{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime, date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = 120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "      <th>Application Category</th>\n",
       "      <th>Application Type</th>\n",
       "      <th>Application Criteria</th>\n",
       "      <th>Application Stream</th>\n",
       "      <th>Application Substream</th>\n",
       "      <th>Branch Location</th>\n",
       "      <th>Decision Type</th>\n",
       "      <th>Job Offer?</th>\n",
       "      <th>Applicant Type</th>\n",
       "      <th>...</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Financial Year Decided</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Occupation Standard</th>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th>Standard Minor Group</th>\n",
       "      <th>Standard Unit Group</th>\n",
       "      <th>Region</th>\n",
       "      <th>Period</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-11-01</th>\n",
       "      <td>2</td>\n",
       "      <td>Group Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew of foreign fishing vessel</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew</td>\n",
       "      <td>Offshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006/07</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-11-01</th>\n",
       "      <td>4</td>\n",
       "      <td>Group Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew of foreign fishing vessel</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew</td>\n",
       "      <td>Offshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-01</th>\n",
       "      <td>1</td>\n",
       "      <td>Group Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew of foreign fishing vessel</td>\n",
       "      <td>Work</td>\n",
       "      <td>Crew</td>\n",
       "      <td>Offshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Number of Applications Application Category Application Type  \\\n",
       "Month Decided                                                                 \n",
       "2006-11-01                          2           Group Visa             Work   \n",
       "2007-11-01                          4           Group Visa             Work   \n",
       "2007-12-01                          1           Group Visa             Work   \n",
       "\n",
       "                         Application Criteria Application Stream  \\\n",
       "Month Decided                                                      \n",
       "2006-11-01     Crew of foreign fishing vessel               Work   \n",
       "2007-11-01     Crew of foreign fishing vessel               Work   \n",
       "2007-12-01     Crew of foreign fishing vessel               Work   \n",
       "\n",
       "              Application Substream Branch Location Decision Type  \\\n",
       "Month Decided                                                       \n",
       "2006-11-01                     Crew        Offshore      Approved   \n",
       "2007-11-01                     Crew        Offshore      Approved   \n",
       "2007-12-01                     Crew        Offshore      Approved   \n",
       "\n",
       "                 Job Offer?                    Applicant Type    ...      \\\n",
       "Month Decided                                                    ...       \n",
       "2006-11-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "2007-11-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "2007-12-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "\n",
       "              Gender Financial Year Decided      Occupation  \\\n",
       "Month Decided                                                 \n",
       "2006-11-01      Male                2006/07  (not recorded)   \n",
       "2007-11-01      Male                2007/08  (not recorded)   \n",
       "2007-12-01      Male                2007/08  (not recorded)   \n",
       "\n",
       "              Occupation Standard Standard Major Group  \\\n",
       "Month Decided                                            \n",
       "2006-11-01                    NaN       (not recorded)   \n",
       "2007-11-01                    NaN       (not recorded)   \n",
       "2007-12-01                    NaN       (not recorded)   \n",
       "\n",
       "              Standard Submajor Group Standard Minor Group  \\\n",
       "Month Decided                                                \n",
       "2006-11-01             (not recorded)       (not recorded)   \n",
       "2007-11-01             (not recorded)       (not recorded)   \n",
       "2007-12-01             (not recorded)       (not recorded)   \n",
       "\n",
       "              Standard Unit Group     Region     Period  \n",
       "Month Decided                                            \n",
       "2006-11-01         (not recorded)  (unknown)  01JUL2010  \n",
       "2007-11-01         (not recorded)  (unknown)  01JUL2010  \n",
       "2007-12-01         (not recorded)  (unknown)  01JUL2010  \n",
       "\n",
       "[3 rows x 22 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_hdf('work_visas_2005-2016.hdf','table')\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Application Category</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Group Visa</th>\n",
       "      <td>289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Permit</th>\n",
       "      <td>323645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Visa</th>\n",
       "      <td>1573258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Number of Applications\n",
       "Application Category                        \n",
       "Group Visa                               289\n",
       "Permit                                323645\n",
       "Visa                                 1573258"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Application Category').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Application Type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Limited</th>\n",
       "      <td>80171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Visitor's</th>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Work</th>\n",
       "      <td>1816954</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Number of Applications\n",
       "Application Type                        \n",
       "Limited                            80171\n",
       "Visitor's                             67\n",
       "Work                             1816954"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Application Type').sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Limited** Visas are often granted to people that have a potential risk of remaining in New Zealand unlawfully after their visa expires. It is Immigration New Zealand's (INZ) way of giving you an opportunity to come to New Zealand for an express purpose even when they see potential risks within your application."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Response Outside Scope/Not Stated</th>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elementary Occupations (incl Residuals)</th>\n",
       "      <td>2877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clerks</th>\n",
       "      <td>2963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plant and Machine Operators and Assemblers</th>\n",
       "      <td>7422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Responses outside of the current definition of the labour force</th>\n",
       "      <td>7531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agriculture and Fishery Workers</th>\n",
       "      <td>8498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trades Workers</th>\n",
       "      <td>8889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Legislators, Administrators and Managers</th>\n",
       "      <td>9261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Machinery Operators and Drivers</th>\n",
       "      <td>15328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technicians and Associate Professionals</th>\n",
       "      <td>16231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sales Workers</th>\n",
       "      <td>17639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clerical and Administrative Workers</th>\n",
       "      <td>18681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Service and Sales Workers</th>\n",
       "      <td>22364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Labourers</th>\n",
       "      <td>46650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Managers</th>\n",
       "      <td>75281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Community and Personal Service Workers</th>\n",
       "      <td>88090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technicians and Trades Workers</th>\n",
       "      <td>115775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professionals</th>\n",
       "      <td>160923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(not recorded)</th>\n",
       "      <td>1272511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Number of Applications\n",
       "Standard Major Group                                                      \n",
       "Response Outside Scope/Not Stated                                      278\n",
       "Elementary Occupations (incl Residuals)                               2877\n",
       "Clerks                                                                2963\n",
       "Plant and Machine Operators and Assemblers                            7422\n",
       "Responses outside of the current definition of ...                    7531\n",
       "Agriculture and Fishery Workers                                       8498\n",
       "Trades Workers                                                        8889\n",
       "Legislators, Administrators and Managers                              9261\n",
       "Machinery Operators and Drivers                                      15328\n",
       "Technicians and Associate Professionals                              16231\n",
       "Sales Workers                                                        17639\n",
       "Clerical and Administrative Workers                                  18681\n",
       "Service and Sales Workers                                            22364\n",
       "Labourers                                                            46650\n",
       "Managers                                                             75281\n",
       "Community and Personal Service Workers                               88090\n",
       "Technicians and Trades Workers                                      115775\n",
       "Professionals                                                       160923\n",
