311_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis of the 2014 New York City 311 Call Data\n",
    "#### The aim of this EDA is to understand the NYC 311 call data and observe any noticible trends that we can make predictions on.\n",
    "Author: Ikponmwosa Felix Ogbeide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Questions to answer through this project:</h2>\n",
    "<br>\n",
    "<li>Which boroughs have the most call incidents</li>\n",
    "<li>Which agency gets the most incidents</li>\n",
    "<li>What borough has the fastest incident resolution time</li>\n",
    "<li>How does the incidents vary month to month</li>\n",
    "<br>\n",
    "\n",
    "<p>\n",
    "<strong>PS</strong>\n",
    "<br>\n",
    "<em>I'm also on the lookout for interesting trends and observations beyond the questions above!</em>\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "Before I begin exploring the data, it is essential to understand what type of data I am working with. This would enable me decide on what kind data cleaning or wrangling is necessary for this project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import python libraries data manipulation\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ikp\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2698: DtypeWarning: Columns (8,17,40,41,42,43,44,45,46,47,48,49) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unique Key</th>\n",
       "      <th>Created Date</th>\n",
       "      <th>Closed Date</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Agency Name</th>\n",
       "      <th>Complaint Type</th>\n",
       "      <th>Descriptor</th>\n",
       "      <th>Location Type</th>\n",
       "      <th>Incident Zip</th>\n",
       "      <th>Incident Address</th>\n",
       "      <th>...</th>\n",
       "      <th>Bridge Highway Name</th>\n",
       "      <th>Bridge Highway Direction</th>\n",
       "      <th>Road Ramp</th>\n",
       "      <th>Bridge Highway Segment</th>\n",
       "      <th>Garage Lot Name</th>\n",
       "      <th>Ferry Direction</th>\n",
       "      <th>Ferry Terminal Name</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28457271</td>\n",
       "      <td>07/11/2014 03:08:58 PM</td>\n",
       "      <td>08/05/2014 12:41:37 PM</td>\n",
       "      <td>DOT</td>\n",
       "      <td>Department of Transportation</td>\n",
       "      <td>Sidewalk Condition</td>\n",
       "      <td>Defacement</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>11368</td>\n",
       "      <td>37-73 104 STREET</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.751870</td>\n",
       "      <td>-73.862718</td>\n",
       "      <td>(40.75187005911849, -73.8627181241703)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28644314</td>\n",
       "      <td>08/08/2014 02:06:22 PM</td>\n",
       "      <td>08/12/2014 11:33:34 AM</td>\n",
       "      <td>DCA</td>\n",
       "      <td>Department of Consumer Affairs</td>\n",
       "      <td>Consumer Complaint</td>\n",
       "      <td>False Advertising</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10014</td>\n",
       "      <td>113 WASHINGTON PLACE</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.732623</td>\n",
       "      <td>-74.001119</td>\n",
       "      <td>(40.732623326327484, -74.0011185474772)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29306886</td>\n",
       "      <td>11/18/2014 12:52:40 AM</td>\n",
       "      <td>11/18/2014 01:35:22 AM</td>\n",
       "      <td>NYPD</td>\n",
       "      <td>New York City Police Department</td>\n",
       "      <td>Blocked Driveway</td>\n",
       "      <td>No Access</td>\n",
       "      <td>Street/Sidewalk</td>\n",
       "      <td>11358</td>\n",
       "      <td>42-10 159 STREET</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.760384</td>\n",
       "      <td>-73.806826</td>\n",
       "      <td>(40.76038370367052, -73.80682559743896)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unique Key            Created Date             Closed Date Agency  \\\n",
       "0    28457271  07/11/2014 03:08:58 PM  08/05/2014 12:41:37 PM    DOT   \n",
       "1    28644314  08/08/2014 02:06:22 PM  08/12/2014 11:33:34 AM    DCA   \n",
       "2    29306886  11/18/2014 12:52:40 AM  11/18/2014 01:35:22 AM   NYPD   \n",
       "\n",
       "                       Agency Name      Complaint Type         Descriptor  \\\n",
       "0     Department of Transportation  Sidewalk Condition         Defacement   \n",
       "1   Department of Consumer Affairs  Consumer Complaint  False Advertising   \n",
       "2  New York City Police Department    Blocked Driveway          No Access   \n",
       "\n",
       "     Location Type Incident Zip      Incident Address  \\\n",
       "0         Sidewalk        11368      37-73 104 STREET   \n",
       "1              NaN        10014  113 WASHINGTON PLACE   \n",
       "2  Street/Sidewalk        11358      42-10 159 STREET   \n",
       "\n",
       "                    ...                    Bridge Highway Name  \\\n",
       "0                   ...                                    NaN   \n",
       "1                   ...                                    NaN   \n",
       "2                   ...                                    NaN   \n",
       "\n",
       "  Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name  \\\n",
       "0                      NaN       NaN                    NaN             NaN   \n",
       "1                      NaN       NaN                    NaN             NaN   \n",
       "2                      NaN       NaN                    NaN             NaN   \n",
       "\n",
       "  Ferry Direction Ferry Terminal Name   Latitude  Longitude  \\\n",
       "0             NaN                 NaN  40.751870 -73.862718   \n",
       "1             NaN                 NaN  40.732623 -74.001119   \n",
       "2             NaN                 NaN  40.760384 -73.806826   \n",
       "\n",
       "                                  Location  \n",
       "0   (40.75187005911849, -73.8627181241703)  \n",
       "1  (40.732623326327484, -74.0011185474772)  \n",
       "2  (40.76038370367052, -73.80682559743896)  \n",
       "\n",
       "[3 rows x 53 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read 311 data from xls file into pandas dataframe\n",
    "datafile = '311_Service_Requests_from_2014.csv'\n",
    "df = pd.read_csv(datafile)\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Setting pandas maximum colummns display so as to view all columns at once.\n",
    "pd.set_option('display.max_columns', None)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ikp\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2698: DtypeWarning: Columns (8,17,40,41,42,43,44,45,46,47,48,49) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n",
      "C:\\Users\\Ikp\\Anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:463: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    }
   ],
   "source": [
    "# Since the datafile has a Unique Key column its better to have that as the index\n",
    "# Re-read datafile into df pandas dataframe setting unique key as index\n",
    "df = pd.read_csv(datafile, index_col='Unique Key')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "#### From warning, we know we have mixed types in some columns. Its best to investigate what the mixtypes are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# I'll create a list to store the data with mixed data types.\n",
    "# Later on in the project, I'll visit this list of mixed data types\n",
    "df_mixed_dt = [df.columns[7], df.columns[16], df.columns[39],df.columns[40],df.columns[41],df.columns[42],\n",
    "               df.columns[43], df.columns[44], df.columns[45],df.columns[46], df.columns[47], df.columns[48]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2099056 entries, 28457271 to 29607189\n",
      "Data columns (total 52 columns):\n",
      "Created Date                      object\n",
      "Closed Date                       object\n",
      "Agency                            object\n",
      "Agency Name                       object\n",
      "Complaint Type                    object\n",
      "Descriptor                        object\n",
      "Location Type                     object\n",
      "Incident Zip                      object\n",
      "Incident Address                  object\n",
      "Street Name                       object\n",
      "Cross Street 1                    object\n",
      "Cross Street 2                    object\n",
      "Intersection Street 1             object\n",
      "Intersection Street 2             object\n",
      "Address Type                      object\n",
      "City                              object\n",
      "Landmark                          object\n",
      "Facility Type                     object\n",
      "Status                            object\n",
      "Due Date                          object\n",
      "Resolution Description            object\n",
      "Resolution Action Updated Date    object\n",
      "Community Board                   object\n",
      "Borough                           object\n",
      "X Coordinate (State Plane)        float64\n",
      "Y Coordinate (State Plane)        float64\n",
      "Park Facility Name                object\n",
      "Park Borough                      object\n",
      "School Name                       object\n",
      "School Number                     object\n",
      "School Region                     object\n",
      "School Code                       object\n",
      "School Phone Number               object\n",
      "School Address                    object\n",
      "School City                       object\n",
      "School State                      object\n",
      "School Zip                        object\n",
      "School Not Found                  object\n",
      "School or Citywide Complaint      float64\n",
      "Vehicle Type                      object\n",
      "Taxi Company Borough              object\n",
      "Taxi Pick Up Location             object\n",
      "Bridge Highway Name               object\n",
      "Bridge Highway Direction          object\n",
      "Road Ramp                         object\n",
      "Bridge Highway Segment            object\n",
      "Garage Lot Name                   object\n",
      "Ferry Direction                   object\n",
      "Ferry Terminal Name               object\n",
      "Latitude                          float64\n",
      "Longitude                         float64\n",
      "Location                          object\n",
      "dtypes: float64(5), object(47)\n",
      "memory usage: 848.8+ MB\n"
     ]
    }
   ],
   "source": [
    "# View object types of each columns\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Created Date                      2099056\n",
       "Closed Date                       2053916\n",
       "Agency                            2099056\n",
       "Agency Name                       2099056\n",
       "Complaint Type                    2099056\n",
       "Descriptor                        2086658\n",
       "Location Type                     1546759\n",
       "Incident Zip                      1952035\n",
       "Incident Address                  1641505\n",
       "Street Name                       1641401\n",
       "Cross Street 1                    1675745\n",
       "Cross Street 2                    1668168\n",
       "Intersection Street 1              323622\n",
       "Intersection Street 2              323523\n",
       "Address Type                      1994598\n",
       "City                              1953071\n",
       "Landmark                              810\n",
       "Facility Type                      536769\n",
       "Status                            2099053\n",
       "Due Date                           870518\n",
       "Resolution Description            2085477\n",
       "Resolution Action Updated Date    2060578\n",
       "Community Board                   2099056\n",
       "Borough                           2099056\n",
       "X Coordinate (State Plane)        1888333\n",
       "Y Coordinate (State Plane)        1888333\n",
       "Park Facility Name                2099056\n",
       "Park Borough                      2099056\n",
       "School Name                       2099056\n",
       "School Number                     2098598\n",
       "School Region                     2088711\n",
       "School Code                       2088711\n",
       "School Phone Number               2099056\n",
       "School Address                    2099055\n",
       "School City                       2099056\n",
       "School State                      2099056\n",
       "School Zip                        2099054\n",
       "School Not Found                   857159\n",
       "School or Citywide Complaint            0\n",
       "Vehicle Type                          481\n",
       "Taxi Company Borough                 1689\n",
       "Taxi Pick Up Location               14906\n",
       "Bridge Highway Name                  9223\n",
       "Bridge Highway Direction             9216\n",
       "Road Ramp                            9177\n",
       "Bridge Highway Segment              10678\n",
       "Garage Lot Name                       624\n",
       "Ferry Direction                       479\n",
       "Ferry Terminal Name                  1596\n",
       "Latitude                          1888333\n",
       "Longitude                         1888333\n",
       "Location                          1888333\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count of non-null values for every column \n",
    "df_columns = list(df.columns)\n",
    "df[df_columns].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Columns with a lot of missing data won't be useful to my analysis. Also, some columns in the data aren't just useful to this analysis, its best to remove these columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# A list of columns to remove from the dataframe\n",
    "df_cols_rmv = ['Incident Address', 'Street Name', 'Cross Street 1', 'Cross Street 2',\n",
    "               'Intersection Street 1', 'Intersection Street 2', 'Landmark', 'Facility Type',\n",
    "               'Due Date', 'Resolution Description','Community Board', 'X Coordinate (State Plane)',\n",
    "               'Y Coordinate (State Plane)', 'Park Facility Name', 'Park Borough', 'School Name',\n",
    "               'School Number', 'School Region', 'School Code', 'School Phone Number', 'School Address',\n",
    "               'School City', 'School State', 'School Zip', 'School Not Found', 'School or Citywide Complaint',\n",
    "               'Vehicle Type', 'Taxi Company Borough', 'Taxi Pick Up Location', 'Bridge Highway Name',\n",
    "               'Bridge Highway Direction', 'Road Ramp', 'Bridge Highway Segment', 'Garage Lot Name',\n",
    "               'Ferry Direction', 'Ferry Terminal Name', 'Location', 'Address Type', 'Agency Name',\n",
    "               'Resolution Action Updated Date', 'Descriptor', 'Location Type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Remove the columns added to the df_cols_rmv list from df dataframe\n",
    "df.drop(df_cols_rmv, inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2099056 entries, 28457271 to 29607189\n",
      "Data columns (total 10 columns):\n",
      "Created Date      object\n",
      "Closed Date       object\n",
      "Agency            object\n",
      "Complaint Type    object\n",
      "Incident Zip      object\n",
      "City              object\n",
      "Status            object\n",
      "Borough           object\n",
      "Latitude          float64\n",
      "Longitude         float64\n",
      "dtypes: float64(2), object(8)\n",
      "memory usage: 176.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Incident Zip',\n",
       " 'Landmark',\n",
       " 'Vehicle Type',\n",
       " 'Taxi Company Borough',\n",
       " 'Taxi Pick Up Location',\n",
       " 'Bridge Highway Name',\n",
       " 'Bridge Highway Direction',\n",
       " 'Road Ramp',\n",
       " 'Bridge Highway Segment',\n",
       " 'Garage Lot Name',\n",
       " 'Ferry Direction',\n",
       " 'Ferry Terminal Name']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Time to investigate df columns with mixed data types\n",
    "df_mixed_dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Drop columns in df-mixed_dt that aren't in df anymore\n",
    "df_mixed_dt = [x for x in df_mixed_dt if x in list(df.columns)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Incident Zip']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mixed_dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['11368', '10014', '11358', '10018', nan, '10466', '11357', '10309',\n",
       "       '10030', '10029', '11417', '11369', '10465', '10473', '10461',\n",
       "       '11101', '10010', '11217', '11355', '10019', '10128', '10462',\n",
       "       '10456', '11385', '11356', '11225', '10028', '11104', '11203',\n",
       "       '10024', '11249', '11103', '11211', '11364', '11432', '10023',\n",
       "       '10003', '11375', '11354', '11361', '10009', '10314', '11412',\n",
       "       '10036', '10012', '10163-4668', '11429', '10451', '11426', '10011',\n",
       "       '11233', '10457', '10460', '10305', '10021', '11237', '10007',\n",
       "       '10016', '10306', '11210', '11213', '11372', '11226', '11218',\n",
       "       '11221', '11414', '11205', '10307', '11204', '11418', '11234',\n",
       "       '11230', '11223', '10004', '11377', '11370', '11423', '10017',\n",
       "       '11367', '10031', '10002', '11222', '10027', '11207', '10025',\n",
       "       '11235', '11421', '10469', '11216', '11219', '11434', '10312',\n",
       "       '11238', '11411', '11214', '10005', '11365', '11373', '10452',\n",
       "       '11201', '10468', '10038', '11228', '10282', '10303', '11105',\n",
       "       '10472', '10000', '10308', '11378', '11236', '10001', '10475',\n",
       "       '10020', '10034', '11004', '11102', '11374', '10464', '11428',\n",
       "       '11416', '10304', '10453', '11208', '11209', '10022', '11379',\n",
       "       '11435', '11360', '11212', '10026', '10065', '11001', '11106',\n",
       "       '07114', '11215', '07512', '10032', '11419', '11427', '11096',\n",
       "       '07631', '10035', '10463', '11220', '11436', '10467', '11422',\n",
       "       '11229', '10301', '10013', '10040', '10033', '11366', '11433',\n",
       "       '11362', '10075', '11363', '11040', '10458', '10470', '11206',\n",
       "       '11231', '11413', '10454', '11239', '10455', '10459', '10704',\n",
       "       '10302', '11232', '11514', '11420', '10037', '10310', '11415',\n",
       "       '10474', '11224', '10710', '10006', '11691', '10039', '11692',\n",
       "       '11693', '10044', '11694', '11430', '29616-0759', '10471', '07017',\n",
       "       '10069', '11746', '10280', '94524', '11109', '00000', '10048',\n",
       "       '23450', '85044', '10804', 'OOOOO', 'UNKNOWN', '07601', '11749',\n",
       "       '10533', '11566', '11359', '11716', '11516', '00083', '32789',\n",
       "       '11803', '11559', '55426-1066', '11706', '11710', '10281', '10701',\n",
       "       '11553', '23541', '55438', '11580', '11757', '37615', '11697',\n",
       "       '07054', '11042', '11802-9060', '10116', '11554', '08857', '10805',\n",
       "       '12602-0550', '07030', '07642', '77072', '92123', '11735', '10801',\n",
       "       '10119', '11520', '10163', '11003', '55614', '92046-3023', '95476',\n",
       "       '10129', '11005', '10601', '08817', '07087', '11452', '10153',\n",
       "       'NEW YORK A', '11581', '33319', '12550', '11590', '10402',\n",
       "       '61702-3068', '08691', '11579', '07024', '07981', '07305', '11550',\n",
       "       '44139', '000000', '11747', '07047', '10548', '11501', '98057',\n",
       "       '10591', '23502', '10538', '75081', '10803', '77081', '07302',\n",
       "       '11776', '11021', '75244', '75201-4234', '10589', '77057', '1000',\n",
       "       '10112', '91752', '07306', '11598', '89703', '11242', '07652',\n",
       "       '63301', '32824', '11563', '07010', '66211', '11572', '10122',\n",
       "       '10603', '11556', '10606', '10705', '11791', '11758', '11030',\n",
       "       '07666', '07310', '10103', '07351', '75007-1958', '10930',\n",
       "       'NJ 07114', '01701-0166', '10954', '11720', '06851', '10536',\n",
       "       '14221-7820', '10552', '61654', '07647', '60089', '10501', '10162',\n",
       "       '30071', '11552', '15251', '11241', '75024-2959', '11801', '11371',\n",
       "       '11530', '11771', '08876', '11725', '07936', '0000', '11722',\n",
       "       '07094', '07605', '29603', '11714', 'NJ', '327500', '75240',\n",
       "       '37917', '32896', '11723', '08003', '07390', '19053', '000',\n",
       "       '07073', '06902', '11777', '30356', '11545', '10507', '92508',\n",
       "       '11010', '11901', '60181', '99999', '30005', '07052', '33634',\n",
       "       '07111', '07207', '20705', '07960', '55439', '14221-5783', '30188',\n",
       "       '84020', 11370.0, 11361.0, 11417.0, 10021.0, 10312.0, 11375.0,\n",
       "       10465.0, 11206.0, 11697.0, 11357.0, 10458.0, 11224.0, 10305.0,\n",
       "       11236.0, 11214.0, 11691.0, 11354.0, 11102.0, 10022.0, 10023.0,\n",
       "       11209.0, 10463.0, 11229.0, 10075.0, 11231.0, 10024.0, 11223.0,\n",
       "       10028.0, 11412.0, 11385.0, 11360.0, 10451.0, 11692.0, 11040.0,\n",
       "       10308.0, 10038.0, 11220.0, 11369.0, 11235.0, 11416.0, 11372.0,\n",
       "       11238.0, 10128.0, 10017.0, 11230.0, 11694.0, 10012.0, 10309.0,\n",
       "       11414.0, 11232.0, 10472.0, 10033.0, 11434.0, 11356.0, 10468.0,\n",
       "       11358.0, 11228.0, 10306.0, 10016.0, 10036.0, 10304.0, 11001.0,\n",
       "       10454.0, 11377.0, 11216.0, 11106.0, 10461.0, 10003.0, 10006.0,\n",
       "       10314.0, 10030.0, 11365.0, 11005.0, 11103.0, 11379.0, 10462.0,\n",
       "       11368.0, 11435.0, 10014.0, 11215.0, 10029.0, 11233.0, 11222.0,\n",
       "       10471.0, 11225.0, 11373.0, 10301.0, 11212.0, 11201.0, 10307.0,\n",
       "       10452.0, 11237.0, 11104.0, 11432.0, 11436.0, 11362.0, 11420.0,\n",
       "       11208.0, 10470.0, 11366.0, 11429.0, 11219.0, 11413.0, 10466.0,\n",
       "       11367.0, 11419.0, 10455.0, 10019.0, 11422.0, 10467.0, 11239.0,\n",
       "       11378.0, 10025.0, 11226.0, 10011.0, 10009.0, 11210.0, 11423.0,\n",
       "       11426.0, 10034.0, 11105.0, 10475.0, 10002.0, 11355.0, 11221.0,\n",
       "       10032.0, 11204.0, 11374.0, 11364.0, 10001.0, 11249.0, 11411.0,\n",
       "       11234.0, 10473.0, 10065.0, 11211.0, 11217.0, 11218.0, 11203.0,\n",
       "       10460.0, 10013.0, 11205.0, 10310.0, 10010.0, 11101.0, 10007.0,\n",
       "       11004.0, 11433.0, 10005.0, 10027.0, 10474.0, 11421.0, 10469.0,\n",
       "       10026.0, 10035.0, 11207.0, 11213.0, 10453.0, 11418.0, 11415.0,\n",
       "       10040.0, 10457.0, 10031.0, 10303.0, 11427.0, 10069.0, 11428.0,\n",
       "       10464.0, 10004.0, 10018.0, 10456.0, 10302.0, 11363.0, 11693.0,\n",
       "       10459.0, 10037.0, 10039.0, 7094.0, 10103.0, 10044.0, 10280.0,\n",
       "       7030.0, 11563.0, 10553.0, 11430.0, 7117.0, 10523.0, 11552.0,\n",
