
       "      <td>DIPLOMAT</td>\n",
       "      <td>US GOVERNMENT</td>\n",
       "      <td>100.0</td>\n",
       "      <td>20-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.1020839</td>\n",
       "      <td>P2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>RUCINSKI, ROBERT</td>\n",
       "      <td>APO</td>\n",
       "      <td>AE</td>\n",
       "      <td>090960009</td>\n",
       "      <td>US ARMY</td>\n",
       "      <td>PHYSICIAN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>10-MAR-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1082559</td>\n",
       "      <td>SA17.1078677</td>\n",
       "      <td>P2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>RUCINSKI, ROBERT</td>\n",
       "      <td>APO</td>\n",
       "      <td>AE</td>\n",
       "      <td>090960009</td>\n",
       "      <td>US ARMY</td>\n",
       "      <td>PHYSICIAN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>08-MAR-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1082559</td>\n",
       "      <td>SA17.1074981</td>\n",
       "      <td>P2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     cmte_id    cand_id       cand_nm            contbr_nm contbr_city  \\\n",
       "0  C00458844  P60006723  Rubio, Marco        BLUM, MAUREEN  WASHINGTON   \n",
       "1  C00458844  P60006723  Rubio, Marco  DODSON, MARK B. MR.     ATLANTA   \n",
       "2  C00458844  P60006723  Rubio, Marco    CHILDERS, WILLIAM         DPO   \n",
       "3  C00458844  P60006723  Rubio, Marco     RUCINSKI, ROBERT         APO   \n",
       "4  C00458844  P60006723  Rubio, Marco     RUCINSKI, ROBERT         APO   \n",
       "\n",
       "  contbr_st contbr_zip                        contbr_employer  \\\n",
       "0        20         DC  STRATEGIC COALITIONS & INITIATIVES LL   \n",
       "1        30         GA              MORTGAGE CAPITAL ADVISORS   \n",
       "2        AE  098309998                               DIPLOMAT   \n",
       "3        AE  090960009                                US ARMY   \n",
       "4        AE  090960009                                US ARMY   \n",
       "\n",
       "          contbr_occupation  contb_receipt_amt contb_receipt_dt receipt_desc  \\\n",
       "0         OUTREACH DIRECTOR              175.0        15-MAR-16          NaN   \n",
       "1  PRIVATE MORTGAGE BANKING               25.0        16-MAR-16          NaN   \n",
       "2             US GOVERNMENT              100.0        20-FEB-16          NaN   \n",
       "3                 PHYSICIAN              200.0        10-MAR-16          NaN   \n",
       "4                 PHYSICIAN              100.0        08-MAR-16          NaN   \n",
       "\n",
       "  memo_cd        memo_text form_tp  file_num       tran_id election_tp  \n",
       "0     NaN              NaN   SA17A   1082559  SA17.1152124       P2016  \n",
       "1     NaN  DEBT RETIREMENT   SA17A   1082559  SA17.1153048       P2016  \n",
       "2     NaN              NaN   SA17A   1056862  SA17.1020839       P2016  \n",
       "3     NaN              NaN   SA17A   1082559  SA17.1078677       P2016  \n",
       "4     NaN              NaN   SA17A   1082559  SA17.1074981       P2016  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doner_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### As we can see there are 7,440,252 rows 18 columns and some null values<br>This gives us some useful info like the canidates name, contributors name, state, zip, eomployer, occupation, ammount and date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 25.00      1051165\n",
       " 50.00       885354\n",
       " 100.00      785577\n",
       " 10.00       637262\n",
       " 5.00        434221\n",
       " 15.00       327665\n",
       " 27.00       313461\n",
       " 250.00      278865\n",
       " 35.00       150087\n",
       " 20.00       142855\n",
       " 200.00      133909\n",
       " 40.00       125064\n",
       " 19.00       120481\n",
       " 500.00      118679\n",
       " 80.00       103486\n",
       " 8.00        102787\n",
       " 75.00        95509\n",
       " 2700.00      90866\n",
       " 28.00        85847\n",
       " 1000.00      83443\n",
       " 3.00         76709\n",
       " 38.00        69111\n",
       " 1.00         57444\n",
       " 30.00        55169\n",
       " 150.00       50352\n",
       " 37.00        39914\n",
       " 400.00       34955\n",
       " 16.00        27659\n",
       " 7.00         25740\n",
       " 300.00       23758\n",
       "             ...   \n",
       " 227.93           1\n",
       "-1564.34          1\n",
       "-8.70             1\n",
       " 102.26           1\n",
       " 102.24           1\n",
       " 9.66             1\n",
       " 420.48           1\n",
       " 183.46           1\n",
       " 225.57           1\n",
       " 1730.00          1\n",
       " 960.56           1\n",
       " 225.82           1\n",
       "-975.44           1\n",
       "-5700.00          1\n",
       " 224.93           1\n",
       "-133.55           1\n",
       "-79.05            1\n",
       " 33.46            1\n",
       " 1732.00          1\n",
       "-530.89           1\n",
       "-742.87           1\n",
       " 225.43           1\n",
       " 91.46            1\n",
       " 426.77           1\n",
       " 97.22            1\n",
       " 91.21            1\n",
       " 1735.00          1\n",
       " 421.98           1\n",
       " 21.08            1\n",
       "-106.13           1\n",
       "Name: contb_receipt_amt, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doner_df['contb_receipt_amt'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The top donation ammount was $25 and donations tend to stick around even values, 5, 10, 25, 50, 100<br><br> We can also see that there are some negitive values, this is because the FEC also tracks Refunds, these can be Excessive Contributions, Illegal Contributions or Prohibited Contributions we don't need those because we only want too see how much a canidate raises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# removing negitives from our main dataframe\n",
    "doner_df = doner_df[doner_df.contb_receipt_amt > 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Next we will clean up the data a tad by adding party affiliation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Rubio, Marco', 'Santorum, Richard J.', 'Perry, James R. (Rick)',\n",
       "       'Carson, Benjamin S.', \"Cruz, Rafael Edward 'Ted'\", 'Paul, Rand',\n",
       "       'Clinton, Hillary Rodham', 'Sanders, Bernard', 'Fiorina, Carly',\n",
       "       'Huckabee, Mike', 'Pataki, George E.', \"O'Malley, Martin Joseph\",\n",
       "       'Graham, Lindsey O.', 'Bush, Jeb', 'Trump, Donald J.',\n",
       "       'Jindal, Bobby', 'Christie, Christopher J.', 'Walker, Scott',\n",
       "       'Stein, Jill', 'Webb, James Henry Jr.', 'Kasich, John R.',\n",
       "       'Gilmore, James S III', 'Lessig, Lawrence', 'Johnson, Gary',\n",
       "       'McMullin, Evan'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get a list of all canidates\n",
    "canidates = doner_df.cand_nm.unique()\n",
    "canidates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# dictionary of party affiliation\n",
    "party_map = {'Rubio, Marco': 'Republican',\n",
    "            'Santorum, Richard J.': 'Republican',\n",
    "            'Perry, James R. (Rick)': 'Republican',\n",
    "            'Carson, Benjamin S.': 'Republican',\n",
    "            \"Cruz, Rafael Edward 'Ted'\": 'Republican',\n",
    "            'Paul, Rand': 'Republican',\n",
    "            'Clinton, Hillary Rodham': 'Democrat',\n",
    "            'Sanders, Bernard': 'Democrat',\n",
    "            'Fiorina, Carly': 'Republican',\n",
    "            'Huckabee, Mike': 'Republican',\n",
    "            'Pataki, George E.': 'Republican',\n",
    "            \"O'Malley, Martin Joseph\": 'Democrat',\n",
    "            'Graham, Lindsey O.': 'Republican',\n",
    "            'Bush, Jeb': 'Republican',\n",
    "            'Trump, Donald J.': 'Republican',\n",
    "            'Jindal, Bobby': 'Republican',\n",
    "            'Christie, Christopher J.': 'Republican',\n",
    "            'Walker, Scott': 'Republican',\n",
    "            'Stein, Jill': '3rd Party',\n",
    "            'Webb, James Henry Jr.': 'Democrat',\n",
    "            'Kasich, John R.': 'Republican',\n",
    "            'Gilmore, James S III': 'Republican',\n",
    "            'Lessig, Lawrence': 'Democrat',\n",
    "            'Johnson, Gary': '3rd Party',\n",
    "            'McMullin, Evan': '3rd Party'}\n",
    "\n",
    "# creating a party column and mapping party to canidate\n",
    "doner_df['Party'] = doner_df.cand_nm.map(party_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmte_id</th>\n",
       "      <th>cand_id</th>\n",
       "      <th>cand_nm</th>\n",
       "      <th>contbr_nm</th>\n",
       "      <th>contbr_city</th>\n",
       "      <th>contbr_st</th>\n",
       "      <th>contbr_zip</th>\n",
       "      <th>contbr_employer</th>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th>contb_receipt_amt</th>\n",
       "      <th>contb_receipt_dt</th>\n",
       "      <th>receipt_desc</th>\n",
       "      <th>memo_cd</th>\n",
       "      <th>memo_text</th>\n",
       "      <th>form_tp</th>\n",
       "      <th>file_num</th>\n",
       "      <th>tran_id</th>\n",
       "      <th>election_tp</th>\n",
       "      <th>Party</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>BLUM, MAUREEN</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>20</td>\n",
       "      <td>DC</td>\n",
       "      <td>STRATEGIC COALITIONS &amp; INITIATIVES LL</td>\n",
       "      <td>OUTREACH DIRECTOR</td>\n",
       "      <td>175.0</td>\n",
       "      <td>15-MAR-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1082559</td>\n",
       "      <td>SA17.1152124</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     cmte_id    cand_id       cand_nm      contbr_nm contbr_city contbr_st  \\\n",
       "0  C00458844  P60006723  Rubio, Marco  BLUM, MAUREEN  WASHINGTON        20   \n",
       "\n",
       "  contbr_zip                        contbr_employer  contbr_occupation  \\\n",
       "0         DC  STRATEGIC COALITIONS & INITIATIVES LL  OUTREACH DIRECTOR   \n",
       "\n",
       "   contb_receipt_amt contb_receipt_dt receipt_desc memo_cd memo_text form_tp  \\\n",
       "0              175.0        15-MAR-16          NaN     NaN       NaN   SA17A   \n",
       "\n",
       "   file_num       tran_id election_tp       Party  \n",
       "0   1082559  SA17.1152124       P2016  Republican  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doner_df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cand_nm\n",
       "Gilmore, James S III              84\n",
       "Pataki, George E.                343\n",
       "Jindal, Bobby                    761\n",
       "Webb, James Henry Jr.            800\n",
       "Perry, James R. (Rick)           875\n",
       "Lessig, Lawrence                1337\n",
       "Santorum, Richard J.            1675\n",
       "McMullin, Evan                  2569\n",
       "Graham, Lindsey O.              3926\n",
       "O'Malley, Martin Joseph         5250\n",
       "Christie, Christopher J.        5838\n",
       "Huckabee, Mike                  6360\n",
       "Walker, Scott                   6656\n",
       "Stein, Jill                    11014\n",
       "Johnson, Gary                  13400\n",
       "Kasich, John R.                25212\n",
       "Fiorina, Carly                 27536\n",
       "Bush, Jeb                      28038\n",
       "Paul, Rand                     32196\n",
       "Rubio, Marco                   99259\n",
       "Carson, Benjamin S.           244904\n",
       "Cruz, Rafael Edward 'Ted'     541088\n",
       "Trump, Donald J.              762871\n",
       "Sanders, Bernard             2047595\n",
       "Clinton, Hillary Rodham      3471128\n",
       "Name: contb_receipt_amt, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A count of how many donations were to each campaign\n",
    "doner_df.groupby(\"cand_nm\")[\"contb_receipt_amt\"].count().sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "top_doner = doner_df[['contbr_nm','contb_receipt_amt']].copy()\n",
    "top_doner = top_doner.sort_values(by='contb_receipt_amt',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>contbr_nm</th>\n",
       "      <th>contb_receipt_amt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3239378</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>12777705.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3274161</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>7402361.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3224394</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>6358481.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3284270</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>4904860.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3379521</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>4575438.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3447482</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>4560967.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3484760</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>4126693.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3364742</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>3686373.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3369437</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>3600489.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384894</th>\n",
       "      <td>HILLARY VICTORY FUND - UNITEMIZED</td>\n",
       "      <td>2976430.32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 contbr_nm  contb_receipt_amt\n",
       "3239378  HILLARY VICTORY FUND - UNITEMIZED        12777705.58\n",
       "3274161  HILLARY VICTORY FUND - UNITEMIZED         7402361.45\n",
       "3224394  HILLARY VICTORY FUND - UNITEMIZED         6358481.89\n",
       "3284270  HILLARY VICTORY FUND - UNITEMIZED         4904860.51\n",
       "3379521  HILLARY VICTORY FUND - UNITEMIZED         4575438.56\n",
       "3447482  HILLARY VICTORY FUND - UNITEMIZED         4560967.14\n",
       "3484760  HILLARY VICTORY FUND - UNITEMIZED         4126693.23\n",
       "3364742  HILLARY VICTORY FUND - UNITEMIZED         3686373.26\n",
       "3369437  HILLARY VICTORY FUND - UNITEMIZED         3600489.08\n",
       "3384894  HILLARY VICTORY FUND - UNITEMIZED         2976430.32"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_doner.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000000007EB6BF28>]], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEFCAYAAAASWssjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nryk4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7eb6bd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "com_don = top_doner[top_doner < 250]\n",
    "\n",
    "com_don.hist(bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gilmore, James S III raised 105561\n",
      "Webb, James Henry Jr. raised 439246\n",
      "Pataki, George E. raised 507349\n",
      "McMullin, Evan raised 553408\n",
      "Lessig, Lawrence raised 624220\n",
      "Santorum, Richard J. raised 1139075\n",
      "Perry, James R. (Rick) raised 1189868\n",
      "Jindal, Bobby raised 1275393\n",
      "Stein, Jill raised 2493803\n",
      "Huckabee, Mike raised 2499978\n",
      "Johnson, Gary raised 3584074\n",
      "O'Malley, Martin Joseph raised 4064948\n",
      "Graham, Lindsey O. raised 4632862\n",
      "Paul, Rand raised 6314863\n",
      "Walker, Scott raised 6601235\n",
      "Fiorina, Carly raised 6693845\n",
      "Christie, Christopher J. raised 8214280\n",
      "Kasich, John R. raised 14752678\n",
      "Carson, Benjamin S. raised 29014000\n",
      "Bush, Jeb raised 33773733\n",
      "Rubio, Marco raised 40542078\n",
      "Cruz, Rafael Edward 'Ted' raised 69752747\n",
      "Sanders, Bernard raised 97572014\n",
      "Trump, Donald J. raised 127578631\n",
      "Clinton, Hillary Rodham raised 521951750\n"
     ]
    }
   ],
   "source": [
    "# The Total the canidate raised\n",
    "cand_amount = doner_df.groupby('cand_nm')['contb_receipt_amt'].sum().sort_values()\n",
    "\n",
    "i = 0\n",
    "\n",
    "for don in cand_amount:\n",
    "    print '%s raised %.0f' %(cand_amount.index[i],don)\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15902eb8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAygAAAHoCAYAAACig8tsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xu8p2O5+PHPmHGIVA6zcyptqis66FxKlNKudqddats7\n2UWHUYripwM2xe6gKKeinJJjksQunXRGJRLZriI5REVGKcKwfn/czzPrO8taMxPruZ+H9Xm/Xl7z\nXWvWcj1rzVrf73Pd93Vf16yxsTEkSZIkaQiW6fsCJEmSJKllgiJJkiRpMExQJEmSJA2GCYokSZKk\nwTBBkSRJkjQYJiiSJEmSBmNOV//jiHgG8NHMfO5iPmZ/YBPgLmDnzPxRV9cjSZIkafg6SVAiYlfg\n9cDfFvMxGwHPAp4BPBI4EXhKF9cjSZIk6b6hqx2Uy4FXAZ8HiIjHAwcCs4A/AdsCvwNuAZYHHgTc\n0dG1SJIkSbqP6OQMSmaewqIJx2eBtzflXl8FdgUWUEq7LgW+BXy8i2uRJEmSdN/R2RmUCTYAPhUR\nAMsCvwa2AX4P/AuwMvDDiDg3M6+pdE2SJEmSBqZWF68Etml2UHYFzgDmA3/NzDuBm4HbgJUqXY8k\nSZKkAaq1g7I9cExEzAHGgO0o51SeHRFnA7OB4zIzK12PJEmSpAGaNTY21vc1SJIkSRLgoEZJkiRJ\nA2KCIkmSJGkwpv0MyvXX33yPa8ZWWWVF5s+/ZTov5z4T39j9mKlf+0yN3Xd8Y/djpn7tMzV23/GN\n3Y+Z+rXfl2PPnbvyrKn+blA7KHPmzJ6x8Y098+Ibe+bFN/bMi2/smRff2DMvvrGn36ASFEmSJEkz\nmwmKJEmSpMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAk\nSZIkDYYJiiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkajDl9X4AkSZKk4dn2I2fd\n48898r2b3+PPdQdFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBB\nkSRJkjQYJiiSJEmSBmOpBjVGxPnAX5o3r8jMN3Z3SZIkSZJmqiUmKBGxAjArM5/b/eVIkiRJmsmW\nZgdlI2DFiPhG8/Hvz8xzu70sSZIkSTPR0pxBuQX4OPAvwDzguIhYqtIwSZIkSfpHzBobG1vsB0TE\n8sAymXlr8/ZPgFdn5tWTffyCBXeOzZkze9ovVJIkSVI9L9v5tHv8uafv94olfcisqf5iaXZCtgUe\nD7wtItYCHgRcN9UHz59/y1L8Lyc3d+7KXH/9zff48++tPuMbux8z9WufqbH7jm/sfszUr32mxu47\nvrH7MVO/9r6/74uzpOuaO3flKf9uaRKUI4CjI+KHwBiwbWYu+EcuUJIkSZKWxhITlMy8HfjPCtci\nSZIkaYZzUKMkSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIk\naTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GC\nIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIk\nSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwT\nFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIk\nSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCY\noEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIk\nSdJgzFmaD4qIfwJ+BmyRmZd2e0mSJEmSZqol7qBExLLAYcCt3V+OJEmSpJlsaUq8Pg4cClzb8bVI\nkiRJmuFmjY2NTfmXEfEGYJ3M3CcivgvMW1KJ14IFd47NmTN7Wi9SkiRJUl0v2/m0e/y5p+/3iiV9\nyKyp/mJJZ1C2BcYi4gXAE4FjIuLlmfn7qT5h/vxblnQxU5o7d2Wuv/7me/z591af8Y3dj5n6tc/U\n2H3HN3Y/ZurXPlNj9x3f2P2YqV9739/3xVnSdc2du/KUf7fYBCUzN20fj+ygTJmcSJIkSdK9YZth\nSZIkSYOxVG2GATLzuR1ehyRJkiS5gyJJkiRpOExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmS\nBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYo\nkiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmS\nNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBB\nkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmS\npMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJ\niiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmS\nJA2GCYokSZKkwZizpA+IiNnAZ4EAxoB5mXlx1xcmSZIkaeZZmh2UlwFk5rOB3YH/6fSKJEmSJM1Y\nS0xQMvPLwFuaN9cFbur0iiRJkiTNWEss8QLIzAUR8Tng34Atu70kSZIkSTPVrLGxsaX+4IhYA/gx\nsGFm/m2yj1mw4M6xOXNmT9PlSZIkSerDy3Y+7R5/7un7vWJJHzJrqr9YmkPyrwfWycwPA7cAdzX/\nTWr+/FuW9L+c0ty5K3P99Tff48+/t/qMb+x+zNSvfabG7ju+sfsxU7/2mRq77/jG7sdM/dr7/r4v\nzpKua+7claf8u6Up8foScFREfB9YFtgpM2/9Ry5QkiRJkpbGEhOUppTrtRWuRZIkSdIM56BGSZIk\nSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwT\nFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIk\nSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCY\noEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIk\nSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYokiRJkgbD\nBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmSNBgmKJIk\nSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwZizuL+MiGWB\nI4FHAMsD+2TmVypclyRJkqQZaEk7KFsDf8rM5wAvAg7u/pIkSZIkzVSL3UEBTga+2DyeBSzo9nIk\nSZIkzWSzxsbGlvhBEbEy8BXgs5l5/OI+dsGCO8fmzJk9TZcnSZIkqQ8v2/m0e/y5p+/3iiV9yKyp\n/mJJOyhExMOAU4FPLSk5AZg//5YlfciU5s5dmeuvv/kef/691Wd8Y/djpn7tMzV23/GN3Y+Z+rXP\n1Nh9xzd2P2bq1973931xlnRdc+euPOXfLemQ/EOBbwA7ZOa378nFSZIkSdLSWtIOyvuBVYA9ImKP\n5n0vzsxbu70sSZIkSTPRYhOUzNwR2LHStUiSJEma4RzUKEmSJGkwTFAkSZIkDYYJiiRJkqTBMEGR\nJEmSNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKk\nwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmK\nJEmSpMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIk\nDYYJiiRJkqTBMEGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCYoEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQ\nJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgzOn7AiRJkiTd3bYfOeteff6R7918\nmq6kLndQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmD\nYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYokiRJkgZjqRKUiHhGRHy342uRJEmSNMPN\nWdIHRMSuwOuBv3V/OZIkSZJmsqXZQbkceFXXFyJJkiRJS0xQMvMU4I4K1yJJkiRphltiidc/apVV\nVmTOnNn3+PPnzl15Gq/mvhXf2DMvvrFnXnxjz7z4xp558Y098+L3/bVP5b76PZn2BGX+/Fvu8efO\nnbsy119/8zRezX0nvrH7MVO/9pkau+/4xu7HTP3aZ2rsvuMbux9dxt/2I2fdq88/8r2bT9OV/OP6\n/DdZUuzFJTC2GZYkSZI0GEu1g5KZvwWe2e2lSJIkSZrp3EGRJEmSNBgmKJIkSZIGwwRFkiRJ0mCY\noEiSJEkaDBMUSZIkSYNhgiJJkiRpMExQJEmSJA2GCYokSZKkwTBBkSRJkjQYJiiSJEmSBsMERZIk\nSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTDm9H0BkiRJ0uJs+5Gz7vHnHvnezafxSlSDOyiSJEmS\nBsMERZIkSdJgmKBIkiRJGgwTFEmSJEmDYYIiSZIkaTBMUCRJkiQNhgmKJEmSpMEwQZEkSZI0GCYo\nkiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg2GCIkmSJGkwTFAkSZIkDYYJiiRJkqTBMEGRJEmS\nNBhz+r4ASZIkDd+2HznrHn/uke/dfBqvRPd37qBIkiRJGgwTFEmSJEmDYYIiSZIkaTA8gyJJknQf\ncG/OgIDnQHTf4Q6KJEmSpMEwQZEkSZI0GJZ4SZIkLSXLrKTuuYMiSZIkaTBMUCRJkiQNhgmKJEmS\npMEwQZEkSZI0GCYokiRJkgbDBEWSJEnSYJigSJIkSRoMExRJkiRJg+GgRkmSdJ9yb4YlOihRGj53\nUCRJkiQNhgmKJEmSpMGwxEuSJP3DLLOS1BUTFEmS7qF7c5MO9+5Gvc/YktSlJSYoEbEM8ClgI+A2\n4E2ZeVnXFyZJ0tJwJV+S7l+WZgfllcAKmblxRDwT2A94RbeXJUn3PTN5Nd0kQZI0XZYmQdkEOBMg\nM8+NiKd2e0mS7uv6vFn1RlmSpPu2WWNjY4v9gIg4HDglM7/WvH0VsF5mLqhwfZIkSZJmkKVpM/wX\nYOXRzzE5kSRJktSFpUlQfgS8BKA5g3JRp1ckSZIkacZamjMopwJbRMTZwCzgjd1ekiRJkqSZaoln\nUCRJkiSplqUp8ZIkSZKkKkxQJEmSJA2GCYokSZKkwViaQ/KdiIgXTvV3mfmNmtfSioinZuZ5PcVe\nJzOvqRhvZeDFwArt+zLzmEqxZwNvANYFzgIuzswbasSe4np6+3evKSLOAA4HTs/MOyvFHNTveUSs\nmpk3Voy3XGbeXiuehiEi3pSZh4+8/c7MPLBS7F2Az2Xm9TXiDVlEzOljLELt1/O+RcSqwPrAFX2+\nluv+pbcEBfiPKd4/BvSSoACvAfq6Uf0f4L8qxjsNuBa4unm7ZreEw5rYWwA/BY6haWXdk87/3SPi\nOcBOwCbA7cAC4Bzg4Mw8u8vYI3YBtgX2ioivA4dn5q87jjmI3/OI2Aw4BJgdEScDV2bmERVCnxcR\nZ1G+1xdXiLeIiHgqZTFgxfZ9mblt7etoruXgzNyhQpwrWPT57A5gWeC2zNyg49j/AbwceF5EbN68\nezbwOKBKggL8FTg1In4PHAGcmZm9dMOp9W++GP8L/EsPcau+nkfEesDHgEcDFwO7ZubVi/+saYv9\nWmAf4BLgcRGxV2YeWyHuHcCFwItrJ+MRcR3lOWZ5ynPr1cA6wB8z8xE1r2Xkmr6YmVtWivUyyr3E\n8u37MnPa7+F6S1Ays/d2xRHxvMz8Tvt2Zr6nr2vJzJrJCZSBm1tXjtlaPzPfFBGbZObpEfHenq4D\n6P7fPSIOogw83RO4JDPvat7/eGDriNg6M9/W5TUAZOalwK4RsS/lZuniiPg+8N+ZeU5HYd/a0f/3\nH7U3sClwCvAhynynGgnKE4EXAXtGxFzgWODEzPxrhdgAnwYOBn5fKd7iHFIpzmMoLfEPAQ7LzJ9E\nxJOAzn/HgDOB64DVKAsxAHcBl1eIDUBmHgocGhGPBXYDDouII4EDMnN+reto1Po3n1Rm9pGc9PF6\nfgSwL3A25XnuSMoCYA3vAp6cmX9tKjPOojzPdW2FWpUAE2XmmgARcSzwvsy8OiLWAj7Rx/U03lwx\n1scpr+2dPp/0WeJ1AlOs2mfmf1a6jA8A31niR02jiHhjZh7VPH5sZv6yebxnZn6g4qX8IiKeAfyc\n5t+hYinKnIhYHRaWmt1VI+gkP3NjwB8puxhd3kDsnZl/nPjOzLwIeE9EPLTD2AtFxIspq+kbAJ+n\n7OgsC3wV2KijsMndf89nNe9br6OYk7krM2+MiLHM/HtE3FwjaGbeFRFfo3y9bwLeAbwxIk7IzIMr\nXMJfMvNzFeIsIiJmUW6U1gWuAr6Xmf9XI3Zm3tZcw/qZ+ZPmfRdERFSIPR/4brP48r32/RHxYeB9\nXcdvYj0E2ArYBrgJ2JGyi3MG8OyOYj56wrvGgOtr/ZtHxBzKztX8dtGxeV49MDP/vcO4K1Bu1A4E\n1gY+Cfwd2CUzay4K3JmZX2senx4RO1WMfVe74JKZN0fE3yvFPTMiprqHnLK0eJqt1+5UZea1EfHw\nrgNOUjY9Rtm5ubDr2CN+mZnf7TpInyVeh/YYuzUWEadSbqLuAsjM93cc8/XAUc3jg4C2DGCzjuNO\ntBnwspG3a94w7k5ZwV4TOJdyo1zDZD9za1NKzDp54QZok5PRHbuIeADwicycl5l/6Cr2BFsDnxq9\ncWquZa+uAmbmP3f1//4HXdbcJK7W7NhdWSNos1v1CuB7wEeb1fxlgJ9Rdja6itu+iP05It7fxGsX\nIjotrWtuDM8ALgOuoDzP7B8R/5qZ13UZe4KbImJv4CfAsyg7G52KiO0oiegGEdGWPMymLARUSVAo\nZbPHAltl5lUj1/akDmMeNsn75kbEyZUW3o6jlM2u2ewcXUHZVTig47gHUkrqlqHsFv0U+CVl5/Lf\nOo49+nv+t4jYFfg+8HSg1msKwG8iYr8m9qbU2y1s7xv2AL5Cuad4OuVsbS2XRMTnKc8xG1OeZ7s2\nWdn0WhFxVWbW2kU5LSLOARYuQHRROtxngtJVSck/4sgeYs5aisedy8yuVsyXJvb3ImIL4FbgEZn5\n01pxJ3t/RLy9Rnxg72Zlaw7lsPrnK8VtbQe8OSK2pNQpH56Zd2bmqV0FbGvQmyezRVa7MvNZXcWd\nxDzKjeMPgb81j2u4GnjKaElXs6vS9c1L+yL2Z+BRzX9Q5+zPfsB7M/Pb7Tsi4kWU8oetOo496nWU\nf/eXUm4a96oQ81jg28D7KecQoCx+3W0HdbpFxHLNwycAd46+LzNvz8zduoqdmc+b5HqWoSxA1UhQ\n1s/MpzZf78+A24DnVdjBeWxmPrvZSXkOsGVm3hERO3cct9X+nt9I2Rlvz1jdVik+wBspu0hbUM6h\nVCnZHqk+WT0zj2/efWVEzKsRv7Er8DzK2Z+TMvO0rgNOdTyieY2t5Z2UksKbugzSZ4LSW+nHyKpD\nu6JWc4tsYonRZI87FxEvB95OWdmbBayWmU+oFPtQ4LLM/HhE7N6cwdixRuwJ1/EgyspLVgr5yibe\ncsBrapU/jDga+C3wLcqL6ZF0f5Bz7+bPmjemk3lOU5tPRKxI2b2s8UL275l50MR3ZuZvuww6+iLW\nrJwHZVv+oi7jNh42mpw013NmROxRIfaoW4AfUFa1AZ5BWeXtTFNe9tuIeBvwFuCxwK8oK+pdG0o5\nZdupcRPqLbz9BUoi1iRGL8w63fraUtFnAz/JzDuatx9QIfbE3/NHA48EfkFpQlPLU4DZzULUcZTF\n5wsqxl8mIv6L8Z3SmudSvpKZm1SMdzcRsTwlUa15D/n7zDyp6yB9HpLvs/Rjqi2yKzPzLR3HXq3Z\nPVgGWLVJlmYBq3Ycd6J9KKse8yjncGodqINyoG4eQGbu2BzU7sPNwA5dd1dqSovaJ49LKYemXx8R\nNUoKR62RmW2icFpETLqjNM12nFD63577qb171O5ezaaUftSK/7eI+ASLlpF+plJsmhKnzSkv3u+M\niFMz82Mdh+3l4OokTgHmUnax2hv1Ws81h1F2r75JKac9nHImpDPta2qz4FPjkPLirEA5b/WOHmL/\noVJyAvDXiHgLsCVwfJMcvY5y7qqaiNiBUlK2KmUh6lFAre5pBzO+ALVHE3/TSrGhlC7vQSmfv4Ty\n/a/lxojYkUWf32t3oZ1F6RJYszHDrRFxJiURbUuHp/1eps8dlN70vEV2PtA2AbiA8WSp5ooDwHWZ\neU5EzMvMoyPiDTWDR8Rqmfmn5kBnLz+HWVpv1mj9euloWMp5hGpGSj+uiIinZeZPI+IJlJXdrk22\