       "(not recorded)                                                     1272511"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df.groupby('Standard Major Group').sum().sort_values('Number of Applications')\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1.drop('(not recorded)',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xc60f9b0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lY5JDgU8CVwLrgLOA97dq7kpyEHAacC0wBAyWUs4c99VKkqQtzuAuTYBm7fVx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gi4/kICXttYf4b46Gtbn/0LAeh77f+3WApxxEOtIYrjTGJVGWjP/m8sdGR4FpIFfn4k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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc5074a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.plot(kind='bar')\n",
    "fig = plt.gcf()\n",
    "ax=plt.gca()\n",
    "ax.legend().remove()\n",
    "fig.autofmt_xdate()\n",
    "plt.title(\"Work Visas Granted 2005-2016\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">(not recorded)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>49490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>111029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>119645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>118173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>113575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>105249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>104334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>107509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>116680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>130661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>147405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>48761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Agriculture and Fishery Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>1807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Clerical and Administrative Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Clerks</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Community and Personal Service Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>8599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>9403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>8264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>8041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>8332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>9730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>10779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>12346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>3747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Elementary Occupations (incl Residuals)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Labourers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>5476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>3999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>3380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>4028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>5445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>7102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>2937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Legislators, Administrators and Managers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Machinery Operators and Drivers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>10400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>14668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>15634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>15121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>13694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>13623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>16249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>17158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>16106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Response Outside Scope/Not Stated</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Responses outside of the current definition of the labour force</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>1218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Sales Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Service and Sales Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>6042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>14033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Technicians and Associate Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>9588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"11\" valign=\"top\">Technicians and Trades Workers</th>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>11804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>10792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>9238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>11721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>5886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Trades Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  Number of Applications\n",
       "Standard Major Group                               Month Decided                        \n",
       "(not recorded)                                     2006-12-31                      49490\n",
       "                                                   2007-12-31                     111029\n",
       "                                                   2008-12-31                     119645\n",
       "                                                   2009-12-31                     118173\n",
       "                                                   2010-12-31                     113575\n",
       "                                                   2011-12-31                     105249\n",
       "                                                   2012-12-31                     104334\n",
       "                                                   2013-12-31                     107509\n",
       "                                                   2014-12-31                     116680\n",
       "                                                   2015-12-31                     130661\n",
       "                                                   2016-12-31                     147405\n",
       "                                                   2017-12-31                      48761\n",
       "Agriculture and Fishery Workers                    2006-12-31                       1807\n",
       "                                                   2007-12-31                       5742\n",
       "                                                   2008-12-31                        949\n",
       "Clerical and Administrative Workers                2008-12-31                       2037\n",
       "                                                   2009-12-31                       2152\n",
       "                                                   2010-12-31                       1905\n",
       "                                                   2011-12-31                       1687\n",
       "                                                   2012-12-31                       1588\n",
       "                                                   2013-12-31                       1698\n",
       "                                                   2014-12-31                       1874\n",
       "                                                   2015-12-31                       2190\n",
       "                                                   2016-12-31                       2567\n",
       "                                                   2017-12-31                        983\n",
       "Clerks                                             2006-12-31                        840\n",
       "                                                   2007-12-31                       1863\n",
       "                                                   2008-12-31                        260\n",
       "Community and Personal Service Workers             2008-12-31                       8599\n",
       "                                                   2009-12-31                       8849\n",
       "                                                   2010-12-31                       9403\n",
       "                                                   2011-12-31                       8264\n",
       "                                                   2012-12-31                       8041\n",
       "                                                   2013-12-31                       8332\n",
       "                                                   2014-12-31                       9730\n",
       "                                                   2015-12-31                      10779\n",
       "                                                   2016-12-31                      12346\n",
       "                                                   2017-12-31                       3747\n",
       "Elementary Occupations (incl Residuals)            2006-12-31                        793\n",
       "                                                   2007-12-31                       1816\n",
       "                                                   2008-12-31                        268\n",
       "Labourers                                          2008-12-31                       5476\n",
       "                                                   2009-12-31                       4555\n",
       "                                                   2010-12-31                       3999\n",
       "                                                   2011-12-31                       3573\n",
       "                                                   2012-12-31                       3380\n",
       "                                                   2013-12-31                       4028\n",
       "                                                   2014-12-31                       5445\n",
       "                                                   2015-12-31                       6155\n",
       "                                                   2016-12-31                       7102\n",
       "                                                   2017-12-31                       2937\n",
       "Legislators, Administrators and Managers           2006-12-31                       2710\n",
       "                                                   2007-12-31                       5754\n",
       "                                                   2008-12-31                        794\n",
       "                                                   2009-12-31                          2\n",
       "                                                   2010-12-31                          1\n",
       "Machinery Operators and Drivers                    2008-12-31                       1876\n",