       "       11003.0, 7114.0, '19044', '11701', '11754', '54305-1654', '07664',\n",
       "       '10549', '95476-9005', '10577', '33137-0098', '07102', '171111',\n",
       "       '92019', '11797-9012', 75081.0, 10020.0, 10595.0, 10119.0, 10111.0,\n",
       "       11109.0, 10591.0, 83.0, 10701.0, 10129.0, 11520.0, 10122.0, 7310.0,\n",
       "       11733.0, 92123.0, 7632.0, 11507.0, 8776.0, 8691.0, 11042.0, 10710.0,\n",
       "       98206.0, 14225.0, 11577.0, '10523', '23541-1223', 11716.0, 75240.0,\n",
       "       11550.0, 7070.0, 10000.0, 13202.0, 8540.0, 10282.0, 11021.0,\n",
       "       11763.0, 7801.0, 60148.0, 11501.0, 11749.0, 7663.0, 11241.0,\n",
       "       10153.0, 10123.0, 10281.0, 0.0, 33486.0, 85080.0, 11704.0, 55812.0,\n",
       "       11.0, 10801.0, 11530.0, 11371.0, 7104.0, 23113.0, 11741.0, 11695.0,\n",
       "       10162.0, 85044.0, 7073.0, 10048.0, 11566.0, 11202.0, 10705.0,\n",
       "       11553.0, 11561.0, 8724.0, '48195-0391', '08540', 11746.0, 11797.0,\n",
       "       77201.0, 11542.0, 11251.0, 7410.0, 7450.0, 11793.0, 11559.0,\n",
       "       11768.0, 11581.0, 11359.0, 11590.0, 11703.0, 75024.0, 95476.0,\n",
       "       92506.0, 7307.0, 10107.0, 8520.0, 7144.0, 11011.0, 10803.0, 14644.0,\n",
       "       7920.0, 10984.0, 11570.0, 10965.0, 11778.0, 17032.0, 11580.0,\n",
       "       11569.0, 11565.0, 7901.0, 7041.0, 11756.0, 90304.0, 18466.0,\n",
       "       11386.0, 33304.0, 7306.0, 1123.0, 11710.0, 30339.0, 8069.0, 7024.0,\n",
       "       11598.0, '11788', '07086', '45274-2596', 7042.0, 10604.0, 7304.0,\n",
       "       8854.0, 11743.0, 11803.0, 10708.0, 6851.0, 30005.0, 60018.0, 6511.0,\n",
       "       91754.0, 7302.0, 8527.0, 23502.0, 11599532.0, 11735.0, 8690.0,\n",
       "       7430.0, 11554.0, 8003.0, 7601.0, 10112.0, 11725.0, 10041.0,\n",
       "       114566.0, 95762.0, '14221', 20188.0, 73126.0, '60179', '11434-420',\n",
       "       '07661', '14450', '07632', '07712', '61602', '10583', '29616',\n",
       "       '11576', '20201', '11570', '11317', 'ZIP CODE', '11730',\n",
       "       '35210-6928', '11251', '63042', '32255', 92018.0, 11776.0, 6854.0,\n",
       "       1000000.0, 3110.0, 53707.0, 80155.0, 7652.0, 11791.0, 11801.0,\n",
       "       11030.0, 10601.0, 11804.0, 7047.0, 7730.0, 11020.0, 19044.0,\n",
       "       12203.0, '10041', '11561', '75403', '43216', '06801-1459',\n",
       "       '6462430478', '02140', '07410', '11738', '74147', '10925', '11695',\n",
       "       '08854', '07458', '32750', '11215-0389', '18519', '15219',\n",
       "       '11756-0215', '11715', '48195-0954', '33428', '70163', '11704',\n",
       "       '11779', '75026-0848', '02205', '7056', '11802', '02459', '08807',\n",
       "       '11510', '64108', '85711', '07620', '98036', '10541', '10573',\n",
       "       '11590-5114', '92013-0848', '10514', '07304', '07650', '91710',\n",
       "       '18773-9635', '30303', '0', '11729', '78265', '07090', '11542',\n",
       "       '10550', '11797', '55125', '33486', '30348-5658', '60076', '30360',\n",
       "       '10101', '10111', '12203', '12941-0129', '91754', '11001-2024',\n",
       "       '10123', '91356', '44122-5340', '10602-5055', '48451-0505', '35219',\n",
       "       '07144', '11024', '1143', '07042', '07079', '08873', '10522',\n",
       "       '11756', '11762', '08827-4010', '08080', '18966', '07002', '10994',\n",
       "       '75086', '07093', '11797-9001', '60018-4501', '11020', '48393-1022',\n",
       "       '33611', '11793', '11111', '43607', '32073', '12345', '11766',\n",
       "       'INDIAN WEL', '03104', '10528', '20123', '07203', '12024', '11549',\n",
       "       '19850', '27713', '07670', '07067', '54602', '11767', '37214',\n",
       "       '78265-9707', '0000000', '14206', '07417', '11540', '92923',\n",
       "       '85251-6547', '30144-7518', '11741', '11797-9004', '91504', '43054',\n",
       "       '10015', '117', '11507', '11753', 11747.0, 7981.0, 11980.0, 11576.0,\n",
       "       7372.0, 14615.0, 1208.0, 7940.0, '07675', '28201-1115', '14108',\n",
       "       '10532', '14009', '10566', '34230', '14203', '06901', 'NEWARK',\n",
       "       '11743', '14883', '11570-4705', '11535', '94566-9049', '6201-5773',\n",
       "       '10008', '11533', '60523', '66207', '43218-3083', '80111', '10703',\n",
       "       '10107', '29659', '320896', '08086', '12590', 'ANONYMOUS', '92036',\n",
       "       '10952', '35476', 'NY', '45241', '11772-3518', '43614', '10150',\n",
       "       '18042', '48090-2036', '11795', '14692-2878', 'UNSURE', '20188',\n",
       "       '90036', '30345', '782659705', '11735-9000', '08830', '11760',\n",
       "       '10435', '11518', '33122', '07045', '67504', '92506', '55438-0902',\n",
       "       10177.0, 10115.0, 11242.0, 10165.0, 76406.0, 17602.0, 12814.0,\n",
       "       10550.0, 7646.0, 33130.0, 11111.0, 7093.0, 33480.0, 2907.0, 22172.0,\n",
       "       11787.0, 14626.0, 68135.0, 7017.0, 10104.0, 10589.0, '10023-0007',\n",
       "       11341.0, 29006.0, 10703.0, 10605.0, 11431.0, 10116.0, 1850.0,\n",
       "       74106.0, 11514.0, 12345.0, 84770.0, 18015.0, 10150.0, 12779.0,\n",
       "       100000.0, 10603.0, 10108.0], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Explore Incident Zip\n",
    "df['Incident Zip'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Its clear to see that Incident Zip has some issues other than the mixed data types, these issues are:\n",
    "<br>\n",
    "<li>Mixed data types, sometimes floats, sometimes strings</li>\n",
    "<li>Some on the zipcodes have 4 digits added to it after an hyphen</li>\n",
    "<li>Some zipcodes are nan, others are ?, UNKNOWN, ANONYMOUS and so on</li>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Function that cleans the Incident Zip values and returns nan for data that cannot be cleaned\n",
    "def correct_zip(zip_code):\n",
    "    try:\n",
    "        zip_code = int(float(zip_code))\n",
    "    except:\n",
    "        try:\n",
    "            zip_code = int(float(zip_code.split('-')[0]))\n",
    "        except:\n",
    "            return np.nan\n",
    "    if zip_code < 10000 or zip_code > 19999:\n",
    "        return np.nan\n",
    "    else:\n",
    "        return str(zip_code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Apply correct_zip function to clean Incident Zip data\n",
    "df['Incident Zip'] = df['Incident Zip'].apply(correct_zip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Remove rows from data that have incident zip as null i.e nan\n",
    "df = df[df['Incident Zip'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Created Date      1951306\n",
       "Closed Date       1910835\n",
       "Agency            1951306\n",
       "Complaint Type    1951306\n",
       "Incident Zip      1951306\n",
       "City              1951245\n",
       "Status            1951303\n",
       "Borough           1951306\n",
       "Latitude          1887423\n",
       "Longitude         1887423\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Count of non-null values for every column \n",
    "df_columns = list(df.columns)\n",
    "df[df_columns].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Closed date, Latitude, and Longitude all have missing values, best to remove the rows where data in those columns are missing\n",
    "df = df[(df['Latitude'].notnull()) & (df['Longitude'].notnull()) & (df['Closed Date'].notnull())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Created Date      1847268\n",
       "Closed Date       1847268\n",
       "Agency            1847268\n",
       "Complaint Type    1847268\n",
       "Incident Zip      1847268\n",
       "City              1847211\n",
       "Status            1847265\n",
       "Borough           1847268\n",
       "Latitude          1847268\n",
       "Longitude         1847268\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Count of non-null values for every column \n",
    "df_columns = list(df.columns)\n",
    "df[df_columns].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['DOT', 'DCA', 'NYPD', 'FDNY', 'DOHMH', 'TLC', 'DOE', 'DOB', 'DPR',\n",
       "       'EDC', 'DSNY', 'DEP', 'DOITT', 'HPD', '3-1-1', 'DFTA', 'DHS'], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#As part of the EDA process, all columns should be explored to identify columns with messy data or nan\n",
    "df['Agency'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Sidewalk Condition', 'Consumer Complaint', 'Blocked Driveway',\n",
       "       'EAP Inspection - F59', 'Derelict Vehicle', 'Street Condition',\n",
       "       'Indoor Air Quality', 'Broken Muni Meter', 'Illegal Parking',\n",
       "       'Animal Abuse', 'Taxi Complaint', 'Street Sign - Damaged',\n",
       "       'Noise - Street/Sidewalk', 'Noise - Commercial',\n",
       "       'School Maintenance', 'Homeless Encampment', 'Noise - Vehicle',\n",
       "       'Construction', 'Vending', 'Traffic', 'Food Establishment',\n",
       "       'Damaged Tree', 'Street Sign - Missing',\n",
       "       'For Hire Vehicle Complaint', 'Dead Tree', 'Standing Water',\n",
       "       'Illegal Tree Damage', 'Highway Condition', 'Noise - Park',\n",
       "       'Overgrown Tree/Branches', 'Drinking', 'Maintenance or Facility',\n",
       "       'Fire Safety Director - F58', 'Noise - Helicopter',\n",
       "       'Illegal Fireworks', 'Root/Sewer/Sidewalk Condition',\n",
       "       'Urinating in Public', 'Dirty Conditions',\n",
       "       'Noise - House of Worship', 'DPR Internal', 'Food Poisoning',\n",
       "       'Industrial Waste', 'Water System', 'Graffiti', 'Curb Condition',\n",
       "       'Building/Use', 'Fire Alarm - New System', 'Mold',\n",
       "       'Street Sign - Dangling', 'Rodent',\n",
       "       'Unsanitary Animal Pvt Property', 'Public Payphone Complaint',\n",
       "       'Animal in a Park', 'General Construction/Plumbing', 'Asbestos',\n",
       "       'Sewer', 'Street Light Condition', 'Plumbing', 'FLOORING/STAIRS',\n",
       "       'Harboring Bees/Wasps', 'Fire Alarm - Modification',\n",
       "       'Fire Alarm - Addition', 'Bike/Roller/Skate Chronic',\n",
       "       'Violation of Park Rules', 'City Vehicle Placard Complaint',\n",
       "       'Fire Alarm - Reinspection', 'Disorderly Youth',\n",
       "       'Bus Stop Shelter Placement', 'Open Flame Permit', 'Indoor Sewage',\n",
       "       'Bike Rack Condition', 'Public Toilet', 'Bridge Condition',\n",
       "       'Posting Advertisement', 'GENERAL', 'Senior Center Complaint',\n",
       "       'Panhandling', 'Snow', 'Special Projects Inspection Team (SPIT)',\n",
       "       'Municipal Parking Facility', 'Special Enforcement',\n",
       "       'Highway Sign - Damaged', 'Taxi Report', 'Broken Parking Meter',\n",
       "       'Beach/Pool/Sauna Complaint', 'Derelict Vehicles',\n",
       "       'Traffic Signal Condition', 'HEAT/HOT WATER',\n",
       "       'Missed Collection (All Materials)', 'Public Assembly',\n",
       "       'Overflowing Litter Baskets', 'Sweeping/Missed', 'Vacant Lot',\n",
       "       'ELEVATOR', 'Sanitation Condition', 'Other Enforcement',\n",
       "       'Investigations and Discipline (IAD)', 'Drinking Water',\n",
       "       'Found Property', 'Squeegee', 'Unsanitary Pigeon Condition',\n",
       "       'ELECTRIC', 'Hazardous Materials', 'UNSANITARY CONDITION',\n",
       "       'Bottled Water', 'Boilers', 'Electrical', 'Elevator',\n",
       "       'Emergency Response Team (ERT)', 'BEST/Site Safety',\n",
       "       'Request Xmas Tree Collection', 'Cranes and Derricks', 'Tanning',\n",
       "       'PLUMBING', 'APPLIANCE', 'HEATING', 'Litter Basket / Request',\n",
       "       'For Hire Vehicle Report', 'DOOR/WINDOW', 'WATER LEAK',\n",
       "       'Sweeping/Inadequate', 'Scaffold Safety',\n",
       "       'Fire Alarm - Replacement', 'Radioactive Material',\n",
       "       'Recycling Enforcement', 'Overflowing Recycling Baskets',\n",
       "       'Derelict Bicycle', 'Homeless Person Assistance', 'PAINT/PLASTER',\n",
       "       'Highway Sign - Dangling', 'OUTSIDE BUILDING', 'Water Quality',\n",
       "       'Public Assembly - Temporary', 'Miscellaneous Categories',\n",
       "       'Lifeguard', 'NONCONST', 'PAINT - PLASTER', 'GENERAL CONSTRUCTION',\n",
       "       'CONSTRUCTION', 'Legal Services Provider Complaint',\n",
       "       'Non-Residential Heat', 'Highway Sign - Missing',\n",
       "       'X-Ray Machine/Equipment', 'SAFETY', 'VACANT APARTMENT',\n",
       "       'Stalled Sites', 'Building Condition', 'AGENCY',\n",
       "       'Transportation Provider Complaint', 'Water Conservation', 'Noise',\n",
       "       'Air Quality', 'Plant', 'Lead', 'Collection Truck Noise',\n",
       "       'Special Natural Area District (SNAD)', 'Adopt-A-Basket',\n",
       "       'Literature Request', 'SG-99', 'Noise - Residential',\n",
       "       'Non-Emergency Police Matter', 'New Tree Request'], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Complaint Type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CORONA', 'NEW YORK', 'FLUSHING', 'BRONX', 'WHITESTONE',\n",
       "       'STATEN ISLAND', 'OZONE PARK', 'EAST ELMHURST', 'LONG ISLAND CITY',\n",
       "       'BROOKLYN', 'RIDGEWOOD', 'COLLEGE POINT', 'SUNNYSIDE', 'ASTORIA',\n",
       "       'OAKLAND GARDENS', 'FOREST HILLS', 'BAYSIDE', 'SAINT ALBANS',\n",
       "       'QUEENS VILLAGE', 'BELLEROSE', 'JACKSON HEIGHTS', 'HOWARD BEACH',\n",
       "       'RICHMOND HILL', 'WOODSIDE', 'HOLLIS', 'WOODHAVEN', 'JAMAICA',\n",
       "       'FRESH MEADOWS', 'ELMHURST', 'Ridgewood', 'MASPETH', 'GLEN OAKS',\n",
       "       'REGO PARK', 'Long Island City', 'MIDDLE VILLAGE', 'Bayside', nan,\n",
       "       'SOUTH RICHMOND HILL', 'ROSEDALE', 'Little Neck', 'LITTLE NECK',\n",
       "       'Jamaica', 'Richmond Hill', 'SPRINGFIELD GARDENS', 'Fresh Meadows',\n",
       "       'East Elmhurst', 'Woodhaven', 'Howard Beach', 'FLORAL PARK',\n",
       "       'KEW GARDENS', 'SOUTH OZONE PARK', 'CAMBRIA HEIGHTS',\n",
       "       'Far Rockaway', 'Flushing', 'South Ozone Park', 'Elmhurst',\n",
       "       'Ozone Park', 'Corona', 'South Richmond Hill', 'Jackson Heights',\n",
       "       'FAR ROCKAWAY', 'Queens Village', 'Springfield Gardens', 'Astoria',\n",
       "       'Cambria Heights', 'Glen Oaks', 'ROCKAWAY PARK', 'Rego Park',\n",
       "       'ARVERNE', 'Middle Village', 'NEW HYDE PARK', 'Woodside',\n",
       "       'Kew Gardens', 'Rockaway Park', 'Hollis', 'Maspeth', 'Rosedale',\n",
       "       'Saint Albans', 'Arverne', 'BREEZY POINT', 'Forest Hills',\n",
       "       'Oakland Gardens', 'Sunnyside', 'Bellerose', 'QUEENS', 'Whitestone',\n",
       "       'Floral Park', 'New Hyde Park', 'College Point', 'NEW HEMPSTEAD',\n",
       "       'UNKNOWN', 'BEDFORD HILLS', 'Breezy Point', 'BELLMORE', 'MANHATTAN'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['City'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Closed', 'Pending', 'Assigned', nan, 'Open', 'Started'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Status'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['QUEENS', 'MANHATTAN', 'BRONX', 'STATEN ISLAND', 'BROOKLYN',\n",
       "       'Unspecified'], dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Borough'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Columns with messy or missing data\n",
    "<br>\n",
    "<li>City - contains some cities in uppercase and others in lowercase</li>\n",
    "<li>status - contains nan values</li>\n",
    "<li>Borough - contains 'Unspecified' boroughs</li>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Agency</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unique Key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29167930</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28650971</th>\n",
       "      <td>DPR</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28993659</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28337889</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28768853</th>\n",
       "      <td>TLC</td>\n",
       "      <td>NEW HEMPSTEAD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27339785</th>\n",
       "      <td>TLC</td>\n",
       "      <td>BEDFORD HILLS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28911820</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28767733</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28867255</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29044115</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29183835</th>\n",
       "      <td>DCA</td>\n",
       "      <td>BELLMORE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28994609</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29503930</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29040790</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29211842</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28151378</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28356529</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28983245</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28763594</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29217588</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29209600</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28961292</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29159476</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28945701</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28305246</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28501571</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27739170</th>\n",
       "      <td>DPR</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28135459</th>\n",
       "      <td>TLC</td>\n",
       "      <td>BAYSIDE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28944841</th>\n",
       "      <td>NYPD</td>\n",
       "      <td>STATEN ISLAND</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Agency           City\n",
       "Unique Key                      \n",
       "29167930     NYPD  STATEN ISLAND\n",
       "28650971      DPR  STATEN ISLAND\n",
       "28993659     NYPD  STATEN ISLAND\n",
       "28337889     NYPD  STATEN ISLAND\n",
       "28768853      TLC  NEW HEMPSTEAD\n",
       "27339785      TLC  BEDFORD HILLS\n",
       "28911820     NYPD  STATEN ISLAND\n",
       "28767733     NYPD  STATEN ISLAND\n",
       "28867255     NYPD  STATEN ISLAND\n",
       "29044115     NYPD  STATEN ISLAND\n",
       "29183835      DCA       BELLMORE\n",
       "28994609     NYPD  STATEN ISLAND\n",
       "29503930     NYPD  STATEN ISLAND\n",
       "29040790     NYPD  STATEN ISLAND\n",
       "29211842     NYPD  STATEN ISLAND\n",
       "28151378     NYPD  STATEN ISLAND\n",
       "28356529     NYPD  STATEN ISLAND\n",
       "28983245     NYPD  STATEN ISLAND\n",
       "28763594     NYPD  STATEN ISLAND\n",
       "29217588     NYPD  STATEN ISLAND\n",
       "29209600     NYPD  STATEN ISLAND\n",
       "28961292     NYPD  STATEN ISLAND\n",
       "29159476     NYPD  STATEN ISLAND\n",
       "28945701     NYPD  STATEN ISLAND\n",
       "28305246     NYPD  STATEN ISLAND\n",
       "28501571     NYPD  STATEN ISLAND\n",
       "27739170      DPR  STATEN ISLAND\n",
       "28135459      TLC        BAYSIDE\n",
       "28944841     NYPD  STATEN ISLAND"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lets look at the unspecified boroughs, we want to be sure that removing data from df won't cause problems later on\n",
    "df[df['Borough']=='Unspecified'][['Agency', 'City']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.005\n"
     ]
    }
   ],
   "source": [
    "# Majority of the data belongs to NYPD Agency and occurs in Staten Island\n",
    "# To ensure I don't lose too much data from NYPD, I need to ensure this accounts for a neglegible number of NYPD\n",
    "nypd_total = df[df['Agency']=='NYPD']['Borough'].count()\n",
    "nypd_unspecified = df[(df['Borough']=='Unspecified') & (df['Agency']==\"NYPD\")]['Borough'].count()\n",
    "nypd_unspec_perct = nypd_unspecified/nypd_total*100\n",
    "print(\"%1.3f\"%nypd_unspec_perct)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Boroughs that are unspecified are negligible that it can be removed\n",
    "df = df[df['Borough'] != 'Unspecified']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n"
     ]
    }
   ],
   "source": [
    "#Number of Status columns with nan\n",
    "status_nan = len(df[df['Status'].isnull()].index)\n",
    "print(status_nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#The number of rows with columns Status as nan is 3, which is also negligible, I can remove it from the dataframe also.\n",
    "df = df[df['Status'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Since some city values are represented both in uppercase and lowercase, it's better to have the city in the same case\n",
    "# Convert all City Values to Camel Case\n",
    "def camel_case(city):\n",
    "    try:\n",
    "        city = city.split(' ')\n",
    "        city = ' '.join([x.lower().capitalize() for x in city])\n",
    "        if city == 'Unknown':\n",
    "            return np.nan\n",
    "        else:\n",
    "            return city\n",
    "    except:\n",
    "        return np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Apply camel_case function to City column\n",
    "df['City'] = df['City'].apply(camel_case)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Agency\n",
       "DOT    57\n",
       "TLC     1\n",
       "Name: Status, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets view the City values with nan\n",
    "df[df['City'].isnull()].groupby('Agency')['Status'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.024\n"
     ]
    }
   ],
   "source": [
    "# 57 of Cities with nan value are of DOT Agency.\n",
    "# It's better to know if this is significant before removing it\n",
    "city_null_dot = len(df[(df['City'].isnull()) & (df['Agency']=='DOT')].index)\n",
    "dot_total = len(df[df['Agency']=='DOT'].index)\n",
    "city_null_dot_perct = (city_null_dot/dot_total)*100\n",
    "print(\"%1.3f\"%city_null_dot_perct)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 0.024% is negligible and so Cities with nan can be removed from df\n",
    "df = df[df['City'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Created Date and Closed Date aren't in DateTime object. It's convenient when working with DateTime object\n",
    "# Convert Created Date and Closed Date values to DateTime object.\n",
    "import datetime\n",
    "df['Created Date'] = df['Created Date'].apply(lambda x:datetime.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p'))\n",
    "df['Closed Date'] = df['Closed Date'].apply(lambda x:datetime.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# It would be useful to create a column to compute how long it takes to close a complaint\n",
    "df['Processing Time'] =  df['Closed Date'] - df['Created Date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                    1847178\n",
       "mean     14 days 18:28:19.930685\n",
       "std      47 days 13:22:45.772770\n",
       "min          -365 days +00:00:00\n",
       "25%              0 days 03:10:15\n",
       "50%              2 days 00:00:00\n",
       "75%       8 days 19:38:00.750000\n",
       "max            918 days 14:08:12\n",
       "Name: Processing Time, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Viewing the descriptive statistics on the Processing Time can give some insights on turn around time\n",
    "df['Processing Time'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From the descriptive statistis, we can see minimum processing time is negative, this means something is wrong with the date data and it should be explored"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Created Date</th>\n",
       "      <th>Closed Date</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Complaint Type</th>\n",
       "      <th>Incident Zip</th>\n",
       "      <th>City</th>\n",
       "      <th>Status</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Processing Time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unique Key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28581213</th>\n",
       "      <td>2014-07-31</td>\n",
       "      <td>2014-07-23</td>\n",
       "      <td>DOHMH</td>\n",
       "      <td>Unsanitary Animal Pvt Property</td>\n",
       "      <td>10456</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>Pending</td>\n",
       "      <td>BRONX</td>\n",
       "      <td>40.835153</td>\n",
       "      <td>-73.912449</td>\n",
       "      <td>-8 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28541630</th>\n",
       "      <td>2014-07-25</td>\n",
       "      <td>2014-07-07</td>\n",
       "      <td>DOHMH</td>\n",
       "      <td>Rodent</td>\n",
       "      <td>11206</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Pending</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>40.701265</td>\n",
       "      <td>-73.929265</td>\n",
       "      <td>-18 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28934215</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2014-08-25</td>\n",
       "      <td>DOHMH</td>\n",
       "      <td>Rodent</td>\n",
       "      <td>10031</td>\n",
       "      <td>New York</td>\n",
       "      <td>Pending</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>40.827318</td>\n",
       "      <td>-73.946620</td>\n",
       "      <td>-28 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Created Date Closed Date Agency                  Complaint Type  \\\n",
       "Unique Key                                                                   \n",
       "28581213     2014-07-31  2014-07-23  DOHMH  Unsanitary Animal Pvt Property   \n",
       "28541630     2014-07-25  2014-07-07  DOHMH                          Rodent   \n",
       "28934215     2014-09-22  2014-08-25  DOHMH                          Rodent   \n",
       "\n",
       "           Incident Zip      City   Status    Borough   Latitude  Longitude  \\\n",
       "Unique Key                                                                    \n",
       "28581213          10456     Bronx  Pending      BRONX  40.835153 -73.912449   \n",
       "28541630          11206  Brooklyn  Pending   BROOKLYN  40.701265 -73.929265   \n",
       "28934215          10031  New York  Pending  MANHATTAN  40.827318 -73.946620   \n",
       "\n",
       "           Processing Time  \n",
       "Unique Key                  \n",
       "28581213           -8 days  \n",
       "28541630          -18 days  \n",
       "28934215          -28 days  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View Prcoessing Time data that is negative\n",
    "df[df['Processing Time']<datetime.timedelta(0,0,0)].head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>There are issues with some data in df, the Closed Date in some rows preceede its Created Date, thus, resulting in the negative processing time.</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Remove all data from df that have negative Processing Time\n",
    "df = df[df['Processing Time']>=datetime.timedelta(0,0,0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Created Date       1830970\n",
       "Closed Date        1830970\n",
       "Agency             1830970\n",
       "Complaint Type     1830970\n",
       "Incident Zip       1830970\n",
       "City               1830970\n",
       "Status             1830970\n",
       "Borough            1830970\n",
       "Latitude           1830970\n",
       "Longitude          1830970\n",
       "Processing Time    1830970\n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Count of non-null values for every column \n",
    "df_columns = list(df.columns)\n",
    "df[df_columns].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now that the data looks clean enough for further exploration, I'll create a function to incorporate all the data cleaning process\n",
    "<p>This makes future work on the dataset convenient.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def open_311_data(datafile):\n",
    "    import numpy as np\n",
    "    import pandas as pd\n",
    "    import datetime\n",
    "    \n",
    "    #Function to clean Incident Zip\n",
    "    def correct_zip(zip_code):\n",
    "        try:\n",
    "            zip_code = int(float(zip_code))\n",
    "        except:\n",
    "            try:\n",
    "                zip_code = int(float(zip_code.split('-')[0]))\n",
    "            except:\n",
    "                return np.nan\n",
    "        if zip_code < 10000 or zip_code > 19999:\n",
    "            return np.nan\n",
    "        else:\n",
    "            return str(zip_code)\n",
    "    \n",
    "    #Function to clean City values, i.e convert City values to Camel Case\n",
    "    def camel_case(city):\n",
    "        try:\n",
    "            city = city.split(' ')\n",
    "            city = ' '.join([x.lower().capitalize() for x in city])\n",
    "            if city == 'Unknown':\n",
    "                return np.nan\n",
    "            else:\n",
    "                return city\n",
    "        except:\n",
    "            return np.nan\n",
    "    \n",
    "    #Read the file\n",
    "    df = pd.read_csv(datafile, index_col='Unique Key')\n",
    "    \n",
    "    #Drop columns that aren't relevant to this analysis\n",
    "    df_cols_rmv = ['Incident Address', 'Street Name', 'Cross Street 1', 'Cross Street 2',\n",
    "                   'Intersection Street 1', 'Intersection Street 2', 'Landmark', 'Facility Type',\n",
    "                   'Due Date', 'Resolution Description','Community Board', 'X Coordinate (State Plane)',\n",
    "                   'Y Coordinate (State Plane)', 'Park Facility Name', 'Park Borough', 'School Name',\n",
    "                   'School Number', 'School Region', 'School Code', 'School Phone Number', 'School Address',\n",
    "                   'School City', 'School State', 'School Zip', 'School Not Found', 'School or Citywide Complaint',\n",
    "                   'Vehicle Type', 'Taxi Company Borough', 'Taxi Pick Up Location', 'Bridge Highway Name',\n",
    "                   'Bridge Highway Direction', 'Road Ramp', 'Bridge Highway Segment', 'Garage Lot Name',\n",
    "                   'Ferry Direction', 'Ferry Terminal Name', 'Location', 'Address Type', 'Agency Name',\n",
    "                   'Resolution Action Updated Date', 'Descriptor', 'Location Type']\n",
    "    \n",
    "    df.drop(df_cols_rmv, inplace=True, axis=1)\n",
    "    \n",
    "    #Clean Incident Zip \n",
    "    df['Incident Zip'] = df['Incident Zip'].apply(correct_zip)\n",
    "    \n",
    "    #Clean City values\n",
    "    df['City'] = df['City'].apply(camel_case)\n",
    "    \n",
    "    #Drop unspecified boroughs\n",
    "    df = df[df['Borough'] != 'Unspecified']\n",
    "    \n",
    "    #Drop all rows with nan\n",
    "    df = df.dropna(how='any')\n",
    "    \n",
    "    #Convert Created Date and Closed Date to datetime objects, create a Processing Time column\n",
    "    df['Created Date'] = df['Created Date'].apply(lambda x:datetime.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p'))\n",
    "    df['Closed Date'] = df['Closed Date'].apply(lambda x:datetime.datetime.strptime(x,'%m/%d/%Y %I:%M:%S %p'))\n",
    "    df['Processing Time'] =  df['Closed Date'] - df['Created Date']\n",
    "    \n",
    "    #Remove negative processing time rows from the dataframe\n",
    "    df = df[df['Processing Time']>=datetime.timedelta(0,0,0)]\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ikp\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2802: DtypeWarning: Columns (8,17,40,41,42,43,44,45,46,47,48,49) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  if self.run_code(code, result):\n",
      "C:\\Users\\Ikp\\Anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:463: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Created Date</th>\n",
       "      <th>Closed Date</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Complaint Type</th>\n",
       "      <th>Incident Zip</th>\n",
       "      <th>City</th>\n",
       "      <th>Status</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Processing Time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unique Key</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28457271</th>\n",
       "      <td>2014-07-11 15:08:58</td>\n",
       "      <td>2014-08-05 12:41:37</td>\n",
       "      <td>DOT</td>\n",
       "      <td>Sidewalk Condition</td>\n",
       "      <td>11368</td>\n",
       "      <td>Corona</td>\n",
       "      <td>Closed</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>40.751870</td>\n",
       "      <td>-73.862718</td>\n",
       "      <td>24 days 21:32:39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28644314</th>\n",
       "      <td>2014-08-08 14:06:22</td>\n",
       "      <td>2014-08-12 11:33:34</td>\n",
       "      <td>DCA</td>\n",
       "      <td>Consumer Complaint</td>\n",
       "      <td>10014</td>\n",
       "      <td>New York</td>\n",
       "      <td>Closed</td>\n",
       "      <td>MANHATTAN</td>\n",
       "      <td>40.732623</td>\n",
       "      <td>-74.001119</td>\n",
       "      <td>3 days 21:27:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29306886</th>\n",
       "      <td>2014-11-18 00:52:40</td>\n",
       "      <td>2014-11-18 01:35:22</td>\n",
       "      <td>NYPD</td>\n",
       "      <td>Blocked Driveway</td>\n",
       "      <td>11358</td>\n",
       "      <td>Flushing</td>\n",
       "      <td>Closed</td>\n",
       "      <td>QUEENS</td>\n",
       "      <td>40.760384</td>\n",
       "      <td>-73.806826</td>\n",
       "      <td>0 days 00:42:42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Created Date         Closed Date Agency      Complaint Type  \\\n",
       "Unique Key                                                                      \n",
       "28457271   2014-07-11 15:08:58 2014-08-05 12:41:37    DOT  Sidewalk Condition   \n",
       "28644314   2014-08-08 14:06:22 2014-08-12 11:33:34    DCA  Consumer Complaint   \n",
       "29306886   2014-11-18 00:52:40 2014-11-18 01:35:22   NYPD    Blocked Driveway   \n",
       "\n",
       "           Incident Zip      City  Status    Borough   Latitude  Longitude  \\\n",
       "Unique Key                                                                   \n",
       "28457271          11368    Corona  Closed     QUEENS  40.751870 -73.862718   \n",
       "28644314          10014  New York  Closed  MANHATTAN  40.732623 -74.001119   \n",
       "29306886          11358  Flushing  Closed     QUEENS  40.760384 -73.806826   \n",
       "\n",
       "            Processing Time  \n",
       "Unique Key                   \n",
       "28457271   24 days 21:32:39  \n",
       "28644314    3 days 21:27:12  \n",
       "29306886    0 days 00:42:42  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Open, read, and process the NYC 311 dataset using the open_311_data function\n",
    "datafile = '311_Service_Requests_from_2014.csv'\n",
    "df = open_311_data(datafile)\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Visualizations</h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Visualizing 311 call data Incidents with a heat map\n",
    "import gmaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "40f4a725e1e648f9979830f979bad4f7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Figure</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Figure()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import settings # Contains my Google map API key\n",
    "gmaps.configure(api_key=settings.API_KEY) # Fill in with your API key\n",
    "new_york_coordinates = (40.75, -74.00)\n",
    "locations = df[['Latitude','Longitude']]\n",
    "fig = gmaps.figure(center=new_york_coordinates, zoom_level=12)\n",
    "heatmap_layer = gmaps.heatmap_layer(locations)\n",
    "fig.add_layer(heatmap_layer)\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sbd/j+iRLN8eLliRJkqbKpoxwHwt8d+j5ccBFVbUHcFF7TpI9gSOAZwMHAx9NMqf1OQV4\nE7BHexzc2o8C7qmq3YGTgPe1c80Hjgf2A/YFjh8O9pIkSdKom1TgTrILcAjwj0PNhwJntO0zgMOG\n2s+uqger6gZgBbBvkp2B7arqkqoq4MxxfcbOdS5wQBv9PghYVlWrq+oeYBmPhnRJkiRp5E12hPvD\nwDuBR4baFlbVbW37dmBh214E3Dx03C2tbVHbHt++Vp+qehi4F9hxA+daS5KjkyxPsnzVqlWTfEmS\nJElS9zYauJO8Erizqq5Y3zFtxLo2Z2GboqpOraolVbVkwYIFfZUhSZIkrWMyI9wvAn4zyY3A2cDL\nk/wTcEebJkL7emc7fiWw61D/XVrbyrY9vn2tPknmAtsDd2/gXJIkSdK0sNHAXVXvqqpdqmoxg4sh\nL66qNwDnA2OrhiwFPtO2zweOaCuP7Mbg4sjL2vST+5Ls3+ZnHzmuz9i5XtO+RwGfBw5MMq9dLHlg\na5MkSZKmhbmPo++JwDlJjgJuAg4HqKprkpwDXAs8DBxTVWtan7cApwNbAxe2B8DHgLOSrABWMwj2\nVNXqJO8FLm/HvaeqVj+OmiVJkqQptUmBu6q+DHy5bd8NHLCe404ATpigfTnwnAnafwK8dj3nOg04\nbVPqlCRJkkaFd5qUJEmSOmTgliRJkjpk4JYkSZI6ZOCWJEmSOvR4VimRJG0Gi4+7oO8SRsaNJx7S\ndwmStNk5wi1JkiR1yMAtSZIkdcjALUmSJHXIwC1JkiR1yMAtSZIkdcjALUmSJHXIwC1JkiR1yMAt\nSZIkdcjALUmSJHXIwC1JkiR1yMAtSZIkdcjALUmSJHVobt8FzFSLj7ug7xJGxo0nHtJ3CZIkSb1x\nhFuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuSJEnqkIFbkiRJ6pCB\nW5IkSeqQgVuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuSJEnqkIFb\nkiRJ6pCBW5IkSeqQgVuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuSJEnqkIFbkiRJ6pCBW5IkSeqQgVuS\nJEnqkIFbkiRJ6tBGA3eSrZJcluRbSa5J8hetfX6SZUmub1/nDfV5V5IVSa5LctBQ+z5JvtP2nZwk\nrX3LJJ9q7ZcmWTzUZ2n7HtcnWbo5X7wkSZLUtcmMcD8IvLyqngfsBRycZH/gOOCiqtoDuKg9J8me\nwBHAs4GDgY8mmdPOdQrwJmCP9ji4tR8F3FNVuwMnAe9r55oPHA/sB+wLHD8c7CVJkqRRt9HAXQP3\nt6dbtEcBhwJntPYzgMPa9qHA2VX1YFXdAKwA9k2yM7BdVV1SVQWcOa7P2LnOBQ5oo98HAcuqanVV\n3QMs49GQLkmSJI28Sc3hTjInyVXAnQwC8KXAwqq6rR1yO7CwbS8Cbh7qfktrW9S2x7ev1aeqHgbu\nBXbcwLnG13d0kuVJlq9atWoyL0mSJEmaEpMK3FW1pqr2AnZhMFr9nHH7i8Gody+q6tSqWlJVSxYs\nWNBXGZIkSdI6NmmVkqr6AfAlBtM67mjTRGhf72yHrQR2Heq2S2tb2bbHt6/VJ8lcYHvg7g2cS5Ik\nSZoWJrNKyYIkO7TtrYFfB74HnA+MrRqyFPhM2z4fOKKtPLIbg4sjL2vTT+5Lsn+bn33kuD5j53oN\ncHEbNf88cGCSee1iyQNbmyRJkjQtzJ3EMTsDZ7SVRp4AnFNV/5bkG8A5SY4CbgIOB6iqa5KcA1wL\nPAwcU1Vr2rneApwObA1c2B4AHwPOSrICWM1glROqanWS9wKXt+PeU1WrH88LliRJkqbSRgN3VX0b\n2HuC9ruBA9bT5wTghAnalwPPmaD9J8Br13Ou04DTNlanJEmSNIq806QkSZLUIQO3JEmS1CEDtyRJ\nktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS\n1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLU\nIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQh\nA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CED\ntyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3JEmS1CEDtyRJktQhA7ckSZLUIQO3\nJEmS1KGNBu4kuyb5UpJrk1yT5NjWPj/JsiTXt6/zhvq8K8mKJNclOWiofZ8k32n7Tk6S1r5lkk+1\n9kuTLB7qs7R9j+uTLN2cL16SJEnq2mRGuB8G3l5VewL7A8ck2RM4DrioqvYALmrPafuOAJ4NHAx8\nNMmcdq5TgDcBe7THwa39KOCeqtodOAl4XzvXfOB4YD9gX+D44WAvSZIkjbqNBu6quq2qrmzbPwS+\nCywCDgXOaIedARzWtg8Fzq6qB6vqBmAFsG+SnYHtquqSqirgzHF9xs51LnBAG/0+CFhWVaur6h5g\nGY+GdEmSJGnkbdIc7jbVY2/gUmBhVd3Wdt0OLGzbi4Cbh7rd0toWte3x7Wv1qaqHgXuBHTdwLkmS\nJGlamHTgTrIN8C/AW6vqvuF9bcS6NnNtk5bk6CTLkyxftWpVX2VIkiRJ65hU4E6yBYOw/c9V9enW\nfEebJkL7emdrXwnsOtR9l9a2sm2Pb1+rT5K5wPbA3Rs411qq6tSqWlJVSxYsWDCZlyRJkiRNicms\nUhLgY8B3q+pDQ7vOB8ZWDVkKfGao/Yi28shuDC6OvKxNP7kvyf7tnEeO6zN2rtcAF7dR888DByaZ\n1y6WPLC1SZIkSdPC3Ekc8yLgd4HvJLmqtf0JcCJwTpKjgJuAwwGq6pok5wDXMljh5JiqWtP6vQU4\nHdgauLA9YBDoz0qyAljNYJUTqmp1kvcCl7fj3lNVqx/ja5UkSZKm3EYDd1V9Hch6dh+wnj4nACdM\n0L4ceM4E7T8BXruec50GnLaxOiVJkqRR5J0mJUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJ\nkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmS\npA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKk\nDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQO\nGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4Z\nuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQObTRwJzktyZ1J\nrh5qm59kWZLr29d5Q/velWRFkuuSHDTUvk+S77R9JydJa98yyada+6VJFg/1Wdq+x/VJlm6uFy1J\nkiRNlcmMcJ8OHDyu7TjgoqraA7ioPSfJnsARwLNbn48mmdP6nAK8CdijPcbOeRRwT1XtDpwEvK+d\naz5wPLAfsC9w/HCwlyRJkqaDjQbuqvoqsHpc86HAGW37DOCwofazq+rBqroBWAHsm2RnYLuquqSq\nCjhzXJ+xc50LHNBGvw8CllXV6qq6B1jGusFfkiRJGmmPdQ73wqq6rW3fDixs24uAm4eOu6W1LWrb\n49vX6lNVDwP3Ajtu4FySJEnStPG4L5psI9a1GWp5zJIcnWR5kuWrVq3qsxRJkiRpLY81cN/RponQ\nvt7Z2lcCuw4dt0trW9m2x7ev1SfJXGB74O4NnGsdVXVqVS2pqiULFix4jC9JkiRJ2vwea+A+Hxhb\nNWQp8Jmh9iPayiO7Mbg48rI2/eS+JPu3+dlHjuszdq7XABe3UfPPAwcmmdculjywtUmSJEnTxtyN\nHZDkk8CvADsluYXByiEnAuckOQq4CTgcoKquSXIOcC3wMHBMVa1pp3oLgxVPtgYubA+AjwFnJVnB\n4OLMI9q5Vid5L3B5O+49VTX+4k1JkiRppG00cFfV69ez64D1HH8CcMIE7cuB50zQ/hPgtes512nA\naRurUZIkSRpVGw3ckiRJGg2Lj7ug7xJGxo0nHtJ3CZPmrd0lSZKkDhm4JUmSpA4ZuCVJkqQOGbgl\nSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJ\nkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmS\npA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKk\nDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQO\nGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDhm4JUmSpA4ZuCVJkqQOGbglSZKkDk2LwJ3k4CTX\nJVmR5Li+65EkSZIma+QDd5I5wN8BrwD2BF6fZM9+q5IkSZImZ+QDN7AvsKKqvl9VDwFnA4f2XJMk\nSZI0KdMhcC8Cbh56fktrkyRJkkZeqqrvGjYoyWuAg6vq99vz3wX2q6o/HDrmaODo9vQXgeumvNDR\ntBNwV99FaOT4vtB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qfn5qK5q+HOGWZrZHhrZ/PG6ff23PXncwuPvoQmABcD2+HySt62VV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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30aea13c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Exploration of incidents by Borough\n",
    "borough = df.groupby('Borough')\n",
    "borough.size().plot(kind='bar', figsize=(12,6), title=('Incidents by Borough'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From the graph, we can see that Brooklyn has the most incidents, while, Staten Island has the least. It should also be noted that Staten Island is the smallest of the five boroughs so that could be why it has the least incidents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lSZKkHhm4JUmSpB4ZuCVJkqQeGbglSZKkHhm4JUmSpB4ZuCVJkqQeGbglSZKkHhm4JUmS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\nqUf/PzSWeVT4mVRhAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30ad54b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of incidents by Agency\n",
    "agency = df.groupby('Agency')\n",
    "agency.size().plot(kind='bar', figsize=(12,6), title=('Incidents calls per Agency'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HPD has the highest complaints followed by NYPD in Brooklyn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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safRYjz32GN27d+eTn/xkXe3www/nL3/5CwsXLtyscd9555189rOfpV27dnW1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\ns9TPIcDJwDFV9ctuo1q3tm7BvwHbAxfS/CzsBvw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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30aa08518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualization of numnber of incidents in each Borough by Agency\n",
    "agency_borough = df.groupby(['Agency','Borough']).size().unstack()\n",
    "agency_borough.plot(kind='bar', title='Total Inicidents in each Borough by Agency', figsize=(15,7));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TP1fRe/PnL7otZ/J/R5ilvol5DatqS/N34uHAU5M8YWB756/fHDVOxGu4FH5X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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30a70e080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualization of top Agencies with most incidents per borough\n",
    "col_number = 2\n",
    "row_number = 3\n",
    "fig, axes = plt.subplots(row_number,col_number, figsize=(12,12))\n",
    "\n",
    "for i, (label,col) in enumerate(agency_borough.iteritems()):\n",
    "    ax = axes[int(i/col_number), i%col_number]\n",
    "    col = col.sort_values(ascending=True)[:5]\n",
    "    col.plot(kind='barh', ax=ax)\n",