nO7UW8AXgBRXit/ravWpbSLeNEGq3e30x8PSmrGw2ZXWz6wTlqoh4aWae0b4jIv6VsntX0xqVywhH\nPSoz25u0L0dErVbiULr59JqgZObfKDfttTw2Io6n3Ky1j9tr6bLpzjzg/1G6t32OshiwJfW7F25F\nSQq+nZkHRESVsunGHW2Tmcz8TURUaXrTag6nn0TZJfwJzW5aJX+idGp8YvN29TEZmfl3ygiBmk6v\nEWRGJigT1dwimyo56sFtEbEpsGxE/AuwesXYH6TMh5gPPJhSana/1XZRiohnUm4WD2y2wverdQmU\nn+1ZwHMj4nbKjXrn3Vam6iDV3LB2ru/dq8z8QESsyXgp5Vpdx5zgGmBlymr+stQ5PLsL8KVmZfly\n4J8pCdrLFvtZ0+/SiFgrM2uWu7RWiIgVM/OWpiHG7Iqxl4+IC1h0VbdWZ8y+vHbkcbUGPFmGEo62\nqf92819ty1Ce59rnuppnUK6MiA9RFj+eDvyuYux2l3h9yjmQMUoziiq7KBPv55rn+pngOOBpdPy6\nZoJS9LFF1rftKfMC9qGcE9inVuDMPCNK69XVKWd/ehki1oOD6GErfLScMkr719Wyp2m/UdpKH0TH\n/dNH9L17dQSlu8tKlLr03wDPrHgJawG/iogLgQ2B29vV/K52F5qfrU0j4imUVc2Ts94w0lGbUHZz\n2iFuY5lZK0E8ALgwIi6mfN/3rBQXFr1hrioiIjNrnelbaKoGKDPI8ZTyxXUj4qvAlyvG3o5y3uol\nlK5O1e4lGptl5qYR8Z3MPCoiqu1eRcQHKfdSy1EGNv6Kcu7s/u5USnKyNmXx5VrghOkO0ucclH8G\n9qdM8X4WpeTjr8Drs7uhcZPqaYusb7sAn83MS4BX1wzcnMF5F6VOmWY1e/PFf9a0xO17+muvW+FR\n5qAcTGk9+0DgLTV6mU/wN+CL1NsG/2Vmnhd37x1fy0aUF6zDKJ2dvlg5/msqx1soM39GnbabU8Wf\nOJujZuzjIuIHwD9Rnl9qnkm4iDI9fXR1s9YN/BGUxFAVZebBEfFtykJrZuYvKob/ctabOzKZOU0V\nzFhTxlrzDNzLKfcQn6Dcz36q64ARcRRTzxCc9la/U1g9MzeOiMMp58y+2UWQPndQDqZM+V3Q9NBu\nDzgdBzy3x+uqJiKeT9maPBf4VZMo1fJDYN9mRfsoSou8WyvF/gSlh/nVleIBg5j+2utWOKXN6jMz\n8/qIWIOyylZzNZ/MvIsyI6OW5wPncffGGLVqhf+UmWMRsVJm3hDdzwqcaAHwUcqN8snALzLzx7Uv\nog9NSeUbGblRz0qTxSNiT2D5zHx/RJwcEedl5kdrxKasbv4f8HhKGectleJCz00h+hQR/0Sz6AZQ\nIymdUMJK83itiLimYqOA+U1X0F8x/m9e43xj6wDKc/w/UV5b79Y1sUPXZeZtEbFyZl42ct6zSyc2\nf25POeP4I0q51dMrxG61zykrZeatMcXAzHurzwTlgZn5lYhYjdKW8puwsHd6FRGxRtad9joa+0OU\nzHsDSr3o+5i8u1gnMvMU4JSmZvITlAm4D6kU/qrM/FalWJOpPv218UbKocqXUJLx2lvhN2fm9QCZ\n+fuI+Fvl+NW1N4U9nv36WUTsAlwbESdSqf3oiM9QzjrtQSkB+RyVktI+n18bn6b06t+SsqtQ4+ah\n9fLMfApAZr4mIn5ESRRrmJWZ8yLiSMq8nx9Uigt3bwpRVUQ8jPI6OpoofLBC3E9RntevZbxjXI0G\nDZdO8r7aTUj+iVIR0RpjfAB1ZyJizcy8LjNPanaPHgVcns1g5EquiYhtKYn5h6lwD5WZXweIiJ0z\nc9/m3T+KiE52MabwpYj4b0oZ67mU6qdp12eC0u4WPB84CxbWxz+44jV8salPPgL4arO6W8smI3WT\nn4uI7SvGprkp34by4n0+daev/jHKLJTRFnU1V9mqTn+NiKdm5nmU8yaXNP9BaT/a+Sp+kwxD2Qo/\ng7J79nTqHqTsRVNGdyNw+8i7Z1HpPEKzgr4yZSjpiyk/czU9IDPPiojdMzMjouYubZ/PrwA3ZOYJ\nEfHCzNz/I8b7AAAgAElEQVQr6rTVbt0VEctlmcuxLOUQcy0LogwOXIny/Frtdb5pCvECytmjc6nT\nKXDUyZQ5T1V35ynPp+vV/hnvuwlJcw2LDOmstIsApdpm8+YabgD6OFf5VuBhlJ+7NzDeobWGB0bE\n5pQ5T89iJCnvWmYe0j6OiP8Fft1FnD4TlIubVoBPpUy3XpPS3emsWheQmZtExIaUle3dmyz8iMz8\nTYXwc5oXkT7qJqHMCDgc2DQza7blA7ii+XONynFbtae/9l1mlBP+HAM6n3i7OE0ZyF+Bj+bIlPUO\n7EJJDC4HjsvMaqvJEfGCZqdwD0pDiDGgdnnV35sufbObkqdqCUrPz69QkoTHAitGqa2rOWvqUMpr\n3EWUZiS1dk8ADqGU0H6DcqP+w1qB+64MoOwS714xXusyyg1izXK6u+mhCQnNofR3M15KeQfltXUm\nWIkyAHYFSqfEpzK+ANm17Sg7xI8GfknFJk9NArw95Sxva9p3zfpMUHahtPzcvznE+njKP+yBla/j\nd5TOOk+hHDA7ICJ+mZnv7TjuJygr93MpNy1VzkGMbIs+bcL7n1GrNn0Aq2xVp79OVWbUHFqvEb9t\nczyHsuKzIfWmW0/laMqqS6fPQZm5P7B/RDwGeF1E7EUpQzm2y25DEbE75fnkW5Sdsz2B51CSlZrD\n694CfJySIO1CeVGpqa/nVyg3TY+lvKYcT9nJqSIzj4iIr1Ce4y7LzD9VjH0KLJzmfnLlBaheKwMo\nSeFWLLo7X+P15eGUM4aXNW+PddUlbwlqNyGBMibgucDulJ2EnSrFfUrcfb5Quzte63t/GqWsr92x\n67wj6cgO1eWUBkdtSWFNe1PK+jot4e1zkvwY8LWRty+i1AlXExFfoLxoHgtsnU2//Ig4r+vYmXly\nRHwLeCTwm4ovYAu3RSPi85n5+ub9H6ZC3WgTt+9VtqrTXyPivyjf31spJXW/AT5L+fq/tphPnW6H\nATdRcbr1qAmHSOdnZrXVxsy8FNgjItahnMm4kG63xF9A2TkDuDUzv978vlfdQcnMayLidZQXsY2p\n2Jihz+dXgMz8JWVlEcrNTOcLAhGxKiUJ3ZlyDuMQyi7Wdl0mxE3sdYCTgJdm5nzg34F3RsSrst4s\nmL4rA0aH5kGl8xDUff2aUg9NSACuzczrmoPi320aRNRwCf1/35fJzK0rxxyda9YmJu3j9Spdw41Z\nobX3TJ+DcvgUN6adr65HxHcYyXoj4g5KFr5PZv62w9CzRh6vM8X7u9b3Klvt6a87U1Zy16TcHK9F\nWXmpMkxqRG/TrXs8RNreNL6W8WFuJ1FhJyEz25uzA9q3I+LPXccdFRGfpHR0Whd4MmVQY61SgM+2\nzU8m6PT5NSLeAHyIfhYEDmW8pOpASrnNRZSfgRdViP2xJjkhM49vXlcOpbRDraGXyoDWxPMQXYuI\nN2Xm4ZTmJxNXsTsfBDsQf46IV1KS0rdSb+jz3zPzykqxpvKLiHgG8HPGd+xuX/yn3Ds5MtestijD\nd6HM0/oM5Xe9s3PEMz1B2Z1JbkyzTrvf31Law/2AsrL5MkqLvCMYX3mtqeYWYa+rbJOUWnU9/fXG\n5qZhflOTPy8za+6ctPqcbt3LIdIoQ8vWppQevJl6h2eXaw9JZ+aXm2tZjvrPuU/LzJ2axYDnNedA\narkuyiyQVSi7KBdn5hkVnl/b0q4+FgTWzMwDm7MATwCOyabNdIXYK7c/a61mp37HCrFH4/VRGQBA\n01loB0p77faaumyG0T6fTOymNVOGD0PpFPdISiXEztQrYT28UpzF2Yxy7za6o1FlFyNKa+e3M372\nZ7XMfELHYdt7pbYSoNNzxL0nKBGxNqVz1wLKBNyDMvPnlcKPRcSpLFrqU2vV4+EjN8oZEa9r6pa7\nLrmZ2DO9D/uz6Crb/jWDR/3pr6M35Vf2lJxAv9Ot+zpEuiHl53w7oB1iVeOF5DjgyIh4R2bOj4iH\nUFp5H99hzMnMjjLR/bdNgrRyxdgHUA7If5ay8PI16pSf9Lkg0Lbu3gz4QVPKDOUwbdem2gWvtjs+\n8fBsVBrCO+JlwLpZaaZX2/KVMlNqMyp2UlqcGk1IImLTCe9ambrNV97UlG3uWDsRHvGxzDy2p9j7\nUM6UzgO+A2xRIeZRFWIs1HuCQnnB3ouSCX6RsiVca5v2yEpxJrNc013nHEqpy7IRsR6LdkXowiYR\n0ZbZrDryeJWO4476E6XM45HAFU2LwJpqT39dLSK2oLQafVCMTDXv8uzLRFmmW3+NcmN+ReUn9V4O\nkWbmI7qOMUXcQ6K0OP5+RKwC3AwckpmHVb6UYyg/39tSOr5UjZ9leNlYluGgN1cK2+eCwHXNGbsX\nAvs0Oyk7ATUme/84It6ZmQsbzUTEOyrFblU5PLsYf6R0kartG5QzETc1b49RZpH05Wi6b0LyXcpB\n7Z82b7eJ8Bhl5lLX9gJ+32NyAmVXvq8E5brMPCci5mXm0U1pa9dOovz7rk5JSC+iLO7+ntIIZVoN\nIUG5i/LDvFtmnhgRb64Y+xjKBM4+Vj3eAHyMsqp6EeUG4pmU8oTOZGbNYWVT+UBzFuKnS/zIbtSe\n/no+4/3RL2D8YF+VNsMR8SDKNvwfKW28P0xJiN+dmed3Hb/R92HG6jLz0/TbKY3M/FREnERJSvep\nvBhwY1OTvlLTWemmJX3CNOlzQWB7yq7RhzLzy1FaO69OWYDr2u7AJyPid5QbhocAX6fj15QJqhye\nnSgiTqA8nz4UuKDZJYayEFJjNsWfJ5YO19SUSj+JkQXOCk1Inkp5XXsy5XXl2I7Pzy6ij5+zSSwf\nERewaBVOrVkotzW7WMs2i92dn/3JzI0BmsqjbTLz5qZ89YQu4g0hQVmWsrL3/Yh4HnWn/Z5CmYI6\n2iKuRuYP8LbMfNWE99WaD9C3PkvroP7017cv7sWiPRfSYfzjKV2rHkk5PLwncA3lEG/XB5Y9RNqj\niHgtZVX7/4DHRcReFUsStqP8G99AuZnZrlLc3hYEmvM1nx55+1xKK/XOZeZtwPYR8U5gNcqgygVL\n+LRpUfvw7CQOrRBjcb4eEfMYmYGRmbXuJaBUnzyE8Z2rzu9lmsWt86MM2N6c0iVxDUob/9o7xX15\nT4+xt6fMWNqH8hy/T8XY62TmzQCZ+beuzvEOIUF5I6V27nDglVQcNgOs0VOvcoANI+IhmVlrVXFI\n+iytg1K3uQ7j01+7Xt0/pGmteuLodnRErA5sTVn56vLn/sGZuVsT89mZeVTzeNcOY7amOkSqOt4F\nPCUz/9qUG51FpZKEzPxLswBwF+W5vcqZtz5XsocgM++gfolV1cOzE7Wr6c1u8R6Mz3rau9IlPAdY\nnnIOBeoudgKsnpnPqRhvoaYJxNmUxd5tKLv1MyVBOZ+SpKxFOV9XrZwyM3/XdOlbgfI8X9M3IuJ7\nlAHUz6CcwZp2Q0hQfgPcTtmePguoOVTq0ohYq2KP+FEbAn+KiBsoL+BjHXcbGZL/AL4EnJqZ1/cQ\n/+GU9qMrUupmXwN8sKtgmfnGZiX7yxHxMMqK8oOA64BPZeYnu4rdGK3JHq3X7byL18gh0uMoyeDD\nKb/nF0/1OTXUOEQ6EHe1X1+zHV9tknxEnEh50X4WpdzqVcC/1YqvejLzAwDNavoraaZbZ2btmRxH\nAt+jPN9sRjmLUaPF8gMz8wUV4kzlyoh4WGbW6lJIRCwLvJiyWxmUA/I7ZXY772ck/iKjGkZVbMxw\nJKX5x2aURYEjGE9SO9Vn6/7M3K1pvvIo4HOZ2UliNoQE5TDKN3gLypmEYyjf9Bo2Aa5qkoQxKiYJ\nmblujThLKyLeQ/kh/3iFsoDtKC8aR0bE8sAZowc7KzgBOJOKq4yZ+QXgC0175VWAP3XdL33E2k0J\nxqwJj2smxIfS3+/5ZI6mwiT7iZpa+Wso3V/+WCHkbyJiP8pq7qaUQ621rJWZx0YZUvi8pv3sjBRl\nSOnNtbpL9eizwAMpzV+2iYjNM7PmGZjVMvOg5vHPI2LLSnF7mWAfEdc18VYAXhsR7QJUjXuZP1Ke\n00+gdHcaA9aNiHUrNX+Z1/y5J2UF/0eUdvYvrRC7tVpmHhkRW2fm2RGxTMXYvbTuh4VDYd9LOSCf\nEfGuLs4fDSFBWT8z3xQRm2Tm6RHx3lqBM/PRtWJNFBGPp2Tf61BulLfNzAv6uh7KoKHzKTfPne5q\nNFuTP21ivZIy8bhmgnJLu+JXW1Ojfl3lsMczXoIx+riTg21TaH/Pn1P797wVEc8H1qecCcisM+9o\nop0oO2i1Wr++kVLSuAXlHErN7/tyEfEq4JKmnLFmi+OhOQC4PCIOzcxragauvFv4+Mx8RvP4gIio\ncv5mxAMiYo3M/H1EPJR6s542av5rVZlgn5ldz/BanNMoX+f6zX+tKs1f2p2aiHhoswAIcGrTua6a\niHhM8+c6jMzfqaCv1v1QFiI+TVn4ei4dze8bQoIyp3nxoqmRrpYNRsRjKSu7iwwSqxT+QOBNmXlh\nRDwROAR4dqXYdzNSitO5iLgRuBL4CLBFZlaZrh0RbUL6h4j4TxY9yNn5aldf+krGJmh/z8dq/54D\nNK1f16FME7+NMlSs885iTcnLIp0CM/MPFeK+cOTNX1Pq8f/YnE+oZV9gK0oXqXdS7zzApJqSkAuA\n/TLzdx3HitFSl8zss4vd0dTbLbwsIv45M69odo2uqhBz1B7A2RHxF0pCXKUraE6YYF+hM+QiIuIF\nlH/fZYCDgD0ys9OZS5n5hi7///+IiNgO+AmlxKlWZQLAjpTdow0ojQreVjF2L637Gytk5leax1+O\niE7OwAwhQdmdsjW3JmVlc6eKsQ+kn0FiALMy80KAzPx5RNTMvImI9wO7UrLvWdQ9A/MS4EWUUq8t\nI+Jblbp+jMZ4M+MvXlVWu2a43Vj097zadOvGJpm5aZSJ6p+LiO0rxe2rU+BkN8RrRcRVmVnrpu1L\nlLNmAP9dI+biTLyJ7NgRdNwhb3GarjrthOmuuwSO2phytvMqYG1KK9TrqPT6kpnfBNaLiNVrttRu\n2mm/m/Hv+R2Uczi1/A/lLEi70PkF6g+F7cvrKK8vrwV+2bxdRWZeBGzclKq3nfRq6XPRY05EPD4z\nL2qqgboJ0tX/eGk13TciIub2cWA6+xkkBnBnRLwU+AGlNrzmDzaUsqq1Kr5wLZSZ50bE1ZT61f+k\nHJ7uPEFpb1CacyAbZOYFEfFK4H+7jj2ZiNg9M2u2BuzTLZkZETGXUuI0cQpx1+Y0/+5jUWYG3Fkp\nbi+dAqfqZBUR53Qde6QufnlKI4qrKTer12eFwZkjLW/vplLLWygtzD/Boq3Uq8SOiCMoicJKlO//\n5ZQZW53LzPVqxJmo+bkePTA9FhF/BD6cmT+pcAlvp5S67E7pDllzoRXKQuMfgAVNeVuVjnkDsX/W\nmz0CQERsRGnr+wfgRJoBhs1ZjM9Xuow7KcOm2451NTt5vZNyhnhNyn1cJ4tevScozcrDW4EVIgKA\nzNywUvi+BolBGcz4ccrQvP+j0lb0iCuAXg5sRhlsdANwKvC6rsstJnEsJSm5gLLK9VrG5ybU9KMe\nYi5U4+BuRDyH8gT6rojYv3n3MsAOwOO6ijuJT1BK+uZSWqF+olLcPjsFLtSs8P0HFVr9tnXxEXEs\n8L7MvDoi1qLe97zPuvzW2c2fD+0h9kaUw6uHUebQfLFW4B7PVm41yfvWpuwoPK1C/Gsz87oow3+/\nGxF7Vog56mZK45fPRMTbKQfYZ4rlI+IJlJv0djGg6zKvT1MO569KOaD/JMrZ3TOBWglKlXMgk2l+\npxf+XnW1i9J7gkIp9XgJML+H2H0NEiMzr4yI3Sht2i4Eat+kLwdcFBEXNW/XmrgL8PzMvLF9IyLW\nzMyaB8fXzmYWSGbu29Sm92GFJX9Ip2oc3J1PmYmwPOM3jndRygurycyTmy5SjwSuqFj+0VunwAlm\nURLCmnOm1mvbnmbmtRHx8BpBR1reVok31TU05wLWo5Q01jzj9qcssylWyswb2oW/Sno5W5mZV07y\n7isjotZZtz83u/FjzaJn51O9J3gNpRHJJRHxOMrNay9qnvVqPJpyYL81Rvm969LtTTkhEbFjZv66\neVyzZf3EcyCdd8uLMrH+48CNlMqXqynDn7einImZVkNIUH4BXJ2ZtUouJr5wfWrk8QMp3/ga17AD\nZSbAqpRDjI+irCrX8tGKsSbaKcrU3bYE5NeUVfZaxiLi0Zn5q4hYn447vUTEGyi/xLdS5q/8hvIC\nsgHl3FMvahzczcyLKS04P9vcpD4EuDObKbS1TGyIERFVGmL02SlwVNOxbJfKYS+JiM8zfnj1Z5Xj\nn0S5WVkG+GfK80yVcyF9NWVo/CwidgGujTKLZsVKcaHns5Wt5nnmfCoNJaUMJ3wk5d95Z6BqJyma\nieYTktHOZnstTuWzXmRmZ2cgFmM08R3tBlmzzfDEcyA1yvr2BV4NPILS5Kg9X7nRYj7nHhtCgnIW\npVf/5Ywf1u76wHL7wjWL8gJyCZUH3VAyzk2Bb2fmAVHa7nYuIl7a3Jg9hrv/QH+vxjVQZqA8jFLy\nsT+LJok1vAs4KSLWoOxczVvCx99b76aUXKwJ7EeZP3IalQ7zRZnmPdVAq/d3HPvJlK3np0dpOXso\nMD8idsnM07uMPUEvDTF6LHkZgrdQFmEeDZyYmact4eOnVWZu3D5ublhrnT+B/poykJnvbzrl3UoZ\npPfjJXzKdOr7bCUAmXlTRGzU9UJIRDw1M8+jnPmBUkL6dUqL7ecCF1TqUtl2BpwFPJmKN8oR8SBK\n97T2LMTeoxUSFeK/nHIGqG1QsFpmPqHjsI+NiOObeKOPay60tudA1qLcx0x59m4a3dR0PP1Vc9bt\ng5nZ2W7dEBKUt1LOAFQ7/zHhhes7tTP+xjI0JR/N27WeyFdr/lxjwvtrHqq7LjNva+p1L4vKLRkz\n88eUmtFabszM+ZQb8w2BeZlZc+fk0oqxJvoY8F+ZeUdE7EO5Yfo1JUGomaD01RBjUO3EK1uJsjv5\nO+DBEbFNZh7T07X8me7LPkb11ZSBiHgYZbemLSF9EvVW09uzlR+hLPy9qVLcu6m0S/t84Dwm3x1b\nlrIA+pSuL2JiF8yIqPn6ciTlHMRxlCnqR1MWIWvZh3IfOQ/4DmXmU9deO/L40Cked+2XwL9Smo/U\nun8bfR67qsvkBIaRoFwD/DR7mIbZ6KvbxfGUX+p1I+KrlINWNZwTZR5IzSF9E10TEdtSOt18GHhI\njaAR8cXM3HKkyxDUabE8+rN9ZeXkhMz8HEBEzKEcbGtXmmqchZidmb9oVnlWysyfNddS+/e9r4YY\nfbcTfyJlZW10Dsu2lcKfRunwMtpiuZqRzk6zKCvbNSfZ99WUAUoXqW8x/n2vaYvMfE37RkS8k7pD\neKvKzI82f07VNa/KYNQYn/EFZad+3RpxG6tlZvtv/POI2LJibCgLnudExLzMPLopqe5U0322FxGx\nKmU3+Mk0Zzwj4tvA2ysk5StFxKMoC+yzm8ezoJtZckNIUJYHLoyIixkfmtdHR6WqMvPg5ofqccCl\nWfpp1zBVO9+as0DeSinxOply0KpKbXZmbtn8uUiXn4joukZ7tYjYgvJL/aAYGaKXmZ1P3B1xKiU5\nWZuysn0t3Seq7WDAF9HcIEbEstSfKt5XQ4y+S16OBg6mn5vVZTJz6x7itkY7O/09KwzIbE1sykDF\nHRRKZ77dK8YjIv6Dsmr+vIhoX0eWAR7P/ThBaUXE+yjnQBaZK5aZH6l0CaOv63+nnIOp5QERsUbT\n3vihdHymcxK3RcSmwLLNIe7aDQpq+yTwpfZ+BiAi3kTZnd+m49i3MF4qe+vI407uH4eQoHy4dsBY\ntE/+2qNv1+hVHxEvyMxvUWriVwdeFBHvy8zOWwP2VM428RruokySBzioOUj7+q7jRsS6lCfu+cBH\nM/OWiHgxZfLuIzsMfT7jbYwvYDwhGwNqJiirZ+bGEXE45RDnNyvE/FZE/IiSkL68aUpwMOUcWDWZ\n+ZfmOm4ALqpYIz2x5KV2O/HfZ+bhlWO2fhERzwB+zvjiU80pz8tSuhstC8yK0u75rTUCR8RBmfkO\n4KfNTdNB1Bvcd3GzS3gB49/3rruInQlcRykhbm+W76LMYOlNxY5SW9HTXDFYZMZXHwMD9wDOjoi/\nUBaeapyFGLU9EJRSr72bP+/P1svMRYZwZubhEdH5wn7t+8chJCgXAf/ComUnXW+fja6gHz/yducl\nCBGxO2XX5FuUFdU9gedQfsk77/wxobypVXuS/ES1+mCeQFlRXhf4YETcDryKsovTmam2/3vQvniu\nlJm3RoVhXpn50Yj4CvDnpovX+sBnMvPUrmOPiohDKDdP5wBvahYJ/l/XcbO0E9+K8ju2MeUmrqbf\nNmUmozertZLizYCXjbxdo/3nqOMpu4abUHYLH1gx9l8i4iNNzMdRzl7V8sTmv1bnu+PNGbvvRsT3\nKDepd1EaJFzcZdyluK5aN1S9zBWLAQwMbNrtrhcRq2e99u2j9gC+VC4lX91D/IWa6ojbM/O7HYaZ\napHnfjeccwgJyqmUQYWPp2xNdr4CkU2f/J68gPFhOrdm5tebUoAqnVYmljfNMHe1O2QRcQXlDNAT\nmxasM8GXIuK/KSWV5wJVerZn5v+NPL6cflZVN8rMtsXsARFx9mI/eppExCcpz2/rUmqG/0DdWSTL\nUxYA2kWAart2mdlJ68l/wF8z88MR8ajM3DYiflArcGbuFhEfAx6Zmc+tFbeJ3ecu+QmU7njPopR4\nvYqSqFQREY+gtHJfWLabmTUaBIzOFatZqt7bwMCIODgzdxg567WwzXFm1uqGCnAM8Apgz4i4DDgl\nx+eD1PYk4JcRsU52N1tsxdGzHyNW6iheb4aQoMzKzHkRcSSl40e1F5G+5PjMlwPatyOiRivChZrv\n98Tr6vTw7OjZixGzgAd1GXfEHSOPbwTeULH7Re8y85D2cUT8L6Wb1kxxVfui0dRJ1zqT8bTM3Knt\nFticO+tcRMzJzAWU815VTXbj0qp84zIWpZX4yhGxEhV2UCZpwPHQ9n1d71BP0QQEgIq742tl5rER\nsV3z816zMQGUBOlMSkvvmvqaK9bnwMC9mz+3WuxHdSwzz24SkwspVSifAqonKBGxTNs0oWOjZz8m\nvr+KKHOWPpeZ13cZZwgJyoKmHeNKlCfVIVxTl5aLiOUy8/bM/DJAlDa7tb/u9gxA2ze9xgvYVIfh\nz6kQGxZ90f5zH8lJlJ7xbfnDGU1pRNcxj2Lq7d9aHZ16MXKztgLwbxFxFWUmSa1ShNkR8RRKqdVy\n1GsOcAzl3FMyoWMd3ZdZDeLGBfgA5ffs85ThqJ2XvPS5Qz1yaPZ1mXlWT5exXJR5R5dExOrUb4Zx\nS08VEudTDsmvRdlB+kWluL0NDBxpOjGb0k7+0ZSSvl27jj0qIi6kNKE4DnhzluHAtWK/rom9PPCx\niNg3Mz/eZcwhnCOmVF+cGhG/p8wVO7OL+6khJAOHUAbnfYOyqvnDWoGbVbVVKCvrbwGOycwrF/9Z\n99pxlOE678jM+VEGiH2SUi9dTWZ+feTNMyOi87KPAZzF2CQirqXcqK068rjK+ZsoU537KH84sflz\ne+Bs4EeUdsNPrxC7VwMoaTyGsqK3LWUK71Rd9KbVSHnJazNz4RDYKMPjuo79h+bPRZ5Lm92j50/6\nSdOsWQg4LzO/37yryopqRJzA1ENRa3Wn3IsyALkP+1IS03dTBsntvfgPnx4x3mb3D81h4Z9Rr0EA\nlFkgX6Ocu2pv2jarEHcIAwOPoPy7n005V3skdWaRtD5M6RL5EkrTo69PuL/p0o6U82UnUhrBfIPS\nFOV+LTMPBQ6NiMcCuwGHNVU5B0znomvvCUpmntI+joiTM/MvFcN/kTJY59WUDjufoRzY70xmHhJl\nBsT3I2IV4GbgkJwwaKlrE8qt1gQeWjN+HzKz6kDISfRS/tA+WUfEzpm5b/PuH0VEjS5egxARz6R0\nzVvYjCMzO/1dB8jMT1ESFICduo7XiohNgMcC74qI/Zt3LwPsQDm03YcqpZwRsQOlW9+CiNih4s0K\n1B3UNpWxiDiVsnt2F5Tp8l0GHCkpPKP5D+p2Uxp9/Xwz493yarXPXy0zj4yIrZuSo1qT3IcwMPDO\nHJ/tdXpEVHueA8jMEyPiFMq/83uBf6e00q+h3bW6Ocvw6d7vqWtoFta3orQ1vomSqM2m/O5P2yDi\n3r6Zk9QnjwF/jIgPja74dWxFysrajpm5TUS8oEbQzPw05XBbn0bLrf7O/bzUZyD6Ln94YJQZBT+l\n7OKssISPvz/5NGWVb0tK58AqyWpEbEN50RwdlFijk9VNwBqU0oN2F+kuKpdfTFCrpPI/KU0BHkQp\n66qWoGQzwC3KMLXa3SlbdztfWEGfJYWjbXZXADbIzAsi4pXA/3YduxURj2n+XAeoMpA1+x0Y2C5y\n/i0idqU0nXk6pRFIzes4HXg45fd8N+qVjANcBpxLWQjak3qlfX37KXAssFVmXtW+MyKeNJ1B+sz2\nJqtPXpuy2vi0StewHCXz+1lEbMj9sAvCVAZQbjUT7UtZ3dmZiuUPI7ZlvFb4l9TtJtW3GzLzhIh4\nYWbu1bRDreE9lAF2VQclNnXYF0fEWKUuRgvFonOmWu009xr+nmXeyg3NuZ8+VO9OOeI4SnOEDYFf\nUWExbKR8bY/MPLbreItxLCUpuYDyPPdaxmdQdWlH4ChgA0plxtsqxOxbu8h5I+Xr3qB5u/Yw2t0y\ns6/E4PPAOzPzrxFxXmbWbs6wUFNeeg3wsex+pt7pk531yszdpjNIbwnKFGc9rmzKn2rZGXgl8D/A\n1pQnmfu15vt7I4v20u51DkrUG6bVq8z8UkRcDDyBUk5Y9WvNzEtZdC7FTHJXUy+7YpRemKtWivub\nzLysUqzJPDci/mekc2ANU537ObriNbQmtuKsFrfH7pSHUXbQvkk5B3E43U+Ybr2ZkiT0Ze3MPAog\nM644AlcAACAASURBVPdtXls6l5kXARtHP4MSe9H3ImeUUQGj7Y3voOxY3paZGyzmU6fTBzJzU4A+\nk5PGTpTmLzWe8zaIiIdk5k1dBhlMvVxT03Y+FZ/cmlrRFSmrLN+nrDbd3+1COdR1OXBcZvbe1rnv\nrhQR8R7KL/XHmzrqruLsQDkUvyrlZu1RlDMBVUTE+yklPrfQ/3DO2t5NOZNxIKUhxRGV4t4SEV9j\n0WnqnZ4HmGAucO3Ii/lY161+e+qiNGqyg8NA1YPqfXanfFR70wR8OSrN/GksHxEXMF7qNVbxew7l\n/M2jM/NXUYbCzu4yWAxgUGLfRjolzqK8tv2mUoLwmCbmIcBhmfmTpsSo5u5V9fNerYh4AGWnNCgV\nEYdVXIjaEPhTRFzP+O/5tN9LDCZBycybImKjzLy5VsyI+BCl5egGlG3J9zF1K9yur6XK9lxm7g/s\n39TLvi4i9qJ03zg2M7OruKOiDAscdQelBOakzLxjkk/p2s8pyfEqlCFXXdmK0uXk25l5QETUOmvV\n+nfK4fCa5SZD8efM/ELz+ClRprvX8NUJb9dubf3SyvGGYKqDwzUdQlnRrN6dElghIlbMzFuam5hO\nb9IneE/FWJN5F3BSlPk3vwPmdRyvt0GJQzHaKTEi1qV0kasR97Ym5vqZ+ZPmfRc0O+S19HHeq3UC\nJTE6k3Iw/ShKJVDnMnPdGnEGk6AA1ExOGptk5qZRhqh9LiK2rxx/VM3tubbcZ4/mQN9+lCFHtQ5N\nb0QZKvQD4JmU9nzXUQ6Vvr7GBTRtSNuv94LseOBQYxma1Ybm7dplAFdQcZjTwJwcES+lHF79NCUZ\nPXHxnzItvkxpubnikj6wI8sCr2HRw9rVhzfW1PPB4Sdk5i967k55AHBhU066IZVuGBtXMmGSO/Wa\nA5CZP6YkCbX0OShxcDLzyrZZQEU3RcTewE8ozV+uqxj7OOANlEP6Z1HmwNSyWma2CwKnRUS1apha\nXTEHlaD0YE6zDT8WEbMpA3c6FRFPzczzYpKp6pnZ+SyS5hpWpawytiuNJ1FmZNTykMx8dfP4sIj4\nRma+PiKqrDJGxDHAJpQ67bbTzJMrhD6eUkq4bkR8lXLzWtNywEURcVHzdu3yiz7tCJwGPBj4RGbW\nWvk6Ffgt451t/n975x1maVWl+18RBGlRBFFARSX4ShwDIF7oEVAUUXCcISpDDs61DQiPIEEBAeUa\nuCgoSQZGMihRYJSsmEiCgLwKSBJaQbjkFpGaP9Y+XaeLbpur9e19qLN+z1NPfeerOrV2dX/1fXvt\nvdb71t5BObmMYW3gPiq4qc8JSa8k5Dgnc5J8mKSliUn5RcAPuq7THo/tk0pZ4TLA72z/qWL4Jk7u\nks60vUlfuRHUKWNtZpQ4KGhW758lqaziBXyE2Cn7AGEXsV/F2EcS99X1CWWr/yL8WGpws6S1bF8l\naRWih3t+ov/t6bm9+R+kiirmsCcohxKGTosDPy+vu+ZdwDU8t5RslCgH6JQyMX41cAbR0FhVXaiw\niKRX2H5Q0mLAy8ofVq1VZlWSep0F24crzOpWBm4tjZU1OaRyvOaMWwi4hHiQ3FvUvGosCIzYbinh\n/bjtL0pa3vb2NVfZZsNhwO2SjrR9b8NxdEbxN1oAeAewDrBT8cS4oms1NUn72D5w3IQRSTV7b5o4\nudvepHyubcw6CEaJrekvo5xBTNQ7R9JbbF9v+wmiCqR3/oPEYlQNlrW9o6Spts+TtGeluABTgfdK\n6okDQPRR15D2rqKKOXAJSk1FJ9tnKMzyliMauzpfabLdmyTu2/+QrlgTvyJxAe/AmPdJNb36wueB\nn0t6lFjR/TihqFarcfkXklSr56aHpDWIPpQFgXXLxKHzhj5JH7B9PtFUOH4Fv1k5TCXGLwSYMYnz\nzhKUPnnbOyS9g+hx6jXJd7261c9oqcdfWNIUGu6g2G7S31cbh2HbtURfwsLE7uybK4Q+r3yu3nej\nWZ3ct2TW672a+IzCy2w+YgfjG8Rz9uS//a5/iEEwSmyCwpRwY+Bh25eVc68idtE2rzCEr1JMOCX9\n0HbPvb63W16D+RSeZqOSFmbWHbVOsb1SrVizoYoq5sAlKDUVnSRtRNTRLVheY7vW9lyTmnjbr+8d\nS5pi+wlJS9m+r+vYfWM4v+zkLA780fYoURZQi0eAq0udcE01qxOIXYyHK8TqZ7HyeYnKcZvTk8Is\nD5G32P5hUVPrWi2wp2I0wqxO1jUXAgD2J5TjvgPcQcXG3XEJOUCVhLwlknYjSjwWAS4mnJX3rCT+\nsRFwg+0rJC1pu2Ytfr+Te78PTi0n9x4HEb4nRxCNw6cTZY6d0LLfaQA4iZi/LFkmq78jFhkPqxS/\nv193vjmc75p9gKuI0rafEb3EVZC0C9FP2H9/rbVzN14Vs5OS6eYJSsk69yCaN88HbnQ934CvEP/B\ntSeM0K4mHgCF6+kCwF5E3fQ1fbs7XcU83PY0ST/luSUInUqfjmM9YNEuJYXnwG9tH185JsBPywrn\nKeX1KPBA7dr4xpzC2IPzISJB6UzhyvYb+l+X/os/VZSB7I3jSqLvCeDcmrFpl5C3ZF9iseWLRFlX\nTVXC9QjJW4jJY7XEoJS2zdu7vstz/akG99gniR6IZ2xPl1S752uYWNb2amW3+FpC9GVd27+uFH/0\neRx3SklQJWlxouyp5vX2SWIxpNr9ta8y4LflA6KctROaJyhE5nUhYSg1ncjA31kp9s22L68UCxiI\nmvgeG9t+G4DtTSVdRfc9Cj3n9FrlbHPiN8CrqGyUCHxX0qlEIx8AXdelF/pXN3ur+osXdaHWnhW1\nmFLK3LB9sqSdagSVtA5xj3sEeLmknXqqPx3HnWliNp6K/VetEvKWLE7Uhm8IHFyati8ELrB9d8ex\nR+Zw3DmSViY8V1a3/TDRa/lVSRvZvmUub59IHiUSxKMlfQzo2lF7mHkUomS19Fm9x/ZDFePPU3pX\n5xl/3HXg0orwnPtrWWyttTBwI3BP5UWv/sqAfjqpDBiEBGUx28dJ2sphnFhT/eKcspo/M+Ov0NA6\nu5r4LanUJN/Hs5JeVG4uvT/sTrHdU/d4GWFg9ixwcPm4q+v4fawN3CnpwfK6VonXx4DvEuph1Zhd\n2WT5O/sZUQI0DDwtaX3id16DCop9hQMJOfP7JL0a+B7h8N015wGrlVgnAl1PjmdHq4S8GWXH5NLy\ngaQNiF3qI+jej6TJKnLhMGCLkpxg+2xJfyRKQN5dcRybESv7t5Sk6ZiKsWdSFiKfrr0A2pA/VE5O\nAF5HzJ8gJsxmrJ+2a3r+Op8n1DivIp4rNX2nLiV6HG9nrFS90+RofGVA1wxCgoKKbrbCk6PmlvAn\nCKm0ahPGXk38eCTVVh85ErhJITn7JuLfoWbsacTkeO8S+5JawW0vVyvWOP7UdRnd80Ehqb02lVdZ\nG7MjUdL5dWLCXMsL5K+9/i7bv5c0Y25vmAhsf6K3qkmUHfWM5E6nnv9Ok4S8JZJWI3ZQphL31RuI\nUrcaBmpvU7jGjwAr9h2PViihncf2Nf0nyoJjJ/Kjf4PXAh+UtAltfX/eQsjAvmayKtYxewUzgCqq\ncbUny+NiG0IUwGMGwGdJ+njFYexCJOTV7q/jy/P76eIeMwgJyicIB8wVgDOBmk2U022fVjHeTCQd\nQHiPvIiQ1/0N0XRUBdvflnQusS13u+0H5/aeCWQGcDPwIts/k1S1Ll/SfzLuj6ySFOyDko5iVoWb\noyvEHc+ChHJazZtpU0pf2780CP1oeWhdCfwz0f9SBdvPEuUuFym8j75FJGi15LwHIiGvzJeInfAD\nCQPYmjsZq1aMNZ457Q7NP4fzXTEQvj9Dct3PScFsqJC0A2MmkTUVGu8Fri73+VpULc8fhARlA9ud\nNdnMhackXUTIGvcmjHtVir0x8BrCe+VrwDdrBJU022b8UjtZy69hlDA0ukDSZkDNRlIYU0sbISRA\na5R3AfTEH3pqWk0aOItu/CYtYrdCYwZuI8Ruwh22V6gQeitC6eUgYuemmidK2UFZnyghfTPRC7FG\nrfgMTkJeDds1y5nGx65ZJjueCyV9BfiC7UckvYQwzLu08jia+P6U8tFPE8IzADV7EZow5ApmPT5C\nVIFsRiy6fqRi7AWAGyTdxNj9teudq/VtHyvpizx3/jLhc+dBSFA2lHRobXWbwnlz/5bOuL/o5S9s\n+7aKW+GrESuoJwK9EoDabE5MlHriCFWzctv/3ffyIklVen9s719K+eZnrPwgqYD7DNwkvY6O3Yb7\nfCEg6uCrKqdJ+iaxY3M5cLTtn9SIO46BSMiTKnwJ+AxwnaQXE8pCJxBllTVp5ftzKCEx28L4OGlE\nUYr7AmNSv1OAzv30Cl+sFKef3vV9a41gg5CgLA7c16c6U6NetsdJwOq0mTDeK2l74ImSjS5SI6jt\nVUvz4FbAnkTpyYkVpZ0hMv87geWBfycMtaqVvoxTUluSUPSqEffbhCTfFODFhC/FmjViJ2PYvqvX\n99YhrZXTPko8KP8N+Lcit1rT8ycT8iGilLIdQvdKkHNjf6KUs7bvz922L64UK2GWXXGYdaG12j2u\nLAS9D7ifsQb9WvPX11WK089Tkv6Z8LzpnEFIUGqqHoznLOLh+WqihvY+xrwiumYXoqHvDGBbnqvu\n1Rm2byKSE8rF9kVJr7Vda7J8MrGC/TGi7+hQoJpBJ7P+W8+gXtnNPxF9RkcR26FnVoo79Eg6hbGH\n2VKEV0JntFZOs11TDXG2ZEKe1KLXjD7e90dSLcuCP0o6klnLxSd1OWNr+nfFG7IGoRpXsw+kR69E\neYQo4X2IKJ3vkv/oO16XKOHsJWZXzvYd/wCDkKD8lZigrkg0iu9aMfYrbL9D0rFEw3ANf4J5iWTo\nVKLUaQQ4Fvg+FY21ipHWvxKT9Sl076zdz7PExby37VNreVL08ZDt3SrHhGgaHpU0xfaDkhoMYWjp\nb+KcAVwzp2/sgiFVTsuEPKnFBZLW6xd7kbQ3sRC4dIX4vRXlJf7mdyUTjsLF/kjg5cQ85qae51UF\nbiPKu56sFG8mtj/bO5Y0Qhiddx1z5uKupMu67nkZhATlGEJd5kpgHcKo8V2VYvcuqim2n6rkOrs9\n8bBegjHd7r8CP64Qm9KUvgWxPfhd4KO276wRu4/5CWnhKyWtSyiZ1WRFSYvU6gfo41pJuxMljacS\nq8pJh0jaek5fovvVpn6GTjmNTMiTehxANOq/i3i+nETIab+1RvBSzvh+IiG37XNqxE2AUCbcjphL\nfpvoba2VoCwN3CWpVyJfrUVhXN/ykkBt2eXO58uDkKAsaPvccny2pE9XjP09SZ8jlBB+BjzedUDb\nxwDHSNre9mwVtTrmVKLB6QZgFcLtuDe2zrXLC9sR6kLHEvXC21SK22NF4E/FqPFZKtWs2t6rqNvM\nIOpWf9F1zIR+pa4tifLCWmZeMxlG5TSem5DXkjdOBoRSWnkv8GXbnbm62z6zGA7/kFhJP8z2EV3F\nG0/pI12eWGjcRtJU27vXij/sFKGhUdsPSHqsYuhqpfmzod/V/Sngyw3H0gmDkKDMJ2kV27+StAoV\nJw79NzBJ32dMdaYGV0r6LH0NpLZrGErV7PWYE3cQeuH7EDWMj9YMbrtqc9lsJPlGgT8S7rNJh4zb\nBl+zooz4QCJpD+J+8xXbnZriziYh/3mX8ZKB5FPAg1QobbR9Siml3In6DvL/bHstAEmHEb1mSR0e\nkrQLMEXSFtQ1hp0f2JRZhUBqGYPua7tmaf74ucyykg7ufa2LZ+sgJCifAI6TtBTwe2DnrgOOa5iF\nsQnj4cDtXccvNDGUGhDt8qOI33l94Gqi1GbDWsFLInwc4UMzHdje9vUdhpydJN9ShKt3M9+EISRl\nbuGXhC/Jy4EHugxUXNW3ZWzn5ENU9IFJ6lMShG2JEuJLiX6Azi0E+p7pI8CywI97ZTeVKgPmlzRP\naZauvkM75OxAlM0/SNgo7FAxdktj0J2o2zsMs85lPtd1sOYJSpkYrl457OxcT5ciJsprVRpDE0Op\nAWFZ2ztKWtv2eZL2rBz/68COtm+Q9GbgCDr8f7d9wuzOl5rlJOmMUmJ1gu0H4DkeQF3zLWLRZ3rF\nmElbWi0+HTmH41qcBlxVSsXfzpgZcNIxth8tu1a9XQwBP60UvuU8bgFJ1xOlXs9C98n4nOYyXdE8\nQZF0ELGqNnPFoet+gDntIkia1mXccbQylBoE5pP0CpipJlZbom/E9g0Atn8pqdNSl/GU3/kbhJlZ\n0iHjVlZXknRy72sVe65a8jhwlqTpRAPpRcWzogaP1n6gJc1psvjUujLA9lcl/TfwJuBY2ze3HM8w\nIek4Qr68hZx5y3ncHhVjNaF5ggK8H3i97T+3GoCklwLnEploLfYnSh5qG0oNAnsT/RdLErW6n6wc\n/6+SPgD8iHDbrn3tPUFIrlZxsB9yWq+sNsX2kcCRRYpzb+Co8kA/zHYnCXKfEeojkvYCrmXMGyKv\n+clN68WnJkhalZgg3wt8XdLBti9pPKxhYVXayZlXn8dJOs325q2T8hoMQoJyPSHB2SxBAR4DphUD\nw84pCdE1xVQKIjkaGsrvLUmLE3Wjy1YewvbAV4AvAbcAO9YMXuqUa8kgDjXDcBP/W0hahJAV35po\nHv0k4cN0Pt2VNfaUbR4hlI2WL69HyaR8srMPsy4+fartcKpxJDCNmLDuTcjoZ4JSh2Zy5j1j0HKf\nXd52DcGfxSvE+P+iJOiP275jIn/uICQoNwH3lxKEEULydZmaAyglD7WSk2nAbsAzkqZVrgkfKHp1\n8aXsZo2Kode3vWnvhaRPEH0pSTLZuJpopNzC9t29k5Le0lVA29vN7rykQXB+TjqkLAjMXHyqWE7Y\nmhnAzcCLbP9MUufCAMlMqvuLSXorUTK7BrARkaA+LGl32+d1HH4W9ax+GqpUbgfcJukc2/dO1A8d\nhARlc8JgprZpXis+TDRxvZTYDhzaBKWPKu7akrYENgbWlbReOT0P4QeTCUoyGXkjsBywsqRngd/b\nHrW9d9eBJR0A/AdhxLoQ8BuiFCOZZEg63PY0ST+lr59UErWM6xozSggCXFDMkP/SeDyTHkmb2j6D\nKO16iPACqeUv9mVgG9t/kXQgsAFhU3Eh0HWC8iR12xHmiu1du/i5g5Cg3AU80bIHpTIzbD8NPDjO\nCXSYqbXKdhFwP7AYcVODqJGuJS09C5IOJZqYD7HduUloMpR8jKiRXhQ4gUhWaomBbExIeR8KfA34\nZqW4SX2+UD5vTXhc9Vi0wVhasDmxmn4hsA5RVpl0y36SbiF2Mv6dWOg08DLgDx3Hntf2jcUeY4rt\n6wDKIlDXTG8tPlLUT3cm2jMAsD3hEvKDkKC8FrhdUq92bbTVikst19s+quwcDAqz8Z+B+DeoUtJX\nmoIvBy6X9ErG/rha/R0cD/y2Yfxk8rMFIQRxie3/K+nqirHvt/1nSQsXp+dckJm8jEh6I7GL0Jss\nzkMsBNUs323F2bbXLseXNR3J8PAtovJBwNF950eB9Wb7jomjt0O2AXAxgKT5gYU7jgshOtKa4wkJ\n+Xu6DDIIE6PNWw+gjxqutz2p02GUPZ2TilJVdSVJRxDqcfcxZqrVeVIs6XBCgvKXAD2p4yTpkHmI\n67u3MFBzp/peSdsDTxQH4kUqxk7qsiYhwCAiKRkhdqeHpYT5IUmfZFZPihSE6BDbhwOHS9rJ9jGV\nw18s6SpigX1jScsSE/bTug5se/euYzwPpts+tusgzRKU8sCaU2lPlUYfSQsQbpwimuSPreB6u1nf\n8VDJng6QotLbgWWKmlZNzgf2kvRqonH5pEqqH8nwcjJwJfA6SRcAZ1eM/Rmi1+4Mwl18si/ADC22\nzwbOlrSh7Qtaj6cBfwLeXD4gFetqcpOkoxgzalzK9nu7DGj7EEnnAo/Yvq8kKEfbPqvLuAPEncXj\n6Ho6lJBvuYNya8PYPU4gemAuBqYCxwHbdBlwgCbpw8xtRHnXkzWD2r4IuKgo3BwGfFnSmcAXbDfp\ng0kmN7YPl3QJsHK89I0Vw5/XV/byjYpxk3Y8LWkDYufuG8C+tk+ey3te8IxXrkvFuqp8k5B13gT4\nFSHK0Tm2f913fDuNelkbsQCxsN/TdO4kIW+ZoNxs+5o+U68WLGG718x2jqRMHoaDpYG7JN1WXlfp\ne5K0ArGSvBFRpzyV+Bs8HXhb1/GT4WEOO9RvkbRFRSnKLHsZPg4idsqOIHx2Tid28SY1qVjXlAdt\nnyLpPbb3y3lc99jeTtLKwIrAb3pl6xNNywRlPeAaxky9enS+NdrXrPk7SavbvroYzfymy7jJwDD+\nmqvF0cCxwP62Z+7eFGfvJJlIBmGHOsteho8nCQWlZ2xPlzQsPiipWNeOZyWtBCykcGkcFuW4Zkj6\nOLEQ8XNgd0mn2/7KRMdplqDY/j/l83alJn9eYiW7U1WAXnjiYTkCrCPpaWLlY0aF2El75gc2pa9m\nFdilQtx7ZycPaPuICrGT4eL+1gMo9/aliOdMrXt70pbHCDn3oyV9DKihhjkIpGJdOz5N7FZ9ndit\n+3bb4QwFHwam2n6mqJf9BJg8CYqkFYHDba8HXEIY7bxG0qdsf6/L2Lbf0DeOEWAx2w92GTMZKE4G\nzgLWJpS8XlIp7vx9O3W9kpen//ZbkuTvYk67hDV2qPvv7ZdS8d6eNGdTYFnbt5QSkNrqSq1IxbpG\n2L4ZuLm8fJuk97Ucz5AwYvsZgGJW2YkxacsSr0MIlReI1Yd1JS1HlMBUeYiVC/lw4BFJLwF2tn15\njdhJUx63/UVJy9veXtKPKsUVcA5ju3ejVPKASYaL8U27PSo17za/tyd1kbRjkR3dDxiNSpuZ1Op5\naskuhORsKtZVQtK2wMGEg/wmwB1EQrwCYZiZdMdVReDnR8RC71VdBGmZoCxk+5py/AhA2RqtOab9\ngDVtPyBpCUKCc82K8ZM2jJb/74UlTaHeDsohtk+sFCtJWjXvDsK9PalLr3zvt0DXUv0DhaSdgeNs\n3yVpKvAX27e0HtcQ0CvtWhL4KlGqfQ7wkZaDGgZs7ybp/UQyeLzt73cRp+UD48W9A9v/0ne+k62i\nOfCY7QfKGKZLeqJi7KQd+wMfAr5DrLp8p1LcnQj/kySpRYvm3UG4tycVsd0zZNzCdktlzqpI2o+Q\n8D4ReIZI1HaVtLjtL7Qc2xDwkO2HgYdLWelHbefOSYdImpfoFz+VMFn/ITCvpEtLSe+E0jJB+b2k\nNWz/ondC0hrA9K4DSzq4HM4n6Xzgx8Aa1HVZThph+0rgSkmLAMtXNEtcQNL1zCq7mqUASZe0aN5t\ndm9PmvOwpI2Ztc9uMqtjvo+owuiZ1d0paXOiaTgTlG7pN1q+K5OTKmxPlGwuQcxjRogd0x93Eaxl\ngvIZ4NxiInYbUYv/LsIjoms87jPE1mAyiZH0VkLhYw3iOjuSeKDubvu8CkPYo0KMJOmnRfNuy3t7\n0pZXArv2vR4lLAUmK4/3kpMepWn4sVYDGiIWk7Q+YQr60n5PvfRb6gbbxwDHSNreduf2CC1lhn9X\nVtU2At5AeKLsa7vzMque1Gupid6WMO67FLip69hJU74MbFMeIAcCGxATqAuBGgnKdUSSshRwPlDT\n1TsZTqo377a8tydtsb1u6zFU5ilJy9i+o3dC0jI81yQ1mXiuY+x+dj1jyoXpt9Q9P5T0GWDB3gnb\nB0x0kKZNi7afIpxmW3EkITO7PnA18F/Ahg3Hk3TLvLZvLN4MU2xfByDp2bm8b6I4jkiG3kmUu3y7\nHCfJhCJp69mcfgRYDei8gXcA7u1JAyR9DphG9GMAYHupdiPqnD2As8tu4R3EYud7gW2ajmoImJNS\nYVKFM4CLGRPH6IRhV1VZ1vaOkqbaPk/Snq0HlHRKr0l3A+KPi2IytHCl+IvZPk7SVrZ/ImmeSnGT\n4eNY4C5iZ3AGUSucJF2zEfC6kqBOemzfXJS7PkjsjF8HHGA7S7ySycxjtvfpOsiwJyjzSXoFITu7\nMLM2XSWTj4slXUWUvGwsaVnCB+e0WgOQ9Kby+TX0rTImyQTzamAL4APA3cBJ6fGUVOCPDJlam+1H\niOqLJBkWbpK0BVFa1xOImHAxjJHR0eEtlZT0TuBoQkf7HuCTti9uO6qkSyStADxi+76SoKxq+6xK\nsVchrrcVgFuB/90rM0uSrijX+UcIQ61rbX+28ZCSSYakU4iJyhuBBRjr5xxNpcIkmVxIumzcqdEu\nZIaHMkGRtKrtG/teLw48OF6NI0kmCkkvBZ6x/WTrsSTDhaTXEw2kHwTusb1p2xElk42y2DdbbF9R\ncyzJcFMmz9cDX7X9+9bjSf5+hjVBuYxoZrsCuAj4ge3/13ZUyWRF0jRgN6Kka1qfqVmSdIKkJYDN\nyscTwCnA9yp6/iRDRp+j+jOlL2Ml20e2HleSJBODpDNtbyLpfsaU6kaIHZQJF8MYygQFQNICwDuA\ndYC1CC3tK7qQSkuGG0k/Ia6zlwLfsf2+tiNKJjuSniF8nk4D/kCf7Knto1uNK5mcSPo8sAqwte0n\ny67d14Dr01E96ZKioLaN7XvL64tsb9B4WMkEMLRN8sVd+VpgUULF6a3Am9uOKpmkzLD9NPBgJSfv\nJOlNCkcI198k6ZINSUf1pA1LA9+VtJ3tW4geqKQD+nrNnkMXvWZDmaBI2o24oS5CyM2eD+xpe6jU\nR5ImpNxrUoPLgPts39Z6IMlQkI7qSSvuAbYHzpC0K6mO2SVVSzaH1YdhX+ABwmRpH9uXZXKSdMhK\nkk4uqw+945Mlndx6YMmkZX/gAEmLtR5IMhQ8VRzUZ5KO6kklRmzfSXjwfBlYvu1wJi9F8ELAVeX4\nWWCFroQwhnIHBVgcmErsohxcGn4uBC6wfXfTkSWTkc36jrNpNOkc2+sCSHqdpJWAu8tDPEm6IB3V\nk1YcBmB7uqQNgIMaj2fS0tdrdiKxU3UPsKukxbvoNRvaJvl+ykW9F7CW7XlbjydJkuQfQdIUuI3f\nlgAABLhJREFU4FRgMeBOYDli13jLVPJKukDSyxhzVL8LOD8d1ZOukbT1+HO20zizAyT9nL5es3Ju\nfuAntlef6HhDuYMiaTViB2Uq8CbgBuAEYKuW40qSJJkgDgHO6H9QS9qRKIHYpdmokklLOqonjVih\nfB4hhI4eIq/DrqjaazaUCQrwJeAHwIGEDGJuIyVJMpn4J9vT+k/YPlbSDq0GlCRJMtHY/mzvWNII\nIXqUdMNTkpaxfUfvRJe9ZkOZoNh+d+sxJEmSdMicRD9S4SZJkknDOOn+JYE3tBrLEFC112xYVbyS\nJEkmMw+VUtaZlNcPNRpPkiRJFxi4tXy+kChjTTrA9s1Ea8T1wBTgOqJ3+/ou4mWTfJIkySSjOHmf\nC1wO3E6sKr4b2Mj279qNLEmSZOKQtJXtE1uPI5l4cgclSZJkklEkhdcArgBeBPwCeHsmJ0mSTDJ2\naj2ApBtyByVJkiRJkiR5wSHpZ8ACRInXKDBq+8NtR5VMBEPZJJ8kSZIkSZK84Nmj9QCSbsgSryRJ\nkiRJkuQFhaSdgatsXwE8C6xQjpNJQCYoSZIkSZIkyQsGSfsB7yF67ADuAd4jad9mg0omlExQkiRJ\nkiRJkhcS7wM2tf0kzBQG2RzYuOWgkokjE5QkSZIkSZLkhcTjtmdRebL9F+CxRuNJJphMUJIkSZIk\nSZIXEk9JWqb/RHmd0rSThFTxSpIkSZIkSV5I7AGcLekS4A5gaeC9wDZNR5VMGOmDkiRJkiRJkryg\nkPQy4IPAUsBdwPm2s8RrkpAJSpIkSZIkSZIkA0P2oCRJkiRJkiRJMjBkgpIkSZIkSZIkycCQCUqS\nJEnSGZLulPT61uNIkiRJXjhkgpIkSZIkSZIkycCQMsNJkiQJAJJGgC8BHwKeAY4CfgkcBCwEvBz4\njO0zJB0PPAK8DXgNsL/t/