       "                                                   2009-12-31                       1532\n",
       "                                                   2010-12-31                       1502\n",
       "                                                   2011-12-31                       1366\n",
       "...                                                                                  ...\n",
       "Professionals                                      2006-12-31                       4690\n",
       "                                                   2007-12-31                      10400\n",
       "                                                   2008-12-31                      14668\n",
       "                                                   2009-12-31                      15634\n",
       "                                                   2010-12-31                      15121\n",
       "                                                   2011-12-31                      13694\n",
       "                                                   2012-12-31                      13623\n",
       "                                                   2013-12-31                      16249\n",
       "                                                   2014-12-31                      17158\n",
       "                                                   2015-12-31                      16106\n",
       "                                                   2016-12-31                      17425\n",
       "                                                   2017-12-31                       6155\n",
       "Response Outside Scope/Not Stated                  2006-12-31                        134\n",
       "                                                   2007-12-31                        133\n",
       "                                                   2008-12-31                         11\n",
       "Responses outside of the current definition of ... 2008-12-31                        110\n",
       "                                                   2009-12-31                        255\n",
       "                                                   2010-12-31                        296\n",
       "                                                   2011-12-31                        521\n",
       "                                                   2012-12-31                        820\n",
       "                                                   2013-12-31                       1363\n",
       "                                                   2014-12-31                       1276\n",
       "                                                   2015-12-31                       1218\n",
       "                                                   2016-12-31                       1162\n",
       "                                                   2017-12-31                        510\n",
       "Sales Workers                                      2008-12-31                       1477\n",
       "                                                   2009-12-31                       1702\n",
       "                                                   2010-12-31                       1565\n",
       "                                                   2011-12-31                       1454\n",
       "                                                   2012-12-31                       1696\n",
       "                                                   2013-12-31                       1687\n",
       "                                                   2014-12-31                       1869\n",
       "                                                   2015-12-31                       2367\n",
       "                                                   2016-12-31                       2841\n",
       "                                                   2017-12-31                        981\n",
       "Service and Sales Workers                          2006-12-31                       6042\n",
       "                                                   2007-12-31                      14033\n",
       "                                                   2008-12-31                       2280\n",
       "                                                   2009-12-31                          8\n",
       "                                                   2014-12-31                          1\n",
       "Technicians and Associate Professionals            2006-12-31                       4668\n",
       "                                                   2007-12-31                       9588\n",
       "                                                   2008-12-31                       1591\n",
       "                                                   2009-12-31                        325\n",
       "                                                   2010-12-31                         59\n",
       "Technicians and Trades Workers                     2007-12-31                          1\n",
       "                                                   2008-12-31                      11098\n",
       "                                                   2009-12-31                      11804\n",
       "                                                   2010-12-31                      10792\n",
       "                                                   2011-12-31                       9238\n",
       "                                                   2012-12-31                       9734\n",
       "                                                   2013-12-31                      11721\n",
       "                                                   2014-12-31                      13485\n",
       "                                                   2015-12-31                      14975\n",
       "                                                   2016-12-31                      17041\n",
       "                                                   2017-12-31                       5886\n",
       "Trades Workers                                     2006-12-31                       2613\n",
       "                                                   2007-12-31                       5434\n",
       "                                                   2008-12-31                        839\n",
       "                                                   2009-12-31                          3\n",
       "\n",
       "[140 rows x 1 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df.groupby(['Standard Major Group', pd.Grouper(freq='A')]).sum()\n",
    "#df1.drop('(not recorded)', axis=0, inplace=True)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2007, 2009])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.loc['Technicians and Trades Workers'].iloc[[0,2]].index.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Response Outside Scope/Not Stated</th>\n",
       "      <td>278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elementary Occupations (incl Residuals)</th>\n",
       "      <td>2877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clerks</th>\n",
       "      <td>2963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Plant and Machine Operators and Assemblers</th>\n",
       "      <td>7422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Responses outside of the current definition of the labour force</th>\n",
       "      <td>7531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agriculture and Fishery Workers</th>\n",
       "      <td>8498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trades Workers</th>\n",
       "      <td>8889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Legislators, Administrators and Managers</th>\n",
       "      <td>9261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Machinery Operators and Drivers</th>\n",
       "      <td>15328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technicians and Associate Professionals</th>\n",
       "      <td>16231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sales Workers</th>\n",
       "      <td>17639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clerical and Administrative Workers</th>\n",
       "      <td>18681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Service and Sales Workers</th>\n",
       "      <td>22364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Labourers</th>\n",
       "      <td>46650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Managers</th>\n",
       "      <td>75281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Community and Personal Service Workers</th>\n",
       "      <td>88090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technicians and Trades Workers</th>\n",
       "      <td>115775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professionals</th>\n",
       "      <td>160923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(not recorded)</th>\n",
       "      <td>1272511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Number of Applications\n",
       "Standard Major Group                                                      \n",
       "Response Outside Scope/Not Stated                                      278\n",
       "Elementary Occupations (incl Residuals)                               2877\n",
       "Clerks                                                                2963\n",
       "Plant and Machine Operators and Assemblers                            7422\n",
       "Responses outside of the current definition of ...                    7531\n",
       "Agriculture and Fishery Workers                                       8498\n",
       "Trades Workers                                                        8889\n",
       "Legislators, Administrators and Managers                              9261\n",
       "Machinery Operators and Drivers                                      15328\n",
       "Technicians and Associate Professionals                              16231\n",
       "Sales Workers                                                        17639\n",
       "Clerical and Administrative Workers                                  18681\n",
       "Service and Sales Workers                                            22364\n",
       "Labourers                                                            46650\n",
       "Managers                                                             75281\n",
       "Community and Personal Service Workers                               88090\n",
       "Technicians and Trades Workers                                      115775\n",
       "Professionals                                                       160923\n",
       "(not recorded)                                                     1272511"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df.groupby('Standard Major Group').sum().sort_values('Number of Applications')\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def dateGroupData(dataset, date_ranges, exclusions=[]):\n",