    "    ax.set_title(label)\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B3wF+BGD7/2zv2vqp7TbW9hBgY2B7SVs1KN/mXAj8ExhkexNgX6DVoKyjbDfZPjQ2twG2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VlJV0naVtLDkp6TtFFnzzUingM+AL6Y615V0vA82jeyNPuW6z5fUktuw84VzmcjSY9KGivpEUlr\n5PQeks6QNClfs6E5faCkB3Jdd0rql9NHSDoz1/WUpA0l3ZzP9ZRCfd+TNCqPhl4gqUdOnyHpV3kU\n9jFJy+druytwes6/amevmZnZQmBp4B2ovvJC0k75nr+cpL6SbsqxcbSkzVsrPCJmAuOAFXNZHYof\nhTb0kvR3SYeUpa8KbAwcHxFzcp1TIuKOvP+nucxJko4snOdTki6SNFnSXbkjWIpX4yWNB35cqGeQ\npNslNQGHAT/JMWbL/PfDUTnfgByPJki6RVIp5o6QdFqOZc9K2rI9vxwz617uYHVcL81dHnhLlTxr\nA9tGxH6kDtP0iNgQ2BA4RGlUrNxuwPCIeBZ4W9LACnneAL4dERsA+wDFZYkbAEdExNfz9mrA74A1\n8893SR24o4D/7cD5zkPSBsBzEfFGTroQGBoRA3PZ5xayNwEbATsB50tavKy4p4EtI2J94ATg1zn9\n0HzsgIhYD7hK0qLAn4A9c12XAL8qlPVxRDQD5wN/JQW0dYAhkr4kaS3SNds8j7jOBvbPxy4JPBYR\n/YEHgUMi4hHgVuDoiBgQEc+XXYdDc4euZfYH09t9/czMPkdK8fBp0uzPL6tllLQ7cCywY0S8BfyB\ntDJiQ2CPfHxVuYOxOukeDR2IH4ViegO3AddExEVlVXwDGBcRsyvUPRA4mNQB24QUx9fPu1cHzomI\nbwDT8rkAXEqKjf0rnU9ETCXFqzNzjBlZluVy4Gf5HCYy76qWnhGxEXAkVVa7OEaZ1ZeXCHZcpSWC\n5W7No20A2wHrSSotl+hDuiFPKTtmP1LAAbg2b48py7MocLakUgfh64V9oyKiWOaUiJgIIGkycG9E\nhKSJpODTUT+RdHCuc5dcbm9gM+AGSaV8ixWOuT6PBD4n6QVSR6+oD3CZ0rLDyOcHsC1wfmmpY0T8\nW9I6pA7T3bmuHsCrhbJuzf9OBCZHxKu5jS8AK5E6lwOB0fn4XqQOK8DHpKWAkK75t9u6GBFxIalz\nyWL9Vo+28puZfQ4VlwhuClye79XlvgU0A9tFxLs5bVtg7ULsWFpS74iYUXbslnkWaHXgrIh4Lae3\nO34Uyvor8NuIKHa62mML4JaIeD+f683AlqS4MyUixuV8Y4AmScsAy0REqTN4BbBDeyuT1Ccf/0BO\nugy4oZDl5mJ9lcpwjDKrL3ewFoz3C59FGsW6s1pmScuSAtC6koLUeQhJR5dl/QnwOtCfNPv4YZU6\nAT4qfJ5T2J5Dhd+7pEuB9YFXImLHCs0sPYO1K/DnvJxiEWBaKx3O8pt6+fYvgfsjYve8XGJElXIg\nXcfJEbFplf3F8ys/9575+Msi4ucVjp0VEaW2zcb/X5iZdUhEPKr0Eom+FXY/D6xCGqArPX+0CLBJ\nRHxYIX9R6RmsrwGPSbo+d2g6Ej9KHga2l3R14Z5fMhnoL6lHpVmsVhTjzWzS4N2CVqrT8cqsQXmJ\n4IJ3J/BfeYkbkr4uacmyPHsCV0TEyhHRFBErkWa4ytdW9wFezbNCB5A6YjUREQfnZQqVOlfFfLeS\nAuRBeSRyiqS9AJQUl0PsJWmR3BlbBXimwvm8nD8PKaTfDfw/ST1zucvmY/vmUVIkLSrpGx04xXuB\nPSV9uVSmpJXbOOY9YKkO1GFmtlBSev62B/B2hd0vkpbOXV64b98FfPp8VF6ZUVVeoXEq8LOc1JH4\nUXIC6TmxcyqU/zwptp2kPK2Wn7HaCRgJDJa0RI7fu+e0am2dBkyTtEVO2r9K1ooxJiKmA+8Unq86\nAHigPJ+ZNS6PfCx4F5Om8J/IN+03SW+nK9oPOK0s7aYK6ecCNym9xnU4889adZeTgaslXUQKHOdJ\nOp60RONaYHzO9xIwivTw82ER8WFhOQjAb0lLPI4Hil/ScTFppHOCpFnARRFxdl5m+ce8fKIncBZp\n1LFNEfFkrucuSYsAs0jPab3YymHXAhdJOpz07NfzlTKtu2IfWvydP2a28OklqbQ8TqSBt9ll93kA\nIuJpSfuTlpTvAhwOnCNpAul+/iDppQ+tOR84Ks9YtTt+AMXXxB8BXCLptxFxTFn5PyQ9u/wPSTOB\nt0jP4T4haRgpngFcHBFjczuqOTjXE6TOZCW3ATdK2o1CZzM7iPTs8hLAC7m8TnGMMut+mn+W3Kzr\ncjC6PSJurHdbFrTm5uZoaZnvLf1m1g6SxuQX1JjZAuAYZdZ5nY1RXiJoZmZmZmZWI14iaAtERAyp\ndxvMzMzMzLqbZ7DMzMzMzMxqxB0sMzMzMzOzGnEHy8zMzMzMrEbcwTIzMzMzM6sRv+TCrIsmvjyd\npmPvaDujWTtN9XfWmFmNOEZZLTk+tY9nsKwiSbMljZM0XtITkjZrI3+TpO8WtgdI2rGwPUTS2ZWP\nrlrmVEnLlaUdIemswvYFku4pbA+V9Mc2yv3fjrTDzKzRSFpJ0hRJy+btL+btpgp5T5T0cr6nPylp\nvxq14URJIWm1QtqROa3D3xvTWpyQ9DdJy3Shrf0k3ZVj1cx8LUo/B3ayzBUk1e27Hh3LzBqXO1hW\nzcyIGBAR/YGfA79pI38T8N3C9gBgx8pZu+RhoNjZ6w/0kdQjb28GPNJGGR0OSoXyzczqLiL+CZwH\nnJqTTgUujIipVQ45MyIGALsBF0hatEZNmQjsW9jeC5hco7I/FRE7RsS0LhSxPXBn/vx8jm+ln8s7\n2aZXImLPLrSpq9zBMmtQ7mBZeywNvAOg5HRJkyRNlLRPznMqsGUeDfwZcDKwT97ep1iYpL6SbpI0\nOv9sntO/lEcYJ0u6GFCFtowDvi6pl6Q+wMyctm7evxmpE4akv0gak8s7NKedCvTK7boqp31P0qic\ndkGpMyVphqTfSRoPbFqTK2lmVjtnAptIOhLYAjijrQMi4jngA+CLAJIOyffh8fm+vISkpfJs2KI5\nz9LF7TJ/IXXakLQqMB14q7RT0nmSWvJ9+KRC+oaSHsn1jpK0VN61gqThkp6T9NtC/qmSlsszUE9J\nuiiXeZekXqX687FjJI2UtGahndsDf2/t2kg6WNKzuT0XlWbTJA2TtGch34z8b5OkSfnzEEl/lTQi\nt/0XhTxP5zKelXSVpG0lPZzzbZTzLSnpklz3WEm7Fcq9ufyaVIplZtY43MGyako37qeBi4Ff5vT/\nJM1O9Qe2BU6X1A84FhiZRwNPA04Arsvb15WV/QfSaOqGwB65fIBfAA9FxDeAW4CvljcqIj4BxgIb\nApsAjwOPAZtJWhFQHtkF+H5EDASagcMlfSkijmXu7Nz+ktYC9gE2z6O7s4H98/FLAo9HRP+IeKjY\nDkmH5j8aWmZ/ML39V9XMrEYiYhZwNKmjdWTebpWkDYDnIuKNnHRzRGyYVys8BfwgIt4DRgClhy32\nzfkqlf8u8E9J6+R85ff74yKiGVgP2ErSepK+kPMdkevdljRYBim+7EMaNNtH0koV6lwdOCfHimmk\nOAJwITA03/ePAs7N59wDWCMinsz5VtW8SwS3zHHsJGBzUmd17epXsaqNclvWA/bS3GWSqwG/A9bM\nP9/NdRzF3Fmo44D7ImIjYGtSbF2y2jUpj2XlDXGMMqsvv+TCqpmZOxxI2hS4PAfQLYBrImI28Lqk\nB0idnXc7UPa2wNrSpxNUS0vqDXyT1IEjIu6Q9E6V4x8hzVT1Ah4FniMFqTeZd3ng4ZJ2z59XIgXl\nt8vK2gYYCIzO7ekFlP7wmA3cVKkBEXEhKZizWL/Vo/XTNTNbYHYAXgXWAe5uJd9PJB0MfB3YpZC+\njqRTgGWA3sxdRncxcAxphupg4JBWyr6W1Ln6DumeenBh3955BUFPoB+p4xLAqxExGiAi3gXI9+B7\nI2J63n4SWBn4J/OaEhHj8ucxQFOOIZsBNxRiy2L5341Jg3Elz5fiW4mkwcCIiHgzb19HulYdcXdE\nvJ2Pv5kUL/+S2zsxp0/O5xiSJpKW1wNsB+wq6ai8vThzBxnbc03m4RhlVl/uYFmbIuJRpZdN9K1R\nkYsAm0TEh8XEQlBsy8PAYaQAdA6pY7U2hQ6WpEGkjtymEfGBpBE5fzkBl0XEzyvs+zB3JM3MGo6k\nAcC3SbP5D0m6NiJelfQr8uxToSNxZkScIWlX4M+SVs334GHA4IgYL2kIMCgf93Be3jYI6BERk1pp\nyu3A6UBLRLxbupdL+hpplmbDiHhH0jAq34eLPip8nk3lv1PK8/QixZVp5R2nbAdgeBv1tuaTXD6S\nFgG+UCVfeUemtF1s75zC9hzmnp+APSLimWIBkjamfdfEzBqIlwham/I69h6k2Z+RpCUKPST1Jc06\njQLeA5YqHFa+XXQXMLRQfikgPkh+UYakHcjPCFTwKOkPir4R8UZEBKlztRv5+SugD/BO7lytmfOX\nzNLcZwnuBfaU9OVc77KSVq56MczMGoBSL+Y80tLAl0gdnDMAIuK40gscyo+LiFuBFuCgnLQU8Gq+\nJ5YvNbscuBq4tLW2RMQHwM+AX5XtWhp4H5guaXlSRwfgGaCfpA3zuSwlqUudhjwLNkXSXrlMSeqf\nd28D3FP14ORx0hLGL+VrsVdh31TSSgeAXYFqLwj5do4hvYDBzI1H7XEnMDT/XpG0fjuOKcYyM2sg\nHgWxanpJKi3BEHBQRMyWdAvphQ/jSaNzx0TEa5LeBmYrvRBiGHAZcGwuo/wNhIcD50iaQPpv8EHS\njNRJwDV5CcUjwEuVGpZHQt9k3jdVPUpaOz8+bw8HDpP0FCmYP1bIeyEwQdIT+Tms44G78sjkLODH\nwIvtvVDrrtiHFn8vhJl1r0OAlyKitCzwXOBgSVtFxANtHHsycLWki4D/I3Uu3sz/FgfGrgJOAa5p\nqzERcW2FtPGSxgJPk5a0PZzTP1Z6+dGfcmdkJmnFQVftD5yX7+mLAtdKeoW0GuG9Qr5VC/EN4JKI\n+KOkE0mxZBrp5UklFwF/zfFtOKnTWMko0rLyrwBXRkSLKrw2v4pfAmeRYtMiwBRg5zaOmSeWVcvk\nGGXW/ZQG/82ss5qbm6OlpaXezTD7TJI0Jr8EwRqM0pvzdouIA+rdls6S9D3gKxFxapuZ5z1uCNAc\nEf+9IPJ3J8cos87rbIzyDJaZmZnNQ9KfSEv6FsT3GXabiLiy3m0ws4WPO1hmZmY2j4gY2nauz6+I\nGEZa7r5A8pvZ55tfcmFmZmZmZlYj7mCZmZmZmZnViDtYZmZmZmZmNeIOlpmZmZmZWY34JRdmXTTx\n5ek0HXtHvZthnyNT/Z01ZlYjjlFWS45P7bPQzGBJmi1pnKRJkm6QtEQb+UdImu+995KGSDo7fz5M\n0oEdbMdgSSFpzY6dQW1ImlElfVj+zpOulP2lfI3HSXpN0suF7S90pWwzM/t8cnz+tP4FFp/NrHst\nNB0sYGZEDIiIdYCPgcO6WmBEnB8Rl3fwsP2Ah/K/nysR8Xa+xgOA84EzS9sR8XG92qWkXf+tS/Ks\nrplZ93J8NrPPlYWpg1U0ElhNUpOkSaVESUdJOrGQ74DCqNpG5YVIOlHSUfnzapLukTRe0hOSVq2Q\nvzewBfADYN9Cej9JDxbq2lJSjzxqNUnSREk/yXlXlTRc0hhJI0sjbTnveZIek/SCpEGSLpH0lKRh\nZe04U9JkSfdK6lu271uS/lLY/rakWzpwbauSdJCkUfk8z5W0iKSekqZJ+n1u052SNpb0QD6PHfOx\nP5R0S05/TtLxhXKPyddpkqShOW01SU9KugqYDPSTdKGkllzPCYXj/yXpVEljgf+RNLqwby1Jo2px\n/mZm1ibH5zrEZzOrrYWug6U0Q7EDMLEd2ZfIszE/Ai5pI+9VwDkR0R/YDHi1Qp7dgOER8SzwtqSB\nOf27wJ25rv7AOGAAsGJErBMR6wKX5rwXAkMjYiBwFHBuofwvApsCPwFuBc4EvgGsK2lAzrMk0BIR\n3wAeAH5R1sb7gTULN/aD23HubZK0DrA7sFk+z57MDWJ9gL/nNn0MnAhsA+wFnFwoZiNgMOnafFfS\nAEkbA/sDG+Zz/5GkdXP+NUmzaGtHxMvAsRHRTLrG35a0dqHsNyJi/Yg4DZiZ23qVwgkAACAASURB\nVFs6/0spI+nQ3Flrmf3B9C5cGTMzA8dnahifHaPM6mth6mD1kjQOaAFeAv7cjmOuAYiIB4GlJS1T\nKZOkpUg321ty/g8j4oMKWfcDrs2fr2XuMoTRwMF5dG7diHgPeAFYRdKfJG0PvJtH2DYDbsjncgHQ\nr1D+bRERpOD0ekRMjIg5pBmcppxnDnBd/nwlacTuU/n4K4Dv5fPdFPh7K9eovbYldYJactu3Akqj\niDMj4u78eSIwIiI+yZ+bCmXcGRHvRMT7wF9y27cAboqImfm6/QXYMud/PiJaCsfvJ+kJ4AlgLaDY\nwbqu8PnPpN9HT1In75ryk4mICyOiOSKaeyzRp0MXwszM5uH4nNQsPjtGmdXXwvS8ycw8AvUpSZ8w\nbydz8bJjoo3tdpO0LPAt0mhVAD2AkHR0RDwo6ZvATsAwSb+PiMsl9Qe+Q1qPvjdwJDCt/DwKPsr/\nzil8Lm1X+11XOqdLgduAD4EbcmeneC4bk4IHwAkRcWvVEy8cBlwSEf9XVlZP0qxVsa3F8yi2u6O/\nj/cL9awOHAFsFBHTJF3JvL/v9wufbwD+F3gYeDQiprVRj5mZdZ7jc2Udjs9m1hgWphmsSl4Hvqz0\n9rvFgJ3L9u8DIGkLYHpEVJxnzyNa/5I0OOdfTPO/BWlP4IqIWDkimiJiJWAKsKWklUkjWhcBFwMb\nSFoOWCQibgKOBzaIiHeBKZL2yvUo3+Q7YpHcFkhLHx6qcD6vAK/keudbHhcRjxdeXtGezhXAPcDe\n+bxKbxz8agfbvp2kZfK13Y3UARoJ7C6pVx5B3C2nlVsaeI800tiPFBgryqOb9wFnU+H8zcxsgXN8\n7kR8NrPGsDDNYM0nImZJOhkYBbwMPF2W5UOlFx8sCny/jeIOAC7I5c0iLS17obB/P+C0smNuyumP\nAUdLmgXMAA4EVgQu1dy33/08/7s/cJ7SSx4WJS1lGN+O0y15H9goH/8GOUhVcBXQNyKe6kDZVUXE\nREknAffkc5pFGvl7pQPFjAb+CqwAXBYR4wAkXZP3AZyX61qt7NgngCdJv+MXSZ2z1lwF7Ajc21aj\n1l2xDy3+Xggzs5pxfK5dfHaMMut+Skt6zeal9F0iYyOiPWvhFzhJPwTWiYgju6m+Y4HFIuKktvI2\nNzdHS0tLW9nMrAJJY/LLZ8ysHToanx2jzDqvszFqoZ7BssokjSGNpP1PvdtSD5JuA1Yirck3MzNr\nCAt7fDb7rHAHy+aTXzHbUCLi4m6sa5fuqsvMzKy9GjE+m9n8FvaXXJiZmZmZmdWMO1hmZmZmZmY1\n4g6WmZmZmZlZjbiDZWZmZmZmViN+yYVZF018eTpNx95R72bY58hUf2eNmdWIY5TVkuNT+9R9BkvS\njAVc/tT8revl6d+XNFHSBEmTJO1Wo/oOk3RgLcqqUPYwSVMkjZP0hKRNa1TuyZK2rZA+SNLtXSz7\nPyRdK+l5SWMk/U3S17tSZhv1tdlmSc2S/thGnmUk/ai2rTMzs+4gaXaOlZMk3SBpiTbyj5A033fd\nSBqSv3eq3fFd0pdy3eMkvSbp5cL2F6oc00PSyPx5NUnj2qhjFUn7ttUWM6uPhXIGS9JXgOOADSJi\nuqTeQN8OHN8zIj6ptC8izq9RM6s5OiJulLQdcAGwXnvbVk1EnFCLhpXXLUnALcBlEbFvTusPLA88\nW4s6OyMiWoC2vnVxGeBHwLkLvkVmZlZjMyNiAICkq4DDgN93pcD2xveIeBso1X0iMCMizmjjmNnA\nlh1ozirAvsC1HTjGzLpJ3WewKpHUV9JNkkbnn80L6XdLmizpYkkvlmanJP0lz5BMlnRoG1V8GXgP\nmAEQETMiYkouZ1VJw3NZIyWtmdOHSTpf0uPAb/PM2DKFNj8naXlJJ0o6KqetJukeSePzjNOqOf3o\nfF4TJJ2U05aUdEfOO0nSPm2cw4PAavnYEZLOktQCHCGpSdJ9ufx7JX1VUp98vRYp1PdPSYvmc9sz\np28v6WlJTwD/WTi/JSVdImmUpLGlGb88unerpPuAe8vauDUwqxiUImJ8RIxUcno+14ml880zUA9I\n+qukFySdKmn/XO/EwjUs/T5aJD0raefyCyRpI0mP5vY+ImmNQh23588n5vMakes7PB9+KrBqHnE8\nvY3fhZmZNa6RwGo5Nk4qJUo6KneASg7Q3FmvjcoLaU98bw9Jx+Q6JkkamtN6SppWIW9PSb/PMXCC\npB/mXacCW+f2Hl5+nJnVV6POYP0BODMiHpL0VeBOYC3gF8B9EfEbSdsDPygc8/2I+LekXsBoSTfl\nUaRKxgOvA1Mk3QvcHBG35X0XAodFxHOSNibNYHwr7/sKsFlEzJbUA9gduDTnezEiXpdUrOcq4NSI\nuEXS4sAiSjNPqwMbAQJulfRN0gzaKxGxE4CkPm1co12AiYXtL0REcz72NtKs0WWSvg/8MSIGKy05\n2Aq4H9gZuDMiZpXanNt4UT7ffwDXFco/jnTtv6/UsRwl6Z68bwNgvYj4d1kb1wHGVGn/f5JG+PoD\ny5F+Zw/mff1Jv+9/Ay8AF0fERpKOAIYCR+Z8TaTruCpwv6TVyup4GtgyIj5RWgL5a2CPCm1Zk9QZ\nXAp4RtJ5wLHAOqUR0HJKnfhDAXos3e7JTzMz60aSegI7AMPbkX2JiBiQY/IlpBhWzXzxvZ3t2RjY\nH9iQ9DfYKEkjgKeqHHIo8EaOgYsBj0m6ixSj/jsiBlepxzHKrI4atYO1LbB2obOytNIyvi1InRoi\nYrikdwrHHC5p9/x5JVInpmIHK3eQtifd4LYBzpQ0EDgD2Ay4oVD3YoVDb8jT+JA6HycAl5Km6Yud\nESQtBawYEbfkOj/M6dsB2wFjc9beua0jgd9JOg24PSJGVrk2p0s6HniTeTuYxfo3Ze7s0xXAbwt5\n9iF1sPZl/uVvawJTIuK53NYryTfo3OZdS6N3wOLAV/Pnuyt0rtqyBXBNvp6vS3qA9Pt4FxgdEa/m\nNjwP3JWPmUjqCJVcHxFzgOckvZDbX9QHuEzS6kAAi1Zpyx0R8RHwkaQ3SEsYWxURF5I64yzWb/Vo\n82zNzKw79dLc55hGAn8GVmjjmGsAIuJBSUursEqlqFp8b6ctgJsiYmYu6y+kpYHVOljbAWtp7vNW\nfUh/M7TKMcqsvhq1g7UIsEn5TatsdqiYPojUKds0Ij7Io0GLt1ZBRAQwijR6dDepo/R7YFq1WQvg\n/cLnR0lLDvoCg4FT2jinT5sL/CYiLqhwHhsAOwKnSLo3Ik6ucPzREXFjG22r5lbg15KWBQYC97Wz\nzaV27xERz5S1eeNW6p4M7NmBOko+KnyeU9iew7z/zZYHjfLtXwL3R8TukpqAEe2obzaN+/+FmZm1\nz8zyWC7pE+adaSr/O6GtmFIPAn4UEfMswVeFF1OZWeNoyGewSDMWQ0sbkko3yYeBvXPadsAXc3of\n4J3cuVoT2KS1wiWtkDszJQNIS/zeJS0b3Cvnk9JLGeaTO2i3kDplT5UvR4yI94B/SRqcy1pM6S1G\ndwLfzzNySFpR0pclrQB8EBFXAqeTlt111iOkGSpISxFG5jbNAEaTlmDeXpiNK3kaaCqsJd+vsO9O\nYKhyL1fS+u1ox33AYio8EydpPUlb5jbto/TmpL7AN0kd3o7YS9Iiub2rAM+U7e8DvJw/D+lg2e+R\nlgyamdnnw+vAl5Xe8rcYaal8UelZ4C2A6RExvVIhrcT39hgJ7C6pV/47YLecVs2dwI/yUkckrZEf\nhXCMMmtgjTBSv4SkfxW2fw8cDpwjaQKpjQ+S3gB0EnCNpANIM0ivkW4yw4HDJD1F+iP7sTbqXBQ4\nI3dqPiQttzss79sfOC8vw1uU9Iae8VXKuY7UYRlSZf8BwAWSTgZmAXtFxF2S1gIezX2VGcD3SC+s\nOF3SnJz3v9o4h9YMJT0bdnQ+t4PL2nwDMKj8oIj4MHeG7pD0AemmX7qB/xI4C5ig9KKMKcwfnMrL\ni7xs8yxJPyNd66mkZ6geIi1lHE8aJTwmIl7LHeT2eonUKVua9Nzch2WznL8lLRE8HujQl4BExNuS\nHlZ6IPrvEXF0tbzrrtiHFn8vhJlZQ8vPHJ9MihsvkwYViz6UNJYU+7/fRnHzxXfSM8NttWGUpGtI\nfzsAnBcRE0sdqAouIC3HH5fj2xukTtlYoIek8cCfI6LqV484Rpl1P6WJmM+GPOI0O7+0YFPSjana\ncj77HJM0jDQLV2m5ZLdqbm6Olpa23vpuZpVIGlN6QY+Z1Z5jlFnndTZGNcIMVkd8Fbg+z6B8DBxS\n5/aYmZmZmZl96jPVwcpvt2vPsz/2ORcRQ+rdBjMzMzOzco36kgszMzMzM7PPHHewzMzMzMzMasQd\nLDMzMzMzsxpxB8vMzMzMzKxGPlMvuTBrRBNfnk7TsR36mi1bQKb6u17MzObhGGW15DjbPp7BakCS\nZksaJ2mSpNskLdPB40+UdFT+fLKkbWvYtiZJ3y1sN0uq+gWHHSh3kKSQ9MNC2oCcdlQbxw6WtHYn\n6txV0rFt5Bki6eyOlm1m1t3y/fLKwnZPSW9Kuj1vt3nP62B9wyTtmT+PkPSZ+D4zSQfm+DpR0tgF\nFWM62bZHuqMeM1uw3MFqTDMjYkBErAP8G/hxZwuKiBMi4p7aNY0m4NMOVkS0RMThNSp7ErB3YXs/\nYHw7jhsMdCj4SeoZEbdGxKkdOc7MrIG9D6wjqVfe/jbwcmmn73kgaQfgSGC7iFgX2ASY3sZhHY4x\nnWhXT4CI2GxB1mNm3cMdrMb3KLAigKTeku6V9EQeedutlEnScZKelfQQsEYhvTjCuE0erZso6RJJ\ni+X0EySNziN6F0pSTl9N0j2Sxuc6VwVOBbbMM2w/yTNPt0taRNLU4mybpOckLS+pr6Sbch2jJW1e\n5VxfBBbPxwjYHvh7obxD8vHjc3lLSNoM2BU4Pbdp1fwzXNIYSSMlrVm4FudLehz4bXF2StIukh7P\n1+ceSct38fdmZlYPfwNKa3j2A64p7Si75+2V7/njJT2Y03pIOiOnT5A0NKcPlPRAvqfeKalfaw2Q\ndJ6kFkmTJZ1USJ8q6aRCDCvdm5fMMWlUvgfvltMXl3RpYaZp6/LzyNu351jUI9/nS7NTP6nQvJ8D\nR0XEKwAR8VFEXJTL6WqMWVXSY7nuUyTNyOmSdHqhXfvk9EH5+FuBJ3PajMJ5HZ3bM6F0HfO1uiO3\ncVKpLDNrLO5gNTBJPYBtgFtz0ofA7hGxAbA18Lt84x4I7AsMAHYENqxQ1uLAMGCfPGrXE/ivvPvs\niNgwz5j1AnbO6VcB50REf2Az4FXgWGBknmE7s1R+RMwB/grsnuvbGHgxIl4H/gCcGREbAnsAF7dy\n2jcCe+X6ngA+Kuy7ObezP/AU8IOIeCRfn6Nzm54HLgSGRsRA4Cjg3EIZXwE2i4ifltX7ELBJRKwP\nXAsc00obkXRo/gOiZfYHbQ1+mpl1m2uBffM9fz3g8Sr5TgC+k++nu+a0Q0mrFAZExHrAVZIWBf4E\n7JnvqZcAv2qjDcdFRHOufytJ6xX2vZVj2Hmk+zPAccB9EbERKbadLmlJ0uqNyDFrP+CyfF7VDABW\njIh18jGXVsizDjCmyvFdjTF/AP6Q6/5Xodz/zG3rD2ybz6/USd0AOCIivl5siKTtgNWBjfKxAyV9\nkzTw+EpE9M8xe3ilE3GMMqsvv+SiMfWSNI40c/UUcHdOF/DrfJOdk/cvD2wJ3BIRHwDk0bByawBT\nIuLZvH0ZKXidBWwt6RhgCWBZYLKkEaRAdQtARHyYy26t3deRgvalpA7fdTl9W2DtwrFLS+odETPm\nL4Lr83FrkkZei8sl1pF0CrAM0Bu4s/xgSb3zMTcU6luskOWGiJhdod6vANfloPcFYEprJxoRF5KC\nLIv1Wz1ay2tm1l0iYoKkJlKH5G+tZH0YGCbpeuDmnLYtcH5EfJLL+rekdUidkrvzPbUHabCtNXtL\nOpT0N0Y/0vK6CXlfqa4xpI4HwHbArpr7LNTiwFeBLUidOyLiaUkvAvN0RMq8AKwi6U/AHcBdbbSz\nXFdjzKak5YQAVwNn5M9bANfk2PO6pAdIA6HvAqMiolK82S7/jM3bvUkdrpGkwdXTgNsjYmSlE3GM\nMqsvd7Aa08yIGCBpCdIN/sfAH4H9gb7AwIiYJWkqKRB1Wh4NPBdojoh/SjqxC2U+CqwmqS8pyJyS\n0xchzQ592FYBEfGapFmkZweOYN4O1jBgcESMlzQEGFShiEWAaRExoEoV71dJ/xPw+4i4VdIg4MS2\n2mpm1qBuJf1xPwj4UqUMEXFYXmmwEzAmr4SoRMDkiNi0PRVL+hppVmfDiHhH0jDmjSmlVQmzmfs3\niIA9IuKZsrKqVfMJ867AWTyf0zuS+gPfAQ4jPdP7/bJjJwMDgfsqlDuMrseYjqoWkwT8JiIumG+H\ntAFptcopku6NiJNr1BYzqxEvEWxgeUbqcOB/lB6A7QO8kTtXWwMr56wPAoMl9ZK0FLBLheKeAf4/\ne+cdbldRrvHfS2iBhKCACIhEQodAIIdOEBQ7SidELhJQEfVSVPTiBRGRS5WmICVIR0BKMID0Gmo4\nCWl0IUFAuiQQCC157x8zO1nZ2e30c5Lv9zz7OWtN/WbtZL17Zr6Z6S9pjXy/D3Avc4XvzTwyt3uu\n+13gJUk7A0haInf43gX6VrHXwEjgVOBJ22/lqNuAg0rpJNUTpqOA/6kw09QXeCW7rOxdCJ9jk+13\ngCmS9sh1KQtuPfoxdzH4vg2kD4Ig6K5cAPzO9qRqCSQNsP2I7aOAN4BVSd4SP8p6g6RPk7RjBUlb\n5rDFJK1fo+5lSJ2G6UprWb/RgL23AgdJc9b/bpzDR5Pf9ZLWIs1qPQ1MBQYprf1dleRGh6TlgUVs\nXwscSXK/K+d4koveZ3OexTV399q2aszDJDd4SF4cJUYDQ5XWiK0AbAuMaeCZ7J91GUmrSPqMpJWB\n921fBpxcpY1BEHQxMYPVzbH9mKSJJHePy4EbJE0CmoGncppxkq4i7bj3OvBohXI+kLQfya1h0Zzm\nHNsfShpB2sHv1bK8+wDnSjoG+Ji0NmoiMEvSBNJo32PMy1W5jOGFsIOBs3I7FiV1CA+s0eZq29T+\nhrSe4I38t9TRuxIYIelgUgdxb+BsSUcCi+X4ersRHk16Nm+TRja/UCf9HAau0o/mOBciCIJugu2X\nSF4PtThZ0pqkmZI7Se/IySQXvInZk2CE7TOVNkr6o6R+pHf46aSZoEp1T5D0GEmfXiS5Itbj97nM\niZIWIblo70jyrjg7a94nwPCsWQ/kNE+Q3OjH5XJWAS7MZUDa0KLcvn/kjt8duUNnUocU2q4xhwKX\nSTqCtDaqtPhpJMl9cEKu71fZW2Odag/E9m2S1gUeyv3OGcB/AWuQvrvZJF3+cbUySoRGBUHnozTp\nEARBa2lqanJzc3NXmxEEPRJJY/OGCEHQo8leHjNtW9JewDDbO9XL19GERgVB62mtRsUMVhAEQRAE\nQdsZDJyZZ8amMf/6ryAIFhKigxUEQRAEQdBG8o5+jaz5DYJgASc2uQiCIAiCIAiCIGgnooMVBEEQ\nBEEQBEHQTkQHKwiCIAiCIAiCoJ2o28HKZyv9WtI5+X4NSY2caxEEQRAEXU7oWBAEQdCZNLLJxQXA\nJGCbfP9v4Grg5o4yKgh6EpNenk7/w2/qajMCYGqc9RJUJnQsWGgJjeo+hEYtPDTiIrim7eNIB9ph\n+33SwYRBOyHpbklfKws7VNLZZfcf5IMei+k2k3SfpKclPSbp/HwWRyn+ekkPl+U5WtL7kj5TCJsh\naTlJ4/PnVUkvF+4Xr2D3IEmW9PWy8Fk5z2RJV5fZs3POs04hrL+kmTnPE5IukbSYpK8V6p+R2zg+\nx2+Xy/lBBXsOy/cXSZpSKOPBHD5c0mxJGxbyTs52PJLT/kvSG4W8/Wt9h0EQdGtarWOSZnSkYZKm\nSlq+Qvj+kiZJmpjfT+1ynpKkAyV9rz3KqlB28Z07TtKW7VTuMZJ2qBC+naQb21j2ZyVdKek5SWMl\n/UPSWm0ps059dW2W1CSp5kHRkpaV9JP2tS4IgvaikQ7WR5KWJJ0+jqQvAB91qFULH1cAe5WF7ZXD\nSwwDHgV2LQUonUZ/NfA/tte2vTHp9Pi+OX5Z0rkc/SStXlb+m8AvigG237I9yPYg4BzgtNK97Urf\n+TDg/vy3yMycZwPSv5UDG8jzXK53IPA5YE/btxbsaQb2zvelHweTgT3Lyp5QVu4vC23YqhD+EnBE\neYNsb57rOwq4qpB3aoX2B0HQM+hROibpc6T30za2NwS2ACa2IH9V7xTb59i+pO1WVuWX+R16OHBu\nS2yrhu2jbN/RVsPK687nVY0E7rE9wPZg4NfAim2tqy3YbrZ9cJ1kywLRwQqCbkojHaxjSD/aPyfp\nYuBu0gsoaD+uAb5VmiXKsyUrA6Pz/QCgD3Ak83ZMfgpcbPuhUoDta2y/lm93BW4ArmT+DtwFwFBJ\nn26NwVmY9gCGA1/JP14qMRpYI+fpQ3LR+X4Fe0r2zwLGAKs0YMYLwJKSVsz2fJ3GXX5uBNaXtHaD\n6YMg6Lm0q45JWkHStZIezZ+tC+G3S3pcyZvghdLslJI3wdgcd0CdKj4DvAvMALA9w/aUXM4ASbfk\nskaXvAHy7NE5kh4BTsozY8sWbH42vyuPLszyryHpDkkT8ozTgBz+y9yuiZJ+l8OWlnRTTjtZ0tA6\nbbiPue/+eySdLqkZOCR7C9yVy79T0ucl9cvPa5FCfS8qeTNcJGn3HP51SU9JGse8A45LS7pA0hgl\nb46dcvhwSaMk3QXcWWbj9sDHts8pBdieYHu0Eifntk4qtTfPQN0r6e+Snpd0gqS9c72TCs+w9H00\nS3pG0o7lD0jJA+WhbO+DJT1SYZYrf18X5Gf4vKRSx+sEYIDSbOHJdb6LIAg6mbodLNu3kH5I/5A0\n0rOZ7fKXVNAGbP+H1KkoLbreC/ibbRfuryR1VtZWmrkC2AAYW6PoYaRZsCuYf8ZoBqmTdUgrzd4K\nmGL7OeAeYD7H4jxa+A3S2geAnYBbbD8DvCVpcIU8SwKbk34MNcI1pH+fWwHjgA/L4k/WXDe/ywvh\ns4GTgP9tsJ5yOw/Iwtk86/3prSkiCIJOogN07AzSDP+mwG7A+Tn8t8BdttcnvZs+X8izf54haQIO\nlrRcjfInAK8BUyRdKOnbhbjzgINyWYcBfy7EfQ7YyvbPgb8DuwBI2hx4oTD4VuJy4CzbG5Heoa9I\n+iqwJrAZMAgYLGlb0gDWv21vlL0T6r2jv83cdz/A4rabbJ8C/Ik0OLhhtuGPtqcD44Ev5vQ7Arfa\n/rhUQNaHEbnswcBnC+UfQXr2m5E6TidLWjrHbQLsbvuLzEstDd01t38jYIdc3ko5biOSZ8a6wD7A\nWrne84GDCmX0Jz3HbwHnaP6ByKeAIdn75CjguCq2rAN8LZf1W0mLkWYIn8seFr8szxAaFQRdS6Pb\ntG8JbJ3/bt5x5izUFN0EK7kHXml7NnAt6YdCTXInbE3g/tyh+VjSBmXJ/gjsK6lvK+wdRur0kf8W\nO3C9JY0nufX9C/hLA3kG5DyvAa/YbtQd5m+k51HqTJZTdBHcuyzur8AWSu5CLcL2efnHQlOvpfrV\nzxAEQVfTnjq2A3BmfmeNApbR3Bn6K2FOp+7tQp6DJU0AHgZWJb2fK5Jn8r8O7A48A5yWZzL6kDpC\nV+e6zwVWKmS9OucFuAoozTLtle/nkN/7q9gemev8IK9N+2r+PEYatFon2zqJ5K1woqQhuUNUiZOz\nbQeQvBVKFOvfkvT+BbiUuZuP1LQ52zLF9rN5APKyQtxXgcNz3fcASzK3g3t7HshsCdsAV9ielTum\n9wKb5rhHbb9i+0PgOeC2HD6J1Kkq8Tfbs20/Czyf7S/Sj/RdTgZOA9avYstNtj+0/SbwOg24MIZG\nBUHXUtcXWtKfgPWY+8P4YElfacA/OGgZfyeJ6CbAUrbHAkgaSBK32yUBLA5MAc4EHieN4v29Qnl7\nAp8ijYACLEPqhMxZd2R7mqS/klwNG0ZSL9Ko7U6SjiAtFl9OUl/b75LXYJXl+TTwJWCgJAO9AEsq\njbw9Z3uQkjvNA5K+Y3tUPVtsvyrpY+ArpNm4repkKeb9RNIpwP80micIgp5HB+jYIsAWtj8oq6da\n/duROmVb2n5f0j2kDkBVcgdiDDBG0u3AhcCpwLTy92uB9wrXDwFrSFoB2Bk4tk6b5pgLHG+70vqp\nTYBvAsdKutP2MRXy/9L2NXVsq8Yo4LisF4OBuxq0uWT3brafLrN58xp1P07qxLaUoqfE7ML9bOb9\nXWXmpfz+98DdtndRWhpwTwP1zaKxHaCDIOhCGpnB2gHYwfYI2yNIo2pf6VizFj5szyCtC7iA+Wev\njrbdP39WBlaWtBqpk7VvFhAAJO2aZ6+GAV8v5SOJVaV1T6cCP6JlL+wvAxNtr5rLX400s7ZLjTy7\nA5faXi3nWZXUURxS9hzeJLk+tGR9xFGkjT5m1U05PxeR/o2v0Iq8QRD0DNpbx26j4AomqdTheYC8\n8U52tftUDu8HvJ07V+uQNq2oiqSVc2emxCCSi987pEGzPXI6SdqoUhm5gzaS9I5/0vZbZfHvAi9J\n2jmXtYTSjq+3Avvn2TIkrSLpM5JWBt63fRlwMsntrrU8yFw92pu83jjr4KMkF8wbK7zTnwL6l9Y5\nMa8XxK3AQcq9XEkbN2DHXcASKqyJk7ShpCHZpqGSeuVO6rakDm9L2EPSItne1YGny+L7AS/n6+Et\nLPtd8oZWQRB0Pxr5UT2F5Nf9Yr5fiTQlHrQ/V5AEsdgR2os0YlhkJLCX7RMl7QX8QWnL9dmkhcVP\nAauRXFEAsD1F0vRiZyyHvylpJPCzFtg5LNtQ5Frgx0C13amGASdWyFMp/Hrg6OyGMrqeMbYfrBF9\nsqQjC/ebleX9SGk73DPq1VONgav0oznOtgiC7kxbdGwpSS8V7k8FDgbOALlVpgAAIABJREFUkjSR\npKP3kdbk/A64QtI+pBmkV0k/hG8BDpT0JOlH9jxHZ1RgMdJ7fWXgA+AN5u7Gujdwdn6vLUaalSvf\nPbXEVaQOy/Aq8fsA50o6hrSF/R62b5O0LvBQ7qvMAP6LtGHFyZJm57Q/rtOGWhwEXJg9GN4A9iuz\n+Wpgu/JMtj/InaGbJL1P6gSVOhm/B04HJiptlDGFtI6rKrYtaRfgdEn/Q3rWU4FDSbvdbkl6tgZ+\nlT0myt38avEvUqdsGeDAbH8x/iTg4vxdtuigKttvSXoguxfeXGkdVonQqCDofDR3H4UqCdLOO5uR\nBMGkkbcxwHQA27tWzx0ECz5NTU1ubm7uajOCoEciaaztpg6uo1N0TNISwKzsfrwlcHYNd75gAUbS\nRaRZuErukp1KaFQQtJ7WalQjM1j/1wp7giAIgqC70Fk69nngb3kG5SPSroVBEATBQkYjHay1gL/W\n2DEoCIIgCLoznaJjebe4Rtb+BAs4tod3tQ1BEHQdjWxysRowTtJfJe3Q0QYFQRAEQTsTOhYEQRB0\nGo0cNHw4aZvwy0mLdJ+VdEzeUjQIgiAIujWhY0EQBEFn0tBBw/mA26n5M5u0A9PfJR3fYZYFQRAE\nQTsROhYEQRB0Fo0cNPxTYF/gHeAvwBG2P8yLeP9Jy84rCoIgCIJOJXQsCIIg6EyqdrAkLWr7E2Bl\nYJjtec4MsT1b0nc62sAg6O5Menk6/Q9v0REmQQcxNc56CQqEjgVBaFR3IjRq4aGWi+AYANtHlItS\nCduTO8SqbowkS7qscL+opDck3diGMo+ptfBaUlM+DLe15c+oEj5L0nhJkyVdLWmpFpY7VdLyFcJr\nHfzbkvK3y4cjj8+fO1pZzj8kLZuvZ+S/K0u6Jl8PklR+mHMQBD2f0LF2pKAZpU//tupToeyds76u\nUwjrnw/S7XJye6+sEV/VVkn3SGrK1/+QtGz+/KSQZo4mBUHQ86nVwVKNuIWZ94ANJPXO918BXm5L\ngbaPsl2182C72fbBbamjCjNtD7K9AenMlgMbzSipV7U421u1h3GZ0dnGQbZbtfuX7W/anlYW9m/b\nu+fbQUB0sIJgwSN0rH2ZWXgfD7I9tZo+SWrkGJgiw4D7899W0Yo6Gy13XaAXMETS0m0pq6BHywI/\nKYQXNSkIgh5OrQ7WCpJ+Xu3TaRZ2T/4BlOZ5hwFXlCIkHS3psML95Dyy1V/Sk5JGSHpc0m2lTpqk\niyTtnq83lfSgpAmSxkjqm2dybiyUf6mkh/JOWD/M4X0k3SlpnKRJknZqYZtGA2vksq6XNDbbeUCh\nLTMknSJpArBlIby3pJsLtpRmibbLI3fXSHpK0uWSlOO+mcPGSvpjS2YAJX1b0iOSHpN0h6QVC8/g\nwtz+iZJ2y+HzzbSVRhslLQ4cAwzNI5RD83NdIadbRNI/S/dBEPQoQsc6mCr69ABwqaRekk6W9Gh+\nJ/+oShl9gG2A7wN7VUnTX9LorHHjJG1VqH+0pFHAEzndU1lXn8m6s4OkB/K7fbNWNHMYcClwGzBH\nWyUNzlo9AfhpIby3pCuz5o8EehfiSnp0AjAg687JKsyASVqyoGWPSdo+hw+XdJ2kW3JbTmpFW4Ig\n6ARqdbB6AX2AvlU+CzNXAntJWhLYEHikwXxrAmfZXh+YBuxWjMw/9q8CDrG9EbADMLNCORsCXyJ1\nco6StDLwAbCL7U2A7YFTSp2ZeiiN+n0DmJSD9rc9GGgCDpa0XA5fGnjE9ka2789hfYAbgCtsj6hQ\n/MbAocB6wOrA1vm5nQt8I9dTq/MyRHPdUY7IYfcDW9jemPRd/CqH/waYbnug7Q2Bu+q13fZHwFHA\nVXlE9irgMmDvnGQHYILtN4r5JB0gqVlS86z34wzuIOimhI61L70L7+ORVdKsB+xgexipwzTd9qbA\npsAPJX2hQp6dgFtsPwO8JWlwhTSvA1/JGjcUKLolbkLSzbXy/RrAKcA6+fNdUgfuMOB/W9DeEkNJ\nWnMF886wXQgclPW6yI+B922vC/wWqNSew4Hnsu78sizup4BtD8z1XZx1E5LHxVBgIGlgcNVKBodG\nBUHXUms6/RXbx3SaJT0I2xOVzk8ZRprNapQptsfn67FA/7L4tUnP/dFczzsAFfpJf7c9E5gp6W5g\nM+Am4DhJ25K2IF4FWBF4tYY9vSWV7BlN2l0LUqdql3y9Kqlj+BYwC7i23BbgJNuXV6ljjO2XcjvG\n5zbPAJ63PSWnuQI4oHJ2RtvesSzsc8BVklYCFgdK5exAYfTT9ttVyqzHBaR2nQ7sTxLRebB9HnAe\nwBIrrelW1hMEQccSOta+zLQ9qE6aUVmfAL4KbKjsoQH0I+nJlLI8w4Az8vWV+X5sWZrFgDMlDSJp\n0VqFuDEFPYGktZMAJD0O3GnbkiYxv+7WRGnt1Ju2/yXpZeACSZ8m6eyytu/LSS8lDVQCbEvuAObf\nCxNbUiepM/innP8pSS8wt7132p6ebXuCdIj2i+UFhEYFQddSq4MVvuu1GQX8AdgOWK4Q/gnzzgwu\nWbj+sHA9i4LbQAspf1maNOOyAjDY9seSppbVXYn5xFLSdqSOypa235d0T6GcD2zPKivjAeDrkv5q\nu9JLvLzN7eEj/yfgVNujsr1Ht0OZc7D9oqTXJH2J1Hndu16eIAi6JaFjnc97hWuRZnhurZY4d1a+\nBAyUZNKsoyWVz+r8DHgN2IiksR9UqRPm1Z3ZhfvZVNAgSReSvC3+bbt8Pe4wYJ2sqQDLkLxPrq7W\npg6mIzQ1CIJ2ppaL4Jc7zYqeyQXA70qjZAWmktwVkLQJUMkdohpPAytJ2jTn76vKi3Z3yj7ay5E6\neI+SRgZfz52r7UmjWq2hH/B27lytA2xRJ/1RwNvAWS2o42lg9TwLCMndoaU2ljYW2bcQfjvz+sF/\nqsHy3mV+d6HzSa6CV1foVAZB0DMIHetabgV+LGkxAElraf5NInYHLrW9mu3+tlclzXANKUvXjzQj\nORvYh9QRaxds75dd9ebpXCmdk7YnMDDb1p/kzjgsb1QxTdI2OXlxIO4+klsikjYgufWXU0l3Sowu\nlSdpLeDzJN0MgqCHUHXkw/Z/OtOQnkZ2e6u0Ne21wPeyW8IjwDMtKPMjSUOBPyltgDGTNJtUzkTg\nbmB54Pe2/y3pcuCG7ALRDDzVogbN5RbgQElPkl7oDzeQ5xCS28RJtn9VL7HtmUrb094i6T1SB7El\nHA1cLelt0jqrUif2WOCsvFB4FvA74LoGyrsbODy7MB6f12GNIrkGzuceWM7AVfrRHGdbBEG3I3Ss\nyzmf5JI3Lq8JfgPYuSzNMODEsrBrK4T/GbhW0vdIOlU+a9URDAFetv3vQth9wHrZRX0/kvaZtAFG\nibOBC7OOPsn87o7YfitvvDEZuJl5Byn/DJyd9fwTYHg+GLtVjQiNCoLOR5W9uoLuiqSjgRm2/9DV\ntrQFSX1sz8iiexbwrO3TutquEtnv/jTb5aOo89HU1OTm5uZOsCoIFjwkjbXd1NV2BMGCSmhUELSe\n1mpULRfBUsHlI0sVw4Kghfwwzxg9TnL9OLeL7ZmDpMNJI6i/7mpbgiBoO6FjQRAEQWdSt4NFOki3\nnG9UCAs6AdtH9/TZKwDbp2Wf9/Vs7237/a62qYTtE/J6gPvrpw6CoAcQOhYEQRB0GlXXYEn6MemU\n8dXLthjtS9o5LgiCIAi6LaFjQRAEQVdQa3vPv5IWXh5POhCvxLuxcDgIgiDoAYSOBUEQBJ1OrV0E\npwPTgWGSepEOrV0U6JM3KPhXJ9kYBEEQBC0mdCwIgiDoCuoeUCfpv0nbYr9GOqQP0sG2lc51CIIg\nCIJuRehYEARB0Jk0cgL4ocDatt/qaGOCoCcy6eXp9D/8pq42IwCmxlkvQWVCx4KFltCo7kNo1MJD\nI7sIvkhysWgRko6Q9LikiZLGS9q85ebVLP8fkpatk2aqpOWrhF9buN9d0kV1yhok6Zu10rQUSffk\n85YqxS0v6WNJB7ZnnWV1DJf0hqTHJD0r6VZJWxXij5FU6aDjUvzOktarEX9gPhSyWnx/Sd+tEb+S\npBvz9VKSLpc0SdJkSfdL6pPjLOmUQr7D8nlhxbLGS7qyLOwiSVMkTZD0jKRLJH2uEH+HpE9Vsy8I\ngh5Dq3SspyNpRtn9cEln5uua7+fy9J2JpC0kPZLf20+W3ueSvpOP0ejo+qdmrZkk6QlJx0pasgPq\n2a6gcZ3StiAIOodGZrCeB+6RdBPwYSnQ9qnVMkjaEtgR2CSfPr48sHhbjS1iu62dncGS1rP9RIPp\nBwFNwD8arSAfoivbs+smnp89gIdJp9mfU6X8XrZntaLsIlfZ/u9c3vbAdZK2t/2k7aPq5N0ZuBGY\n7xlKWtR2RbsL9Ae+S1qIXomfAyPy9SHAa7YH5vLXBj7OcR8Cu0o63vabFWxZF+gFDJG0tO33CtG/\ntH1N/q4OBe6StIHtj4BLSTuQ/V+ddgRB0L1psY4t6DTwfu5KLgb2tD0hr51bG8D2KGBUJ9mwve03\n80DeeaSzGvftqMo6uW1BEHQwjcxg/Qu4ndRB6lv41GIl4E3bHwLYftP2v2HOyNBJeWRojKQ1cvgK\nkq6V9Gj+bJ3D+0i6MKefKGm3QjnL5+vrJY3NM2YHNNj2U4AjygMlbSbpoTyr86CktSUtDhwDDM0j\nakMlHS3psEK+yXlGpr+kpyVdAkwGVpV0tqTmbN/vGrRvGPALYJWyWZUZkk6RNAHYUtJgSffm9t8q\naaWc7of5OU7Iz3WpehXavpskJAfkMi6StHu+PiGP5E2U9Aelma7vACfnZzJAaUbudEnNwCHFZyRp\njTwjNEHSOEkDgBNInZ7xkn5WwaTdgFvy9UrAywVbny79+wI+yXZXKqP0LC8FbgN2qtJ22z4NeJW5\n5+OMynmDIOjZtEbHFmjK3s+baq63ycmSJheSrizpFiUvh5Ny+j0knZqvD5H0fL5eXdID+fqorEGT\nJZ2nxABJ4wo2rFm8L/AZ4BUA27NKA6GadwZugKSH82+DY5Vn65Rmhe6RdI2kp5Q8H9Ta52R7BnAg\nsLOkT+ffJHdmHZskaadcb3+l2bYRWetvk9S7gedbehbFtl0k6Y/5N8jzBR1eRNKfc7tuV/Lk2b21\nbQuCoOOoO4Nlu9EOQZHbgKMkPQPcQZolubcQP932QCX3hNNJs11nAKfZvl/S54FbgXWB35TSA6iy\ny9b+tv+TX2aPSrq2AV/7vwE/Ue7gFXgKGGL7EyX3uONs7ybpKKCpMNtzdI2y1wT2tf1wTntEtq8X\ncKekDW1PrJZZ0qrASrbHSPobMJTUIQRYGnjE9i8kLQbcC+xk+w1JQ0mzLfsD19kekcs7Fvg+8Kc6\nzwRgHPCjMnuWA3YB1rFtScvaniZpFHCj7WtyOoDFbTdVeEaXAyfYHqnkarEIadvkw2zvWOEZfAF4\nu9CJugC4LYvJncDFtp8tZDkLmFj6AVDGUNJBo+sAB1F9xqzU/nWAv9t+W9ISkpYr//ek1JE/AKDX\nMivUKC4Igq6mlTq2INBb0vjC/aepPEtyIfBD2w9JOqEsbhCwMWnm72lJfwJGA7/K8UOAtyStkq/v\ny+Fn2j4GQNKlwI62b5A0XdIg2+OB/XLd5ZyW67qHNMh2se0PytKcAZxh+wrN70q/MbA+8G/SeWdb\nA60+ON72O5KmkLR9LLBLDlseeDhrITl+mO0fZu3eDbiM2s+3GisB25D0aBRwDbAryfNjPVIn9EmS\nNs5HaFQQdC1VZ7AknZ7/3iBpVPmnVqF5xGcw6T/3G8BVkoYXklxR+Ltlvt4BODOLwShgGaWp+R1I\nP55LZb9docqDlWZ0HgZWJb3k6jELOBn4dVl4P+DqPMJ0Gukl3VJeKHWuMnvmUbrHcnlV1y1lhpI6\ngABXMu8syiygtH5sbWAD4Pb83I4ESrNdG0gaLWkSsHcL2lFppG868AHwF0m7Au/XyH/VfAVKfYFV\nbI8EsP2B7VplQBKXN0o3WYxXJ31nnyZ1pNctxL8DXAIcXFZ3E2k29V+kjtnGkj5do97y9r8OrFye\nyPZ5tptsN/Vaql+dpgRB0BW0RccWEGbaHlT6APO5fSutZe5r+6EcVD4Adaft6bmD8wSwmu1XSVvd\n9yVp7l+BbUkdrNE53/ZK66gmAV9irgadD+yXBxyHVqiP3DFrIg3Wfpe5ngxFtgSurmLzGNsvZff8\n8aROSVtR4e9xSgdX3wGsQtr+H2BK1ipIHbH+DTzfalxve3aevSuVvw1wdQ5/Fbi7WubQqCDoWmrN\nYF2a//6hNQXntUH3kPzeJ5F8ly8qRReT5r+LAFuUj1LVm9mXtB2pE7al7ffziFeji1EvJXWwitP1\nvwfutr2LpP65DZX4hHk7qMU656zxyTMxhwGb5hmRixqwbxjwWUl75/uVJa2ZZ2w+KKy7EvC47S0r\nlHERsHP2YR8ObFenzhIbk0bF5pBn8zYDvgzsDvw3STAr8V6V8JYyk7LnlDvu15HWic0Gvllm6+mk\nGajiiOgwYB1JU/P9MqRRxRFUZmNSR6zEktmWIAh6Hm3SsQAorFkjDfCVfjc8SJqBeprUqdqf1On5\nRfZS+DPJ6+PF7M1Qep9fC/wWuAsYW83bxPZzwNmSRgBvZE+KttoMzPESuSHfnlNvPVruSPYHniEN\nWK4ADLb9cdaWUtvK6+3dApvLKZbVahfHIAi6hqozWLbH5r/3VvrUKlRp3VJxFmkQ8ELhfmjhb2lU\n5zaS+1apjEH58nbgp4XwchfBfiRXsvclrQNsUcu2IrY/Js1SFdfu9GPuWp/hhfB3mddnfyqwSbZp\nE+ALVapZhtTpmC5pReau76mIpLWAPrZXsd3fdn/geCqvBXoaWEFpUxEkLSapNErYF3gluxHuXSFv\npbq/SJp1HFEW3gfoZ/sfpGe1UY4qfyYVsf0u8JKknXN5SyitCauV/xkKo46Sti5990pr4tZj3n9T\n2P4Paebv+zndIsCewMDCs9yJCs9SiYNJM2e3lMKAz5K+6yAIehht0bGFBdvTgHc1d6ffvRrMOpo0\neHgfyTtje+BDp8OdSx2O0iYRc9YJ5UHUW4GzqeweiKRvae7o6pqkzsq0smQPkwbLWmJzyYYXCzN7\n9TpXfUidxeuzB00/4PXcudoeWK1OXa19vpV4ANhNaS3WijQ+cBoEQSfTyEHDa5J+4K9HYUbB9uo1\nsvUB/pSnxj8B/kn2Bc58Kk+vf8jcH7sHA2fl8EVJL+0DgWNz+GTSS/Z3pFmMErcAB0p6ktThKLrm\nNcJfSK51JU4CLpZ0JFA8OOJu4PDsinc8aRTue5IeBx4hdQjmI88gPUZa2/Ui6QVZi2HAyLKwa0mu\nd8eUlf1RXpP0R0n9SM/tdOBx0tq1R0hudo9QvSMzVNI2wFLAFGA320+WpekL/D2PSoq0ux8k98UR\nuWNSb6HtPsC5ko4h7f63BzARmJXdOy9y2mSi1Lb3JD0naQ3b/wQGkEYzRRoYuIm5rpJFTiHNsEFy\nV3nZeYOVzH3AesqbgZA26fhNbv/DpJ2jPspxg4GHbX9Sq2EDV+lHc5xtEQTdllbq2MLE90nv8tmk\ndb2NbGk/muQeeJ/tWZJeJOkceY3uCJJ3yKvAo2V5Lyet672tStn7AKdJep/0G2LvXEcxzaHAZZKO\nIP0OaO9t+O8u6M1IkndLyfYbsmdOM7nNdWjN863EtSRPkidIvyfGNVJWaFQQdD6yXTuBdD9pOv80\n4Nskl4BFXH8L72rlTSW5Dcy3nXYQFJG0C8kN48i6iTum/jOAUbbvrJWuqanJzc3NnWRVECxYSBpb\n2hinA+toVx1b0JDUJ7tgo3QW00q2D+nA+g4jeUX8pg1lLEVaY2ZJe5E2l6i4S2xX057Pt1RWdpkc\nA2yd12NVJTQqCFpPazWqkXOwetu+U5JsvwAcLWksFRbLBkF74rTjYEv87tubyfU6V0EQ9AhCx2rz\nLUm/Jv0meIF53ePbFUkjSR4J1dbxNspg0sZYIrkP7t9W2zqQ9ny+N2bvoMWB39frXAVB0DU00sH6\nMK9leVbSf5PWJ/VpbYV5HUwQNITt87uw7mobYQRB0LNoVx1b0LB9FRV2gO2gunZpp3JGM3c9cLem\nPZ+v7e3ao5wgCDqWRg4aPoS0PuVg0ojRPnTgaeZBEARB0M6EjgVBEASdRiMHDZcWp84g+a0HQRAE\nQY8hdCwIgiDoTKp2sCTdwLznVc2D7e90iEVBEARB0A6EjgVBEARdQa0ZrDiYMQiCIOjJhI4FQRAE\nnU7VDlbxEMZ8sOs6pJHApwvnBAXBQs+kl6fT//Cb6icMOpypcdZLUCB0LAhCo7oToVELD3U3uZD0\nLeA54I/AmcA/JX2jow3rzkiaUXY/XNKZ+fpASd+rk39O+s5E0haSHpE0XtKTko7O4d/JZ3N0dP1T\nJU3KnyckHZsPL+62SNpO0o1dbUcQBK0ndKwyoWWtrn+qpNFlYeMlTc7XTZL+2Ipy/5G3YA+CoIfT\nyDbtpwDb2/4ngKQBwE3AzR1pWE/F9jldbUMNLgb2tD1BUi9gbQDbo4BRnWTD9rbflNQHOA84l9jN\nKwiCjiV0rIWEltWlr6RVbb8oad1ihO1moMUn+9r+ZrtZFwRBl9LINu3vlkQp8zzwbgfZ0+ORdHQ+\npR5Jm0qamEe2Ti6NbmVWlnSLpGclnZTT7yHp1Hx9iKTn8/Xqkh7I10dJelTSZEnnKTFA0riCDWsW\n7wt8BngFwPYs20/k9MVRywGSHs6zTMeWRjjzTM49kq6R9JSky/MBj60in2p/ILCzpE9L6iPpTknj\nct075Xr75/oukvRMrncHSQ/kZ7dZTreZpIckPSbpQUlr5/ClJP0tz5iNzKOeTTnuqznPOElX504f\nkr6e6xwH7NraNgZB0G0IHWshoWV1+RswNF8PA64o2D3H80HSF/NzG5/1qa+klSTdl8MmSxqS006V\ntHzWvScljZD0uKTbJPVu4LsIgqCb0EgHq1lp2nq4pH2BG4BHJe0qaWH98dm78MIcDxxTJd2FwI9s\nDwJmlcUNIr