5S0KHAi8FrgFmDBucRcB9gLeBJYAfgV8GFCmedsQkJ0FeAa4HJg2zKO\nD9n+9YT84kmSJMlAkTsoSZIkSY9NgLWIhGANYDtgX2BH228FdgA+1/f9rwWmAhsBXynnDgCus70K\ncATwqucR938B04gEpednALAq8AVAwOrA622/AzgF2Pnv+xWTJEmSQSd3UJIkSZIe7wROt/1n4M/A\nmyUtCHxA0qbAmsBL+r7/B7ZHJd0ELFrOrQNsCWD7Skl3PI+4N9m+F0DSr/t+1nTb15fz9wKXlPN3\nAW/4O3/HJEmSZMDJHZQkSZKkx1/6X5Tm9h8RuynXEqVeI33fMgPAdr+h1iizPlueeR5xZ4x7fy/G\n0+O+7/n8rCRJkuQFTiYoSZIkSY8rgX+VNL+khYAfACsDn7N9AfAeYN65/IyLga0AJK0OLNfheJMk\nSZJJSJZ4JUmSJADYPkvSasB1xALWoUSCcbOkR4GfAgtJmvI3fszngeMl3QzcSjS5J0mSJMnzZmR0\ndHTu35UkSZIkSZIkSVKB3EFJkiRJOkXSVOAbc/jyhrbvqzmeJEmSZLDJHZQkSZIkSZIkSQaGbJJP\nkiRJkiRJkmRgyAQlSZIkSZIkSZKBIROUJEmSJEmSJEkGhkxQkiRJkiRJkiQZGDJBSZIkSZIkSZJk\nYMgEJUmSJEmSJEmSgeF/ANDC1KSOcVvfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f87f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cand_amount.plot(kind='bar',figsize=(14,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b626a0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAskAAAGnCAYAAABFI8paAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm4XFWVsPE3JJAIBowQBdR2djWiaIviwChCK7ZT2w44\ntAOCQKOAw6co0DigICoKgqKBiIhTA+JAN44IImKDigqiywYVVECiBIgCYcr3xz7FrRxvppuzT6jy\n/T1Pnlv3pKpW1b11q9bZe+21py1ZsgRJkiRJE9Za0w9AkiRJursxSZYkSZJaTJIlSZKkFpNkSZIk\nqcUkWZIkSWoxSZYkSZJaZqzpBzCZBQsWrXJfujlz1mXhwptqPJy/i1jj+JyMNTpxjDVascbxOY1r\nrHF8TsYanTijEGvu3NnTlvV/YzOSPGPGdGONQBxjjVascXxOxhqdOMYanTjGGq1Y4/icasQamyRZ\nkiRJ6opJsiRJktRikixJkiS1mCRLkiRJLSbJkiRJUotJsiRJktRikixJkiS1mCRLkiRJLSbJkiRJ\nUotJsiRJktQyY00/AEmSJGll7Hb4WVO63fwDdlzl2ziSLEmSJLWYJEuSJEktJsmSJElSi0myJEmS\n1GKSLEmSJLWYJEuSJEktJsmSJElSi0myJEmS1LJSm4lExBOB92XmDhFxH2AeMAeYDrwiMy+PiD2A\nPYHbgUMz84yIuAdwMnAfYBHwysxcUOOJSJIkSV1Z4UhyRLwFOB6Y1Rw6AvhMZm4HHAT8Y0RsDOwL\nbA08HTgsImYCewMXZ+a2wEnN9SVJkqS7tZUpt7gceP7Q91sD94+IbwEvA84GtgLOy8zFmXkDcBmw\nBbAN8LXmdmcCO3X0uCVJkqRqVlhukZmnRcSDhg49CFiYmTtFxH8CbwV+BdwwdJ1FwAbA+kPHB8dW\naM6cdZkxY/rKXHUpc+fOXuXbTNU4xhrH52Ss0YljrNGKNY7PaVxjjeNzMtboxOk7VpePYaVqklv+\nDHylufxV4D3AD4Hh6LOB64Ebh44Pjq3QwoU3rfKDmjt3NgsWLFrl203FOMYax+dkrNGJY6zRijWO\nz2lcY43jczLW6MTpO9byLOsxLC95nkp3i+8Bz2wubwf8HLgA2DYiZkXEBsBmwCXAeUPX3QU4dwrx\nJEmSpF5NJUl+E/CKiPg+8AzgvZl5DXA0JQk+CzgwM28BPgZsHhHfA14LvLObhy1JkiTVs1LlFpn5\nW+BJzeUrgJ0nuc48Smu44WM3AS9c7UcpSZIk9cjNRCRJkqQWk2RJkiSpxSRZkiRJajFJliRJklpM\nkiVJkqQWk2RJkiSpxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJajFJliRJklpMkiVJ\nkqQWk2RJkiSpZcaafgCSJEkaXbsdftaUbjf/gB07fiTdciRZkiRJajFJliRJklpMkiVJkqQWk2RJ\nkiSpxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpZaU2E4mIJwLvy8wdho69FHh9Zj65+X4PYE/g\nduDQzDwjIu4BnAzcB1gEvDIzF3T7FCRJkqRurXAkOSLeAhwPzBo69k/Aa4BpzfcbA/sCWwNPBw6L\niJnA3sDFmbktcBJwUNdPQJIkSerayowkXw48H/g0QERsCLwX2B+Y11xnK+C8zFwMLI6Iy4AtgG2A\nI5rrnAkc3N1DlyRJ0rJMZbvou/tW0X1aYZKcmadFxIMAImI6cALwRuDmoautD9ww9P0iYIPW8cGx\nFZozZ11mzJi+Mlddyty5s1f5NlM1jrHG8TkZa3TiGGu0Yo3jcxrXWOP4nIw1HvHv7rFWqiZ5yJbA\nw4GPUcovHhkRHwbOAoajzwauB24cOj44tkILF960ig+rPPkFCxat8u2mYhxjjeNzMtboxDHWaMUa\nx+c0rrHG8TkZq64+498dYi0veV6lJDkzLwA2B2hGlz+fmfs3NcnviYhZwExgM+AS4DzgmcAFwC7A\nuasST5IkSVoTOmkBl5nXAEdTkuCzgAMz8xbKiPPmEfE94LXAO7uIJ0mSJNW0UiPJmflb4EnLO5aZ\n85hYyDc4dhPwwtV9kJIkSVKf3ExEkiRJalnVhXuSJEmaItuyjQ5HkiVJkqQWk2RJkiSpxSRZkiRJ\najFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJajFJ\nliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJapmxph+AJEnSmrTb4Wet8m3mH7BjhUeiuxNHkiVJkqQW\nk2RJkiSpxSRZkiRJajFJliRJklpMkiVJkqSWlepuERFPBN6XmTtExGOBjwB3AIuBV2TmHyNiD2BP\n4Hbg0Mw8IyLuAZwM3AdYBLwyMxfUeCKSJElSV1Y4khwRbwGOB2Y1h44CXp+ZOwBfBN4aERsD+wJb\nA08HDouImcDewMWZuS1wEnBQ589AkiRJ6tjKjCRfDjwf+HTz/a6ZefXQ7W8BtgLOy8zFwOKIuAzY\nAtgGOKK57pnAwV09cEmSNL6m0rsY7F+s7qwwSc7M0yLiQUPfXw0QEU8BXgdsRxk9vmHoZouADYD1\nh44Pjq3QnDnrMmPG9JW56lLmzp29yreZqnGMNY7PyVijE8dYoxVrHJ/TuMYax+d0d3gM4/pzNdaE\nKe24FxEvBg4E/iUzF0TEjcBw9NnA9cDw8cGxFVq48KZVfkxz585mwYJFq3y7qRjHWOP4nIw1OnGM\nNVqxxvE5jWuscXxOK9LXY+jzuRqrXqzlJc+rnCRHxMspC/R2yMzrmsMXAO+JiFnATGAz4BLgPOCZ\nzf/vApy7qvEkSZKkvq1SkhwR04GjgSuBL0YEwDmZeUhEHE1JgtcCDszMWyLiY8CnIuJ7wK3ASzt9\n9JIkqVdTqRW2TlijaKWS5Mz8LfCk5tt7L+M684B5rWM3AS9cjccnSZIk9c7NRCRJkqQWk2RJkiSp\nxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZ\nkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJajFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJ\najFJliRJklpMkiVJkqQWk2RJkiSpxSRZkiRJapmxMleKiCcC78vMHSLiYcCJwBLgEmCfzLwzIvYA\n9gRuBw7NzDMi4h7AycB9gEXAKzNzQYXnIUmSJHVmhSPJEfEW4HhgVnPoSOCgzNwWmAY8NyI2BvYF\ntgaeDhwWETOBvYGLm+ueBBzU/VOQJEmSurUy5RaXA88f+n5L4Jzm8pnATsBWwHmZuTgzbwAuA7YA\ntgG+1rquJEmSdLe2wnKLzDwtIh40dGhaZi5pLi8CNgDWB24Yus5kxwfHVmjOnHWZMWP6ylx1KXPn\nzl7l20zVOMYax+dkrNGJY6zRijWOz2lcY/X5nO4Oj2Ecf67GWjOxVqomueXOocuzgeuBG5vLyzs+\nOLZCCxfetMoPau7c2SxYsGiVbzcV4xhrHJ+TsUYnjrFGK9Y4PqdRj7Xb4Wet8m3mH7BjZ/FXpK+f\na5+xxvE5/T3GWl7yPJXuFhdFxA7N5V2Ac4ELgG0jYlZEbABsRlnUdx7wzNZ1JUmSpLu1qSTJbwLe\nGRHnA+sAp2bmNcDRlCT4LODAzLwF+BiweUR8D3gt8M5uHrYkSZJUz0qVW2Tmb4EnNZd/BWw/yXXm\nAfNax24CXrjaj1KSJEnqkZuJSJIkSS0myZIkSVKLSbIkSZLUYpIsSZIktZgkS5IkSS0myZIkSVKL\nSbIkSZLUYpIsSZIktZgkS5IkSS0myZIkSVKLSbIkSZLUYpIsSZIktZgkS5IkSS0myZIkSVKLSbIk\nSZLUYpIsSZIktZgkS5IkSS0myZIkSVKLSbIkSZLUYpIsSZIktZgkS5IkSS0myZIkSVKLSbIkSZLU\nMmMqN4qItYFPAQ8C7gD2AG4HTgSWAJcA+2TmnRGxB7Bn8/+HZuYZq/+wJUmSpHqmOpL8TGBGZj4F\neBfwHuBI4KDM3BaYBjw3IjYG9gW2Bp4OHBYRM1f/YUuSJEn1TDVJ/hUwIyLWAtYHbgO2BM5p/v9M\nYCdgK+C8zFycmTcAlwFbrN5DliRJkuqaUrkF8BdKqcUvgY2AZwHbZeaS5v8XARtQEugbhm43OL5c\nc+asy4wZ01f5Qc2dO3uVbzNV4xhrHJ+TsUYnjrFGK9Y4PqdxjrWm449jrHF8TsZa2lST5DcAX8/M\nt0XEA4CzgHWG/n82cD1wY3O5fXy5Fi68aZUf0Ny5s1mwYNEq324qxjHWOD4nY41OHGONVqxxfE7j\nHGtZ+ow/jrHG8Tn9PcZaXvI81XKLhUyMEF8HrA1cFBE7NMd2Ac4FLgC2jYhZEbEBsBllUZ8kSZJ0\ntzXVkeQPAfMj4lzKCPLbgR8C8yJiHeAXwKmZeUdEHE1JmNcCDszMWzp43JIkSVI1U0qSM/MvwIsm\n+a/tJ7nuPGDeVOJIkjSqdjv8rFW+zfwDdqzwSCRNhZuJSJIkSS0myZIkSVKLSbIkSZLUYpIsSZIk\ntZgkS5IkSS0myZIkSVKLSbIkSZLUYpIsSZIktZgkS5IkSS0myZIkSVKLSbIkSZLUYpIsSZIktZgk\nS5IkSS0z1vQDkCSpL7sdftaUbjf/gB07fiSS7u4cSZYkSZJaTJIlSZKkFpNkSZIkqcUkWZIkSWox\nSZYkSZJaTJIlSZKkFpNkSZIkqcUkWZIkSWoxSZYkSZJaprzjXkS8DXgOsA7wUeAc4ERgCXAJsE9m\n3hkRewB7ArcDh2bmGav7oCVJkqSapjSSHBE7AE8Btga2Bx4AHAkclJnbAtOA50bExsC+zfWeDhwW\nETM7eNySJElSNVMtt3g6cDFwOvBV4AxgS8poMsCZwE7AVsB5mbk4M28ALgO2WK1HLEmSJFU21XKL\njYAHAs8CHgx8BVgrM5c0/78I2ABYH7hh6HaD48s1Z866zJgxfZUf1Ny5s1f5NlM1jrHG8TkZa3Ti\nGGu0Yo3jc7o7PIZx/bmOY6xxfE7GWtpUk+Q/A7/MzFuBjIhbKCUXA7OB64Ebm8vt48u1cOFNq/yA\n5s6dzYIFi1b5dlMxjrHG8TkZa3TiGGu0Yo3jc1qRvh5Dn8/VWKMRx1h1Yy0veZ5qkvw9YL+IOBLY\nBFgP+HZE7JCZZwO7AN8BLgDeExGzgJnAZpRFfZIkAbDb4WdN6XbzD9ix40ciSROmlCRn5hkRsR0l\nCV4L2Af4DTAvItYBfgGcmpl3RMTRwLnN9Q7MzFu6eeiSJElSHVNuAZeZb5nk8PaTXG8eMG+qcSRJ\nkqS+uZmIJEmS1GKSLEmSJLWYJEuSJEktU65JliSNt6l0nbDjhKRx4UiyJEmS1GKSLEmSJLWYJEuS\nJEktJsmSJElSi0myJEmS1GKSLEmSJLWYJEuSJEktJsmSJElSi0myJEmS1GKSLEmSJLWYJEuSJEkt\nM9b0A5AkrbzdDj9rlW8z/4AdKzwSSRpvjiRLkiRJLSbJkiRJUotJsiRJktRikixJkiS1mCRLkiRJ\nLSbJkiRJUotJsiRJktSyWn2SI+I+wI+AnYHbgROBJcAlwD6ZeWdE7AHs2fz/oZl5xmo9YkmSJKmy\nKSfJEbE28HHg5ubQkcBBmXl2RBwHPDcizgf2BR4PzAK+FxHfzMzFq/m4Jeluww0+JGn8rE65xQeA\n44Crmu+3BM5pLp8J7ARsBZyXmYsz8wbgMmCL1YgpSZIkVTelkeSIeBWwIDO/HhFvaw5Py8wlzeVF\nwAbA+sANQzcdHF+uOXPWZcaM6av8uObOnb3Kt5mqcYw1js/JWKMTZ5xjren4xhqdWOP4nMY11jg+\nJ2MtbarlFrsBSyJiJ+CxwEnAfYb+fzZwPXBjc7l9fLkWLrxplR/Q3LmzWbBg0SrfbirGMdY4Pidj\njU6cGrGmUgIB/ZVB9PVzNdZoxRrH5zSuscbxOf09xlpe8jylJDkztxtcjoizgb2A90fEDpl5NrAL\n8B3gAuA9ETELmAlsRlnUJ0mSJN1trVZ3i5Y3AfMiYh3gF8CpmXlHRBwNnEupfz4wM2/pMKYkSZLU\nudVOkjNzh6Fvt5/k/+cB81Y3jiRJktQXNxORJEmSWkySJUmSpBaTZEmSJKnFJFmSJElqMUmWJEmS\nWkySJUmSpBaTZEmSJKnFJFmSJElqMUmWJEmSWkySJUmSpBaTZEmSJKnFJFmSJElqMUmWJEmSWkyS\nJUmSpBaTZEmSJKllxpp+AJL+fux2+FlTut38A3bs+JFIkrR8jiRLkiRJLSbJkiRJUotJsiRJktRi\nTbKkKdUKWycsSRpnjiRLkiRJLY4kS3dTju5KkrTmOJIsSZIktUxpJDki1gbmAw8CZgKHApcCJwJL\ngEuAfTLzzojYA9gTuB04NDPPWP2HLa0Zju5KkvT3YaojyS8H/pyZ2wLPAI4BjgQOao5NA54bERsD\n+wJbA08HDouImav/sCVJkqR6plqTfApwanN5GmWUeEvgnObYmcA/A3cA52XmYmBxRFwGbAFcuLw7\nnzNnXWbMmL7KD2ru3NmrfJupGsdY4/ic+o61puMba3RijeNzMtboxDHW6MQx1pqLNaUkOTP/AhAR\nsynJ8kHABzJzSXOVRcAGwPrADUM3HRxfroULb1rlxzR37mwWLFi0yrebinGMNcrP6e6+1XFfP1dj\njVascXxOxhqdOMYanTjGqhtrecnzlBfuRcQDgO8An87MzwJ3Dv33bOB64Mbmcvu4JEmSdLc1pSQ5\nIu4LfAN4a2bObw5fFBE7NJd3Ac4FLgC2jYhZEbEBsBllUZ8kSZJ0tzXVmuS3A3OAgyPi4ObYfsDR\nEbEO8Avg1My8IyKOpiTMawEHZuYtq/ugJUmSpJqmWpO8HyUpbtt+kuvOA+ZNJY5Gm+3SJEnSqHIz\nEUmSJKnFJFmSJElqmWpNskaUJRCSJEkr5kiyJEmS1GKSLEmSJLVYbnE3YAmEJEnS3YsjyZIkSVKL\nI8nLMJXRXXCEV5IkaRw4kixJkiS1mCRLkiRJLSbJkiRJUotJsiRJktRikixJkiS1mCRLkiRJLSbJ\nkiRJUotJsiRJktRikixJkiS1mCRLkiRJLSO1LbVbRUuSJKkPjiRLkiRJLSbJkiRJUotJsiRJktRi\nkixJkiS1VF+4FxFrAR8FHgMsBnbPzMtqx5UkSZKmqo+R5OcBszLzycABwAd7iClJkiRN2bQlS5ZU\nDRARRwIXZObnm+//kJn3qxpUkiRJWg19jCSvD9ww9P0dETFS/ZklSZL096WPJPlGYPZwzMy8vYe4\nkiRJ0pT0kSSfBzwTICKeBFzcQ0xJkiRpyvooezgd2Dkivg9MA17dQ0xJkiRpyqov3JMkSZJGjZuJ\nSJIkSS0myZIkSVKLSbKkNSYi1lnTj0GSpMlYkzwFEXH/zPx9hfu9DfgpsEtmLuj6/ieJ92xgN2Dm\n4FhmPrN23HESEbOBXYBZg2OZeVKH9//Py/q/zPxGV3FaMd8MfKqn1+DPgLOA4zPzktrxmpj3zszr\n+ogDPBT4TWb+qVKM6cCrgAdSfo6X1Io1SezHZ+YPe4o1o6/WobWeV0Q8nvK7WndwLDN36zpOE2v3\nzDx+6Pt9M/PoGrH6FBEPAd4PPAK4BHhLZv6u4xi9vedGxLbA/sA2wK3A7cD5wDGZ+f0uY61pFfOm\nM4Djga9m5h1d3/9IbuoREVcDSyjJ3brA74D7A9dm5oN6eAjvAV5Z4X5n1fglL8cHgD2BhT3GBCAi\nTs3MF3R8n7+hvC4GbgPWBhZn5mZdxhryZeAqymuQVvwuvGQZx5cAVZJk4C/A6RFxDXAC8LXMrHU2\n/VjgGcAhETEXOBn4fGb+petAEbE9cCwwPSJOAa7IzBO6jtPEehFwKHAp8KiIeEdmnlwh1Mcpr7+d\ngQuBk2habvbghUAvSTLw38DTe4pV63l9DDgGuKbCfQMQES8BngM8NSJ2bA5PBx4F9JIkR8Qxmfm6\nSnd/AnAE8H1gO2A+5bXfpV7ecyPiI5R9JA4BLs3MO5vjjwZeHhEvz8z/6CreMh5Dzd9VW6286c2U\nwb53RMTXKQMu/9fVnY/0SHJEnAy8LTN/FxGbAh/KzBev6cc1VRHxTZaRZGXmMs9uVyPeFzPz+V3f\n70rGnpOZnSbnETGT0mbwWODjmXlBRPwT8B+ZuUeXsYZinp2ZO9S47+b+l1mOkJm31orbxN4cOJAy\nyjEfOKrr31kTZxolUd4deBglSf9cZh7TcZzvAs8DTqOM/p+XmVt2GWMo1vnAzpn5l2a24azMfEKF\nON/JzKdGxFmZuWNEnJeZW3cdp4n11Mz8To37/nsQEd/OzKdVjjEHeAzwdkpSAnAncHlmXlUz9tBj\n2Cwzf1Hpvr+VmTsNfV/9Z1pLRNwnM69dzv/fNzP/WPkxVPtd9S0iNqKcCP4b8F3gPzPz/NW935Ec\nSR7ykMFUS2ZeFRH/0OWdR8Qsykjr0cD9gA8DtwBvzswaowH7N18PBr5C2YhlK8oHeg1fbj7M7/oj\n6Xr6b5KpqyWUEf+fdhkHIDMXNzEfmpkXNMcuiojoOtaQn0XEE4Gf0JzgdJy8Jn974jStOfaQDuPc\nJSLuBewKvAK4HtiPMhp1BtBpAhYRRwDPBc4B3tec2KwF/Igy6talOzPzuohYkpm3RMSiju+/Hesv\nAJm5KCJuqRRnRvPhMCj9ubNSHIB3AlWT5IiYQRkJXThIyCPivsDRXQ+ARMTnWPpvawlwLWWq+/IO\n4wzeA2+IiLdTXtuD94pOZ4Oak9izI2KbzDxn6DEcBryty1jN/U6jjOg+ELgSOKdG0jX0M/xrRLyF\nkgRtBXSeRE7yurhLZr60qziDBHn45DMi7kEZ7NurywQ5Ih7ROrQEWFDpd/XqzPxkc3nzzPx5c/mQ\nzHxnhXi7UMqYNgM+Tcmj1gb+h3LCuFpGPUm+NCI+DVwAPJny5tOloymjWmtRRicvBH5OmTb7145j\nMfRi2igzP9scviIi9uo6VmNfytTV9ZXuHyafuto0Iq6sNboLXB8R76a8Lp4CXF0pDsD2wLOHvu80\nec3MB3d1X6vgQkrZw66ZeeXgYDMq37XfAVsOl1dk5p0R0fnfF3BZkyxsGBEHAFdUiDHw64j4IOXD\nfDugs6Sr5SDKyfQmwA+YONGuYUlEnE45cbsTIDPf3nGMz1DqMjdpZjJ+Q5liP6rjOADHTXLsfpSS\nlS5PBgfvgTcAD2/+QYWSqYh4DWVGZrOIGJTdTKckDZ0myc3JyxnAZZTf07OBIyPiXzKz6/fcwc/w\nOkoyNCifW9xxHJj8dVHTuyNif0o+djwl0evaxyc5NjciTqmQuP478Mnm8keAQdnP9h3HGXg58NHh\nk0KAiHhHF3c+6knyW4CnUor4v5CZX+74/jfPzK2bEeVtgRdk5m0R8aaO47StFRGvZCLJq1WnfE1m\nfqHSfQOQmZPusNiMYNfyMmAv4FmUk5p31AqUmat9pro8g5qx5ue11OhGZj6l41iD0o4taF5zg2OZ\neWtmHthlvMaLM/Mj7YOZ+dsKsfaiJBDfA/7aXK7l1ZRZqJ0pdckH1AiSmedExM7AzcCDMvPCGnEa\n8yve98BDM/PxzevuR5Qk6Kk1RrzaH6oDEbFPx3Hueg9sTjQD+HlmXtxlnMbJwLf523KLZU7rr4YP\nAgdk5rcHByLiGcCHKDNRnWn9DB9BKcv6GaUev2s1P5sm8zzKzPE6wAsrvdaf2j7WzNj9gDJD1KVp\nK3G5S68B9oiIF1AWcx6fmXdk5uld3PmoJ8lfycxtKt7/YDp2a+CCzLyt+f4eFWNCOTM6mHJGdikl\n6avh5oj4GnARE9N/XY8MLaWpG34J3S9wG3YTcC5lRBTgiZQRvc5FxHOAfSgjNdOADTNziw5DvLv5\n2umHzjL0XtpBmT79EEuPTn6iUqxtM/M4gIhYlzLKUWuWZktgenOC8xnKB+9FXQeJiOOAyzLzAxFx\nULPYZ7+OYwymugejg9VKpigLmcjMW5sP8X/OHjqRAETE+pRkJSvd/7spo2oXAPtGxOmZ+f4uYzQl\nZ7+NiP8AXgtsDvyKMvvZtQcMJ8hN/K9FxMEVYgEQEa+jzOLeGziRMirf9cKzXt4Hm1mtQZxfUtZl\n/HtE9PE5PJ2y1qRG4touYZrscpdOBH4LfIsymDmfDhcIjnqSfF1E7MfSH7BdTl/9JSJeC7wA+Gzz\npv0ySu1VNU199Rcof5AX0HxwVPDVSve7PNMoK61rrHIdOA2YS5nKH7y5VUmSKR0M9qQkW9+h+5XW\n+7VKqgd1k51PyQ1KO5pEq0YnhskM2hzdt/la8+RpMK05nTKFX2Nac+AYJk5sDqa8kW9XIc7jMnMv\ngMzcr1mc2LVllUxdkZmvrRBv4I99JciNRcDrsl4rwl2ArZpyoumUE6dOk+QhH6eUd3yTMs19PGWN\nQZf67MQ0sCvl7+jbmXlURHQ+c9Jjidsvh8NS1mX0ZRbw+uZf1zZsZrfWAu7dnGRPo5zY1LBxZg7e\na78cEZ3+HEc9Sf4zpYXUY5vvu67x2gv4f8DXgE9RRgFeQEmKqmlGHB5KKSNZQqklqzGa/BngCUyM\ngm5aIcZSMvMWSsuWmjbuuhRhOa7OzPMjYq/MPDEiXtXx/U82qrUp8F/ATpP8Xxf2oEzbVpeZ74yI\nTejnNVh9WnPIbYPFX5n564iotqAuIjbMzD83Cy47f0/vuWRq84j4LOW1MLg8eBydLZqaTJY2hzV7\ndf8emE1JXtemwqKzIQ/PzMFJ2ZciokbP3Ssj4lmZecbgQET8C2VUr5a1KJ+Jg5PpGjXJvcjMTwFE\nxJMoJ09HN7NOH+wh9l8puUwNPwYGf6sXMXGS3elM2lB54G8i4gmZeWFEbEGZOenMSCfJ7Tfv5sO2\ny/v/E/DWoUPfbv7Vtn1mbhelvdMnI6JWUn465c36fpTRtauAz1WK1adfRsSmPbU8WhwR2wFrR8TT\ngY26vPPBG2lb82FUy8yIuIilZ2iqJCgRcQJl0e16lDKmXwNP6jjGmpjWvCIi3ksZLdwK+EOlOO8C\nfhgRC4FYBxYoAAAgAElEQVQNKKU/VVUumXrR0OW+F1DVtinwq4j4KfBI4NZB8lrhpH5WRKybmTc1\nHROmd3z/UAY7vtjMtl4OPJgyI/Ts5d5q9XyWMiv4wIj4H+BLFWP15SP0M+vUi2WdVNcIRXkPmgbs\nEBG3UgZAOu0kNNJJckS8C9ib8oNZl3IGsfkafVDdmNF8EC1ppuVqTWttlJlPjojjKdMu36wUp2/b\nUEY5BjvGLcnMWiOUewP/SCm7eHfztZoobb4+Qt0NYN664qt05jGUv9mPUxYbnVohxpqY1nwNpSb0\nmZQWi1VeF5l5RkScSTk5uzbrbfoyrFrJ1LIW042JF/YY6yjgpxFxCSUhP6TrAM0g0nYRsSWlNPCU\nrLxLXGYeExHfprz+MjN/VjNeT/qcdYrMrFJz37fhspgorQg3zAq7jY50kkzpp3l/ymraI4GPrtmH\n05mjKDs+3YcyEvU3q/87clPzdb3MvDkiOv+AjYhPsuyek1W2ZM3Mdk/Imt4MzMvMSylNzGv7KyWR\nrLXbHsDFlN3NhksgaiUvf87MJRGxXmb+Keq0tP55Zv4wlrPdbAVfygobALU1tX9voNkWvRkd33H5\nt1o9PZVMVRf979x6O/A+yvv6KcDPMvN/K8QhMz8TEec2sa4dbuVYIdaP6L796lJas0E0lzeNiN93\nXbceEQ+m5BMvpHSX+i9KK9h/zw42p5hEX7NOUNZi1Gx20LsofZKPofQhvyfw2sw8u6v7H/Uk+erM\nXBwRszPzsljO7mSrKyLuQ/NBBFDjTSciNsnMqzPzC83Z8sMpOyXVaN8DZarsPykjDj+gvBF07fPN\n170pi7TOo9RBb1UhFnBXjderGUryMrPWlrbfA45oRng/SWlFeHOlWGTZuvSMFV5x9ZxOGf18NGXq\n6qblX321/Cgi3gxcFRGfp07nmKdRTjrbC9Bqbu29sOl88ismSlY6rZVrfIjSG/l3K7qilpaZm8Dk\nO7dWCvkJSr3pwZSSgU/RcWnRQEQcAszMzLdHxCkR8cPMfF+NWD355STHaq3NOIayY+vtUXqdD7pM\nfQbYoeNYUD6r9qLMOl1K3dnIPrsJERFPo6yv+gHwq+YEu2vvAJ6UmQsiYmNKCU5nf1ejniT/PiJ2\no/ziDwPuVSNIRHyU8gK+ioluCTUWhn2GpvF2M23Q+dTBsMw8dnA5Iv4b6Gy/86EYX2/u/02ZeURz\n+LwoW3DX8jHKJikvoIyKVjt5yszTgNOaevgPUXZlrPI67NG0zNwrIuZTegmfWytQ8yE+m9LndxdK\nN5euY7yv+dpXrRyUEbw3DH2/hImm+l26MjO/VeF+/0ZEbJx1dhqdLNYDKCc1wwMT76oUrurOrUPu\nkZlnRcRBmZlRbxdGgOdks+V6Zr4wIs6jjGJ3ro/XRc9rM+6ZmV+JiA0pbe6+2cRaq8sgEfH4zPwh\npf740uYflG4ktU7e292EqmlGx+9P2fhlMaUBwWSdclbXosxcAJCZ10TEX7u881FPkvcEHkCZunoV\nEysqu7YV5Y205pavvWveYPamTDUO1JqqvWdE7EjpXfwUhj78KvhTZn4uIv45M9/RdUuYYc0H6iso\nCfmPqbeFeJ9uj7KBznqU5K7K+0RE7NQkeAdTamqXAJ1PPzc1ftcBw9uFT6NirXq2mvdXnOW6Nkqv\n5OFe57VGhk5t6vxPAP6n8vvhKZS+p32MkNfeuXXglmZx7/RmtqtmknxnRKyTpd/02pSuELX0+boA\nqq/NGPxengac1cSbRlkY26XeZ7iabkI7UWrIf0DHnSBathlqQPCpiNi7yztvknAoa7jOoMzqbkXH\nHU9GPUlej7JRxCxKW53HM3E21qXLmhg1p50BtpykVc/gw7zGyPW7KaNdfYwOvYYyuvsIyi54Nfsk\n3xllS9t1oxS51urPCKUn8/HAdplZq5/132imzP4CvC+HtnTuyLGUKfxvUJKU73V8/0TEQZTFN9+i\njKQcQmkEfzDd9+58M+Xk5XLgM5lZbWR8oOlI80YmSn5uo7z2u/ab5uvGFe57KZm5TUQ8kjI9fFBT\nEnZCZv66QrhFmXlQhfudTO2dWwdeC3yAckL4ZsoARS3HAZdExMWUhcXVSi16fl0M1FybcUmU1oOP\np+zktgmli8xZXQZZ1gxXU2NbRY+ju1CS11nUa0CQra9LgM7/dkc9Sf4ypQRiMNpQa2X3P1CK6y8b\nxKmUtF5KvRfsZK6rvZp8aATtcsrCtkG5Sk1vpHRMOJrSMuiErgMM1Y8/oXX8ibUW47ScSCmPqdEX\n9zS4a1emUyol/ztRRlIAbs7Mr0fEt6gwkpyZRwJHRsQ/Ai+LiHdQph1PrrjSex9K/eJBlFHR/WsE\n6XlkCMqiol9TdhR8FHBURPw8M7vedvuSiNiVpUfIaz232ju3ApCZv4+Il1HeA59MxQVamXlCRHyF\n8rq4LDP/XCtWo6/XBVB9bcabKW0ij2wW/D6a8tl8dJdBIuKVwGGUUrMXUH5+8ygJ7JldxhpSdXS3\n5UOUWZm5lPf1Tmv9c6LP9AxKVcEjqbC75KgnyWtl5st7iNNX4npLZl5RO0iUvpZQ+nR+gvJCrjVV\nO9zLcJAcV93qODN/ThmthjI6X+PM/K768Yj4dGb+e3P8MCqVrLQWjy7MzE5nNiLi/sAXgGdl5kLg\nxZTtc5+fFXpOZ+ZgZOGowfcRcUPXcYbi/RI4uHmeHwR+Sr2yn6sy8+pmUfHZzUKqzvU5MhQR/0VJ\ngE4GXj54TUTEDyuEG94kCurVdEP9nVsBiIgPUxbEPhB4HGUzkU5n1CLi3pTZmDdR6k6PpZR5vKbW\nCWHPr4vqsrRRPHPo+4spa1u69ibKYM4mlPejTSkDfzU2DhuoPbp7l8w8pRn4eBjw64onah8HrqfS\n7pKjniT/LCKeCPyEiSTv1uXfZOVFxO6ZeTxl5Wl79LPGJgTHV7jPyQw2XRmM2lWbqs3+tvgkym53\n76WfM/PhPe/vv4zjnelp8ehxwPubBJnM/GxE3NYcf07HsdYZ1Exm5pfgrlmHWvXP96ZsVDHYrOIL\n1J3uviEinkf5MNqTjjeZGdLnyNDxy0geOx+Fbdd0V1Z759aBJ2Tm/s3v6qlNWULXjmOiPOpoSt3u\nxZQT0WdUiAelBeZkC7HHqtVYBdc177ULm3KVvTKz1gjyQNXR3WER8R2G8qbms+R3wKGZ+dsOQ1Xd\nXXLUk+TtKbv7DI9Udjk6OSjjaLefqVUusHsz6rlf5emxT1a870lFaYe1DxM1mhtm5hYdhxmUWfR5\nZt5W67XRx+LR2YOEdaAZDdivQqzPAPMj4vWZuTDKlsofppTHdCrKzlz3o5Q97EE/i8F2p4ygvI0y\nYtR1nfVAbyNDlNKRv0kea7R1itKa8nWU3sKDOLUWWVbduXXI9Cgbb/y2OSGcXSHGJlm2N54NbAGc\nlE0f8gqxBq6O0pN5DmU0+ZLMPKPG66Kt8tqM2obfy6/oIUHuc3QXyvbk51G6Iz2ZkqudTyl/fNqy\nb7bKqu4uOepJ8vsz8+Rad55N+zJK373tqduRAUq/v2t6qB/7AiWZ24jyRn0xJbm8hlJTVsOhlLqh\nvYDvADtXiNHnmXm7sX1tfSweXdYoeOej45l5bNN14rsRMQdYBBybmR/vOhalVm0JZfHoYAObKiU/\nUbYoHzabCotJhhzJ0iNDR1aMtSQiTmfpsoRa23o/G3hgVuw5PhD97dx6EmXDq90oi5hrvNYH7a+2\nB87NiR0YaybJR1EW7c2jJEBnUr+X+8CJVFqbERH3o3S0uJ2yC+lHMvMnHYbYMMpmQGsB68fQZkc1\nyn3gbztaRd3Nh/5h6AQ0I+JlTa18Z6UQjaq7S456krwH5cy1tm9QCvevb75fQmli3qnai+iG4jwZ\noPnAe0VmLmpGGj5XMezVmXl+ROyVmSc2pRFd6/PMfJuIGJQ+3Hvo8pxK8fpYPPq/EbFvZt61QCUi\nXg9U2fo1Mz9Gx4sslhHnQbVjDDmbskj1wub7wQnGEsoGEl37M2Va+2HAb7LCtqxD5le877ZrKR1B\n+tDLzq2Z+dGI+ALlxOzQSr+rq5s69X8GDm1GlPen0t/wQJbNvJZk2dBhUa04zWzJPzHUtrTrtRlD\nPksZuNqH0knjQ5QuKF35MRNtay9iYi1BzU2O+uxotU6UlofnU0oD146Ih7B0y9nVlmV3yTMpf1e/\n6XqQcdST5JkRcRFLj2zU6JV8Q3tKbkzcPzMXAWTmXytOMwIsbkbZ1m7+cGrUaPZ2Zp6Z1TYoWYY+\nFo8eBHw4Iv5AeRO9F/B1ShmLVs7jKR98j6O0jDq54/q7tnc29XgXrvCaq+8kym6Z1WbUIuJzlCTh\nvsBFzegQlJPCWn3we9m5NSJeRElSfgE8KiLeUWEmdG/KqO57M/NLUfoxb0RJ9Gq5rqm7X6/pSHL9\nim6wGk6lvC8NkrxaJ59QcorvAgdm5ucjYo+O73+f5SX4gxKCjmNW72g15FXA+ylldBdTZlCeREef\nJxGxPqWs7VrKe+1hlPzijZn54y5iwOgnyW/tKc7XI2IvhnowZ2atP8w+fSPKRhs/pPSb/tIKrr86\n9qb06zyU8kFRY+vNNXFmXlWfi0czczGwd0TsC2xI2ZTl9hXcTEOaN+cfR9l8YEdKN42NKW3Gakyv\n91kCcRplJ8Hhlptdvw8e1/H9rYxedm6ljOBtmZl/aUZ4z6LjmdCmDvhjQ9//gNIasKbXUN6L/kQ5\nSXxNxVgbZea2Fe9/2NqUspjvRsRT6X7n1mObDiCfHx79jIiNgJdTRsw76X4S/Xa0GviPzHx+61iX\nvbM/S+lQ9DDKgv1DgN9TFqx2tmh01JPkH1MS5U0pNVC1ppS2BWZS6ryg0tlrezXosBp1Q5l5YLOQ\n5OHApzKz2pRcZv6hWd06i6W36+0yxjiO9i9r8Wg1mXkb/UzHja1msdT3KUnlKygjHjWS5D5LIDau\nUOKzlMEoVzNKdDATvU/fXTHsnpRyi8HOrbVmbe4cLC5rStyqL2zrQ2be2Jxc3Ak8j7prNK6IiAdk\ns414Za+mrJ05nvK8Om3Xl5mvbmYXvhRlG/Y/AesDVwMfzcwPdxiut45WQx4ZEffKzFozCxtk5oEA\nEbF1Zn6yufyWLoOMepI8n7JIYHvKh/oJTCSyXbpnZu5U4X7b9mq+HkIZ1T2P0tXgWTWCRekXewBl\nkUpGxBtqTQ331MJs7AwtHv0M5QP8HygjUJcs6zajrJlu/z1lUe61lWN1vjI+yhbAu1BmNIKyaG//\nzGqblrwE+CJwemYuqBRj4JcRsWlW6Jk9ifnAOZTX/faUBVpdtyEc+AdKy8h1Ke9NL6TssNa1X0fE\nBykDLNtRatdHXkR8njJI9RRKqdvzgX/tOMbVlM+MWcCLImIw8lpta3nKqOetlDK0s4DON1XKzP8C\n/qvpUDMH+HN22MZ2KM474a7ttZ9Hs/NtZtZcYPlI4M8R8SfKCVTXv6vhNQvDdch2txiyYWbOj4iX\nZ+b3I6LW/vS97P40+CCNiPs2fzwApzeLp2qYR5ma+y5ld7CuW7MM66OF2RoXEW+lfNB+oONSheMo\nJxg7U+pPT6KcdIyb/SkjKlX6TbecSPcr46+l/J4+R2m1uAR4YEQ8sNKK9ddQksf5ETETOGN44WXH\ntgGubD70llA3QdkwMz/SXP5JRLygUhwov6uvUX/25NWUUeudKXXJVXajm0yUjYgWVeoWsmlmnhxl\nw5KnNi3GOpWZNdfLLMvH6ek9tymTubrGfbfMA+5JWUz3iojYMTOrrDnJzAfWuN8h92vKSKa1Lnf6\nnjTqSTJRtpodjIrWqp98TPNvoObuTwBExGuACyhn552fWTZmZeZXmstfiogqZRCNPlqY3R38hFIG\nNAfocmTvoZm5e0Rsm5lfjYg+P2Cr9SJtRjaWWgyWmX/sMkYr3tOAh1LqNDO77+X6Zcr7w0ObfwNV\n6uKbMqYLKa+351F2SaySJGfmI2rc7zLcIyI2zsxrIuK+dDw61HLTYKSthuEFxJSTsl8B1zZlTX05\nCrg8Io7LzN93fN/rRMTzgUubetoa/Z8BiLIF+wzKiPVHgIMzs/Pe6o3Be+42fb/nVvTozHxic/mo\niKhWrx5lO+/5lFKma4DdMvOiDkN8lokykuHLnXbpGvUkeT/KaM1mlFWv/1EjSLZ2f6q1+nnIy4AD\nKbuD/Zx6m2HMiIhHZ+bFzQu6pj5amE2qqfW+CPhgZv6hZqyh8oiuzWg+gJY0i376HJE/kUq9SOln\nMRjQzxbOmfmqLu9vRSLiOuAK4HBg58ystq13RGxOmdFYatOISuEOBr4fETdSkq6uOwsQEYOk/48R\n8VKWXszU5UzhZK+xTSPiyszs/HkBREQMl/hkZs3uOEcAu1K6FuxL3frx91BKmY4Ftqa0Yq2VJA/e\nc1kD77m1XBYRD87M3zSzC1dWjHU0sHtm/jQiHsvE76wTNU9sh410kpxlT/UnN9OMg9X5nWva27yR\nid3ibqPU9NRyZMV2R8P2pUzTbkKZVqryht3oo4XZpNonOV2KiLcDb6GMkE+j3hT0gZQa9U0oo6A1\ndsG7S/OaGLzea7QiGqi+GGxIn1s49+WZlO2GXwO8ICK+VamLBpQPvV42jciyzfFDImKjrNf7efjn\ntAcT73+dzhQua0FxRJzfVYxJnEBP20Jn5hcpdfEA/1k53E3AH4Hbm1mGmosED2Lp99z9K8a6S0Qc\nlJk1uj9B2fnulxFxJWUX0sWDeu8Kn1vTMvOnAJn5k4gYyU5JI5kkR8RjKC3E/gh8nmYHuWbh2acr\nhNyHUrN7EGUFdO0/lpkRsQVlWm7Q1qlGMf9FlKlu4K7pkVruoDRjH6xW77y0Y6jNzd+o2ObmxZSa\nvNplJDdlZkTEXErNbntnt85ExAmUN9P1KIuZLqf0t6yhz8VgfW7h3IvM/EFE/I5ykvtSyuLOWkly\n9U0jmsRxqd0sI+Ja4LDMvKDLWIOT5+Y1sVlmXhQRzwP+u8s4bc2gzkuo2wXir02Z1HBrwE7fA4cW\n082kvE/8jpJ4Lch6G/gsotSPfyIi9qGsAaii6bQSETG3h0Wxw86rdceZ2ekOoytwR0Q8i7It9XaU\n2buRM5JJMmWx2SHAvSldIP6JUv/5NaBGknxVZl4dpdn82RHR6baHk3gES29l2+n2uVE28/gAcB3l\nQ/V3lD6Du1LKImroY5Hgmljc8Rug2ta5EbEt5cTiDREx2HJ4LeB1wKMqhX0MpePJxyn9T0+tFAf6\nXQz2IZbewvlDleL0JspmSn8CTgdeVrmcqI9NI3ad5Nj9KFO1T5jk/7pwMiUxvojy3vsiJvqt1zCN\n8rfbaUuxlu83X+9bK8BgMV1EnAy8LTN/FxGbUvfv6oWUWuFLI+JRlM+VKprX+p7ArIgAIDMfWSve\nkJqb9dSuEx62GyXPOIyyULXmTPVdul6kOqpJ8q3NdBwRsV9m/l9zudNFRUNuaEYYljR/ODV2i7tL\nZtauDz4C+DfgQZRaxkFN6GOWc5vV1V4k2PmK2qE2N7US/cmsA1wcERc333e9M9hCSk/LmUycBNxJ\nKfGo5c9Z+vyul5l/GnxA1NDnYrDMPKVZed/HFs5LqVgX/7TMvG4oziaZWWuVfPVNIzLzikkOXxER\nNetB75dNj9XMPKL5XVXTLBZ9c+UY72wWuT2EUirQeTemIQ/Jpm9xZl5V+f33rQCt96Qa7fqglLQ9\nk/Ie3LmIeBVlcOpmSgvCX1OS/s0opUw1VK0THpaZV0TEgZR9GH4KVF0PNKTTRaqjmiQPv2EOr06v\n1QJud8oH69uANwG1WrIBEBHPoZR4DGpCN8zMLToMcX2zMOVXzdT6uzKz2hl5o71IsOZU4xea+18L\neDBl0Vmt+rz3VbpfADLzEkoLwnnNB9C9gDuy2U68kh9FxJuBq6L0QF23VqA+RzbaC88ioubCs6VU\nrIvfP8puoIMp7/+jzDx0ppX0fHTo8j0ps1HVNK/3H9PxznQtSyLiEZn5q4h4KHU7afSij0WqQy6N\niE8z0Y3pR5XiQCmxhPK5+DjqfeZD2Zzsd5lZqyzrjZQZu02AD1Jal32Zegv1occ64Yh4HaVf9r0p\ni78fTpkBrarrRaqjmiRvHhGfpfyhDF/u+sPh8Zn5Q0p9JpRp2q9TWt7sAFxUaTX5oZRpnr2A71D6\nNHZp+I/+yh4SZJhYJLgp5YxymfXDqyszB7+vwYds5/XIEfGsJsH6R/424T+nwziPo5SmbBWlzdJx\nwMKIeHNmfrWrOMMy8+3Nau6bKRtj/O8KbrI6ehvZoMeFZzHJjnHDI74deg7wAMoU95EsncR2ZXDS\nOY2SdF1KTxsCZeb1EfGYyieFbwC+EGX78D8wsanTKOtzkeprKcnQIyhbLH95Bdefsvai1IioNeIK\nZQORX0fE5Uwsyu6y9et1mbmQ8n7+SGCvzKz5fKDfOuFdmxjfzsyjorSq7EyUXR6XtUPx27uKM6pJ\n8ouGLh+3jMtdeBrwQyY/A1+b8oGxZccxAa7OzPMjYq/MPLGZlunSehHxcMpZ+PTm8jSos0lK4+fA\nv1AWddQcRW67gQ7ruYds2Hxtb+/Z9XN7P/DKzLwtIg6lJK3/R0nwqiTJUbZIfQkTtXH/RL0pzV5X\nQNdeeDZkPqX+vvaOcVdn5uJmvcRlUaE9Zeuk8zs1u8UsI37N3xOZ+b+U13hVzUnga1m6J/hulcL1\nuUh1Pcro+x+ADSLiFZl5Uo1AMdG2D8oIbM0NK/ak5Bq1tlUenhG/oocEGSbqhA+nnOzuXjHWWjTr\nTJrvu07If9nx/U1qJJPkZtVpH3He13xdVgufWs3FF0fEdsDazSK7rmugb2JidPXmocudb5ISEfdu\n7v9xNPW1EfFtYJ9aH35DK+SnUUb/O98BCji/ecPutHH5JKZn5s+aEfj1MvNHAJVrNE+h/Mx+t6Ir\ndqDPkY0+Fp4NbJgTO9/V3DHu9xGxG6WbwWHAvSrFGejzBLeqiDg1M18w1KUB6rZxPBE4hn7+rvpc\npPplSneV4V7ntQyPJN9CKX+s5ffAhVlvl9gNI2JnSjK5fgxtOpN1dueE0kv9hYNvImJfKm0+ROlf\n/V3KjqP/Q2my0JnM/BRARMygLOodlKe6417fIuJtlAUDS/XCzczDK4XcGwhK2cW7m6+d6Xkk6MPA\nFzPzriQhInanTKu/olLM4RXyt2SdHdyW1War6xONwa5cz6BJ9iNibSruakVZGXxQxfsf1h7ZqLkC\nuvrCsyF97Ri3J6Xc4hRKp5o11o981Azek7K15XFE1KrBvyYzj69030tpL1Kl7kjyWpn58or3f5eh\ntn1V90ZozAR+GhGXMLHJTJeLsn/MRBeVi5j42+18d86IeAllJuupETH4fFoLeDT1dug8phkQexTw\nyyz7WtRwOiVBvh/lffYqOhy8MkleObvSTy/cgYMpzdkzM/+tp5i1PCRb24Zm5vFRdriqZW1Kq6C1\ngWlR+vDu2WWAHk80vhUR51ESoec0C4uOodSJ1nJJM9J6EXV2ILtLswJ6V8rJ55OBWp0ZyMwbm5/l\nn4CLK9UID7R3jKtSg9+Mcg06QnykWUD1713GiKX7j99v+Pus13+8/Rg67w4SEQ+kjEQupGy5flNE\n7ELZ7vhhXcRo+W0z+zj8d1VlxDAiPpKZrwcubGYjP0K9DbB+FhFPBH7CxPPqtK9/9L83ApTWZdUs\na4a6kq9R3ls3ZGKA505KD/zORcROmfktyhqQjYBnRMTbMrNGX+uNMvPJEXE8panCN7u887FKkpvp\nilsz8+yO77pqL9xJnAQ8FzgkyjbOp+VE+7RRs6w3y5pTcp+lnF1uQzmrvGfXAVpTtAOdT9Vm5vsi\n4ivADU13i4cCn8jM07uKMYnHNv8GOi/DGYiID1N6aD6QUpLzRyr1j42IYykfEucDuzdv5P+vRqzs\nZ8e4ydTo1zc80vrZoe97K72odFL6OUoJxAOBd0XErcDzKSPyNcyk/H4Gv6PORwyH3BgRh1Pe+x5F\nWctQy/bAs4e+77Svf6PvvREALgaeztLT+L2UenatWSB4dkScQzlpv5Oy2PKSrmNFxEGU19y3KCV0\nhwDbUgYOanQGGwxerpeZN0fHuzCOVZJM+cP5eUTcv4v+eEOGe+HWmHZZSmZ+v0mOf0p5UX0U6DxJ\njtLm61NZdzehdYcXBg5Zr2LMv2TmYRHx8MzcLSLO7TpAe4q2psz8xdDly6l09j8Uo89ynCdk5v6D\nBWHN9Fwtj8nMQSvAoyLi+8u99hRExDGZ+bqhuvi7erpmf9tvdyqb/uN9iogHUXrH3lX6kJldLx69\nczASHhG/odRPPjZLH+PORMSMzLydUhrTi8w8MCLeDzwsM3eoHKtmf/2BvvdGgDLQ8gtKScItTCRj\no+xzlI4+T6GUWzyfkix3aScmNgq7OTO/3pT+1OqS9MWI+E9KacwPgE5fE2OTJEfEWoOFdhVU7YXb\nFhE/pdSQfQbYI0uv3Br+ApweEddQWmJ9rULnieGFge3jtSxp2jnNjoj1qDCSPBAR89vHKq5Yr2oZ\nC5kAqLSQCUp3lS0pU9HrULfW+srBCXRTJ1xjAdW7m6+T7RzXmeFFPkOmAevXjNujz1FGCa+pGOO2\nocvXAa+q1HnnJErtadJaIEjHI66TLEK87+BY13/Dk50QDlQ4Iex7bwQonXf2at7jd6csLq4iSsvI\nwejuGc3Ibw2bZubJEfGaZlCixqJ2cqK39FGD7yOiRrtcMvPYweWI+G9K96fOjHSSHBEvoySTM4H3\nR8QRmfmBCqF+TFm4tynlLOxnFWIMO4yyUOuZlBrAr2fm17sOkpnHAcdF2WThQODjzRvCUV39kfbd\nLqrxTsqbzacpuxjVmo6DidrgQXP7WslkdUOLK1+WmWf1FPYkykzJbpSdIJe1IHLKhhKHWcC/RsSV\nlI0WOi+DGFokOp3Svu8RlCnNrndIXNYCvfM7jrOm3NTDCPZwYndDpQR5eNbxRZl5V6/YKL32u47V\n22/ASAcAACAASURBVAwXPZ0QNnrZG6Hl9iht9NajvFaq5EtRNmyqPbo7sE6UfvuXRsRG1BmUWCci\n1snMWzPzSwDNAEinP7+I+CTLLvnqbKBqpJNkyraRu1AK+R9Aqe+qkSTPp/Sl3Z4ysnFCc7mKzPx8\nRJxGqQM9AHgxZeVmp6JstLErpcvE9ZSf53TKH2ytDR2qas7If5iZ320OVa3lbp28fC0iatUY9ukd\nlEb61WXmR5nYAGP/SjH6TBwGTqAk/d+n1OXNp8NNgXpe9ANAMyszhzIC+1rgpJx8G+nViTFYXPbH\nZnHvj6i3eHSbiLiKkmzde+hyp6OuEbENZWe1N0TEkc3htSi7jz2qqzhNrM+x7A0WOi0RHJwQtl8D\nTcnU0ya90dT1tTfCsGMpG818gzLr9L1KcXoZ3W0cQfnMfyNlg693L//qU/IZysZhr8/MhU2e8WHK\neoYufb75ujflffY8Siu4rboMMupJ8mDaZVGWhvq1ns+GmTk/Il7e1AvXnOIhIr4K/ANld78DqTc6\ndCFlu9ddM/PKofjVG+vXEGUbzDdRRgBeV2P0fZKYw9PemwD3rR2zB0si4nTK9PCd0O0ORsMi4hWU\nE8HhDRZqbP5CRDyJstr6roU4mfn0GrEoW4cPNgf4akRUOQHo2amUpOTfKO36PkFZ2NSl4ZmEPZho\nCdj54tHM7HzjlWW4nrLp0EwmFj3eSfezC1A3aVxZnZf8ZE97I7Rinja4HBGnZOaNlUJVH90dqos/\ng4ldRjttLTuQmcdG6eP/3YiYAywCjs3WbokdxPk6QES8KTOPaA6fFxF2txhyGfADyhn6IVQsg4iI\nf2y+3h+ouisYcGBm1i7pAPjqZFOamXlgD7FreCll5fj6lBKL6kkyS09730KH0zxr0N/UWVf0Vkr/\nzj42WPgYZSTlBZSV650nSUMnTX+NiLdQFoNtRenaMerWpczM7JeZr4iInboOkBN9cGcBm2XmRRHx\nPOC/u47Vl2ZNySVRdnqstXPlINY5cNcmTmuqM8NIbzgzSY31EuDaiHjvcLlMh46gzBa/iXqju73V\nxQNk5sco77d9uGeU3s8XUkpWZq3g+qtk1JPkTwP7/v/2zjzMsqo6+79iEISgCBIFFFQkr6CgIhD4\nFAUNiAZITGSKqIAgSSSiwieKogwCEgc+psgkgzLIoIwBgoDYBgemVgT0RUAwCEQQBWUQkP7+WPt0\n3b5dPUCffW6d6vV7nnrq3ttVZ53bde+5a6+91vva/qOk62zXGvLYAziJsKE+B/jXGkHKhPXgRPyT\nxEXuT7bXqBByDUnL2q7pPDYhZVvwbuALLWonPu7Q53xAFex5J2IU294dcBoxib8mcCt1L3Z32L6t\n4vEHecD2GZI2s71fkUNqm2bR9CBxvWjetzVND7riOcS18HpJa1JXoeZUIjGeTvR1b8O48UJf2VjS\nQQNDTTWprsygWfWzGxqX0z4zUY/1ykRb2HptB7P9LYVhydrE7kwrOuBDMZr3zr62T237+CNmZ8bn\nP26mZQnRvifJ+9t+M0DFBBmHU8yGqu/y8yriInM0cKzta0rrQ5WknEiCfivpforHekUVg2E+QgxO\nDUvDtUWt4wIzbaEfZFYd6JqWtl1yLLFF/G2i9/4E6rkjPirpEmY1IqjS2gE8XYZUl1KsQpdrO8Co\nF02qYLoxwJ7A3wMHATsQCXMtVrZ9EoDtfy/Pq++sANwzUAyZUVEWsAtlhjn1+p9cIVZnzKHP/q5y\nzW+d0ib4LuJ6dDKwOtGvXoNdiQXolMH2z5lVp7tV+p4kV+2dVMcuP03yLWk129eUx6aXD/TWsb1q\njeNOhKTnEtVJEau9YytUVCaagAaq6FrvRQyN3g6cZruaPNAIWL1ZfALnqYKe8AAXD92vuVX7MWKA\n6ghiiOSrtQINKGqMER9+d1TaDZqFmmoyZR5jKaKqO43YZajFDEl/ZftWhYFOLVvv2ZC0N/F3+2Lp\n42yLLVo81ryorszQgfrIpKAMnt1AveRyO2K49wrbh0uq0dLRsISk6Yy3Xcyo8NnYKZL2Ifr7H6VC\noarvSXLt3slRuPwA/F7SgcA1RI9NFavejgeZziDemJcSyhknEdWoNpnTBHTr2P4y8OXSq/4eSfsR\nE7an2nbN2B2wpKSlHDa9z6VugnIeofqw1Lx+sAUesn1Wuf0GhR12FQYVNRT2x/vViKMQ0R/kSaK/\n+0zbT07wKwsS62BCOm8Non3kk8xZim5B+ShwpkLv/NfAP1eKMxE/JpKiFxDX+7ZYHNiaWfuEaxmM\nHE3s1tVWZpjy2P69pNfa/kOlEItQEtZyv2Zr1t4Vjz1XKrVYQvRzr2S7itlL35Pk0wgL0VUIyaq2\nTTdG4fID8B7iQ2ELYop8v0pxqg8yDbC87eYNer7quOCNYgL658C+ZaDzS4RLYquDAyPgcMK96Cai\nJWe/irHOBe5kfLCtZiX5bElbEIO3XyGSoG/M/VcWHNt3NYO/FXgtYczzPWADQgrzXmJo670tx3qT\n7Tcr3BFPkfQvLR9/JrZ/RBQlOqFIRzbv2+mu40J6OvF6fxNwDxVMjiStbfvGDpUZFgoqJsgQr4tp\nwKqSLiYKB7W4iyEnS7ob6KzVYvlLKpqT9T1JPoa42GxKTDZ+jTDgaItOXX4kvd72dNuPEAlX8/jf\nAedXCNnFIFPDzZLeaPtqSWsRPV6LE71zT8zrlycjZYJ8G8Yr2GcSmo29xvZppU/4FcAvbf+2Yrgx\nd+dQuAfxPno+cJjtajtRQ3q1K1JP3WJZ2/9Ybh8r6TLb75VUo3K4WNnCnyFpUcLIqVU0setj1V5/\nSV8jEtffMz7xv06FUH+0fYik1W3vXKNQQNitr0IkPpcCl3U9mC3pLwlZ1pquqlMG20cptKVfA/y8\nzEDVorqTpaR1bV+nCVxBbdfwEXgO8FNJzf9bqy0kfU+SV7O9i6SNbF8o6RMtH79rl58vUbRAJX3b\ndmM+0Hy4t031QaYBNgLeLqlR7IDoaawiQVObsuJfGTibGIboQsKsKpI+bftzQwkeklrv6R5QH7lD\n0obE9nYzuNfqomnoYn0Fsai+uywOa5m/DLb7PE4s4muwrKQX2n5A0vLA88vis0b7ymGEuccKwI/K\n/VZxcX10twYwciVt7iFmlPaRZRTGLK1Xkh1mFEsAGwIbA7sqdP2/W1t+boDDgdslHWP77o5i9hZJ\n6xN9yUsCm5Trba1h/S6cLN8GXMfsrVgziPaftjm0wjFn0vckeTGF+PYMScswa+W3Dbp2+Rnchlhs\nDo+3yfAgU7XKmu1X1zr2iFiTeNN/gHFt5Gq6kx1xYfnehSFBMzgyxqwmETX+/4Yv1mZc5qnVi7bC\n0Ggr4He2v1MeexFRwdm2zViFzwI/kvQwkXT9G6FC0fpQou2zFW5gryQGEavtMCg0mBcjdu2OJKSr\n2nbsarhGkjqYJdifUDH4OnAHleZaHMZa1xNFj2WIqvjrasSaQ/xafeojpaJyzClEove7Fo85C5rV\nyXJ7Zi1KtDqAa7tJWvcdXCS1PQMiaQvbFxGqYMNteq3tivc9Sf40YUW4ImEq0qqr1Qh6XIcFzCe6\nvcAMVPF+Ub4gKg/VkLQbMaQy6KxWqyJfHdsva25LWtr2I5JWsn3PCE9rQdkS+Int70pa0XaVgVEA\n2y8fvF+2aH9bQfFkpixbWVC/3va3i+xSjWn104ie5xXLLs0viYT18AqxsH1R2dVYAfiN7RnEdmrr\nSNqSGPRdstzHdpvtbYMcROgiH00M+p5F+7a2DQ8B15ZZk2qtHbanEb2nEKYsrSNpT6LlcFngcsJd\n7RNtD3EOxRyshALUrISOjIrKMb+wfXKlYzcMut0N6lu37mQ5QO0ZkOXL9xe3eMzZ6HWSXJJYSVqB\n6K/ttdMPsEjZKl1k+HbLcQareIPUrILuQVy8q62WR4HC6XEJYB+iH/C6gZV033gr41alp1Hv4jkT\nSRsTOxgPAS+QtGszLFuBMxhPVh8kkuS2ZblWs71uWYheT0yqb2L7Z20GkXSU7d015A5WEtda2rtf\nJBa6XbyHHyX6uJ+yfZ+kmtf2twLLtSz3NhMNmEQNU6HNY19ikXQI0WJRLTkeoHoldBSU3em9CRWS\ni4AbXcf46JuSvkEM6QPQdmtMacNZtClClOf2WK3XfKH2DMgPSoX8jHJ/BnB/2z34vUySy7bHbBed\n8gFR/YO9IqsSCSxEAmvGt/BbY7iK1xE3Av9To1I4Yray/QYA21tLuprKPVIVGZvD7Zp8jlBNuEfS\nysC3CBOTGixdtuewfbqkXSvEeLgc/4nSC7qZ7QcrxGmsa6vJ2E3Azbav6ijWw0Syd5ykDwFtSkYN\ncyvwIio4nRUuBNYlXtenAr+qFAdiR2EjoiBxcBmAvAS42HatuF1UQkfBicT/3VuIQbevlttt8yHg\nm8TgaBUkvYbQvF/P9u+IvuEvSdrS9i3z+PVnGqurGZDB6nhT9FuhqLm01nfdyySZcc3MzxJyKVcD\n69ORWHt5ETzR9gdGV8nrcPVp6BxqVaGuJIa0bmd8S7PPC5qGpyU9pyRFTeW/r1Rr8ZkLf25aVGz/\nWtLj8/qFBeAJSZsSrVnrU0GdYYj/rZQgY7tRy3g+YRjxNHBw+ZrIMawNzi/XjplV8YrKJNsQVflb\nygf88ZXiQChb3CnpgXK/1XYL2x9uFkxEpbfR3T+LljVxS+X4yvKFpM2JXa6jqad3Xr0SOiKWt32i\npB0cRjq1ru2/7WD38XBgu5IgY/s8Sb8h5pH+puVYE82AbE/Lg3sTtb+Uv9EPif7/VuhlktwMWEh6\nkcfNAc6V9G8dncLrCUmzl/R0erfL6lPDbsQHX6dyRB1wDHBTkZ95FaE73VfeoHDXGwPWHLhd0z73\n4fK+nUa4TlVJKgu7EC0DRxAf6DWMHLp0fYR4/e1OfCh8inj9XVEhDsCHy/G7eA+/FPg7Se+msvGG\n7VfWOO5QjKeJyvilCunIrxCvw1ZVSCStS1SSNyKuRz8h2iHaNm4apHoldFSo6JsrdPBrtSY8IOlY\nZh2mO67lGIvYvm7wgZL4t+6N0MyADCOpqmKNQpbyTbS8C9rLJHkQSR9g3JmuE73dHvecNmxq+wRJ\nhzB7xbA1W+8h7gauLR8WUwbbX5V0AdHLfbvtB+b1O5OYtUcQcwdiAPcgInGtpplc+gn/vtbxC525\nPhYeJ2zen2P7h5JqVsfvs31mxeMPUt14o0HSSQxdB9uukJcK16ZERe11xDb++m3GKHyeqNZ9jjBF\n6WJHqItK6Cj4MOEMuwZwDlBrGLHpc24G0Gr8zea0i7D4HB5fYCQdQPgGPIdYDN5KqGnVYklC3afV\nYmnfk+T3ENWTbYgPivfUCFK2aD9GDGgB9L33udH0/XmHMZdg3MWtWS331jNe0oRDCKUvvitzjFax\nXWubfjYGJIkgttKrDF0MxWwMKsaILe87bK/RZowRKeJ8DbhY0jaELXUtHpN0KSGD1byHay2quzDe\naGgm7scIubRWlS0k/QexS3IVcJzt77d5/EFst711Pj90UQkdBZvbrqr6BGB7/1JlHbQrb5tLJH0R\nOND2Q5L+gnBSvbJCrIatCBv7w4AvA/9RMRYOE7Z3t33cXifJZer5QMalZ5YGamh3HkbIy1U1jNDs\nLlMNbUsSPSbpzYQ8VVcc0mGsLliXWB2fCjRtCcn808nQxSAeMKiQtCp17ba7YluiItkMGNVspbpw\n3j/SGtWNNxps/9fA3UsltW148M/E59I/Av9YlDqqugh2TBeV0FHwTkmH1R42l/RVQoJ1aeC5hIb2\nBi2H+TzwceAGSc8llEhOIdrPanGvQ7N7Gdu31Wjt6IJeJ8llhf4O4F7GVSBq9E7+yvblFY47C+7O\nZWrQOnkTYjXZ/P9Nm/A3FpxVKx13JNheuwwU7QB8gvh/O7WSRNCUo6uhi7nEv6vpN+w5SwB3AqsD\n7yWMN2r1dZ8GrEfdilfD/kRrTFXjDZhtGn9FQumiNWz3eZh3nnRUCR0FKwD3DEj41ZrNeC3RhnAs\n0e54TtsBStvNoXSrvHS3pJ2BR0pr57Idxm6NXifJRAVltQ76XH8j6Rhm3Wastp1UTAiOIcS3TwVu\naqSr2sADjkiSvtNR20OzrT1G9OQ9SGwT9xbbNxEJMqUyf4ikl9puuwow5ak1dDEUY9BueyVCh7fv\nnE5UxD9EfLgeRix8a3AukQitTPQ43sO4RmkrNMPQHjLekFRDeqthcBr/cSr2xU9FOqqEjoJO1LKI\nnu4ZClOqByR1FLY6uxEDuGcDOzK76kUv6HuSfBvRavFo5ThNW0JVZ5cBjiCcrY4ntBkvIcTMa9DJ\n1pjtTza3JY1R7/l0ShFl/wfiArA0dVzcFgaqDF0MMThI9zhw3Zx+sEc8TSSTn7L9jUrazw0vtL2h\npBOIv1MNPeuLJb11cABW0qeID9xVKsQDeND2npWOvTBQvRI6Iv5MLDrXJIbOPlopzvWS9iKq1t8g\nFhq9pRQ8FiV6/bclCh8nAP9JBwZVbdP3JHkV4C5JzRZ3le2Qsp30t8SFwLbPbzvGBDFvkzTD9v2S\n/lA7Xm2G+pFWBEZhaNIaZUhqO6KN5JvAP9u+c6Qn1WNqDV0ASHrfnP6Jnu9mEJXdfwemSdqEmCSv\nRVOMWNr2Y6rjgncAMWT0NuK5nUZoCa9TIVbDmpKWrTk0OsWZqpXQ4wmpvmnAxkTB6m1tB7G9Txmk\ne5xoH72m7RgdszOxWHox44Zofwb+e5Qn9Wzpe5LcSfm+9NOsTvyR3y9pI9t7VQz5oKTdgKUlbUfL\n+pND0m+rSTq4+beK0+qDVtiPAV+oFKcrvkGog/wEWItwtwL6rdoxRRlUsNieaFFo3clyROxESIud\nQPTwvr9irG9J+gyhUvND4I9tB7B9TjHl+TbRbna47aPbjjPEmsBvi5nI03Q0UCdpb+J1+EXXtQeu\nzXAltFXt5xGypO0Lyu3zJH2szYNPIME6g3CWvLrNOPM4hzMIedYv2G7F1dL28cDxknZ2+1bUndP3\nJHlxYGtmHRioITj/ZttvBJB0ODFcVJMPECuxBwgVhQ+0fPxB6bfPtHzsObGv7anUilCr7zNpmaFW\nnw0qLgRHwR2EPvyniQHch2sFGkxWJf0n46oGbcc5o2zZ7kpdp70m3qiGin9MyKa9ALh/ROewwExQ\nCf3RiE+pLRaTtJbtn0pai/YX1RNJsK5EODF2JeX3ESLPqDELMk3SJxnIz2xXMQSqSd+T5K4E5xeX\ntEgZEKxegbL9cEnGmxeXgB+0ePxT2jrWM2BXplC/7gj0cJN2mArV40GOJa59mwLXEu0j72wzwNDA\nI4xXvI4Cbq8UawxYDfjvpp2u1g5NSYBOJDRd7wN2tj29Qpy9gFNs3w+zSc/1luLytyPjFeR3MTWG\nHz8MnChpJeDXwAfbPPicPodLa2cVyuJzR6JN8EpCFKCWxF1nhkA16XuS3JXg/JnA1WWL8a8ZF5+v\nQjGq2ICpNS28hKTpRNvF05BtCUnSAqvZ3kXSm2xfKOkTFWJM5By4EpGQv7FirC4cCyEGpXex/RNJ\nrwOOpv3nBdGecq6k+4j+1ks7csSrzVeIBdN9oz6RNikLpfW6ileGwI8kNIxrUX1RPUCXhkDV6HuS\n3IngvO0vSfov4FXACbZvrhFngLWZetPCe4/6BJKFk6Hq5Kslnd782xRYqC0m6YUw80O2dTnMOe2a\nSNq9q1iVGbP9kxL/x5Kq9AfbPgY4pkh8fgo4thREDrddMzGqzcMj2p2siqSDiIr4zIVM5V71R4jP\n+rbNbAbpYlHd0JkhUE36niTvT2ztVBWcl7Q2UdW9GzhC0sG2r6gRqzCSaeHyPP9o+44Wj3mm7W2z\nPSEZIaOoTnbFp4hBnxWJWYk9ageU9DzgAmJXaCrwZ0lbAN8j7KP/VCOIpGUJRZz3EcPYexBSWRdR\np3JdlQETlock7QNcz7iPQM1Eryv+FniZ7Sqvh2FKO2dtadTqi+oBOsnPatPrJLkRnC8Xn9Vt1xpa\nOQbYnfijf4qQXKqZJI9KN3En4DZJ59u+u6VjrtDScZLkWTGVF2jlGihJKxADOKt1EPYPwO7FTGcq\nsDNhz/t54BZgl0pxriXmMraz/avmQUmvrxSvNo261EOE+tPq5f4M6lZDu2I6od/eSZLcEZ9m1kX1\nR2oEKQvp68r1CWJR3UvGZszoX0uUpHWInq71gS2JJPZ3wF62L6wQ70piavcC228vLnWtqxtI2tr2\n2ZJWJRzpHitxr7HdS3cwSXcRWqezMcVUBpJk5Ei6xvb6oz6PPiFpF9snDNz/sO0jKsQZA15JJJM3\nAr+eIj3JsyBpRdv3jvo8FhRJewIHEr3WY4Q04CtGe1bt0Cyqa7z+ShvWnsBTxGK61wOqfa0kfwF4\nv+0nJX0O2JyQI7oEaD1JJlbGXyPcoLYBnqwQA2A/SbcQC4D3Em9MA8+ngoVuGVL5ILFaBsB221PJ\njzJ1tmWTZLJTzdZ7qiFpe2ArYBNJjRPYIoTueetJMmEd/i5gOeAUImFuva+7ayQdAPwLYWSzFOFO\n9+qRnlQ7bEuYXnVqMiPpMGLI81DbrWiRSzrK9u6SfsBAj7UkKhiw/ROhyPU8osUik+QRsKjtG4s0\ny9K2bwCQVKu/Zluian0J4byzXaU4XyEuzgKOG3h8BnXsHE8mppL/p8KxG+6bikMdSTJJmXKVyYpc\nCtwLLE8MSUP0aLYqazfAdkTP8xW2/5+kayvF6ZqtCPm8w4AvA/8x2tNpjbuAR7rqSR7gZOAXtJuf\nHVi+v4/QVW9YrsUYDY/bfgJ4QLM67faSvibJTSV3c+BygOLStEyleOfZflO5/Z1KMbB9FHCUpF2L\na01t7hvcZqzE9ZWPnyQLHRNoF0NUkTvbDq7h1tUlRVHiKuAqSX/J+I5arc/FRYi/WfN3myq9rvfa\n/pOkZWzfNhUSo8JLgdslNYPsMypUXZF0FKGa9WOARmmlZcYk/RWxI97sUi9CLA5rtmf1fmerr0ny\n5ZKuJl7EW0lajaiInlkp3oOS9mBWjd+agwk3STqWWZ1q3l4hzp1FAmY6laaSK9t3J8nCypxUOrpU\n76jp1tUZko4mlAzuYdwsqvVkiDBXmAasKuli4LwKMUbB3ZJ2Bh4pVsvLjvqEWmLbjuJcBOwjaWVi\nsPO0CiIEGxBqKiIS4zEil6nRCtHIbE4Jyc1eDu4BSFoDeMj2PSVJXtv2uZVinTT00IwKvbuD8aYT\nChrvBn5KKHe8p0KcTp9XkiT9RdIShHOmgJuI6lctt67OkHQdsH6R4Kodaw3gNYBt31g7XhdIegHR\nf/og4eZ2he1bRnpSC0BJ9CdMjGoOm5dhusOJ9pVzgANtt+1o+U7bF7d5zAlivGVO/9ZHpaG+VpKx\n/bOB27dTr48M2zsN3pe0Yq1YhQdsnyFpM9v7SarywrK9k6TXAGsCtzbbPUmSJBNwCtGneTmwEWHl\n/P6RnlE73Ea0Wjxa4+BzSLpeL2m7KaLwc+FAO+KRIz2Tdvh5l8HKwmlHQqnrO8R7azHgLOANLYd7\nQtLmRKvFkcC+tk+fx+88I/qYCM+N3ibJXTKC6d2niyvTUgonkRrN9Uj6N2IS9UfAXpLOsv3FGrGS\nJOk9L7bdDC2fX2vxPgJWAe6SdFu533bvaadJ1wjouh2xNjfbvm7ALKU2xwEnAPvbnrlQK26MbXMQ\n8ZnfWK+fRbQBJXMgk+T5o+vp3Y8RSfgRxAv4q5Xi/BOwke2nyuDj9wlR/SRJEgAGBrF+KWk929cW\nd85bR3leLbL9vH9kgei9ZvA8+C3wuvIF/TcTeStwHbO/Lmo9r7snUoCyfXSFWI8ScrJP2b5PUj/7\nbTskk+T5o9PpXds3AzeXu2+Q9I5KocZsP1ViPimplv5zkiT9xUSCMAZsLOkJYlft8ZGeVXssDmzN\nwKA0sFuLx59TEt73ZBKY2ba3EpFPzLBdU1K0Orb/vXzfqQzTLUrd57X4wKKzqcQ/Mfdfedb8gZA+\nPE7Sh4DeqdJ0TSbJ80cn07uSdgQOJpz23k34nR8PrEFoNLfN1ZLOAb4HvImwq0ySJJmJ7Zc3t4tr\n3PK2HxjhKbXN6cC5xDXwHuAv2jz48ExLQwezLVWRtCZwlO23AlcSg3svkfQR298a7dk9e4ae1xXU\nf14Czmd8ITqDelKOWwOr2b6lzCN1ITXbaxYZ9Qn0hN2IN8v/JS6itWRMmjaLLYlkeRrRz7ZOjWC2\n9wROIiooJ9v+vzXiJEnSf8qO1m3AZZJulbTxiE+pLf5o+xBi23tH4EU1gkg6QNL9kh4qu3aX14jT\nIYcCHy+37y193G8FPjy6U2qFrp/XobZfbvsVzfe2A0japdzcD9hB0sFEHrNf27GmGpkkzwNJHwQW\nsX0X0XP1ZEV5mwdt/64cf03gE7Y/Y7vVNghJi0p6jqRvEdt9RwBXSrqyzThJkkwp9gM2sL0O4Rz3\n+dGeTmvMkPRiYBlJS9NyJXmAZrblNGJ38NeV4nTFUravK7cfArB9G/3foe76ee1a6biDNK0ivyDa\npwa/krnQ9xdzVSTtR2hango8RbzQPippBdsHzu13nyWDOp132a7RYgGwM7AP8GLiTTIG/Bn470rx\nkiTpP3+wfT9AGfp5ZNQn1BL7A+8Cvk60uH29Upyp5kz33OaG7b8feLzvsy1dP68lijfCoDpIq7vV\nthvTkO1sd6XaMSXIJHnuvIOonDRudHdK2pZQgaiRJC8vaVOiwv+8QQmaNiV1iuX18ZJ2tl1DZiZJ\nkilC2ZoFWEzSRcRien2miK2y7WnANEnLEsZNbbudNUw1Z7pfS1rf9jXNA5LWB+4b4Tm1QdfPa+9K\nx52I30nailmHBKeKSk0VMkmeO39sEuSGogLxh0rxbmC833k641PRtaagvy3p44SQPgC2D6gQJ0mS\n/uKh7xCDRr1G0jqEvOb6xBzIMUQSsZftCyuE3A14KXA2YR7RO4veIT4OXCDpCqJX/RXA24j/Y0GC\nSQAACHxJREFUyz7T9fO6gUiUVyIsqms6Mf4l8NGB+zOIfutkDmSSPHcek/QK23c0D0h6BXOwrFxQ\n5jQFXZGzieGRXkv2JElSj0bDVdJiRHK3CqFmcNMIT6sNvgC8vxQ+PgdsTiRFlwCtJcmS3jfBww8B\n6wK9tW+2/ctSYd0SeDmhLbyv7V634YzgeZ1IvObeQlSrv1put47tTWocdyqTSfLc2Rs4r6wo7yA+\nHN7O1LBihegx/PSoTyJJkl5wDKHusylwLfA14J0jPaMFY1HbNxaN36Vt3wAg6el5/N4z5QTCzvtC\nQlt6rOXjjwzbjxGubVOKjp/X8rZPlLSD7e9LqiaoIOkzwO7EjBUAtleqFW8qkEnyXLB9s6SNgL8j\ntkJuAA6wXavdomtukrQd0drR9F1nf1KSJBOxmu1dJG1k+0JJnxj1CS0gzSDW5hQ5tuI8ukzLcVYG\ntgO2AH4FnGb7qpZjJD1G0qvK95cwkMBWYEtg1bIISOaDTJLnge2HiIrJVGTQShSyPylJkjmzmKQX\nEpJpyzCrGk8fuVzS1USf8FaSVgOOAs5sM0hRBDkSOLLEeI+kfYDrbX+yzVhJL9mD8CtYAzgH+NeK\nsX5D/9VHOiWT5B4g6TtEtfdLtlvT1sz+pCRJngGfJlw5VwR+SHy49xbbh0q6AHjI9j0lgT3O9rkV\nw/6ZSFKeB7yyYpykB0h6HnC77Q0rxzmDKIK9CJguqZknmNG23NxUY2zGjCozaMkkRtI5tt8t6V7G\nhxDHiDdM9iclSTITSWvbvnHg/grAA8PKP8nEFKOSbcrXI8AZwLcqSs0lPUDS7sCeRHvF7gNaxjVi\nzXEQ0PZ3a8WdCmSSPAkpg4Lvt313uX+p7c1HfFpJkiyElJ2sVYDvApcCl9n+/WjPqj9IeoqQzzsT\n+F8G1JFsHzeq80pGi6TvAxsTuwpft/2OyvE+CJxo+6kya/Vq28fUjDkVyHaLyckqwDcl7VQsqpdo\n8+ADWy+zkVsvSZIMYnsTSUsAGxIf6ruWCfzvpq76fNEYT40RLqdJAvC47SeAB2q7L0r6LLAW3bkH\nTxkySZ6c/A9hHX22pI/S/rRrrh6TJJlvip3y9cByhPrDOsw69JvMme8A99i+bdQnkkxaassCvpNu\n3YOnDNX0+JIFYsz2nYRcyxeA1ds8eOlBEnB1uf00sEb2JiVJMoykPUsL2FXAXxOuYJvZ/oeRnlh/\n2B84QNLyoz6RZFLxakmnl53d5vbpkk6vEGtC92BgqsjZViMryZOTwwFs3ydpc+CgNg+eWy9JkjwD\n9iV6kQ8hWixSQuoZ0KgISVpV0quBX5UiSLJws83A7dq7u526B08lcnBvEjKRjant1rSaJf2Iga2X\n8tjiwPdtr9dWnCRJ+k+5NmxEbNm+GbiXsNG92PavRnlufUDS0sA3gOWBOwnpt/uB7VPhIumCsjg7\nA5jNPdj29FGe22QnK8mTkzXK9zGi7+9B2jU0mXDrRVJuvSRJMgulcnxl+aLsbu0DHA0sOsJT6wuH\nAmcPFjok7UK00u02srNKFhoWAvfgamSSPAkZdGGSNEb0ALZJbr0kSTJfSFqXqCRvBLwK+AlwCrDD\nKM+rR7zW9u6DD9g+QdIHRnVCycLHFHcPrkYmyZOQITmYFYGXtxxib+C8Mowzy9ZLy3GSJOk/nwcu\nAz4HTE8TkWfMnHq421YtSpKkZTJJnpyYqOqOAY8R23LtHTy3XpIkmU9s/82oz6HnPChpXdvXNQ+U\n6vyDIzynJEnmgxzcm4RI2sH2qaM+jyRJkmTBkPQy4AJCQu92Ymfwb4Atbf9ydGeWJMm8SJ3kycmu\noz6BJEmSZMEpcm/rE7bezwGuAf46E+QkmfxkJXkSIumHhBV103YxI+2ikyRJkiRJuiN7kicne4/6\nBJIkSZIkSRZmst1ikiHpg6RddJIkSZIkyUjJJHkSIWk/YDOibw3CLnozSfuO7KSSJEmSJEkWQjJJ\nnly8A9ja9qMwc+BjW2CrUZ5UkiRJkiTJwkYmyZOLCe2igdQvTpIkSZIk6ZBMkicXjxV76JmkXXSS\nJEmSJEn3pLrF5CLtopMkSZIkSSYBqZM8yZD0fMbtou8CLkq76CRJkiRJkm7JJDlJkiRJkiRJhsie\n5CRJkiRJkiQZIpPkJEmSJEmSJBkik+QkSZKeI+lOSS8b9XkkSZJMJTJJTpIkSZIkSZIhUgIuSZKk\nQySNAZ8H3gU8BRwL/Bg4CFgKeAHwcdtnSzoZeAh4A/ASYH/bJ0laDjgVeClwC7DkPGJuDOwDPAqs\nAfwU+CdCRec8QnJyLeA64Cpgx3Ie77L9s1aeeJIkSc/ISnKSJEm3vBt4I5GUrg/sBOwL7GJ7HeAD\nwGcGfv6lwEbAlsAXy2MHADfYXgs4GnjRfMT9P8DuRJLcaLADrA0cCAhYD3iZ7Q2BM4APPrunmCRJ\n0n+ykpwkSdItbwHOsv0n4E/A6yQtCWwhaWtgA+AvBn7+MtszJN0ELFce2xjYHsD2NEl3zEfcm2zf\nDSDpZwPHus/29PL43cAV5fG7gJc/y+eYJEnSe7KSnCRJ0i1PDt4pA3ffI6rK1xNtF2MDP/I4gO1B\nUfsZzHr9fmo+4j4+9PtNjCeGfm5+jpUkSTLlySQ5SZKkW6YB/yBpcUlLAZcBrwE+Y/tiYDNg0Xkc\n43JgBwBJ6wGvrHi+SZIkCyXZbpEkSdIhts+VtC5wA1GoOIxIcm+W9DDwA2ApSUvP5TCfBU6WdDPw\nc2LwLkmSJGmRtKVOkiRJkiRJkiGykpwkSTIFkLQRcOQc/vmdtu/p8nySJEn6TlaSkyRJkiRJkmSI\nHNxLkiRJkiRJkiEySU6SJEmSJEmSITJJTpIkSZIkSZIhMklOkiRJkiRJkiEySU6SJEmSJEmSITJJ\nTpIkSZIkSZIh/j/WH/wbyOAYwQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x167a43c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Average\n",
    "avg_donations = doner_df.groupby(\"cand_nm\").mean().sort_values(by=\"contb_receipt_amt\")\n",
    "avg_donations[\"contb_receipt_amt\"].plot(kind=\"bar\",figsize=(12,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Thats a bit easier to see and understand just how much Hillary out funded everyone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2a4f08d0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAE4CAYAAACZqQIcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ns6QlqWCWtCQV7P8BD/CV6u6AwaYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x66a2470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "doner_df.groupby('Party')['contb_receipt_amt'].sum().sort_values().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### While there were a ton of Republican canidates the Democrats specifically Hillary significantly out raised them in total\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets look at donations by Careers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pivot table much like in excel\n",
    "job_pt = doner_df.pivot_table('contb_receipt_amt', index='contbr_occupation', columns = 'Party', aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ADMINISTRATIVE ASSISTANT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>150.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARTIST</th>\n",
       "      <td>NaN</td>\n",
       "      <td>100.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATTORNEY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2100.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2100.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAREER ADVISOR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>50.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CERTIFIED REGISTERED NURSE ANESTHETIS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2927.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2927.72</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party                                   3rd Party  Democrat  Republican  \\\n",
       "contbr_occupation                                                         \n",
       " ADMINISTRATIVE ASSISTANT                     NaN    150.00         NaN   \n",
       " ARTIST                                       NaN    100.00         NaN   \n",
       " ATTORNEY                                     NaN   2100.50         NaN   \n",
       " CAREER ADVISOR                               NaN     50.00         NaN   \n",
       " CERTIFIED REGISTERED NURSE ANESTHETIS        NaN   2927.72         NaN   \n",
       "\n",
       "Party                                     Total  \n",
       "contbr_occupation                                \n",
       " ADMINISTRATIVE ASSISTANT                150.00  \n",
       " ARTIST                                  100.00  \n",
       " ATTORNEY                               2100.50  \n",
       " CAREER ADVISOR                           50.00  \n",
       " CERTIFIED REGISTERED NURSE ANESTHETIS  2927.72  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_pt[\"Total\"] = job_pt.sum(axis=1)\n",
    "job_pt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_pt = job_pt.sort_values(by=\"Total\",ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 127268 entries, SERVICE SALES REPRESENTATIVE to RETIRED\n",
      "Data columns (total 4 columns):\n",
      "3rd Party     3290 non-null float64\n",
      "Democrat      79117 non-null float64\n",
      "Republican    61340 non-null float64\n",
      "Total         127268 non-null float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 4.9+ MB\n"
     ]
    }
   ],
   "source": [
    "job_pt.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Okay so this has 127,268 'jobs' but includes blanks errors and duplicates so we clearly dont want all<br><br>Lets try grouping by ammount donated and see if that gets us some cleaner information lets try 2 million"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_pt = job_pt[job_pt['Total'] > 2000000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44, 4)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 44 jobs are over $2,000,000\n",
    "job_pt.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INVESTMENTS</th>\n",
       "      <td>18884.75</td>\n",
       "      <td>6.567254e+05</td>\n",
       "      <td>1.353727e+06</td>\n",
       "      <td>2.029337e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EDUCATOR</th>\n",
       "      <td>9771.80</td>\n",
       "      <td>1.883753e+06</td>\n",
       "      <td>1.672757e+05</td>\n",
       "      <td>2.060800e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENTREPRENEUR</th>\n",
       "      <td>17053.00</td>\n",
       "      <td>1.285851e+06</td>\n",
       "      <td>8.152827e+05</td>\n",
       "      <td>2.118187e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BANKER</th>\n",
       "      <td>6304.70</td>\n",
       "      <td>1.098698e+06</td>\n",
       "      <td>1.014728e+06</td>\n",
       "      <td>2.119731e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARCHITECT</th>\n",
       "      <td>12008.49</td>\n",
       "      <td>1.735440e+06</td>\n",
       "      <td>4.588543e+05</td>\n",
       "      <td>2.206302e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FARMER</th>\n",
       "      <td>10176.55</td>\n",
       "      <td>5.318559e+05</td>\n",
       "      <td>1.692710e+06</td>\n",
       "      <td>2.234742e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSYCHOLOGIST</th>\n",
       "      <td>12250.00</td>\n",
       "      <td>2.117766e+06</td>\n",
       "      <td>1.345607e+05</td>\n",
       "      <td>2.264577e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPA</th>\n",
       "      <td>21170.95</td>\n",
       "      <td>1.128238e+06</td>\n",
       "      <td>1.308780e+06</td>\n",
       "      <td>2.458188e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARKETING</th>\n",
       "      <td>13616.45</td>\n",
       "      <td>1.986465e+06</td>\n",
       "      <td>5.504764e+05</td>\n",
       "      <td>2.550558e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACCOUNTANT</th>\n",
       "      <td>25204.50</td>\n",
       "      <td>1.545158e+06</td>\n",
       "      <td>1.054324e+06</td>\n",
       "      <td>2.624687e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REALTOR</th>\n",
       "      <td>9785.00</td>\n",
       "      <td>1.679468e+06</td>\n",
       "      <td>1.132490e+06</td>\n",
       "      <td>2.821743e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SELF EMPLOYED</th>\n",
       "      <td>23545.75</td>\n",
       "      <td>1.340535e+06</td>\n",
       "      <td>1.497272e+06</td>\n",
       "      <td>2.861353e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIRECTOR</th>\n",
       "      <td>19953.60</td>\n",
       "      <td>2.282283e+06</td>\n",
       "      <td>6.664497e+05</td>\n",
       "      <td>2.968686e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CONDUIT TOTAL LISTED IN AGG. FIELD</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.096980e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.096980e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VICE PRESIDENT</th>\n",
       "      <td>6029.45</td>\n",
       "      <td>2.034357e+06</td>\n",
       "      <td>1.058275e+06</td>\n",
       "      <td>3.098661e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FINANCE</th>\n",
       "      <td>41934.68</td>\n",
       "      <td>1.922821e+06</td>\n",
       "      <td>1.302961e+06</td>\n",
       "      <td>3.267716e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAIRMAN</th>\n",
       "      <td>13738.40</td>\n",
       "      <td>1.093243e+06</td>\n",
       "      <td>2.232494e+06</td>\n",
       "      <td>3.339475e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARTIST</th>\n",
       "      <td>30383.00</td>\n",
       "      <td>3.060754e+06</td>\n",
       "      <td>2.698506e+05</td>\n",
       "      <td>3.360987e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PARTNER</th>\n",
       "      <td>3445.00</td>\n",
       "      <td>2.251080e+06</td>\n",
       "      <td>1.190405e+06</td>\n",
       "      <td>3.444931e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SELF-EMPLOYED</th>\n",
       "      <td>24622.00</td>\n",
       "      <td>3.628544e+05</td>\n",
       "      <td>3.671933e+06</td>\n",
       "      <td>4.059410e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOFTWARE ENGINEER</th>\n",
       "      <td>155812.17</td>\n",
       "      <td>3.941078e+06</td>\n",
       "      <td>4.105275e+05</td>\n",
       "      <td>4.507417e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STUDENT</th>\n",
       "      <td>42628.07</td>\n",
       "      <td>3.709696e+06</td>\n",
       "      <td>9.290034e+05</td>\n",
       "      <td>4.681327e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WRITER</th>\n",
       "      <td>58619.96</td>\n",
       "      <td>4.696448e+06</td>\n",
       "      <td>3.928428e+05</td>\n",
       "      <td>5.147911e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SALES</th>\n",
       "      <td>45785.38</td>\n",
       "      <td>2.540823e+06</td>\n",
       "      <td>3.243667e+06</td>\n",
       "      <td>5.830276e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BUSINESS OWNER</th>\n",
       "      <td>42160.66</td>\n",
       "      <td>1.870745e+06</td>\n",
       "      <td>4.057967e+06</td>\n",
       "      <td>5.970873e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INVESTOR</th>\n",
       "      <td>69264.00</td>\n",
       "      <td>2.542662e+06</td>\n",
       "      <td>3.401620e+06</td>\n",
       "      <td>6.013546e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MANAGER</th>\n",
       "      <td>82777.36</td>\n",
       "      <td>4.113470e+06</td>\n",
       "      <td>2.902017e+06</td>\n",
       "      <td>7.098265e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REAL ESTATE</th>\n",
       "      <td>41567.55</td>\n",
       "      <td>3.084272e+06</td>\n",
       "      <td>4.097864e+06</td>\n",
       "      <td>7.223703e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEACHER</th>\n",
       "      <td>70832.40</td>\n",
       "      <td>6.771090e+06</td>\n",
       "      <td>9.592108e+05</td>\n",
       "      <td>7.801134e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ENGINEER</th>\n",
       "      <td>151310.23</td>\n",
       "      <td>4.909299e+06</td>\n",
       "      <td>3.634184e+06</td>\n",
       "      <td>8.694793e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PROFESSOR</th>\n",
       "      <td>64964.25</td>\n",
       "      <td>9.683826e+06</td>\n",
       "      <td>5.585040e+05</td>\n",
       "      <td>1.030729e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OWNER</th>\n",
       "      <td>47775.71</td>\n",
       "      <td>4.355606e+06</td>\n",
       "      <td>6.240037e+06</td>\n",
       "      <td>1.064342e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXECUTIVE</th>\n",
       "      <td>62106.34</td>\n",
       "      <td>4.995736e+06</td>\n",
       "      <td>6.227872e+06</td>\n",
       "      <td>1.128571e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRESIDENT</th>\n",
       "      <td>53596.45</td>\n",
       "      <td>6.048134e+06</td>\n",
       "      <td>7.937873e+06</td>\n",
       "      <td>1.403960e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAWYER</th>\n",
       "      <td>48255.73</td>\n",
       "      <td>1.249978e+07</td>\n",
       "      <td>2.281451e+06</td>\n",
       "      <td>1.482948e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INFORMATION REQUESTED PER BEST EFFORTS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.529517e+07</td>\n",
       "      <td>1.529517e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CONSULTANT</th>\n",
       "      <td>103017.70</td>\n",
       "      <td>1.240737e+07</td>\n",
       "      <td>3.875750e+06</td>\n",
       "      <td>1.638614e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEO</th>\n",
       "      <td>75970.60</td>\n",
       "      <td>8.035269e+06</td>\n",
       "      <td>8.839239e+06</td>\n",
       "      <td>1.695048e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHYSICIAN</th>\n",
       "      <td>151211.88</td>\n",
       "      <td>1.343999e+07</td>\n",
       "      <td>6.999147e+06</td>\n",
       "      <td>2.059035e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HOMEMAKER</th>\n",
       "      <td>117034.51</td>\n",
       "      <td>1.237521e+07</td>\n",
       "      <td>1.659512e+07</td>\n",
       "      <td>2.908736e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOT EMPLOYED</th>\n",
       "      <td>1315.00</td>\n",
       "      <td>3.116304e+07</td>\n",
       "      <td>2.171659e+05</td>\n",
       "      <td>3.138152e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INFORMATION REQUESTED</th>\n",
       "      <td>9527.50</td>\n",
       "      <td>1.980982e+07</td>\n",
       "      <td>1.990326e+07</td>\n",