    "    newlist = []\n",
    "    for l in dataset.index.get_level_values(0).tolist():\n",
    "        if l not in newlist and l not in exclusions:\n",
    "            newlist.append(l)\n",
    "    d = []\n",
    "\n",
    "    for l in newlist:\n",
    "        cum = np.zeros(len(date_ranges), np.uint32)\n",
    "        for idx, ranges in enumerate(date_ranges):\n",
    "            y1,y2 = ranges\n",
    "            for ix, s in dataset.loc[l].iterrows():\n",
    "                #print (ix.year,s)\n",
    "                if y1 <= ix.year <= y2:\n",
    "                    cum[idx]+= (s.iat[0])\n",
    "        d.append((l,cum))\n",
    "\n",
    "    ylist = sorted (d, key=lambda x:sum(x[1]))\n",
    "\n",
    "    vals = np.zeros((len(date_ranges),len(newlist)),np.uint32 )\n",
    "    \n",
    "    xlabels=[]\n",
    "    for idx, elmts in enumerate(ylist):\n",
    "        xlabels.append(elmts[0])\n",
    "        for idx2, el in enumerate(elmts[1]):\n",
    "            vals[idx2][idx]=el\n",
    "    #print (xlabels)\n",
    "    return (xlabels, vals)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 5, 4])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array((2,3,0))+np.array((1,2,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def colourRange(colours, n, skipFirst=False):\n",
    "    start, end = colours\n",
    "    val = list(start)\n",
    "    diff = [float(y-x)/(n-1) for x,y in zip(start, end)]\n",
    "    if not skipFirst:\n",
    "        yield val\n",
    "    for ii in range(0, n-1):\n",
    "        for jj in range(0,3):\n",
    "            val[jj] += diff[jj]\n",
    "        yield val\n",
    "\n",
    "from itertools import izip\n",
    "\n",
    "\n",
    "\n",
    "def stackedTimeBars(plt, vals, colors, width=0.85):\n",
    "    ind = np.arange(1,len(vals[0])+1)    # the x locations for the groups\n",
    "    #width = 0.3       # the width of the bars: can also be len(x) sequence\n",
    "    p1 = plt.bar(ind, vals[0], width, color=colors[0])\n",
    "    ps = [p1]\n",
    "    for ii, clr in izip(range(0,len(vals)-1), colourRange(colors,len(vals),skipFirst=True)):\n",
    "        bottoms = np.copy(vals[0])\n",
    "        for jj in range(0,ii):\n",
    "            bottoms += vals[jj+1]\n",
    "        p = plt.bar(ind, vals[ii+1], width, bottom=bottoms,  color=clr)\n",
    "        ps.append(p)\n",
    "    return ps\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">(not recorded)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>49490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>111029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>119645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>118173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>113575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>105249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>104334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>107509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>116680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>130661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>147405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>48761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Agriculture and Fishery Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>1807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Clerical and Administrative Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Clerks</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Community and Personal Service Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>8599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>9403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>8264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>8041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>8332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>9730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>10779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>12346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>3747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Elementary Occupations (incl Residuals)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Labourers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>5476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>3999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>3380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>4028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>5445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>7102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>2937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Legislators, Administrators and Managers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Machinery Operators and Drivers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>10400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>14668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>15634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>15121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>13694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>13623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>16249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>17158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>16106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Response Outside Scope/Not Stated</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Responses outside of the current definition of the labour force</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>1218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"15\" valign=\"top\">Sales Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>6042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>14033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Technicians and Associate Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>9588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"15\" valign=\"top\">Technicians and Trades Workers</th>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>11804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>10792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>9238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>11721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>5886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  Number of Applications\n",
       "Standard Major Group                               Month Decided                        \n",
       "(not recorded)                                     2006-12-31                      49490\n",
       "                                                   2007-12-31                     111029\n",
       "                                                   2008-12-31                     119645\n",
       "                                                   2009-12-31                     118173\n",
       "                                                   2010-12-31                     113575\n",
       "                                                   2011-12-31                     105249\n",
       "                                                   2012-12-31                     104334\n",
       "                                                   2013-12-31                     107509\n",
       "                                                   2014-12-31                     116680\n",
       "                                                   2015-12-31                     130661\n",
       "                                                   2016-12-31                     147405\n",
       "                                                   2017-12-31                      48761\n",
       "Agriculture and Fishery Workers                    2006-12-31                       1807\n",
       "                                                   2007-12-31                       5742\n",
       "                                                   2008-12-31                        949\n",
       "Clerical and Administrative Workers                2008-12-31                       2037\n",
       "                                                   2009-12-31                       2152\n",
       "                                                   2010-12-31                       1905\n",
       "                                                   2011-12-31                       1687\n",
       "                                                   2012-12-31                       1588\n",
       "                                                   2013-12-31                       1698\n",
       "                                                   2014-12-31                       1874\n",
       "                                                   2015-12-31                       2190\n",
       "                                                   2016-12-31                       2567\n",
       "                                                   2017-12-31                        983\n",
       "Clerks                                             2006-12-31                        840\n",
       "                                                   2007-12-31                       1863\n",
       "                                                   2008-12-31                        260\n",
       "Community and Personal Service Workers             2008-12-31                       8599\n",
       "                                                   2009-12-31                       8849\n",
       "                                                   2010-12-31                       9403\n",
       "                                                   2011-12-31                       8264\n",
       "                                                   2012-12-31                       8041\n",
       "                                                   2013-12-31                       8332\n",
       "                                                   2014-12-31                       9730\n",
       "                                                   2015-12-31                      10779\n",
       "                                                   2016-12-31                      12346\n",
       "                                                   2017-12-31                       3747\n",
       "Elementary Occupations (incl Residuals)            2006-12-31                        793\n",
       "                                                   2007-12-31                       1816\n",
       "                                                   2008-12-31                        268\n",
       "Labourers                                          2008-12-31                       5476\n",
       "                                                   2009-12-31                       4555\n",
       "                                                   2010-12-31                       3999\n",
       "                                                   2011-12-31                       3573\n",
       "                                                   2012-12-31                       3380\n",
       "                                                   2013-12-31                       4028\n",
       "                                                   2014-12-31                       5445\n",
       "                                                   2015-12-31                       6155\n",
       "                                                   2016-12-31                       7102\n",
       "                                                   2017-12-31                       2937\n",
       "Legislators, Administrators and Managers           2006-12-31                       2710\n",
       "                                                   2007-12-31                       5754\n",
       "                                                   2008-12-31                        794\n",
       "                                                   2009-12-31                          2\n",
       "                                                   2010-12-31                          1\n",
       "Machinery Operators and Drivers                    2008-12-31                       1876\n",
       "                                                   2009-12-31                       1532\n",
       "                                                   2010-12-31                       1502\n",
       "                                                   2011-12-31                       1366\n",
       "...                                                                                  ...\n",
       "Professionals                                      2006-12-31                       4690\n",
       "                                                   2007-12-31                      10400\n",
       "                                                   2008-12-31                      14668\n",
       "                                                   2009-12-31                      15634\n",
       "                                                   2010-12-31                      15121\n",
       "                                                   2011-12-31                      13694\n",
       "                                                   2012-12-31                      13623\n",
       "                                                   2013-12-31                      16249\n",
       "                                                   2014-12-31                      17158\n",
       "                                                   2015-12-31                      16106\n",
       "                                                   2016-12-31                      17425\n",
       "                                                   2017-12-31                       6155\n",
       "Response Outside Scope/Not Stated                  2006-12-31                        134\n",
       "                                                   2007-12-31                        133\n",
       "                                                   2008-12-31                         11\n",
       "Responses outside of the current definition of ... 2008-12-31                        110\n",
       "                                                   2009-12-31                        255\n",
       "                                                   2010-12-31                        296\n",
       "                                                   2011-12-31                        521\n",
       "                                                   2012-12-31                        820\n",
       "                                                   2013-12-31                       1363\n",
       "                                                   2014-12-31                       1276\n",
       "                                                   2015-12-31                       1218\n",
       "                                                   2016-12-31                       1162\n",
       "                                                   2017-12-31                        510\n",
       "Sales Workers                                      2008-12-31                       1477\n",
       "                                                   2009-12-31                       1702\n",
       "                                                   2010-12-31                       1565\n",
       "                                                   2011-12-31                       1454\n",
       "                                                   2012-12-31                       1696\n",
       "                                                   2013-12-31                       1687\n",
       "                                                   2014-12-31                       1869\n",
       "                                                   2015-12-31                       2367\n",
       "                                                   2016-12-31                       2841\n",
       "                                                   2017-12-31                        981\n",
       "                                                   2006-12-31                       6042\n",
       "                                                   2007-12-31                      14033\n",
       "                                                   2008-12-31                       2280\n",
       "                                                   2009-12-31                          8\n",
       "                                                   2014-12-31                          1\n",
       "Technicians and Associate Professionals            2006-12-31                       4668\n",
       "                                                   2007-12-31                       9588\n",
       "                                                   2008-12-31                       1591\n",
       "                                                   2009-12-31                        325\n",
       "                                                   2010-12-31                         59\n",
       "Technicians and Trades Workers                     2007-12-31                          1\n",
       "                                                   2008-12-31                      11098\n",
       "                                                   2009-12-31                      11804\n",
       "                                                   2010-12-31                      10792\n",
       "                                                   2011-12-31                       9238\n",
       "                                                   2012-12-31                       9734\n",
       "                                                   2013-12-31                      11721\n",
       "                                                   2014-12-31                      13485\n",
       "                                                   2015-12-31                      14975\n",
       "                                                   2016-12-31                      17041\n",
       "                                                   2017-12-31                       5886\n",
       "                                                   2006-12-31                       2613\n",
       "                                                   2007-12-31                       5434\n",
       "                                                   2008-12-31                        839\n",
       "                                                   2009-12-31                          3\n",
       "\n",
       "[140 rows x 1 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df.groupby(['Standard Major Group', pd.Grouper(freq='A')]).sum()\n",
    "df1.rename(index={'Service and Sales Workers':'Sales Workers'}, inplace=True)\n",
    "df1.rename(index={'Trades Workers':'Technicians and Trades Workers'}, inplace=True)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IyCAzM/P4hoXQWbduXSm0qGy1/dYvjvbpp59OfHz8ce12795d3GYVCj/1g6rtt35Qtf3W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\nrLen/rZut71q7zlRrSvOovL9Lga+6GpN8kbgTteIsoWAR54rLzIGpz9to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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1084cdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "def stackedWorkVisasDatePlot(title, dataset, filename, left_adjust=0, bottom_adjust=0.4):\n",
    "    dateranges=((2006,2007),(2008,2010),(2011,2013),(2014,2017))\n",
    "    xlabels, vals = (dateGroupData(dataset, dateranges, ['(not recorded)']))\n",
    "    colors = [(1,1,0), (0,0,1)]\n",
    "    N = len(xlabels)\n",
    "    ps = stackedTimeBars(plt, vals, colors, width=0.3)\n",
    "    plt.ylabel('Applications Granted')\n",
    "    plt.title(title)\n",
    "    plt.xticks(np.arange(1, N+1), xlabels)\n",
    "    #plt.yticks(np.arange(0, 81, 10))\n",
    "    legend_strs = []\n",
    "    for ds,de in dateranges:\n",
    "        legend_strs.append(\"{}-{}\".format(ds,de))\n",
    "    plt.legend(ps, legend_strs,loc='upper left', prop={'size': 8})\n",
    "    fig = plt.gcf()\n",
    "    ax=plt.gca()\n",
    "    fig.autofmt_xdate()\n",
    "    plt.grid()\n",
    "    for tick in ax.xaxis.get_major_ticks():\n",
    "        tick.label.set_fontsize(8)\n",
    "    fig.subplots_adjust(left=0.20, bottom=0.40)\n",
    "    fig.savefig(filename, transparent=False, bbox_inches='tight')\n",
    "\n",
    "stackedWorkVisasDatePlot('Work Visas Granted', df1, 'work-visas-granted.png', left_adjust=0.2, bottom_adjust=0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WUL16dfbv30+LFi1o2bIl7dq1Y8uWLQwfPpz169dTrVo1unXrxnPPPcegQYM4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\nVuNnRhtdTYFSpQrvZVEklbgsVzYQGBv7OyPJ0t1o0t+k6D5c1me2jj7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aHhkRPhP38fz9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\nZ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dpz6vYG9MSJwePU82cHcRxOc30T2D7XnZ0fhQ2xC/w+HCqJIR1vGLR3YswZuqxl+eaY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\nzB4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f54518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1=df[df['Standard Major Group']=='Professionals'].groupby(['Standard Submajor Group', pd.Grouper(freq='A')]).sum()\n",