2cBwJDJa0KjAaG5PghwFuSVsnX9+XwM21vansDoDewo+3ngOmSBuU0++W6yzkNeDp3\nNH6kyu55ZwBn2B4IvFQWtzFwKLAesDqwdZV2N4Ttd4ApwJrAB8AutjcBtgdOKYjeGqQR6HXy57vA\nNsBhwP/mNE8BQ2xvDBwFHJfDfwK8bXs94DekM3CQtDxwJLBDrrMZ+Hl+JiOAb+e0n61ku6QDJDVL\nap71/vS2PIYgCDqe0LHKhJa1XsuuZe4A3LdJ/6YqcRjw0/zshgAzSRp2aw7bCBhfId+awFm21wem\nAbvl8FrfxRxCo4Kga2mkg7Uk8BrwRWA74A3Sy/DbwI4dZln3ZqbtQaUP6Qf9PCj5Ufe1/VAO+mtZ\nkjttT7f9AfAEsJrtV4E+kvoCq+Y825JeyiV/7+3zLMwk4EvA+jn8fGA/JXeJoRXqw/YxQBNwG+kF\nf0uFtm0JXF3F5jG2X7I9myQI/Svkbykq/D1O0kTgDmAVYMUcN8X2pFzv46RnZ2BSwYZ+wNV5NO80\n5j6XbYArAWxPBibm8C1I4vpA/mGxL7AaqQM3xfazuY7LKhlt+zzbTbabei3Vr63PIAiCjiV0rDKh\nZa3XsreAtyXtBTwJvF8l3QPAqZIOBpa1/QnwKKmNRwMDbVeaTZ1iu9TxGgv0b+C7mENoVBB0LY0c\nNByHMnYMHxauZzH3u3iQNGr3NEmI9icJxS/yKN2fgabs93006YcDpNG03wJ3AWNtv1Wp0jxCeLak\nEcAbkpZrB5sByCOXpVG8c+r58Gfx7Q88A+wNrAAMtv2xpKnMbVux3tmF+9kFG34P3G17F0n9gXvq\ntEXA7baHldk0qEr6IAh6KKFjHcrCrGVXAWcBw6tVZPsESTcB3yQN6H3N9n2StgW+BVwk6VTbl9Sx\nsXedNgVB0I1oZBfBL0g6VdJ1kkaVPp1hXE/G9jTgXUmb56C9Gsw6muRScB/wGMld7kPb05krQKVN\nInYv1PcBcCtwNpVdKpD0rYLb3Zqkl/a0smQPM9cVoVGbSza8WBgNrde56kMS2Ottv02agXo9d662\nJ80mtYR+wMv5engh/AFgz1zneiQ3Fkjt3FrSGjluaUlrkVwN+ystgofkWx8EQQ8mdKz1hJbV1LKR\nwEnZ3opIGpA9ME4kzVytI2k14DXbI0gzdps0aFdrv4sgCDqZRnYRvB74C2k0Z3bHmrPA8X1ghKTZ\nwL1AI47Qo0kuFffZniXpRdKPfmxPy6N1k4FXSS/rIpcDu5DcJiqxD3CapPeBT4C9cx3FNIcCl0k6\nguR20d7O23dnYVyEJE6/L9h+Q3YXaSa3uQWcBFws6UjS7mAl/pzDn8hlPg5Mt/2GpOHAFZKWyGmP\ntP2MpAOAm/JzGg30rVXxwFX60RxnWwRBdyZ0rG2EllUgu/adCKDq+2QcmgcNSy7uN5M6Rr+U9DEw\nA6i5HX4ZLf4uQqOCoPNRWmZSI4H0iO3NayYKKiKpT94tD6WzOVayfUgH1ncY0M/2b9pQxlIkv3xn\n3/JhtndqNyM7mezHv5jtD/Ks1B3A2m7HQ0abmprc3NziHXmDIAAkjbXd1MF1hI61gdCy7kNrvovQ\nqCBoPa3VqEZmsM6Q9FvSSNIcn2DblbZODeblW5J+TXrOL1DDT7utSBoJDCAtFm4Lg4Ez8yzTNJLf\nfE9mKdKs2WKkdVc/ac/OVRAEPYLQsbYRWtZ96LTvIgiC1tPIDNbxpOn455jrWmHbbX35BcECQYwO\nBkHr6aQZrNCxYKElNCoIWk9HzmDtAaweo/5BEARBDyV0LAiCIOg0GjkHazKwbEcbEgRBEAQdROhY\nEARB0Gk0MoO1LPCUpEeZ13f9Ox1mVRAEQRC0H6FjQRAEQafRSAfrtx1uRRAEQRB0HKFjQRAEQadR\nt4Nl+15JKwKb5qAxtl/vWLOCoOcw6eXp9D/8pvoJgw5napz1ElS86w32AAAgAElEQVQgdCxYmAmN\n6j6ERi081F2DJWlPYAxpkfCewCOSdq+dqz6SlpM0Pn9elfRy4X7xtpbfEUj6uaQlW5pO0q2Sah5W\n22D9xxae0yRJ7fI/VdJPJe1dIXwNSePbWPYykkZIek7SWEl3S9q0fs5W11fXZkmrSrqqTppF8hkj\nQRD0cFqqY6FPrao/9Kl+faFPQbCQ0IiL4BHApqXRPkkrkA5rvaYtFdt+CxiUyzwamGH7D8U0+fwK\n2Z49fwmdSz6w9ufABcAHdZLPk87219rRlJNtny5pA9L5Tp9xYa99SYva/qQlBdo+qz0Mq1L3BcCT\nwBr5wMcBwFrtUV9rsf0iMLROskWAw4ETOt6iIAg6mBbpWOhTqwl9aiOhT0GwYNDILoKLlLlSvNVg\nvlaRR3iekHQ58DiwkqTzJDVLelzSUYW0L0k6WtJjkiZKWiuHf0nShDySNk7S0pJ2yKNTN0t6WtJZ\nWSCR9F95xG2ypONy2KKSpkk6XdJE4FfAZ4DRku7IaeazS9LPKqR7SdKy+fpXuZ7Jkg4qtHmypL/k\nsm6uNxJpezLp4NxPSbpM0tmSxgDHSVpe0qj8TB6UtIGkXpJekLRMrlOSns9pj5V0aA7fNOcbDxxY\neNaLSjpV0pgc/4McvoOkeyTdCEwq+y7XJv1I+W1JZG0/Z/vmBp7FpZKekXSJpK/ldjwrqSmnO1bS\nxZIezuHzHSIpaYCk0fnfx1hJmxfqGJ+vfyDpGqVR3GeVzsuBJFx987+hS2p9F0EQdHvaRcdCn0Kf\nQp+CIGiERmawbpF0K3BFvh8K3NxxJgGwDvA9280Akg63/R9Ji5JGxa6x/URO+5rtjSUdTBqZOxD4\nJXCA7Uck9WHuiN7mwHrAi8DtwE6SmoFjgSZgOnCHpB2BW4B+wH22Sy/3nwJDbE/L5VWy6zRJvyhL\nR86/ObA3aR3AosAYSfcAM4G1gWG2J0m6DtgZuLLaA5K0FfBBrh9gJWAL27MlnQ08Yvs7kr4KXGS7\nKYvMTsClwFbAM7bfzPlLXJSf3QOSTiuEHwC8bnszSUsAD0u6Lcc1AevZ/leZmesDj1Ua4W3gWewJ\nPAWMy+3cStJupFG7kmvPwNyOZYBxksqdzF8BvmL7A0nrABeT/g2UsxEwGPgYeEbSn3I9P7A9qEJ6\nJB2Qnwm9llmhUpIgCLoP7aljoU+hT91an3IbQqOCoAupO4Jn+5fAucCG+XOe7V91sF3PlcQrM0zS\nONLLbF2SCJW4Lv8dC/TP1w8AZ+RRp2Vsz8rhD9uemu+vBLYhvdDusv2m7Y+BvwLb5vQfASNr2FnL\nrkpsA1xre6btd4HrgSE57p+2SyNsxbaU88s8unUi87oRXF0Qim1IIoXt24CVJS0NXFXIs1e+n4Ok\n5YHeth/IQZcWor8K7JfrfoS07fGaOe6hCuJVj3rP4oncnieAO3P4JOZ9Ltfb/iCPTN/H3AXsJZYA\n/iJpMun7rvb93GH7HdszSaL5+XrG2z7PdpPtpl5L9avb2CAIuo521rHQp9Cnbq1PEBoVBF1N1Rks\nSWsAK9p+wPZ1ZKGQtI2kAbaf60C73ivYsSZwCLCZ7WmSLgOK7gmlM01mkdtj+1hJo4BvkUayvpzT\nmHkpvy9nZtF/vEgDdrWUDwvXc9pSgZNtn14h/L0KYeWMBi6StBzwHeA3LbBPwE9s3zlPoLRDjbof\nBwZJWqTSKGENis9iduF+NvM+l3rf5y9Io8H/BSwGzGigvlrPPgiCHkQH6VjoU+hTidCnIAgqUmsG\n63TgnQrh03NcZ7EM8C7wjqSVgLoLcrNwTrR9PGn0bu0ctYWkzystCN4TuJ802rW90q5Ri5JGzu6t\nUvS7QGm3pVp2FdMVGQ3sIql3dg3ZKYe1N6NJ7g0lgXnZ9ntZjP9O+v4mlLuI2H4TmClpyxxU3Lnp\nVuAn+RkhaW1JvWsZYftp0qjeUdKc9QRfkPQN2udZ7CxpCaUF60OA5rL4fsArud37kkS4IZwXQ5fa\nGwRBj6SjdSz0qeWEPiVCn4JgAabWf84VCy4Bc8g+2P07zKL5GUeahn8KeIHkXlGPwyQNIY0oTQRu\nI7lVjAHOAQaQdpAaZduSfgPcQ3rB3WD7piovrvNIPvAvAl+pYdecdLZ3KAXaHiPpCuDRHHR2fp5r\nNNCmlnAUcIHS4ucZwH6FuKuAh0ijZpXYDzhf0mzSOoAS55JcE8ZnLXqdJDr12A84FfinpJnAG8Bh\ntse2w7OYTPqxsRxpofJrmne74TOBa5QWGN/EvCOBjfAXYKKkZtvfq5Zo4Cr9aI6zLYKgO9LROhb6\n1HJCnxKdok8QGhUEXYGqeBgg6Vnba1aJ+6ft9n7pdih5pOy/be/c1bYEbUfSscCbVdxROpWmpiY3\nN5cPTgZB0AiSxtpu6qCye4SOhT4tWHQnfYLQqCBoC63VqFougs2Sflihoh+QFrkGQRAEQXcmdCwI\ngiDodGq5CB4KjFQ6Qb0kRE3A4sAuHW1Ye2P7DpLbRbAAYPvIrrYhCIJuT4/QsdCnBYvQpyAIqnaw\nbL8GbCVpe2CDHHyT7bs6xbIgCIIgaAOhY0EQBEFXUHcHGtt3A3d3gi1BEARB0O6EjgVBEASdSd2D\nhoMgCIIgCIIgCILGiA5WEARBEARBEARBOxGH1AVBG5n08nT6H35TV5sRAFPjrJcgCIJ5CI3qPoRG\nLTzEDFbQLZC0nKTx+fOqpJcL94u3Ux2rSrqqPcoKgiAIFh4k7SzJktYphK0p6UZJz0kaK+luSdvm\nuOGS3ijo2HhJ60nqn8s5qFDOmZKGF+4Pk/RUzvOopO9J+j9JJxbSrCbpeUnLdtIjCIKgBUQHK+gW\n2H7L9iDbg4BzgNNK97Y/aqc6XrQ9tD3KCoIgCBYqhgH3579IWhK4CTjP9gDbg4GDgNULea4q6Ngg\n20/k8NeBQyoNHko6EPgKsFnWwy8DAo4Fdpa0bk56BvAb29PavaVBELSZ6GAF3R5JN+TRwcfzAaFI\nWlTSNEknSJog6SFJn8lxl0k6Q9KDeYRvlxy+hqTx+foHkq6RdKukZyUdX6jvR5KekfSIpPMlnd4V\n7Q6CIAi6Hkl9gG2A7wN75eC9gYdsjyqlsz3Z9kUNFPkGcCewb4W4/wV+bPudXOY7ti+2PRP4GXCW\npG8CfW1f3to2BUHQsUQHK+gJ7JtHBzcFfi7pUzm8H3Cv7Y2Ah4D9C3k+A2wN7AwcT2U2AvYANgT+\nS9LKklYFDgc2B4YA61XKKOkASc2Smme9P71trQuCIAi6MzsBt9h+BnhL0mBgfWBcnXxDy1wEexfi\nTgQOk9SrFCBpGVLH6flKhdn+B/A2cDHwk1oVh0YFQdcSHaygJ/AzSRNInajPAQNy+EzbN+frsUD/\nQp7rnZgIrFKl3Dvy6OBM4Cng86SO1V22386uiddUymj7PNtNtpt6LdWvTY0LgiAIujXDgCvz9ZX5\nfh4kjZQ0WdJ1heByF8GZpYjciXoE+G4LbTkLeNT207UShUYFQdcSuwgG3RpJOwDbAlvYninpfmDJ\nHF1cmzWLef89f1gspkrxxTTl+YMgCIKFHEmfBr4EDJRkoBdg4HckbQLA9i6SmoA/tKD440iDePfm\nMt6RNEPS6tVmsYDZ+RMEQTcmZrCC7k4/4D+5c7U+yU2wIxkDbC9pWUmLAbt2cH1BEARB92V34FLb\nq9nub3tVYArwT2BrSd8ppF2qJQXbfgp4Avh2Ifh40jqrZSCt/5L0vTa1IAiCTidG7IPuzk3AAZKe\nAJ4muVR0GLb/Jelk4FHgP7nOmg7sA1fpR3OcbREEQbAgMoy0XqrItaTNLnYETs0bIb0GvEva7a/E\nUEnbFO5/Avy7rKz/Ax4r3J8N9AEelfQx8DFwSlsaEBoVBJ2PbHe1DUHQrZDUx/aMPIP1d+Bs2zdU\nS9/U1OTm5ubOMzAIFiAkjbXd1NV2BMGCSmhUELSe1mpUuAgGwfz8XtJjwETSDNaNXWxPEARBEARB\n0EMIF8EgKMP2z7rahiAIgiAIgqBnEjNYQRAEQRAEQRAE7UR0sIIgCIIgCIIgCNqJ6GAFQRAEQRAE\nQRC0E9HBCoIgCIIgCIIgaCdik4sgaCOTXp5O/8Nv6moz2szUOCclCIJggWNB0KjQp6CnETNYPRhJ\nsySNlzRB0jhJWzWQ53xJ6+XrqZKWr5DmaEmH5etjJO3QTvb2kXSupOckjZV0j6TN26Hc/pIm5+sm\nSX/M19sVn4mkAyV9r631BUEQBB1LQd9Kn/4dXN+MOnZMlnS1pKU60o4K9c+jY0EQ9AxiBqtnM9P2\nIABJXwOOB75YK4PtH7SkAttHtd68+TgfmAKsaXu2pC8A67Vj+dhuBkonKm4HzAAezHHntGddQRAE\nQYcxR9+6mKLOXg4cCJxaipQkQLZnt3fFkhalTMeCIOgZxAzWgsMywNswZ8RrzuG4ks6UNDxf3yNp\nvhOpJR0h6RlJ9wNrF8IvkrR7vp4q6Xd5tmySpHVy+AqSbpf0eJ4he6F8ZkzSAGBz4MiSENmeYvum\nHP/zPEI4WdKhOay/pCcljchl3yapd44bnGfuJgA/LdSznaQb82jngcDP8ujjkLKZuUGSHpY0UdJI\nSZ8qPJ8TJY3Jz2NI67+SIAiCoL2QtKSkC7P+PCZp+xw+XNKZhXQ3StouX8+Q9H9ZLx6WtGIO/4Kk\nh3JZxzZowmhgjaxNT0u6BJgMrCppWC5rsqQTC7bMkHRa1rA7Ja2QwwdIuiV7c4wu6OlFks6R9Ajw\nN+bXsSmSFstplyneB0HQfYgOVs+md37pPkWaHfp9awqRNBjYCxgEfBPYtEbyN21vApwNHJbDfgvc\nZXt94Brg8xXyrQ+Mtz2rSv37kTpgWwA/lLRxjl4TOCuXPQ3YLYdfCBxke6NKRtqeCpwDnGZ7kO3R\nZUkuAf7H9obApNyGEova3gw4tCy8aPMBkpolNc96f3qlJEEQBEHrKenbeEkjc9hPAdseCAwDLpa0\nZJ1ylgYezlpxH/DDHH4GcHYu65V6xuTZpG+Q9AKSNv05a9PHwInAl0g6uqmknQv1N+d09zJXU84j\nadhgkpb+uVDd54CtbO/K/Dp2D1BakLQXcJ3tjyvYGxoVBF1IdLB6NjPzS3cd4OvAJdldoaUMAUba\nft/2O8CoGmmvy3/HAv3z9TbAlQC2byHPpLWAbXL979mekesozRxNsT2+WKekZYFlbd+Xwy9tSWWS\n+uX89+agi4FtC0kqtXEebJ9nu8l2U6+l+rWk+iAIgqA+JX0bZHuXHLYNcBmA7aeAF4C16pTzEVDy\n6Ci+07cGrsjXtTSkt6TxJNfzfwF/yeEv2H44X28K3GP7DdufAJczV1NmA1fl68uAbST1AbYCrs5l\nnwusVKjz6kqDkZnzSQOS5L8XVkoUGhUEXUuswVpAsP1QdstbAfiEeTvP9Ub4WsKH+e8sWvbv53Fg\nI0m9aghHrfpKdfZuQd7W0to2BkEQBJ1PLc372Lbzdfk73dRnvrVgeRzzvVbYWapzEWBajTVmVcu2\n/UB2UdwO6GV7civtCIKgA4kZrAWE7L/dC3iLNKq3nqQl8mzPl+tkvw/YWVJvSX2Bb7ew+geAPbMd\nXwU+VZ7A9nOkEcDflWbZskh8i+TXvrOkpSQtDeySwypiexowTdI2OWjvKknfBfpWyD8deLuwvmof\nkutGEARB0H0ZTX7fS1qL5I7+NDAVGCRpEUmrAps1UNYDJBc7qK4hjTIG+KKk5SX1IrkvljRlEWD3\nfP1d4P7sKTJF0h65LZJU0d2dyjp2CfBXqsxeBUHQ9cTofM+m5LoAIGDfPDv0oqS/kRbfTgEeq1WI\n7XGSrgL+n707j7OjqtM//nkIWyAhjIKIAY1GFpEMkTSyCQZFBFFABQERAUXEUUAUnPgDERkdF1RU\n9mUgzoCIbBpAAUGBsIV0ICurQhAQZI8EQoTw/P6o06Robq/p5HY6z/v1uq/UPXXq1LfuTe7Jt86p\nqmnA48DkHsbxHeB8SfsCtwCPUXUK7R0I/AT4i6R5wJPAkWX/46k6KYCzbN+hzm/LewBwtiQDV3dQ\n5zLgIkm7Aoe0W7cfcJqqW+7ez8IpFz02avgwWvOMjoiIxe0U4FRJM6hGrfa3PV/STVR93Z3AXcDt\n3WjrMOBXkv4T+N2iBGX7UUnjgD9T9cVX2G5r83ngvZKOpupf9yzl+5RjORpYgWqa/bQGzb+mHyvX\nYZ0HfJeFUxw7lT4qYsnTwpHziN6RtBKwwPbLkrakunC4P9xed4loaWlxa2tr1xUj4nUkTbH9ujub\nRgwEkubaHtLHbe4O7Gp73+7UTx8V0Xu97aMyghV94a3AbyQtR3VB8Re6qB8RERE9JOlEqrsZfqTZ\nsUREx5JgxSKzfR/wni4rRkRELEP6evTKdvvp7hHRD+UmFxEREREREX0kCVZEREREREQfSYIVERER\nERHRR5JgRURERERE9JHc5CJiEc14ZA4jxl3R7DAW2ew8JyUiYsAZCH1U+qdY2mQEazGSNLfd+/0l\nnVSWD5b02S62f7X+kiRpC0mTJE2VdJekY0v5LuVhiot7/7MlTWxXNlXSzLLcIukXvWj395JW76s4\nIyLi9dr3faXs1T6v9G1v6cP9jZW0VV+116D96yTdI2mapMmSmv6cx77+DCOib2UEq0lsn9bsGDrx\nS+BTtqdJGgRsAGB7AjBhCcUwVNK6th+S9K76CtutQI+fmmg7zw2JiGiCdn3e/sBM4O/d3V7S8rZf\n7mD1WGAucHMftdfIPrZbJR0AHA98qAfbLg7708PPMCKWnIxgNYmkYyUdUZY3kzS9jNIc3zZSU7xF\n0pWS7pP0o1J/D0k/LcuHSbq/LL9D0k1l+Zhypm2mpDNUGSnp9loM69Xf17wJeBTA9gLbd5b69RG4\nkZJulTRD0nfbzliWM4nXSbpI0t2SzpOkXnxEvwH2LMt7A+fX4h4r6fKy/P7yuU2VdIekoZLWlnRD\n26iXpG1K3dmS1pA0oozMnSlplqSrJQ3uxncRERG90NbnSdodaAHOK7+zgyWNkXS9pCmSrpK0dtnm\nOkk/k9QKHCbpY2V2xR2SrpG0lqQRwMHA4aW9bSSNL/tp23e9f5ooaQLQ1q99RtJtZdvTy0nFztwC\nDK+1vYOkWyTdLulCSUNK+Y6lD7xd0i9qfdarfX95P7McQ8NYymt8qTdD0uGNPsPefzMRsTgkwVq8\nBtf+8z8VOK6DeucAX7Q9GljQbt1oqkRjFLCnpHWBicA2Zf02wFOShpflG0r5SbY3s70xMBj4qO2/\nAnO0cHrDAWXf7Z0A3CPpUklflLRygzo/B35uexTwcLt17wG+CmwEvAPYuoPj7szFwCfK8seAyzqo\ndwTw5fLZbQPMAz4NXFXKNgGmNthuPeBk2+8GngU+Wco7+y5eJekgSa2SWhe8MKdnRxYRsYyyfRHV\nDIR9yu/sy8CJwO62xwBnA9+rbbKi7RbbPwFuBLaw/R7g18A3bM8GTgNOsD3a9mumlzewKXCY7fVV\nzY7YE9i69pu/Txfb7wj8FkDSGsDRwPa2Ny3H9bXSZ55J1XeNAd7c1efSSSyjgeG2Ny797TntP0Pb\n8xq0lz4qookyRXDxmld+KIFqBIjqrBO1stWBobZvKUW/Aj5aq3Kt7Tml7p3A22zfKGmIpKHAumWb\nbakSjEvKdttJ+gawCvAGYBZVknIWcICkr1H9mL+3fdC2j5N0HrADVbKyN9UUjLotgd1qMf+4tu42\n2w+XmKcCI6g6xp54CnhG0l7AXcALHdS7CfhpifcS2w9LmgycLWkF4Le2GyVYD9TKpwAjuvFdvMr2\nGcAZACutvZ57eGwREVHZANgY+GOZ7DCIMoOiuKC2vA5wQRnhWhF4oBf7u81223YfpEqAJpd9DwYe\n72C78yStCAyhSnoAtqA6kXhT2X5FqhGuDan6mPsAJJ0LHNRFXB3FchnwDkknAlcAV3fnINNHRTRX\nRrD6v/m15QUsTIpvphqBuoeFI1pbUv3QrwycQnVGcBTVmbS2UaiLgZ2oEocptp9qtFPbf7V9KtWP\n/iaS3tgHMQMgad3ayN7BnbRzAXAytemBDeL8AXAgVWd0k6QNbd9AlXA+AoxX45uJdBpjREQsEQJm\nlZGY0bZH2d6htv752vKJVLMzRgFfZGG/1t7LlP/fSFqOKvFp1J6AX9b2vYHtYztocx+qGRm/LHG0\nbf/H2vYb2f58F8f7amxF2zE0jMX2M1QzMa6jmgp5VhftR0Q/kASryWw/CzwnafNStFc3N51INT3u\nBuAOYDtgfhntavvBfrLMB391LrrtF4GrgFNpPD0QSTtLr143tR5VAvJsu2q3snBaXXdjbovhoVon\n0tnNPi4FflTibUjSSNszbP8QmAxsKOltwD9sn0nVGW3azbh6+11ERET3PQcMLcv3AGtK2hJA0gqS\n3t3BdsOoTpwB7NdBewCzqUaDAHYBVuigvWuB3SW9qez7DaX/aMi2gW8BW0jakKof3FrSO8v2q0pa\nH7ibalbEyLLp3u1i27TU3xR4e2exlGmIy9m+mGo6Ylt/1v6YI6IfyVn7/uHzwJmSXgGuB7ozYXoi\n1fTAG2wvkPQQ1Y86tp+VdCbVHYYeo0o86s4DPk7HUw32BU6Q9ALV2bZ9yj7qdb4KnCvpKODKbsbc\nI7afA34IoI7vk/FVSdsBr1BNg/wDVWJ0pKSXqO4s1ent8Nvp8XcxavgwWvOMjoiINqtIql+b+9N2\n68cDp0maRzXzYnfgF5KGUf2/5GdUv+ftHQtcKOkZ4E8sTE4uAy6StCtwCNWsjd9JmkbVPz3foC1s\n3ynpaODqMtL1EvBl4MGODsz2PEk/AY60/fky9f98SSuVKkfbvlfSQcAVpR+dyMJk6GLgs5JmAZOA\ne7uIZR5wTikD+Gajz7DRdVht0kdFLHmqTshEM0kaYrvtLkfjgLVtH7YY93cEMMz2txahjVWorjFz\nuU5qb9u79lmQTdKb76KlpcWtrT2+a3xEAJKm2G7pumbE0knSWOAI2w2v6V3c0kdF9F5v+6iMYPUP\nO0v6JtX38SDV8y0WC0mXAiOBDyxiU2OAk8pUwmeBzy1qbP3EEvsuIiIiImLgSYLVD9i+gNfeKWlx\n7uvjfdTORKoLbweUJfldRETEwGf7OqqbVETEMiI3uYiIiIiIiOgjSbAiIiIiIiL6SBKsiIiIiIiI\nPpIEKyIiIiIioo/kJhcRi2jGI3MYMe6KZoexyGbnOSkREQPOQOij0j/F0iYjWP2AJJcHF7a9P0LS\nsX3U9rGSHpE0VdKdkvbuequG7bRI+kUH62aXp833pt3dJG1Ue3+cpO272Ga8pN27Uy5pbm/iKtv+\nv95uGxExEElaUPqTmZIuk7R6D7c/tjyLsVu/9z1se4SkT9fed9hv9bDdsaWfPrBWNrqUHdHFtq/p\n43qwz13Ksxg7q7O/pJN62nZELH5JsPqH+cAnepukdMMJtkcDuwKnS1qhpw3YbrV9aN+Hxm7Aq52P\n7WNsX7MY9tMbSbAiIl5rnu3RtjcGnga+3NuGFsPv/Qjg1QSrj/utmcCnau/3BqZ1Y7vX9HHdIWl5\n2xNs/6An20VE/5EEq394GTgDOLz9inJG7k+Spku6VtJbS/l4Sb+QdLOk+xuN6LRn+z7gBeDfShsj\nJV0paYqkiZI2LOV7lLOT0yTdUMrGSrq8LL9R0tWSZkk6C1At3s9Iuq2c4Txd0qBSPlfS90qbt0pa\nS9JWwC7A8aX+yPoolKRjJE0usZxRHmrca5KOLO1Nl/SdWvlvy2cwS9JBpewHwOAS13mLst+IiAHq\nFmA4gKQhpY+6XdIMSbu2VZJ0lKR7Jd0IbFArr//ef1DSHWXbsyWtVMob9gOS3inpmtKn3C5pJPAD\nYJvyu314W78labky02L12r7vK/3QmpIuLvuYLGnrDo71QWDlso2AHYE/1Nr7Qtl+WmlvlQ76uI76\n3fGSTpM0CfhRfXRK0sckTSqfzzWS1lrE7y0iFrMkWP3HycA+koa1Kz8R+KXtfwfOA+rTHdYG3gd8\nlKpj6ZSkTYH7bD9eis4ADrE9BjgCOKWUHwN82PYmVJ1De98GbrT9buBSoC3pexewJ7B1GTFbAOxT\ntlkVuLW0eQPwBds3AxOAI8sZ0b+2289JtjcrZ0oHl+PsSltHNlXS1Nqx7wCsB7wXGA2MkbRtWf25\n8hm0AIdKeqPtcSw8U7tP+51IOkhSq6TWBS/M6UZYEREDRzl59kGq33CAF4GP294U2A74iSpjgL2o\nfnc/AmzWoK2VgfHAnrZHUV0f/qWyuqN+4Dzg5NKnbAU8CowDJpbf7RPa2rf9CvA74ONlf5sDD9r+\nB/BzqlkemwGfBM7q5LAvAvYo+7udavZJm0tKnJsAdwGf76CP66jfBVgH2Mr219rt90ZgC9vvAX4N\nfKOTGCnHmD4qoolyk4t+wvY/Jf0vcCgwr7ZqS+ATZfn/gB/V1v22dBx3dnFG63BJBwDrAx+D6mwj\nVSdxYW1gaKXy503AeEm/AS5p0N62bTHZvkLSM6X8g8AYYHJpczDQlsz9C7i8LE8BPtRJvG22k/QN\nYBXgDcAs4LIutjnS9kVtb7TwGqwdyuuO8n4IVcJ1A1VS9fFSvm4pf6qzndg+g6qjZKW113M3jiUi\nYiAYXE5eDadKJP5YygX8dzlx9UpZvxawDXCp7RcAJE14fZNsADxg+97y/pdUUw9/RoN+QNJ1wHDb\nlwLYfrG03VncF1CdPDyHKuG7oJRvD2xU23Y1SUNsN7p+9zdluw2B86n60DYbS/ousDpV/3JV+427\n6HcBLrS9oMF+1wEukLQ2sCLwQGcHCumjIpotCVb/8jOqs2LndLN+/exZ27SJ7wE7A5RRJKjOzv1Y\n0i7A/5SpFMsBz9bqvMr2weUM387AlHIGsjtENdr2zQbrXrLd9iO/gC7+7pUzmqcALbYfUnXTj5W7\nGUdHsX3f9unt9jOWqoPd0vYLpeNelP1ERAxk82yPlrQKVdfJRskAACAASURBVBLxZaqZFfsAawJj\nbL8kaTaL+Fvax/3ALcA7Ja1JdV3Ud0v5clSjQy921YDtxyS9RHWC8DBem2CNB3azPU3S/sDYBk10\n2O8Wz3dQfiLwU9sTSp91bFexRkRzZYpgP2L7aaozZJ+vFd9MdbYNqg5sYhdtHFWmIjRKnCYArcB+\ntv8JPCBpD4AylWOTsjzS9iTbxwBPUI3q1N1AuZBY0k6Ua7qAa4HdJb2prHuDpLd1cdjPAUMblLd1\nok+Ws35dXmPWhauAz5W2kDS8xDkMeKYkVxsCW9S2eUm9uCFIRMRAV0akDgW+Lml5qt/Sx0tytR3Q\n9tt/A7CbpMGShlJmUbRzDzBC0jvL+32B6+mgH7D9HPCwpN0AJK1UEr6O+hPKCb5LgZ8Cd9lum6Vw\nNXBIWz1JHSU/bY4B/rPBSNNQ4NHSZ9Snlb8aU2f9bheGAY+U5f26UT8imiwjWP3PT4Cv1N4fApwj\n6UiqZOeARWz/OOBXks6k6gROlXQ0sALV3O5pVNcxrUc16nNtKXt/rY3vAOdLmkWVAP4NwPadpa2r\nJS0HvER1dvPBTuL5NXCmpEOpJVG2ny0xzgQeAyYvykHbvrpcI3ZLmZoxF/gMcCVwsKS7qDr5W2ub\nnQFMl3R7o+uw2owaPozWPKMjIpYxtu+QNJ3qjnrnAZdJmkF1Iu/uUud2SRdQ9SOP0+C33PaLZRr7\nhSVZmwycZnt+J/3AvlR3xT2Oqq/ZA5gOLJA0jWpE6Q5e64LSxv61skOBk8txLE+VEB7cyTHf3MGq\nbwGTqPrpSSxM9Nr3cR31u505luqzeQb4E/D2Luq/RvqoiCVPC2dtRURvtLS0uLW1tdlhRCyVJE2x\n3dLsOCIGqvRREb3X2z4qUwQjIiIiIiL6SBKsiIiIiIiIPpIEKyIiIiIioo8kwYqIiIiIiOgjSbAi\nIiIiIiL6SBKsiIiIiIiIPpLnYEUsohmPzGHEuCuaHcYim53npEREDDgDoY9K/xRLm4xgxRIh6ShJ\nsyRNlzRV0ubNjikiIqIrkt5Y+q2pkh6T9Ejt/Yp9tI91ywOZI2IAyAhWLHaStgQ+Cmxqe76kNYA+\n6ZQiIiIWJ9tPAaMBJB0LzLX94z7ex0PAnn3ZZkQ0T0awYklYG3jS9nwA20/a/rukHSXdLel2Sb+Q\ndDlUHZikI9o2ljRT0oiy/BlJt5Uzh6dLGlTKd5B0S2nrQklDSvlHyj6mtNvHqpLOLm3dIWnXUj5I\n0vGSJpfRti8uwc8pIiKWIpIuK/3LLEkHlrLlJT0r6QeSppW+6U1l3bmSfi7pZkn3S/p4KX+npKll\n+UBJF0m6StJ9kr5f298XJd0raZKksyT9rBnHHRGdS4IVS8LVwLqlUzhF0vslrQycCXwMGAO8uatG\nJL2L6gzf1rZHAwuAfcqI2NHA9rY3BVqBr5V9nA7sZHsMsGatuaOAP9l+L7AdcLykVYHPA3NsbwZs\nBnxB0tsbxHKQpFZJrQtemNO7TyUiIpZ2+5X+ZTOqfuffSvkw4HrbmwC3AJ+rbfMmYGtgN+D7NLYJ\nsAfw78BnJL1F0rrAOGBzYBtgo46CSh8V0VxJsGKxsz2XKok6CHgCuAA4GHjA9n22DZzbjaY+WNqZ\nXM70fRB4B7AFVUdzUynfD3gbsCFwv+0Hyvbn19raARhX6l8HrAy8tZR/tpRPAt4IrNfgmM6w3WK7\nZdAqw7r9WURExIByuKRpVEnUOsDIUj7P9h/K8hRgRG2b37oyHRjeQbvX2P6n7XnA3VT90+ZUJwaf\nsf0v4KKOgkofFdFcuQYrlgjbC6gSmeskzaBKgjryMq9N/lcufwr4pe1v1itL+hjwR9t7tysf3ck+\nBHzS9j3tthFwiO2rOtk2IiKWcZK2B7YFtrA9T9KNLOyv/lWruoDX/n9rfr2ZDpqv12m/fUT0cxnB\nisVO0gaS6qNAo4F/ACMktZ3tqydHs4FNy7abAm1T9K4Fdq/NZX+DpLcBtwJbS3pnKV9V0vrAPcA7\n2q7f4rUXEF8FHFISKiS9p1b+JUkrlPL1y9TBiIiIumHA0yW5ejfVNMHF6TZgO0mrlz7qE4t5fxHR\nSzkjEkvCEOBESatTjU79hWq64EXAFZJeACYCQ0v9i6mm6c2imqZ3L4DtOyUdDVwtaTngJeDLtm+V\ntD9wvqSVShtH275X0n8AV0p6Hphci+m/gJ8B00tbD1Dd6fAsqqkct5fk6wmqefIdGjV8GK15RkdE\nxLLmCuAgSXdSndCbtDh3Zvtvko6n6sueLvvs8gKr9FERS56qy18imkvSWOAI2x/t43aH2J5bkqWT\ngftsn9CX+2hpaXFra2tfNhmxzJA0xXZLs+OIWBrU+rQVgN8Bp9q+rLNt0kdF9F5v+6hMEYyB7gvl\nhhWzqKZznN7keCIiInrrvyTdAUynGsG6vMnxREQDmSIY/YLt66hugtHX7Z4A9OmIVURERDPYPrzZ\nMURE1zJFMGIRSXqO6kzi0m4N4MlmB7GIBsIxwMA4ju4ew9tsr9l1tYjojQHSRw2E30QYGMcxEI4B\nFnMflRGsiEV3z0C4hkRS69J+HAPhGGBgHMdAOIaIAWKp76MGyu/JQDiOgXAMsPiPI9dgRURERERE\n9JEkWBEREREREX0kCVbEojuj2QH0kYFwHAPhGGBgHMdAOIaIgWAg/FscCMcAA+M4BsIxwGI+jtzk\nIiIiIiIioo9kBCsiIiIiIqKPJMGKiIiIiIjoI0mwIhaBpB0l3SPpL5LGNTue3pB0tqTHJc1sdiy9\nJWldSX+WdKekWZIOa3ZMPSVpZUm3SZpWjuE7zY5pUUgaJOkOSZc3O5aIZVH6p/5hIPRPMLD6qCXR\nPyXBiuglSYOAk4GdgI2AvSVt1NyoemU8sGOzg1hELwNft70RsAXw5aXwu5gPfMD2JsBoYEdJWzQ5\npkVxGHBXs4OIWBalf+pXBkL/BAOrj1rs/VMSrIjeey/wF9v32/4X8Gtg1ybH1GO2bwCebnYci8L2\no7ZvL8vPUf1wDm9uVD3jytzydoXyWirvQiRpHWBn4KxmxxKxjEr/1E8MhP4JBk4ftaT6pyRYEb03\nHHio9v5hlsIfzYFG0gjgPcCk5kbSc2XawlTgceCPtpe6Yyh+BnwDeKXZgUQso9I/9UNLc/8EA6aP\nWiL9UxKsiBgwJA0BLga+avufzY6np2wvsD0aWAd4r6SNmx1TT0n6KPC47SnNjiUior9Y2vsnWPr7\nqCXZPyXBiui9R4B1a+/XKWXRBJJWoOq8zrN9SbPjWRS2nwX+zNJ57cHWwC6SZlNNS/qApHObG1LE\nMif9Uz8ykPonWKr7qCXWPyXBiui9ycB6kt4uaUVgL2BCk2NaJkkS8D/AXbZ/2ux4ekPSmpJWL8uD\ngQ8Bdzc3qp6z/U3b69geQfVv4k+2P9PksCKWNemf+omB0D/BwOijlmT/lAQropdsvwx8BbiK6qLV\n39ie1dyoek7S+cAtwAaSHpb0+WbH1AtbA/tSnY2aWl4faXZQPbQ28GdJ06n+c/RH27nFeUT0WPqn\nfmUg9E+QPqpHZC91NwCJiIiIiIjolzKCFRERERER0UeSYEVERERERPSRJFgRERERERF9JAlWRERE\nREREH0mCFRERERER0UeSYEVERERERPSRJFgRERERERF9JAlWREREREREH0mCFRERERER0UeSYEVE\nRERERPSRJFgRERERERF9JAlWREREREREH0mCFRERERER0UeSYEVEt0h6n6SbJc2R9LSkmyRtJun/\nSZpbXi9KWlB7P6u2vSTdL+nOdu3OqtVfUNpoe///JO3frs2211vK9rMlPS5p1VqbB0q6roPjGCHJ\nkpYv79eRdLGkJ8uxzZS0f6O6HbS3f6mzZ7vysaX8lHblN9bab39sD0g6R9L63fpSIiIiot9JghUR\nXZK0GnA5cCLwBmA48B1gvu3/tj3E9hDgYOCWtve2311rZlvgTcA7JG3WVmj73bXtJwJfqW3/36Va\nvc22199rbQ8CDuvl4f0f8BDwNuCNwL7AP3qw/X7A08BnG6x7HthX0ohOtr+lHPswYHtgHjBF0sY9\niCEiIiL6iSRYEdEd6wPYPt/2AtvzbF9te3oP2tgP+B3w+7Lcl44HjpC0ei+23QwYb/t52y/bvsP2\nH7qzoaS3Ae8HDgI+LOnN7ao8C4wHvt1VW+Vz/avt/wCuB47twTFEREREP5EEKyK6415ggaRfStpJ\n0r/1ZGNJqwC7A+eV116SVuzD+FqB64AjerHtrcDJkvaS9NYebvtZoNX2xcBdwD4N6nwP+KSkDXrQ\n7iXANj2MJSIiIvqBJFgR0SXb/wTeBxg4E3hC0gRJa3WziU8A84GrgSuAFYCdexDCFpKerb3+2qDO\nMcAhktbsQbsAe1BNTfwW8ICkqfUpjF34LPCrsvwrGkwTtP0YcBpwXA9i+jvVVMyIiIhYyiTBiohu\nsX2X7f1trwNsDLwF+Fk3N98P+E2ZgvcicDE9myZ4q+3Va6+RDeKbSXWd2LgetIvtZ2yPK9eLrQVM\nBX4rSZ1tJ2lr4O3Ar0vRr4BRkkY3qP5DqimEm3QzrOFU13VFRETEUiYJVkT0mO27qa4t6vJGDJLW\nAT4AfEbSY5Ieo5ou+BFJa/RxaN8GvkCVoPSY7SeBH1Mlj12NIO0HCJhajmlSrbx9u09RJaP/1c1Q\nPk41qhYRERFLmSRYEdElSRtK+npJlpC0LrA31fVLXdmX6hquDYDR5bU+8HBpo8/Y/gtwAXBod7eR\n9ENJG0taXtJQ4EvAX0pS1GYlSSvXXqsAn6K6ucXo2usQ4NMd3Nb9p8BWwLs6iGOQpLdLOhEYS3WX\nxoiIiFjKJMGKiO54DtgcmCTpearEaibw9W5sux9wiu3H6i+q65K6O01wywbPweroOqnjgFU7WNfI\nKsClVHf8u5/qdu27tKszl+r26W2vT5Q//7fdMZ0NLA/s2H4n5Tq2H/H6kbEtJc0F/kl1o47VgM1s\nz+jBMUREREQ/IdvNjiEiIiIiImJAyAhWREREREREH0mCFREREdFkks6W9LikmR2sl6RfSPqLpOmS\nNl3SMUZE9yTBioiIiGi+8TS4frNmJ2C98joIOHUJxBQRvZAEKyIiIqLJbN9A58+/25Xqxjq2fSuw\nuqS1l0x0EdETjW4lHBE9sMYaa3jEiBHNDiNiqTRlypQnba/Z7DgilgLDgYdq7x8uZY+2ryjpIKpR\nLlZdddUxG2644RIJMGKg6W0flQQrYhGNGDGC1tbWZocRsVSS9GCzY4gYaGyfAZwB0NLS4vRREb3T\n2z4qUwQjIiIi+r9HgHVr79cpZRHRzyTBioiIiOj/JgCfLXcT3AKYY/t10wMjovkyRTBiEc14ZA4j\nxl3R7DAi+pXZP9i52SFELFUknQ+MBdaQ9DDwbWAFANunAb8HPgL8BXgBOKA5kUZEV5JgLeMkHQV8\nGlgAvAJ80fakXrRzPNUP/++BHwGXAysCh9qe2ME2s4EW20+2Kz8WmGv7x+3KNwBOB1YHVgIm2j6o\nu3HZPrKDOmOBf9m+ufOjjIiIWDxs793FegNfXkLhRMQiSIK1DJO0JfBRYFPb8yWtQZUU9cZBwBts\nL5C0FzDD9oF9FWvxC+AE278DkDSqJ3F1UmcsMBdIghURERERiyTXYC3b1gaetD0fwPaTtv8OIGkz\nSTdLmibpNklDJY2QNFHS7eW1Vak7ARgCTJH0n1QjWLtKmippsKS9Jc2QNFPSDxsFIukoSfdKuhHY\noJN4H257Y3tG2bY7ce0paU1JF0uaXF5bSxoBHAwcXuLdRtIDklYobaxWfx8RERER0ZmMYC3brgaO\nkXQvcA1wge3rJa0IXADsaXuypNWAecDjwIdsvyhpPeB8qil+u0iaa3s0gKR/lPKvSHoL8ENgDPAM\ncLWk3Wz/ti0ISWOAvYDRVH8nbwemNIj3BOBPkm4usZ9j+9kexPUrqhGwGyW9FbjK9rsknUZtSqKk\n64Cdgd+WuC6x/VI9kPozRgatlkf4REREREQlI1jLMNtzqRKfg4AngAsk7U81gvSo7cml3j9tv0x1\nse2ZkmYAFwIbdWM3mwHX2X6itHEesG27OtsAl9p+wfY/qe6U1Cjec4B3lX2PBW6VtFIP4toeOEnS\n1LKP1SQNaVDvLBZePHwAcE6DWM6w3WK7ZdAqwzrYXUREREQsazKCtYwr1yZdB1xXEpT9aDx6BHA4\n8A9gE6rk/MUlEWNdmcJ4NnC2pJnAxsDHuhnXcsAWtl+zXlL7fdxUph2OBQbZntmnBxERERERA1ZG\nsJZhkjYoU+rajAYeBO4B1pa0Wak3VNLywDCqka1XgH2BQd3YzW3A+yWtIWkQsDdwfbs6NwC7leu1\nhlIlTI3i3bF2bdSbgTdSPWSxu3FdDRxSa290WXwOGNqu7v8Cv6LB6FVEREREREcygrVsGwKcKGl1\n4GWqZ2scZPtfkvYs6wZTXX+1PXAKcLGkzwJXAs93tQPbj0oaB/wZEHBF210Aa3Vul3QBMI3qeqrJ\nHTS3A/BzSW0jUEfafkxSd+M6FDhZ0nSqv/s3UN3g4jLgIkm7AoeU28qfB3yX6nquTo0aPozWPPMn\nIiIiIgBVj1WIiDpJuwO72t63q7otLS1ubW1dAlFFDDySpthuaXYcEQNV+qiI3uttH5URrIh2JJ0I\n7ET1gOKIiIiIiG5LghXRju1Duq4VEREREfF6uclFREREREREH0mCFRERERER0UeSYEVERERERPSR\nJFgRERERERF9JDe5iFhEMx6Zw4hxVzQ7jIh+ZXaeDRcREcuojGD1kCRLOrf2fnlJT0i6vLzfpTxY\nt6/2N748kwlJ10laKp4XI+mzkmZKmiHpDklHdFF/N0kbLaHYbl4S+4mIiIiIZU8SrJ57HthY0uDy\n/kPAI20rbU+w/YOmRNZPSNoJ+Cqwg+1RwBbAnC422w1YrAmWpOUBbG+1OPcTEREREcuuJFi983ug\nbf7L3sD5bSsk7S/ppLK8RxnFmSbphlI2SNKPS/l0SYeU8jGSrpc0RdJVktbuLABJp0pqlTRL0ndq\n5bMlfUfS7WX0aMNSvqqksyXdVkaUdi3lK0s6pzbStF374yjvL5c0tsQ/vjY6dXiD8L4JHGH77wC2\n59s+s7TzBUmTy2dysaRVJG0F7AIcL2mqpJHldWX5PCbWjmOkpFvLvr8raW4pl6Tja3HtWcrHlu0n\nAHeWsrm14zqyxDO97XMsn9UVJcaZbW1FRERERHQl12D1zq+BY8q0wH8Hzga2aVDvGODDth+RtHop\nOwgYAYy2/bKkN0haATgR2NX2E+U/9N8DPtdJDEfZflrSIOBaSf9ue3pZ96TtTSX9B3AEcCBwFPAn\n258rsdwm6RrgYMC2R5Uk5mpJ63ey39HAcNsbA9SOq25jYEoH219SS7a+C3ze9oklAbrc9kVl3bXA\nwbbvk7Q5cArwAeDnwM9tny/p4Fq7nyixbQKsAUxuS2qBTYGNbT9QD0TSDsB6wHsBARMkbQusCfzd\n9s6l3rD2ByHpIKrvkkGrrdnBoUZERETEsiYjWL1QEpkRVKNXv++k6k3AeElfAAaVsu2B022/XNp6\nGtiAKin5o6SpwNHAOl2E8SlJtwN3AO/mtdPrLil/TilxAuwAjCvtXwesDLwVeB9wbonlbuBBoLME\n637gHZJOlLQj8M8u4mxv4zKiNAPYp8T+GpKGAFsBF5Z4TwfaRvS2BC4sy7+qbfY+4HzbC2z/A7ge\n2Kysu619clXsUF53ALcDG1IlXDOAD0n6oaRtbL9ueqPtM2y32G4ZtMrr8q+IiIiIWEZlBKv3JgA/\nBsYCb2xUwfbBZfRlZ2CKpDEdtCVglu0tu7NjSW+nGpnazPYzksZTJUxt5pc/F7DwOxbwSdv3tGur\no928zGsT8JXLMT0jaRPgw1SjX5/i9SNts4AxwJ8atDse2M32NEn7U31+7S0HPGt7dEfB9dDzHZQL\n+L7t01+3QtoU+AjwXUnX2j6uj2KJiIiIiAEsI1i9dzbwHdszOqogaaTtSbaPAZ4A1gX+CHxR5YYL\nkt4A3AOsKWnLUraCpNeN7NSsRpU0zJG0FrBTN+K9CjhEJaOS9J5SPpFqJIkyNfCtJZ7ZwGhJy0la\nl2oaHZLWAJazfTHVSNumDfb1farrqd5ctllR0oFl3VDg0TItcp/aNs+Vddj+J/CApD3K9ipJHcCt\nwCfL8l617ScCe5ZrxNYEtgVu68Zn8rkyYoak4ZLeJOktwAu2zwWO7+AYIyIiIiJeJyNYvWT7YeAX\nXVQ7XtJ6VCMl1wLTgJlUU/CmS3oJONP2Sapuxf6Lcr3P8sDPqEaCGu17mqQ7gLuBh6imInblv0qb\n0yUtBzwAfJTq2qZTy5S9l4H9bc+XdFOpcydwF9UUOoDhwDmlDahuaNE+vt+XxO+aktCZKiEF+BYw\niSrhnERJqqiuaztT0qHA7lTJ16mSjgZWKOunUd2d8FxJRwFXsvDuhJdSTR+cVvb3DduPtd0coxHb\nV0t6F3BLyTvnAp8B3kn13b0CvAR8qeOPFUYNH0ZrnvkTEREREYBsNzuGiG6TtAowz7Yl7QXsbXvX\nZsbU0tLi1tbWZoYQsdSSNMX2UvF8v4ilUfqoiN7rbR+VEaxY2owBTiojY8/S+Z0WIyIiIiKWqCRY\nsVSxPZHqVuwREREREf1ObnIRERERERHRR5JgRURERERE9JEkWBEREREREX0kCVZEREREREQfyU0u\nIhbRjEfmMGLcFc0OI6JfmZ1nw0VExDIqI1j9kKQFkqZKminpMkmr93D7YyUdUZaPk7R9H8Y2QtKn\na+9bJHX1wOXutDtWkiUdWCsbXcqO6GLb3SRt1It97iJpXBd19pd0Uk/bjoiIiIhlUxKs/mme7dG2\nNwaeBr7c24ZsH2P7mr4LjRHAqwmW7Vbbh/ZR2zOBT9Xe7w1M68Z2uwE9SrAkLW97gu0f9GS7iIiI\niIjOJMHq/24BhgNIGiLpWkm3S5ohade2SpKOknSvpBuBDWrl4yXtXpY/KOmOsu3ZklYq5cdImlxG\nzM4oD/FF0jslXSNpWtnnSOAHwDZlhO3wMvJ0uaTlJM2uj7ZJuk/SWpLWlHRx2cdkSVt3cKwPAiuX\nbQTsCPyh1t4XyvbTSnurSNoK2AU4vsQ0sryulDRF0kRJG9Y+i9MkTQJ+VB+dkvQxSZPK53ONpLUW\n8XuLiIiIiGVQEqx+TNIg4IPAhFL0IvBx25sC2wE/UWUMsBcwGvgIsFmDtlYGxgN72h5Fdf3dl8rq\nk2xvVkbMBgMfLeXnASfb3gTYCngUGAdMLCNsJ7S1b/sV4HfAx8v+NgcetP0P4OfACbY3Az4JnNXJ\nYV8E7FH2dzswv7bukhLnJsBdwOdt31w+nyNLTH8FzgAOsT0GOAI4pdbGOsBWtr/Wbr83AlvYfg/w\na+AbncSIpIMktUpqXfDCnM6qRkRERMQyJDe56J8GS5pKNXJ1F/DHUi7gvyVtC7xS1q8FbANcavsF\nAEkTXt8kGwAP2L63vP8l1dTDnwHbSfoGsArwBmCWpOuA4bYvBbD9Ymm7s7gvAI4BzqFK+C4o5dsD\nG9W2XU3SENtzG7Txm7LdhsD5VIlWm40lfRdYHRgCXNV+Y0lDyjYX1va3Uq3KhbYXNNjvOsAFktYG\nVgQe6OxAbZ9Blcix0trrubO6EREREbHsyAhW/zTP9mjgbVRJVds1WPsAawJjyvp/ACsvyo7KyNYp\nwO5lZOvMRWjzFuCdktakui7qklK+HNXo0OjyGt5BcoXtx4CXgA8B17ZbPR74SonzOx3EuRzwbG1f\no22/q7b++Q5iP5FqJG8U8MUO2o6IiIiI6FQSrH6sjEgdCnxd0vLAMOBx2y9J2o4qAQO4AdhN0mBJ\nQ4GPNWjuHmCEpHeW9/sC17MwkXiyjP7sXvb9HPCwpN0AJK0kaRXgOWBoB/EauBT4KXCX7afKqquB\nQ9rqSRrdxaEfA/xng5GmocCjklagSjbbvBqT7X8CD0jao+xLkjbpYn9QfbaPlOX9ulE/IiIiIuJ1\nMkWwn7N9h6TpVHfUOw+4TNIMoBW4u9S5XdIFVHfcexyY3KCdFyUdQDV1bvlS5zTb8yWdSXUHv8fa\nbbsvcLqk46hGlfYApgMLJE2jGlG6o92uLiht7