       "      <td>3.972261e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATTORNEY</th>\n",
       "      <td>166154.85</td>\n",
       "      <td>4.129244e+07</td>\n",
       "      <td>1.022316e+07</td>\n",
       "      <td>5.168176e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIRED</th>\n",
       "      <td>835991.40</td>\n",
       "      <td>7.735237e+07</td>\n",
       "      <td>8.732449e+07</td>\n",
       "      <td>1.655129e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party                                   3rd Party      Democrat    Republican  \\\n",
       "contbr_occupation                                                               \n",
       "INVESTMENTS                              18884.75  6.567254e+05  1.353727e+06   \n",
       "EDUCATOR                                  9771.80  1.883753e+06  1.672757e+05   \n",
       "ENTREPRENEUR                             17053.00  1.285851e+06  8.152827e+05   \n",
       "BANKER                                    6304.70  1.098698e+06  1.014728e+06   \n",
       "ARCHITECT                                12008.49  1.735440e+06  4.588543e+05   \n",
       "FARMER                                   10176.55  5.318559e+05  1.692710e+06   \n",
       "PSYCHOLOGIST                             12250.00  2.117766e+06  1.345607e+05   \n",
       "CPA                                      21170.95  1.128238e+06  1.308780e+06   \n",
       "MARKETING                                13616.45  1.986465e+06  5.504764e+05   \n",
       "ACCOUNTANT                               25204.50  1.545158e+06  1.054324e+06   \n",
       "REALTOR                                   9785.00  1.679468e+06  1.132490e+06   \n",
       "SELF EMPLOYED                            23545.75  1.340535e+06  1.497272e+06   \n",
       "DIRECTOR                                 19953.60  2.282283e+06  6.664497e+05   \n",
       "CONDUIT TOTAL LISTED IN AGG. FIELD            NaN  3.096980e+06           NaN   \n",
       "VICE PRESIDENT                            6029.45  2.034357e+06  1.058275e+06   \n",
       "FINANCE                                  41934.68  1.922821e+06  1.302961e+06   \n",
       "CHAIRMAN                                 13738.40  1.093243e+06  2.232494e+06   \n",
       "ARTIST                                   30383.00  3.060754e+06  2.698506e+05   \n",
       "PARTNER                                   3445.00  2.251080e+06  1.190405e+06   \n",
       "SELF-EMPLOYED                            24622.00  3.628544e+05  3.671933e+06   \n",
       "SOFTWARE ENGINEER                       155812.17  3.941078e+06  4.105275e+05   \n",
       "STUDENT                                  42628.07  3.709696e+06  9.290034e+05   \n",
       "WRITER                                   58619.96  4.696448e+06  3.928428e+05   \n",
       "SALES                                    45785.38  2.540823e+06  3.243667e+06   \n",
       "BUSINESS OWNER                           42160.66  1.870745e+06  4.057967e+06   \n",
       "INVESTOR                                 69264.00  2.542662e+06  3.401620e+06   \n",
       "MANAGER                                  82777.36  4.113470e+06  2.902017e+06   \n",
       "REAL ESTATE                              41567.55  3.084272e+06  4.097864e+06   \n",
       "TEACHER                                  70832.40  6.771090e+06  9.592108e+05   \n",
       "ENGINEER                                151310.23  4.909299e+06  3.634184e+06   \n",
       "PROFESSOR                                64964.25  9.683826e+06  5.585040e+05   \n",
       "OWNER                                    47775.71  4.355606e+06  6.240037e+06   \n",
       "EXECUTIVE                                62106.34  4.995736e+06  6.227872e+06   \n",
       "PRESIDENT                                53596.45  6.048134e+06  7.937873e+06   \n",
       "LAWYER                                   48255.73  1.249978e+07  2.281451e+06   \n",
       "INFORMATION REQUESTED PER BEST EFFORTS        NaN           NaN  1.529517e+07   \n",
       "CONSULTANT                              103017.70  1.240737e+07  3.875750e+06   \n",
       "CEO                                      75970.60  8.035269e+06  8.839239e+06   \n",
       "PHYSICIAN                               151211.88  1.343999e+07  6.999147e+06   \n",
       "HOMEMAKER                               117034.51  1.237521e+07  1.659512e+07   \n",
       "NOT EMPLOYED                              1315.00  3.116304e+07  2.171659e+05   \n",
       "INFORMATION REQUESTED                     9527.50  1.980982e+07  1.990326e+07   \n",
       "ATTORNEY                                166154.85  4.129244e+07  1.022316e+07   \n",
       "RETIRED                                 835991.40  7.735237e+07  8.732449e+07   \n",
       "\n",
       "Party                                          Total  \n",
       "contbr_occupation                                     \n",
       "INVESTMENTS                             2.029337e+06  \n",
       "EDUCATOR                                2.060800e+06  \n",
       "ENTREPRENEUR                            2.118187e+06  \n",
       "BANKER                                  2.119731e+06  \n",
       "ARCHITECT                               2.206302e+06  \n",
       "FARMER                                  2.234742e+06  \n",
       "PSYCHOLOGIST                            2.264577e+06  \n",
       "CPA                                     2.458188e+06  \n",
       "MARKETING                               2.550558e+06  \n",
       "ACCOUNTANT                              2.624687e+06  \n",
       "REALTOR                                 2.821743e+06  \n",
       "SELF EMPLOYED                           2.861353e+06  \n",
       "DIRECTOR                                2.968686e+06  \n",
       "CONDUIT TOTAL LISTED IN AGG. FIELD      3.096980e+06  \n",
       "VICE PRESIDENT                          3.098661e+06  \n",
       "FINANCE                                 3.267716e+06  \n",
       "CHAIRMAN                                3.339475e+06  \n",
       "ARTIST                                  3.360987e+06  \n",
       "PARTNER                                 3.444931e+06  \n",
       "SELF-EMPLOYED                           4.059410e+06  \n",
       "SOFTWARE ENGINEER                       4.507417e+06  \n",
       "STUDENT                                 4.681327e+06  \n",
       "WRITER                                  5.147911e+06  \n",
       "SALES                                   5.830276e+06  \n",
       "BUSINESS OWNER                          5.970873e+06  \n",
       "INVESTOR                                6.013546e+06  \n",
       "MANAGER                                 7.098265e+06  \n",
       "REAL ESTATE                             7.223703e+06  \n",
       "TEACHER                                 7.801134e+06  \n",
       "ENGINEER                                8.694793e+06  \n",
       "PROFESSOR                               1.030729e+07  \n",
       "OWNER                                   1.064342e+07  \n",
       "EXECUTIVE                               1.128571e+07  \n",
       "PRESIDENT                               1.403960e+07  \n",
       "LAWYER                                  1.482948e+07  \n",
       "INFORMATION REQUESTED PER BEST EFFORTS  1.529517e+07  \n",
       "CONSULTANT                              1.638614e+07  \n",
       "CEO                                     1.695048e+07  \n",
       "PHYSICIAN                               2.059035e+07  \n",
       "HOMEMAKER                               2.908736e+07  \n",
       "NOT EMPLOYED                            3.138152e+07  \n",
       "INFORMATION REQUESTED                   3.972261e+07  \n",
       "ATTORNEY                                5.168176e+07  \n",
       "RETIRED                                 1.655129e+08  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_pt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# remove these rows\n",
    "job_pt.drop(['INFORMATION REQUESTED PER BEST EFFORTS', 'INFORMATION REQUESTED', 'RETIRED', \n",
    "             'CONDUIT TOTAL LISTED IN AGG. FIELD'],axis=0,inplace=True)\n",
    "\n",
    "#combine like rows\n",
    "job_pt.loc['SELF-EMPLOYED'] = job_pt.loc['SELF-EMPLOYED'] + job_pt.loc['SELF EMPLOYED']\n",
    "#remove self employed without dash\n",
    "job_pt.drop('SELF EMPLOYED',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2caa39b0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsAAAAOQCAYAAAA31sesAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XuYpFV57/1viSAgjQgUIlEBD7mN0W3ExBPGjBgUQbeH\n/aIjCKIZBUTUgFsxapQQEgTxRHZAERhhg4jRSFAkwZDRCPEQVPSVlx8EjFEUuhHiDHKSod4/6mkt\ny+6enpnu6a5+vp/rmmvqWc9a61n3mobr7tV3VXd6vR6SJElSW9xvoRcgSZIkbUomwJIkSWoVE2BJ\nkiS1igmwJEmSWsUEWJIkSa1iAixJkqRWuf9CL0Cj49571/Zuu+2OhV7Ggnrwg7emzXtg/O2OH9wD\n4293/OAejFL83e5YZ7p7ngBr1u5//80WegkLru17YPztjh/cA+Nvd/zgHiyV+E2AJUmS1ComwJIk\nSWoVE2BJkiS1igmwJEmSWsVPgdDsdTp0F3oNi0Db92Ay/onx1Qu6DkmSNpQnwJIkSWoVT4DnQFW9\nFfhTYHdgDPhUc+v3gGuBO4BzgAOAzYDHAuPArcClSY6vqicCJwBbAVsA/wIcm+SeqloJ7NH07wA7\nACcnOauq3gPsCzwjyb3Ner4KLAd2Ay4Arh5Y7kSz1q8Bz0pyfTPmhcAxTdvaOdweSZKkRcUEeG68\nEjgfWJ5kJbAMoKpWAYcluabpd0bTvhI4P8klzfVDgE8AL05ybVV1gHcBHwCOaMa+daD/9sD3mnmg\nn+i+HThuirVdlmT5cGNVHQOcWVXLgO2Ak4Dnm/xKkqSlzhKIjdQkkNcDp/GrZHV9HQScmeRagCQ9\n+snsvlW11RT9dwbuavoBnAgcWFVPmu0Dk5wD3AIcCrwPOD7J9zdw/ZIkSSPDE+CNtwL4WJJU1d1V\n9dQkX1vPOR4JXDrYkKRXVTcBD2maTqyqdwC70i9p2H+g++3A64CVVfWUobn3ak6iJ30+yUnN68OA\nfwO+0STEM+rQW1cXtclOC72AhTK20AtYBNq+B8avtu/BxsXfWwTphAnwRqiqB9Ovv92pqo4EHgS8\ngX597fq4kX4Zw+DcmwG70K8VhqYEoqr2Bd5L/9T5l5J8uaq+CPzF0NxTlkA0Yyaq6iv0yzckSZLm\n3cTEmk3ynG53+kTdEoiN80rgjCTPTbIP8FTguVW1vp+U9XHgdVX1GICmBvjdwMVJ7hjsmORi4LPA\nR6eY5x30E/JHr+fzJUmSWsMEeOOsoP/pDgA0yeqngdeuzyRJfkS/Dvhvq+py+ifIWwJvnmbIccDj\nqmq/oXnuAl5N/yR60l5VtWroz1R1xZIkSa3Q6S2GQgyNhI5FwJIkaSONj2+yEojOdPc8AZYkSVKr\n+CY4zVqvt+kK1xerbnes1Xtg/O2OH9wD4293/OAeLJX4PQGWJElSq5gAS5IkqVVMgCVJktQqJsCS\nJElqFRNgSZIktYoJsCRJklrFBFiSJEmtYgIsSZKkVjEBliRJUquYAEuSJKlV/FXImr1Oh27zcmJ8\n9YIuRZIkaUN5AixJkqRWWZInwFW1DLgQeHySHzZtJwDXJFlZVdsAxwNPAnrAauDoJNdW1cnAk4Gd\nga2BG4CJJPsPzH8I8BfNvUnfTXJkVa0CHpLkdwb6vxT4NLA7sGxgbA/YEvhAkguasYcluWYont2B\n9wE7AJsDVwFva25/Gzg4yeVN3z2Ac4E/AP5f4L+A+wamOxoYAy4ArgY6zZwfTHLBundXkiRptC3J\nBLhxN3BWVe2dpDd073TgiiRvAqiqJwKfraqnJzm6aTsEeGySY6aZ/7wZ7lFVv5fk283lcuAHU42t\nqu2B71TVp6aZZyvgH4AVSb7WtL0K+ESSF1TVa4CPNYnv2ia2Q5LcXlUAz01y19Ccy4DLkixvrrcB\nvlRV1w6sWZIkaUlayiUQlwG3AkcMNlbVjsATkpwy2ZbkKuAi4KVz9OxPAK9onrcd/VPem6bpux1w\n5xRJ+qT9gC9NJr/Nej8O7FhVuyf5EnAx8G76p8KfHew7G0luBz4C/D/rM06SJGkULeUTYIDDga9X\n1SUDbY8Erp+i7w3Arusx9wFV9bSB6zOSnNO8vgg4u6qOoZ9U/h3w+inG3gfcARw0w3OmW+/3m/V+\nH3gH8FXgFuB5Q/3+qaomSyDWJnnONM+5GdhjhnXQYSBH32mmnkvd2EIvYIEZv9q+B8a/IXrTHfOM\noG633V8DSyH+JZ0AJ/lpVb0Z+DhwedP8Y6ZOdB9DvyZ2tmYqgbgT+BbwdODF9EsgBhPgGcsnhtwI\nPGWK9kfTr+8lyV1V9VngpiRrh/r9RgnENHYFfjTLNUmStF4mJtYs9BLmRLc7tmRi2RCjFP9MifpS\nLoEAIMlFQIBDmusfAddX1S9LI5r62RcCn5nDR58HHAXc1pQYbKgLgb2r6pdJcFWtAG5JcsP0w2av\nqrYFXgtMWYcsSZK0lCzpE+ABbwYGf/R/MHBSVX2N/hvHbgNenOS/12PO4RKInyV50cD1F+mfPL96\nPdf6d1U1eWK7KslbquqFwAeqagf6/2bfoakxnoXBEgiAD9GPd6/mUyfWNnO+O0nWc62SJEkjp9Nb\nSkU5mledXysCliRp9sbHR+PH5usySiUA82GU4u92xzrT3VvyJRCSJEnSoLaUQGgO9HpL500MG2qU\nvvOdD8bf7vjBPTD+dsevpcMTYEmSJLWKCbAkSZJaxQRYkiRJrWICLEmSpFYxAZYkSVKrmABLkiSp\nVUyAJUmS1ComwJIkSWoVE2BJkiS1igmwJEmSWsVfhazZ63ToLvQaFoG274Hxz62J8dVzPKMkaV08\nAZYkSVKreAI8pKqWAYclWT7QdgJwDfB54H3ArsBmwA+Bo5LcVFWHAGcBT0/y1Wbc5sBPgL9J8p6q\nuge4YuiRBwJ7r2ts0/YU4CvAnkm+0bQdAjw2yTHN9ZuAlwP7AX8PbA3cMfC8k4DvAd8Bvtm0bQnc\nDuyf5LYN2TdJkqRRYQI8ex3gM8D7klwIUFV/DHyuqp7a9LkGWA58tbneB/jZwBy3Jlk2PHFVzWYs\nwGuBk4EjgEOmmOd/A88D9k7y82beg5NcM9RvN+DqwbVU1V8Df0I/wZckSVqyLIGYvR2An00mvwBJ\nvghcDzyrafoCsHdVTe7rK4BPzHL+GcdW1TbAXsCxwJ5VtePg4Kp6R3N/vyQ/X5/AqqoDPBzw9FeS\nJC15ngBPba+qWjVw/Ujgb+gnu8NuoF8SAXAP8G/AH1XVvwPbAj8Cdm7ubz80741JDpzl2OXAZ5Lc\nVVWfpH9a+97m3oHAdcCD6Z9UDzq7qgZLIPZv/n5cs5btga2Ac4GPTxGfJEnSkmICPLXLpqgB3hzY\nbYq+jwEuBR7RXJ9H//T2EfRLJrYY6DtlCcSAmcauAO6tqkvo1/U+rKpOau59C3gxcCL9RH3FwLip\nSiAeSFMCUVVbARcBNye5d4a10aE3021pXvWW6JffKH6qRrc7ttBLWFDG3+74wT1YCvGbAM/ej4Gd\nq+qFSS4CqKp9gEcDXwIOavqtAj4I7AIc0PyZrSnHVtUTgM2SPG2yY1VdCrygubw6yX1V9WfAv1XV\nQUnOmc0Dk9xZVQcC366qK5JctR7rlTaZiYk1C70Eut2xRbGOhdT2PTD+dscP7sEoxT9Tom4CPHs9\n4IXAB5tEE/qfArFfkrXNG85oEtFLgYcnWT3Z3hgugQB4++SLGca+FhhOaE8H3kD/1Hhy/D1VdQDw\n5aq6smkeLoH4JP16YwbG3VxVbwE+UlXPSHLfujZDkiRpVHV6S/XnippzHWsgtIDGxxf+xGGUTj7m\nS9v3wPjbHT+4B6MUf7c7Nvy+qF/yUyAkSZLUKpZAaNZ6vcVRh7mQRuk73/nQ9vglSUuDJ8CSJElq\nFRNgSZIktYoJsCRJklrFBFiSJEmtYgIsSZKkVjEBliRJUquYAEuSJKlVTIAlSZLUKibAkiRJahUT\nYEmSJLWKCbAkSZJa5f4LvQCNkE6H7kKvYRGY7z2YGF89z0+QJKndPAGWJElSq3gCvJGqahlwAXA1\n0AO2As4Fngycn+SSgb43AY8Bvg0cnOTypn2PZswfAI8D/pL+NydjwAVJTq6q3Zr5ntaMeR3wSuA+\nYHPgHUlWVdUhwGOTHNP02wX4D+BVST41sOYLgccn+WHTdgJwTZKVc75JkiRJi4gnwHPjsiTLkjwb\n+CPgaGC7qTomWQO8BvhYVW1VVVsApwOHJLkd+BvgjUn+GHgmsLyqnjQ4R1UtB/YGnpNkGf1E+Jyq\n2nGKR74a+DBwxFD73cBZVdXZoIglSZJGlAnw3BsD1gL3TtchyZeAi4F3A28DPpvka83tm4E3VNWT\n6Z/u7pnkW0NTHAr8VZJfNPN9H/i9JLcMdmqS24OAk4EtqurxA7cvA27lNxNjSZKkJc0SiLmxV1Wt\nop+w/gI4EngZcGJVHTPQb/uB1+8AvgrcAjxvoP1A4E3AqcCjgPOq6i1Dz9sFuGGwIclPp1jXc4Dv\nJpmoqjPpJ7uHD9w/HPh6VV0yxdjf0KE3m27aWDst9ALWZWyhFzBrvXn4ku12Ryf++dL2PTD+dscP\n7sFSiN8EeG5clmT5YENVvQx46xQ1wAAkuauqPgvclGRtc39LYI8kxwHHVdX2wFnA64CLBqb/AfBw\n4GcDcz8P+M7Qul4L7N4kuFsATxxMyJP8tKreDHwcuHyDo5cWqYmJNXM6X7c7Nudzjpq274Hxtzt+\ncA9GKf6ZEnVLIBaX+4D/W1W/DZDkVvrJ7t1D/c4E3lVV9wdo+n+MfukFTduOwNOApybZJ8lewGeA\nVw1OlOQiIMAh8xGQJEnSYmMCvIgkuYd+6cSZVfW1qvoq0KGf8A72O59++cRXqurL9E+JX5lkfKDb\nwcCnJ0+XG6cDr2/mHPRm4M45DUaSJGmR6vTmo0hOS1LHImCNmPFxSyDmWtv3wPjbHT+4B6MUf7c7\nNu0nXXkCLEmSpFbxTXCatV5v7t9UNGpG6Tvf+dD2+CVJS4MnwJIkSWoVE2BJkiS1igmwJEmSWsUE\nWJIkSa1iAixJkqRWMQGWJElSq5gAS5IkqVVMgCVJktQqJsCSJElqFRNgSZIktYq/Clmz1+nQXeg1\nLAKjvgcT46sXegmSJC0oT4AlSZLUKp4Aj7iq+l3gRGBrYBvgYmAlcBXwzaHuz0mytqqeDbyL/jdA\nWwB/B3wgSW9TrVuSJGmhmACPsKraDjgfeGmS66pqM+BTwPOAq5Msm2LM44GTgf2S/KSq7g+cCrwF\nOGmTLV6SJGmBWAIx2l4EXJbkOoAka4GDgctmGHMY8FdJftKMuRc4Gjh0ntcqSZK0KHR6PX/qPaqq\n6u3AHUk+NNS+G/Adfr0E4sokR1fVxcA7knxraMyPgYcluW+653U6+MWyiPmfsiRJv6Yz3Q1LIEbb\nD4A9Bhuqanfg4UxTAgHcCOwGfGtgzLbAPTMlv1r8JibWzPszut2xTfKcxart8YN7YPztjh/cg1GK\nv9sdm/aeJRCj7XPAPlX1KICq2hx4P/D4GcacCryzqnYeGPPBpl2SJGnJ8wR4hCVZXVWvAk6vqvsB\nY8BFwBeAE6pq1dCQVyf5ZlX9GfDJ5k1zmwOfwTfASZKkljABHnFJrgT2muLWtjOM+UfgH+dtUZIk\nSYuYJRCSJElqFU+ANWu93qZ5o9ViNkrF/5IkaWqeAEuSJKlVTIAlSZLUKibAkiRJahUTYEmSJLWK\nCbAkSZJaxQRYkiRJrWICLEmSpFYxAZYkSVKrmABLkiSpVUyAJUmS1Cr+KmTNXqdDd6HXMAcmxlcv\n9BIkSdIC8gRYkiRJreIJcKOqfhc4Edga2Aa4GHgPsCPwPmBXYDPgh8BRSW6qqkOaPk9IsqaZ53zg\ntCSrqupVwKuADrAFcGySf6qq9wA3JTlt4PlfBZYDy4DHJjlm4N7ewDuay2cAVzSvj05yZVVtCfwn\ncHKSk5oxuwHXAU9LcmXTdhiwM3D5TPNt0AZKkiSNCBNgoKq2A84HXprkuqraDPgUcBhwAPC+JBc2\nff8Y+FxVPbUZvjXwQeBPhuZ8EPAu4HFJ7qmqXYCvV9Uj1nd9SS4FLm3mvSnJsqEu/6tZ/yFVdXKS\n+5r21cBZVfUHSe5ej/kkSZKWLEsg+l4EXJbkOoAka4GDgSuBn00mv829LwLXA89qmj4O/E5VvWBo\nzrvpn/oeXlWPSvJj4FEDyelcWgGcBVwF7DvQfh1wCXD8PDxTkiRpJJkA9+0C3DDYkOR2YDf6ye6w\nG+iXRACspV/m8MGq2mFg/F3AXsBjgEuq6gfAa9axjt76LryqHgM8MMlVwJnAEUNd3gXsXVXPXN+5\nJUmSliJLIPp+AOwx2FBVuwM300+Chz2GfgnBIwCasokPAX9Lk8Q2JQ9bJXlDc/3b9BPhrwB3Ag8Y\nmnObpn19rQAeWFWX0K81fkZVPRq4t1nb3VX1auA84PQNmP+XOuufny9OO23sBGNzsYoRtjDx9xbJ\nl1+32/Z/f/fA+NsdP7gHSyF+E+C+zwF/VlWnJrm+qjYH3g98Edi5ql6Y5CKAqtoHeDTwJeCggTn+\nBngx8ATgNPpvNjurqp7ZvEHuB8AtwD3AN4Fjqur/JLm3qh4FPCDJeFXNetHNOpcDT0pya9P2DuD1\nwIcn+yX5ZlWdB7yNfpIujZyJiTULvQS63bFFsY6F1PY9MP52xw/uwSjFP1OibgIMJFndfGLD6VV1\nP/pHXBfRTxY/Rb+84c+a7j8E9kuydjBZTdJrTlq/21x/s6pOAb5cVXfS/wSJjyUJkKYk4cqqWk3/\n5PbggSW9qnmz3aRlTUnGsBcCV04mv43JWuCPDfX9q6a/JElSq3V6i+Xnilr0OkumBkKjaHx84U8c\nRunkY760fQ+Mv93xg3swSvF3u2Od6e75JjhJkiS1iiUQmrVeb3HUYS6kUfrOdz60PX5J0tLgCbAk\nSZJaxQRYkiRJrWICLEmSpFYxAZYkSVKrmABLkiSpVUyAJUmS1ComwJIkSWoVE2BJkiS1igmwJEmS\nWsUEWJIkSa3ir0LW7HU6dBfgsRPjqxfgqZIkaanyBFiSJEmtYgIsSZKkVrEEYhOqqmXAYUmWD7Vv\nCfwncHKSk5q2M4B/THJBc/3/AZclOaK5Xgl8EXgv8Kwk1zftLwSOAZ4F3AlcMbSMA4G9gb8Abmja\ntgMun5xbkiRpKTMBXhz+F3A+cEhVnZzkPuBS4A+BC6rqUcD1wB8NjNkTOBLoAGc2yfV2wEnA85Os\nrapbkywbflhVAZyX5Jjm+n7Av1bV7yf593mKUZIkaVGwBGJxWAGcBVwF7Nu0/TP9JJem7R+A/6yq\nx1XV7sCNSdYkOQe4BTgUeB9wfJLvr+fzx+gnzz/buDAkSZIWP0+AF1hVPQZ4YJKrqupM4Gjgc0km\nquq+qnoQ8Hz6Ce7mzetbgUsGpjkM+DfgG01CPGn7qlo1cH1jkgOb1wdU1dOBhwKr6SfO18201g69\nDY5zo+y0MI+d3thCL2CBLVz8vQX6EhzU7bb93989MP52xw/uwVKI3wR44a0AHlhVl9AvZ3hGVT06\nyX/QPwX+Y2DHJD+sqi/QL3FYA3xwcoImWf4K/TKKQVOWQDTOS3JMc5p8CXDtnEYlzYOJiTUL+vxu\nd2zB17DQ2r4Hxt/u+ME9GKX4Z0rULYFYQFW1ObAc+MMk+yR5HnAC8Pqmy6XAm4FVAEluALYHHk2/\nXGKjNeUSRwCfqqqt52JOSZKkxcwT4E3vuVU1+Uaz7YErk9w6cP8s4KqqeifwFeDJwLsG7l8FPCjJ\nbH4YPFwCAfD24U5JvlhVXwSOBf737MKQJEkaTZ3eYiiq00joLFgRsNQ3Pm4JxEJr+x4Yf7vjB/dg\nlOLvdsc6092zBEKSJEmtYgmEZq3XW/g3IS20UfrOdz60PX5J0tLgCbAkSZJaxQRYkiRJrWICLEmS\npFYxAZYkSVKrmABLkiSpVUyAJUmS1ComwJIkSWoVE2BJkiS1igmwJEmSWsUEWJIkSa3ir0LW7HU6\ndBd6DYvAYtyDifHVC70ESZJGhifAkiRJahVPgNdTVS0DLgCuBnrAVsC5wJOBPYBbgQ6wA3BykrOq\n6j3AAcCPB6a6NMnxVfUU4C/pfzMyBlyQ5OSq2g04P8nTqmrlwNz3B24B/jTJ99cx938CH0jyoWbt\njwVOA/YHPtX0/T3gWuAO4JwkZ2z8LkmSJC1eJsAb5rIkywGq6gFAgG8Db01ySdO+PfC9JnkFeH+S\n06aY62+Ag5NcU1WbA1dU1WXAbUP9Buf+Q/pJ+B+sY26AP62qS5JksiHJBLCsmWsVcFiSa2YdvSRJ\n0gizBGLjjQFrgXuH2ncG7krSW8f4m4E3VNWTgfuAPZN8a6YBSf4V+EVVPXoW6zsKWFlVm82iryRJ\n0pLnCfCG2as5Ob0P+AVwJPAy4MSqegewK/0Sif0HxhxVVcsHro9PcilwIPAm4FTgUcB5VfWWWazh\nZmDHdcwNcDHwfOBtwGdmH+Jv6rCuXF5T6W2CbduUb8zrdsc24dMWn7bHD+6B8bc7fnAPlkL8JsAb\n5pclEJOq6mU0ZQpVtS/wXuD6gS6/UaZQVVsCeyQ5DjiuKZs4C3gdcNE61rAr8KPp5h5yFPDvQ+vR\nJjIxsWahlzBnut2xJRXP+mp7/OAeGH+74wf3YJTinylRtwRiHiS5GPgs8NF1dL0P+L9V9dvNuFuB\nHwB3zzSoqvYG7kjyo5n6DaxnDXAo8KHZ9JckSVrKPAGeP8cB36qq/Zrr4TKFJDm0OTk+s3kDXA/4\nBnAm8LCh+U6sqmPo1xuvAV4+cG/Kufn1hlVV9QngSRsdmSRJ0gjr9DZFgaKWhI5FwBtkfHw0flQ0\nG6P0o6/50Pb4wT0w/nbHD+7BKMXf7Y51prtnCYQkSZJaxRIIzVqvt7Te0LUhRuk7X0mSNDVPgCVJ\nktQqJsCSJElqFRNgSZIktYoJsCRJklrFBFiSJEmtYgIsSZKkVjEBliRJUquYAEuSJKlVTIAlSZLU\nKibAkiRJahV/FbJmr9Ohu9BrWAQ2Zg8mxlfP2TokSdKG8QRYkiRJreIJ8AaoqmXABcDVA80TwF3A\ntUmOa/qtAPZKckBV3QNcMTTVgUlurKo/BP4c2Bx4IHBWkr9tnnNYkuUDzz4BuIb+QeR+wHbALgNr\neQ5wPfA7wPeAvZNcPzD+QuAU4J3A1sAdA+s5KcnnN2hTJEmSRoQJ8Ia7bDAxBaiqMeAbVfXPwN3A\n64E/bG7fmmTZ8CRV9Ujgw8A+SW6uqq2Af6mqG+gn1FNKchJw0jRJMkAPOBM4CHhP0/4QoIB/pp8A\nH5zkmvWOXJIkaYRZAjGHkqyhn3CeAZwOvDLJz9cx7CDg7CQ3N3PcCTwPuHQOlnQW8IqB64OBlUl6\nczC3JEnSSPIEeMPtVVWrBq4/n+SkJN+oqluAO5MMlkhsP9T/xiQH0i9f+PbgxEl+Br88yZ3KrBLY\nprwiVbVnksuBA+kn15POrqrBEoj9k0zMZm5JkqRRZQK84X6jBAKgqt4IfB94SFW9LslHm1tTlkAA\nPwAePjTHE+mfzt8JPGCo/zZN+2ydDhxcVWuB6yZPmhvrVQLRmV3evaT1NnILlsKnaHS7Ywu9hAXV\n9vjBPTD+dscP7sFSiN8EeA5V1VOAQ4Gn0U9Uv1pVlyf53gzDzgM+W1WfTDJRVdsAHwH+AvgK8KSq\nemiSn1TVlsCzgA+ux7IuBo4H7gM+uo6+moWJiTULvYQF0+2OGX+L4wf3wPjbHT+4B6MU/0yJugnw\nhhsugdge2ApY3tQCr6mqI4Dzm8R4uAQC4O1J/q2q3gp8pjmlHQM+luRigKo6Cvh8U6qwBXBKkv+Y\n7SKTrG0++WF/+m/KGzRcAvHJJKfOdm5JkqRR1Olt7M901RodayDo9TwBNv72xg/ugfG3O35wD0Yp\n/m53rDPdPT8FQpIkSa1iCYRmre2nn32jX/gvSVLbeQIsSZKkVjEBliRJUquYAEuSJKlVTIAlSZLU\nKibAkiRJahUTYEmSJLWKCbAkSZJaxQRYkiRJrWICLEmSpFYxAZYkSVKr+KuQNXudDt2FXsMisDF7\nMDG+es7WIUmSNownwJIkSWoVE2BJkiS1iiUQC6yqdgfeB+wAbA5cBbwdCPBbSdZW1dOBy4GnJvlG\nVW0JXA88HFgLvDjJhc18+wDLkxxSVauArYE7Bh55EvA94DvAN5u2LYHbgf2T3Daf8UqSJC00E+AF\nVFVbAf8ArEjytabtVcC5wLeB3wOuBPYFPtX8/Q3g6cC/Jrmvqu4A3l9Vlye5ZYrHHJzkmqHn7gZc\nnWTZQNtfA39CPxmXJElasiyBWFj7AV+aTH4Bknwc2BG4FPjDpvk59E+Fn99cLwMuaV6vAU4GTt3Q\nRVRVh/5psqe/kiRpyfMEeGE9kn4pw7DvA78A/qiqPgH8PMkNVdWpqi7wR8BpA/1PBV5cVQcAtw7N\ndXZzSjxp/+bvxzUlEtsDW9E/df74TIvt0JtdVCOqtwnCWwqfotHtji30EhZU2+MH98D42x0/uAdL\nIX4T4IV1I/CUKdofDbwTWAHsw69Oe/+R/unvlkl+Mtk5Sa+qXgN8GfjLobmmKoF4IE0JRFOGcRFw\nc5J7Nz6k0TUxsWadfbrdsVn1W6qMv93xg3tg/O2OH9yDUYp/pkTdEoiFdSGwd1X9MgmuqhXALUmu\np/9GtRXAF5rbXwDeBKwanijJj4D3ACeszwKS3AkcCPx5VT1x/UOQJEkaLZ4AL6Akt1fVC4EPVNUO\n9P89vgO8oulyKXBskqub668Dv0P/dHiq+c6uqpcMNQ+XQHySXyXUk+Nurqq3AB+pqmckuW+jApMk\nSVrEOr1NUfioJaGzxIuAx8ctgVgX4293/OAeGH+74wf3YJTi73bHOtPd8wRYs9brza5OVpIkaTGz\nBliSJEmtYgIsSZKkVjEBliRJUquYAEuSJKlVTIAlSZLUKibAkiRJahUTYEmSJLWKCbAkSZJaxQRY\nkiRJrWICLEmSpFYxAZYkSVKr3H+hF6AR0unQneH2xPjqTbYUSZKkDeUJsCRJklrFE+AZVNUy4ALg\naqAHbAXXRzuPAAAgAElEQVScCzwZ2AO4FegAOwAnJzmrGfds4F30v8HYAvg74ANJelW1cmDspIOB\nv5ii/ZwkZ1TV84G3NM/aGjglyblVdT/gfcATgAcAPweOSHJDVXWAw4EDgHub+d6b5AvNGu8Brmja\nNwc2A16R5Psbs2eSJEmLnQnwul2WZDlAVT0ACPBt4K1JLmnatwe+1yS3vwucDOyX5CdVdX/gVPoJ\n7EnNnL8cO6mqpmxvfAT4H0n+u6rGgKuq6lLg94FdkuzdzPFi4APAi4DXAXsCf5zkrqraAbi4qm5L\n8lXg1iTLBp5/KHA08IaN2CtJkqRFzxKI9TMGrOVXJ6qTdgbuStIDDgP+KslPAJLcSz+xPHQjnvvf\nwJuq6neB24HfSTIOTAC/X1Uvr6odgQuB/ZsxRwJvSnJXs46fAu+hfyo8lV2B2zZijZIkSSOh0+v1\nFnoNi9ZQCcR9wC+ADwEvo1+u8DP6iePVwDuT/HtVXQy8I8m3hub6MfAw4Ex+vdTh0iTHT1MacWSS\n71bVzsCfAs8HdgJOA45tSiqeTf+0dy/gR8BRSb5UVTcl2XloDQV8JMmygRKIbYHtgc8Af57k9un2\no9PBL5aW8X8PkqQR1pnuhiUQ6/bLEohJVfUymnKFqtoXeC9wfXP7RmA34FsD/bcF7kly3zpKHaYq\njXgwsGuStwFvq6rfAj4NXFlVPwCS5BVNze/ewAVNwry6qrZPMphQPwb4r+b1rU0ivBmwslnftMmv\n2mliYs2vXXe7Y7/R1iZtjx/cA+Nvd/zgHoxS/N3u2LT3LIHYSEkuBj4LfLRpOhV4Z5OEUlWbAx9s\n2jfEA4BPVtVDmuufADcBdwN/DPxFVd2vKb/4HvDz5vUpwIebumWqaifg3fRPjwfXv5b+CfJLqmq/\nDVyjJEnSyPAEeG4cB3yrqvZL8vmq+jP6Setm9D9h4TP86g1wMzmxqo4ZuP5SkndX1RuBz1XVvfQ/\nreFzSf6pqi6j/ykQ366q1fTLNA4CSHJK8/wvV9Uv6H+KxXFJrmBIkjuragXw8apaleTnG7oRkiRJ\ni501wJo1a4DbZ3zcEohBbY8f3APjb3f84B6MUvzd7ti0NcCWQEiSJKlVLIHQrPV6v/mmqLYZpe98\nJUnS1DwBliRJUquYAEuSJKlVTIAlSZLUKibAkiRJahUTYEmSJLWKCbAkSZJaxQRYkiRJrWICLEmS\npFYxAZYkSVKrmABLkiSpVfxVyJq9TofuQq9hA02Mr17oJUiSpEXCE2BJkiS1iifAc6CqlgEXAFcP\nNE8APwe2TfLSgb43Jdm5ef0k4HhgO+Au4DbgjUlurKr3ADclOa2qesCLk1zYjNsHWJ7kkKpaBWwN\n3DHw7JOA7wHfAb45tNznAO8CDgB+3LTtAJyf5PiN2QdJkqRRYAI8dy5LsnywoapWAs+sqoOSnDN0\n76HAucBLk1zTtL0EOBE4cGjuO4D3V9XlSW6Z4tkHT84xMP9uwNVJlg13riqA9yc5rbl+AHB1VZ2e\nZHyW8UqSJI0kSyDm39uBY6vqYUPtBwMfG0xck/w98Mop5lgDnAycOk9r3AHYHLhznuaXJElaNDwB\nnjt7NeUIkz7f/H0j/ZKDM4DnDdzfHbgYoKq2Ar7QtD8ceNQU858KvLiqDgBuHbp3dlUNlkDs3/z9\nuKE1XZnk6Ob1UVX1iuZ5NwIrkqyZMUJJkqQlwAR47kxXAkGSc6vqJVV1+MDtH9JPgklyJ7CsGXPT\nVJMn6VXVa4AvA385dHuqEogHMk0JROP9TX3xk4HzgWvXFWCH3rq6LF47bfwUvSb8bnds4ycbYcbf\n7vjBPTD+dscP7sFSiN8EeNM5HPgqMPlVczbwhar6QpJrAZpkdJvpJkjyo+bNce+jOT3eWEmurKoT\ngPOr6hlJ7puLeZeiiYk1dLtjTEy096Dc+NsdP7gHxt/u+ME9GKX4Z0rUTYDnznAJBMDNky+STFTV\nUcBnm+sfVtWBwMlVNQZsCawGXjTTQ5Kc3bxZbtBwCcQn6ZdUDJdAALx6ijnPqKqX00/S/89Mz5ck\nSRp1nV5vhH+srU2qM9I1EBtvfNwTYONvd/zgHhh/u+MH92CU4u92xzrT3fNTICRJktQqlkBo1no9\nRua7PkmSpOl4AixJkqRWMQGWJElSq5gAS5IkqVVMgCVJktQqJsCSJElqFRNgSZIktYoJsCRJklrF\nBFiSJEmtYgIsSZKkVjEBliRJUqv4q5A1e50O3fUcMjG+el6WIkmStKE8AZYkSVKreAI8D6rqZODJ\nwM7A1sANwATwPOCbQ92fk2RtM+4fgPslecHAXFsCfwk8FegBtwOHJvlhVa0CDktyzUDfa5LsVlUr\ngT2AWweedU6SM6rqHuCKpm1zYDPgFUm+P0dbIEmStGiZAM+DJEcDVNUhwGOTHFNVuwEPT7JsqjFV\n9QhgG2DzqnpkkhuaWx+kn9S+pen3EuAC4OmzWMpbk1wyRfutg+uoqkOBo4E3zGJOSZKkkWYJxOLx\nGuBC4Bzg9QBVtQXwIuBDk52S/D3wgqkm2Ai7ArfN8ZySJEmLkifAm9bjmrKFSVcmObqq7gccADwN\nuBf4XlW9C9gOuClJb3CSJD8duDy7qu5oXg9/Q3NiVR0zcH1kku8C2zfr2BbYHvgM8OcbF5okSdJo\nMAHetK6epgTiecAYcF5zPZkQnw1sV1WdwSS4qg6kXwYBcPBwDfDAvDOWQFTVZsBK4J4kt69r8R16\n6+rym3Za/yGL39i8zNrbgO1dCN3u/MQ/KtoeP7gHxt/u+ME9WArxmwAvDiuAFUk+D1BVewKnNG9Y\n+0fgSODDzb39gTclObeqNuqhSdZW1euAb1fVv04+XwtjYmLNQi9hnbrdsZFY53xpe/zgHhh/u+MH\n92CU4p8pUTcB3rSGSyAA3kb/Ex5ePtmQ5PKq2rKqngEcBby/qq6g/ykQtwH/a5bPGy6B+FKSdw92\nSHJnVa0APl5Vq5L8fP1CkiRJGi2d3qj83FULrrNBNRCarfHxxf8d9Sh95z8f2h4/uAfG3+74wT0Y\npfi73bHOdPf8FAhJkiS1iiUQmrVebzTqVOfTKH3nK0mSpuYJsCRJklrFBFiSJEmtYgIsSZKkVjEB\nliRJUquYAEuSJKlVTIAlSZLUKibAkiRJahUTYEmSJLWKCbAkSZJaxQRYkiRJrWICLEmSpFa5/0Iv\nQCOk06G70GuYYxPjqxd6CZIkaRPzBFiSJEmt4gkwUFXLgAuAq4EesC1wA3AgsAvwHeCbQ8Oek2Rt\nM/4fgPslecHAnP8JPDbJXdM8cyWwB3DrQPM5Sc6oqucDbwE6wNbAKUnOrapzgd8CdgPuAX4MfDfJ\nkc2cbwX+FNg9yV1V1QU+1cz9e8C1wB3AOcDDgQOaOSZdmuT4mXdLkiRptJkA/8plSZZPXlTVecD/\nBP4duDrJsqkGVdUjgG2AzavqkUluWI9nvjXJJVO0fwT4H0n+u6rGgKuq6tIkBzbPfA9wU5LThsa9\nEjgfWA6sTDIBLGvGrAIOS3LNwBzvn2IOSZKkJc0SiClU1RbAQ4HbZtH9NcCF9E9VXz9HS/hv4E1V\n9bvA7cDvJBmfaUBzin09cBpwxBytQ5IkacnxBPhX9mpOSXcC7gM+muSfq2o34HHNvUlXJjm6qu5H\nv4zgacC9wPeq6l1J7pzlM0+sqmMGro9M8l3gufRLGT7RrOe0qjo2SW+GuVYAH0uSqrq7qp6a5Gvr\neP5RVbV84Pr4JJdO17nDTI9feL0NWN6GvKmv2x3bgFFLh/G3O35wD4y/3fGDe7AU4jcB/pXLkiyv\nqh2AS4HvD9ybrgTiecAYcF5zPZkQnzHLZ/5GCURVPRjYNcnbgLdV1W8BnwauBC6aapJmzL7ATlV1\nJPAg4A3AuhLgJVUCMTGxZt6f0e2ObZLnLFbG3+74wT0w/nbHD+7BKMU/U6JuCcSQJD+lX0v7sap6\n6Dq6rwBWJNknyT7Ay9j48oMHAJ+sqoc01z8BbgLunmHMK4Ezkjy3WcdTgec2b4KTJEnSAE+Ap5Dk\n6qr6MPBh4H/zmyUQAG+jn2i+fGDc5VW1ZVU9o2m6vKomfzB/XpL3D80xXALxpSTvrqo3Ap+rqnuB\nzYDPJfmnGZa8AjhoYB13VNWngdcCfzXDuOESiCQ5dIb+kiRJI6/T25DCSbVSZ5EXAY+PWwIx34y/\n3fGDe2D87Y4f3INRir/bHetMd88SCEmSJLWKJRCatV5v07zRTJIkaT55AixJkqRWMQGWJElSq5gA\nS5IkqVVMgCVJktQqJsCSJElqFRNgSZIktYoJsCRJklrFBFiSJEmtYgIsSZKkVjEBliRJUqv4q5A1\ne50O3YVewxQmxlcv9BIkSdII8QRYkiRJreIJ8ByqqmXAvwCvSHL+QPt3gG8mOaSqdgH+A3hVkk8N\njLsQeHySHzZtJwDXJFnZXD8F+AqwZ5JvDMz9JOB4YDvgLuA24I1JbqyqlcAewK0DyzwnyRlVdQ9w\nRdO2ObBZs+7vz92OSJIkLT4mwHPvGmA5cD5AVT0BeODA/VcDHwaOAD410H43cFZV7Z2kN8W8rwVO\nbsYd0sz9UOBc4KVJrmnaXgKcCBzYjHtrkkummO/WJMsmL6rqUOBo4A3rEaskSdLIsQRi7l0F7FpV\nD2quX0k/SaWqOsBB9BPZLarq8QPjLqN/UnvE8IRVtQ2wF3AssGdV7djcOhj42GTyC5Dk75tnrq9d\n6Z8eS5IkLWmeAM+PTwMvbUoQngK8F3gE8Bzgu0kmqupM+snu4QPjDge+XlXDJ7bLgc8kuauqPgn8\nSTPn7sDFAFW1FfCFpv/DgUc1r0+sqmMG5joyyXeB7atqFbAtsD3wGeDPZwqqw1QH04vAThs+tLcB\nIXW7Yxv+wCXA+NsdP7gHxt/u+ME9WArxmwDPj/OAU4EbgH8daH8tsHuT4G4BPHEwOU3y06p6M/Bx\n4PKBcSuAe5txWwMPq6qTgB/ST4JJciewDKCqbhoYO2MJRFVtBqwE7kly+4aHPJomJtasV/9ud2y9\nxywlxt/u+ME9MP52xw/uwSjFP1OibgnEPEhyA/263zcC/7dp3hF4GvDUJPsk2Yv+qeurhsZeBIRf\n1fk+AdgsyTObcc8CrgdeAJwNvLaqfntyfFU9GdhmPda6Fngd8JKq2m8DwpUkSRopJsDz55PAw5Nc\n21w/C/h0k3BOOh14PdAZGvtm4M7m9WuBc4bunw68ofnEiAOBk6tqVVV9Ffhr4EUDfU9s7k3+OXZ4\noc3p8QrglKp64PB9SZKkpaTT25AiSLVSZ9EWAW+48XFLINaH8bc7fnAPjL/d8YN7MErxd7tjwweM\nv+QJsCRJklrFN8Fp1nq99X/TmCRJ0mLjCbAkSZJaxQRYkiRJrWICLEmSpFYxAZYkSVKrmABLkiSp\nVUyAJUmS1ComwJIkSWoVE2BJkiS1igmwJEmSWsUEWJIkSa3ir0LW7HU6dBd6DethYnz1Qi9BkiQt\nQp4AS5IkqVU8AZ4jVbUbcD5wDbBtkpcO3LsJeChwPbB3kusH7l0InAK8E9gauGNg2pOSfL6qXgW8\nCugAWwDHJvmnqvpnYDPgscA4cCtwaZLjq+qJwAnAVs2Yf2nG3VNVK4E9mv4dYAfg5CRnze2uSJIk\nLT4mwPPjmVV1UJJzJhuS9KrqTOAg4D0AVfUQoIB/pp8AH5zkmsGJqupBwLuAxzXJ6y7A16vqEUme\n0/RZCZyf5JKBeT8BvDjJtVXVaeb4AHBEM/VbB/pvD3yvqlYm6c3DfkiSJC0alkDMj7cDx1bVw4ba\nzwJeMXB9MLCupPNu+ie4h1fVo5L8GHhUkvtmGHMQcGaSa6GffAPHAftW1VZT9N8ZuMvkV5IktYEJ\n8Py4kf6J6xmDjUluBFJVezZNB9JPiiedXVWrBv50k9wF7AU8Brikqn4AvGYdz38k/XKLwWf3gJuA\nhzRNJ1bVv1bVfwHvB/Zf7yglSZJGkCUQ8yTJuVX1kqo6fOjW6cDBVbUWuC7JzQP3piqB2AXYKskb\nmuvfpp8IfyXJd6d5/I3AbkPzbAbsQr9WGJoSiKraF3gvQwnzVDos/AFxbz2WMF+fWNHtjs3TzKPB\n+NsdP7gHxt/u+ME9WArxmwDPr8OBrwKDXykXA8cD9wEfncUcOwNnVdUzk6wBfgDcAtwzw5iPA5dW\n1eeSXNfUAL8buDjJHVX1y45JLq6qpzdrWfSnwBMTaxb0+d3u2IKvYSEZf7vjB/fA+NsdP7gHoxT/\nTIm6JRDzKMkEcBT9T3eYbFsLXAg8G/ji0JDhEojDk3yT/qdEfLmqrgC+DHwsSWZ47o/o1wH/bVVd\nDnwN2BJ48zRDjgMeV1X7bVCgkiRJI6TTW5+fKavVOougBmJ83BPghWT87Y4f3APjb3f84B6MUvzd\n7lhnunueAEuSJKlVrAHWrPV6C1+DK0mStLE8AZYkSVKrmABLkiSpVUyAJUmS1ComwJIkSWoVE2BJ\nkiS1igmwJEmSWsUEWJIkSa1iAixJkqRWMQGWJElSq5gAS5IkqVX8VciavU6H7kKvYY5NjK9e6CVI\nkqRNzBNgSZIktYoJsCRJklplJEogqmoZcAFwNdABHgAcnuRbVbUSOD/JJQP9b0qyc1VtBZwK7AJs\nDdwEHJrkp1W1CjgM2Bm4EHh8kh82408ArkmysqruAa4YWtKBwE+A9wFPaNbzc+CIJDdU1aOBDwGb\nA9sCXwLenuS+obieCJwAbAVsAfwLcCzwEOAfkzyu6fcK4BxglyTjVbUb8FngxcB1wNOSXNn0PQzY\nOcl7quo/gf8CBp97NDA2sJ+9Zo03AAcmuWfGfwxJkqQRN0onwJclWZbkj4A/B46bxZhXAzcleW6S\nZwJfacYOuxs4q6o6U9y7tXnu4J8bgX3oJ6R7J3kW8BHgA82YvwJOSfJc4OnAbwMvGpy0qh4CfAJ4\nU5JlwJ7NOj7QJOKdqtqx6b4v8Gng+c31s4HJhH91s/YHTLMHzx1a+5VN++R+PjvJk4FfAP9zmjkk\nSZKWjFFKgAc9GBifRb+bgedW1QuralvgFPonoMMuA24FjliPNUwAv19VL28S1QuB/Qeee0hV7Un/\nlP1l9E9sBx0EnJnkWoAkPfpJ/b7NyfUXgWdW1f3onzK/D9ivGbuMXyXA1zWvj1+Ptf+aqtoCeChw\n24bOIUmSNCpGogSisVdTtvAA4In0f/w/nR5Akk9XVQ/4E2Al8F3gyObvYYcDX6+qS4bat2+eO+nG\nJAcm+UZVvRZ4HfBh4EfAUfTLHd7y/7N353GSldXBx38FDALSqGAhoKxqjpKoBBNAIHFYRERAJRqH\nfZFVISoggoggBFzQEXFjlU0QCBBMRAgjw2hEUBZBXuflYADlDQjdijCDLAMz9f5xb0NN0d1T3dPV\nXdX39/185mPf5XnuOQ/+cfrpU7fK+b5AUbxeAxwKPN40zwbArOYHZWYjIh6haIGYBbwTeBi4HbgN\n2KgsiDcG9gdeWw49rox9yyHyuj4iBlsgFmbmNuXPg+u5OkWLxFmZecMQ419QK5a1YxqdnX5IY3mr\nRb3eN+5x9BLzr3b+4BqYf7XzB9dgKuTfSwXw7MycARARAdwcEa8FnqYoipstV973DuCGzLwqIpal\n2HU9H3h76+RlX/AngAuAm5ouPVa2KCwmIt5aDMtdy9aJdwGXR8QawFaZeRpwWkSsTLF7exyL7z4/\nBKzXMueyFP3K/cAc4NMULQ4/KovjW4Adgfsy87liGSAzn42IfYFLgLNbQt0uM59pjZ9yPSNiNYpi\n+4Eh7plQAwPzJzuEJarX+3oizk4x/2rnD66B+Vc7f3ANein/kQr1Xm2BeLTp5zuAXQYPIuIfKD7c\nBbAr8HGAzFwI/Jqiz3ZImfmfQAL7tBHDtsCJEbFM2b7wG+Av5c9fjoh3lnM+Cdw7xHMvAA6MiDeW\ncdeA4ymK3acyc1455l28uFN8LXAUL7Y/NMd+B0UB/Ok2Ym8e9ydgD+CciFhzNGMlSZJ6US/tAA/+\nyX4hxVsMDs/Mp8u3QGwUEXcC84EFFG0JAMcC3yyv/aX895ElPOcTwDZNx60tEADHULQ9fAW4MyLm\nUbQR7Fle/zBwekR8tYznfoqWiBdk5v9GxJ7AtyNiJYo3Rswpnz/oJxS7yYPf1nA98D2KgnUopwA7\ntZxrboGA4u0Ui/X6ZubciDi9zOlDSJIkTWG1xmQ0Xqon1TrcBNzf3/1/UumlP/10gvlXO39wDcy/\n2vmDa9BL+dfrfUO93Qvo3RYISZIkaUx6qQVCk6zR6I0PqkmSJI3EHWBJkiRVigWwJEmSKsUCWJIk\nSZViASxJkqRKsQCWJElSpVgAS5IkqVIsgCVJklQpFsCSJEmqFAtgSZIkVYoFsCRJkirFr0JW+2o1\n6pMdQxsG+udNdgiSJKmLuQMsSZKkSnEHuEtFxNHAtsA0YBFwZGbeXl67E7gpMz/WdP8jmblGyxwn\nALsBDzednpWZJ0fEJsC/UvwS1Adcnplf7WBKkiRJXcECuAtFxIbAzsAWmdmIiI2AC4C3RcQWwN3A\n1hHRl5nzlzDdzMw8Y4jz3wT2ysx7ImIa8POImJ2ZvxrPXCRJkrqNLRDd6QlgHWC/iHhtZt4JbFJe\nOwC4Avh3YO+leMajwKER8XaKHeYtLH4lSVIV1BqNxmTHoCFExMbAoRRtEE8BxwKzgDuANwHrA1dn\n5l+X97fbAnFyZs6KiFWAjwM7Aa8HLqFos3h2uJhqNSb9/yz+31WSJLWpNtwFWyC6UES8AZiXmfuV\nx38HXAucRrFr/8Py1jUjYpvMvGGE6V7SAhERKwAbZ+ZJwEkRsSpwHnAg8I3xzWZ8DQwsqeOjs+r1\nvkmPYTKZf7XzB9fA/KudP7gGvZR/vd437LW2CuCIWJdiN3JVmqrpwQJN4+6twIERsXNmLgDuBR4H\nPgjslJm/AYiI3YGPASMVwENZBHwvIrbOzHsz87GI+D0w7O6vJEnSVNHuDvDlwH+X//wjdIdl5lUR\n8Wbg1oh4kmLX9zvAHoPFb+lK4GsRsTawWkTc1nRt8I0Oh0fEjMWnz4Mi4p+B75YfgGsAtwLf7VRO\nkiRJ3aLdAnhaZh7Z0Ui0mMw8GTi55fTMlnueAVYvD6cNM9UJw8z/c2DLpQhRkiSpJ7X7FoifRcRO\nEbF8R6ORJEmSOqzdHeAPUvQAExGD5xqZuWwnglJ3ajQm/0NokiRJS6utAjgz1+p0IJIkSdJEaPct\nECsBxwPblGNmA8dl5l86GJskSZI07trtAf4m8HJgP4pvH1seGOrrdSVJkqSu1m4P8Nsz821Nx4dG\nxNxOBCRJkiR1Urs7wMtExCsHD8qfn+9MSJIkSVLntLsDPJPiSxn+g+Kb4HYCvtCxqCRJkqQOaWsH\nODPPAz4A3A88AOySmX5rmCRJknrOiAVwROxY/u9ewMbAfOAJ4G/Lc5IkSVJPWVILxN8DPwS2GuJa\nA7hw3COSJEmSOmjEAjgzjy9/vCQzZzVfi4hdOhaVJEmS1CEjFsAR8WHgZcCJEfG5lnGfAa7qYGzq\nNrUa9ZZTA/3zJiUUSZKksVpSC8QqwOZAH4u3QTwPHNupoCRJkqROWVILxNnA2RGxTWbeMEExTXkR\ncQNwTGb+MiKWBwaAf83MU8vrc4CNgHuBpyg+rPgq4KjMvDYiTgAeAf4CfARYAdgQuKN8xO7ATcCD\nwKKmRx9B8cvM5cBcij7uVSje7rF7Zi7oUMqSJEldo933AD8bET8AVqZ4D/CywLqZuV6nApviZgH/\nAPyy/N//AnYATo2IFYB1gbuAgzLzHoCICOBK4NrBSTLzIuCiiFgPuDQzpw9eK25nu8x8pvnBETEd\nmJ2ZM5rOXQLsDFwxznlKkiR1nXa/Ce4c4GqKgvlbwG+Bf+9UUBUwWABDUfieA7wyIl4BvAP4CcXu\nbLN1gT+PdyDlDvSanZhbkiSpG7W7A/x0Zp5X7jT+GTgAuL1jUU19vwLeFBE14B8pPlD4Y2Bb4K3A\ndcDBwIUR8TywDnAzsO8on3N9RAy2QCzMzG3Kn7cu2yxWp2iROMsWF0mSVBXtFsDPRMSqQAKbZebs\niHh5B+Oa0jJzUUTcBWwPPJKZz0bEtcCOwNuAr1MUwHtl5j0RcRCwG0VP72i8pAWiNDszZ0TEahS7\n0Q+0M1ntJZvSFCX0FNYYIuV6vW/iA+ki5l/t/ME1MP9q5w+uwVTIv90CeCZwGbALcGtE7A7c1rGo\nqmEWxc7v98vjnwGfAxqZ+VjZwwtAZp4ZEVsCJwOfGq8AMvNPEbEHcGNEbJSZfxivuaeKgYH5ix3X\n630vOVcl5l/t/ME1MP9q5w+uQS/lP1Kh3lYPcGb+G8Vu4nzg7cAewJ7jEl11zQK2BH4EUL6B4XGK\n/t+hfBzYNSLeNopnXB8Rc5r+faD1hsycC5xe/pMkSZryao2h/sbbIiLWAb4BbA08R/Emgk9k5kBn\nw1M3qQ3ZAzG19fe7A9zM/KudP7gG5l/t/ME16KX86/W+2nDX2n0LxMUUO5ZrARtQtD9csPShSZIk\nSROr3R7gVTLzm03HX4uIfToQj7pYo/HSnlhJkqRe0+4O8O3lh6UAiIj3UrzKS5IkSeop7e4A7wTs\nExFnUnxBw0oAEbEXxVsLlu1QfJIkSdK4aqsAzsx6pwORJEmSJkJbBXBEfG6o85l54viGI0mSJHVW\nuz3AtaZ/ywM7A6/pVFCSJElSp7TbAvH55uOIOAm4viMRSZIkSR3U7g5wq5WBdcYzEEmSJGkitNsD\n/AC88C1gywCvBE7tVFCSJElSp7T7GrTpTT83gMczc974hyNJkiR1VrstEH3AlzLz98DLgR9GRHQu\nLEmSJKkz2t0BPgf4PEBm/t/yQ3DnAlt2KjB1oVqN0bwQeqDfPxJIkqTu0+4O8Msz89rBg8ycRbET\nLEmSJPWUdneA+yPiYOB75fGuwKOdCUmSJEnqnHYL4H2Bb1O8+WEB8FNg/04FNVVExNHAtsA0YBFw\nNMj7TM0AACAASURBVPCl8vJGwL3AU8BFwNrAI5l5RtP4W4AZFB9CPBG4n2LXvgF8PjNnR8R04HJg\nbtOjBzLzQxFxPrBKZu7SNOcjmblGRFwMvBZYj+K/6cPA3Zl52DgugSRJUtdp94swHoyI4zLzVxHx\nCuDtmfm/HY6tp0XEhhTfmLdFZjYiYiPggsx8W3l9DnBwZt5THp+whCkvycyjy3tfA/w0It5ZXpud\nmTOGGbdlROyZmRc1n8zM3Zueu1jhLUmSNJW11QMcEV/kxZ3LlYDPtVGwVd0TFF8Wsl9EvDYz7wQ2\nGY+JM/NR4EpgxzZuPwb4fES8bjyeLUmS1OvabYHYEXgbQGb+ISK2BX4FnNChuHpeZj4UETsDhwLH\nR8RTwLEUhetoNIY5/yjwauB/gK3LHeVB12Tm4BeVPAQcR/HWjneP8tmLqQ0byjBWX5qnjb/GKMMf\nTr3eNz4T9Sjzr3b+4BqYf7XzB9dgKuTfbgG8HLAi8GR5vDzDF2YCIuINwLzM3K88/jvg2oi4MTMf\nG2LI08DLWs6tXJ4fyrrAHeXPI7VAkJkXR8QHIuKQUSUxxQwMzF/qOer1vnGZp1eZf7XzB9fA/Kud\nP7gGvZT/SIV6u69BOxO4PSK+EhFfBW4FvjMOsU1lbwW+GRHLl8f3Ao8DC4e5/w5g54hYDiAiXg+8\nLDP7W2+MiDWB9wE/GkU8hwBHUnypiSRJUmW1+yG4r0XEz4B/pHhjwB6Z+auORtbjMvOqiHgzcGtE\nPEnxy8anMvOJYe6fFRFbUvyiMQ+oAXs13bJbRGxGUUDXgH0z87HyC/laWyAA3tMy/0BEHA5cPQ7p\nSZIk9axao43GyIioAQdTvNJrWeBG4BuZuaiz4amb1EbdBNxd+vttgVha5l/t/ME1MP9q5w+uQS/l\nX6/31Ya71m4P8JeBNwLfpdx9BNYHPrHU0alnNBrj00crSZI0mdotgLcD/nZwxzcirgHu7lhUkiRJ\nUoe0+yG45Vi8WF6O4T/MJUmSJHWtdneALwbmRMT3y+NdgUs6E5IkSZLUOW3tAGfmKcBJFN9sth5w\ncnmOiFijY9FJkiRJ46zdHWAy81rg2iEu/QjYeNwikiRJkjqo3R7gkQz7iglJkiSp24xHAdzT74aV\nJElStYxHASxJkiT1DAtgSZIkVYo9wJIkSaqUtgrgiLh+hMuHjVMskiRJUse1+xq0FSNi7cz8f60X\nMvNn4xyTulWtRn2I0wP98yY8FEmSpLFqtwB+NfC7iOgHnqZoe2hk5gYdi0ySJEnqgHYL4O1HO3FE\nHA1sC0wDFgFHZubt5bUPUbROLCpjOCszLyyvzQFWAp5qmu7jwNfLnzcDflmOPQ/4dGZuWI7dFbgI\nWCsz+yNiPeDqzNyovP7P5Zg3ZubD5bkTgN2Ah8v5VwMuzcyTI2If4ETg/qZY7s7Mxdo+ImIB8POW\nJdgdeBdwAvCWzJxf3nspcEZmzomIOnAq8OYy3+eBEzPzvyNiOnBwZs4o1+RXmfnJco4VgHsyc70h\n4geYVcb/O+DBcq0GHQH0AZcDcyleY7dKmePumbkASZKkKaytAjgzfx8ROwHTgeeAH2fmj4e7PyI2\nBHYGtsjMRkRsBFwAvC0i3g0cDOyUmU9ExIrAFRHxdGb+WznFXpl5T8u008u5fwdsl5nPlMdHR8Sr\nM/OPwA7AlcB7yudtBVzXNMcBwOnAgRSF6aCZmXlGOd/LgLkRcXZ57ZLMPHoJS/RYZk4fYh2gKOZP\nAz7Scq0G/AA4NTP3Kc9tAFwZEZsM8YxdI+LqzPzJENdeiH8IL6xV07OnA7Mzc0bTuUso/ptdMcw8\nkiRJU0K7H4L7AnAU8DuKncaTIuKYEYY8AawD7BcRr83MO4HBou4wil3bJwAy82ngSODQMWUAPwa2\njIhlgLcAXwHeW16bTlkAR8T6wKrAl4A9I2LaMPOtRrFr/fQY42l1AfDmiNix5fwmwB8z898HT2Tm\n/cDGmfncEPN8HDgrIlYep7heEBHLA2sCfx7vuSVJkrpNuy0QO9JUmEXEWcBtwBeGujkzH4qInSmK\n2uMj4ingWIrd2Q2A+1qG3A+s23R8YTkG4KLMPHeE2GYB76QozG8v49qoLIg3BvYv7/sI8N3MfDwi\nbgZ2AS4rrx1etk+sDTwE7J+Z88sd3N0iYrOm552bmRe1xLBq2aYw6KHM3L38eSGwN3Bt+dxB6wP/\nM3gQEWcCAdQjYrHd4tJdwIXATOBfWq4dHhEzmo5PzsxZ5c/XR8RgC8TCzNym/HnrMubVKVokzsrM\nG4Z47gtqw33p3+ojjepOjaX4/sJ6vW/8AulB5l/t/ME1MP9q5w+uwVTIv90C+DGKvtHHyuPlKXZ5\nhxQRbwDmZeZ+5fHfURSAN1IUmOux+G7jGyl6VQcN1QIxnDnAp4F5wI/KlotbKIr2+zLzuYhYFtgD\neKBs5ViVojgfLIBnZuYZEfF24FLg3qb5x9wCMSgzfxsRXwe+zYtfHf3/gA833XMQvNAjvMIwU30R\nuImixaPZqFogSrPL/uLVKH6JeGC4+KeigYH5YxpXr/eNeexUYP7Vzh9cA/Ovdv7gGvRS/iMV6iO2\nQETEeRHx3fK+uyLiW2UhdzsvFsNDeSvwzfJP61AUlI9T7IaeDpwaEauUz1iZ4oNg32ovncVl5jzg\nWYoPnA3uel5L0bIx2P+7A3BrZm6Vmdtn5ibAayLirS1z3U5RZF5a7iCPp29SvE1j6/L4ZmCNcqcc\ngIhYA3gTDL3VmpmDu8lfG6+gMvNPFL8cnBMRa47XvJIkSd1qSTvAc8r/bf3g1R0MU6QBZOZVEfFm\n4NaIeJKigP5U2ff7n2Xxe135p/llgXMy87Lh5mvDT4CtymIY4HrgexSFHRQffjunZcw5FLvAzW9P\nIDPPjYgPA4cAf+GlLRBPZOb7WuZqbYEAWKxHutyZ3he4uzxeVO5GfyEiPlXeNo1il/i/gX8cKtHM\nzIj4GvDJptOtLRA5uKPM4i0QULxNY7Fe38ycGxGnU/xy8qGhnitJkjRV1BptNENGxDGZ+YWWc6dk\n5mc6Fpm6Tm3YJuDe099vC8RYmH+18wfXwPyrnT+4Br2Uf73eVxvu2og7wBHxRYqPOO0cEW9sGbcZ\nYAEsSZKknrKkFogrgQ2BbVi8DeJ54KROBaXu1GiM/cNjkiRJ3WLEAjgzb6Xo47168L29kiRJUi9r\n9zVo74+IrwKvKo9rQCMzl+1MWJIkSVJntFsAHw9Mz8z/08lgJEmSpE5r9123D1n8SpIkaSpodwf4\n9oi4guL9ui98q1hmXtiRqCRJkqQOabcAfgUwH3hH07kGYAEsSZKkntJWAZyZ+0bENCDKMf8nM5/v\naGSSJElSB7TVAxwRbwd+C1wAnAc8GBGbdjIwSZIkqRPabYE4HfhwZv4CICI2A74BbNKpwCRJkqRO\naPctECsPFr8AmXkLsEJnQpIkSZI6p90d4Mci4n2Z+QOAiHg/8KfOhaWuVKtRn+wYukAdGOifN9lh\nSJKkMWq3AD4Q+GFEnEv5LXDA5h2LSpIkSeqQdgvg9wBPARsDrwcuA6YD93YmrNGLiKOBbYFpwCLg\nSOAwipgfa7r1osw8NyIeycw1WubYBzgRuL/p9MzM/I+W+xYAP28JYXfgXRQfEnxH2SZC+faMPwDf\nzMwTmsY2ylj/L3AIsAfwpsw8uuVZ04BjyrkXAs8Bn83MX0TEV4C+zDyovHdZ4Cbg88CmwG7Aw03T\nzcrMkyPid8CD5TqtANwOHJGZzyBJkjTFjWYHeJPMfAr4dflWiF8AZ3UsslGIiA2BnYEtMrMRERtR\nvLHiV8BRmXndKKa7pLUIHcJjmTl9iDgA7gFmALeUp7cHnhhubERcBuwwwrNOBJYF3pmZiyJiXeCa\niNgJ+CxwW0Rsm5k/Bj4F3JqZ15Zv6ZiZmWcMM+92gwVvRBwLnAwcMXLakiRJva/dD8FNAxY0HS+g\n2MHsFk8A6wD7RcRrM/NOJu8NFdcC74qIwbXdFfj+UDeWu7srA0+OMN8ewGcycxFAZv4e+BawT1nA\n7gV8KyLeCnyIoggerZnAP41hnCRJUs9pdwf4amB2RFxeHu8C/KAzIY1eZj4UETsDhwLHR8RTwLHl\n5S+X7RGDDsvMu0eYbrfyNW8AA5n5oSHuWTUi5jQdP5SZu5c/LwBuBt4ZEbcBqwD/C6zRMrZR/rs2\nM2eX7ReLiYjVKXaMW7905H6KFgcy846IuBi4Adi2pY3h8IiY0XR8cmbOan1OZj4dEb7VQ5IkVUK7\n3wT36Yj4IPBOih7U0zPz6o5GNgoR8QZgXmbuVx7/HcVO7M2MQwtERJwDvIEXC+IhWyCa56DY+V0H\nuApYvunaksY2e5yiYF6upQh+I0UP76ALgR0y866W8SO1QLwgIlah+KrrEdU6tOnf6Ka/JbSpym/D\nqNf7JjuESVX1/ME1MP9q5w+uwVTIv90dYDLzCuCKDsayNN4KHBgRO2fmAooP5z1O8aGxpZaZ+49y\nyBzgNGAtig+i7TbG5y4od91Pjohjyh7gDYCPAjuOZc5hHEXxwcZJMTCwxNq7a9TrfT0V73gz/2rn\nD66B+Vc7f3ANein/kQr1tgvgbpaZV0XEm4FbI+JJit7mTwHv56UtED/JzOOB1coWhUFfHcUjW1sg\noHhTw2A8iyJiFrB2Zs4rPxzXjr0jYtum4+nAp4ETgFvKN0g8C+yfmfe/dPhLtLZA5OAbI4DrI2Ih\nxQfs7qR4a4YkSdKUV2v04t+fNSlqHeqB6O/vjd8kobd+8+0E8692/uAamH+18wfXoJfyr9f7asNd\na/ctEJIkSdKUMCVaIDQxGo3e6teVJEkaijvAkiRJqhQLYEmSJFWKBbAkSZIqxQJYkiRJlWIBLEmS\npEqxAJYkSVKlWABLkiSpUiyAJUmSVCkWwJIkSaoUC2BJkiRVil+FrPbVatSXYvhA/7xxC0WSJGms\n3AGWJElSpbgD3CERMR24HJgLNIAVgYsz8xvl9TuBmzLzY01jFgA/Lw+nAcsCuwJvAI4tz2/edM8R\nwFeBX2XmJ8s5VgDuycz1IuIEYDfg4abQZmXmyRHxO+BBYFH5nJWBAzLztvFZAUmSpO5kAdxZszNz\nBkBEvAzIiLgI+GvgbmDriOjLzPnl/Y9l5vTBwRFxEHBEZh4KzCrPPdJyD8CuEXF1Zv5kiBhmZuYZ\nw8S3XWY+U87zbuAEYMexJitJktQLbIGYOH3AQuB54ADgCuDfgb1HGLMu8Oc25v44cFZErLwU8bX7\nLEmSpJ7mDnBnbR0RcyjaDJ4DDqP4pWNLYH+K9oirgW+W969a3r8KsCpwFfC5Np5zF3AhMBP4l5Zr\nh0fEjKbjkzNzVvnz9WXLxFrAdcCRo0lOkiSpF1kAd9YLLRCDIuIQiiL4h+WpNSNim8y8gbIFIiKW\nBc4HFmTmk20+64vATcB7Ws4vsQUiIk4B1gf6R3pAjUaboQxj9dEPaSzlIzuhXu+b7BAmlflXO39w\nDcy/2vmDazAV8rcAnnj7Aztl5m8AImJ34GPADYM3ZObCiDgQuDMi/jszr1nSpOWYvYH/GkNMnwVu\nBD4KfGsM4ztmYGD+km+aQPV6X9fFNJHMv9r5g2tg/tXOH1yDXsp/pELdHuAJFBEbA7XB4rd0JbBl\nRKzdfG9mPk1RLH8jIl7ezvyZmcDXWk4fHhFzmv6dOcS4ReWzPhsRa40iJUmSpJ5Ta3Tj35jVlWpL\n3QMxev393fVbZi/95tsJ5l/t/ME1MP9q5w+uQS/lX6/31Ya75g6wJEmSKsUeYLWt0ei+nlxJkqTR\ncgdYkiRJlWIBLEmSpEqxAJYkSVKlWABLkiSpUiyAJUmSVCkWwJIkSaoUC2BJkiRVigWwJEmSKsUC\nWJIkSZViASxJkqRKsQCWJElSpSw32QGoh9Rq1JsOB/rnTVookiRJY+UOsCRJkirFHeAuExFHAZ8E\n1s/MZyLifGBj4DGgBqwGfDUzz4uIG4BlgTcB/eU9s4CbgIMzc0ZEvAH4OjANWAX4CXAMcATwXuCV\nwFrA3DKEbTJz4UTkKkmSNBksgLvPHsClwAzg/PLcUZl5HUBErAr8JiLOz8xtynPnA5c23TO9ab5T\ngG9k5nURUQOuAt6XmacCp5b3HpyZMzqdmCRJUjewBaKLlMXofcAZwMeGuW0N4JnMbLQ57aPAPhGx\nBcUvPP8MXL2UoUqSJPUsd4C7y/7AOZmZEfFsRGxanv9yRBwLrEvRqvChUcx5JHAI8AXgLcA1wKHA\n46MNrkZLzb36aGforEa7vxIspXq9b2Ie1KXMv9r5g2tg/tXOH1yDqZC/BXCXiIhXATsAq0fEYcAr\nKArVhZQtEBGxA/Alil3idm2VmacBp0XEysBXgOMoeoCnlIGB+R1/Rr3eNyHP6VbmX+38wTUw/2rn\nD65BL+U/UqFuC0T32AM4NzO3y8ztgU2B7eDFN49l5o8o2hfOGsW8X46Id5bjnwTuBZ4dt6glSZJ6\njAVw99gfuGjwIDOfAq4E3tVy30nAhhHx3jbn/TDw2Yi4LSJ+TvFGiS+MQ7ySJEk9qdaYqMZJ9bza\nS5qAu0t/vy0QnWb+1c4fXAPzr3b+4Br0Uv71el9tuGvuAEuSJKlS/BCc2tZoTMwHzSRJkjrJHWBJ\nkiRVigWwJEmSKsUCWJIkSZViASxJkqRKsQCWJElSpVgAS5IkqVIsgCVJklQpFsCSJEmqFAtgSZIk\nVYoFsCRJkirFr0JW+2o16hP8yIH+eRP8REmSNNW5AyxJkqRKcQd4HETEXwNfBlYCVgZ+BJwPfD8z\nN2u672Bgjcw8oTzeBPgZsEVm3lqemw4cnJkzImJOOedTFL+svAo4KjOvjYjzgfcDr8nMZ8uxGwO3\nA1tl5pzy3FHAJ4H1M/OZ8tz5wCqZuUtTbI9k5hrjvDSSJEldxx3gpRQRrwQuBT6RmVsBmwFvAd7d\nxvADgK8CHxvhnr0yc3pm/iPwQeDUpmt/AN7TdLw7cH/L+D3K+Ga0nN8yIvZsI0ZJkqQpxQJ46b0P\nmJ2ZvwXIzIXAXsDskQZFxMrA1sDngS0i4tVtPGtd4M9Nx98Hdi3nWwbYGLi16RnTgfuAM3hpkX0M\n8PmIeF0bz5UkSZoybIFYemvRsuuamU9GxAJgw7KNofneS8qfZwBXZeYzEXEZ8BHgS0PMf2FEPA+s\nA9wM7Nt07ZfAP0XEy4F3ADcCGzZd3x84JzMzIp6NiE0z8xfltYeA44BzaW+3mhqNdm57icbYhgFM\n+Ifu2lGv9012CJPK/KudP7gG5l/t/ME1mAr5WwAvvd9T7Ly+ICLWB9YG5mbm9KbzBwODfbb7A89H\nxHUUfb6vi4jm9oZBe2XmPRFxELAb8GDL9R9Q7EJvC/wrcEr5rFcBOwCrR8RhwCuAQ4HBApjMvDgi\nPhARh4wl8XYNDMzv5PQTql7vm1L5jJb5Vzt/cA3Mv9r5g2vQS/mPVKjbArH0fghsHxGvB4iIacBM\n4G+GGxARbwGWzcwtM3P7sr/3PmDH4cZk5pkUxe/JLZcuoWi5WDMzm3ei9wDOzcztMnN7YFNgu4ho\n3VQ9BDgS6P1f5yRJktpgAbyUMnMesDdwdtnucAtwF3DtCMMOAC5qOXc2xQ7tSD4O7BoRb2t6/j0U\nnQL/2XLv/s3PyMyngCvLZzfHPwAcTrELLUmSNOXVGkvToKlKqY2xCbi/vzf+VNKOXvrTTyeYf7Xz\nB9fA/KudP7gGvZR/vd5XG+6aO8CSJEmqFD8Ep7Y1GlPrA22SJKma3AGWJElSpVgAS5IkqVIsgCVJ\nklQpFsCSJEmqFAtgSZIkVYoFsCRJkirFAliSJEmVYgEsSZKkSrEAliRJUqVYAEuSJKlS/Cpkta9W\no76UUwz0zxuXUCRJksbKHWBJkiRVijvAEyQi1gN+DdzRdHo28NHMXCMiTgB2ADbPzOfLMbcAMzLz\nd+XxUcAngfUz85ny3PnAKpm5S9OzHsnMNcqf/wH4HDANeDlwXmZ+OyKmA5cDc5viGcjMD41v5pIk\nSd3FAnhizc3M6c0nIuKjTYfrAccAJw0zfg/gUmAGcH7T+S0jYs/MvKhl7g2A04HtM/PRiFgRuDEi\n7geeAWZn5oyxpyNJktR7bIHoLl8Gdo+Iv229UO7Y3gecAXys5fIxwOcj4nUt5/cELszMRwEy82ng\n3cCscY5bkiSpZ7gDPLE2jIg5Tce7t1x/EjgQOD8iNmm5tj9wTmZmRDwbEZtm5i/Kaw8BxwHnUhS4\ng9YC7myeJDOfAIgIgK1b4rkmM08ddVaSJEk9xAJ4Yg3VArHYDZn504j4MXBi0z2vougPXj0iDgNe\nARwK/KJp3MUR8YGIOKRput8Da7c87228uPM/qhaIGo12bx3e6iNfbozDIzqtXu+b7BAmlflXO39w\nDcy/2vmDazAV8rcA7k7HArcCa5bHewDnZuanACJiJeCBiGh9K9khwC3A4P8zLwGujojLMnMgIlYG\nzqQorp/qcA5jMjAwf7JDGFG93tf1MXaS+Vc7f3ANzL/a+YNr0Ev5j1So2wPchco3POxLsdMLRfvD\nRU3XnwKuBA5oGTcAHA6sVB7/DjgKuKpsdfgJcEFm/qgcsnVEzGn5t2LHEpMkSeoCtUYv/M1ZXaE2\nLj0QI+vv7+7fKnvpN99OMP9q5w+ugflXO39wDXop/3q9rzbcNXeAJUmSVCn2AKttjUb39+hKkiQt\niTvAkiRJqhQLYEmSJFWKBbAkSZIqxQJYkiRJlWIBLEmSpEqxAJYkSVKlWABLkiSpUiyAJUmSVCkW\nwJIkSaoUC2BJkiRVil+FrPbVatTHMGygf964hyJJkjRW7gBLkiSpUiyAJUmSVClTpgUiIn4CfD4z\nZzed+zpwN/A64JHMPCMiXgV8BXgDMA14EDgoM5+IiN+Vx4uapj4iM29vmvMEYDfgYaABvAz4TGbO\naRm/LLAycEBm3hYRc4CVgKea5j41M6+JiL2BvYEasHyZx/URsQ/wpsw8umXuFYDby9ieGW5u4DfA\nb4HNBnOIiIOBNYCbgGPLezcHfj5UvpIkSVPNlCmAgbOBvYDZABGxPLAT8BngU033fR84MzP/vbzv\nk8CZwIzy+naZ+cwSnjUzM88ox78ZuBjYuHV8RLwbOAHYsby2V2be0zxRRLwCOA7YMDMXRMRawC8j\nYp0hnts897HAycARI8y9HjAPOC8i/j4znx28lpmzgFnlfY9k5vQl5CxJkjQlTKUWiCuArSNipfL4\nfcD1mfmXwRsiYl1gjcHit3Q6cNBSPHdV4Mlhrq0L/HkJ45+l2PU9JCJen5kPA6/PzEVLGDcT+Kc2\n4vstcB1FsSxJklR5U2YHuGwFuBr4AMWO7L68+Cf+QWsBD7SMWwg80XTq+ogYLD4XZuY2Qzzu8IiY\nASwEHgcOaBm/Qvms64Ajm65dGBHNbQofysyBiNga+ARwXblz/UXgO0vI9+nyOcPO3fTzcRS7yluO\nNOeS1GiMbeDqox/SGOOjJkK93jfZIUwq8692/uAamH+18wfXYCrkP2UK4NLZwKllT+yrMvNXLdcf\npOgHfkFETAP+OTMvLk+NqgViCNuVxfgpwPpAf9O1odoU1gJWzMxDy+O/oiiEfzZSABGxCjB/CXO/\nHCAzn42IfYFLKNao6w0MzF/yTZOgXu/r2tgmgvlXO39wDcy/2vmDa9BL+Y9UqE+lFggy826gD/gX\n4LtDXH8I+GNEvK/p9Mcp2iXG22cpdoE/uoT71gC+FxGD/5V+D/wRWLCEcUcBl7UbTGbeQVEAf7rd\nMZIkSVPRVNsBhqLwPRUY6kNkAHsC34qIIyl6b+/jpS0Mzf23X2/pGW5LZi6KiP2Bn0bE4PjWNoXL\nMvM7EfGN8r6nKd4ecU5mZkS8o2Xa6yNiYXnPnYzcXnEZcG3L+FMoPhgoSZJUWbVGNzdbqqvUxtwE\nPHr9/d3555Ve+tNPJ5h/tfMH18D8q50/uAa9lH+93lcb7tqUaoGQJEmSlmQqtkCoQxqN7v1wmiRJ\nUrvcAZYkSVKlWABLkiSpUiyAJUmSVCkWwJIkSaoUC2BJkiRVigWwJEmSKsUCWJIkSZViASxJkqRK\nsQCWJElSpVgAS5IkqVL8KmS1r1ajvoRbBvrnTUgokiRJY+UOsCRJkirFHeBxEBHTgcuBuUANmAac\nlpmXR8QjmblGRJwA7AY8XA5bDbg0M0+OiH2AE4H7m6a9OzMPi4hlgKOB9wALgQbwL8AjwL+V924E\n3As8BVyUmedGxFbAcRS/5CwPXAF8LTMbETEHWKm8fxngVcBRmXntuC6MJElSF7IAHj+zM3MGQESs\nDPwkIu5tuWdmZp5R3vMyYG5EnF1euyQzjx5i3qOAVwPvzMxFEfH3wA+AyMzp5VxzgIMz857y+G+A\nrwLvzcw/RMRywHeAI4FTy3n3aro/gCsBC2BJkjTl2QLRAZn5JHAm8MERbluNYqf46SVMdyBwUmYu\nKue+Ffj7zHxuhDEHA6dk5h/KMc8DRwAHDXP/usCflxCHJEnSlOAOcOc8Cmzccu7wiNgVWBt4CNg/\nM+cXG7DsFhGbNd17bmZeBKyUmYsVp5n5pyU8ewPg3JYx8yJipbKlAuDCiHgeWAe4Gdh3SQnVaCzp\nFlh9ybeMVqONx06ker1vskOYVOZf7fzBNTD/aucPrsFUyN8CuHPWBf635dzMzDwjIt4OXErRtzto\nuBaIP0fEKpn5wusVIuIDwA3N51o8BKwH/KppzCrAgrKNAsoWiIg4iKI3+cHRpTdxBgbmT3YIL6jX\n+7oqnolm/tXOH1wD8692/uAa9FL+IxXqtkB0QFlsHsCLH1JbTGbeDnwRuLRpR3Y4FwDHR0StnHtz\nYCbwzAhjvgN8NiLWKMdMA04rz7fGciZF8XvyEuKQJEmaEtwBHj9blx9GW0ixrsdnZpa7rS9Rvqnh\nw8AhwF94aQvEE5n5PooPrZ0E3BwRzwHPATtn5oLhAsnMOyLiM8BlEbEsRa/xVbz4AbhWHwd+btr3\nZgAAIABJREFUHRHfy8y72k9ZkiSp99Qa3dZgqa5Va6sJePz193fPn1p66U8/nWD+1c4fXAPzr3b+\n4Br0Uv71el9tuGu2QEiSJKlSbIFQ2xqN7vpAmiRJ0li4AyxJkqRKsQCWJElSpVgAS5IkqVIsgCVJ\nklQpFsCSJEmqFAtgSZIkVYoFsCRJkirFAliSJEmVYgEsSZKkSrEAliRJUqX4VchqX61GfYxDB/rn\njWsokiRJY+UOsCRJkirFHeAOiYjpwOXAXKABrALcDxwL3Abc0TJkm8xcWI79D2CZzNyxab7fAW/K\nzGeazl0MvBZYD1gAPAzcnZmHRcT6wFeA1YBpwF3ApzNzfkScAOxW3k95z6WZefL4ZC9JktS9LIA7\na3Zmzhg8iIhLgJ2BuZk5fagBEbEOsDIwLSI2yMz7h5s8M3cvx5wAPJKZZ5THKwL/Aeyfmb8oz+0N\nfB8YLKpnNt3/MmBuRJydmf1Lka8kSVLXswVigkTE8sCawJ+XcOt+wA+Ai4CPjvFx7wV+Mlj8AmTm\nBcCry53hVoO7xE+P8XmSJEk9wx3gzto6IuYAqwOLgLOAG4CvlecH3Z6ZR0TEMhStCZsBzwO/iYjj\nMnO0hekGwH1DnH8AWLf8+fCI2BVYG3iIYrd4/iifI0mS1HMsgDtrdmbOiIjVgFkUBSgM3wLxbqAP\nuKQ8HiyIzx3lcx8CNhni/BuAB8ufZ2bmGRHxduBS4N4lTVqjMcowmqw+/KXGUkw7Ger1vskOYVKZ\nf7XzB9fA/KudP7gGUyF/C+AJkJl/iog9gBuB949w6/4UO7HXAETEFsA3GH0B/APg2IjYJDN/Wc61\nP/DHzLw/Ippjuz0ivghcGhGbZ+aiUT5rqQ0M9M7Gc73e11Pxjjfzr3b+4BqYf7XzB9egl/IfqVC3\nAJ4gmTk3Ik4HDgc2bGmBAPg0sCnw4aYxN0XEChGxeXnqpogY3C+9JDNnDvOsJyNiJ4pWi9Uo/jv/\nGth1mPvPjYgPA4cA3xpbhpIkSb2h1ui1vz9r0tSWqgdieP39vfGbJPTWb76dYP7Vzh9cA/Ovdv7g\nGvRS/vV6X224a74FQpIkSZViC4Ta1mj0Vr+uJEnSUNwBliRJUqVYAEuSJKlSLIAlSZJUKRbAkiRJ\nqhQLYEmSJFWKBbAkSZIqxQJYkiRJlWIBLEmSpEqxAJYkSVKlWABLkiSpUvwqZLWvVqM+hmED/fPG\nPRRJkqSxcgdYkiRJlWIBLEmSpEqxBaIUEUcBnwTWz8xnynMHAnsAi4BpwLGZOae89n7g40ANWBE4\nNTOvKK+9DfhieX554Ebg85m5ICLOBy7NzOuanv1IZq4REScAOwCbZ+bz5bVbgBnAYcDbgTWAlYD7\ngYHM/FB53z8D5wFvzMyHy3Njnk+SJGmqsgB+0R7ApRTF4fkRMQN4F7BNZj4XEesDP42IvwX+iqJY\nfm9mPhkRqwG3RMRc4E/A94H3Z+a9EVEDjgO+BnysjTjWA44BTmo+mZlHAETEPsCbMvPolnEHAKcD\nBwInjMN8kiRJU5ItEEBETAfuA87gxSL1IOCUzHwOIDMfADbKzD9SFJunZeaT5bU/AZsA/xfYE/hu\nZt5bXmtQFJ87RMSKbYTzZWD3stBuN/71gVWBLwF7RsS0pZlPkiRpKnMHuLA/cE5mZkQ8GxGbAmtR\ntAW8oCx0GebanwEiYgNgVsu1RkQ8ArxmmOc3mn5+kmIX9/yI2KTN+D9CUXQ/HhE3A7sAly3FfEOq\nLRbmKKw+9OnGGKebbPV632SHMKnMv9r5g2tg/tXOH1yDqZB/5QvgiHgVRZ/s6hFxGPAK4FDg98Da\nwBNN974b+HXTtbuarm0BPAo8RNF20PyMZSmK5n7gaeBlLWEs9t8hM38aET8GTmwj/mUp2jceiIid\nKHaCD+XFAnhU802kgYH5kx3CqNXrfT0Z93gx/2rnD66B+Vc7f3ANein/kQp1WyCK4vHczNwuM7cH\nNgW2Ay4CjouI5QAi4q+Ac4CFFB82+1REvLy8tnp5biXgAuDAiHhjea0GHA/8KDOfAu6g2KGlvP4P\nwNwh4jqWojB/wxLi3wG4NTO3ysztM3MT4DUR8dYxzidJkjSlVX4HmKL9Yc/Bg8x8KiKupNjhvQX4\nWUQsAJYF9sjMfqA/Is4CZkXEcxRvezgmM38NEBF7At+OiJUo3h4xB/hE+YjzgY0i4k5gPrCAokVh\nMZn5TETsC9y8hPgPoCjMm51DsQv88BjmkyRJmtJqjV5txNSEq425CXho/f298SeUZr30p59OMP9q\n5w+ugflXO39wDXop/3q9rzbcNVsgJEmSVCm2QKhtjUZvfnBNkiSpmTvAkiRJqhQLYEmSJFWKBbAk\nSZIqxQJYkiRJlWIBLEmSpEqxAJYkSVKlWABLkiSpUiyAJUmSVCkWwJIkSaoUC2BJkiRVil+FrPbV\natSHuTTQP29CQ5EkSRord4AlSZJUKe4AtykipgM3Artm5qVN538N3JGZ+0TEWsD/AHtn5r81jbsc\nmAs0gFWA+4HdgbWASzNzs/LeLYHzgA8CHwB2Ax5uCmMW8Evg2PJ4c+Dn5c9HAIcBlwL3AL8FNsvM\n28u5DwbWyMwTImK5co4dgGfK8Rdn5llLt0qSJEndzwJ4dO4BZlAUmUTEW4CXN13fFzgd+Bjwb03n\nZ2fmjMGDiLgE2Bm4rencdODbwHsz896I+AAwMzPPGCKOWeWYRzJzetMczffMA86LiL/PzGdbxp9M\nsfu/eWYujIiVgWsi4qeZec8SV0GSJKmH2QIxOncB60bEK8rjPYCLASKiBuwJfBVYPiL+ZqgJImJ5\nYE3gz03ntqUofrfPzHvHKdbfAtdRFLvNz18O+DBwTGYuBMjMJ4HpFr+SJKkK3AEevSuBXSLifGAT\n4EvAOsA2wN2ZORAR36XYBT6kHLN1RMwBVgcWAWdl5g0RsR7weooidQVgxZZnHR4RM5qOT87MWaOI\n9Tjgl2VrxaBXA49l5vMAEXEIRUHcFxEXZeZpw01WozH8k1YfRVRL0BjhMd2gXu+b7BAmlflXO39w\nDcy/2vmDazAV8rcAHr1LgO9Q9PH+d9P5A4D1I+I6YHngbRFxdHltdmbOiIjVKNoXHmga9zTwHop+\n3ssjYrPMfLq8NlwLRFsy89mI2LeM+ezy9J+A1SJi2cxcmJnfAb4z2CM81meNp4GB+ZMdwrDq9b6u\njq/TzL/a+YNrYP7Vzh9cg17Kf6RC3RaIUcrM+yn6fv8F+F55+tXAZsCmmbl9Zm4NXAXs3TL2TxRt\nE+dExJrl6Ycz87HM/CFFQf3NcY73DooC+NPl8XMUu9j/GhHLAETECmX8Xb73KkmStPQsgMfmMmDt\npn7dfwSuHOypLZ0NfBSoNQ/MzLkUH5Q7fYh5jwQ2iYi9yuPDI2JO078zxxjvKcDvm46PAuYDPy1b\nM34O/AH42hjnlyRJ6hm1Rrc3XKpr1EZsAh4//f3d+6eVXvrTTyeYf7XzB9fA/KudP7gGvZR/vd5X\nG+6aO8CSJEmqFD8Ep7Y1Gt39ATVJkqR2uAMsSZKkSrEAliRJUqVYAEuSJKlSLIAlSZJUKRbAkiRJ\nqhQLYEmSJFWKBbAkSZIqxQJYkiRJlWIBLEmSpEqxAJYkSVKl+FXIal+tRn0ppxjonzcuoUiSJI2V\nO8CSJEmqFHeAp4CI+Gvgy8BKwMrAj4DzgbuAO4AGsAJwY2Z+pmncfwDLZOaOEx2zJEnSZHEHuMdF\nxCuBS4FPZOZWwGbAW4B3A3Mzc3p5fgtgq4h4azluHYpi+RURscHkRC9JkjTxLIB73/uA2Zn5W4DM\nXAjsBcxuuW8F4GXAU+XxfsAPgIuAj05MqJIkSZPPFojetxZwf/OJzHwyIhYAG0bEHIoWiIXA1zPz\nfyJiGWA3it3i54HfRMRxmfn0xIYuSZI08SyAe9/vgY2bT0TE+sDalC0QQ4x5N9AHXFIeDxbE5470\noBqNMQfZKIcu7VskukG93jfZIUwq8692/uAamH+18wfXYCrkbwHc+34IfCYivpOZ90XENGAmMGuE\nMfsD+2fmNQARsQXwDZZQAC+NgYH5nZp6QtXrfVMml7Ew/2rnD66B+Vc7f3ANein/kQp1e4B7XGbO\nA/YGzi7bHW6hePvDtUPdHxGvATYF/qtpjpuAFSJi844HLEmSNMncAZ4CMvN2YOshLm02xL2PAq8b\n4vyGHQhNkiSp67gDLEmSpEpxB1htazSmTi+vJEmqLneAJUmSVCkWwJIk6f+3d/fxVo35/8dfuxyl\nOkXZlQydMD70rUEYjCYpYsbNYBgpGRSKzExuy+gUikmDJImkJne5vycZI4Nh5keDGekzI2Km1DlS\nKifdnf37Y63TrHb73Na52Xu9n4+Hh7Ova61rXZ9rrxmffZ3P2kckVpQAi4iIiEisKAEWERERkVhR\nAiwiIiIisaIEWERERERiRQmwiIiIiMSKEmARERERiRUlwCIiIiISK0qARURERCRWlABL1SUSJNu2\nrO9ZiIiIiGwTJcAiIiIiEis71PcEapOZ9QQeBeYDKWAn4EFgFjAFyAdahP2XAgOBE939+MgYTwB/\ndPe7zOzHQCGQBzQHprv75PA6g929b+S83wEL3H2GmSWB3wMdgcbAf4DL3H2pmZ0L7Ofuw9PmngeM\nAI4FNgEbgGvd/a9hfxIYD+wPlAAbgevd/Y3ofMxsH+D2cM4tgdfDcS8HTgB2BjqEawDQ2903VX+1\nRURERLJDTifAoT+VJaZm1gRwoCvwirtPCdsnAIOBCcDPzGygu08zs75AXpj87gVMBI5392VmthPw\nmpl9CnxX3sXNLAE8Cfze3Z8J244BnjezwyqY9/UEyfJR7l5qZh2BF8zsJGAR8Aww3t3PDcfcC3jC\nzH6YNs6NwB3uPjsyl5+5+3hgfKbkXURERCSXxa0EIp9gN3UxcLqZHRMmslcAE909BZwPjDSzzsBv\nCXaFAQYAM919GYC7rwWOA16p5JoHA9+UJb/huX8EFgI9KjjvbOAady8Nz/kcuBM4F/gh8JW7PxUZ\n81Ogm7tvSBtnGXCumR1J8IHnF8DTlcxZREREJGfFYQe4l5nNBUoJygguBWYTJJJXAo8BbwIXA/9x\n9/+YWSHwNtDX3YvDcToA70cHdvdvAMwsep0yexGUS+xFkOym+5SgJGIrZtYW+NrdN2Y45zCgE/BJ\n5Pi7AQOSZjYw7ZwrgCHATQQ73y8AQ4GVma4tIiIikuvikAD/Kf3X+2EJwkx3vy8si7iKoPzh5wDu\nPtPMbnb3lyKnfQ7skTbOAfxvF32L64Q1wBDsNhdkmNf3CXaP98zQtxJobWY7pCXB3we+IKghPrOs\n0d0vCq85C2iaNtbR7j4BmGBmLQhqkUcS1ABXS4JU8EPb6p5ZM6lU3VynupLJ/PqeQr1S/PGOH7QG\nij/e8YPWIBfij0MCnMmvCHZ0Z7r7OjP7iOBhsoo8BDxtZo+4e3GYTN5NUKtbUsF5fwHam9lJ7v4c\ngJkdD+xD8EDagPQT3H29mT0KjDWzEWEN8F4Eu9QnEtQAtzezk9392XDM9sB+BA/7JSLD3Wxma939\ndXdfY2b/AnatJNYGobh4dX1PYSvJZH6DnFddUfzxjh+0Boo/3vGD1iCb4q8oUY9rAjwYmGxmw4C1\nQDFBmUC53H2RmV0FPGlmmwjqie919xfDB8nKOy8VPrg2wcyuCZv/A5zg7pvC8olfhrvSZXoCVwOj\ngXfMbD2wDhgU1voSjnmTmV0ZnpMHTAbeYMva4jOBiWZ2C7CeoIyiwlhFREREclki1VB/zywNTmJz\nDUTdKCpqeJ8ws+mTb21Q/PGOH7QGij/e8YPWIJviTybzE+X1xe1bIEREREQk5uJaAiE1kEo1zLpc\nERERkerQDrCIiIiIxIoSYBERERGJFSXAIiIiIhIrSoBFREREJFaUAIuIiIhIrCgBFhEREZFYUQIs\nIiIiIrGiBFhEREREYkUJsIiIiIjEihJgEREREYkVJcAiIiIiEis71PcEJIskEiRrYdjiolW1MKqI\niIhIZtoBFhEREZFY0Q5wHTKzAuBDYF6k+U/ufr2Z/QKYDnzf3ZeEx48G+gFLwmPbALPcfayZnRse\nf4S7vxMenwd8CUxy99Fmth74S9o0+gPHAtcDn4ZtOwNvufsl2zFcERERkQZJCXDdm+/uPTO0XwBM\nBC4ERkfab3X3KQBm1gSYb2ZTw74FQF/gnfD18cA3kXO/znQtMwN4yN2Hh68bAW+Y2SHu/m7NwhIR\nERHJDiqBaADMrBPQGhgHDAh3cjNpA+QBa8PXLwHHhgkswFnAwzWYQj7BLvA3lR0oIiIiku20A1z3\nOpvZ3Mjr/sBA4D53X2lmbwOnAY+E/ZeZ2VnAHsBiYJC7rw53cdcDbwNHmdm7QEvgv0D78NzWadda\n7O79w5/7mdkRwG7AKmCsu/+7ooknSJXblyq/q1K18WBdbUom8+t7CvVK8cc7ftAaKP54xw9ag1yI\nXwlw3duiBMLMGgNnA5+Z2UkEO8FD+V8CfKu7TzGzg4FZwL/SxnuIYOd3T+BJYMdIX8YSiLLz3H14\nuPs8O8O41VJcvHpbTs8ayWR+bGLNRPHHO37QGij+eMcPWoNsir+iRF0lEPXvp8D/c/ej3f14d/8h\n0M7MfhA9yN3fA34HzIqUPADMBQ4HzgAer+7F3f0z4BLgMTNrVsMYRERERLKGEuD6dwFwf1rbvQS7\nwFtw92kE5QpDIm2lwCtAibunf6FuazObm/bPERnG/SPwR+C6bQtFREREpOFLpLaleFNiJVFBEXBR\nUXb8OmRbZdOvfmqD4o93/KA1UPzxjh+0BtkUfzKZnyivTzvAIiIiIhIreghOqiyVis/DbiIiIpK7\ntAMsIiIiIrGiBFhEREREYkUJsIiIiIjEihJgEREREYkVJcAiIiIiEitKgEVEREQkVpQAi4iIiEis\nKAEWERERkVhRAiwiIiIisaIEWERERERiRX8KWaoukSCZobm4aFWdT0VERESkprQDLCIiIiKxoh3g\nbWBmVwHDgE7u/p2ZzQC6AV8DCaANcIu7Tw+PPwX4ddi3EzDe3R83s3OB/dx9eGTsWcAUYBEwCzgJ\neCzsPhD4F1AC3A/sAfQDlkSm94q7jzWzpsAY4DAgBawBLgJ2Bu4Ijz0c+BtQGs7phe2wPCIiIiIN\nkhLgbXM2QXLaF5gRtl3l7rMBzKw18FGYGB9BkCyf4O5rzKwN8I6Zza/Khdy9GOgZjjsXGOzuC8LX\no4Fb3X1KhlMnAAvc/Yrw2FOBR939iMh4i4A+7v5dlSMXERERyVIqgaghM+sJLCTYpb2knMPaA9+5\newq4AJjg7msA3H058EPg41qc447Az4Dby9rc/SngxNq6poiIiEhDpx3gmhsE3OvubmbrzOywsP1m\nM/st0BGYD5wRtncAPo0O4O4rAMwMoJ+ZHR7p7kyQXFfVZWbWN/J6LPBPYGmYgEevu7wa426WIJW5\no21NRttSqpyhG6JkMr++p1CvFH+84wetgeKPd/ygNciF+JUA14CZ7QL8FGhrZpcCrYChwCbCEggz\n+ykwjmCXGOBzglrdDyLjHAksC18+lKEGuDq2KoEwszxgZzNLRJNgM+tPUAaxoZrXqDXFxavrewpV\nkkzmZ81ca4Pij3f8oDVQ/PGOH7QG2RR/RYm6SiBq5mxgmrv3cffjCR4w6wP/+5Ywd38ReBq4J2ya\nDlxpZs0BzKxt2NastiYZJrgvA5eWtZnZGcCvG1LyKyIiIlKXtANcM4OAAWUv3L3EzJ4I2++IHHcD\n8HczO8HdXzCze4BXzGwDwbdAjHD3D82s23aYU3oJhLv7RcBlwK1m9heCb4FYAfx8O1xPREREJCsl\nUtlUfCn1KlFuEfC2KyrKnl+nZMuvfmqD4o93/KA1UPzxjh+0BtkUfzKZnyivTyUQIiIiIhIrKoGQ\nKkulsudhNREREZHyaAdYRERERGJFCbCIiIiIxIoSYBERERGJFSXAIiIiIhIrSoBFREREJFaUAIuI\niIhIrCgBFhEREZFYUQIsIiIiIrGiBFhEREREYkUJsIiIiIjEiv4UslRdIkGymqcUF62qlamIiIiI\n1JR2gEVEREQkVrQDXMfMrCfwKDAfSABNgCHu/vew/33gLXe/JHJOCjjF3Z8JXx8P9HX3c81sLjDY\n3ReYWQvgBeAlYBbwITAvbQq9gZFAP2BJ2NYGmOXuY7d/xCIiIiINixLg+vEnd+8LYGZ9gBuAE83s\nSOAfQC8zy3f31eHxJcCtZvaWu3+VaUAzawm8CDzk7pPNrACY7+49MxwLcKu7TwlfNwHmm9lUdy/a\nnoGKiIiINDQqgah/uwBlSecFwOPAU8AvI8esBm4B7ipnjJ2BV4Cp7j65BnNoA+QBa2twroiIiEhW\n0Q5w/egVli40AQ4ATgl3cLsDgwjKI54GJkXOuSs8rh/wddp4DwBLgd3T2juH1ynznrtfHv58mZmd\nBewBLAYGRXacRURERHKWEuD6ES2BMOBt4LcEO/LPh8fsZma93f1VAHdPmdn5wJ+BMWnjDQfmAO+G\nZRKvh+0ZSyBCt7r7FDM7mKBe+F+VTTpBqsoBbtY2+FeqBqc2VMlkfn1PoV4p/njHD1oDxR/v+EFr\nkAvxKwGuf8vCfw8CTnL3jwDMrD9wCfBq