F8rOxQ4uRzH8lQJ4cGdHPPNHaz6FjAJeKL82Zbo\n/Ro4U9KhVAniPsCpko4GVijru7ob4bFUn80zwJ+At3dR/1Wjhg+jNc/8iYiIiAhA1aBDRPRWS0uL\nW1tbmx1GxFJJ0hTbLc2OI6LZJO1IdVOoQcBZ7R8jImkYcC7wVqqTlT+2fU5X7aaPiui93vZRmSIY\nERER0UTlrsEnAztRPddxb0ntn+/4ZeDOcifdsVR3El5xiQYaEd2SBCsiIiKiud4L/MX2/bb/RTW1\nfdd2dQwMLc+JHAI8Dby8ZMOMiO5IghURERHRXMOBh2rvHy5ldScB7wL+DswADivPoHyd+rMan3ji\nicURb0R0IglWRERERP/3YWAq8BZgNHCSpNUaVbR9hu0W2y1rrrnmkowxIkiCFREREdFsjwDr1t6v\nw8JHh7Q5ALjElb8ADwAbLqH4IqIHkmBFRERENNdkYD1Jby83rtgLmNCuzt+ADwJIWgvYALh/iUYZ\nEd2S52BFLKIZj8xhxLgrmh1GRL8yO8+Gi+g22y9L+gpwFdVt2s+2PUvSwWX9acB/AePLszAF/Kft\nJ5sWdER0KCNYi5Gkue3e7y/ppLJ8sKTPdrH9q/WXJElbSJokaaqkuyQdW8p3kTRuCex/tqSJ7cqm\nSppZllsk/aIX7f5e0up9FWdERERfsf172+vbHmn7e6XstJJcYfvvtnewPcr2xrbPbW7EEdGRjGA1\nSdsPZj/1S+BTtqeVZ3NsAGB7Aq+fsrC4DJW0ru2HJL2rvsJ2K9Djpyba/kifRRcRERER0UBGsJpE\n0rGSjijLm0maXkZpjm8bqSneIulKSfdJ+lGpv4eku2936gAAIABJREFUn5blwyTdX5bfIemmsnyM\npMmSZko6Q5WRkm6vxbBe/X3Nm4BHAWwvsH1nqV8fgRsp6VZJMyR9t220TtJYSddJukjS3ZLOK8/s\n6KnfAHuW5b2B82txj5V0eVl+f/ncpkq6Q9JQSWtLuqFt1EvSNqXubElrSBpRRubOlDRL0tWSBnfj\nu4iIiIiI6FQSrMVrcO0//1OB4zqodw7wRdujgQXt1o2mSjRGAXtKWheYCGxT1m8DPCVpeFm+oZSf\nZHsz2xsDg4GP2v4rMEfS6FLngLLv9k4A7pF0qaQvSlq5QZ2fAz+3PYrqeR117wG+SvU0+ncAW3dw\n3J25GPhEWf4YcFkH9Y4Avlw+u22AecCngatK2SZUt7Vtbz3gZNvvBp4FPlnKO/suXlV/xsiCF+b0\n7MgiIiIiYsBKgrV4zbM9uu0FHNO+QrkmaKjtW0rRr9pVudb2HNsvAncCb7P9GDBE0lCq27r+CtiW\nKsFou3Zpu3Id1QzgA8C7S/lZwAFl6t+eDfaH7eOAFuBqqmTlygbHtiVwYQcx32b74fIAxKnAiAbb\nd+Up4BlJewF3AS90UO8m4KeSDgVWt/0y1d2YDijXjo2y/VyD7R6w3ZZ4TQFGdOO7eFX9GSODVhnW\n44OLiIiIiIEpCVb/N7+2vICF183dTDUCdQ8LR7S2BG4qI06nALuXEaYzgbZRqIuBnYCPAlNsP9Vo\np7b/avtUqlvCbiLpjX0QMwCS1q2N7B3cSTsXACdTmx7YIM4fAAdSjdLdJGlD2zdQJZyPUN1xqdHN\nRDqNMSIiIiKiN5JgNZntZ4HnJG1eivbq5qYTqabH3QDcAWwHzLc9h4XJ1JOShgC71/b3ItVtYE+l\n8fRAJO1cu25qPaoE5Nl21W5l4bS67sbcFsNDtZG9zm72cSnwoxJvQ5JG2p5h+4dUI1cbSnob8A/b\nZ1KN2G3azbh6+11ERERERAA5a99ffB44U9IrwPVAdy7qmUg1PfAG2wskPQTcDVWiIOlMYCbwGFXi\nUXce8HGqKYCN7AucIOkF4GVgn7KPep2vAudKOopqCmGfX4hUpvb9EKCT+2R8VdJ2wCvALOAPVInR\nkZJeAuYCnd4Ov50efxejhg+jNc/8iYiIiAhAtpsdwzJP0hDbbXfhGwesbfuwxbi/I4Bhtr+1CG2s\nQnWNmct1Unvb3rXPgmyS3nwXLS0tbm3t8V3jIwKQNMV2S7PjiBio0kdF9F5v+6iMYPUPO0v6JtX3\n8SCw/+LakaRLgZFUN75YFGOAk8pUwmeBzy1qbP3EEvsuIiIiImLgSYLVD9i+gOqGDktiXx/vo3Ym\nUt0CfUBZkt9FRERERAw8uclFREREREREH0mCFRERERER0UeSYEVERERERPSRJFgRERERERF9JDe5\niFhEMx6Zw4hxVzQ7jIh+ZXaeDRcREcuofjOCJWmBpKm117hmx7S4SDpW0iPlOO+UtHezY+oNSaNq\n39fTkh4oy9cswRjWkfS7sry9pDnt/h5tJ2n52t+vmZImSFpN0ugO4r9K0psl/X5JHUdEREREDAz9\naQRrnu3Ri6vx8rwm2X5lce2jh06w/WNJ6wFTJF1k+6VmB9UTtmcAowEkjQcut33REg7j68AZtfd/\ntr1bvYKk5YHn2v5+SToP+JLtH7Iw/nOBi2z/trbdU5I2tz1pcR9ERERERAwM/WYEqyOSZkv6fhlZ\naJW0aRlh+Kukg2v1jpQ0WdJ0Sd8pZSMk3SPpf4GZwLqSPi/pXkm3STpT0kml7pqSLi5tTJa0dSk/\nVtLZkq6TdL+kQ2v7/GzZ3zRJ/ydpaBkFWaGsX63+vhHb9wEvAP9Wthkp6UpJUyRNlLRhKd+jjL5M\nk3RDKdtf0u9KbPdJ+nYttq+V+jMlfbX2edxVjnuWpKslDS7rDi2jadMl/bqUrVqO/TZJd0jatYff\n3biy7XRJx9TKLyvHN0vSgaVseUnPSvppKb9K0uaSri+f+0catC9gN+CPPYkLuAUY3o16vwX26WHb\nEREREbEM608jWIMlTa29/3556CvA32yPlnQCMB7YGliZKmk6TdIOwHrAewEBEyRtC/ytlO9n+1ZJ\nbwG+BWwKPAf8CZhW9vFzqlGlGyW9FbgKeFdZtyGwHTAUuEfSqcD6wNHAVraflPQG289Jug7Ymeo/\n53sBl3Q2MiVpU+A+24+XojOAg23fJ2lz4BTgA8AxwIdtPyJp9VoT7wU2pkrSJku6AjBwALB5+Twm\nSboeeKZ8Hnvb/oKk3wCfBM4FxgFvtz2/1v5RwJ9sf66U3SbpGtvPd3Q8teP6CPDWWgy/l7SV7ZvL\n9/G0pFWAVkkXl+9jGPAH21+TdBlwLPBBqgcanw60n7L3TuBx2/+qlW3X7u/RbsDDtbgGlc/zlK6O\nAWil+o4bHd9BwEEAg1ZbsxtNRURERMSyoD8lWJ1NEZxQ/pwBDLH9HPCcpLZkYIfyuqPUG0KVSPwN\neND2raX8vcD1tp8GkHQhVaIEsD2wUTUoAsBqkoaU5StszwfmS3ocWIvqP+kX2n4SoK1N4CzgG1QJ\n1gHAFzo4psMlHVD2/7ESzxBgK+DCWhwrlT9vAsaXpOiSWjt/tP1U2f4S4H1UCdalbYlQKd+mfI4P\n2G5LQKYAI8rydOA8Sb8tsVM+010kHVHer0yVNN3VwTHV7QDsxGu/k/WBm8ux71LK1wFGAlOp/g60\njUbNAObYflnSjFqcdWsDT7Qr62iK4NCSeK1T2v5zN47hceAtjVbYPoMyNXGltddzN9qKiIiIiGVA\nf0qwOjO//PlKbbnt/fJUIyTft316fSNJI4AuR1uK5YAtbL/Yro36/gEW0MnnZvumMhVvLDDI9swO\nqrZdg7UL8D+SRpYYnm2UaNo+uIxo7Ux1zdaYtlXtq3Z4hJX2xzK4LO8MbEuV7B0laRTV5/pJ2/d0\n0WYjAr5r+39eUyhtX/azhe15km6kStwA6iNR9e+67Xtub15t2648V0ZBV6WaUvhFuh7FWrnsIyIi\nIiKiW/r9NVjddBXwubYRJ0nDJb2pQb3JwPsl/VsZ1fhkbd3/Z+/O4+wq6nX/fx4io4EgGvkhUxiC\nzAToMKOg6AVRAQ1iRAREA15B9P7gisPRiBPKOSKggIEDKIJwmDQMEhRBIlPSCRkgjJIoBFQQjQQi\nQ3juH6ua7Gx6zt7pdPfzfr32q/euVavqu1YHdr6pWlU3Aye0fZDU1YIbvwMOlfTmUn+dmmM/Ay4D\nLuoqcNsTqaaiHWn7X8BcSYeWNiVph/J+M9v32P4a1ajNhqWJ90hapzxLdTDVSNdk4GBJa5SE4pBS\n1i5JKwEb2r4V+CLVVL2hVPf1hPKsE5J27Op6akwCjin9t63295bS9rMludoGGN2DNus9BGzSkxPK\nqN6JwMllumBntqCahhoRERER0S0r0ghW/TNYN9nu1lLttm+WtBVwV8kFFgIfpxqhqa03X9J3gCnA\ns8CDwIJy+HPAjyXNorovtwPH0QHb90v6NvB7SYuppsIdVQ5fCnwL+EV34gdOBS6TdD7VogrnSvoq\nsDJwOdVzYqerWnFQwC2lbFS5lquppr793HYrvLaq35TS/gW27y0jeu0ZAvxc0rDS/lm2/ynpm8AP\ngVklCZsLvL87F2T7RlULdNxdfifPAR8DbgDGSZpDlSD1eoU+2/+S9LikTWzPLcX1z2B9A7iu7ryp\nkh4EPkLnv6N9S7yd2m79YbRmz5+IiIiIoFq2vK9jWK4kDbW9sIxgXQtcaPvaBvcxBjjI9hGNbLed\nfo4CWmwf38x+VmRltG8b2+Mb3K6oRv0OtL2gs7otLS1ubW1tZPcRg4akabZb+jqOiIEq31ERvdfb\n76gVaQRreRlfngNajWpa4C+7qN8jks6mWtzhdcuKR1NcRTXtsNHeCny/q+QqIiIiIqLWoEuwbJ/U\nda1lav+Erms1rK+LqZatH7RcDcFe0IR2/8qS1SsjIiIiIrploCxyERERERER0eeSYEVERERERDRI\nEqyIiIiIiIgGaXiCJWl1SV+SdF75vLmkAxrdT0RERERExIqmGYtcXAjMBvYqn58ErgR+3YS+Ivrc\n7PkLGHFKl9tlxXIwL/uRRURERB9rxhTBkba/A7wMYPsFqs1rBwRJiyXNqHmNkNQi6awGtH2wJJcN\netvKRki6b1nbXsa4xkuaX653jqSxy9DWPpKub2R8zVJ+H1v3dRwRERER0X80I8F6SdJqgAEkbQK8\n1IR++soi26NqXvNst9r+XH3FsplxT4wF/lB+9kov+uyuM2yPAg4CfiJp5Sb1syI5GEiCFRERERHd\n1owE61TgJmADST8FbgW+1IR+Vhi1ozJltOcSSXcAl0gaIul0SVMlzZJ0bAdtDKWaVnkM8NEO6oyQ\nNFnS9PLao6b/yZImAnNKvQclXSzpYUmXStpP0h2SHpG0S2+v1fYjwAvAm0rfm0m6SdK0EsOWpfxi\nSedJai0xvL+d69lF0l2S7pV0p6S3l/Ihkv5T0n3lnp1QyneW9PvS1yRJ65Xy2ySdUfp6QNJoSdeU\na/1WTX8flzSljMT9RNKQUr5Q0rclzZR0t6R1y739IHB6qb9Zb+9ZRERERAweDR/tsH2TpGnAHlRT\nA0+2/bdG99OHVpc0o7yfa/uQdupsDexle5GkccAC26MlrQrcIelm23PrzjkIuMn2w5L+Lmln29Pq\n6vwNeI/tf0saCfwCaCnHdgK2tT1X0ghgc+BQ4JPAVOBjVAncB4EvU43O9JiknYBHan6nE4DjbD8i\naVfgHOBd5dgIYBdgM+BWSZvXNfcgsLftVyTtB3wH+DAwrpw7qhxbp4yYnQ0cZPtpSYcB3y7XB/CS\n7RZJJwK/AnYGngX+KOkM4K3AYcCetl+WdA5wOPAz4I3A3ba/Iun7wKdtf6skrNfbvqqd+zCuxMmQ\ntYb35lZGRERExADUrOlkuwN7Uk0TXAxc16R++sKiMlWuMxNtLyrv3wtsL2lM+TwMGAnUJ1hjgTPL\n+8vL5/oEa2XgR5JGUd3XLWqOTalL2ubang0g6X7gFtuWNJsqeempL0g6uvT5gdLuUKpE+krptcfs\nVq05539svwo8IukxYEuWNgz4aUkWXa4PYD/gPNuvANh+VtK2wLbAb0pfQ4CnatqaWH7OBu63/VSJ\n8TFgQ6rkcmdgajl/daqEFaoprG3PhU0D3tPVzbA9gSq5ZNX1Rrqr+hERERExODQ8wZJ0NtUIzuWl\n6HOS3tPeM0oD2PM17wWcYHtSR5UlrUM16rOdJFMlD5Z0cl3VLwB/BXagmt757w76BHix5v2rNZ9f\npZ3fu6SLgB2BJ22/r50wz7D9n5I+CPx3mTK3EvDPThLO+sSj/vM3gVttH1JG3W7roB2o7uP9tnfv\n4Hjt9dVf+xvK+T+13d501Zdtt8W2mOb9w0NEREREDHDNeAZrP2A/2+fbPh/Yn26MCAxgk4DPtC0K\nIWkLSW+sqzMGuMT2xrZH2N6QaoRr77p6w4CnyqjQEVSJWEPYPros2tFeclVbbyLQChxp+1/AXEmH\nAqiyQ031QyWtVJKxTYGH2rme+eX9UTXlvwGOVVmwoySgDwHDJe1eylaWtE0PLvEWYIykt7a1KWnj\nLs55DlizB31ERERExCDXjH+pnwtsADxePq8H/LEJ/fQXF1BNyZuuam7a07z++aexwPfqyq5up/wc\n4GpJn6BaSKR+1Gp5ORW4TNL5VM8xnSvpq1RT/C4HZpZ6fwamAGtRPaf175qphADfp5oi+FWgdiOp\nC6imIs6S9DJwvu0flWmWZ0kaRvVn94fA/d0J2Pac0s/Nklai2kbgs8CfOjntcuB8SZ8Dxthu98/x\ndusPozX7L0VEREQEoCUzoxrUoPQ7qoUN7qaaErYb1V+yFwDY/lBDO4wVkqSL6WCBiIGmpaXFra2t\nfR1GRL8kaZrtlq5rRgxskvanehZ7CHCB7dPaqbMP1T8urgw8Y/udXbWb76iI3uvtd1QzRrC+3YQ2\nIyIiIgaksm3Ij6keqXiCakGmibbn1NRZm2omy/62/9w25T0iVjzNSLC2AC6zvaAJbUc/Yfuovo4h\nIiKin9gFeNT2YwCSLqfavmVOTZ2PAdfY/jPAANsCJ2JAacYiFxtTPW90WdnbKCIiIiI6tj5Lnl2H\nahRr/bo6WwBvknSbpGnleex2SRonqVVS69NPP92EcCOiMw1PsGyfQrXP06XAcZIekXRqWYY7IiIi\nInruDVT7OR4I/C/gPyRt0V5F2xNst9huGT58+PKMMSJozggWZRnxeeX1KtVKgr+S9N1m9BcRERHR\nj80HNqz5vAFLtjFp8wQwyfbztp8BbqfaFzMiVjANT7AkfVbSFKqVcKYB29v+NNUmtoc1ur+IiIiI\nfm4qMFLSJpJWAT4KTKyr8ytgL0lvkLQGsCvwwHKOMyK6oWGLXEh6g+1XgLcBY+v3DLL9qqQPNqq/\niBXF7PkLGHHKDV1XjKabl/3IIqIfsv2KpOOBSVTLtF9o+35Jx5Xj59l+QNJNwCyq2UEX2L6v76KO\niI40chXBKcBOtr/SUYX8j2BpkhYDswEBi4Hjbd/Zg/NHUO01tW2D47oYeCfV3mWvAp+1fVcPzh8P\nLLT9n3XlpwK32/5tA2KcBzxue++ashnAGzq7H+We7WH7smWNISIiolFs3wjcWFd2Xt3n04HTl2dc\nEdFzjZwiqAa2NVgssj3K9g7Al4DXPaMmqRlL6XfHybZHAacAP+nuSZ3Fa/trjUiuaqwpacPS71bd\nPGcE1VK33daHv4OIiIiI6GcamWANl/R/Ono1sJ+Bai3gH1Dt1C5psqSJlD0wyn28r7w+X3+ypE0l\n3StptKQhkk6XNFXSLEnH1rR7m6SrJD0o6VJJXSXGtwObl/M/XdqcKenqMgccSRdLOk/SPcD36+L6\ntKRfS1q91BtTyudJ+oak6ZJmS9qylA+X9BtJ90u6QNKfJL2lg9j+hyXP9Y0FflHTb7v3ADgN2FvS\nDElf6OJeLfU7iIiIiIjoSiMTrCHAUGDNDl7xequXv+g/CFwAfLPm2E7Aiba3kLQzcDTVA627AZ+W\ntGNbRUlvB64GjrI9FTgGWGB7NDC61N+kVN8R+DywNbApsGcXMX6AahojVBscji4jbg+UftpsQDX1\n7rVkuswnfz9wsO1F7bT9jO2dgHOBk0rZ14Hf2d4GuArYqJPYrgY+VBPndTXHOroHpwCTy8jhGZ3U\ng5rfQX3HtXuMLH4he2pHRERERKWRU5+esn1qA9sbDBaVaXhI2h34maS254em2J5b3u8FXGv7+VL3\nGmBvqhWGhlOtLPQh220jLe8Ftm8bLQKGUe1N9lJp94nSzgyqKXN/aCe20yV9FXiaJYnUtpK+BaxN\nlUxPqql/pe3FNZ8/QbVp4sG2X+7g+q8pP6exJFHaCzgEwPZNkv7RwbkAfwf+IemjVAnfCzXHOrsH\ndLNe7e9gKbYnABMAVl1vpDuJMSIiIiIGkUYmWHkGaxnYvqtMhWvbEfD5bp66APgzVWLSlmAJOMF2\nbQKEpH2AF2uKFtPxn4GTbV9VV3YxVcI0U9JRwD41x+rjnQ2MohrZajdJqYmlszi6cgXwY+CouvLO\n7kF363X3dxARERERATR2iuC7G9jWoFOeQRpCNSpTbzJwsKQ1JL2RaoRncjn2Uvn8CUltizdMAj4j\naeXS9hblvGW1JvBUaffwLureCxwLTJT0th70cQfwEQBJ7wXe1EX9a6me+5pUV97RPXiOpaesNute\nRURERMQg1LARLNvPNqqtQWT1Mk0PqpGUI20vrl93wvb0snT6lFJ0ge17y5Lj2H5e0vuB30haSPU8\n1whgelnE4mng4AbE+x/APaW9e+ji2Trbf5B0EnCDpPd0s49vAL+QdARwF/AXqqSooz6eA74HUHff\nOroHs4DFkmZSjcid2UG9bttu/WG0Zv+liIiIiABk5/GRWHFIWhVYXDZd3B04t+05tRVVS0uLW1tb\n+zqMiH5J0jTbLX0dR8RAle+oiN7r7XdUI6cItgXyve6URXRgI2BqGWE6C/h0H8cTEREREdFtDU+w\ngPamgh3QhH5iALL9iO0dbe9QloSf2tcxRURERER0V8OewZL0GeB/A5tKmlVzaE2qhQsiIiIiIiIG\ntEYu034Z8Gvgu1SbubZ5LgtgRERERETEYNDIVQQXUO3JNFbSEGDd0v5QSUNt/7lRfUVERERERKyI\nGjmCBYCk44HxwF+BV0uxge0b3VdERERERMSKpOEJFvB54O2229swN2LAmT1/ASNOuaGvwwhgXvYj\ni4iIiD7WjFUEH6eaKhjRbZLeLGlGef1F0vyaz6s0qI8NJV3RiLYiIiIiItrTjBGsx4DbJN0AvNhW\naPsHTegrBogy4jkKQNJ4YKHt/2xwH48DhzWyzYiIiIiIWs0Ywfoz8BtgFaol2tteEb0i6TpJ0yTd\nL+lTpewNkv4p6TRJMyXdJemt5djPJZ0p6U5Jj0k6pJRvLmlGef8pSVdJmiTpEUnfrenvWEkPS7pH\n0gWSftgX1x0RERER/U/DR7Bsf6PRbcagd6TtZyWtAbRKuhp4DhgG/N72KZJ+AHwSOK2c81ZgT2A7\n4H+Aa9tpdwdgZ+Bl4GFJZwNDqLYZ2Al4HrgNmNKsC4uIiIiIgaWRGw3/0PbnJV1HtWrgUmx/sFF9\nxaDzBUltf342ADYDZgCLbP+6lE8D9q4555e2DcyStH4H7f7W9r8AJD0IbFTa/53tf5Tyq0r5UiSN\nA8YBDFlr+LJcW0REREQMII0cwbqk/GzoczMxuEnaD3gHsJvtRZL+AKxWDr9UU3UxS/95frHmvTpo\nvrZO/fmdsj0BmACw6nojX/cPChERERExODVyo+Fp5efvG9VmBNU0wGdLcrUNMLrJ/U0Bvi9pbaop\ngh8CWpvcZ0REREQMEM3YaHgk8F1ga5aMNGB700b3FYPCDcA4SXOAh4B7mtmZ7T9LOh2YCjxb+sy2\nAxERERHRLaoeU2lgg9UUrq8DZwAfAI4GVrL9tYZ2FNEkkobaXihpZeBXwLm2r+uofktLi1tbM8gV\n0RuSptlu6es4IgaqfEdF9F5vv6OasUz76rZvoUre/mR7PHBgE/qJaJZvSroXmEU1gnV9H8cTERER\nEf1EMzYaflHSSsAjko4H5gNDm9BPRFPY/kJfxxARERER/VMzRrBOBNYAPke1x9ARwJFN6CciIiIi\nImKF0oyNhqeWtwupnr+KiIiIiIgYFBq50XC7Gwy3yUbDEREREREx0DVyBCsbDEdERERExKDWyI2G\nX9tgWNIqwJZUI1oP2X6pUf1ERERERESsqJqx0fCBwHnAHwEBm0g61vavG91X9I6kxcBsYGXgFeBn\nwBm2X21Q+/OAFtvPSLrT9h6d1D0KuNn2k+0cuxh4J9VGv6sBv7D9jXLsAuAHtuc0KOaFtnu12uXs\n+QsYccoNjQgjltG807IjRERERPStZizT/l/AvrYfBZC0GXADkARrxbHI9igASW8FLgPWotogukuS\n3mD7le7U7Sy5Ko4C7gNel2AVJ9u+StJqwBxJP7M91/anutN/RERERMTy1Ixl2p9rS66Kx4DnmtBP\nNIDtvwHjgONVGSLpdElTJc2SdCyApH0kTZY0EZhTyj4uaYqkGZJ+ImlIffuSFta8/6Kk2ZJmSjpN\n0higBbi0tLF6J6GuVn4+X9q6TVJLeb+/pOml3VskrSTpEUnDy/GVJD0qabikdSVdW+rOlPS6BFDS\nyTXX/41e3NaIiIiIGKSaMYLVKulG4H+onsE6FJgq6UMAtq9pQp+xDGw/VpKjtwIHAQtsj5a0KnCH\npJtL1Z2AbW3PlbQVcBiwp+2XJZ0DHE413fB1JB1Q2t7V9guS1rH9bNmM+iTbrR2Ed7qkrwKbA2eV\nhLC23eHA+cA7Slzr2H5V0s9LPD8E9gNm2n5a0hXA720fUq55aF177wVGArtQTXGdKOkdtm/v7v2M\niIiIiMGrGQnWasBfqZ6dAXgaWB34AFXClQRrxfZeYPsyugQwjCrheAmYYntuKX831UbSUyVB9Tv+\nGx3bD7jI9gsAtp/tZjxtUwSHArdI2sP2nTXHdwNub4urpt0LgV9RJVifBC4q5e8CPlHqLqZ6vqv+\n+t8L3Fs+D6W6/qUSLEnjqEb+GLLW8G5eSkREREQMdM3YaDibC/czkjYFFlMlSAJOsD2prs4+lOl5\nbUXAT21/aXnEaHuhpNuAvYA7u6iO7ccl/VXSu6hGow7vZlcCvmv7J120PwGYALDqeiM73P8tIiIi\nIgaXhj+DJWkTST+QdI2kiW2vRvcTjVGm2J0H/Mi2gUnAZyStXI5vIemN7Zx6CzCmLJKBpHUkbdxJ\nV78Bjpa0Rlv9Uv4csGY34nwDsCvV6pS17gbeIWmTunYBLgB+DlxZRqva4v5MqTtE0rC69iYBnywj\nZkhav+0aIyIiIiK60owpgr8E/hu4DmjIst/RcKtLmsGSZdovAX5Qjl0AjACmq5r79zRwcH0DtueU\nZ6NulrQS8DLwWeBP7XVo+yZJo6ie0XsJuBH4MnAxcJ6kRcDuthfVndr2DNYqVMnRUlNMy3NV44Br\nShx/A95TDk+kmhp4Uc0pJwITJB1DNWr3GeCumvZuLs+X3VWmPi4EPk7n0x8jIiIiIgBQNWjRwAal\ne2zv2tBGI3qhrDJ4hu29m9lPS0uLW1s7WqMjIjojaZrtlr6OI6KvSdofOBMYAlxg+7QO6o2m+ofB\nj9q+qqt28x0V0Xu9/Y5qxgjWmZK+DtwMvNhWaHt6E/qKaJekU6hGp7r77FVERESfKKva/phqBsYT\nVAtITbQ9p51636P6O1ZErKCakWBtBxxBtVpb2xRBl88Ry0X5l792//UvIiJiBbML8KjtxwAkXU61\ntcmcunonAFcDo5dveBHRE81IsA4FNrX9UhPajoiIiBho1gcer/n8BNXCTq+RtD5wCLAvSbAiVmgN\nX0UQuA9YuwntRkRERAxWPwS+aLvLBcQkjZN49DluAAAgAElEQVTUKqn16aefXg6hRUStZoxgrQ08\nKGkqSz+D9cEm9BURERHR380HNqz5vEEpq9UCXF5WuH0L8D5Jr9j+ZX1jtXs1trS0ZK/GiOWsGQnW\n15vQZkRERMRANRUYWfZ0nA98FPhYbQXbm7S9l3QxcH17yVVE9L2GJ1i2fy9pXZbMD55iO3sIRURE\nRLTD9iuSjqfa7H4IcKHt+yUdV46f16cBRkSPNDzBkvQR4HTgNkDA2ZJO7s5eDYONpK9Q/QvVYqoV\nF4+1fc9y6vttwFm2xyxDG+sBPwXGUf1L2rYNiGsf4CTb71/WtnrQ30u27+xtG7PnL2DEKTc0Lqjo\ntXmnHdjXIURE9IrtG4Eb68raTaxsH7U8YoqI3mnGFMGvAKPbRq0kDQd+CyTBqiFpd+D9wE62X5T0\nFmCV5dW/7SeBXidXxf5U/9rWn+0DLAR6nWBFRERERLRpxiqCK9VNCfx7k/rp79YDnrH9IoDtZ4D1\nJV0DIOkgSYskrSJpNUlte2NsJukmSdMkTZa0ZSkfLulqSVPLa89SPl7SJZLukvSIpE+X8hGS7ivv\nj5J0TWn3EUnfbwtS0jGSHpY0RdL5kn5Ucw37A7+uvagu2jq3rGp0v6Rv1JTvL+lBSdOBD9WUv1HS\nhaXveyUdVMpXl3S5pAckXSvpHkkt5djCmvPHlHnqSPpAqXevpN9KWlfSCOA44AuSZkjau6P7GBER\nERHRHc0YwbpJ0iTgF+XzYdT9JTyAahf2r0l6mGqE7wrgDmBUOb431ZL3o6l+T21TBycAx9l+RNKu\nwDlUmzifCZxh+w+SNqIaWdqqnLM9sBvwRuBeSe3NZxsF7Ei18uNDks6mmrr4H8BOwHPA74CZ8Npu\n8m+3PackKp22Zftx4Cu2ny3n3iJpe+Bh4PxyDY+W+9DmK8DvbH9S0trAFEm/BY4FXrC9VWljemc3\nuvgDsJttS/oU8H9t//+SzgMW2v7Pcl2XdXIfIyIiIiI61YxFLk6W9CFgr1I0wfa1je6nv7O9UNLO\nVInUvlSJxSnAHyVtRbWr+w+Ad1A98DpZ0lBgD+DKskwrwKrl537A1jXla5X6AL+yvQhYJOnW0vaM\nupBusb0AQNIcYGOqZWB/b/vZUn4lsEWpvytLkr567bX1OPARSeOo/tytB2xNNbo51/Yjpf7PqZ7p\nAngv8EFJJ5XPqwEblXtyVrmPsyTN6iCOWhsAV5TnxlYB5nZQr937aHthbaVyHeMAhqw1vBvdR0RE\nRMRg0LAES9LmwLq277B9DdA21W0vSZvZ/mOj+hoobC+mWgzkNkmzgSOB24EDgJepRrYupkqwTqZK\nRv5pe1Q7za1ENULz79rCkijU74HR3p4YL9a8X0zXfzYOAG7q4Njr2lK19OxJVM/n/aNM3Vutiz4E\nfNj2Q0sVLkl+2lN7bbXtnw38wPbEsrDF+A7Ob/c+vq6Tmj1GVl1vZPYYiYiIiAigsc9G/RD4Vzvl\nC8qxqCHp7ZJG1hSNAv4ETAY+D9xl+2ngzcDbgfts/wuYK+nQ0oYk7VDOvxk4oab92iTsoPIc15up\nFnWY2s0wpwLvlPQmSW8APlxz7N1UCWB3rQU8DyxQtYz/AaX8QWCEpM3K57E150wCTlDJqCTtWMpv\np+wPImlbqimQbf4qaStJKwGH1JQPY8mmjUfWlD8HrFnzubP7GBERERHRqUYmWOvanl1fWMpGNLCf\ngWIo8FNJc8oUt62pRlXuAdalSiIAZgGzbbeNkhwOHCNpJnA/cFAp/xzQImlWmZZ3XE1fs4BbgbuB\nb5YVBLtkez7wHWAK1fNh86gSpOHAv20/192LtT0TuJcqobqstEcZKRoH3FAWuahdIOWbwMrALEn3\nl88A5wJDJT0AnApMqznnFOB6qlUBn6opH081tXIa8ExN+XXAIW2LXND5fYyIiIiI6JSW/L19GRuS\nHrE9soNjj9revCEdRY9IGk/NIg69OH9oeV7sDcC1wIVUi2VsYPu0xkXae5Juo9o7q7Uv+m9paXFr\na590HdHvSZpmu6Wv44gYqPIdFdF7vf2OauQiF62SPm37/NrCsmLbtA7OiRXfeEn7UT3PdDPwSzcq\nK4+IiIiIGGAamWB9HrhW0uEsSahaqFZsO6TDs6KpbI9fxvNP6rpW37K9T1/HEBEREREBDUywbP8V\n2EPSvsC2pfgG279rVB8RERERERErsmbsg3Ur1YIKERERERERg0ojVxGMiIiIiIgY1JJgRURERERE\nNEgSrIiIiIiIiAZp+DNYMfBJ+grwMWAx8CpwrO17JH0emGD7hS7Ov42yb5WkeUCL7Wc6O6fm3KNK\n/ePrytcF/hvYkGpz4nm23yfpbcBZtsdIGgW8zfaNPbjcLs2ev4ARp9zQyCajl+addmBfhxARERGD\nXBKs6BFJuwPvB3ay/aKkt1AtxQ/VUv0/BzpNsJrkVOA3ts8scW4PYPtJYEypM4pq64CGJlgRERER\nEW0yRTB6aj3gGdsvAth+xvaTkj4HvA24VdKtAJLOldQq6X5J3+iqYUkflzRF0gxJP5E0pJQfLelh\nSVOAPTuJ64m2D7ZnlXNHSLpP0ipUSdhhpf3DJL1R0oWlz3slHVTO2aYmjlmSRvb2ZkVERETE4JIE\nK3rqZmDDkvCcI+mdALbPAp4E9rW9b6n7FdstwPbAO9tGldojaSvgMGBP26Ooph8eLmk94BtUidVe\nwNYdNPFj4L8l3SrpK2Vq4GtsvwR8DbjC9ijbVwBfAX5nexdgX+B0SW8EjgPOLHG0UJO4RURERER0\nJglW9IjthcDOwDjgaeCK8lxUez4iaTpwL7ANHSdHAO8u7U6VNKN83hTYFbjN9tMlSbqig7gmlfrn\nA1sC90oa3sXlvBc4pfR3G7AasBFwF/BlSV8ENra9qP5ESePK6Fzr4hcWdNFNRERERAwWeQYresz2\nYqqE5DZJs4EjgYtr60jaBDgJGG37H5IupkpgOiLgp7a/VNfOwT2I61ngMuAySdcD7wCmddHnh20/\nVFf+gKR7gAOBGyUda/t3dX1NACYArLreSHc3xoiIiIgY2DKCFT0i6e11zySNAv5U3j8HrFnerwU8\nDywoK/wd0EXTtwBjJL219LOOpI2Be6imF75Z0srAoR3E9S5Ja5T3awKbAX+uq1YbH8Ak4ARJKuft\nWH5uCjxWpj3+imqKY0RERERElzKCFT01FDhb0trAK8CjVNMFoRrRuUnSk7b3lXQv8CDwOHBHZ43a\nniPpq8DNklYCXgY+a/tuSeOppu39E5jRQRM7Az+S9ArVPxxcYHuqpBE1dW5lyZTA7wLfBH4IzCp9\nzqVaIfEjwBGSXgb+Anyne7cmIiIiIgY72ZndFLEsWlpa3Nra2tdhRPRLkqaVxXAiognyHRXRe739\njsoUwYiIiIiIiAZJghUREREREdEgSbAiIiIiIiIaJAlWREREREREgyTBioiIiIiIaJAkWBERERER\nEQ2SBCsiIiIiIqJBstHwCkbSYmB2TdHBwFuAT9j+3DK2fTBwLbCV7QdL2QjgetvbLkvbjVA2AH7Q\n9kc7OD6CDmKVdBtwku1WSTcCHyuHPmb7nFLnbcBZtsc0Mu7Z8xcw4pQbGtlk9NK80w7s6xAiIiJi\nkMsI1opnke1RNa95tlvbS64k9TRBHgv8ofzslV702d12twKGAHtLeuOytGX7fbb/CawN/O+a8icb\nnVxFRERERNRKgtUPSNpH0vXl/XhJl0i6A7hE0hBJp0uaKmmWpGM7aGMosBdwDNDhCJGkyZKml9ce\nNf1PljQRmFPqPSjpYkkPS7pU0n6S7pD0iKRdenGZY4FLgJuBg2pi2lnSTEkzgc/WlK8u6XJJD0i6\nFli95tg8SW8BTgM2kzSj3KMRku4rdVaTdJGk2ZLulbRvKT9K0jWSbirX8v1eXEtEREREDFKZIrji\nWb1MlQOYa/uQdupsDexle5GkccAC26MlrQrcIelm23PrzjkIuMn2w5L+Lmln29Pq6vwNeI/tf0sa\nCfwCaCnHdgK2tT23TNXbHDgU+CQwlWpK3l7AB4EvU01t7InDgPcAWwInAJeV8ouA423fLun0mvqf\nAV6wvZWk7YHp7bR5Sol5FLw2xbDNZwHb3k7SlsDNkrYox0YBOwIvAg9JOtv24z28noiIiIgYhJJg\nrXgWtSUEnZhoe1F5/15ge0ltU9+GASOB+gRrLHBmeX95+VyfYK0M/EjSKGAxsEXNsSl1Sdtc27MB\nJN0P3GLbkmYDI7qIfymSWoBnbP9Z0nzgQknrAK8Ca9u+vVS9BDigvH8HcBaA7VmSZvWkT6pk8Oxy\n/oOS/sSS673F9oIS2xxgY2CpBKsktuMAhqw1vIddR0RERMRAlQSrf3q+5r2AE2xP6qhySVbeBWwn\nyVTPOlnSyXVVvwD8FdiBavrovzvoE6rRnTav1nx+lXb+XEm6iGpU6Enb76s7PBbYUtK88nkt4MPA\nlR1dU5PVXtti2rke2xOACQCrrjfSyymuiIiIiFjB5Rms/m8S8BlJKwNI2qKdRSLGAJfY3tj2CNsb\nUo1w7V1XbxjwlO1XgSOoErGGsH10WbRjqeRK0krAR4DtSmwjqKYzji0LVfxT0l6l+uE1p95OWSlQ\n0rbA9u10+xywZgchTW5rr0wN3Ah4qDfXFhERERHRJglW/3cBMAeYXhZw+AmvH3EZS7U8e62ref1q\ngucAR5YFJbbk9aNWzbA3MN/2kzVltwNbS1oPOBr4cXkuTTV1zgWGSnoAOJXXT3fE9t+pnkm7r+75\nLaiudaUypfEK4CjbL9a3ERERERHRE7IzuyliWbS0tLi1tbWvw4jolyRNs93Sdc2IgU3S/lTPSg8B\nLrB9Wt3xw4EvUv1j43PAZ2zP7KrdfEdF9F5vv6MyghURERHRhyQNAX5MtZDT1sBYSVvXVZsLvNP2\ndsA3Kc8BR8SKJwlWRERERN/aBXjU9mO2X6Ja7feg2gq277T9j/LxbmCD5RxjRHRTEqyIiIiIvrU+\nS28H8kQp68gxwK+bGlFE9FqWaY+IiIjoJyTtS5Vg7dVJndf2atxoo42WU2QR0SYjWBERERF9az6w\nYc3nDUrZUiRtT7V68EFlpdx22Z5gu8V2y/DhwxsebER0LglWRERERN+aCoyUtImkVYCPAhNrK0ja\nCLgGOML2w30QY0R0U6YIRkRERPQh269IOh6YRLVM+4W275d0XDl+HvA14M3AOZIAXskWBxErpiRY\nDSBpMTC7puhg4C3AJ2x/bhnbPphqk+CtbD9YykYA19vedlnaXsa4xgNfB0bafrSUfR44Axhtu1ub\nbkg6CmixfXz5InnB9s8kbUm1ipKBMcAltvfoRZwHAw/bnlM+nwrcbvu3PW2rI7PnL2DEKTc0qrlY\nBvNOO7CvQ4iI6BXbNwI31pWdV/P+U8CnlndcEdFzSbAaY5HtUXVl84DXJRmS3mD7lR60PRb4Q/n5\n9d4E14s+u2s21TSGb5XPhwL397ax2i8SqiT1Ktttbfc4uapp53pgTunja72NLyIiIiKiK3kGq0kk\n7SPp+vJ+vKRLJN0BXCJpiKTTJU2VNEvSsR20MZRqlaBjqBKZ9uqMkDRZ0vTy2qOm/8mSJgJzSr0H\nJV0s6WFJl0raT9Idkh6RtEsvLvOXlH06JG0GLACeqYltrKTZku6T9L2a8qNLDFOAPWvKx0s6SdL7\ngM8Dn5F0azm2sKbeF0u7MyWdVso+Xe7nTElXS1qj3IsPAqdLmiFps3L9Y8o575Z0b2nrQkmrlvJ5\nkr5R7ufsMpoWEREREdGlJFiNsXr5C/wMSdd2UGdrYD/bY6kSpgW2RwOjgU9L2qSdcw4CbioPs/5d\n0s7t1Pkb8B7bOwGHAWfVHNsJONH2FuXz5sB/AVuW18eoEriTgC/34Hrb/At4XNK2VAngFW0HJL0N\n+B7wLmAUMFrSwZLWA75BlVjtRXVfllKmSZwHnGF739pjkg6gui+72t4B+H45dI3t0aXsAeAY23dS\nPSR8su1Rtv9Y085qwMXAYba3oxrN/UxNV8+Ue3puuT8REREREV1KgtUYi8pf4EfZPqSDOhNtLyrv\n3wt8QtIM4B6qh1ZHtnPOWKrnkCg/x7ZTZ2XgfEmzgStZOmGZYntuzee5tmfbfpVqKt8ttk011W9E\nl1fZvsupkqu2Z8XajAZus/10mZ54KfAOYNea8peoScq6aT/gItsvANh+tpRvW0bsZgOHA9t00c7b\nqe5H20pMPy3xtbmm/JxGO/dG0jhJrZJaF7+woIeXEBEREREDVZ7BWn6er3kv4ATbkzqqLGkdqtGf\n7SSZalUhSzq5ruoXgL8CO1AlzP/uoE+AF2vev1rz+VXa+bMg6SJgR+BJ2+/rINTrgdOBVtv/Kisb\n9YWLgYNtzywLZ+yzjO213ZvFtHNvbE8AJgCsut5IL2NfERERETFAZASrb0yier5oZQBJW0h6Y12d\ntpXzNrY9wvaGwFxg77p6w4CnyqjUEVSJWEPYPrqMynWUXFFGkr4IfLvu0BTgnZLeImkI1ejb76lG\n7N4p6c3l+g/tYVi/AY6WtAa8logCrAk8Vdo8vKb+c+VYvYeAEZI2L5+PKPFFRERERPRaEqy+cQHV\nqnbTJd0H/ITXj5KMZekpdwBX8/ppgucAR0qaSfVcVf2oVdPZvtz29Lqyp4BTgFuBmcA0278q5eOB\nu4A7qJ6X6klfN1E9V9Vapli2PR/1H1TJ2x3AgzWnXA6cXBaz2KymnX8DRwNXlmmFr1I99xURERER\n0WuqHsGJiN5qaWlxa2u3tv2KiDqSpmWz1IjmyXdURO/19jsqI1gRERERERENkgQrIiIiIiKiQZJg\nRURERERENEgSrIiIiIiIiAZJghUREREREdEgSbAiIiIiIiIaJAlWREREREREg9RvbhsRPTR7/gJG\nnHJDX4cRwLzTDuzrECIiImKQywjWMpK0sO7zUZJ+VN4fJ+kTXZz/Wv3lSdJuku6RNEPSA5LGl/IP\nSjplOfQ/T9Ls8poj6VuSVmtCP/tIur68Xy7XFhERERGDV0awmsj2eX0dQyd+CnzE9kxJQ4C3A9ie\nCExcTjHsa/sZSUOBCcBPgCOb1dlyvraIiIiIGIQygtVEksZLOqm8Hy1pVhkxOl3SfTVV3ybpJkmP\nSPp+qX+opB+U9ydKeqy831TSHeX91yRNlXSfpAmqbCZpek0MI2s/13gr8BSA7cW255T6tSNwm0m6\nu4wyfatttK6MCt0m6SpJD0q6VJJ6e59sLwSOAw6WtI6koZJukTS99H1Q6XdEGW07X9L9km6WtHo3\n7m/bvai9toslnSXpTkmPSRpTyleSdE65rt9IurHtWEREREREV5JgLbvVy1/qZ0iaAZzaQb2LgGNt\njwIW1x0bBRwGbAccJmlDYDKwdzm+N/B3SeuX97eX8h/ZHm17W2B14P22/wgskDSq1Dm69F3vDOAh\nSddKOraD6XlnAmfa3g54ou7YjsDnga2BTYE9O7jubrH9L2AuMBL4N3CI7Z2AfYH/qkngRgI/tr0N\n8E/gw6W8s/vbkfWAvYD3A6eVsg8BI6iu6whg9/ZOlDROUquk1sUvLOj2dUZERETEwJYEa9ktsj2q\n7QV8rb6CpLWBNW3fVYouq6tyi+0Ftv8NzAE2tv0XYKikNYENyznvoEqwJpfz9i3PUc0G3gVsU8ov\nAI4uU/8Oa6c/bJ8KtAA3Ax8Dbmrn2nYHruwg5im2n7D9KjCDKilZVqr5+R1Js4DfAusD65Zjc23P\nKO+nASO6cX878kvbr5bRu7b29wKuLOV/AW5t70TbE2y32G4Zssawbl9gRERERAxsSbBWDC/WvF/M\nkmfj7qQagXqIJSNauwN3lBGnc4AxZYTpfKBtFOpq4ACqkZlptv/eXqe2/2j7XODdwA6S3tyAmAGQ\ntGHNyN5xXTVWEskRwMPA4cBwYOeStP615to67beHatvq9RTHiIiIiIg2SbCWA9v/BJ6TtGsp+mg3\nT50MnEQ1JfBequlyL9pewJKEo22RiNeeEyojYZOAc2l/eiCSDqybdreYaspdrbtZMgWvuzG3xfB4\nzchep4t9lPjPoRpR+gcwDPib7Zcl7Qts3EVfvb2/7bkD+HB5FmtdYJ9laCsiIiIiBpmsIrj8HAOc\nL+lV4PdAdx7cmUw1PfB224slPQ48CFVSIel84D7gL8DUunMvBQ6hmgLYniOAMyS9ALwCHF76qK3z\neeDnkr5CNYWw0Q8b3VqSvJWAa4Fv1sR+XZn62Eq55i705v6252qqEb05wOPA9K7a2m79YbRm/6WI\niIiIAGS7r2MYFCQNLavlUfZiWs/2iU3s7yRgmO3/WIY21qB6xsySPgqMtX1Qw4JsoEbe37a2ypTJ\nKcCe5XmsdrW0tLi1tbVXcUcMdpKm2W7p6zgiBqp8R0X0Xm+/ozKCtfwcKOlLVPf8T8BRzepI0rXA\nZlQLXyyLnYEflVGmfwKfXNbYmqiR9/f6snDGKsA3O0uuIiIiIiJqJcFaTmxfAVyxnPo6pEHtTAZ2\naERbzdbI+2t7n0a0ExERERGDTxa5iIiIiIiIaJAkWBEREREREQ2SBCsiIiIiIqJBkmBFREREREQ0\nSBa5iFhGs+cvYMQpN/R1GAHMy35kERER0ccygtVPSVrYTtlxkj5R3h8l6W0N7G8fSXs0qr122r9N\n0kOSZkqaKmlUs/rqQUwNvYcRERERMfAlwRpAbJ9n+2fl41FAj5IDSZ2NaO4D9CjB6qK99hxuewfg\nHOD0Hp7bDEfRw3sYEREREYNbEqwBRNJ4SSdJGgO0AJdKmiFpdUk7S/q9pGmSJklar5xzm6QfSmoF\nTpT0AUn3SLpX0m8lrStpBHAc8IXS3t6SLi79tPW9sPzcR9JkSROBOaXs45KmlHN/ImlIF5dyF7B+\nTdvvlXSXpOmSrpQ0tJTvL+nBUn6WpOtr70PN+feVa2g3lvK6uNSbLekL7d3D3v9mIiIiImKwSII1\nANm+CmilGhEaBbwCnA2Msb0zcCHw7ZpTVrHdYvu/gD8Au9neEbgc+L+25wHnAWfYHlU2IO7MTsCJ\ntreQtBVwGLBniWUxcHgX5+8P/BJA0luArwL72d6pXNf/kbQacD7wAWBn4P/r6r50EssoYH3b29re\nDrio/h7aXlTX1jhJrZJaF7+woKuuIyIiImKQyCIXg8PbgW2B30gCGAI8VXP8ipr3GwBXlBGuVYC5\nvehviu22895NlQBNLX2vDvytg/MulbQKMJQq6QHYDdgauKOcvwrVCNeWwFzbjwBI+jkwrou4Oorl\nOmBTSWcDNwA3d3WBticAEwBWXW+ku6ofEREREYNDEqzBQcD9tnfv4PjzNe/PBn5ge6KkfYDxHZzz\nCmUEVNJKVIlPe+0J+KntL3UjzsOBaVTPX50NfKic/xvbY5e6oM4XwXgttmK1rmKRtAPwv6imQn4E\n+GQ34o2IiIiIWEqmCA5czwFrlvcPAcMl7Q4gaWVJ23Rw3jBgfnl/ZAftAcyjGg0C+CCwcgft3QKM\nkfTW0vc6kjbuKGjbBv4D2E3SlsDdwJ6SNi/nv1HSFsCDwAhJm5VTaxOweVTTFJG0E7BJZ7GUaYgr\n2b6aajriTh1cc0REREREpzKC1X+tIemJms8/qDt+MXCepEXA7sAY4CxJw6h+7z8E7m+n3fHAlZL+\nAfyOJcnJdcBVkg4CTqB6/ulXkmYCN7H0qNVrbM+R9FXg5jLS9TLwWeBPHV2Y7UWS/gs42fYxko4C\nfiFp1VLlq7YfljQOuEHSC8BkliRDVwOfkHQ/cA/wcBexLAIuKmUAbSNcS93D+uew2my3/jBas/9S\nRERERACqBgwi+rcynfEk2+9f3n23tLS4tbV1eXcbMSBImma7pa/jiOhrkvYHzqR6TvoC26fVHVc5\n/j7gBeAo29O7ajffURG919vvqEwRjIiIiOhDZfuSHwMHUC3sNFbS1nXVDgBGltc44NzlGmREdFsS\nrBgQbN/WF6NXERERDbAL8Kjtx2y/RLVNykF1dQ4CfubK3cDabXtaRsSKJc9gRSyjadOmLZT0UF/H\n0QBvAZ7p6yCW0UC4BhgY19Hda+hw0ZuIQWR94PGaz08Au3ajzvosve0KUO3VyJKtS16UdF/jQm2K\n/vL/vP4QZ3+IEfpPnG/vzUlJsCKW3UMD4RkSSa39/ToGwjXAwLiOgXANEf1V7V6N/eG/xf4QI/SP\nOPtDjNC/4uzNeZkiGBEREdG35gMb1nzegCVbpvSkTkSsAJJgRURERPStqcBISZtIWgX4KDCxrs5E\nqi1IJGk3YIHt100PjIi+lymCEctuQl8H0CAD4ToGwjXAwLiOgXANEcuF7VckHQ9Molqm/ULb90s6\nrhw/D7iRaon2R6mWaT+6m833h/8W+0OM0D/i7A8xwgCPM/tgRURERERENEimCEZERERERDRIEqyI\niIiIiIgGSYIV0U2S9pf0kKRHJZ3SznFJOqscnyVpp76IszPduIZ9JC2QNKO8vtYXcXZG0oWS/tbR\nvi794fcA3bqO/vC72FDSrZLmSLpf0ont1OkXv4+I/qy/fD91I87DS3yzJd0paYcVLcaaeqMlvSJp\nzPKMr6b/LuMs3yMzyv+ff7+8YywxdPU7HybpOkkzS5zdfbawkTE2/u8VtvPKK68uXlQPHf8R2BRY\nBZgJbF1X533ArwEBuwH39HXcvbiGfYDr+zrWLq7jHcBOwH0dHF+hfw89uI7+8LtYD9ipvF8TeLi/\n/XeRV179/dVfvp+6GecewJvK+wOWd5zdibGm3u+oFh4Zs4Ley7WBOcBG5fNbV9A4vwx8r7wfDjwL\nrLKc42z43ysyghXRPbsAj9p+zPZLwOXAQXV1DgJ+5srdwNqS1lvegXaiO9ewwrN9O9X/gDuyov8e\ngG5dxwrP9lO2p5f3zwEPAOvXVesXv4+Ifqy/fD91GaftO23/o3y8m2qvrxUqxuIE4Grgb8szuBrd\nifNjwDW2/wxguy9i7U6cBtaUJGAo1ZiYzVoAAAMsSURBVPfiK8szyGb8vSIJVkT3rA88XvP5CV7/\nF8nu1OlL3Y1vjzIE/mtJ2yyf0BpqRf899ES/+V1IGgHsCNxTd2gg/T4iVkT95fuppzEcQzVqsDx1\nGaOk9YFDgHOXY1z1unMvtwDeJOk2SdMkfWK5RbdEd+L8EbAV8CQwGzjR9qvLJ7xu6/F/P9kHKyJq\nTaeaTrBQ0vuAXwIj+zimwarf/C70/9q5f9iawjiM498naSXEpgkD0kaEyaJBwoJBYmHo0IXEhhhs\nTQwMdjGJAbEIgzR0EI2NgcQiGmkiDSIVC4PGn6XpYzinIpSexnXuOc3zme499wzPyS/nvvd33ve+\n0mqKp7mnbc90O09EtJukvRQN1p5uZ1nARWDE9lwx6dJYPcB2YD+wEngs6Yntl92N9ZsDwDNgH7AJ\neCDpUdvHksxgRVTzDtjw0/v15bGlntNNi+azPWP7c/n6HtArqa++iB3R9DpU0pZaSOqlaK5u2B5d\n4JRlUY+IBmvL+FQpg6RtwBXgkO2PNWWbVyXjIHBL0htgCLgk6XA98X6oknMaGLf9xfYH4CFQ96Yh\nVXIeo1jKaNtTwGtga035qlry/ZMGK6Kap8BmSQOSVgDDwNgv54wBR8vdZnYBn2y/rzvoXyx6DZLW\nleugkbSD4jui7gHuXzW9DpW0oRZlvqvApO0LfzhtWdQjosHaMj5VGYM2AqPAkS7NtCya0faA7X7b\n/cBt4KTtO03LCdwF9kjqkbQK2EnxP9mm5XxLMcuGpLXAFuBVrSkXt+T7J0sEIyqwPSvpFDBOsSvO\nNdsvJB0vP79MsZvQQWAK+ErxVKYxKl7DEHBC0izwDRh2uYVOU0i6SbHDXp+kaeAc0AvtqMO8CtfR\n+FoAu4EjwISkZ+WxM8BGaFc9ItqqLeNTxZxngTUUs0IAs7YHG5ax66rktD0p6T7wHJgDrthecBvy\nbuYEzgPXJU1Q7NI3Us641eZ//K5Q88briIiIiIiIdsoSwYiIiIiIiA5JgxUREREREdEhabAiIiIi\nIiI6JA1WREREREREh6TBioiIiIiI6JA0WBERERERER2SBisiIiIiIqJDvgPh4folEdcmowAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30a8327b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of most Complaints per Borough\n",