2YHu/l8zGw38nqDet8w/3X2VmZ0DPGpmh1T14u7+npn9\nDphlZj9y99JtCyez4uLc2FxOJvNzJpaaUPzxjh+0Boo/3vGD1iCb4q8oUVcCXD/KSiA2AfkEO7pn\nlyW/oSeA28xsj+iJ7j7TzE7NNKi7v2Nm9wAPAReydQkEwHkZzptmZmcCQ4A7axaSiIiISHZIpHLp\nd9NSqxI1qoEIFBVlx6fFymTTJ9/aoPjjHT9oDRR/vOMHrUE2xZ9M5ifK69O3QIiIiIhIrKgEQqos\nlcqdWl4RERGJL+0Ai4iIiEisKAEWERERkVhRAiwiIiIisaIEWERERERiRQmwiIiIiMSKEmARERER\niRUlwCIiIiISK0qARURERCRWlACLiIiISKwoARYRERGRWNGfQpaqSyRIVvHQ4qJVtToVERERkZrS\nDrCIiIiIxIoSYBERERGJlZwqgTCznsCjwPxIczHwLdDS3U+LHLvU3dub2YPA7kABsB5YAvwDeCIy\nVgpoCXwK9Ac6AB8C89Km0BsYCfQLx0kBTYBr3H2umS0CvgBKgcZAC+ACd3/XzOYCzYCSyHjjgY+A\nfwOHu/t74dwHA+3dfXTamGUuB/KBwe7eNxLz74AFwNy0+TcF1gBnuPuKrRZWREREJIfkVAIc+lM0\n6QMwsxlAdzMb4O73R/vcvX94zGhgqbtPCV/3TB/LzB4CTgbeBea7e8/0i5sZwK2RcfYHHgS6hYf0\ncffvwr7jgNHAiWHfOe6+IG28AmAVMN3MDnX3dRli3jxm5Lyt5pZmi/mb2U3AQOD3lZwnIiIiktXi\nVAIxArjOzL5Xk5PNbEdgN6C6O6StCXZXM+lYxfH+DcwGxlbz2lViZglgjyrORURERCSr5eIOcK+w\nnKDMC+G/FxOUJ0wDjqvmWG0JSgzucfdXw13ZzmnXec/dLw9/vszM+gKbgJXABZHj5phZU4IyitnA\nFZG+mWYWLYE4I/LzSOBvZtY9wzznmFlZCcQmd+9dQUyp8N9l828N7ESwS/2HCs4jsfnUKmhbzsWr\nMURDlUzm1/cU6pXij3f8oDVQ/PGOH7QGuRB/LibA5ZVA4O4PmtmpZjakOmOZWRvgFeCzSF/GEojQ\n5hKIDPq4+3dmdiPQCSiK9GUqgWgezn2dmZ0HPARMzTRmWttagvrjqBZh++b5m9lOwHPAMnffWM6c\nt5vi4tW1fYlalUzmZ30M20Lxxzt+0Boo/njHD1qDbIq/okQ9TiUQZYYQ7LpW+eOLuy8HzgbuNbPd\nttM8riXYBb64GvOYR5AAX12Fwz8GDiqbb7jr3IO0B/fcfS3Bg32FZnZAVeciIiIikq1ycQc4vQQC\nYFnZD+5ebGaXAU9XZ1B3n29mE4GJwJVsXQIBcF41xis1s0HAn83sqbA5vQTiEeCltFNvBE5Ka4uW\nQADc7u5PhXG+EI65I3CHu38SlnBE57LMzK4A7jazH7l7dCwRERGRnJJI5UJRptSJRLWKgDMrKsqO\nX5uUJ5t+9VMbFH+84wetgeKPd/ygNcim+JPJ/ER5fXEsgRARERGRGMvFEgipJalU9j/EJiIiIqId\nYBERERGJFSXAIiIiIhIrSoBFREREJFZUAywiIiISE/PmvUth4QgKCjqRSCRYt24dffocz+mn9630\n3IULP2HRoo0UFOxXBzOtXUqARURERGLk4IMP4brrbgJg/fr19Ov3c4477gTy8yv+G2Fz575Kx467\nKwEWERERkexVUlJCo0aN+OSTfzF9+lRKS0tZu3Yto0aNIS8vj6uvHkbLlq3o1u0QXnrpeZo2bUKH\nDgXcdtvNTJ06E4DCwhH07dufzp271HM0VacEWERERCRG3nvvXYYOvZBGjRqxww47MGzYlXz22acU\nFt7ArrsmmTnzPl577Y/06fMTvv56OdOmPUBeXh6pVIqOHXenc+cuNGnSlM8++5Q2bdrw5ZeLsyr5\nBSXAIiIiIrESLYEo88Ybc5kwYTw77dSM4uIiunY9AIDddutAXl7eVmOcdNIpvPTSc7Rr154+fX5a\nJ/PenpQAi4iIiMTcuHFjefTRp2nWrDljxoza3J5I/O8Lwxo1akRpaSkAPXv25uGHH6BVq1bccMPv\n6ny+20oJsIiIiEjMHXfcT7j44gvYaaem7LJLG776qnirY8z25+6772DXXTvQrdshHHjgQaxYsYKW\nLVvVw4y3TSKVStX3HCRbJBKbb5biolX1OZN6k0zmx/rPQSv+eMcPWgPFH+/4QWsQjf+WW8bRs2cv\nDj740HqeVWbJZH6ivD79IQwRERERqZZhwy5h9epVDTb5rYxKIGrAzHoCjwLzI83FwLcQMFZvAAAR\ny0lEQVRAN+BrgrX9Chjm7p+Z2WhgqbtPiYzzDtDX3ReZ2Y+BQiAPaA5Md/fJkWOvAoYBndz9OzNL\nAo+F3QcC/wJKgPvdfZqZHQ2MJPiQsyPwOHCbu6fMbC7QLDy+EbALcJW7v7SdlkhERERy2G233Vnf\nU9gmSoBr7k/uvsWfTTGzGQSJ5Ozw9Y8JEuUKPx6Z2V7AROB4d19mZjsBr5nZp2VjAWcDs4C+wAx3\nLwZ6hufPBQa7+4LwdRfgFuAEd//SzHYA7gKuAMaH450TOd6AJwAlwCIiIpLzVAJRi9z9DWCDme1T\nyaEDgJnuviw8by1wHPAKbN5xXghMAS6pwqUHAze6+5fheBuBy4GLyjm+I7CiCuOKiIiIZD3tANdc\nr3DntcwL5Ry3DNi1gnFSQAfg/Wiju38TeTkIuNfd3czWmdlh7v7XCsbcC5iWNt4qM2tmZmUfemaa\n2UZgT+Bt4LwKxgMgQeSBybaVHV0z2fBMZjJZ8Z+KzHWKP97xg9ZA8cc7ftAa5EL8SoBrrrwSiHQd\ngf8Ca4EmaX0twvbPgT3SxjqAYId+EfBToK2ZXQq0AoYCFSXAi4EC4O+R8VoC6929NKh4CEogzOwi\noB/wRQXj1ZmG/mStnv5V/HGOH7QGij/e8YPWIJviryhRVwJci8zsWKDE3f9rZvOA4WZ2p7tvNLO9\ngSbuXmRmDwFPm9kj7l5sZi2Au4Hrge7ANHe/MhyzGfCZmSXDOuBM7gKmmtnb7r7UzPKACWH7Ftz9\nbjPrDowFrtzOSyAiIiIVaNt2++6mFhVVnpzOm/cuhYUjKCjoBMDGjRs544yz6N372O06l5pauPAT\nVq9exYEHdqu1aygBrrn0EggIyh1uNrPhwCZgNXAmgLu/Eiaa75nZKiABnBP2LQq/5eFJM9sE5BOU\nPLxoZh8Q1AgTHltiZk8AFwA3ZpqYu88zs2uAR8ysMcE3SzzJ/x6AS/dr4EMze8DdP6j2SoiIiEhW\nif455JKSEoYOvZA999yT73/f6nlmMHfuq7Rp06ZWE2D9IQypssQWRcC1oyqfXOtTNv3qpzYo/njH\nD1oDxR/v+GH7r0F97QA/88wTmxNggGeeeZJly5ZSWlrKBx/8ndLSUs48sz+9eh3D0KEXss8++/LZ\nZwtp1Sqf/fbryt/+9jZr1qzh1lsn0axZM2688TqWLFnMpk2b6Nu3P7179+Gjj/7JxIm3UFpaSjLZ\nllGjbuDyy3/FLru0ZtWqVYwdezPjxo1hzZrVfPVVMaed9gu6d+/BkCED2WGHPAoLr6dz5y41XouK\n/hCGdoBFREREYq5169bMmvUA++5r3HXXNNatW8dFF53HoYceBkDnzv/Hb35zBcOH/4amTZsyYcJk\nxowZxfvvz6O4eBk777wzhYU3UFLyLeeffzYHH/xDxo+/kdGjx1JQ0Innn3+aRYsWAXDMMcdx1FFH\n476AY47pw1FH9eKrr4oZOvRCTj31dH7ykxNp06bNNiW/lVECLFWWSjX8h9RERESk+pYuXUqfPj/h\n5ZdfZOjQC4GgNnjp0iUA7LvvfgC0bNlyc+1wfn5L1q9fx6JFizjkkB8C0KxZcwoKOrF48X/5+uvl\nm4898cRTNl9rzz07AkHS/eijD/H666/RrFlzNm7cWDfBou8BFhEREYm1b79dw3PPPUXz5i046KBD\nmDTpHiZOnEKvXsew++7fAyCRKLeagIKCAj78MPjiqZKSb1m4cCEdOnRg11135T//Cb5k6oEHZvD6\n668B0KhRkH7OmvUAXbr8gMLCG+jV6xjKynIbNWpEaWntVl1qB1hEREQkZt57712GDr2Qxo0bs2nT\nJgYOvIgePY5m0qTbuPjiQaxdW0KPHkfTrFnzSsc6+eTTGDduDEOGDGTdunWcf/4F7LJLa6688hpu\nuul6GjVqRJs2bfjFL/rx2GMPbz7vyCN7cNttN/Pqq3No0aIFjRs3Zv369Zjtz+TJt1NQ0Ilu3Q6p\nlfj1EJxURyruJRBxfwBE8cc7ftAaKP54xw9ag2yKv6KH4FQCISIiIiKxogRYRERERGJFCbCIiIiI\nxIoSYBERERGJFSXAIiIiIhIrSoBFREREJFb0PcAiIiIi9STZtuV2Ha+4aFWlx8yb9y6FhSMoKOhE\nIpHg22+/pUOH3Rk1agx5eXnbdP2xY0fTu3cfDj/8R5vbvvxyCaNGXcM998xg1KgRXHvt9dt8nW2l\nBFiqLpEguR2Gqcr/OEVERKT2HHzwIVx33U2bX48e/VvefPN1jj76mFq9bvSa9UkJsIiIiEiMbdiw\ngeXLvyI/vyVTpkzigw/+TmlpKWee2Z9evY5h6NAL6dixgM8/X0ReXmOuvfYGPv98Ec8888TmhPbk\nk4/j2WdfBuCppx7j4YfvZ9OmTQwfPpLGjRtvvtbpp5/Egw8+TlHRMsaNG8OGDRto2rQpo0ffyIoV\ny7njjtsoLS1l5cqVXHHFcLp2PYC+fU+la9cD+OKLz2ndujVjxty8xZg1EdsE2MwKgFnAAqClu58W\n6VsK7AYsBI5194WRvmeAO4BrgWZASWTY8e7+gpn9EvglkAB2BK5z9zlm9irQGNgPKAK+Bl4BFgPT\ngSPc/Z3wOnnAl8Akdx9tZuuBv6SF0R84FhgNdHX31eG5s4ApwKHACcDOQAdgfnheb6APcEU4x2bA\nHe7+YPVWUURERLJR2Z9CXrlyBYlEgpNPPo0NGzbw5ZeLueuuaaxbt46LLjqPQw89DIAuXX7AlVde\nw5w5z3L//dPp0ePocsfu0uUABgw4l7fffpPJkydy6aXDtjrmzjsncPbZ53L44T/izTdf59//dlav\nXsXQocPYe+99mDNnNi+++Bxdux7AkiWLuf32u2jXrj1DhpzPxx/Pp0uXrtsUf2wT4DTdzWyAu99f\n1uDuKTO7DxhAkGBiZu0AA14lSIDPcfcF0YHMrBUwEujs7uvNrAPwNzPb0917h8fMAGa5++zw9bkE\niXhf4J1wqOOBbyJDf+3uPdMnbmYQJLATgIHRPncfD4w3s57AYHfvGznvbuAH7r7SzPKBD8zsFXcv\nqtKKiYiISNYqK4H45puVDBt2Cbvt1oFPP/0E9wUMHXohABs3bmTp0iXh8YcC0K1bN2bPnrPVeKlU\navPPBx54EBAkwnfeOTHj9b/44nO6dPkBAN27HwXABx+8z4wZ99KkSRNKSkpo3rw5AK1a7Uy7du0B\naNu2HevXr9vm+PUtEIERwHVm9r209unAWZHX5wAz3D1F+dYR7PoOMbO93X0JsLe7l1Yyh5eAY82s\n7D05C3i4ivP/A7C/mZ1YxeMBVgK/NrP/A9YA+yv5FRERiZdWrXZm5MgbGDduDK1bt+Gggw5h0qR7\nmDhxCr16HcPuuwepkfvHAMybN49OnfZixx2bsHz5cgCWLv2SVav+t2f38ccfAfDBB39nr732znjd\njh07bT5uzpyXePzxWdx++3gGDryIa6+9jr333mdzUp1IJLZ73NoBDiwm2LWdBhxX1ujui83MzexI\nd3+LoOTguMh5M80sWgJxhrsXm1kv4DfAbDPbEfgdcFclc1gPvA0cZWbvAi2B/wLtw/7WZjY3Omd3\n7x/+vImg5OIlM3u7ijH3AYYRJNltgSlmdl0lyb2IiIjkmE6d9uL008/krbfeoF27dlx88SDWri2h\nR4+jadYs2IV98cXneeSRh2jZsgVXX11I8+YtaNGiBRdc8EsKCjqx2267bx7vo4/+wa9+NZhEIsGI\nEYVb7A6XueSSXzN+/I384Q/TaNq0KYWFN7Bx40ZGjrya/PyWJJNt+eablbUWcyLTpOIgrQZ4lrvP\nNrPHCcobRrl7+/C4k4ATCXaDL3f3M8L2uQRlBeklEB2ANu7+j/D1vsBs4GeRthlsXQKxHzCHoAzi\nLYJa4R2B9mEN8NKyOaVd71xgP3cfbmaXAt2BFDDF3eeGx/QkUgJhZrsA+7r7X8PXuwNPAGPd/bny\n1iyRoNKbJaa3k4iISM4aMGAAo0ePZu+9M+/mNmDlbh1rB3hLQwhqcPMjbS8CY4FS4J4qjNEemG5m\n3cOH0j4HviLY4a3MXIJa3g5Av/Cf6pgEnAJ0JXgIrjxNgEfM7DB3X0bwsN1SgvKNbVJcvHpbh2jQ\nksn8nI+xIoo/3vGD1kDxxzt+iOcarF+/kRUrSiguXp1V8SeT+eX2KQGOCMsXLgOejrRtCr/54Qzg\n4rRT0ksgHnH3u8zsDuDPZraWYCf3Xnf3Kly/1MxeAfZw91XhA25l0ksgIKhdjp6fMrPzgH9Ucp2l\nZvYr4Hkz2xjO8Xl337qqXURERGJt0qSq7P9ll9iWQEj1VaUEoqgoOz4V1lQ2ffKtDYo/3vGD1kDx\nxzt+0BpkU/zJZH65JRD6FggRERERiRWVQEiVpVK5X+MrIiIiuU87wCIiIiISK0qARURERCRWlACL\niIiISKwoARYRERGRWFECLCIiIiKxou8BFhEREZFY0Q6wiIiIiMSKEmARERERiRUlwCIiIiISK0qA\nRURERCRWlACLiIiISKwoARYRERGRWNmhvicgDY+ZNQImAwcA64BB7v5JpP8koBDYCNzn7lPrZaK1\npArxDwMGAcVh00Xu7nU+0VpmZocB49y9Z1p7Tr//URWsQU7fA2aWB9wHFABNgDHu/mykP6fvgSrE\nn9PvP4CZNQamAgakgMHu/s9If67fA5XFn/P3AICZtQXeA4519wWR9qx//5UASyanAE3d/QgzOxy4\nBfgZbP4Pw23AocC3wFtm9qy7L6u32W5/5cYfOhg4x93fq5fZ1QEzuwoYQPAeR9vj8P4D5a9BKNfv\ngbOB5e4+wMxaA+8Dz0Js7oFy4w/l+vsPcBKAux9pZj2BscTrvwPlxh/K+XsgfJ/vBtZmaM/6918l\nEJJJd2A2gLu/AxwS6dsf+MTdV7j7euBNoEfdT7FWVRQ/BP/HN8LM3jSzEXU9uTqyEDgtQ3sc3v8y\n5a0B5P498BgwMvw5QbDLUyYO90BF8UPuv/+4+9PAheHLjsDKSHfO3wOVxA8xuAeA3wNTgCVp7Tnx\n/isBlkxaAt9EXm8ysx3K6VsNtKqridWRiuIHmAUMBnoB3c3sxLqcXF1w9yeADRm64vD+AxWuAeT4\nPeDua9x9tZnlA48D10a6c/4eqCR+yPH3v4y7bzSzPwB3AA9GunL+HoAK44ccvwfM7Fyg2N1fztCd\nE++/EmDJZBWQH3ndyN03ltOXz9afjLNdufGbWQKY4O5fhZ98XwAOqoc51pc4vP8Viss9YGZ7AK8B\n97v7Q5GuWNwD5cUfl/e/jLv/EtgXmGpmzcPmWNwDkDn+mNwD5wPHmtlc4EBgppm1D/ty4v1XDbBk\n8hZB/dOjYQ3sPyJ9HwPfD+vi1hD82uP3dT/FWlVR/C2Bf5rZ/gS1T70IHpaJizi8/5XJ+XvAzNoB\nc4Ch7v5qWnfO3wOVxJ/z7z+AmQ0AvufuNwElQGn4D8TjHqgo/py/B9x9c0lDmAQPdvelYVNOvP9K\ngCWTpwg++f2FoP7tPDPrB7Rw93vM7DLgZYLfINzn7ovrca61obL4ryHYGVoHvOruL9bjXOtEzN7/\njGJ2D1wD7AKMNLOyWtipQPOY3AOVxZ/r7z/Ak8B0M/szkAf8BjjVzOLy/wOVxR+He2ALufbfgUQq\nlarvOYiIiIiI1BnVAIuIiIhIrCgBFhEREZFYUQIsIiIiIrGiBFhEREREYkXfAiEiIiIiDZaZHQaM\nc/ee5fQfDwwPXyYI/qJrF3f/uLwx9S0QIiIiItIgmdlVwADgW3c/vArHXwns4u7XVHScdoBFRERE\npKFaCJwG3A9gZl2BiQQ7vcuB8939m7DvewTJ8qGVDaoaYBERERFpkNz9CWBDpGkqcElYDvEicFWk\n7zLgNndfV9m42gEWERERkWyxPzDZzCD4K33/BjCzRsCJwG+rMogSYBERERHJFg6c4+5fmNmRwG5h\nexdggbuvrcogSoBFREREJFsMAWaa2Q5AChgYthvwaVUH0bdAiIiIiEis6CE4EREREYkVJcAiIiIi\nEitKgEVEREQkVpQAi4iIiEisKAEWERERkVhRAiwiIiIisaIEWERERERiRQmwiIiIiMTK/wePLN1n\nJUrcSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23b42f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_pt[['Democrat','Republican']].plot(kind='barh',figsize=(10,16),cmap='bwr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Here you can see the breakdown by job and how they donate differently this looks at sum<br> but how about if we look at how many people donated instead of the ammount they did"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pivot table much like in excel\n",
    "job_pt = doner_df.pivot_table('contb_receipt_amt', index='contbr_occupation', columns = 'Party', aggfunc='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ADMINISTRATIVE ASSISTANT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARTIST</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATTORNEY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAREER ADVISOR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CERTIFIED REGISTERED NURSE ANESTHETIS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party                                   3rd Party  Democrat  Republican  Total\n",
       "contbr_occupation                                                             \n",
       " ADMINISTRATIVE ASSISTANT                     NaN       3.0         NaN    3.0\n",
       " ARTIST                                       NaN       1.0         NaN    1.0\n",
       " ATTORNEY                                     NaN      17.0         NaN   17.0\n",
       " CAREER ADVISOR                               NaN       1.0         NaN    1.0\n",
       " CERTIFIED REGISTERED NURSE ANESTHETIS        NaN      44.0         NaN   44.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_pt[\"Total\"] = job_pt.sum(axis=1)\n",
    "job_pt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "job_pt = job_pt.sort_values(by=\"Total\",ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_pt = job_pt[job_pt['Total'] > 15000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(46, 4)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_pt.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_pt.drop(['DISABLED', 'INFORMATION REQUESTED PER BEST EFFORTS', 'RETIRED', 'INFORMATION REQUESTED',\n",
    "             'CONDUIT TOTAL LISTED IN AGG. FIELD'],axis=0,inplace=True)\n",
    "\n",
    "job_pt.loc['SELF-EMPLOYED'] = job_pt.loc['SELF-EMPLOYED'] + job_pt.loc['SELF EMPLOYED']\n",
    "job_pt.loc['REGISTERED NURSE'] = job_pt.loc['REGISTERED NURSE'] + job_pt.loc['RN']\n",
    "job_pt.loc['BUSINESS OWNER'] = job_pt.loc['BUSINESS OWNER'] + job_pt.loc['OWNER']\n",
    "\n",
    "job_pt.drop('SELF EMPLOYED', inplace=True)\n",
    "job_pt.drop('RN', inplace=True)\n",
    "job_pt.drop('OWNER', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x34b38be0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAskAAAOECAYAAABThKzrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkZj/B+rAltkecF3pAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2a516d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_pt[['Democrat','Republican']].plot(kind='barh',figsize=(10,16),cmap='bwr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Here you can see there was a lot more Not employed then there was Attornies <br>but if you look at the previous graph of sum donated Attornies have a bit more spending money to give away"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "## Looking At Employer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "employer_df = doner_df.pivot_table('contb_receipt_amt',index='contbr_employer',columns = 'Party',aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(398017, 3)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employer_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# once again graphing 398,017 different companies will not only look horrible, but take forever\n",
    "employer_df = employer_df[employer_df.sum(1) > 350000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44, 3)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employer_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_employer</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>APPLE INC.</th>\n",
       "      <td>2390.27</td>\n",
       "      <td>6.157492e+05</td>\n",
       "      <td>1.691403e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT&amp;T</th>\n",
       "      <td>1599.00</td>\n",
       "      <td>3.930897e+05</td>\n",
       "      <td>8.445015e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BANK OF AMERICA</th>\n",
       "      <td>989.00</td>\n",
       "      <td>3.137584e+05</td>\n",
       "      <td>8.756927e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIVIC VOLUNTEER</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.270666e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLUMBIA UNIVERSITY</th>\n",
       "      <td>540.00</td>\n",
       "      <td>5.088942e+05</td>\n",
       "      <td>1.585360e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COVINGTON &amp; BURLING LLP</th>\n",
       "      <td>1000.00</td>\n",
       "      <td>3.371457e+05</td>\n",
       "      <td>2.469000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DLA PIPER LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.859019e+05</td>\n",
       "      <td>5.050000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FACEBOOK</th>\n",
       "      <td>4100.00</td>\n",
       "      <td>4.880039e+05</td>\n",
       "      <td>2.884904e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOLDMAN SACHS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.737989e+05</td>\n",
       "      <td>4.441873e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOGLE</th>\n",
       "      <td>33963.00</td>\n",
       "      <td>1.747589e+06</td>\n",
       "      <td>4.086180e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HARVARD UNIVERSITY</th>\n",
       "      <td>779.00</td>\n",
       "      <td>6.090910e+05</td>\n",
       "      <td>5.147250e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HOMEMAKER</th>\n",
       "      <td>70712.76</td>\n",
       "      <td>1.032269e+05</td>\n",
       "      <td>1.557000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>13394.80</td>\n",
       "      <td>4.785958e+05</td>\n",
       "      <td>9.277686e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INFORMATION REQUESTED</th>\n",
       "      <td>9527.50</td>\n",
       "      <td>1.915960e+07</td>\n",
       "      <td>2.015585e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INFORMATION REQUESTED PER BEST EFFORTS</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.631469e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPMORGAN CHASE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.761825e+05</td>\n",
       "      <td>2.130020e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KAISER PERMANENTE</th>\n",
       "      <td>5051.00</td>\n",
       "      <td>4.486548e+05</td>\n",
       "      <td>5.095701e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIRKLAND &amp; ELLIS LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.053693e+05</td>\n",
       "      <td>7.715636e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATHAM &amp; WATKINS LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.358406e+05</td>\n",
       "      <td>1.774300e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MICROSOFT</th>\n",
       "      <td>8700.00</td>\n",
       "      <td>8.683209e+05</td>\n",
       "      <td>8.708010e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MORGAN &amp; MORGAN</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.768052e+05</td>\n",
       "      <td>1.900000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MORGAN STANLEY</th>\n",
       "      <td>3157.00</td>\n",
       "      <td>4.349717e+05</td>\n",
       "      <td>1.980259e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEW YORK UNIVERSITY</th>\n",
       "      <td>3581.50</td>\n",
       "      <td>4.238838e+05</td>\n",
       "      <td>7.488000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NONE</th>\n",
       "      <td>87436.75</td>\n",
       "      <td>1.657044e+07</td>\n",
       "      <td>2.140423e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOT EMPLOYED</th>\n",
       "      <td>2275.00</td>\n",
       "      <td>1.817125e+07</td>\n",
       "      <td>2.450286e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAUL WEISS RIFKIND WHARTON &amp; GARRISON</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.452812e+05</td>\n",
       "      <td>6.200000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETIRED</th>\n",
       "      <td>853404.11</td>\n",
       "      <td>1.778874e+07</td>\n",
       "      <td>8.684480e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SELF</th>\n",
       "      <td>516475.77</td>\n",
       "      <td>6.375224e+06</td>\n",
       "      <td>4.304496e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SELF EMPLOYED</th>\n",
       "      <td>316031.33</td>\n",
       "      <td>7.194902e+06</td>\n",
       "      <td>9.967645e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SELF-EMPLOYED</th>\n",
       "      <td>288872.18</td>\n",
       "      <td>6.057527e+07</td>\n",
       "      <td>3.011407e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SIDLEY AUSTIN LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.337994e+05</td>\n",
       "      <td>5.223000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SKADDEN ARPS SLATE MEAGHER &amp; FLOM LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.655658e+05</td>\n",
       "      <td>4.201300e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STANFORD UNIVERSITY</th>\n",
       "      <td>3890.00</td>\n",
       "      <td>6.700374e+05</td>\n",
       "      <td>2.810121e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATE OF CALIFORNIA</th>\n",
       "      <td>900.00</td>\n",
       "      <td>3.908809e+05</td>\n",
       "      <td>5.579683e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STUDENT</th>\n",
       "      <td>14591.70</td>\n",
       "      <td>1.132440e+05</td>\n",
       "      <td>6.591907e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TWICE REQUESTED NOT YET RECEIVED</th>\n",
       "      <td>372793.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>U.S. DEPARTMENT OF JUSTICE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.577409e+05</td>\n",
       "      <td>1.030258e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>U.S. DEPARTMENT OF STATE</th>\n",
       "      <td>1275.00</td>\n",
       "      <td>5.311461e+05</td>\n",
       "      <td>4.081750e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>U.S. GOVERNMENT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.733251e+05</td>\n",
       "      <td>3.207180e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UCLA</th>\n",
       "      <td>1000.00</td>\n",
       "      <td>3.321899e+05</td>\n",
       "      <td>2.331297e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNIVERSITY OF CALIFORNIA</th>\n",
       "      <td>1550.00</td>\n",
       "      <td>3.927622e+05</td>\n",
       "      <td>1.969000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNIVERSITY OF MICHIGAN</th>\n",
       "      <td>3395.00</td>\n",
       "      <td>3.789262e+05</td>\n",
       "      <td>1.661126e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WELLS FARGO</th>\n",
       "      <td>9045.00</td>\n",
       "      <td>3.662068e+05</td>\n",
       "      <td>1.049981e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YALE UNIVERSITY</th>\n",
       "      <td>2144.75</td>\n",
       "      <td>3.903887e+05</td>\n",
       "      <td>5.457600e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party                                   3rd Party      Democrat    Republican\n",
       "contbr_employer                                                              \n",
       "APPLE INC.                                2390.27  6.157492e+05  1.691403e+04\n",
       "AT&T                                      1599.00  3.930897e+05  8.445015e+04\n",
       "BANK OF AMERICA                            989.00  3.137584e+05  8.756927e+04\n",
       "CIVIC VOLUNTEER                               NaN           NaN  4.270666e+05\n",
       "COLUMBIA UNIVERSITY                        540.00  5.088942e+05  1.585360e+04\n",
       "COVINGTON & BURLING LLP                   1000.00  3.371457e+05  2.469000e+04\n",
       "DLA PIPER LLP                                 NaN  3.859019e+05  5.050000e+03\n",
       "FACEBOOK                                  4100.00  4.880039e+05  2.884904e+04\n",
       "GOLDMAN SACHS                                 NaN  2.737989e+05  4.441873e+05\n",
       "GOOGLE                                   33963.00  1.747589e+06  4.086180e+04\n",
       "HARVARD UNIVERSITY                         779.00  6.090910e+05  5.147250e+03\n",
       "HOMEMAKER                                70712.76  1.032269e+05  1.557000e+07\n",
       "IBM                                      13394.80  4.785958e+05  9.277686e+04\n",
       "INFORMATION REQUESTED                     9527.50  1.915960e+07  2.015585e+07\n",
       "INFORMATION REQUESTED PER BEST EFFORTS        NaN           NaN  1.631469e+07\n",
       "JPMORGAN CHASE                                NaN  3.761825e+05  2.130020e+04\n",
       "KAISER PERMANENTE                         5051.00  4.486548e+05  5.095701e+04\n",
       "KIRKLAND & ELLIS LLP                          NaN  3.053693e+05  7.715636e+04\n",
       "LATHAM & WATKINS LLP                          NaN  3.358406e+05  1.774300e+04\n",
       "MICROSOFT                                 8700.00  8.683209e+05  8.708010e+04\n",
       "MORGAN & MORGAN                               NaN  5.768052e+05  1.900000e+03\n",
       "MORGAN STANLEY                            3157.00  4.349717e+05  1.980259e+05\n",
       "NEW YORK UNIVERSITY                       3581.50  4.238838e+05  7.488000e+03\n",
       "NONE                                     87436.75  1.657044e+07  2.140423e+06\n",
       "NOT EMPLOYED                              2275.00  1.817125e+07  2.450286e+05\n",
       "PAUL WEISS RIFKIND WHARTON & GARRISON         NaN  3.452812e+05  6.200000e+03\n",
       "RETIRED                                 853404.11  1.778874e+07  8.684480e+07\n",
       "SELF                                    516475.77  6.375224e+06  4.304496e+06\n",
       "SELF EMPLOYED                           316031.33  7.194902e+06  9.967645e+06\n",
       "SELF-EMPLOYED                           288872.18  6.057527e+07  3.011407e+07\n",
       "SIDLEY AUSTIN LLP                             NaN  3.337994e+05  5.223000e+04\n",
       "SKADDEN ARPS SLATE MEAGHER & FLOM LLP         NaN  3.655658e+05  4.201300e+02\n",
       "STANFORD UNIVERSITY                       3890.00  6.700374e+05  2.810121e+04\n",
       "STATE OF CALIFORNIA                        900.00  3.908809e+05  5.579683e+04\n",
       "STUDENT                                  14591.70  1.132440e+05  6.591907e+05\n",
       "TWICE REQUESTED NOT YET RECEIVED        372793.06           NaN           NaN\n",
       "U.S. DEPARTMENT OF JUSTICE                    NaN  3.577409e+05  1.030258e+04\n",
       "U.S. DEPARTMENT OF STATE                  1275.00  5.311461e+05  4.081750e+03\n",
       "U.S. GOVERNMENT                               NaN  6.733251e+05  3.207180e+04\n",
       "UCLA                                      1000.00  3.321899e+05  2.331297e+04\n",
       "UNIVERSITY OF CALIFORNIA                  1550.00  3.927622e+05  1.969000e+03\n",
       "UNIVERSITY OF MICHIGAN                    3395.00  3.789262e+05  1.661126e+04\n",
       "WELLS FARGO                               9045.00  3.662068e+05  1.049981e+05\n",
       "YALE UNIVERSITY                           2144.75  3.903887e+05  5.457600e+03"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Thats better\n",
    "employer_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "employer_df.drop(['INFORMATION REQUESTED PER BEST EFFORTS', 'INFORMATION REQUESTED', 'RETIRED', \n",
    "                  'TWICE REQUESTED NOT YET RECEIVED'],axis=0,inplace=True)\n",
    "# combine like rows\n",
    "employer_df.loc['SELF-EMPLOYED'] = employer_df.loc['SELF-EMPLOYED'] + employer_df.loc['SELF EMPLOYED'] + employer_df.loc['SELF']\n",
    "employer_df.loc['NOT EMPLOYED'] = employer_df.loc['NOT EMPLOYED'] + employer_df.loc['NONE']\n",
    "# remove self employed without dash\n",
    "employer_df.drop('SELF EMPLOYED',inplace=True)\n",
    "employer_df.drop('SELF',inplace=True)\n",
    "employer_df.drop('NONE',inplace=True)\n",
    "# These were far to large to allow us to see anything else\n",
    "employer_df.drop('HOMEMAKER',inplace=True)\n",
    "employer_df.drop('NOT EMPLOYED',inplace=True)\n",
    "employer_df.drop('SELF-EMPLOYED',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_employer</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PAUL WEISS RIFKIND WHARTON &amp; GARRISON</th>\n",
       "      <td>NaN</td>\n",
       "      <td>345281.25</td>\n",
       "      <td>6200.00</td>\n",
       "      <td>351481.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATHAM &amp; WATKINS LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>335840.62</td>\n",
       "      <td>17743.00</td>\n",
       "      <td>353583.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UCLA</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>332189.88</td>\n",
       "      <td>23312.97</td>\n",
       "      <td>356502.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COVINGTON &amp; BURLING LLP</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>337145.72</td>\n",
       "      <td>24690.00</td>\n",
       "      <td>362835.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SKADDEN ARPS SLATE MEAGHER &amp; FLOM LLP</th>\n",
       "      <td>NaN</td>\n",
       "      <td>365565.76</td>\n",
       "      <td>420.13</td>\n",
       "      <td>365985.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party                                  3rd Party   Democrat  Republican  \\\n",
       "contbr_employer                                                           \n",
       "PAUL WEISS RIFKIND WHARTON & GARRISON        NaN  345281.25     6200.00   \n",
       "LATHAM & WATKINS LLP                         NaN  335840.62    17743.00   \n",
       "UCLA                                      1000.0  332189.88    23312.97   \n",
       "COVINGTON & BURLING LLP                   1000.0  337145.72    24690.00   \n",
       "SKADDEN ARPS SLATE MEAGHER & FLOM LLP        NaN  365565.76      420.13   \n",
       "\n",
       "Party                                      Total  \n",
       "contbr_employer                                   \n",
       "PAUL WEISS RIFKIND WHARTON & GARRISON  351481.25  \n",
       "LATHAM & WATKINS LLP                   353583.62  \n",
       "UCLA                                   356502.85  \n",
       "COVINGTON & BURLING LLP                362835.72  \n",
       "SKADDEN ARPS SLATE MEAGHER & FLOM LLP  365985.89  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employer_df[\"Total\"] = employer_df.sum(axis=1)\n",
    "employer_df = employer_df.sort_values(by=\"Total\",ascending=True)\n",
    "employer_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x417e55f8>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzIAAAOECAYAAAB6pgRFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n70pmggAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3ff58588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "employer_df[['Democrat','Republican']].plot(kind='barh',figsize=(10,16),cmap='bwr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "## Lets move on to States"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "state_df = doner_df.pivot_table('contb_receipt_amt',index='contbr_st',columns = 'Party',aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_st</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA</th>\n",
       "      <td>250.0</td>\n",
       "      <td>42749.35</td>\n",
       "      <td>2474.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AB</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4493.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>5987.7</td>\n",
       "      <td>172202.35</td>\n",
       "      <td>37958.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party      3rd Party   Democrat  Republican\n",
       "contbr_st                                  \n",
       "20               NaN        NaN      175.00\n",
       "30               NaN        NaN       25.00\n",
       "AA             250.0   42749.35     2474.07\n",
       "AB               NaN    4493.10         NaN\n",
       "AE            5987.7  172202.35    37958.55"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "state_df.drop(['20','30','FF','FR','GU','IS','LO','MP','ON','PR','SI','VI','XX','AS','AU','BC','BR','EN','JA',\n",
    "'LE','SW','U*','UK','AA','BU','PU','SA','TE','ZZ','AB','BA','BE','CH','DU','E','EU','FM','GR','HE','KE','LI','MB',\n",
    "'NB','NL','NO','NS','OS','QC','SH','SK','SO','ST','TO','W.','GE','N.','C','PW','AE','AM','AP','QB'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Party</th>\n",
       "      <th>3rd Party</th>\n",
       "      <th>Democrat</th>\n",
       "      <th>Republican</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>contbr_st</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ND</th>\n",
       "      <td>2875.00</td>\n",
       "      <td>327070.57</td>\n",
       "      <td>571892.83</td>\n",
       "      <td>901838.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD</th>\n",
       "      <td>3504.00</td>\n",
       "      <td>521135.46</td>\n",
       "      <td>708679.05</td>\n",
       "      <td>1233318.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>6217.00</td>\n",
       "      <td>977554.76</td>\n",
       "      <td>604862.65</td>\n",
       "      <td>1588634.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>22036.86</td>\n",
       "      <td>972811.97</td>\n",
       "      <td>810857.98</td>\n",
       "      <td>1805706.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <td>14072.50</td>\n",
       "      <td>572265.52</td>\n",
       "      <td>1224614.66</td>\n",
       "      <td>1810952.68</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Party      3rd Party   Democrat  Republican       Total\n",
       "contbr_st                                              \n",
       "ND           2875.00  327070.57   571892.83   901838.40\n",
       "SD           3504.00  521135.46   708679.05  1233318.51\n",
       "DE           6217.00  977554.76   604862.65  1588634.41\n",
       "AK          22036.86  972811.97   810857.98  1805706.81\n",
       "WY          14072.50  572265.52  1224614.66  1810952.68"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_df[\"Total\"] = state_df.sum(axis=1)\n",
    "state_df = state_df.sort_values(by=\"Total\",ascending=True)\n",
    "state_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x488137b8>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3gAAAOQCAYAAABredOhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZIkVYQNniRJkiRVhA2eJEmSJFXE/wdnttwZG1Hj0AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x487fca20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state_df[['Democrat','Republican']].plot(kind='barh',figsize=(15,16),cmap='bwr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "## Cleaning Data for Rhode Island"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "RI_df = doner_df[doner_df.contbr_st == 'RI']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cmte_id</th>\n",
       "      <th>cand_id</th>\n",
       "      <th>cand_nm</th>\n",
       "      <th>contbr_nm</th>\n",
       "      <th>contbr_city</th>\n",
       "      <th>contbr_st</th>\n",
       "      <th>contbr_zip</th>\n",
       "      <th>contbr_employer</th>\n",
       "      <th>contbr_occupation</th>\n",
       "      <th>contb_receipt_amt</th>\n",
       "      <th>contb_receipt_dt</th>\n",
       "      <th>receipt_desc</th>\n",
       "      <th>memo_cd</th>\n",
       "      <th>memo_text</th>\n",
       "      <th>form_tp</th>\n",
       "      <th>file_num</th>\n",
       "      <th>tran_id</th>\n",
       "      <th>election_tp</th>\n",
       "      <th>Party</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>83179</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>BLOUNT, F. NELSON</td>\n",
       "      <td>BARRINGTON</td>\n",
       "      <td>RI</td>\n",
       "      <td>028061841</td>\n",
       "      <td>BLOUNT FINE FOODS</td>\n",
       "      <td>PRESIDENT</td>\n",
       "      <td>250.0</td>\n",
       "      <td>02-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.969678</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83180</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>COOPER, DAVID</td>\n",
       "      <td>NEWPORT</td>\n",
       "      <td>RI</td>\n",
       "      <td>028402004</td>\n",
       "      <td>U.S. NAVAL WAR COLLEGE</td>\n",
       "      <td>PROFESSOR</td>\n",
       "      <td>100.0</td>\n",
       "      <td>21-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.1026442</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83181</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>DEYOE, RONALD A. CAPT.</td>\n",
       "      <td>NEWPORT</td>\n",
       "      <td>RI</td>\n",
       "      <td>028401528</td>\n",
       "      <td>RETIRED</td>\n",
       "      <td>RETIRED</td>\n",
       "      <td>50.0</td>\n",
       "      <td>18-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.1018752</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83182</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>FOGG, DAVID</td>\n",
       "      <td>WICKFORD</td>\n",
       "      <td>RI</td>\n",
       "      <td>028525103</td>\n",
       "      <td>AVC</td>\n",
       "      <td>SEMI-RETIRED</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.1010821</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83183</th>\n",
       "      <td>C00458844</td>\n",
       "      <td>P60006723</td>\n",
       "      <td>Rubio, Marco</td>\n",
       "      <td>FOGG, DAVID</td>\n",
       "      <td>WICKFORD</td>\n",
       "      <td>RI</td>\n",
       "      <td>028525103</td>\n",
       "      <td>AVC</td>\n",
       "      <td>SEMI-RETIRED</td>\n",
       "      <td>25.0</td>\n",
       "      <td>18-FEB-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SA17A</td>\n",
       "      <td>1056862</td>\n",
       "      <td>SA17.1017099</td>\n",
       "      <td>P2016</td>\n",
       "      <td>Republican</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         cmte_id    cand_id       cand_nm               contbr_nm contbr_city  \\\n",
       "83179  C00458844  P60006723  Rubio, Marco       BLOUNT, F. NELSON  BARRINGTON   \n",
       "83180  C00458844  P60006723  Rubio, Marco           COOPER, DAVID     NEWPORT   \n",
       "83181  C00458844  P60006723  Rubio, Marco  DEYOE, RONALD A. CAPT.     NEWPORT   \n",
       "83182  C00458844  P60006723  Rubio, Marco             FOGG, DAVID    WICKFORD   \n",
       "83183  C00458844  P60006723  Rubio, Marco             FOGG, DAVID    WICKFORD   \n",
       "\n",
       "      contbr_st contbr_zip         contbr_employer contbr_occupation  \\\n",
       "83179        RI  028061841       BLOUNT FINE FOODS         PRESIDENT   \n",
       "83180        RI  028402004  U.S. NAVAL WAR COLLEGE         PROFESSOR   \n",
       "83181        RI  028401528                 RETIRED           RETIRED   \n",
       "83182        RI  028525103                     AVC      SEMI-RETIRED   \n",
       "83183        RI  028525103                     AVC      SEMI-RETIRED   \n",
       "\n",
       "       contb_receipt_amt contb_receipt_dt receipt_desc memo_cd memo_text  \\\n",
       "83179              250.0        02-FEB-16          NaN     NaN       NaN   \n",
       "83180              100.0        21-FEB-16          NaN     NaN       NaN   \n",
       "83181               50.0        18-FEB-16          NaN     NaN       NaN   \n",
       "83182               25.0        14-FEB-16          NaN     NaN       NaN   \n",
       "83183               25.0        18-FEB-16          NaN     NaN       NaN   \n",
       "\n",
       "      form_tp  file_num       tran_id election_tp       Party  \n",
       "83179   SA17A   1056862   SA17.969678       P2016  Republican  \n",
       "83180   SA17A   1056862  SA17.1026442       P2016  Republican  \n",
       "83181   SA17A   1056862  SA17.1018752       P2016  Republican  \n",
       "83182   SA17A   1056862  SA17.1010821       P2016  Republican  \n",
       "83183   SA17A   1056862  SA17.1017099       P2016  Republican  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25918, 19)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['BARRINGTON', 'NEWPORT', 'WICKFORD', 'WAKEFIELD', 'PORTSMOUTH',\n",
       "       'WEST WARWICK', 'NARRAGANSETT', 'EAST GREENWICH', 'PROVIDENCE',\n",
       "       'SAUNDERSTOWN', 'LITTLE COMPTON', 'CHARLESTOWN', 'EAST PROVIDENCE',\n",
       "       'WARWICK', 'MIDDLETOWN', 'TIVERTON', 'KINGSTON', 'SMITHFIELD',\n",
       "       'WOONSOCKET', 'WESTERLY', 'RUMFORD', 'NORTH PROVIDENCE',\n",
       "       'NORTH SMITHFIELD', 'FOSTER', 'COVENTRY', 'EXETER', 'LINCOLN',\n",
       "       'HOPE VALLEY', 'CUMBERLAND', 'CHEPACHET', 'ASHAWAY', 'PAWTUCKET',\n",
       "       'NORTH KINGSTOWN', 'GREENE', 'BRISTOL', 'N SCITUATE', 'GREENVILLE',\n",
       "       'NORTH SCITUATE', 'WYOMING', 'WCKFORD', 'WEST GREENWICH',\n",
       "       'WEST KINGSTON', 'CRANSTON', 'RIVERSIDE', 'N SMITHFIELD',\n",
       "       'WEST WARWWICK', 'E. GREENWICH', 'JAMESTOWN', 'N KINGSTOWN',\n",
       "       'WARREN', 'BLOCK ISLAND', 'JOHNSTON', 'HOPKINTON', 'HOPE',\n",
       "       'SOUTH KINGSTOWN', 'SCITUATE', 'E GREENWICH', 'CENTRAL FALLS',\n",
       "       'PASCOAG', 'CAROLINA', 'MANVILLE', 'RICHMOND', 'ADAMSVILLE',\n",
       "       'PRUDENCE ISL', 'MAPLEVILLE', 'SLATERSVILLE', 'PEACE DALE',\n",
       "       'WOOD RIVER JUNCTION', 'FORESTDALE', 'HARRISVILLE', 'ALBION',\n",
       "       'E PROVIDENCE', 'PARIS', 'N PROVIDENCE', 'S KINGSTOWN', 'HARMONY',\n",
       "       'ROCKVILLE', 'SLOCUM', 'SHANNOCK', 'CLAYVILLE', 'NEW SHOREHAM',\n",
       "       'W GREENWICH', 'INFO REQUESTED', 'BRADFORD', 'L. COMPTON',\n",
       "       'NARRAGANSET', 'HERMITAGE', 'NORTHPROVIDENCE', 'N. SCITUATE',\n",
       "       'BARRINGTION', 'SPEARFISH', 'VACAVILLE', 'MIDDLEFIELD',\n",
       "       'POOLESVILLE', 'MADISON', 'WEDT KINGSTON', 'SMITHFIELDSMITHFIELD',\n",
       "       'NORTH KING', 'NO. PROVIDENCE', 'WSET GREENWICH', 'SCOTTSDALE',\n",
       "       'LAKE FOREST', 'REDMOND', 'SAUNDERSTROWN', 'PITTSBURGH',\n",
       "       'PORT ST LUCIE', 'HONOMU', 'FTWORTH', 'CLINTON', 'N. KINGSTOWN',\n",
       "       'N. PROVIDENCE', 'PREONZO', 'N.PROV.', 'MIDDLETWON', 'LINCON',\n",
       "       'EAST GREENWICH, RI 02818', 'CHAPACHET', 'CHAMBERSBURG', 'OAKLAND',\n",
       "       'S. KINGSTOWN', 'SPARTANBURG', 'POTTSTOWN', 'FAIR LAWN',\n",
       "       'BURRILLVILLE', 'WARIWCK', 'GLENDALE', 'WARWICK. RHODE ISLAND',\n",
       "       'FAIR HAVEN', 'CHARLESTON', 'N.SCITUATE', 'WAWICK', 'CLAREMORE',\n",
       "       'SALT LAKE CITY', 'NO.KINGSTOWN', 'NARRAGONSETT', 'PERU',\n",
       "       'LITTLE COMPTO', 'KIAWAH ISLAND', 'ESAT PROVIDENCE'], dtype=object)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df.contbr_city.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Well.... aparently there is 140 \"cities\" in RI like previously we have to remove data we don't need like those who live in 'CLINTON' RI<br><br>Aswell as combine like values, like the man who lives in SMITHFIELD and those who live in 'SMITHFIELDSMITHFIELD'<br><br> but first... lets see how many live in each of these 140 cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PROVIDENCE                  5428\n",
       "CRANSTON                    1916\n",
       "WARWICK                     1548\n",
       "NEWPORT                     1286\n",
       "NORTH KINGSTOWN             1084\n",
       "BARRINGTON                  1002\n",
       "WAKEFIELD                    917\n",
       "PAWTUCKET                    854\n",
       "EAST GREENWICH               773\n",
       "BRISTOL                      737\n",
       "RIVERSIDE                    597\n",
       "CUMBERLAND                   553\n",
       "WESTERLY                     551\n",
       "NARRAGANSETT                 507\n",
       "PORTSMOUTH                   507\n",
       "WEST WARWICK                 455\n",
       "JAMESTOWN                    435\n",
       "MIDDLETOWN                   398\n",
       "COVENTRY                     392\n",
       "WEST KINGSTON                382\n",
       "NORTH PROVIDENCE             362\n",
       "LINCOLN                      355\n",
       "WARREN                       291\n",
       "CHARLESTOWN                  288\n",
       "TIVERTON                     286\n",
       "BLOCK ISLAND                 284\n",
       "WOONSOCKET                   264\n",
       "LITTLE COMPTON               252\n",
       "SAUNDERSTOWN                 233\n",
       "JOHNSTON                     202\n",
       "                            ... \n",
       "FTWORTH                        1\n",
       "S. KINGSTOWN                   1\n",
       "CHAPACHET                      1\n",
       "PORT ST LUCIE                  1\n",
       "N. PROVIDENCE                  1\n",
       "EAST GREENWICH, RI 02818       1\n",
       "NARRAGONSETT                   1\n",
       "LINCON                         1\n",
       "L. COMPTON                     1\n",
       "NORTH KING                     1\n",
       "PERU                           1\n",
       "WARWICK. RHODE ISLAND          1\n",
       "CLAREMORE                      1\n",
       "LAKE FOREST                    1\n",
       "N.PROV.                        1\n",
       "NO.KINGSTOWN                   1\n",
       "WAWICK                         1\n",
       "WSET GREENWICH                 1\n",
       "FAIR HAVEN                     1\n",
       "REDMOND                        1\n",
       "SALT LAKE CITY                 1\n",
       "CHARLESTON                     1\n",
       "SCOTTSDALE                     1\n",
       "BURRILLVILLE                   1\n",
       "CHAMBERSBURG                   1\n",
       "MIDDLETWON                     1\n",
       "WEDT KINGSTON                  1\n",
       "SMITHFIELDSMITHFIELD           1\n",
       "BARRINGTION                    1\n",
       "MADISON                        1\n",
       "Name: contbr_city, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df['contbr_city'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Okay so a lot of the typos/wrong places are just 1-3 people, we could just remove them and it woulnd't effect our data much, but instead lets add them <br><br> I found ~23 that were not actual places in RI at all<br>I want to convert the smaller towns into whatever big town/city they are part of"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "RI_df = RI_df[~RI_df['contbr_city'].isin(['CHAMBERSBURG', 'CLINTON', 'FAIR HAVEN', 'CLAREMORE', 'FTWORTH', 'HERMITAGE', 'HONOMU',\n",
    "    'KIAWAH ISLAND', 'LAKE FOREST', 'MADISON', 'MIDDLEFIELD', 'PARIS', 'PERU', 'PITTSBURGH', 'POOLESVILLE', 'PORT ST LUCIE', \n",
    "    'POTTSTOWN', 'PREONZO', 'SALT LAKE CITY', 'SCOTTSDALE', 'SPARTANBURG', 'SPEARFISH', 'VACAVILLE', 'INFO REQUESTED',\n",
    "    'REDMOND'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "RI_df = RI_df.replace(['BARRINGTION'],'BARRINGTON')\n",
    "RI_df = RI_df.replace(['GLENDALE','HARRISVILLE','MAPLEVILLE','OAKLAND','PASCOAG'],'BURRILLVILLE')\n",
    "RI_df = RI_df.replace(['CAROLINA','CHARLESTON','CHARLESTOWN'],'CHARLESTOWN')\n",
    "RI_df = RI_df.replace(['GREENE'],'COVENTRY')\n",
    "RI_df = RI_df.replace(['E GREENWICH','E. GREENWICH','EAST GREENWICH, RI 02818'],'EAST GREENWICH')\n",
    "RI_df = RI_df.replace(['E PROVIDENCE','EAST PROVIDENCE','ESAT PROVIDENCE','RIVERSIDE','RUMFORD'],'EAST PROVIDENCE')\n",
    "RI_df = RI_df.replace(['CLAYVILLE'],'FOSTER')\n",
    "RI_df = RI_df.replace(['CHAPACHET','CHEPACHET','HARMONY'],'GLOCESTER')\n",
    "RI_df = RI_df.replace(['ASHAWAY','HOPE VALLEY','ROCKVILLE'],'HOPKINTON')\n",
    "RI_df = RI_df.replace(['ALBION','FAIR LAWN','LINCON','MANVILLE'],'LINCOLN')\n",
    "RI_df = RI_df.replace(['ADAMSVILLE','L. COMPTON','LITTLE COMPTO','MANVILLE'],'LITTLE COMPTON')\n",
    "RI_df = RI_df.replace(['MIDDLETWON'],'MIDDLETOWN')\n",
    "RI_df = RI_df.replace(['NARRAGANSETT','NARRAGONSETT','SAUNDERSTOWN','SAUNDERSTROWN','NARRAGANSET'],'NARRAGANSETT')\n",
    "RI_df = RI_df.replace(['BLOCK ISLAND'],'NEW SHOREHAM')\n",
    "RI_df = RI_df.replace(['N KINGSTOWN','N. KINGSTOWN','NO.KINGSTOWN','NORTH KING','SLOCUM','WCKFORD','WICKFORD'],'NORTH KINGSTOWN')\n",
    "RI_df = RI_df.replace(['N PROVIDENCE','N. PROVIDENCE','N.PROV.','NO. PROVIDENCE','NORTHPROVIDENCE'],'NORTH PROVIDENCE')\n",
    "RI_df = RI_df.replace(['FORESTDALE','N SMITHFIELD','SLATERSVILLE'],'NORTH SMITHFIELD')\n",
    "RI_df = RI_df.replace(['PRUDENCE ISL'],'PORTSMOUTH')\n",
    "RI_df = RI_df.replace(['SHANNOCK','WOOD RIVER JUNCTION','WYOMING'],'RICHMOND')\n",
    "RI_df = RI_df.replace(['HOPE','N SCITUATE','N. SCITUATE','N.SCITUATE','NORTH SCITUATE'],'SCITUATE')\n",
    "RI_df = RI_df.replace(['GREENVILLE','SMITHFIELDSMITHFIELD'],'SMITHFIELD')\n",
    "RI_df = RI_df.replace(['KINGSTON','PEACE DALE','S KINGSTOWN','S. KINGSTOWN','SOUTH KINGSTOWN','WAKEFIELD','WEDT KINGSTON','WEST KINGSTON'],'SOUTH KINGSTOWN')\n",
    "RI_df = RI_df.replace(['WARIWCK','WAWICK','WARWICK. RHODE ISLAND'],'WARWICK')\n",
    "RI_df = RI_df.replace(['W GREENWICH','WSET GREENWICH'],'WEST GREENWICH')\n",
    "RI_df = RI_df.replace(['WEST WARWWICK'],'WEST WARWICK')\n",
    "RI_df = RI_df.replace(['BRADFORD'],'WESTERLY')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PROVIDENCE          5428\n",
       "CRANSTON            1916\n",
       "SOUTH KINGSTOWN     1754\n",
       "WARWICK             1553\n",
       "NEWPORT             1286\n",
       "NORTH KINGSTOWN     1170\n",
       "BARRINGTON          1003\n",
       "EAST PROVIDENCE      968\n",
       "PAWTUCKET            854\n",
       "EAST GREENWICH       816\n",
       "NARRAGANSETT         745\n",
       "BRISTOL              737\n",
       "WESTERLY             555\n",
       "CUMBERLAND           553\n",
       "PORTSMOUTH           509\n",
       "LINCOLN              485\n",
       "WEST WARWICK         456\n",
       "JAMESTOWN            435\n",
       "COVENTRY             419\n",
       "MIDDLETOWN           399\n",
       "NORTH PROVIDENCE     375\n",
       "CHARLESTOWN          309\n",
       "WARREN               291\n",
       "NEW SHOREHAM         288\n",
       "TIVERTON             286\n",
       "SCITUATE             279\n",
       "WOONSOCKET           264\n",
       "LITTLE COMPTON       261\n",
       "GLOCESTER            218\n",
       "JOHNSTON             202\n",
       "SMITHFIELD           196\n",
       "NORTH SMITHFIELD     167\n",
       "BURRILLVILLE         156\n",
       "HOPKINTON            143\n",
       "RICHMOND             132\n",
       "FOSTER               125\n",
       "WEST GREENWICH        73\n",
       "EXETER                62\n",
       "CENTRAL FALLS         20\n",
       "Name: contbr_city, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df['contbr_city'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Okay so now we got the data into major cities/towns next lets add counties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# dictionary of RI Counties\n",
    "county_map = {'BARRINGTON': 'BRISTOL',\n",
    "            'BRISTOL': 'BRISTOL',\n",
    "            'BURRILLVILLE': 'PROVIDENCE',\n",
    "            'CENTRAL FALLS': 'PROVIDENCE',\n",
    "            'CHARLESTOWN': 'WASHINGTON',\n",
    "            'COVENTRY': 'KENT',\n",
    "            'CRANSTON': 'PROVIDENCE',\n",
    "            'CUMBERLAND': 'PROVIDENCE',\n",
    "            'EAST GREENWICH': 'KENT',\n",
    "            'EAST PROVIDENCE': 'PROVIDENCE',\n",
    "            'EXETER': 'WASHINGTON',\n",
    "            'FOSTER': 'PROVIDENCE',\n",
    "            'GLOCESTER': 'PROVIDENCE',\n",
    "            'HOPKINTON': 'WASHINGTON',\n",
    "            'JAMESTOWN': 'NEWPORT',\n",
    "            'JOHNSTON': 'PROVIDENCE',\n",
    "            'LINCOLN': 'PROVIDENCE',\n",
    "            'LITTLE COMPTON': 'NEWPORT',\n",
    "            'MIDDLETOWN': 'NEWPORT',\n",
    "            'NARRAGANSETT': 'WASHINGTON',\n",
    "            'NEWPORT': 'NEWPORT',\n",
    "            'NEW SHOREHAM': 'WASHINGTON',\n",
    "            'NORTH KINGSTOWN': 'WASHINGTON',\n",
    "            'NORTH PROVIDENCE': 'PROVIDENCE',\n",
    "            'NORTH SMITHFIELD': 'PROVIDENCE',\n",
    "            'PAWTUCKET': 'PROVIDENCE',\n",
    "            'PORTSMOUTH': 'NEWPORT',\n",
    "            'PROVIDENCE': 'PROVIDENCE',\n",
    "            'RICHMOND': 'WASHINGTON',\n",
    "            'SCITUATE': 'PROVIDENCE',\n",
    "            'SMITHFIELD': 'PROVIDENCE',\n",
    "            'SOUTH KINGSTOWN': 'WASHINGTON',\n",
    "            'TIVERTON': 'NEWPORT',\n",
    "            'WARREN': 'BRISTOL',\n",
    "            'WARWICK': 'KENT',\n",
    "            'WESTERLY': 'WASHINGTON',\n",
    "            'WEST GREENWICH': 'KENT',\n",
    "            'WEST WARWICK': 'KENT',\n",
    "            'WOONSOCKET': 'PROVIDENCE'}\n",
    "\n",
    "# creating a party column and mapping party to canidate\n",
    "RI_df['County'] = RI_df.contbr_city.map(county_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PROVIDENCE    12206\n",
       "WASHINGTON     5158\n",
       "KENT           3317\n",
       "NEWPORT        3176\n",
       "BRISTOL        2031\n",
       "Name: County, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RI_df['County'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "RI_df.to_csv('RI_Pres_Election_2016.csv')"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}