    "borough_comp = df.groupby(['Complaint Type','Borough']).size().unstack()\n",
    "\n",
    "col_number = 2\n",
    "row_number = 3\n",
    "fig, axes = plt.subplots(row_number,col_number, figsize=(12,12))\n",
    "\n",
    "for i, (label,col) in enumerate(borough_comp.iteritems()):\n",
    "    ax = axes[int(i/col_number), i%col_number]\n",
    "    col = col.sort_values(ascending=True)[:15]\n",
    "    col.plot(kind='barh', ax=ax)\n",
    "    ax.set_title(label)\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization on processing time.\n",
    "#### The Processing Time in the dataframe is a datetime object, it is easier to convert the processing time into floats for calcuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "df['Processing Time Float'] = df['Processing Time'].apply(lambda x:x/np.timedelta64(1, 'D'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AADZg22YMMm4J/cUkDyVZ6O5nx6nvJVkYx+cleXCm24FR+9E4Xl1f6fNMknT3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\nMCEoAgAAMCEoAgAAMCEoAgAAMPH/ASjfR8Q1nQ+mAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30aea1198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histogram of Processing Time\n",
    "df['Processing Time Float'].hist(bins=30, figsize=(15,7));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Since datetime objects occurs in the dataframe, I can build a bar graph to show Incidents per month and other interesting informtation. This would allow easy discovery of noticible trends and seasonality.\n",
    "\n",
    "#### I can do this by adding a column to the data to keep track of year and months only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import datetime\n",
    "df['YYYY-MM'] = df['Created Date'].apply(lambda x: datetime.datetime.strftime(x, '%Y-%m'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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POdcf+KX3b8ysFzAC6O2d85yZhXrnPA9MBLp5tyPXnADsd851BZ4EHvOu1Qp4GEgH0oCH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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30aea12b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Incidents on a monthly basis\n",
    "monthly_incidents =  df.groupby('YYYY-MM').size().plot(figsize=(12,5), title='Incidents on a monthly basis');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AQgghhBBCCIuSmrV7SGkGGRYWxpo1axg0aBBaa4KDg+nXrx/29vZUqFCBli1b8vfffwPg\n5+eXOsdYcHAwPXr0oHjx4ri4uNCzZ0+2bt16z+NdvnyZa9eu0bRpUwACAgLSrW/bti2lSpXCycmJ\nOnXqcOrUqXw6cyGEEEIIIYQ1kGQtG5o2bUp0dDQXLlzIdLvixYtnWZaDgwPJycmpr7M7L1nRokVT\nf7e3tycxMTFb+wkhhBBCCCFskyRr2RAWFkZSUhJly5alRYsWBAUFkZSUxIULF/jjjz/w8/O7Y58W\nLVqwbNkybty4wfXr11m6dCktWrSgQoUKREVFERMTQ3x8PCtXrgSgdOnSlChRgp07dwIwf/78Aj1H\nIUQ23Lho6QiEEEII8QCRPmv3kNJnDYxBRWbNmoW9vT09evRg+/btNGjQAKUUkyZNomLFioSFhaXb\nv1GjRgwZMiQ1kXvuuedo2LAhAO+//z5+fn5UrlwZLy+v1H1+/PFHhg8fjp2dHS1btqRUqVIFdLZC\niCz9OQXWvQ/NRkG7D8FOnnUJIYQQIn8prXWBHtDX11fv2rUr3bLDhw9Tu3btAo3DGsXGxuLi4gLA\nxIkTiYyMZMqUKRaOKmfkvRSF0q6fYeWrUMYTLp2E+n2g21RwKGLpyIQQQghhg5RSIVpr36y2k0fD\nVmTVqlX4+PhQr149tm7dytixYy0dkhBi/yJYORpqtocRf0Gb/8L+BfDLMxB31dLRCSGEEKIQk2aQ\nVsTf3x9/f39LhyGESHH0d1j6H6jWDJ6ZZdSkPfEGlHCDFS/DzE7QfzGUqGDpSIUQQghRCEnNmhBC\n3E34n7BgEFSoC/3mQ5Fit9c17A8BQRBzAn5sB9HHLBenEEIIIQotSdaEECKjs3vgF38oXRUGLAGn\nknduU/NJGPIr3LoBP7aH038XfJxCCCGEKNQkWRNCiLQuHIE5PcG5DAxcBsVd771t5Ufh2bXgVApm\ndYEjqwsuTiGEEEIUepKsCSFEikunYHZ3sHOAQcugVOWs9ylbA55dB+W9YH4AhMzM9zCFEEII8WCQ\nZM1kb2+Pj48PDRo0oFGjRmzbtg2A8PBwnJ2d8fHxoU6dOgwaNIiEhITU/YKDg/Hz88PLywsvLy9m\nzJiRum7cuHEUK1aMqKio1GUpQ/OfPn0aT09PLl40Jtm9dOkSnp6ehIeHF8DZCiHucO0czO4GCddh\n4FIjCcsul3IweCXUaAO/vgKbJkABT4sihBBCiMJHkjWTs7MzoaGh7N27lwkTJvDOO++krqtRowah\noaHs37+fiIgIFixYAMC5c+cICAhg2rRphIWFERwczPTp01m1alXqvq6urkyePPmO41WpUoUXX3yR\nt99+G4C3336b559/Hg8Pj/w9USHEnW5cNJo+xkYZoztWrJfzMoq6GAOR+PSHLRPh11GQlJj3sQoh\nhBDigSHJ2l1cvXqVMmXK3LHc3t4ePz8/zpw5A8DUqVMZMmQIjRo1AozEbNKkSUycODF1n2HDhhEU\nFJRag5bW6NGj2bFjB19//TXBwcG88cYb+XRGQoh7io+FX/pAzDHoOw+qPJb7suwdjcmyW7wBu2dD\nUH+4dT3vYhVCCCHEA8Xq5ln78NeDHDqbtxPN1qlUkg+61M10m5s3b+Lj40NcXByRkZFs3Ljxjm3i\n4uLYuXMnU6ZMAeDgwYMMHjw43Ta+vr4cPHgw9bWLiwvDhg1jypQpfPjhh+m2dXR05PPPP6dDhw6s\nXbsWR0fH3J6iECI3EuKMfmZnQqDPbKjR+v7LVAra/hdKusGqN2BWVwhYAMXL3n/ZQgghhHigSM2a\nKaUZZFhYGGvWrGHQoEFos8/J8ePH8fHxoUKFCri5ueHt7Z2jskeNGsWsWbO4du3aHetWr16Nm5sb\nBw4cyJPzEEJkU1IiLH4WTm4xasNqd8nb8h97DvznwPkD8OOTcCk8b8sXQgghRKFndTVrWdWAFYSm\nTZsSHR3NhQsXgNt91qKjo3n88cdZsWIFXbt2pU6dOoSEhNCtW7fUfUNCQqhbN/05lC5dmoCAAKZO\nnZpueWhoKOvWrWPHjh00b96cvn374ubmlv8nKMSDLjkZVrwMYSuhw2fgE5A/x6ndBQYtN+Zs+9+T\nMGARuDXIn2MJIYQQotCRmrW7CAsLIykpibJl0zdbcnV1ZeLEiUyYMAGAESNGMHPmTEJDQwGIiYnh\nrbfeYsyYMXeU+dprrzF9+nQSE40BB7TWvPjii3z99ddUrVqVN998U/qsCVEQtIY1b8PeX6DVu9Dk\nhfw9XtUmMOx3sC8CP3eC43c2sRZCCCGEuBtJ1kwpfdZ8fHzw9/dn1qxZ2Nvb37Fd9+7duXHjBlu3\nbsXNzY25c+cyfPhwvLy8aNasGcOGDaNLlzubU7m6utKjRw/i4+MB+OGHH6hatSpPPvkkAC+99BKH\nDx9my5Yt+XuiQjzoNk+Av6ZDkxHQ8s4HK/mivBc8tw7KeMC8Z2BvUMEcVwghhBA2TekCngvI19dX\n79q1K92yw4cPU7t27QKNQ+QPeS+FVds+FX5/FxoOgK7fGYOBFKS4KzC/P4RvhXYfwuOvFHwMQggh\nhLA4pVSI1to3q+2kZk0I8WDYPcdI1Gp3hS7fWCZJcioFAxZD3Z6w/gOjOWZyUsHHIYQQQgibYHUD\njAghRJ47uMyYpLpGG+j1P7C7s4lzgXEoCr1+hBJusGMqXIuEHjPA0clyMQkhhBDCKkmyJoQo3P5Z\nD4ufA/fHwH+ukSxZmp0ddPjUmItt7Vi4HmNMyO1c2tKRCSGEEMKKSDNIIUTh9e8OmD8AynkZE1MX\nKW7piNJr9rJRy3Z6J/zcEa6csXREQgghhLAikqwJIQqnyH0wrw+UrAQDl1hvrVX93sb8a5dPG5Nn\nRx22dERCCCGEsBKSrAkhCp/of2BuTyhawpiU2qW8pSPKXPVWMPQ3SE6En56CU9ssHZEQQgghrIAk\nayZ7e3t8fHxo0KABjRo1Yts242YpPDwcZ2dnfHx8qFOnDoMGDSIhISF1v+DgYPz8/PDy8sLLy4sZ\nM2akK3fGjBmp6/z8/AgODk5d16pVK1KmMTh58iQ1a9bk999/Z/PmzXTu3DldOW+99Rbvvfde6usT\nJ05Qo0YNrl69SvPmzWncuHHquh07dtCuXbu8uzhC2JLLp2F2N2Py60HLoHQVS0eUPW7e8Ow6KF4e\nZneHQ8stHZEQQgghLEySNZOzszOhoaHs3buXCRMm8M4776Suq1GjBqGhoezfv5+IiAgWLFgAwLlz\n5wgICGDatGmEhYURHBzM9OnTWbVqFQArV65k+vTpBAcHExYWxrRp0wgICODcuXPpjh0REUGHDh2Y\nPHkyTz311F3je//991m4cCFHjx4F4JVXXuHTTz+lZMmSAERGRrJu3bo8vy5C2JTYCzCnO8RfNZo+\nuta0dEQ5U6YaPLsW3BrAgsGwc0bW+wghhBCi0JJk7S6uXr1KmTJl7lhub2+Pn58fZ84YgwBMnTqV\nIUOG0KhRIwBcXV2ZNGkSEydOBOCzzz7j888/x9XVFYBGjRoxePBgpk6dmlpmZGQk7du3Z/z48XTt\n2vWeMRUvXpwvvviCkSNHsmLFCm7duoW/v3/q+jfffJNPPvnk/k9eCFt18zLM7WEM0hGwwEh4bFGx\nh4ymm490hNVvwvpxRi2hEEIIIR441jd0/+q34dz+vC2zYn3oODHTTW7evImPjw9xcXFERkaycePG\nO7aJi4tj586dTJkyBYCDBw8yePDgdNv4+vpy8ODB1PWPPvroHetnzZqV+nrw4MF88skn9O7dO8vT\n6Nq1Kz/++CPPPfdcajPNFC1atGDRokUEBwfj4GB9b6sQ+erWDfjFH6LCoN98qNbU0hHdnyLFoM8c\n+O0NCP4Krp2Drt+CvaOlIxNCCCFEAZKaNVNKM8iwsDDWrFnDoEGD0ObT7OPHj+Pj40OFChVwc3PD\n29s7z47brl075s6dy40bN7K1/YgRI2jSpAkPP/zwHevee+89Pv744zyLTQibkHgLFgyEiL+g1w9Q\ns5D017R3gM5fQev3YG8g/NIH4q9ZOiohhBBCFCDrq4LJogasIDRt2pTo6GguXLgA3O6zFh0dzeOP\nP86KFSvo2rUrderUISQkhG7duqXuGxISQt26dQFS17dp0+au6wHGjBnDnDlzeOaZZ1i+fHmWtWJ2\ndnbY2d09x27fvj3//e9/UwctEaLQS06CJcONia+7fgt1e1g6orylFLQcAyXc4NdXYObT0H+R9Y9u\nKYQQQog8ka2aNaVUFaXUJqXUIaXUQaXUK+byh5RS65RSx8yfd3b0skFhYWEkJSVRtmzZdMtdXV2Z\nOHEiEyZMAIxarpkzZxIaGgpATEwMb731FmPGjAGMROytt94iJiYGgNDQUGbOnMlLL72Urtyvv/6a\nkiVL8uyzz6bW5uXWe++9x6RJk+6rDCFsgtZGAnNoGbT/BBoNsnRE+afRQOgXCNHH4H/tIOa4pSMS\nQgghRG4lJWS9jSm7zSATgde11nWAJsAIpVQd4G1gg9a6JrDBfG2TUvqs+fj44O/vz6xZs7C3t79j\nu+7du3Pjxg22bt2Km5sbc+fOZfjw4Xh5edGsWTOGDRtGly5dAKOP2bBhw2jWrBleXl4MHz6cuXPn\n4ubmlq5MpRSzZs0iMjIyNdHbsGED7u7uqf+2b9+erfPo0qXLXQdHEaJQ0RrWjoU9c+CJN6HZy5aO\nKP/VegoGr4Rbscbk2REhlo5ICCGEELmxdmy2N1W5qclRSi0HvjP/tdJaRyql3IDNWutHMtvX19dX\nZ2ymd/jwYWrXrp3jOIT1kfdSFIg/PoeNn4Df89BxktFc8EERc9yY8Ds2Cp6ZaSRxQgghhLANoYGw\n7AXUh1dDtNa+WW2e4wFGlFIeQENgJ1BBax1prjoHVLjHPs8rpXYppXal9AMTQohc2TnDSNS8+0KH\nzx6sRA2gbA1j8mzXmhDYD3bPtnREQgghhMiOs3uMLhweLbK9S46SNaWUC7AYeFVrfTXtOm1U0d21\nmk5rPUNr7au19i1XrlxODimEELftnW/MPfbI09BtKtxjsJ1Cz6U8DFkF1VvBipdhyySZi00IIYSw\nZrEXYP4A4//wZ2Zme7ds3+kopRwxErV5Wusl5uLzZvNHzJ9R2Y9YCCFyIGwVLHsJPJ+A3j8ZQ9s/\nyIqWgIAgaNAPNo2HlaMhKdHSUQkhhBAio6QEWDgEbkSD/1wo7prtXbM7GqQCfgQOa62/TLNqBZAy\nK/RgYHm2jyyEENl1YrPxR66SD/T9BRydLB2RdbB3hO7/B81fg5CfjfnmbmVvzkYhhBBCFJC1/4VT\nwdBlinEvkwPZrVl7HBgItFFKhZr/OgETgSeVUseAduZrIYTIOxG7IDAAyj5szDFWtISlI7IuSkG7\nD6Dj53BkNczuBjcuWjoqIYQQQoDRhWPn/0HjF6FB3xzvnq12RFrrYOBevfjb5vioQgiRHecPwdxe\n4FIOBi6FYg9ZOiLr1fh5KFEBFg+HH9vDgMVQppqloxJCCCEeXGdDbw8o0v7jXBXxgPbOv5NSigED\nBqS+TkxMpFy5cnTu3Dnddt27d6dJkybplo0bN45ixYoRFXW7y56Li8tdfweYOXMmI0eOTLfMx8eH\nvn1vZ9sjRozAx8eHOnXq4OzsnDoHXN26de+6fNGiRenifvvt9FPetWrVCl/f26OD7tq1i1atWmXn\n0ghhGRdPwJzu4OgMg5ZDiYqWjsj61ekGg5bB9ShjLrbIfZaOSAghhHgwXY+GoAFQzBV6/2x0XcgF\nSdZMxYsX58CBA9y8eROAdevWUbly5XTbXL58mZCQEK5cucKJEyfSrXN1dWXy5Mm5Ovbhw4dJSkpi\n69atXL9+HYCpU6cSGhrKb7/9Ro0aNQgNDSU0NJSDBw/edXnv3r1T465VqxYLFy4k4xx6UVFRrF69\nOlcxClGgrp41mvMlJcDAZVDGw9IR2Y5qzWDY72DnAD93Mvr7CSGEEKLgJCUafe1jo6DvXKOFUC5J\nspZGp06dWLVqFQCBgYH069cv3folS5bQpUsX+vbty/z589OtGzZsGEFBQVy8mPO+IoGBgQwcOJD2\n7duzfPn9jdESGBjIK6+8QtWqVdm+fXu6dW+++Sbjx4+/r/KFyHfXY2BOD7hxyWjKV97L0hHZnvK1\njbnYSlcgIqKlAAAgAElEQVSBub1h/yJLRySEEEI8ONa9D+FbzQFFGt5XUVY39vVnf31G2MWwPC3T\n6yEv3vJ7K8vt+vbty0cffUTnzp3Zt28fw4YNY+vWranrAwMDef/996lQoQK9evXi3XffTV3n4uLC\nsGHDmDJlCh9++GG6cm/evImPz+2RXy5evEjXrl1TXwcFBbFu3TrCwsL49ttvCQgIyNV5xsXFsX79\neqZPn87ly5cJDAykWbNmqeubNm3K0qVL2bRpEyVKyCANwgrFXYV5veDiSSNRq9zI0hHZrlKVYehq\nmN8fFj8L1yKh2cuWjkoIIYQo3PYGwY6p0PgF8OmX9fZZkJq1NLy9vQkPDycwMJBOnTqlW3f+/HmO\nHTtG8+bNqVWrFo6Ojhw4cCDdNqNGjWLWrFlcu3Yt3XJnZ+fU5oqhoaF89NFHqet27dqFq6srVatW\npW3btuzZsydXtXMAK1eupHXr1jg7O9OrVy+WLVtGUlJSum3Gjh3LJ598kqvyhchXCTchsB+c2w99\nZoNnC0tHZPucSxtJb53usHYsrHkXkpMtHZUQQghROEXuhV9HQbXm0D5v7retrmYtOzVg+alr1668\n8cYbbN68mZiYmNTlCxYs4NKlS3h6egJw9epVAgMD0zUrLF26NAEBAUydOjXbxwsMDCQsLAwPD4/U\nchcvXszw4cNzHHtgYCDBwcGpZcXExLBx40aefPLJ1G3atGnD2LFj2bFjR47LFyLfpEwWeepP6PU/\neKSDpSMqPBydjI7Nv1c0nvRdi4Qe08ChqKUjE0IIIQqP6zEwfwAUKwvPzMz1gCIZSc1aBsOGDeOD\nDz6gfv366ZYHBgayZs0awsPDCQ8PJyQk5I5+awCvvfYa06dPJzExMctjJScns2DBAvbv359a7vLl\nywkMDMxx3FevXmXr1q38+++/qWVNnTr1rmWNHTuWSZMm5fgYQuSL5CRY+gIcXQNPT4b6vS0dUeFj\nZwcdJsKTH8HBJcZ0CHFXLB2VEEIIUTgkJcKiIRB7Hvzvb0CRjCRZy8Dd3Z1Ro0alWxYeHs6pU6fS\nDdnv6elJqVKl2LlzZ7ptXV1d6dGjB/Hx8Vkea+vWrVSuXJlKlSqlLnviiSc4dOgQkZGROYp76dKl\ntGnThqJFbz8t79atG7/++usdsXTq1Ily5fLuQyRErmkNv70BBxZB2w/gsWctHVHhpRQ8/gr0/AH+\n3Q4/dTRG3RRCCCHE/Vn/AZz8Azp/lef97VXG4d3zm6+vr961a1e6ZYcPH6Z27doFGofIH/JeihxZ\n/yEEfwmPvwpPfpj19iJvHN8IQQPBuYzRp63cI5aOSAghhLBN+xbCkufA73no9Hm2d1NKhWitfbPa\nTmrWhBCWEfyVkag9OhTajbN0NA+WGm1g6G+QGA8/tod/pQ+rEEIIkWOR+2DFy1C1GTz1ab4cQpI1\nIUTB2/UTrB8H9XoZ/dSUsnREDx63BvDcOijuakxAfnilpSMSQgghbMf1GGN6nGIPQZ9ZeTagSEaS\nrAkhCtb+RbDyNaj5FPSYDnb2lo7owVXGA4athYr1YcFA+Pt/lo5ICCGEsH5JibBoqDmgyBxwKZ9v\nh5JkTQhRcI7+Dkv/A9Wa5etTKJEDxcvCoBVQsz2seh02fGQM/CKEEEKIu9swDk5ugc5fQuVH8/VQ\nkqwJIQpGeDAsGAQV6kG/+eDobOmIRIoixcB/HjQaDFsnw/IRxtx3QgghhEhv/yLY9i08NhwaDsj3\nw0myJoTIf2f3wC99oXQ1GLAEnEpaOqIcuxp9k3U/HeTMkUuWDiV/2DtAlynQ6l0InQeB/SA+1tJR\nCSGEENbj3H5YPhKqNs23AUUykmQtjYiICLp160bNmjWpXr06I0eOJD4+npkzZzJy5Mh027Zq1YqU\nKQg8PDyoX78+Pj4++Pj4pM7TNmTIEDw9PVOXN2vWDICZM2diZ2fHvn37UsurV68e4eHhAPz000/U\nr18fb29v6tWrx/Llywvg7IXIJ1FhMKcnFCsDg5YZze5sTPyNBFZ+t5ejf51n2Vd7WD/zEDeu3rJ0\nWHlPKWj1FnT5Bo5vgFmdIfaCpaMSQgghLO/GRZgfYEx702c2OBQpkMM6FMhRbIDWmp49e/Liiy+y\nfPlykpKSeP755xkzZgwNGzbMcv9Nmzbh6up6x/LPP/+c3r1737Hc3d2d8ePHExQUlG55REQE48eP\nZ/fu3ZQqVYrY2FguXJCbJWGjLp2COT3AzgEGLoOSlbLex8okJSWzZsYBrkTdpPPIBkQev8yetf8S\nvi+apj1qUOfxSii7Qjaa5aODwaUCLBwCPz5pzMVWtoaloxJCCCEsI2VAkWvnYOjqfB1QJCOpWTNt\n3LgRJycnhg4dCoC9vT1fffUVs2fPJjY275sCde7cmYMHD3LkyJF0y6OioihRogQuLi4AuLi44Onp\nmefHFyLfXTtnDAmfcMOoUbPBm32tNX8EHiUi7BKtBnhRrV5ZmnSrgf9YP1zdXdg87wiLPw8hOuKa\npUPNe490gMG/QtwVYy62M7stHZEQQghhGRs+hBOb4ekvwT3LeazzlNXVrJ379FPiD4flaZlFa3tR\n8d13M93m4MGDPPpo+tFcSpYsiYeHB4mJiVkeo3Xr1tjbG0OQDx48mNGjRwPw5ptv8sknnwBQt25d\n5s2bB4CdnR1jxozh008/ZdasWanlNGjQgAoVKuDp6Unbtm3p2bMnXbp0yf7JCmENblw0atRio2DQ\ncqhQ19IR5Uro+tMcCj7Lox2qUbuZW+ryh9yK0210Q47uPMefi/9hwae78G7jjl9nT4o4Wd2f1dyr\n8hg8uxbm9oSZnY0RPGs+aemohBBCiIJzYDFs+wZ8n4VGAwv88IXoriL/XLly5a7LVZqJfHPaDBIg\nICCA8ePHc/LkydRl9vb2rFmzhr///psNGzYwevRoQkJCGDdu3P2dhBAFJT4W5j0DMf9A/4XGDb8N\nOhF6gW1L/qFGo/I07lr9jvVKKR5p4ka1+q7sWHacvetPczwkiuZ9alLdp1y6vw82zbUmPLse5vWG\nX/yh67fQsL+loxJCCCHyX8qAIlWaQIeJFgnB6pK1rGrA8kudOnVYtGhRumVXr17l3LlzNGrUiPnz\n56dbd/HixbsmZznh4ODA66+/zmeffZZuuVIKPz8//Pz8ePLJJxk6dKgka8I2JMQZnW/P7jFqYaq3\nsnREuRJ16irrfjpIBY+StBtSO9M+aU7FHWnV3wuvpm5s/uUIa6YfoFr9sjzhX4uSroVkeoISFWDo\nbxA0EJa/BNciocXrxoAkQghR2CTchGUvgmNxeHoyODpZOiJhCTcuwvz+4FSqQAcUyUj6rJnatm3L\njRs3mD17NgBJSUm8/vrrjBw5Ej8/P/7880/OnTsHwK5du4iPj6dKlSr3fdwhQ4awfv361EFEzp49\ny+7dt/uGhIaGUq1atfs+jhD5LikRFj9rTBLZbSrUts3mu7GX4lj1/T6cXYrQ6UVvHIrYZ2u/itVL\n0ecdXx7v/TBnj14m8MOdhKwJJykxOZ8jLiBFS0DAAvD2h40fw29vQHKSpaMSQoi8lXDTmLrk4DII\nnWs06b9x0dJRiYKWnGTc01yLhD5zjIeWFmJ1NWuWopRi6dKljBgxgo8//pgLFy7g7+/Pe++9B8CU\nKVPo1KkTycnJuLi4EBgYiJ3d7Vw3bZ81b2/v1KQvbZ81gL/++ivdcYsUKcKoUaN45ZVXAEhISOCN\nN97g7NmzODk5Ua5cOaZNm5av5y7EfUtOhhUjIWwldJwEPv0sHVGu3IpLZOXUfSTEJ9H1TR+KlczZ\nUzQ7ezt82lXl4UfLE7zgGDuWneDIjnO0DHiEyrXK5FPUBcihCHSfBiUqwp9TjEFkev1PJjgXQhQO\nKYnaic3GQ0dHJ1j6AvzUAQYsgtJVLR2hKCgbPoLjG42pbCzcnUNprQv0gL6+vjplfrIUhw8fpnbt\n2gUaR1a2bdtGv379WLp0KY0aNbJ0ODbDGt9Lkc+0htVvwV/TofV70HKMpSPKleRkzW//t49/D16k\n8whvqta9//ngwvdHszXoKFej43ikSUWa9Xw4xwmg1doxDda8DVUaQ79AKPaQpSMSQojcS7gJgX3h\nhNk6JKVvbniw0bzfwcnoh+3WwLJxivx3YIkxTL/vMOj8Vb4dRikVorXOcmhJaQZ5D82aNePUqVOS\nqAmRlc0TjESt6Uh44k1LR5Nrfy46xqn9MTzhXzNPEjUAj/qu9H2/MY92qMaxv8/zy7gdHNx6Bp1c\nsA/J8kWTF+CZn+HsbuOp8+XTlo5ICCFyJ22i1v379IMoeTSHYb+DnSP83An+2WC5OEX+O38Qlo8w\nHkR2+Czr7QuANIMUQuTe9qmw5TNoOADaf2KzA07s3xzBvo0RNGhThXot3fO0bMci9jTpXoNajSuy\n5ZcjbJ53hLDtkbQM8MLV3SVPj1Xg6vaA4uUgMMCYPLv/IqhYz9JRWZfkZLh1DeKvQdxViL+a5ueV\n9K8TbkLN9lC7K9jJs1QhCsStGzC/3+1EzSfgzm3K14bn1hsjHf/SxxgV927bCdt246JRi1q0pEUH\nFMlImkGKPCXv5QNk9xyjn1qdbtD7Z7DL3kAc1ubUwRhWfbeXavXK0vFFb+wyGfnxfmmtObLzHNsW\n/0Pc9UQatHHnscIwN9v5QzC3F9yKhb7zwPMJS0eUN5KT0iRT1zJPtO71M/4akMX/s3YOxs2BUnAj\nBirUg1Zvg1dnm30AIoRNyE6illbcVVgw0OjT1nosPPGGfEcLi+QkIxk/+Ycx+nEVv3w/ZHabQdr4\nHYIQwiIOLoNfR0GNttDzB5tN1GLOxPL7Dwco6+7Ck8/WzddEDYyBjLyauOFR35Xty44Tuv40/4RE\n0aJPLTx9XG13brYKdeC5dTC3t5G09ZgG9XpZNqakxPRJ1R01W1eyTrRuxWZ9HPsiRqLlVPL2z+LV\n71yW7mep9K8dnY0bvuQkY/LVzRMhaABU9IZW78AjHeWGUIi8duuG0fTx5B/Q/f+yNzCWU0kIWAgr\nXoZNn8CV0/D0l2Avt9M2b+MncHwDdP66QBK1nJBPlxAiZ/5ZD4ufA3c/8J8DDkUtHVGuXL8Sz8qp\ne3Esas/TL3kXaO2WU3FHWvf3onZTNzbPO8Lq6fttf262Uu4wbLXRJHLRMLh2Hpq+lLuyEm/dpfYq\nhzVbCTeyPo6D053JVIkKULRUJolWyfTr83L+JTt78O4DdXvC/oVGE+P5/aBSQyNpq9lekjYh8kJu\nErUUDkWMB1Kl3GHrF8aouM/8DEWK51+8In8dXAbBX8KjQ8B3qKWjuYM0gxR5St7LQu7fHTC7O7g+\nDINXgnNpS0eUKwm3klj25R4uno2lx+uNKF+tpMViSU5KZt+mCHb+ehKSNb5Pe+DTrir2DjbaZykh\nDpYMh8MroMkIqPnkXRKtLGq2EuOyPo5jsfRJVNES9665ulfNlpX0R7inpATYF2QkbZf/hcqPQqt3\n4eG2krQJkVu3bkCgP5zcaiRdDfrmvqxdP8Gq140RIgMWgEv5vItTFIzzh+B/7aBCXRiyskAfQGe3\nGaQka6bx48fzyy+/YG9vj52dHdOnT2fixImcPHmS2NhYLly4gKenJwDff/89zZo1Izo6Gjc3N779\n9lteeOEFABo3bkx8fDwXL17k5s2bVK5cGYBly5bRqlUrSpQokTof2xNPPME333zDkCFDWLduHSdO\nnKBo0aJER0fj6+tLeHj4HXG6uLgQGxtLcnIyr776Khs3bkQphZOTEwsWLMDT0xMPDw927dqFq6vr\nHft3796dc+fOsWPHjtRl48aNY9KkSYSHh1O+fPl0xwGwt7enfv36JCQk4ODgwKBBgxg9enS6eeZS\nWMN7KfJJ5D6Y2RlcysHQNcZPG6STNb//7wDH91yg43/qU93HOs7j2sU4ghce48SeC5RxK06rgFpU\nqmmjc7MlJxnD+v814+7ri7hkkmiVzKJmq5Sxvb1jwZ6TJSXegr2/wB9fGM2u3P2g9TtQvbUkbULk\nRF4maimOrIaFQ41a+f6LjYeZwjbcvAQzWhstMZ7fAiXdCvTw0mctB7Zv387KlSvZvXt3arJ069Yt\nli5dCsDmzZv54osvWLlyZbr9Fi5cSJMmTQgMDExN1nbu3AnAzJkz2bVrF9999126fTZt2nTXJMre\n3p6ffvqJF198MVsxBwUFcfbsWfbt24ednR0REREUL555Ffzly5cJCQnBxcWFEydOUL169dR1rq6u\nTJ48mc8+u3OYUmdnZ0JDQwGIiooiICCAq1ev8uGHH2YrVlEIRP8Dc3oYN8kDl9lsogawY8UJju++\nwOO9H7aaRA2gxENOdPxPfcL3R/PH/KMsnbwHr6bG3GzOJay8BigjO3tjcvT6fSDp1p0Jl432cbQY\nhyJG85wGAbBnDmydbHwfqzaF1u8WngFdhMhP+ZGogdGndMgqY5TIH5+EgCCr6/Mk7iI5CRYPhysR\nxvtXwIlaTthoO5u8FRkZiaurK0WLGlWfrq6uVKpUKcv9AgMDmTx5MmfOnCEiIuK+Ynj11Vf56quv\nSExMzHbMbm5uqbVb7u7ulCmT+VP4JUuW0KVLF/r27cv8+fPTrRs2bBhBQUFcvHgx0zLKly/PjBkz\n+O677yjoWllhIZdPw+xuxu+DlkHpKpaN5z4c3naW3WtOUbdFJRq0tc7z8KjvSr8PGtOoQzWO/nWe\neR/s4FDwWdubm00pqPIYeDwOFetDmWrgXEYStfvhUAQeexZG7YFOX8ClcJjVxajxDv/T0tEJYb3S\nJWrT8y5RS+H+KDy71ugaMKsLHF6Z9T7CsjaNh3/WQadJULWxpaPJlNXVrG1dcJTo09kYgSsHXKu4\n0KJPrXuub9++PR999BG1atWiXbt2+Pv707Jly0zLPH36NJGRkfj5+dGnTx+CgoJ4/fXXs4yldevW\nqc0gBw8ezOjRowGoWrUqzZs3Z86cOXTp0iXLcvr06UPz5s3ZunUrbdu2ZcCAATRs2DDTfQIDA3n/\n/fepUKECvXr14t13301d5+LiwrBhw5gyZUqWNWbVq1cnKSmJqKgoKlSokGWswobFXoA53Y0+R0N+\nBdealo4o1yKOXGLz3CNUqV2GFn1rWfXIi45F7GnavQaP+FVkS+ARNs0N4/C2s4VjbjZx/xyKgt9w\naDgQQmYaHeNndgLPlkZNW9Umlo5QCOtx64ZR63XqTzNR88+f45StAc+ug1/8jeH9O04yvqfC+hxa\nbrRQaDQIHrW+AUUykpo1jEQlJCSEGTNmUK5cOfz9/Zk5c2am+wQFBdGnTx8A+vbtS2BgYLaOtWnT\nJkJDQwkNDU1N1FK88847fP755yQnJ2dZjru7O0eOHGHChAnY2dnRtm1bNmzYcM/tz58/z7Fjx2je\nvDm1atXC0dGRAwcOpNtm1KhRzJo1i2vXrmXrXEQhd/MyzO0BV85A/wVGB2obdencddZM30+pCsV4\nang97O1t40/fQ5WK0/21hrQdXJvLUTdZ8Onf/LnoGLfislcDLwo5Rydo8gK8shee+hSiDsFPTxlN\nJE//benohLC8W9dvJ2rdp+VfopaiuCsM/hVqPgW/vQHrPoBs3NOJAhR1GJa+CJV9jRYKVvzgNoXV\n1axlVgOWn+zt7WnVqhWtWrWifv36zJo1iyFDhtxz+8DAQM6dO8e8efMAOHv2LMeOHaNmzdzXPNSs\nWRMfHx8WLFiQre2LFi1Kx44d6dixIxUqVGDZsmW0bdv2rtsuWLCAS5cupQ6ScvXqVQIDAxk/fnzq\nNqVLlyYgIICpU6dmetwTJ05gb2+fOhiJKIRu3TCeDkaFQb/5Nv2k/mbsLVZO3YedvaLzCG+KFrOt\ngSmUUng1dcPD25XtS9PMzeZfC88GNjw3m8g7js7QdITRr+3vH+HPr+HHdvDwk8ZAJJUftXSEQhS8\nW9eN/8cKKlFLUaQY+M+F1WOM7+LVM9Btqs1Oc1Oo3LwM8wOgqItNTT1kG4+X89mRI0c4duxY6uvQ\n0FCqVat2z+2PHj1KbGwsZ86cITw8nPDwcN55551s165l5r333uOLL77Icrvdu3dz9uxZAJKTk9m3\nb1+mMQcGBrJmzZrUeENCQu7otwbw2muvMX369Hv2nbtw4QIvvPACI0eOlJvEwirxljEhb8Rf0OsH\nqNnO0hHlWlJCMqun7ef6pXg6vehtu3OYYc7NNsCLnm8+StFiDqyetp/fvt/H1eiblg5NWIsixeHx\nUfDKPmg3Ds7sgh/aGDesZ/dYOjohCk7aRC0/mz7ei70DPD0Z2n5gzJk4t5eRKAjLSU4yppW5/C/0\nmQ0lsx6bwlpIsgbExsYyePBg6tSpg7e3N4cOHWLcuHH33D4wMJAePXqkW9arV69sJWutW7fGx8cH\nHx8fBg0adMf6unXr0qhRoyzLiYqKokuXLtSrVw9vb28cHBwYOXJk6npvb2/c3d1xd3enZ8+enDp1\niiZNbteOeHp6UqpUqdTRK1O4urrSo0cP4uPjU5fdvHkTHx8f6tatS7t27Wjfvj0ffPBBljEKG5Ty\nx+z4BugyBer2yHofK6W1ZuPcw0T+c4W2Q2pTsXopS4eUJ9xqlOKZdx+jWa+HiTh6mcAPd7L791Mk\nJUpTG2Eq6gLNR8Or+6HNf435EWe0MiYsj9xn6eiEyF8ZEzXvPpaJQylo8Rr0mGF8B3/uaIw8KCxj\n8wQ4thY6fmZzrYVknjWRp+S9tGFaw4qXjaHB24+HZiOz3seK/b3qJH/9epLGXT3x7eRp6XDyxbWL\ncQQvOMaJ0EIwN5vIP3FXYOd02PadMRl57S7Q6h1jElghCpN0idoM8H7G0hEZTmyGoIHGHJMDFsl3\nr6AdWmEM+tJwIHT91mr6qWV3njWpWRNCGIna2rFGovbEGJtP1I7+fY6/fj3JI40r8mhHD0uHk29K\nPORExxfq8/RL3iTGJ7F08h42zDrEzWu3LB2asCZOpaDlGHh1H7R8G05sgf9rBgsGG53thSgMrDVR\nA6jeCoauNn7/qYPxHRQFIyoMlr1o9N21kQFFMpJkTQgBf3wB278Dv/8YQ3/bsMjjV9g4Kwy3h0vR\neoDXA9G30sPblX7jGtPoqWoc3XmeeeN2cOhPG5ybTeQv59LGgCOv7IUn3oR/1sP3TWHRMLhw1NLR\nCZF7t67DvD7WmailqFgPnlsHJSsbfdj2LbR0RIVfyoAijuagL45Olo4oV6wmWZMJlm2fvIc2aucM\n2PQJePeFDhNt8qlTiisXbrJ62j5cyhSl0wve2DtazZ+4fOdYxJ6mPWrQZ+xjlK3kwqY5YSz5Yjcx\nZ/J23kpRCBR7CNqMNfq0NR8NR9bA941h8XCI/sfS0QmRMymJ2r/boOcP1pmopSjlDsPWGH2mljwH\nwV8ZLVtE3ktOhiXPw+VT0GeWTQ0okpFV3Mk4OTkRExMjN/s2TGtNTEwMTk62+dTigRUaCKvfBK/O\nxtDCdlbxJyFX4m8ksGrqXpKTNJ1HNsDJxbaG6M8rZSu5pJmb7QZB4//mz8X/yNxs4k7FHoJ2HxjN\nI5u9DGErYepjsPQFiDlu6eiEyNqt6zDvmduJWv3elo4oa86lYcBiqNcL1o8z5mNLTrJ0VIXP5glw\n7HfjIXS1ZpaO5r5ke4ARpdRPQGcgSmtdz1zmA0wDnIBE4CWt9V+ZlXO3AUYSEhKIiIggLi4u52cg\nrIaTkxPu7u44Oj6YN8k2JTEetn0Lmz4Fj8chYKHNNg8ASEpKZuW3ezl77DJdX/Ghci0ZZAMgLjaB\n7Uv/4dCfkbiUKUoL/1pU9yln6bCEtYq9YMwL9ff/ICkBGvSDJ96AhwrnAD3CxsXHGhNe/7vddhK1\ntJKTYcM4+HMKPPI09PqfMUebuH+HV0JQf/AZAN2+s9oWQ9kdYCQnydoTQCwwO02ythb4Smu9WinV\nCRijtW6VWTl3S9aEEAXoxBZY9TrEHIM63YwataIlLB1Vrmmt2TzvCIeCz9JmUG1qN3OzdEhWJ/Kf\ny2wJPELMmet4eLvSwr8mJcva7pxzIp9dO28mbT+CTgKfAKOPW+mqlo5MCIOtJ2pp7ZxhTKDt7gv9\ngqB4WUtHZNsuHDHml3StZQzqYsUPovN8NEit9R/AxYyLgZLm76WAs9mOUAhRsK6dh8XPweyukJwA\n/RcZE0PacKIGELruNIeCz/Joh2qSqN2D28Olb8/NduTS7bnZkmRuNnEXJSpAhwnGQCS+w2DvfPim\nEfz6qswTJSyvMCVqAI2fB/85cG4//PgkXDxh6YhsV9wVc0ARZ5seUCSjHM2zppTyAFamqVmrDfwO\nKIzEr5nW+tRd9nseeB6gatWqj546dccmQoj8kpxkPCHf+DEkxhkDCjQfbfwxs3En9lxg9Yz91GhY\nnqeeq4uys86mDtbk2sU4tgYd5eTeaB6qVJyW/R6hUs3Slg5LWLMrEbD1S9g922hO1GiwMdmvDXfY\nFzYqPtboo3Z6h9FssF4vS0eUd/7dCYH+oOyh/wJjqHmRfcnJML+fMcrtoBVGFw8rl+fNIM1CPUif\nrH0DbNFaL1ZK9QGe11q3y6wMaQYpRAGKCIFVoyFyL1RvDU9PhrI1LB1Vnog6dZWlX+ymrLsL3Uc3\nxKGIvaVDsikn90Wzdf5Rrl2Mw6uZG8161sDZpYilwxLW7PK/sHUy7Jlr3FD6DjUe/JSoaOnIxIMg\nNVHbCb1+KFyJWoroY8aw/tcvQO+f4ZEOlo7IdmyaAFsmQsfPjdpKG1BQydoVoLTWWitjMqMrWuuS\nmRQhyZoQBeHmJdjwEez6GVzMJk11e1htJ9ucunYxjkWf7cLe3o7eb/tSrKQkGbmREJ/Ert9OErru\nNI7O9jTr+TC1m7pJDaXI3KVwY27G0F/A3hF8n4Xmr4JLeUtHJgqrByFRSxEbZZzruX3w9JfGQxGR\nubBVRvNHn/5GP3wbudfJ8z5r93AWaGn+3gY4dp/lCSHuh9bGcPzf+kLITGjyIoz8G+r1tJk/Xlm5\nFcy8uaEAACAASURBVJfIqu/3kRCfxNMjvCVRuw+ORe1p2uNh+ox9jIfcirNpThhLJ8vcbCILZTyM\nEdZe3mXcNO/8P/jaG9aONUaUFCIvxcfCvN4PRqIGxkOPIaugRltY+Sps/ETmYsvMhaOw5D9QqaGR\n3BaSe520cjIaZCDQCnAFzgMfAEeAKYADEIcxdH9IZuVIzZoQ+STqsDHK46k/wd3PaPLo5m3pqPJU\ncrLmt//bx78HL9J5hDdV68qoWXlFa03Y9nNsW/wPt24m0qBtFR7r7IljUWleKrIQcxy2TIL9C8DB\nCfyeh2ajZFQ7cf9SE7W/zD5qPS0dUcFJSjS6MeyebUyj0eUbcJCHk+nEXYEf2hqtif6zxZh03Ibk\nSzPIvCDJmhB57NZ12PIZbDeH4G/3ITQcaNMTXN/L1gVH2bcxgpb9alGvpW39UbYV6eZme6goLfrI\n3Gwim6KPGX+L9i+CIsWh8X+g6Uhj8m0hcir+2v+zd9/hUVVbH8e/k8lMem9ACjX03rsICEIAKUFA\nEaXYsCuK9/ree+0K2AtIVRALkKACoYlU6YQSeggtFdIzmSTTz/vHASQhQIAkU7I/z8MzlMyZpZBk\nfmfvvdaVrY81MKhdJUnyjZCtH8rnzh9eAq63PG1Uc1gs8iy1Mxthwh9Qr6e1K7pjIqwJgqOTJHmf\n9rrpoEmFduOh/7sOezf76NZUtv+aSJu+4fR8ONLa5Ti8jKR8tv58mtx0MZtNuEOZp+TQdvw3UHvK\n27G7TQU3MaxeqKDrg1r0QvnMdU12aCmsehGCm8OjK8DbdsbUSBYLJYcOoVm3HufgYAKmTEZRHTeL\nt34MWz+CQTPlG0N2SIQ1QXBkeRdg7RtwZgMEt4Ahn0FEV2tXVWUuHs8h7psj1G0VyKBnWuEkGmBU\nC7PZQsJfqexbI8/96RRVnzb9w1EqHW/VVqgCl0/I3dlO/AEuPnJg6/osuPpYuzLBlukLYWk0pO4X\nQe16SZtg+ePyTY9HYyC4qdVKkSQJ3YkTaOLWolm3DlNGBgqVCsloxDsqijoff4RCpaq6Ak6tldv0\ntxkHw+fY7Tk1EdYEwRGZ9LDrK7kTm5Mz9PmXfEdJWYVfFK0sJ01L7Kx4fILcGPFae9SuztYuqca5\nYTbbI02o00jMZrsXkiRh1JspKTRSUmigpNCAvsREeDN/PHxcrF1e5bp0VL4LfmqNHNS6vSB/3RLb\nuYSyRFC7tfTD8kBwkw7G/lLts8T0586jiYtDExeH4cIFcHbGs2dPvKOi8Op7P7k//0zWp5/hcV9v\nwr74Aie3KtiNkX0G5vcF/wYwab1dz4wVYU0QHM25rRA3DXLOQPOHYOBH4BNq7aqqVFGBnpgZB5DM\nEtFvdsTTz9XaJdVo549ksX1ZItpcPc2616abmM1WitlkKRW+SgoNFJf6tbHUo8loueEaKlclnaLq\n07pvmOOtYGYckUPb6bXy6kD3F6Dz0+Diae3KBFtQKqgtghbDrV2Rbcq7KDddybsAI+ZW+Vk+Y3o6\nmrVrKYhbi/7kSVAocO/cGe+owXgPGIDSt/SNu7xly7n09tu4tW9P+JzZKL0r8aaMTgML+kFxDjy1\nDXzDK+/aViDCmiA4isJLsOEtOBYDfvVh8CcQecvZ8w7BaDDz+6cHyc0oYuS0DgRFeFm7JIHSs9nU\nbs50G9nQYWezSRYJXbGREo3xSvAylA5j2tLhS19sKvc6Ts4K3L3UuHmpcfNSXXmUf+7upcbVU3Vt\nBMW+1ee5eCwHv1ru9BrbmPCmDticI+2gHNrObAD3ALlzZOcn5aYkQs2kL5SHQaceEEGtIopz4Zdx\nkLIHBnwA3Z+v1MubcnLQrF+PJm4tJQcPAuDapjU+UVF4DXwQVcitZypq1q8n7fU3cGnYkIj583AO\nqoQmVRYLLBsPievlhiL1e937Na1MhDVBsHcWM+xfIM9YMemg56vy4Fk7XvKvKMkisWH+Mc4ezmLQ\n061EN0IblJOmZdsvp8lIKqB2Ix/uG9eEgFDbXiH5Z+uhHLCKNeWHrqsrYrpCQ/njjRTg5qm6IXy5\ne6lw9VRfCWZXft9bjdpViaKCZyokSeLC0Rz+Xp6IJltHw/ZB9IiOxMvfAVeVUw/IDQKSNoFHEPR4\nSR6wrXa3dmVCdRJB7e4YdbDySTi5Cro8CwM/AKe7H7ViLiyk8M9NaOLiKNqzB8xmXCIj8Y6Kwjtq\nMOrwO1vF0v69k9QXXsA5KIiIRQtRh91jB+dtM2HLB/Dgx/LZVwcgwpog2LPUeHkY5qUEaNhXXk0L\naGjtqqrN7t/OcnDDRXpEN6Jt/whrlyPchGSROLUng12xZ+XZbP3D6RRVvbPZzEYLJdor4avQgO4m\nWw+vroqZy9l6CKB2VZZa8XLzVl8LZO5lQpmrp6rKm9yYjGYO/5lM/LqLAHQYVI+2D4TjrHLAuXcp\n+2DLh3BuC3gEQ89XoOPEGnFjqsbTaeQtfakHYPT38hZ/oeIsFtj4FuyZDc2Gwch5d/R5YykpQbt1\nKwVxcRRt245kNKIKD8d78GC8owbj2rjxPZVXcvgwyU8/g5OLCxELF+ASeZednE+vh1/GQuuH5a2f\ndtpQpCwR1gTBHpXkwaZ3IP4H8KoFD34EzYc7zBemijixM50tP56iRa863PdIkwqvSAjWU6I1sHvl\nWU7ukmez9R7TmPpt7m411GKR0BddDV7GG7celglfhpKKbD28PmypytmSqLLZEKTJKWFXTBJnD2Xh\nHeRGr4cjqdcq0NplVY2Lu+V5Uue3g2ct6PUatJ8AKgdcVRT+CWpp8fKKmghqd2/3t7Dh3xDeFcb9\ncsvZhpLBgHbXLjRxa9H+9ReW4mKcg4LwHjwI76goXFu1qtTvu7rERFImT0EyGAifNxe3Nm3u7ALZ\nSTD/fvCrB5M3OtRNHBHWBMGeSBIc+QU2/kcObF2egT5v1rhuaamn81j95WFCm/gS9Xwbx2uw4ODS\nk/LZdmU2W/02gfQa0xhPP5fytx6W2XJ49ec6rbHcrYcKBbjeZOuhW5lQ5u6lRnUHWw/tQcqJXHYs\nTyTvUjH1WgXQ8+FIfIIcdLvg+R3y9siLO8E7FHq9Cu0eA2cH65JZk+k08tbH9IMiqFWWYyvht6fB\nty6MjwW/utf+SDKbKd5/AM3atRRu2IC5oAAnHx+8BwzAOyoK904dUSir7oaVITWV5EmTMWVnE/b1\nV3j2qGAXS50GFvSH4mx4aiv4OtZOGxHWBMFeZJ6ENa9C8i4I6yzPTKvVytpVVbu8S0XEzozH3ceF\nUa+3x8XdcccRODKz2cKRv1LYv+Y8FouEQqG4o62HZbccXg1fLh5Vv/XQ1plNFhI2p7I/7jxms4X2\nA+rS/sG6qNS2uSp4TyQJzm+DLR/JTRR8wuWVtraPgrPoQGrXSgW176H5MGtX5Dgu7JTnjzm7Io1b\nhi5HKbfaX7ceU2YmCnd3vPr2xTtqMJ49eqBQV9/nkikri+QpT6I/d47QWbPwfnDgrZ9gscDyx+D0\nOpjwO9TvXT2FViMR1gTB1um1sG2GvNfcxQseeBfajgenmreaVKI1EDMjHqPORPT0jngHOs42h5pK\nk1NCwpZUnBSKK402ypz/8lSjVNW8f+uVoShfz66VSSTuu4ynvws9RkXSsH2QQ60kXiNJcHazvNKW\nul++s977dXkYrgPPl3RYIqhVOf3ejRR88TKaJBPGQiUKlQqP+3rjExWFZ58+VTP7rILMGg0pzzxL\nyeHD1Hr7f/g9/PDNP3jbLNjyPgz8ELo9V31FViMR1gTBVkmSPBx23ZugSZW39/R/BzwCrF2ZVZiN\nFv748hCZFwoZ/mo7ajXwsXZJgmAX0s/ks/3XRHLStIQ19aPXmMb413bQ9veSJHeN3PKh/Ebfrx70\nfgNajwGls7WrEypCp4GlIyH9kAhqlcyQkoImbi2atWvRJyaCkxMeYUq8a2fjNeUdlL2etHaJ11hK\nSkh96SWKtu8g6LVXCXyynNoSN8DPY6DVaLlpiiPeiEKENUGwTbnnYd10eb5QSEuI+gwiuli7KquR\nJIlNP5wgce9lBkxpQWTHEGuXJAh2xWK2cGx7OvtWn8OoM9O6bxidouqjdnPQACNJ8hu5rR/KQ7a9\nQ+XOke2fAE8x4sNmXR/URv8AzYZauyK7Z8zMpHD9egri4tAdSQDArV07udX+gwNx9lTD8glyl9U+\n/4L7pttM6JEMBtL/9W80cXH4T55E8LRp/+wMyDkL8+4HvwiYtNGhR3mIsCYItsSkh51fwY5PwMkZ\n7v83dH66xt8R3h93nn2rz9NlWAM6Dq5n7XIEwW6VFBrY8/tZTuzKwN1LTfdRjWjcOcQxt0bCP6Ft\n73fym1GlGlqMhM5PQVgHa1cnXE9XcGXrowhq98pcUIBm40Y0cWsp3rcPLBZcmjXDJ2ow3oMGoQoN\nLfMEI6x6EY78LO/iGfK5zWwfliwWLr//Pnk//4JP9Chqv/MOClOx3FBEmyk3FLmuSYojEmFNEGzF\n2S2wdhrkJMlt+B/8CLzrWLsqq0vcf4k/F56gSdda9Hu8meO+qRSEanT5vIbtv54m82IhtRv50GtM\nY4LCvaxdVtXKSoT9C+Dwz2AohNAOcmhrMUJ0kLQ2EdTumaWoiMLNW9DExaHduROMRtR168oraEOi\ncGnQ4NYXkCR5mPT2WdDoAfnvwcWzUmozmo1kFGWQqk0lTZtGsbEYF6XLPz+cXXBVuqJWqv95dHa9\n9udqJzXa2fPJ/W4uXgMGUKdLFk5J6+Cx36BBn0qp0ZaJsCYI1lZ4SZ57ciwW/BvA4FnQqL+1q7IJ\nGWcL+OPzQ4TU92bYi21FowlBqESSReLk7gx2/3YWfZGRlr1D6TysAa4etnFHvcroNJCwDPbNg+xE\ncA+EDk9Ax0ngE3rbpwuVTFcAP46EjMMwejE0G2LtiuyGxWCgaMcONHFxFG7ZilRSgnOtWngPujIL\nrUXzO7/BeeB7iHsVarWGR1eAZ/Dt65AsZJdkk6ZNI7UwtdRjmjaNy8WXsUjld/u9E0P2w4RNJk7W\nhUVjfVD4BpUKfKXC3i3C3/XPueH3lC64Opd+rrOTdXc3ibAmCNZiNsl3eTe/D2aDPCOox8tisOsV\nBVklxMw4gIubM9HTO+Lq6eBvIAXBSnRFRvatPs+xbam4eKjoNrwhzbrXRuHoIxAkCc5tlUPb6XWg\ncJKDQuenoG4Pmzm349BEULtjkslE0d698iy0Pzdh0WhQ+vnh9eBAfKKicGvfHsW9dos+vR5iJoJH\nkDyLLTASjUFDWmHatSB2dZUsTZtGujYdvVlf6hJBbkGEeYUR6hl67UeYVxhhnmF4qj3Rm/UYzAZ0\nZp38aNJd+7XerJd/mPT//NysR591iqCVq2mzRU1uPT82PN8JjZtU+uMt5TzPrL+nsOiscL4W+MoL\nguWuDN4qJN4iKF7/+1dDoghrgmANqQdgzStwKQEa9pNX0wIaWrsqm6EvNhI7M55ijYHo6R3xDXHc\ng8OCYCuyUwvZ/msiGUkFBNf1ovfYJoTU97Z2WdUj7yIcWAgHl0BJHgS3gM5PQuuHQe2gnTOtTQS1\nCpMkiZJDh+VZaOvXY87JwcnDA6/+/fEeEoVH164oVPd2Q1Nv1pOuTf9nRexSPGmn15CqVJDq5kWh\nqbjUx3upvEqFsWs/9wqljkcdXJ0r+cZzzlmYfz/4RFDY4C3SXn8TVUQ4EQsXogq5ddMxSZIwSSb0\nJv0/4bCckHhPv2/WVXpIVCqUuChd2Dd+nwhrglBtinPhr3cgfjF41ZbPpTV/SNzBvY7ZbGHN10dI\nP5PPsJfaEtrYz9olCUKNIUkSZ/ZfZmdsEsUFBpp1r03X4Q1x964hA6aNJXA0BvbNhUtHwcUH2o2H\nzlPkbepC5dAVwI8j5E6dDy+BplHWrsjmSJKE/vRpOaDFrcWYno7CxQXPPn3kYdW9e+PkWvFAZLaY\nySzOLLUidi2YFaaRWZJZ6uPVTmrquAURmp9OmL6IsKYjCW004Fo483GpxvE5eu2VhiKXrjQUqUfR\n3n2kTp2K0seHiEULUderV331VND1IbFsiCt35bCc39eZdUzvPF2ENUGocpIkH2r/8z9Qkg9dn4U+\nb8pDroVrJEli69JTnNiZQd8JzWjWvba1SxKEGsmgM7E/7gIJf6Xg7KKky7D6tOwdipOyhpwblSRI\n2StvkTzxB1jMEPmA3J23YV+4121mNdm1oJYADy8WQa0Mw4ULFFwJaIZz50CpxKNHd3lYdb9+KD3L\nb/ohSRL5+nw5hGlTSwWxNG0a6UXpmCymax+vQEGIR4i8KuYZRqjXlccrq2SBboE4KZygKBt+GSvv\nCBo0A7o8XV3/K67+h8GKx+Hkahi/Ehref+2PSo4dJ+XJJ8HJiYgF83Ft1qx6a6smYhukIFS1yyfk\nw7rJuyG8izwzrVZLa1dlkw5tTGbXyiQ6PFiXrsPFtlBBsLbcjCJ2LEsk9VQeAaEe9B7bmDqRNWy1\nW5MB8T9A/PegvSyvsHV6Eto9Cq7VuLrgCEry5TlqIqiVYrx0Cc3adWji4tAdPw4KBe4dOuA9JAqv\ngQNx9pM/54qNxfJWRe2NTTxSC1MpLrNV0dfFt/QWxSvBLMwrjNoetVFVtD2/oRhip8DpOOj+IvR/\np/puWOz4TN6R9MB70OPFG/5Yf+48yZMnYyksJPy7Obh3vG2msTsirAlCVdFrYdvHsHu2/A39gXeh\n7aPijuxNnDuUxbp5R2nYLpiBU1o4fnMDQbATkiRx7nAWf684gzZXT2SnEHqMaoSHbw1rd28ywMlV\n8mpbyl5QeUCbMXJwC2lu7epsX6mgtgSaDrZ2RVZlysujcMMGNGviKI6PB0nCpWUL6N+TrO6NSXUt\nubZKllYoP+bqcktdw1XpWm4Tj6uPHqpKPG9pMcO6N+TGaC1HwfA5VT/y4swm+CkaWo6EUQtvemTE\nmJFB8uQpGNPSCP3yC7z69KnauqqZCGuCUNkkSV6uX/8maNKg/QT5LpS7v7Urs1mZFzX89slBAsI8\nGf5KO5zVSmuXJAhCGUaDmYPrL3JoYzJOSgUdo+rRpm84SucaeAMq/TDsmw9HV4BZD/V6yV0kmwwG\npXXbfNukknx56+OlozU6qJkKC7m07g8K4tag2H8UhcVCQW0vjrbzZVsTM8fccjBL5msfr1QoqeVR\n69o2xeu3LIZ6hhLgGlC9s0clCXZ+AZvehro9YexP4OZbNa+Vew7m9QGfcJi88baNfky5uaQ8+RS6\n06ep89GH+Ax1nFl9IqwJQmXKPS/feTqzEUJawZDPILyztauyaYW5OmJmHECpdCL6zY41p5GBINip\ngqxi/l6RxIWEbHxD3Ok1JpKI5gHWLss6inLg0BLYvxAKUsA7DDpNgvaPg0egtauzDTUsqGkN2lLn\nxjJyL6Lee5SwPRdockqL2gSZPrCrmYKdzZ3QRgQQ6h1Waovi1VWyWh61rD7jq1wJy+H3qRDQCMbH\ngE9Y5V5fr4WFD0BhxrWGIhVh1mpJfe55ivfuJeT//g//8Y9Wbl1WIsKaIFQGkx52fgk7PgUnZ7j/\nLfkuq7jDeksGnYmVnxykMLuEka93ICC0/IPTgiDYngtHs/l7+RkKskpo0DaIHtGN8A50s3ZZ1mEx\nQ+J62DsXzm8DpYu8VazzkxDa3trVWc/1QW3Mj9BkkLUrqnQbL2xkw4UN1wJagb4ApVmi1QWJHick\nOidKuBmg2FvNpS4NMfbtgl+HLoR5h1PHsw5uznb6OXNuGywbL694PRpTeWfxJQlWPCFvOR4fKzf0\nuQMWvZ60V19D+9dfBD7/PIHPTa3e1ccqIMKaINyrs1sg7jXIPQstRsDAD8G7jrWrsnkWi8TaOQkk\nH89lyHOtiWhRQ+/MC4IdMxstHP4rmQNrLyBJ0OHBurR7IKJmb2XOOi1vkTzyCxi0ENpR7qDX/KGq\nP+NjS2pAUDt4+SATN0wk0C2QRt4NaZOhpll8NkH7klAWFKHw9MR7wAB8hkTh3rkzCmcHu4F7+Tgs\njQZ9IYxdCg363Ps1//5c3mb5wLvQ46W7uoRkMpHxn/9S8Ntv+D32GCH/evPeB4VbkQhrgnC3NBmw\n4d9wfKXcHWzwJ9Con7Wrshs7lieSsDmV+8Y1puV9lbyFQhCEalWYq2NXbBJJ8Zl4B7rSc3Qk9VoH\n2v0d7Xui08iBbd88yEkCjyDoMBE6TnT8G3ol+fDjcLh0zGGDWoG+gOjV0YRlSbyX14eSjX9hunQJ\nhZsbXvffLw+r7tkTJ7WDb+0vSJObgGQnwkPfQpuxd3+tpE1y+GsxAqIX3dMMWsliIXPGTHIXL8Z7\n2FDqfPDBPQ8OtxYR1gThTplNsH8+bP4AzAbo9Zp890dV8eGUNd3Rrals/zWRNv3C6Tk60trlCIJQ\nSVJP5bJ92RnyMoqIaBFAr4cj8Q1xt3ZZ1mWxwLkt8mpb4npwUkKzofJW+Yhu9/SG1CaV5F1ZUTsG\nY5ZCkwetXVGlkySJt1Y/T52ft9E3wYJC6Yxnz554R0XhdX8fnDwqsQujPSjJl7dEXtgB/f4LPV+9\n83/Xuedg3v3gHQpT/rxtQ5GKkCSJnLnzyPriCzz79CH0i8/vaJC4rRBhTRDuRMp+iHtF3tbRsB8M\nngUBYh7YnbhwNJu1sxOo2yqQQc+0wkm06BcEh2I2Wzi6JZV9a85jNllo2z+CjoPqoXKpwVsjr8o9\nDwcWwsEfQZcPIS3lc22tHga1A4Taq0Ht8nF4+EeHDGoWg4Gtn72Ozy8bcTU5EfDoowQ+++y1WWg1\nlkkPfzwnd0jtOAkGzar4uX1DESx4QO6g/dRW8K9fqaXl/fILl959D/cOHQibMxull1elXr+qibAm\nCBVRnCsPZYxfDF61YdDH0GyY490RrWLZqVpWzorHJ9iNEa+1R+3qYPv3BUG4pqhAz+7fznJ6zyU8\n/VzoPqoRjToE1+ytkVcZiuU3tfvmweVj8izOdo9BpymV/ka12pTkwZLhkHnCIYOaJEloN28m9cMP\nIC2Dcy386TtzMW4NG1m7NNthscjvlXZ+AY0HQfTC26+QSRLETIQTf8iNSqroOElBXBzp09/EpXEk\nEfPn4xxgP+fkRVgThFuxWODIz/Dnf+Vl/q7PQp83wcW+7srYgqICPTEfH0CySES/2RFPP/vbiiAI\nwp3LSMpn+7JEslO0hDb2pdeYxqLz61WSBMm75dB2YhVIFmg8UF5ta9AX7KUpgoMHNd3p01z+6GOK\n9+whM1jNrwPdeO/VNQS6ifEM5do3H9a+LndCHbcMPINu/rE7v5TfY/V/G3q+UqVlaXfsIPWFF1GF\nhBCxaCGq0NAqfb3KIsKaINzM5eNyl8fk3RDeBaI+q7zWtDWM0WDm908PkptRxMhpHQiKEGFXEGoS\ni0XixI409vxxDoPOTOv7w+g0pD4ubmJ1/RpNOhz4HuK/h6IseYZVpyeh7Th55c1WXR/UxiyVw6aD\nMOXkkPXlV+THxKD08uLA0EhmhB7i2wHf0TO0p7XLs20n10DsZHk30vjY8o+MnN0MS0fJO5VG/1At\nu5WKDx4k5ZlncXJzI2LhAlwa2f7KqAhrglCWXgvbPobds+VvkAPegzaP2M8dThsjWSQ2zD/G2cNZ\nDHq6FQ3a3uIOmyAIDq1Ea2DPH+c48Xc6bl5quo9oSJMutVCIs6v/MOnlVbZ9cyF1P6g95Q57nZ6E\n4KbWrq40Bw1qksFA7tKfyJ49G4tOh98j4zgxrBUvxf+bx5s/zrRO06xdon1I2Qc/j5FD2CPLIey6\nvJF7Hub1kTujTv4TXKpvtV13+jTJU6aA0UT4vLm4tW5dba99N0RYE4SrJEkewrj+X/Ih1/aPy8vy\n7v7Wrsyu7f7tLAc3XKRHdCPa9o+wdjmCINiAzIsatv+ayOXzGmo18Kb32CZixb08aQflLWXHYsGs\nh/q9ofPT0PjBijdvqColebDkIcg8CWN+gsYDrFtPJbh6Lu3yzJkYLybjed99BE9/g7wQd0atGkWY\nVxhLBy1FpbTPFvBWkZ0ES0eCNlNux990sNxQZOEAKEi50lCkQbWXZUhOJnnSZEy5uYR/+w0e3bpV\new0VJcKaIIDcMnbtG5D0J4S0giGfQXhna1dl907sTGfLj6do0asO9z3SRDQWEAThGskicWrPJXb/\nlkSJ1kiLXqF0HdYAV0/xRvgGRdlwcAnsXwiaVPAJh06Tod0E8LBCo4TiXHmOmgMFNd3p01z++GOK\nd+9B3bAhIW++iWevnpgtZiZtmMSp3FMsH7qcut51rV2q/dFmws8PQ8YRuYv2xV1wbKXcUCSyv9XK\nMl7OJGXKFAwXLlDn00/wHmCb/45FWBNqNpNePty641Nwcob735Jn31j7jqUDSD2dx+ovDxPaxJeo\n59ugVIptpIIg3EhfbGTfmvMc3ZqG2k1J14ca0rxnHTHWozxmEySukxuSnN8OShdoNVpuSFKnbfXU\n4GBBzZSTQ9ZXX5O/YgVKLy8CX3wBvzFjUDjL7wPmHJ7D7COz+bDnhwxtONTK1doxQxGsmAhnNsi/\n7vdfeU6tlZnz80l55llKEhKo/d67+I4aZe2SbiDCmlBznd0McdMg9yy0GAkDP5D3Tgv3LO9SEbEz\n43H3cWHUGx1EEwFBEG4rJ03L9l8TST+TT1CEF73HNqZWAxturGFtmSflLZJHfgVjEYR1lm82Nn8I\nnNVV85rFufLWx6xTMPZniHygal6nGpR3Li1o6lSUvr7XPib+cjyTNkxicP3BfNTrIytW6yDMJvjr\nbTAZYNAMmxl/ZCkuJvWFFynauZPg118nYPIka5dUighrQs1TnCt3eTy+Ut4nPfiTKpvrUROVaA3E\nzIjHqDMRPb0j3oFu1i5JEAQ7IUkSSQcy2RlzhqICA0271aLbiEa4e1dR+HAEugI4/LMc3HLPgkcw\ndJwIHSaCd+3Kex0HCWplz6V53NebkOnTcWlQ+txUgb6A6NXRqJ3ULB+6HA/VbeaFCXZNMhhINUlx\nuwAAIABJREFUmz6dwnXrCXjySYJefcVmjm6IsCbULJIk75s+txV6TYMeL4FKzPuqLGajhT++PETm\nhUKGv9pO3BUXBOGuGHQm4tdd4PCmFJxVTnQe2oCWfULFdupbsVjkHSP75sGZjeCklFuid34KIrre\n2yrGtaB2Gsb+ZLdB7cZzadPx7NXrho+TJIlXt77K1pStLB28lBaBLaxQrVDdJLOZS+++R/6yZfg+\n/DC1/vdfFEqltcuqcFgTe5gEx3BwsfxNbNBM6PK0tatxKJIksfnHk2QkFTBgSgsR1ARBuGtqV2e6\njWhE0261+Xv5Gf5ecYYTO9PpNaYxYU38rF2ebXJykps1RPaXm2btXwiHfpR3kdRqJYe2ltGgdr+z\n65YKaj9btSHE3Sp7Li3k//4PvzEPo1CV38xmReIKNiVv4rUOr4mgVoMolEpqvf0/lL6+5Mydi1mj\nIXTmDBRq+1jZFytrgv3LPQ9zeshzPh77XcxNq2T7486zb/V5ugxrQMfB9axdjiAIDkKSJM4fyebv\nFWcozNHRqGMwPUY1wtNP7Iq4LUMRHF0Be+dB5nFw84N2j8mdJP3q3f75dh7UKnIurawzeWcYFzeO\njiEdmd1/Nk4K8V6hJspZ9D2ZM2fi0aMHYV99iZOH9bbBim2QQs1gMcP3g+UD2VN3gU+YtStyKIn7\nLvHnohM06VqLfo83s5l93oIgOA6TwczBjckc3HARhQI6Dq5H234RKFXizfRtSZLcLn3fXDi5BiSL\nPKuty1PQ4P7yt0gW58KSYZCVaHdBTZIktFu2cHnGjFueSytLZ9IxLm4cubpcYofFEugWWE0VC7Yo\nP3YlGf/5D26tWhE+97tbhvyqVOnbIBUKxSJgCJApSVLL637/BeA5wAzESZL0xl3UKwh3Z9fXkLIH\nRswTQa2SZSTl89eSk9SJ9OX+R5uKoCYIQpVwVivpPKQ+TbvW4u8VZ9jz+zlO7sqg15jG1G1hhVlj\n9kShgHo95B8FaRD/PcT/AD+ug4BIeYtkm7Hg6i1//PVBbdzP0Mh+gprudCKXP/7o2rm08Pnzyj2X\nVp5Z+2eRlJ/Ed/2/E0FNwHfUSJy8vUh/9TUuPjaB8AULUIUEW7usm6rwyppCoegNaIElV8OaQqG4\nH3gLiJIkSa9QKIIlScq81XXEyppQaS4dg/n3y3cRH15iM61iHUFBVgkxMw7g4uZM9PSOYpitIAjV\n5uLxHHYsS6Qgs4T6bQLpOTpSdJ+9EyY9HP9dbkiSdgDUntBmHLR+GOJetbugZsrNJeurr8hffmVe\n2gsv3PJcWlmbLm7ila2v8ESLJ3ito/Xnfwm2o2jPHlKnPofS35+IhQtQ163ewehVsg1SoVDUA9Zc\nF9aWA/MkSdpU0WuIsCZUCpMe5vcFbSZM3QMe4u5rZdEXG4mdGU+xxkD09I74htzhoXVBEIR7ZDZa\nOLI5hf1rLyCZJdoNjKD9wLqo1Nbv4GZX0uLl1v/HYsFskIdt20lQK3UuraQEv0ceIei5W59LKytD\nm8Go1aOI8Irgx0E/olKKG49CaSVHj5Ly5FPg7EzEwgW4NmlSba9dXWHtMPAH8CCgA6ZJkrS/nOc9\nBTwFEBER0eHixYsVfk1BKNemt+Hvz2HcMmjyoLWrsUumnBy0W7fhHBiAKjwcVWgokrOKNV8fIf1M\nPsNeaktoY9GdTRAE69Hm6dm1Mokz+y/j5e9Kz9GR1G8bKLZl3yltFiT8CnXay1smbVi559LeeAOX\nhg3v6Domi4nJGyZzKvcUK4auIMI7oooqFuyd/uxZkidNxlJcTPjc73Bv375aXre6wtoxYAvwItAJ\nWAY0kG5xUbGyJtyz5D3w/SBoNx6GfW3tauyOpaSE3MWLyZm/AEtR0bXflxQKEttMIs23Pe3dj9Oo\nkRJ1eDjq8HBU4eEo/f3FGyRBEKwi7XQe25clkpteRHhzf3o9HIlfLTHM2NGUPZd2s3lpFTH78Gzm\nHJnDhz0/ZGjDoZVcqeBojGlpJE+egvHSJcK++hLP3r2r/DWrK6ytB2ZIkrTlyq/PAl0lScq62TVE\nWBPuiV4L3/WQO2A9uxNcvKxdkd2QzGYK/lhF1pdfYrp8Gc/+/Qh85lkkgwFjagoJB4tIuBRCQ8MR\nGib9jimz9PFThbs76rAwVOHh/zxGhKMKC0cVWgcnFxcr/ZcJglATWMwWjm5LY9+qc5iMFtr0C6fj\n4HqoXcXIWHt3r+fSyjpw6QCTN05mSIMhfNDzg0quVnBUppwckp98En3iGep8/DE+Q6Kq9PWqayj2\n78D9wBaFQtEYUAPZ93hNQbi5jW9B3kWYuFYEtTtQtGsXl2fOQn/qFK6tWhH66Se4d/zn68M5RRgJ\n647SqEMwAya/jMLpFSw6Hca0NAwpKRhTUjGmpmBITsGYfJGinTuRdLp/XkChwDkk5FqIU4WHoQ6P\nQB0eJlblBEGoFE5KJ9r0DSeyYwi7fz/LoY3JpJ/JZ+iLbXFxE4HNHt1wLu3RR+/4XFpZBfoC3tzx\nJmGeYfy7y78rsVrB0TkHBFB38WJSn51K+uuvYynU4DdunLXLuqPW/b8AfYBAhUKRCvwPWAQsurId\n0gA8fqstkIJwTxI3yi2Je7wEdbtbuxq7oEtMJHPWJxTt2IEqNJQ6n36C96BBKK4bHJ55UcOfi44T\nUs9bnqXmJIcqJ1dXXBo2LPecgCRJmLOzMVwNcSkpGJNTMKSmUrRz5+1X5SKubK8MC0cVFoqTWl21\n/yMEQXAY7t5q+k1oRv1WgWyYf4zVXx0Wgc3OVNa5tPKu+9+d/yVHl8PSwUvxUImtssKdUXp5Eb5g\nPmmvvMqld97FnJ9PwDPPWPWGsxiKLdiH4lyY3RXcA+CpreAsttzdivFyJllff0XByt9w8vQk8Jln\n8Bv/6A2hqDBXR8zHB1A6OxH9ZkfcvSsnNJVdlTOkJP+zOpeSKlblBEGoFOcOZ7Fh3jGC6nqJwGYn\ndKcTyZzxMUW7dqNu0ICQf7151+fSylp2ahnv732faR2n8XiLxyvlmkLNJBmNZPzf/1Hwxyr8H59A\n8PTppW50V4bq2gYpCFVPkmDNK3JgGx8rgtotWIqKyFn0PTmLFiGZTPg/9hiBzz5T7pYSQ4mJuG8T\nMBnMDHu5baUFNbiDVbmU5CuPFVyVuxbmxKqcIAjQoG0QA59qyYZ5x1j15WGGvSQCm626/lyak5cX\nIW+9hd/YMXd9Lq2sxLxEZu6fSY/QHjzW/LFKuaZQcylUKmp/9BFO3j7kLl6CuUBD7fffQ+Fc/V9f\nxMqaYPsSVsDKKdDvf9DrVWtXY5Mkk4n8lSvJ+vprzFnZeA16kOBXXkEdUX6r4pJCA2u+OUJWipYh\nz7UmooXtzKm7tiqXLK/GGVJTKrwqd7XhiViVE4Sa5dzhLDbMP0ZguBfDXmyDi7uYp2UrJIOB3J9+\nls+lFRff1by02ykxlTBuzTjy9fnEDIsh0C2w0q4t1GySJJE9Zw7ZX32NZ9++hH7+WaU1VKuSbpCV\nQYQ14Y4UpMGcbhDUFCauAycxEPV6kiRRtH07mZ98gv5MEm7t2hH8xuu4t2t30+cU5upY9eVhCnN1\nPPhkS+q1tp9vav+syqXIq3HXrcoZU1JuvioXEY46TKzKCYIjE4HNttxwLq13L0KmT7/nc2nleXf3\nu6xIXMHc/nPpHirOtAuVL/enn7j83vu4d+5M2OxvUXp63vM1RVgT7J/FAktHQso+eGYHBFT+F3h7\npjtxgsuzZlG8ew+quhEEv/YaXg88cMuVpNyMIlZ/dRiDzkzU1NbUiay8O5u2wKLTYUxN/eesXEVX\n5SKunJETq3KCYNfOH8li/bxjBIZ5ylsiRWCzihvOpb05vcrmVv158U9e3foqE1tO5NUOYveNUHUK\nVq8h/V//wrVJE8Lnz8PZ3/+erifCmmD/9s2HtdNgyOfQcZK1q7EZxowMsr74koJVq1D6+BD43HPy\nPJrbrBJdPq9hzTdHUCgVDHuxDYFhNWv0gSRJmLKyMF5ZhSu1KpecjCmr9HjIclfl6tbDvXMnsSIn\nCDZMBDbrKXsuLej55yv1XFpZGdoMRq0eRV2vuiwZtASVUvxdC1WrcOtW0l56GVWdOkQsXICqTp27\nvpYIa4J9yz4D3/WCej3g0RgQKxyYtVpy5s0nd/FikCT8JzxGwFNPofT2vu1zU07msva7o7h7qRj2\nUlt8gtyroWL7YikpKd3BMrV0J0tJrwdA6eeHz7Bh+EaPwiUy0spVC4JQnvMJ2ayfe1QEtmpSHefS\nyjJZTEzaMInEvERWDFlBuHd4lb2WIFyvOD6elGeexcnDg4hFC3Fp0OCuriPCmmC/zCZYNAByz8Gz\nu8G7trUrsirJaCRvxQqyv/kWc24u3kOHEvzyS6hCQyv0/KT4TP5cdBy/Wu4MfbEtHj6im+aduroq\npztxgoLffqdw82YwGnFr0waf6FF4DxqM0lPM8xEEWyICW9WrznNpZX17+Fu+O/IdH/X6iCENhlT5\n6wnC9XQnT5I85UmwWAifNw+3Vi3v+BoirAn2a9ss2PI+RH8PLUdauxqrkSQJ7ebNZM76BMOFC7h3\n7kzw66/f0ReEY9vT2PbLaWo38GHw1Na4eog3K5XBlJtLwR+ryI+NwZB0FoW7O96DHsQ3Ohq3tm3F\nWTdBsBHXB7ahL7YVXwMrUXWeSytr/6X9TNk4hSENhvBBzw+q5TUFoSzDhQskT5qMOT+fsNmz8eja\n5Y6eL8KaYJ/SD8GC/tB8OEQvtHY1VlOSkMDlmTMpORCPukEDgqdNw/P+PhUOAZIkEb/+Inv/OEfd\nlgEMfKolKrXopFnZJElCd+QIeTExaNauQyouRt2wIb6jRuHz0DCcA2xnJIIg1FQXErJZJwJbpTHl\n5pL19dfkL1teLefSysrX5TNq9SjcnN1YNmQZHiqxq0GwHuPlyyRPnowxOYXQzz7Fq3//Cj9XhDXB\n/hhLYO59oNfA1N3g5mftiqqdITWNrM8/RxMXhzIggKAXnsc3OvqOhjBKFomdsUkc+SuFxl1C6Duh\nGUqlUxVWLQCYtUUUrl9HfkwsJYcPg7MzXn374hs9Co8ePVAoRVgWBGu5kJDNunlHCagjb4kUge3O\n3XAubdw4Ap+birNf9X2vliSJl7a8xI60HSwdvJQWAS2q7bUF4WZMeXmkPP0MumPHqP3++/iOHFGh\n54mwJtifDW/B7m9g/Epo1M/a1VQrc0EB2XPnkffjj6BU4j/xCQImT7njc1Bms4UtS05xeu8lWt8f\nRs/RkSicxJa86qZPSiI/JpaCP/7AnJeHc61a+I4cgc/IUajDKnbWUBCEW7NYJJzu4OubCGx3Rz6X\ntpXMGTMwXLyIR69ehLxZPefSyvr11K98sPcDXu/4OhNaTKj21xeEm7EUFZH6wgsU7dpN8JvTCXji\nids+R4Q1wb6c3wGLh0KnyRD1qbWrqTaSwUDeL7+QPXsOZo0GnxEjCHrxBVS1at3xtUwGMxvmH+PC\n0Ry6DKtPh0H1xNkpK5MMBgo3byE/Npaiv/8GwKNbV3xGjcKrf3+cXESzF0G4U5IksTohg7dXHadb\nwwBmRbfGXV2x3QcXjspbIkVgqxhrnksrKzEvkXFrxtG5dme+7fctTgqxY0SwLRaDgfRpr1O4cSMB\nzzxN0Esv3fJ9mAhrgv3QaWBOd1Cq5eHXasfffy5JEoUbNpL52WcYk5Px6N6N4DfewLVp07u6nr7Y\nSNzsBDLOFnDf2Ma0vC+skisW7pUxPZ38336jIHYlxvR0lD4+eF8ZAeDapIm1yxMEu5Cj1fOfP46x\n9uglGgV7ci5LS+MQL+ZP6Ei4f8VGkojAdnvWPpdWVomphLFrxlKgLyB2WCwBbuI8sGCbJLOZjP/9\nj4KYWHzHjqHWf/5z02MQIqwJ9uP3qXDkF5i0EcI7WbuaKld88BCZM2dScvgwLpGRBL/xOh49e971\nKlhRgZ7VXx8hL6OI/hObE9kxpJIrFiqTZLFQtHs3BbGxFP65CcloxLVVK3xHjcJ7SBRKT09rlygI\nNmn9sUu89dtRCnUmXn4gkqd6NeDvpGxe+OUQKqUTsx9tT9cGFXsTLwJb+WzhXFp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ezH+FCPdm/eIggCxTW1jYw+UgqquVBUjUqtA0AiAV8nq/oURjuDMPNztsKkiVNIm8O6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\nTURERERExA8pWRMREREREfFD/x+46ZaPC61r2QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f3781a5e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boroughs with Processing Time on a monthly basis\n",
    "df.groupby(['YYYY-MM','Borough'])['Processing Time Float'].mean().unstack().plot(figsize=(15,7),\n",
    "                                                                        title='Processing time per Borough on a monthly basis');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iBDoAAICJ2mmgq6rXVNWlVXX2orYXVtV/VNVZVXVyVe27wnPPr6p/r6ozq2rb7iwcAABg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\nQAcAADBR/w9o3YHnNBR68QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30707f198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Processing time per Borough\n",
    "df.groupby('Borough')['Processing Time Float'].mean().plot(kind='bar', figsize=(15,7),\n",
    "                                                          title='Processing Time per Borough');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cmZl5eM6cORnbt2/3paWlRbozRkagAQAAAHSbe2ev0b2z1/R2GPgIqqqq6uPz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\ngAYAAAAAoA4soAEAAAAAqMP/A9Dr4YHHNx9VAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f374f5ea90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visulization of Number of Complaints per Agency on a monthly basis\n",
    "date_agency = df.groupby(['YYYY-MM', 'Agency'])\n",
    "date_agency.size().unstack().plot(kind='bar', figsize=(15,7), title='Number of Complaints per Agency on a monthly basis');\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JPWUglCRJkqSeMhBKkiRJUk8ZCCVJkiSppwyEkiRJktRTBkJJkiRJ6ikDoSRJkiT1lIFQ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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f3773f6c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of Agency with their number of Complaints\n",
    "df.groupby('Agency').size().sort_values(ascending=False).plot(kind='bar',figsize=(15,7),\n",
    "                                                             title='Number of Complaints per Agency');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Since HPD has the most complaints, I'll explore data relating to HPD to learn more about complaints handled by HPD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eYa39MUd5tLOPhtbaUVmz0tbaVGvtv621jay1IdbaYtmuo0ezWjSrXZl3lmwm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FtRMb7iIjw5OQrhIjJrDO7eTdu6dXQ+/Ai2v5+s1aspvPgi5pxxBsbrTXbxZAZJ5qwg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\n+ZU19SqGWL4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30c758b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of Incidents handled by HPD by Borough on a monthly basis\n",
    "df[df['Agency']=='HPD'].groupby(['YYYY-MM','Borough']).size().unstack().plot(figsize=(12,7),\n",
    "                                                                            title='Incidents per Borough on a monthly basis');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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S1JAJtyRJktSQCbckSZLUkAm3JEmS1JAJtyRJktSQCbckSZLUkAm3JEmS1JAJtyRJktSQ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\nZNb23/JT7RK2KTROq3U6paQpPwrdgfSLuT3wU9tvqBtVfXl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B9wAn933vo8D6AJKOBv5i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\nhBGKCXcIIYQQQggj9P8BPnWOHlonL2UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30a978e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualizations of Complaints handled by HPD\n",
    "df[df['Agency']=='HPD'].groupby('Complaint Type').size().sort_values(ascending=False).plot(kind='bar',\n",
    "                                                                                          figsize=(12,6),\n",
    "                                                                        title='Number of each complaint type handled by HPD');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizations of Complaint Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HVdV1bfm7wIPa8lbA1SP7XtPatmrL09vX2KeqbgNuBjafZ8ySJEmSJOZ/H8In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\nCCGE2VQMCEMIIYQQQghhNvX/fVNUrLVImy0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f38b4b7a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization of number of complaint type\n",
    "df.groupby('Complaint Type').size().sort_values(ascending=False)[:20].plot(kind='bar', figsize=(15,6),\n",
    "                                                                          title='Bar graph of Complaint Type');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Noise - Residential has the most complaints, lets explore it further "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kHSVppqSZixcvbjJ0MzNr1eAml9srIuZL2gy4XtKjxZkREZKi78PrKiLOB84HGDdu3Gp/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\nMxQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f3782b2630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Borough with the most Noise Complaints - Residential\n",
    "df[df['Complaint Type']=='Noise - Residential'].groupby('Borough').size()[:10].sort_values(ascending=False).plot(kind='bar',\n",
    "                                                                            title='Residential Noise Complaints per Borough');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Brooklyn has the most noise complaints for residential, it would be interesting to know if this noise peaked anytime within the year of if its uniform through the year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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p7ZIkSdJgzOZTOAL8FfCNqnr3yKxzgKPa9FHA2SPtRyR5WJI96C4WvLQN97gr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\nkiSpBwO0JEmS1IMBWpIkSerh/weWo/CahnvnFAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30cf83b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "brooklyn_noise = df[(df['Borough']=='BROOKLYN') & (df['Complaint Type']=='Noise - Residential')]\n",
    "brooklyn_noise.groupby('YYYY-MM').size().plot(kind='bar', figsize=(12,6),\n",
    "                                             title='Residential noise complaint in Brooklyn on a monthly basis');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M3RgTB7istRXe+x8D9wJnAHuttX8wxtwFJFtrf2mMGQ68gBP2e+I0whtorW00xnwD/Cew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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f30c8efe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Complaints per Borough through the year\n",
    "df.groupby(['YYYY-MM','Borough']).size().unstack().plot(figsize=(15,6))\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Observations</h2>\n",
    "<br>\n",
    "<li>Brooklyn has the highest the number of incident calls followed by Queens. Staten Island has the least incident calls.</li>\n",
    "<li>HPD has the most incident calls follwed by NYPD.</li>\n",
    "<li>Majority of incidents occur in January followed by November and then the incident calls dips to its lowest in September followed by April.</li>\n",
    "<li>HPD related incident calls follow a nearly regular pattern across all boroughs from month to month. Heat/Hot water complaints are the most frequent </li>\n",
    "<li>Noise in residential areas were the most complaints in 2014 followed by Heat/Hot water complaints</li>\n",
    "<li>Noise complaints were peaked in September and was lowest in February</li>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Conclusion</h2>\n",
    "<p>Brooklyn has on average the slowest processing from month to month and this caould be associated with the fact that it has the highest number of incident calls, but it should be noted that while Staten Island has by far the lowest incident calls, it doesn't have the fastest processing time. Further analysis should be carried out to understand the variances in processing time\n",
    "</p>\n",
    "<p>Incident calls spike during winter period, during this same period, HPD related incidents spike. This can be explained by the fact that people are complaining about heat or hot water related problems\n",
    "</p>\n",
    "<p>More data from other years are required to know whether a trend does exist in number of monthly incident complaints and in the type of complaints. If a trend does exist, city officials would need to employ more agents during those periods to resolve complaints faster. In addition, during winter periods, city officials should ensure heating systems work so as to reduce heating related complaints\n",
    "</p>"
   ]
  }
 ],
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