    "stackedWorkVisasDatePlot('Professional-Work Visas Granted', df1, 'prof-work-visas-granted.png', left_adjust=0, bottom_adjust=0.4)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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hnFVM38imqOlrZMWMUcPISjOgIrBeRH4Xkd+Ba4GhIvIbbmZScLOfwVQCdnn/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Z/vCK/vYCKEfQtwoe01y2kXrX8Xvw5JKymqoAsjdLEUhl2V+L5eJ2kxQuVhEJH/207S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\nw6gkSZJmxjAqSZKkmfkf0LQKNSEF/ZUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d9e2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1=df[df['Standard Major Group']=='Technicians and Trades Workers'].groupby(['Standard Submajor Group', pd.Grouper(freq='A')]).sum()\n",
    "stackedWorkVisasDatePlot('Trade & Technicians Work Visas Granted', df1, 'trade-work-visas-granted.png', left_adjust=0, bottom_adjust=0.4)\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VcVBE3gwyPbWCuKXl94tbcv8lCVhmXtyWBu+LW5Z/p4iMDzJubxglHhGpihtqeDXSthiG\nUXKwB1oJQEQuwHUrH8F1G9fDJbHu89MZhhsC+SvQFNeFnCjZ93R6BvdF3w2XaHoROcfVX/fqv87T\nbQ284NfOWbjE2rOBZrhhit6EkKdgGJFCRGqI2xhzLm5IYnqETTIMowRhw14lABEZCzRX1TZ56OwA\nnlTVp7335XGb/vVS1Te893uA7qr6lqdTB7cWRjNVXSNuv5xvgcZ6clPD63GzhC5W1Z3eTIN3gKrq\nVtlFRAbglvSvrAVYXdYwIo24/cdm4nKi/p71P2EYhgHW81NSSAC+FJE3xO04nCwi/bMKxe0ofSFu\n5gbgW613NW66LbgZKWcH6GzCJe9l6TQD9mUFPh6f4KadXuOn83VW4OORiJvZUr+oF2oYxYGqzlLV\ns1T1Ugt8DMMIxIKfksGluPUxNuHWFJkKPCsid3vlF+IClF0B5+3yysBtmndUsy/EFqhzIW62hQ91\nU3/3BugEawc/HcMwDMM4bbF1fkoGZwFrVPUR7/16bxn5gRRsE8aIIm7TvutxQwyHI2uNYRiGEcXE\n4laST9Q8VjO34Kdk8DM596lJAW7xXu/ELe5Whey9MlVwC21l6ZQKsp1AFa8sSydw9lcMUDFA548B\ntlTxKwvG9RRg5VjDMAzDKCb+gpvgExQLfkoGK8m5l0sdvL1fVHWLiOzEzdD6L/gSnq8BJnv6SbgF\n164D/BOe4zm579AXwAUi0tAv7+c6XGC12k/nf0Wkkl/eTyfconsbcrE/FWD27NnUq1evUBduhM4D\nDzzA008/HWkzogrzeWQwvxc/p6vPU1JS6NGjB3jPpdyw4Kdk8DRuefN/4lYyvQa38ug9fjrPAA+L\nyA+cXNV3O95y9ap6QERm4DYh3IfbzflZYKWqrvF0NopIIm6vnEG4LRSeA+aqalavzke4IOc1b3p9\nVa+t5zX3zRgPA9SrV49GjRrlomKEm/PPP9/8XcyYzyOD+b34OQN8nmcKhgU/JQBV/VJEbsZNJ38E\ntxXAEFWd56czXkTK4tbkuQC31PqNqnrUr6oHcEusv4nbF2YxOXexvgu3T9EnuH1p3gSG+LVzQkRu\nwiVdf45bT+gVYGS4rtcwDMMwIokFPyUEVf0At7hgXjqjgFF5lB/BbZ44OA+dX4Ee+bSzDbgpL52C\nkJaWRnp6ev6KRkikpaWRnJxcqHMqVapEfHz8KbLozGfv3r2RNiEqMb8XP2e6zy34MU4JaWlp1KtX\nj8zMzEibckbTuHHjQumXLVuWlJQUC4BC5Icffoi0CVGJ+b34OdN9bsGPcUpIT08nMzPTkqBLEFmJ\ngOnp6Rb8hMjYsWMjbUJUYn4vfs50n1vwY5xSLAnaOJPo3bt3pE2ISszvxc+Z7nNb4dkwDMMwjKjC\nen6MYuVUJUFbIq9hGIZRUCz4MYoNlwRdh8zM8O+AUbZsLCkpm/INgI4cOUL37t1JSUmhTJkyxMXF\nMWXKFGrVqsWePXvo2bMnmzdvJjY2lsmTJ9OqVSsADh06RL9+/Vi7di0xMTE8/vjjdOvWzVfvwoUL\nGT16NKqKiPDee+8FtWX+/PmMHTuW48ePA65r+cEHH/SVz5gxg3HjxqGqtG/fnilTphATEwPAe++9\nx0MPPcSJEye48soreeWVVyhXrhzffPMNd999NyICwL59+zh48KDNtDsFPPTQQzz55JORNiPqML8X\nP2e6zy34MYoNlwR9mNmzIZw50Ckp0KPH4QIn8g4YMIAbbrgBgMmTJ9O/f3+WLl3KsGHDaN68OR9+\n+CFffvklN998M6mpqcTExDBhwgRiY2P5/vvvSU1N5ZprrqF9+/ZUqFCBdevW8cgjj7B06VKqVKlC\nRkaGL2AJJD4+nsTEROLi4jhw4ACNGzemSZMmtG7dmi1btjBixAi++uorKleuTJcuXZg+fTqDBg0i\nIyOD/v37s3z5ci6//HIGDx7Mo48+yvjx47niiitYt26dr43Bgwdz1lk2on0qsN7FyGB+L37OeJ+r\nqh12FOkAGgGalJSkWSQlJWnusvCakJREjrYKypdffqk1a9ZUVdVy5crprl27fGXXXHONLlmyRFVV\n69evr6tXr/aV3X777TpjxgxVVe3Ro4e++OKLhW5bVfWmm27SWbNmqarqk08+qYMGDfKVffDBB9qq\nVStVVV2wYIHeeOONvrINGzboxRdfnKO+w4cPa4UKFXT9+vU5yoJ9JoZhGGcSWd9zQCPN48FhPw+N\nqGbSpEl07dqVvXv3cuzYMeLiTu77Wr16ddLS0gA3ZFe9enVfWY0aNXxlGzZsYOvWrbRt25bGjRsz\nYsSIrKAwTzZs2MCqVavo2LFjvm0EK9u5cycnTpzIVufChQupVasWV111VWFdYRiGETVY8GNELWPG\njGHz5s2MGTOmSPUcO3aMr776io8++ojly5fz+eefM3Xq1DzP2b59O127duWFF16gatWqRWrfn5df\nfpl+/fqFrT7DMIwzEQt+jKhkwoQJLFq0iMWLFxMbG0vFihU5++yz2b17t08nNTXVN+5dvXp1tm7d\nGrQsPj6ebt26UapUKcqWLcstt9zCqlWrAGjZsiUNGzakefPmvnN37NhBx44dGTFiBLfccotPHh8f\nn2cbqampvrItW7ZQtWrVbLk9qamprF69mrvuuiscLjKCsHHjxkibEJWY34ufM93nlvBsRB0TJ05k\n3rx5LFmyhPPOO88nv+2225g6dSojR45k7dq17NixgzZt2gBw6623Mm3aNJo2bcqWLVtYtmyZr3fn\nrrvu4t1336VXr14cP36cjz76yDdLbOXKldna/vnnn+nQoQPDhw+nR4/sW6x169aNVq1aMWrUKCpX\nrsy0adPo3r07ADfccAP33Xcf3333HbVr12bq1Km+sixmzJjBzTffTPny5cPrMMPHP/7xD955551I\nmxF1mN+Ln8GDBzNu3Lhia6+4lyux4McodlJSIlffTz/9xNChQ6lVqxbt2rVDVYmNjeWLL75g7Nix\n3H333dSuXZvSpUszZ84c36ythx56iL59+3LZZZdx9tlnM3nyZCpWrAhA9+7dSU5Opn79+px99tm0\natWKIUOGBG1/5MiRbNu2jUmTJvHMM88gIgwZMoRevXpRs2ZNRo8eTYsWLRAR2rVrx4ABAwAoV64c\nL730El26dOH48eNcccUVzJo1y1evqvLqq6/y2muvhehFoyA8//zzkTYhKjG/Fy9paWksX76i0HsH\nFoXY2LJs2lR8+w5KQRIzDSMvRKQRkJSUlOTbyiI5OZnGjRvjLysJ6/xEM8E+E8MwjECyvitgNlAc\nezOmAD3C8t100nYaq2pybnrW82MUG/Hx8aSkbLIVng3DME4L6uFWMjnzsODHKFbi4+MtSDEMwzAi\nis32MgzDKCDFmQBqnMT8boQbC34MwzAKSGZmZqRNiErM70a4seDHMAyjgIwePTrSJkQl5ncj3FjO\nj1GspKWlWcKzYRiGEVEs+DGKjbS0NOrWrcuhQ4fCXneZMmXYuHGjBUCGYRhGvljwYxQb6enpHDp0\niMGDm1KtWvhWIf7ppwM899wa0tPT8w1+jhw5Qvfu3UlJSaFMmTLExcUxZcoUatWqxZ49e+jZsyeb\nN28mNjaWyZMn+1ZqPnToEP369WPt2rXExMTw+OOP061bN9919e3bl61bt3Ls2DGaNm3KtGnTKF26\ndI7258+fz9ixYzl+/DgAvXv35sEHH/SVz5gxg3HjxqGqtG/fnilTphATE0NGRgbdunUjKSmJ48eP\ns3fv3mz1rl69mgEDBnD48GEuvvhiXnvttbDuGWY40tPTqVSpUqTNiDrM70a4sZyfEoCIjBSREwHH\nhgCdR0Vkh4hkisjHInJZQHlpEZksIukiclBE3hSRuACdCiIyR0T2i8g+EXlJRM4N0LlERN4XkQwR\n2Ski40UkrPdJtWrlufTSCmE7ChtIDRgwgI0bN7Ju3To6d+5M//79ARg2bBjNmzfnu+++4+WXX+au\nu+7yBSkTJkwgNjaW77//nsWLF3Pvvfeyb98+AB5//HFq167N+vXr+eabb9i5cyczZ84M2nZ8fDyJ\niYn897//ZcWKFUydOpX//Oc/gNuva8SIEaxcuZLvv/+enTt3Mn36dADOOecchg8fzpIlS3LUqar0\n6NGDZ599lo0bN3LjjTfmusK0UTT69u0baROiEvO7EW4s+Ck5fANUAS70jmuzCkRkGHAf8FegKZAB\nJIpIKb/znwH+DHQDWgMXAQsD2ngdt2rVdZ5ua+AFv3bOAj7A9Qg2A3oBvYFHw3OJkad06dLccMMN\nvvfNmjXzbSa6YMECBg4cCECTJk2oVq0ay5YtA1yPTVZZjRo1aNu2LW+99RYAIsLBgwdRVQ4fPkxm\nZiYXX3xx0PabN29OXJyLScuXL0/dunV9G5YuXLiQLl26ULlyZQAGDhzI3LlzAShVqhRt27bl/PPP\nz1FnUlIS55xzDq1btwZccPfuu+9y9OjR0B1lBGXUqFGRNiEqMb8b4caGvQqIiKwDCrQXiKqGsiTm\nMVXdk0vZEOAxVX3Ps6UnsAvoCrwhIuWBvkB3VV3m6fQBUkSkqaquEZF6wPW4Jb/XeTqDgfdFZKiq\n7vTK6wLtVDUd+FpEHgHGisgoVT0WwnWVaCZNmkTXrl3Zu3cvx44d8wUm4HZyT0tLA1y+UvXq1X1l\nNWrU8JU98sgjdOvWjQsvvJDDhw9z1113cdNNN+Xb9oYNG1i1apWvdyevNvIi8Lxy5cpx/vnns2PH\nDmrUqJHv+UbBsW1BIoP53Qg31vNTcBYBb3tHIlALOAJ85h2HPVliiPVfLiI/ichmEZktIpcAiEhN\nXE+Qb7xDVQ8Aq4HmnqgJLpD119kEpPnpNAP2ZQU+Hp/gArpr/HS+9gKfLBKB84H6IV5XiWXMmDFs\n3ryZMWPGFKmeuXPnUr9+fXbt2sWOHTvYtGkTL7/8cp7nbN++na5du/LCCy+cktwc27PPMAwjdyz4\nKSCqOjrrACoDz6pqc1V90Dta4IaeqoRQ/Src8NL1wECgJvAfLx/nQlyAsivgnF1eGV6bR72gKDed\nC4HdAdd0HNgboBOsHfx0zggmTJjAokWLWLx4MbGxsVSsWJGzzz6b3btPuig1NdWXQF29enXf8Fhg\n2dSpU/nLX/4CwLnnnsutt97K0qVLAWjZsiUNGzakefPmvnN37NhBx44dGTFiBLfccotPHh8fn2sb\neREfH+8bOgP47bffOHDgABdddFFhXGIYhhE12LBXaNyG620JZDbwJW4IqsCoqn9v0TcisgbYCtwO\nbAzVyJLKTz8FxmjFW9/EiROZN28eS5Ys4bzzzvPJb7vtNqZOncrIkSNZu3YtO3bsoE2bNgDceuut\nTJs2jaZNm7JlyxaWLVvGtGnTAKhVqxaLFy+mWbNm/P777yQmJtKiRQsAVq5cma3tn3/+mQ4dOjB8\n+HB69OiRraxbt260atWKUaNGUblyZaZNm0b37t2z6ahqjl6dxo0bc+zYMZYtW0abNm2YNm0aCQkJ\nlCpVCiO8zJgxg379+kXajKjD/G6EnawvUzsKfgA7gd5B5L2BXWFqYw3wOK4X6ARwVUD5Z8DT3ut2\nwHGgfIBOKjDEe90H+CWgPAb4HejivR8NJAfo1PDab5CHrY0ArVKliiYkJGhCQoK2atVKAU1KStIs\ntm7dqmXKlFFcT1ZYjzJlyujWrVs1P7Zv364iopdddpk2bNhQr776am3WrJmqqu7atUs7deqkl19+\nuV5xxRW6bNky33kZGRl6xx13aK1atbROnTr65ptv+sq2bNmi119/vV511VVav3597d+/vx45ciRo\n+/fcc4+WK1fO13bDhg31lVde8ZW/9NJLWqtWLb3sssv0nnvu0WPHjvnKrrrqKr3ooos0JiZGL7nk\nEu3Zs6evbNWqVXrVVVdpnTp1tF27drp9+/YcbSclJSmgEyZMyCZPTEzUhISEHPr33nuvvvTSSznq\nSEhI0D179mSTjxgxQseOHZtNtnXrVk1ISNCUlJRs8meffVaHDh2aTZaRkaEJCQm6fPnybPLXX39d\ne/funcO222+/Xd96661iv4577733jLgOf06H6/D3++l8Hf6U5OuYPXu29936iYL6HSMUxgbItiok\nKKQEyJ8NEk4hAAAgAElEQVRVGBogy/B0lwfIH8/xvCjIdbz++uu+Z06NGjW0QYMG2rp166znQiPN\n4xkrqpYbUFhEZDgwEngRF6SAy5vpi0tMHlvE+svh8nUeUdXJIrIDeFJVn/bKy+OGo3qq6gLv/R5c\nwvNbnk4dIAVopi7huS7wLdBETyY8d8LN7rpYVXeKyA3Au0BV9fJ+ROSvwDggTlV/z8XeRkBSUlKS\nLzExOTmZxo0b4y8DW+E5kuT2mRiGYfiT9V0BSbjftqe8RSA8300nbaexqibnpmfDXiGgqmNF5Efc\nLKyssYsUoI+qvlHY+kTkSVzQsRWohuuB+R2Y56k8AzwsIj/genMeA7bjkq9R1QMiMgOYKCL7gIPA\ns8BKVV3j6WwUkUTgRREZBJQCngPmqpvpBfARsAF4zZteX9Vr6/ncAp/CEh8fb0GKYRiGEVEs+AkR\nL8gpdKCTCxfj1uD5A64HZwWux+YXr63xIlIWtybPBcBy4EZV9V/I5QHc0NebQGlgMfC3gHbuAp7H\nzfI64en6VsNT1RMichMwFfgct57QK7heLsMwDMM4I7DgJ0RE5ALgVuBSYIKq7vWGf3ap6k+FqUtV\n7yyAzihgVB7lR4DB3pGbzq+c7KnKTWcbkP8iNYZhGIZxmmJT3UNARK4CvgOGAQ/hemMAbgGeiJRd\nhmGcWjp37hxpE6IS87sRbiz4CY2JwCuqejluccMsPsBtGWEYxhnIfffdF2kTohLzuxFubNgrNP4I\nDAgi/4kzbDHAcGOzvYzTmU6dOkXahKjE/G6EGwt+QuMIEGwr8dq4hGUjCGlpadStW5dDhw6Fve4y\nZcqwcePGfAOgI0eO0L17d1JSUihTpgxxcXFMmTKFWrVqsWfPHnr27MnmzZuJjY1l8uTJtGrVCoCZ\nM2fy9NNPk5KSwlNPPcX999/vq/ODDz5gxIgRfPPNN9x7771MnDgx1/bnz5/P2LFjfbvF9+7dmwcf\nfNBXPmPGDMaNG4eq0r59e6ZMmUJMTAwZGRl069aNpKQkjh8/zt69e33nZGZm0r59e44cOYKqctFF\nFzFt2jQLBg3DMHLBgp/QeAcYISK3e+9VROJx6+EE7qRueKSnp3Po0CGaNh1M+fLVwlbvgQM/sWbN\nc6SnpxfogT9gwADfzu6TJ0+mf//+LF26lGHDhtG8eXM+/PBDvvzyS26++WZSU1OJiYmhSZMmLFiw\ngCeeyJnSVbt2bWbOnMmCBQv47bff8mw7Pj6exMRE4uLiOHDgAI0bN6ZJkya0bt2aLVu2MGLECL76\n6isqV65Mly5dmD59OoMGDeKcc85h+PDhVKxYkbZt22ars0yZMixZsoRzzz0XgGeeeYb777+fRYsW\nFdCDhmEY0YXl/ITG34FyuL2yygDLgB9w6+v8XwTtOi0oX74aFSpcGrajMIFU6dKlfYEPQLNmzXz7\naS1YsICBAwcC0KRJE6pVq8ayZcsAuPLKK6lTpw4ikqPOyy67jCuvvJKYmJh822/evLlv5/jy5ctT\nt25d375cCxcupEuXLlSuXBmAgQMHMnfuXABKlSpF27ZtOf/883PUKSK+wEdVOXDgAGedZf/apwIL\nKCOD+d0IN/YNGQKqul9VO+KmhN+PWzvnT6raRlUzImudURgmTZpE165d2bt3L8eOHfMFJuA2M01L\nSztlbW/YsIFVq1bRsWNHwA0LVq9e3Vdeo0aNQrXfsWNHqlatyptvvsnkyZPDbq+BLxg1ihfzuxFu\nLPgJARHpKSKlVXWlqk5R1fGq+omIlBKRnpG2zygYY8aMYfPmzYwZM6bY296+fTtdu3blhRdeoGrV\nqmGp8+OPP2bnzp3ccccd/Otf/wpLnUZ25s+fH2kTohLzuxFuLPgJjZlAzvEHOM8rM0o4EyZMYNGi\nRSxevJjY2FgqVqzI2Wefze7du306qampRU4abtmyJQ0bNqR58+Y+2Y4dO+jYsSMjRozglltu8cnj\n4+N9Q3BFab9///689tprRbLbMAzjTMaCn9AQ3K6xgVwM7C9mW4xCMnHiRObNm8fHH3/Meeed55Pf\ndtttTJ06FYC1a9eyY8cO2rRpk+P8vDYDDixbuXIl69at44svvgDg559/pkOHDgwfPpwePbIvtt2t\nWzfeeecddu/ejaoybdo0unfvnqP+wDZ27drFr7/+6ns/b948GjRokJcLDMMwohqb7VUIRGQdLuhR\nYImIHPMrjgFq4vbUMvLgwIFC7f4R1vp++uknhg4dSq1atWjXrh2qSmxsLF988QVjx47l7rvvpnbt\n2pQuXZo5c+b4kphnzZrFww8/zK+//srbb7/NU089xbvvvkuDBg349NNP6dWrFwcPHkRVWbhwIVOm\nTOGmm3LuEjJy5Ei2bdvGpEmTeOaZZxARhgwZQq9evahZsyajR4+mRYsWiAjt2rVjwICTy0k1aNCA\n9PR0Dh48SHx8PO3atWPWrFmkpaUxYMAATpw4gapSq1YtZs+eXXTHGoZhnKFY8FM4sqYcXA0kAv7z\nmo/idly3qe65UKlSJcqUKcOaNc+Fve4yZcpQqVKlfPWqVavGiRMngpbFxcWRmJgYtKxXr1706tUr\naFn79u3Ztm1bgeycPn0606dPz7W8X79+9OvXL2jZ+vXrg8r/+Mc/kpycXKD2jaLRp08fZs60ke3i\nxvxuhBsLfgqBqo4GEJFUYL6qHs77DMOf+Ph4Nm7caCs8G6ctttJwZDC/G+HGgp8QUNVZACJSCogj\nIHdKVU/d/OjTnPj4eAtSjNOWO++8M9ImRCXmdyPcWPATAiJyOfAy0CKwCJcPlP9qd4ZhGIZhRAQL\nfkLjFeAYbpHDnwk+88swDMMwjBKITXUPjauBAar6oap+parr/Y9IG2cYxqlhxYoVkTYhKjG/G+HG\ngp/Q2ADkP7XIMIwzivHjx0fahKjE/G6EGxv2Co1hwHgR+V/ga+B3/0JVPRARq04D0tLSbLaXcdoy\nb968SJsQlZjfjXBjwU9ofOL9XRIgt4TnPEhLS6NOnXocPpwZ9rpjY8uyaVNKvgHQkSNH6N69Oykp\nKZQpU4a4uDimTJlCrVq12LNnDz179mTz5s3ExsYyefJkWrVqBcDMmTN5+umnSUlJ4amnnuL+++/P\nUffu3bu56qqraNGiBf/+97+Dtj9//nzGjh3L8ePHAejduzcPPvigr3zGjBmMGzcOVaV9+/ZMmTKF\nmJgYMjIy6NatG0lJSRw/fpy9e/f6zvnmm2+4++67fTvO79u3j4MHD56SIDPaKVu2bKRNiErM70a4\nseAnNNpF2oDTkfT0dC/wmQ3UC2PNKRw+3IP09PQC9f4MGDCAG264AYDJkyfTv39/li5dyrBhw2je\nvDkffvghX375JTfffDOpqanExMTQpEkTFixYwBNPPJFrvQMHDiQhIYFffvklV534+HgSExOJi4vj\nwIEDNG7cmCZNmtC6dWu2bNnCiBEj+Oqrr6hcuTJdunRh+vTpDBo0iHPOOYfhw4dTsWJF2rZtm63O\nK664gnXr1vneDx48mLPOshFtwzCM3LDgJwRUdVmkbTi9qQc0ikjLpUuX9gU+AM2aNeOpp54CYMGC\nBWzevBmAJk2aUK1aNZYtW0b79u258sorAXy9K4G8/PLLXHrppVx55ZW8/fbbubbvv8Fp+fLlqVu3\nLqmpqbRu3ZqFCxfSpUsXKleuDLhg6oknnmDQoEGUKlWKtm3bZtv4NBhHjhxhzpw5fPbZZ/k7wzAM\nI0qxn4dFQETKikhdEbnK/4i0XUbBmTRpEl27dmXv3r0cO3aMuLg4X1n16tVJS8t/vcotW7bwwgsv\n8Pjjjxeq7Q0bNrBq1So6duwIuGHB6tWr+8pr1KhRoPb9WbhwIbVq1eKqq+w2PBU89NBDkTYhKjG/\nG+HGgp8QEJHKIvIecBD4FlgXcBS1/uEickJEJgbIHxWRHSKSKSIfi8hlAeWlRWSyiKSLyEEReVNE\n4gJ0KojIHBHZLyL7ROQlETk3QOcSEXlfRDJEZKeIjBeRM+5eGTNmDJs3b2bMmDFFqqdfv348//zz\nlC5dOs8d3/3Zvn07Xbt25YUXXqBq1apFat+fl19+Ode9wYyiY0n1kcH8boQbG/YKjWeAC4BrgM+A\nm4EqwMPA34tSsYj8EfgrsD5APgy4D+iJ20D1X0CiiNRT1aN+dt0IdAMOAJNxG6228qvqdc/W64BS\nuAUbXwB6eO2cBXwA7ACaARcBr+E2bn24KNdWkpgwYQKLFi1iyZIlxMbGEhsby9lnn83u3bt9vT+p\nqan5fukeOHCAr7/+mjvuuAOAgwcPcujQITp27MjHH39My5YtyczM9O0cD7Bjxw46duzIiBEjuOWW\nW3x1xcfH8+OPP/reF6R9f1JTU1m9enWuydZG0Rk8eHCkTYhKzO9GuLHgJzTaA11U9UsROQFsVdWP\nReQA8E/g/VAqFZFyuGzg/sAjAcVDgMdU9T1PtyewC+gKvCEi5YG+QPesnCQR6QOkiEhTVV0jIvWA\n64HGqrrO0xkMvC8iQ1V1p1deF2inqunA1yLyCDBWREap6rFQri07KUWvogj1TZw4kXnz5rFkyRLO\nO+88n/y2225j6tSpjBw5krVr17Jjxw7atGmT43z/3p3y5cuzZ88e3/tZs2bx9ttv+wKQlStXZjv3\n559/pkOHDgwfPpwePXpkK+vWrRutWrVi1KhRVK5cmWnTptG9e/ccbefWuzRjxgxuvvlmypcvX0BP\nGIZhRCdn3FBGMXEusNt7vQ+o7L3+mqJl8k4G3lXVT/2FIlITuBC/qfXeWkKrgawM2ia4YNZfZxOQ\n5qfTDNiXFfh4fIKbnn+Nn87XXuCTRSJwPlC/CNdGpUqViI0ti+tkahzGowexsWWpVCn/dSd/+ukn\nhg4dyv79+2nXrh0NGzb0JSGPHTuWzz//nNq1a9O3b1/mzJlDTIxbtWDWrFlccsklvPnmm4wePZr4\n+HjWry/8Yt4jR45k27ZtTJo0iYYNG9KoUSNmzZoFQM2aNRk9ejQtWrSgdu3aVKlShQEDBvjObdCg\nAS1btuTgwYPEx8fTq1cvX5mq8uqrr9K/f/9C22QYhhFtWM9PaGwC6uCGn9YDA0QkFRiI2+ur0IhI\nd9y2GU2CFF+IC1B2Bch3eWXghrKOBllg0V/nQk4GbQCo6nER2RugE6ydrLKQt++Ij49n06aUiC5y\nWK1aNU6cOBG0LC4ujsTExKBlvXr1yhZs5EZ+etOnT2f69Om5lvfr1y/XnJ28gi0RyXcmmFF0Nm7c\nSN26dSNtRtRhfjfCTlY3uh0FP3BdF729142BPcBx4BBwRwj1XQzsBK7wky0FJnqvm3v1Vwk4bz4w\n13t9J3AoSN2rgSe81/8EUoLo7MLtVQYu/+fDgPIywAng+lzsbwRolSpVNCEhQRMSErRVq1YKaFJS\nkholg6SkJAV0woQJ2eSJiYmakJCQQ//ee+/Vl156KUcdCQkJumfPnmzyESNG6NixY7PJtm7dqgkJ\nCZqSkpJN/uyzz+rQoUOzyTIyMjQhIUGXL1+eTf76669r7969c9h2++2361tvvVXs1+Ff/+l8Hf6c\nDtfhX8/pfB3+lOTrmD17tgIKnyio3zFCYWyAbKtCgkJKgPxZhaEBsgxPd3mA/PGgz4v8ruP111/3\nPXNq1KihDRo00NatW3u200jzeu7mVWhHgYOXsl4AUCnE87t4wc1R3FYZv3vBRpbsUu/9VQHnfQY8\n7b1u5+mXD9BJBYZ4r/sAvwSUx3jtdfHejwaSA3RqeO03yMX+RoE3btaD1oKfkoN9JkVn69atkTYh\nKjG/Fy9Z3xWQFBCknKojfN9NJ23PO/ixnJ9CIiLniMhmL3kYAFXNVNVkzZ4nUxg+Aa7EDXs18I4v\nccnPDVT1R1zP0HV+dpTH5el87omSgGMBOnWAeOALT/QFcIGINPRr+zrcthyr/XSuFBH/BJpOwH7c\nhq6GEbXYlOvIYH43wo3l/BQSVf1dRGLDXGcGAYGFiGTgemmypjI9AzwsIj/genMeA7YDb3t1HBCR\nGcBEEdmHW4PoWWClqq7xdDaKSCLwoogMwk11fw43dLbTa+cjz5bXvOn1Vb22nlfVbBu4GoZhGMbp\niAU/oTEZGCYi/TUsU7+Dkm0+s6qOF5GyuJycC4DlwI16co0fgAdwQ19vAqWBxcDfAuq9C3ge19t0\nwtMd4tfOCRG5CZiK61XKwK0FNDKUi0hJCfe0diNU7LMwDMNwWPATGn/EDRd1EpGvcQGCD1W9JehZ\nhUBV2weRjQJG5XHOEWCwd+Sm8yvegoZ56GwDbiqgqUGpVKkSZcuWzbGWjRFZypYt2JIARnDGjRvH\nsGHDIm1G1GF+N8KNBT+h8Stu5WQjF+Lj40lJOTXT2g3HtGnTGDhwYKHOKeiSAEZwMjMzI21CVGJ+\nN8KNBT8hoKp9Im3D6UB8fLw9aE8hea0XZJwaRo8eHWkTohLzuxFubLaXYRiGYRhRhQU/hUBEaonI\ny37v00Rkr9+xx5tebhiGYRhGCcWCn8IxmOxbP1QAnsDNsnoAWOv9NYxTjuVTFT/m88hgfjfCjQU/\nheM64K0A2UJVnaWqs4Bx+C0yaBinkr59+0bahKjDfB4ZzO9GuLHgp3DUAHb4vX8Jt/JxFqm4fboM\n45QzatSoSJsQdZjPI4P53Qg3FvwUjhPARVlvVPUBVf3Fr7wKbp8swzjlNGrUKNImRB3m88hgfjfC\njQU/heNboEMe5dcD3xSTLYZhGIZhhIAFP4VjJvB/IvLnwAIRSQCGezqGYRiGYZRQLPgpBKr6IvAO\n8K6IbBCRt7xjA7AIeN/TMYxTzowZMyJtQtRhPo8M5ncj3FjwU0hU9U7c5qDfAXW843vgL6p6eyRt\nM6KL5OTkSJsQdZjPI4P53Qg3tr1FCKjqPGBepO0wopvJkydH2oSow3weGczvRrixnh/DMAzDMKIK\nC34MwzAMw4gqLPgxDMMwDCOqsODHME5TOnfuHGkTog7zeWQwvxvhxoKfMCAi5UWkq4jUi7QtRvRw\n3333RdqEqMN8HhnM70a4seAnBETkDRG5z3tdBvgSeAP4r4h0i6hxRtTQqVOnSJsQdZjPI4P53Qg3\nFvyERmtguff6ZkCAC4D7gYcjZZRhGIZhGPljwU9onA/s9V7fACxU1UzgfeDyiFllGIZhGEa+WPAT\nGtuA5iJyLi74+ciTVwAOR8wqI6pYtGhRpE2IOsznkcH8boQbC35C4xlgDrAd2AF85slbA18XtjIR\nGSgi60Vkv3d8LiI3BOg8KiI7RCRTRD4WkcsCykuLyGQRSReRgyLypojEBehUEJE5Xhv7ROQlL4Dz\n17lERN4XkQwR2Ski40XE7pMSyNy5cyNtQtRhPo8M5ncj3NhDLQRUdQrQHOgLXKuqJ7yiHwkt52cb\nMAxoBDQGPgXezpo9JiLDgPuAvwJNgQwgUURK+dXxDPBnoBsuCLsIWBjQzutAPeA6T7c18EJWoRfk\nfIDb9qQZ0AvoDTwawjUZp5j58+dH2oSow3weGczvRrixvb1CRFW/xM3y8pe9H2Jdgec9LCKDcAFI\nCjAEeExV3wMQkZ7ALqAr8IaIlMcFYt1VdZmn0wdIEZGmqrrGC6SuBxqr6jpPZzDwvogMVdWdXnld\noJ2qpgNfi8gjwFgRGaWqx0K5PsMwDMMoSVjwEwIiEoPrEbkOiCOgB01V2xeh7rOA24GywOciUhO4\nEFjiV/8BEVmN6316A2iC+yz9dTaJSJqnswYXSO3LCnw8PgEUuAZ429P52gt8skgEpgL1gfWhXpdh\nGIZxupFyhrVzEgt+QmMSLvh5H/gGF0AUCRG5AvgCiAUOAjd7AUxzr/5dAafswgVFAFWAo6p6IA+d\nC4Hd/oWqelxE9gboBGsnq8yCH8MwjDOcI0eO4H7T9yjGVs/y2i0eLPgJje7A7ar6QRjr3Ag0wE2j\nvxV4VURah7F+4wyjT58+zJw5M9JmRBXm88hgfi9eSpcuDZygfv07OPfcuHz1i0pGxm6+/Xa+127x\nYAnPoXEU+CGcFarqMVX9UVXXqer/4XpZhgA7cYsoVgk4pYpXhve3lJf7k5dO4OyvGKBigE6wdvDT\nyZU//elPdO7cOdvRvHnzHNNUP/roo6B79fztb39jxowZ2WTJycl07tyZ9PT0bPKRI0cybty4bLK0\ntDQ6d+7Mxo0bs8mfe+45HnrooWyyzMxMOnfuzIoVK7LJ586dS58+fXLYdscdd5S46+jUqdMZcR1w\n+nwe/isNn87X4c/pcB3+fj+dr8OfknwdKSluGOoPf6hN9eqtfMdvv/3MoUO/ZJNVrlyPbds+p0KF\nS7PJjx79jV9/Tc0mq1atKdu2fc6551bOJheRHHYV5Drmzp3re9bUrFmTq6++mgceeCBoXYGIapFH\nbKIOEfk7cClwn54iB4rIEmCrqvYVkR3Ak6r6tFdWHjcc1VNVF3jv9+ASnt/ydOrgBlKbeQnPdYFv\ngSZ+Cc+dcLO7LlbVnd70+neBqll5PyLyV2AcEKeqv+diayMgKSkpiUaNGp0KdxiGYRjFRHJyMo0b\nN6ZDh7FUqHDpKW9v374f+eST4YTjGZJlO25yT3JuejbsFRrXAu2AG0XkWyBbUKCqtxSmMhEZA3wI\npAHnAX8B2gBZP3eewc0A+wFIBR7DrTH0ttfeARGZAUwUkX24nKFngZWqusbT2SgiicCL3kyyUsBz\nwFxvphe4xRo3AK950+urem09n1vgYxiGYRinGxb8hMavwFthrC8OmIULNvYD/wU6qeqnAKo6XkTK\n4tbkuQC3r9iNqnrUr44HgOPAm0BpYDHwt4B27gKex83yOuHpDskqVNUTInITbnbX57j1hF4BRobx\nWg3DMAwjoljwEwKqmnOQtWj19S+AzihgVB7lR4DB3pGbzq/kk76vqtuAm/Kzx4g8K1as4Nprr420\nGVGF+TwymN+NcGMJz0VARCqLyLXeUTnS9hjRxfjx4yNtQtRhPo8M5ncj3FjwEwIicq6IvAz8DPzH\nO3aIyAxveMowTjnz5s2LtAlRh/k8MpjfjXBjwU9oTMQlJCfgcnAuALp4sqciaJcRRZQta3F2cWM+\njwzmdyPcWM5PaHQDblXVz/xkH4jIIdx2E4MiYpVhGIZhGPliPT+hUZac20CA2z7CfqIYhmEYRgnG\ngp/Q+AIYLSKxWQIRKYObEv5FxKwyoorAVWCNU4/5PDKY341wY8NeoTEEt9v5dhHJ2uyzAXAYuD5i\nVhlRRXx8fKRNiDrM55HB/G6EGwt+QkBVvxGRy3ErMdf1xHOBOap6KHKWGdHE4MG5LulknCLM55HB\n/G6EGwt+QkRVM4EXI22HYRiGYRiFw4KfAiIinYEPVfV373WuqOo7xWSWYRiGYRiFxIKfgrMIuBA3\no2tRHnoKxBSLRUZUs3HjRurWrZu/ohE2zOeRwfxuhBub7VVAVPUsVd3t9zq3wwIfo1j4xz/+EWkT\nog7zeWQwvxvhxoKfEBCRniJSOoi8lIj0jIRNRvTx/PPPR9qEqMN8HhnM70a4seAnNGYC5weRn+eV\nGcYpx6b/Fj/m88hgfjfCjQU/oSG43J5ALgb2F7MthmEYhmEUAkt4LgQisg4X9CiwRESO+RXHADWB\nxZGwzTAMwzCMgmE9P4VjEfA2rucn0XuddcwDBgA9ImadEVWMGzcu0iZEHebzyGB+N8KN9fwUAlUd\nDSAiqcB8VT0cWYuMaCYzMzPSJkQd5vPIYH43wo0FPyGgqrMibYNhjB49OtImRB3m88hgfjfCjQU/\nISAiMcADwO1APFDKv1xVK0bCLsMwDMMw8sdyfkJjJPAgMB835X0i8G/gBDAqcmYZhmEYhpEfFvyE\nxl+Ae1T1KeAYMFdV+wOPAs0iapkRNaSnp0fahKjDfB4ZzO9GuLHgJzQuBL72Xv/GyQUP3wP+XNjK\nROSfIrJGRA6IyC4ReUtEagfRe1REdohIpoh8LCKXBZSXFpHJIpIuIgdF5E0RiQvQqSAic0Rkv4js\nE5GXROTcAJ1LROR9EckQkZ0iMl5E7F4pYfTt2zfSJkQd5vPIYH43wo090EJjO1DVe70Z6OS9/iNw\nJIT6WgHPAdcAHYBzgI9EpEyWgogMA+4D/go0BTKARBHxzzd6Bhd8dQNaAxcBCwPaeh2oB1zn6bYG\nXvBr5yzgA1w+WDOgF9Ab16tllCBGjRoVaROiDvN5ZDC/G+HGEp5D4y1c8LAaF7TMFpF+uOTnpwtb\nmar+yf+9iPTG7R7fGFjhiYcAj6nqe55OT2AX0BV4Q0TKA32B7qq6zNPpA6SISFNVXSMi9YDrgcaq\nus7TGQy8LyJDVXWnV14XaKeq6cDXIvIIMFZERqmq/8KORgRp1KhRpE2IOsznkcH8boQb6/kJAVUd\nrqpjvNfzcT03U4FbVXV4GJq4ALeK9F4AEamJG2pb4mfDAVzw1dwTNcEFs/46m4A0P51mwL6swMfj\nE6+ta/x0vvYCnywScUN79cNwbYZhGIYRUaznJwyo6ipgVTjqEhHBDV+tUNUNnvhCXICyK0B9l1cG\nUAU46gVFuelciOtR8rf9uIjsDdAJ1k5W2fpCXZBhGIZhlDCs5ycEvATlPkHkfb3cnKIwBfh/QPci\n1mOc4cyYMSPSJkQd5vPIYH43wo0FP6ExANgQRP4tMDDUSkXkeeBPQFtV/dmvaCduP7EqAadU8cqy\ndEp5uT956QTO/ooBKgboBGsHP52g/OlPf6Jz587ZjubNm7No0aJseh999BGdO3fOcf7f/va3HF9y\nycnJdO7cOcdU15EjR+bY7yctLY3OnTuzcePGbPLnnnuOhx56KJssMzOTzp07s2LFimzyuXPn0qdP\njriWO+64o8RdR3Jy8hlxHXD6fB7JyclnxHX4czpch7/fT+fr8KckX0dKSgoAR49mZJN/++0bbNyY\nvd7MzHRWrBjHgQM/ZZN///2HrF//WjbZsWNHWLFiHOnp2a95586vcthVkOuYO3eu71lTs2ZNrr76\najj2ag8AACAASURBVB544IGgdQUiqlogReMkInIYqKeqWwLklwIbVDU2hDqfB7oAbVT1xyDlO4An\nVfVp73153HBUT1Vd4L3fg0t4fsvTqQOkAM28hOe6uACtiV/Ccyfc7K6LVXWniNwAvAtUzcr7EZG/\nAuOAOFX9PYhtjYCkpKQkS0w0DMM4zUlOTqZx48Z06DCWChUuPeXt7dv3I598MpxwPEOybMdN7EnO\nTc9yfkJjG9AS2BIgbwnsKGxlIjIFuBPoDGSISFZPy36/zVOfAR4WkR+AVOAx3JT7t8ElQIvIDGCi\niOwDDgLPAitVdY2ns1FEEoEXRWQQbluO53CLNGb16nyE69V6zRvCq+q19XywwMcwDMMwTjcs+AmN\nF4FnROQc4FNPdh0wHngqhPoG4hKaPwuQ9wFeBVDV8SJSFrcmzwXAcuBGVT3qp/8AcBx4EygNLAb+\nFlDnXcDzuFleJzzdIVmFqnpCRG7CzV77HLee0Cu4LT0MwzAM47THgp/QeBL4Ay45OWuRwcPAOFV9\norCVqWqBcq9UdRR57B2mqkeAwd6Rm86vQI982tkG3FQQmwzDMAzjdMMSnkNAHcOAyrh1cRoAFVXV\nVkE2io1gyYvGqcV8HhnM70a4sZ6fIqCqvwFrI22HEZ3cd999kTYh6jCfRwbzuxFuLPgpICLyb6C3\nl1j877x0VfWWYjLLiGI6deqUv5IRVsznkcH8boQbC34Kzn5cUnLWa8MwDMMwTkMs+Ckgqton2GvD\nMAzj1JKWlpZj4cBTSaVKlYiPjy+29ozix4IfwzhNWbRoEV27do20GVGF+bz4SUtL47LLLuf334/m\nrxwmYmPLsmlTigVAZzD/n73zDrOrqt7w+yVAgNB7F1B6DSDSey9BxZ9Ukar0IiUUERAFgoAUKdKL\ndKRXKYIEpEiooUgRA5EWpGNCyff7Y+2TnLmZJDMhmZuZWe/z3Cdzzz3n3H1P7t1n7VW+lcZPG5H0\nJKPCXmPFdsocJxOdK6+8Mm/EHUxe845n6NChxfD5E7BYB7zjCwwbtj1Dhw5N46cLk8ZP27lx3Lsk\nScdx9dVXN3sI3Y685s1kMSDXlcmEIY2fNmL7mGaPIUmSJEmSb04aP98ASSswyg/7vO0nmjmeJEmS\nJEnGTRo/44GkeYAriUamH5bNM0h6mOiq/mbTBpckSZIkyVhJ42f8OB+YHFjM9ksAkhYBLiqvbdTE\nsSXdhJ122omLLrqo2cPoVuQ1T7oTH388pEu9T500fsaPNYFVKsMHwPZLkvYhuq0nyUQnVW87nrzm\nSXdg+PDhgHjssTM67D2lHuV9O4Y0fsaPNwjPTyM9gf908FiSbso222zT7CF0O/KaJ92BXr16AWar\nrZZgttl6T/T3e/fdz7j66kHlfTuGNH7Gj4OBMyTtZfsfMDL5+TTgoKaOLEmSJEkmAH36zMmCC844\n0d/ntdc+4OqrB03096mTxs/4cTEwNfCopK/KtsmAr4ALJV1Y7Wh7po4fXpIkSZIkYyKNn/Fj/2YP\nIEkGDBjAaqut1uxhdCvymidJ1yCNn/HA9iXNHkOSnHjiiXkj7mDymidJ1yCNn/FEUk/gB9REDoGb\nbH815qOSZMJx1VVXNXsI3Y685knSNUjjZzyQtARwMzAHUJW79wPek7S57eeaNrik2zD11FM3ewjd\njrzmSdI16NHsAXRSzgcGAfPYXq50cZ8XeAY4t6kjS5IkSZJkrKTnZ/xYFljB9gfVBtsfSDoCeLx5\nw0qSJEmSZFyk52f8+CcweyvbZwNe6eCxJN2Ugw8+uNlD6HbkNU+SrkF6fsaPw4DTJR0NPFK2rQT8\nCugnabpqR9sfj+tkklYnhBOXB+YEvm/75oZ9fg3sCswAPATsYfuV2uu9gFOArYBewF3Anrbfre0z\nI/AHYDNgBPBnYD/bn9X2mRc4B1gL+AS4FDjU9ohxfY6kY5lvvvmaPYRuR17zZvJCF3ufpJmk8TN+\n3Fr+vQZw+Vvl31tqz020vBgXvYGngAuA6xtflNQP2BvYAXgd+A1wl6TFbH9RdjsV2BjYEvgYOJMw\nblavneoKwmO1LjAFIdb4R2D78j49gNuJFh0rAXMBlwFfAL9sw+dIOpB99tmn2UPoduQ173ii31MP\nyjTVQXRsn6mk40njZ/xYe0KezPadwJ0AktTKLvsBx9q+teyzA/AO8H3gmuJp2hnY2vYDZZ+dgBck\nrWj7MUmLARsCy9t+suyzD3CbpINsv11eXxRY2/ZQ4FlJRwInSDo6y/iTJOloot/TCJZYYit6955t\nor/fZ5+9y6BBV3don6mk40njZzyoDIzWkLTkhCx1l7QAUVJ/b+39P5b0KLAy4X1agfi/rO/zkqTB\nZZ/HCE/OB5XhU7iH8E59D7ip7PNsMXwq7gLOBpYAnp5QnytJkqQ9zDlnH2acccGJ/j4ffPAagwZd\nPdHfJ2kumfA8AZA0raSfSXqMCW8gzEEYKO80bH+nvAYRyvqilfyi+j5zAO/WX7T9NfDfhn1aex9q\n+ySTCC+++GKzh9DtyGueJF2DNH6+AZLWkHQJ8BbRzf0+wnvSLdlkk03o27dvi8fKK6/MjTfe2GK/\nv/zlL/Tt23e04/faay8uuOCCFtsGDhxI3759GTp0aIvtRx11FP3792+xbfDgwfTt23e0G9QZZ5wx\nWpXO559/Tt++fRkwYECL7VdeeSU77bTTaGPbaqutJrnPccghh3SJzwGd5/9jn332YeDAgQwcOJBD\nDjmEHXbYYeTzgQMH8tBDD7HmmmtywQUXtNh+3HHH0bdv3xbbBg4cyAYbbMDJJ5/cYtuZZ57Jmmuu\nycCBAxk8ePBE+Rx1JvX/j4svvrhhbEMZMKA/H388pMX2l1++g6efvqzFtq++Gs6AAf0ZOrTlZx48\neACPP37WaGP7+99/z7vvtuwu3h1/Hy+8EEnfn332RYvt11wziBtvbDneoUM/p3//AQwZ0nLtfccd\nL3PZZS19AcOHf0X//gN48cWW1+epp94ebVxt+RxXXnnlyHvNAgsswLLLLssBBxzQ6rkake1x75WM\nRNIcwI7ALsB0RNhpd2AZ289PgPOPoFbtVcJerwLL2n6mtt/9wJO2D5C0NhHCmrHu/ZH0OvB726eV\nHKCTbM9ce70nMAz4ke2bJB0DbF5EG6t95gdeA/rYbtWrJWk54IknnniC5ZZbrrVdkonA4MGDs/qo\nAxk8eDALL7wIw4cP67D3nHLKqXnppRe69f/zwIEDWX755VlvvRM6LOx1zz2H0p3ns+qan3DCeiy4\n4IwT/f1ee+0DDj30nglyzauxE/mtA8e0X+b8tANJtwBrALcRnd3vtP21pN0n1nva/pekt4kKrWfK\nOKYj8nTOLLs9AXxV9rmh7LMIMB/w97LP34EZJPWp5f2sS1SlPVrb53BJs9TyfjYAPiJ6lyWTEN35\nhtgMhg4dWgyfPzGqpd/E5AWGDdueoUOH5v91kkxg0vhpHxsDpwNn2355Qp1UUm/gO4wql19Q0jLA\nf22/QZSx/1LSK0Sp+7HAm0SScpUAfQFwiqQPCH2e04GHbD9W9nlR0l3AeZL2IErdzwCuLJVeAH8h\njJzLSnn9nOW9/mD7ywn1eZOkc7MY0D09AknSVcicn/axGjAt8ISkRyXtLWmWCXDeFYAnCQ+OgZOB\ngcAxALZPJAyVPxJemqmAjWsaPwAHEPpD1wH3E1o9Wza8z7bAi0SI7Fbgb8DPqxeLkOFmwNfAw4TA\n4cXAURPgMyZJkiTJJEF6ftqB7UeARyTtTygp70yoKvcA1pf0hu1PxuO8DzAOQ9T20cDRY3l9OLBP\neYxpnw8Zh1JY8TRtNrZ9kkmD/v37069fv2YPI0mSpNORnp/xwPZnti+0vRqwFOGpORR4V9LNYz86\nSSYMn3/+ebOHkCRJ0ilJ4+cbYvsl24cA8wDbNHs8SffhmGOOafYQkiRJOiUZ9ppAFMHAG8sjSZIk\nSZJJlPT8JEmSJEnSrUjjJ0k6KY0qskmSJEnbyLBXknRSdt55Z26+OfPrk+5BYzuLzv4+SXNJ4ydJ\nOilHH310s4eQJBOd4cOHA+Kxx87osPeUepT3TboqafwkSSelu/Ydaj4vdLH3mbTp1asXYLbaaglm\nm633RH+/d9/9jKuvHlTeN+mqpPGTJEnSBsIT0INx6IROYNIDUdGnz5wd1mTz6qsHjXvHpFOTxk+S\nJEkbCE/ACJZYYit6955tor/fZ5+9y6BBV6cHIkkmAmn8JEkn5YILLmCXXXZp9jC6HXPO2YcZZ1xw\nor/PBx+8xqBBV0/090mS7kgaP0nSSXnggQfo06dPh73fLLPMwnzzzddh75ckSTKxSOMnSTohgwcP\n5tpr/8xll13WYe855ZRT89JLL6QBlCRJpyeNnyTphAwdOpRhwz4H/gQs1gHv+ALDhm3P0KFD0/hJ\nkqTTk8ZPknRqFgOy5D1JkqQ9ZHuLJEmSJEm6Fen5SZIkaQfZZiFJOj9p/CRJkrSBbLOQJF2HNH6S\npFOTrRY6imyzkCRdhzR+kqQTkq0Wmke2WUiSzk8aP0nSCclWC0mSJONPGj9J0onJVgtJkiTtJ42f\npFUk7QUcBMwBPA3sY/vxsR3zwgsdlxeSrRaCrDxKkiRpP2n8JKMhaSvgZOBnwGPAAcBdkha2PXRM\nx22/fcfln/TqNRX//OeL3dYAqnJvsvIoSZKk/aTxk7TGAcAfbV8KIGl3YFNgZ+DEZg6sYvjw4QwZ\nMqTbGj9V7k1WHiVJkrSfNH6SFkiaHFgeOK7aZtuS7gFWbtrARsPNHsAkQVYeJUmStJ80fpJGZgF6\nAu80bH8HWGRsB66//oIsuugsE2tcI0kvRJIkSfJNSOMnmRBM2Yw37cgE60mN6rM/+eRbDBny8UR/\nv3ff/azF+3ZH8po3h7zuHU9nvua1c4z1viQ7wwfJKErY63NgS9s317ZfDExv+wetHLMtcHmHDTJJ\nkiRJxs52tq8Y04vp+UlaYPtLSU8A6wI3A0hSeX76GA67C9gOeB0Y1gHDTJIkSZLWmBKYn7gvjZH0\n/CSjIenHwMXA7owqdf8RsKjt95o4tCRJkiT5xqTnJxkN29dImgX4NTA78BSwYRo+SZIkSVcgPT9J\nkiRJknQrejR7AEmSJEmSJB1JGj9Jm1Ch2ePobuQ173jymnc8kno2ewzdke583dP4ScaJpJ4uSJqq\n2ePpDlSTUrnm3XaC6miq73r5O+fHiUx1jW1/XZ5P09wRdQ/q113SVJIWaPaYOpr8cSfjpPxAppB0\nCnCWpInfTKqbU7sZ7AOcJmnBJg+pW1C77kcBW0uaoslD6tLYHgEgaR1Jfwc2LlpjyUSgZvRU130v\n4BlgXUlNEattFmn8JKPRGOKStBzwJPAl8EvbnzVtcF2YuqdB0rfKzWBVosnsa80bWdelle/6OpKe\nAb4DPGz7i+aNrmvS8D3vIek3wG+A/ravtf1l80bXNam+5zWjZxpJ/YC1gE1tn2+7W2m0ZbVX0oLy\nA6nc/qsDkwOrAFPbPlzSIsC3gH8Brzi/QN+YEmqpPA7zA98D/gcsB/yOEO2aF+hhe2CThtnlkNSj\ndjNYDJgK2AW4wvZDxeszLzDU9kdNHGqXoP49r22bCbge2AqYBpgVmBv4h+1/d/wouzaS5iAkTG4B\nDgd+Tyj6zwwsCfzF9t3NG2HHkTo/SQtKjsn0wB7AJkA/YABwu6SlgBfL9peJ1do/mjXWrkIJK/YA\n1gYOBc4G5gFWBzYFHgKWBWaV9FPbec0nALZHlByT7YFdgR8DiwH9Jb0JfESsjG+W9GvbnzRtsJ2c\nsqiqDPyfEB7NG23fKekN4F5gIKOM/kclHWL786YNupNTX8iW53sAqwHP2L5F0qzA3sDTwKvEonZb\nSc/afrspg+5A0vjp5jSuxiRNB+wH7A+savuFsn014E3b70o6mbhBv9mMMXd2iqHjBq/Z2cDOwLa2\nry/7/R0YThia0wDHd/RYuxJ1T095PjNwITAb4fp/R9JWRCuXVwhDfyPCCP1fE4bcqSlJtPPZfqA8\nnwc4lWiBczNwiKQ1gR2IG++btr8qN+m50/AZP1qbXyTNSBjyq9jejtjhQkmXVWFGSV8By3cHwwcy\n56db07AaW1/SvMAnwA3AEGD98loVbvlvWbVdSxg+H2ZZcPuobsDFw7ZoCSNCeNiGEaGXyih9krgB\nLwtcRIRgXm7GuDs7DSGu+SVNZvt94H7C2zO87DrU9lXFu9aHWBkPB75u5bTJGJA0NbGI2lbSvOVG\nvAjwkO3tiWs7NfC3Ukj6OtBH0unATsDDTRp6p6c2v6wq6beSNrf9AXAi8KWkdWFkE+sRkraRdCfh\nZR5T/8YuR+b8dHMkLUt4FEYAg4nO7dtK2h9YE9i9rIinALYlJqYjbA9o2qA7OZJmI675YsBbwFO2\nj5X0S2Br20vW9t2VWBmfZ/uypgy4iyBpceC3QE9gCuAwInftUuBp20eWVXNP4DziZn2M7TubNORO\nR72aSNIaRC7P07bPLXPKD4DpiKaTR5SQ70JEU+QrgZeIooq8MbWDhlzNXsAZwELAyYS37VoiTeEA\nYA3bG9SOPQJ4w/aljefqyqTnpxvR6KWRNC2R63AssCXhdVi55EH8FXifyP2hVL1caXvNNHzajlrX\nijkKeMT2KkReyY8kLWL7N8CMkn5e2/fPtteoDB+l5k+baLxOkuYCTgIusN2XuDEcQFQwngNsVP4P\nRpQwwG9tr1wZPmP4f0wKkiaDkV6HEZJ+CPwCWBrYvBj8g4jw1j62Dy2Gz0+JOWZyYDvbR3SHG++E\npBVjZQEihLg2ES438O9SpXsVMLmkA6udbf+2Zvj07C7XP3/Q3QBJy0iaqrYy2FEhVjg1MRmtA/wN\neBtYxPanhPbDI4QxNBeA7eGtvkEyGpL6QAs9jdVKuGVWIsfkHUn3Ef8Hm9h+qRzaDzi7djP5oBxf\niR5m+GUslLySul7P0uWlRYmkzuEll+p2YM9yQ3iA8Dj8pjqP7ZfL8dV1H5krlAQKpleUqn+ntn0v\n4EjgV0QYZQZg+1JFNADoJ+koSbcQeW7X2/4855e2I2lFSdtLmryEuNaWdHIx0ucBdpL0ALA5sJHt\ncyTNZPsVwgs0a8P5BN1sfrGdjy78INzODwPfLc9XAO4kVloLAHcD9wDz1I7Zi1gZTwvM1OzP0Nke\nwIrEDfX/yvOliUl/7vL8KeCfwKK1Y/oC3yl/L9fsz9DZHsRC7leEu3+esu0A4DIijPU9IsR4d3Wd\nyz7V/9FCwLeb/Tk64wNYBhAwbXneH/h57fVdgesIA3QaIpfwCGDnZo+9sz0YlapyFBEmXKk8P5Io\nlqjm+PuBw2vHrQRcQRiiPZr9OSaFR3p+uig1z8HVxKS/Scn4/z8i6fBL4A1CvPA/wMKSFpN0ExGX\nt+1PbP+3OZ+g81ELtTxPeBZ+VDxsmxH6GUPK638o/34iaQ5JZxC5KDMD2B6YieRtp6x+RxCyCzMB\nq5fv/1rAGY7V7OfE/8mTtl+RtICkq4gV8qy2X7b9al73cSOp7uXpQeQK3glsXDZ/h/A+VNxD/F/s\nDfSyfbcj1HJhx4y4a1CS9quQ1CVEgcQaiqq6VYlFFcS8fhuwg6RtJZ1DhHbvtv2hR3mju/X9v1t/\n+K5IzX35VXFJbwH8mRAqXIO4OZxf7QOcQhhAewMXA3fZXs/hHk3agUe5jDcgbgifEQniUwF/qu13\nPhFmPIUQGxtGeOYere3TLeLu34Tad71SBB4KvEd4IjYi8hweK/s8C5wFrCfpWuK6P2V7E9vvVefM\n6z5mJE0u6WLgEUn7wsgcnw8o+l8lX/AkYE9JK5dD5yJuzM8DqZg9ntSMln2JBeqTRNHEAcDntp8v\n+71j+3dEGPfbwIeEh+ii1s7XXclqry6KpE0JtdrBtveX9AeiemtaYiJ6kIj9TlFWwlMCI5xy/uON\npOWJSWl2wpOzIbA7cTM+hZj8HycqKz4s3omZbb9Tjh9NATcZN5LWIsIoNwCPEXlT8wCLE7+BIWW7\niXDv3MCHlVczr3vbKJ6CC4hKuTmA54Djbb9d8gKvAC63fV7JA1qcMHy+IkIwf2vS0DsljYnMkpYk\nRFA/Ao6zPaTM68sSYdu7iBzC+wjD/uGG8+X3vEZ6fjo5JemwR8O29Yi2CENs7182n0L8aM4tj++U\nf/cvP4phafi0nVaqiRYhDJuZbe/m0C15kIi930e4/jch5ORPkjQD8LVDRqBHmehyYhoLjd91ST0l\n7UC0RzjP9lkOfZ77iVDuNcCCRNLtQEKq4Qvbr9n+bzk+r3sb0CidpNeI/J5tgTkJNewlbf+HWExt\nXqrmfkkYnkfZXi0Nn/bRWHVVFkqLEtf9vloI/VrCy3wMUV13OaHi/GXD+fJ73kB6fjoxaincNjcw\nne0XSp7JScBStteo7X84IS52WPH2TFZCX0kbUcs+XFMAswAf2P6fpD8RScwrFONoBPBDYDfimj8p\naRbbQ5v2ATopDdd9WpdWE5IWJloj/MF2/7JtNuAEorrrZNvDJC1t+5kmDb/LIGkdYCfbPykG/L3l\npV1sP6WoYHwQONHZAPkbodDr2ZsSMrT9VslTs+1tavsdR1TtHm/7ueaMtvORnp9ORvESrCZpSoee\nRg9JJxEJbsdLup3IMTkPeF+ho1HxB6LaYgYYmfOTtIESWqF2A96F6IlzFnBjyXXYG1hG0qq2vy4r\nt8eJcNcy5VRV6Xr+9tpAMW7q1/0w4G+SLpF0sO1/EobOliV0i+13ieq6pYiKRirDJxOax0zxrH1b\n0tlj2a03MIdCJfgu4B2imvQ0hYjh7sClafi0D0lrSdq99nxz4Amiz9mOwN2SehOe44UlrV07/HJC\nl+2l2vE5v4yD9Px0MiTtSZSvr12Mnx8RAoU7EMnMpxMeoI0lHUD0JdqjllcyRYa32oekVQjDcUfb\nz0hanyir/hnRbuJG4AXbB0s6Gvi+7WVrx/fOm0H7UEjvH03k6PzS9heSjgKWIK79/IRg2w8ITarz\ngGdtH1WO70H8Dj7s+NF3biR9AuxaKkUbXxORVP4ZcJDta8v2tYEZXfrSJe1DUZH1te29ikf5FOAW\n23eV1wcAD9g+oswx69tetXkj7vykddgJkPTt2tOriNDVouX5+sDHtr8sBs5PgO9JWowo7e1BVL4A\nI5Wak3EgaQZFk1eICpXXCFl+iKq5v9p+oXjPfg0sL+lbto8Glpa0dXWuyvBJr8O4UfSEqiq4/gcs\nUQyfaQnJgN/YftGhvHwy0X7ifULPZ1dFf7qqCunDXAGPF+cAvyjXvJGZiKake9UMn8ls/zUNn7Yj\naR5JPy4eY4gF1JYwco7eiCJ9UTiCkGXoSdwDhkiav+GcOb+0g5wYJnEkbQi8LOmnkmYvFSo3EUYO\nhApzT0lzlOc9iQTbnsQNez/bl3T0uDszip5EbwIHAZQk2lkJuQCI0NWPq/0d5dQzE1UXAEvbvqrx\nvFlGPXYk9QPul7Ri2XQ2odmzbMnx+Tfh6am4HJhW0kyE238r22/Uz9ndy3nbg0L5/e/l6TJEAm0L\niqG5ApFjUm3L8Hn72Zf4/u6lUN+/E/i3pJ3K6xdSW7QSDafvJioWX7b941JUMZKcX9pHGj+TKLUV\n65dE3shCQFW5NRCYurhHXyZ+ECeV135BrM7+U7xB/+64UXcZniHi7dtI2rtsO5+Q4sf2KcA0ko6W\nNJOkLQmNmUqnZxBk3L09lFXrJ8BkwH6S1io32usYdRO4DlirGKcQGkqP2P6vQ7wte861gZLb01gh\nOjuwNXCA7YOJa3uQQkCv2qeqcDyOUd/1pI0oKkIrngEuIozI35Zt9wHfKr+F24F5JF0qaUeiMvel\n4tGs8t9yfvkG5MWbxJC0iEK7Yduy6WkigflWYNGSwPwy4WUYQSQbnkzcjO8kVmzbO5WZ24xCDPJK\nhUQAxPW+mbiuG0raiug6/URJ9IT4/1mSuCHvAhxp+20YtQJLr8PYUSiKH6VQWDbwX+AhQpTzFEU1\n0RCgt6LU9xaijL2/pMeI0O/vmjP6zokU2jElX7BX7Qa6MOGxfATA9pXE3PLr6tjqpmv7quINTdqI\npG2BcyVVVVqDiby1Q4A1i4e/J6GfhO2niHnlaWBtYF/bx9XPmfPLNyMTnicxJM1CVA1tRoSsHpJ0\nAhFquRY4jYjJXwNsYfuectxkwPRltZy0g1Il9CvCoNnC9tPFAK2qWTYllFI/I6rqbqkMHEkL2n6t\n/N3YXTkZC5I2ITp6D7f9o5Jj8gQRVjmEMIYWICQb1qodNxswp+2ny/O87u2kJI+vTxibxxIe5puA\nC21fU/Y5nFAJXiO9at+M4lnrS1QmrmL7pbJY/T2hv7Y+4QX6PiGXMZocRvEIKY2eCUN6fiYhyiQ+\nlFht3Q5cKGkpom/OjETOw7nEzWEq4ocCRNw9DZ/xwyHweDhh7BwsaU2iHcWRJZ/nj0QocVdgdduu\nVsw1w6dn3oDbRpWYaft2IryyqqQjiATnCwhdpOOAj4lcqjVqHjdsv1szfHrkdW87kjaWdCBxXY8k\nPMV/dHRUvwM4WtISkvoCsxEhmZfGeMKkTThaTpxHeIpPKJ6eM4FVi7ftZiJ9YSZq+YQV1fc8DZ8J\nx2TNHkB3RjWRQhgtXPIrSfMRK+NPiP5PvQnPw7PEDeKfHT7oTk6prvisfsPUKLHHXxGJ5GcRE9BT\nkta2/VdJRxLen9lhdJezUz11nNRCLpXXrKftoSWU+zNiVfwYMG855BJCrn9rWla+jCRvBmNGDe0M\nitHZj/AwLGH7c0kvAG9IOsn2aQqx1COJkOK+TmXmdlEWRa7PL9X28l09kCik2IcoSHlV0tTF23w8\nEfq6tvG8+T2f8GTYqwmMy31ZTVqKst0fExo+cwB9XZpflh/M5x026C6AojfOEoSHpzcwd/Hs1Pfp\nQeT6bEY0Drzc9k3ltdkcAnrJeCJpAdv/auXGvB5hAPUB/kLceKvEzpGhxWTcqKXye2+ix9aTquLg\nWQAAIABJREFUjmbHKxBNdZex/XLZ5zjgB7YXq45x6lK1m4brPnOjJ74y/ktqw7bAqUTuz3KNOZoZ\nyp34ZNirCdQSDheX9EdJO0j6Hoz8AVWJhW8AZxCJnrPSUq8nDZ82UqtS+RjYhshtuB3o1bhvqaY4\ngLgB/whYqfbauw3nS8ZCKxVFiwIPS5qxZthUIbB7CK/EdIS3syp3x/ZrKv3POmzwnRi37P79MJFD\neJakJUqi8pWEd7Pa/3Cismil8jwNn/GgzOnTSjoNuE7SMQpB1BZhcdtDbZ9OVHtNQ3iUR5Kh3I4h\nPT8dRLUqqNyiwAGEO/9MYBGiA/jmjgaBrR3f1/bNHTbgLkDj6knSskB/ospiT9v3tnJM5XWbg1DH\nvtX2/zpqzF2R2nd/ScLt/wvbHzTsU133DYFv2z6r1ZMlbUJSfyJ/ZC9CPO8EYIDt7UrC+BNEWft1\nZf+R/dKSttGYtqCQBTiDSE24jchf6+Vaf8WyX/Vdn5ZI9k/h2SaQnp+JTC0xdkTt3ymJiWljovni\nJkSy4WghldrKOA2fdlLLLVle0hWEq3kfQhBvuVKB0XhM5XV72/a1joal+TtpA5JmrbwH5fkqko4l\n8tMgqrc2JPJ4WlC77ndVhk96esZN4zWqPT+dqJg7mVhoHQcsJOn7xYN5EfDz6rg0fNqOgnqIqxKY\nnZUoTX+Q8Ky9TyT0t6D2Xf/EoV6eubdNICf1iUjxPFQ/kLUlnStpHkJTYxki9HIYsLPtXxJ6Ji0S\nO9P92T6qkJRGsQ6R4/Ok7UMcjTAfIBoG9in7zqDoJdUqmWw4diTNXq77PESD0UMUvYqWIzpSH6YQ\nahsGXA2MsydR5jyMnep73uDZHHnNbA8B1gVmsL0iYez0Bn6rSPD/le31mzD0Tk8tbeE7kq4ETi5G\n59yEAvn5wLm2t7b9qqT1VJrujuF8qZDdBNL4mcBImk3SdyB+JJJ6K7okn0D0g3qT8PbMAdxte1Pb\nAyUtRKg0L960wXdiah62r8tKavJyI3iGqKpYsrb7NYRuUt/iETqZUsWVtA+F2vLuRJXKe8AWhMr4\nc7b/YPvPwJ7A0kSu1eKEdtJYFWrT8Bk7tZypHSQdXM8pqXl/ZiU620OE2O8mQjGTpVet7ZR8s60k\n9altW4eYRwYAPy/X/p+E9/6cylMv6ffE72O2jh95MjbS+Jnw/IJYYVUsDMxl+3u2ryyT1KfE6mA5\nSReV+Py1wOu2H2zCmDs9NQ/bbkS/s/MlneLQTTqWuNYLlX2/JgyepwnX9IHFKE3aiKQfluv5oO1j\ngMWIcNb5wL3AW2W/ng49n35Em5YViHBvetTaSd1YlNRH0n1EPs+DxeivQuSV4fgIUUr9DKEWfI7t\nUxy6Vmlctp1pCA2qpxQthQCWB/5i+0zbn5Yw2CCiwe5Wkm4q130KYDfbg5sz9GRMZMLzBKK4kr8q\nE1QfYDqHPsxehJDVtoqy0+GVm1PSMkSzzNmAs51l1G2mtbCIpJ8QMfZ+ROuPWwjtnssIJdWpbI8W\ngy/H9sibcdsoIZeHCU/OqcB3gaOA02zfJOkQSusJ2y/UjpuW6E8nQjnYeRMeN6rJAih0eKYmKj9n\nsH2spF5Eldxw2x9Lmtz2l2X/aYDF3SDpkLSP4k3+FfC87auKN/8VYl6RW8o2zEh4mv9bDKKcXyZB\n0vMzgSiGz2KE8vKOwO6SpiOqKtaTNL3tz8p+60ra0PbTts+2fUwaPm1HYy4F/RFwvu3HbT9BlEwf\n7lCvvQhYV6He3Nr5cmIaByWHqroRHwesRfSDeoBotru2opLo9nLIppIWlrSfpBlKUu20RAXMiDR8\n2kbN8NmMuLarEBWLq5eck1OJ6qI/l/0rw0e2P03DZ/yRNLWkY8uCdQ5gxWJQPgFsACxbvG5zSLpE\n0vK2P7D9oO1B5TeT88skSBo/44katF4UwlVHA2sCxxPx9h84pMvvAa6WtL+kPxJhmExyayc1t34V\n4jpW0mGK8miA54hqoorbgY8kLU6oYm9bbtQtyIlp7DQk11ZVizcRuTtbF8/DFUTC8ya2nyNuxusQ\nrVnet/2hpOWIlizZFHMsqKZpVG6eU0l6hKjO2tX2JYTBcyFwdvn7R0AvSXNW50njsn2MIQdtTmA1\nSXMR+VLzAd+3fT7h+TlR0qVEqPelsugaSZUcPZGHnowHWWLXTior3qO3M/iI6L81wvZ/JN1BVL78\nlSj13YCocvk3sHtOTO2nltC5MqF8PSehwny+pF8QOQ67SdrJ9kWEB+51YlL6mkhOzEqidlLzPPwC\n6CFpkO07iJvuqcBGJdz1GOGNeNb2nyU9Shg+lU7Si0ST0uHN+BydAbUsoZ4L+MAht3AjodkzrHx/\n3wCuKvstTRRUDCKSzpN20MqiaiHgQ9vvEYn8UwFf2X5U0rNEF/ZHCNmMhYn8n36232rKB0jGi/T8\ntJGyAquXrq8q6SFJeyrk978kPA87lENOJa7vTsBktm8ADrF9XN5420YVZmnYthbRiforRylpfyLu\nvhZR1XU1cJCke4kKl/6Nhmpe/7FTueprz78n6SGiNcgrwI2SViyr3AeB/yvhriuIqrn5y2/lzXLj\nngxClTwNn7HjKKGeUdJFRK7ayZLWtX0CoZO0Um0RMIOiIexlwM2293CWTbeLEsa1bSuSyE8nNJKO\nLqHafwKfEsrwEA2PZy7Pp7T9ou3Lbb+lVCHvVKTx00ZqP5DZFRomWxCTzneAS8sE/xhRXTFNMYau\nAOYiFJ0zvNIOqryeEk+fXtK3FEnl9xMihUvUdr8M6EtMRpcThtBBttctYcekjSi6p29UbsJzS5qK\nUCDfn1BnXhv4nPA0AJwCLABs76iY+7ntP9cNzLwhj5kGI1OSZiLaTzxqe13ge8C+5aZ6IrCHpG8B\n2P6QSOpfvng6k3ZSm1++D5xGXM99gRmAPynyOO8Avi6G0qvAjcD9rrUYqhbGubDqPGS111jQ6M0X\ntwbOAU60fVzZJuIH8xxxE+hl+/vNGG9XRNLuRJXFc0RocWuiF84LREPAp8t+dwCH2X6q4fgW/4fJ\n6BTDfQPbt0tamAif/IFo7roR8DaR6/Cn8jgNGEpc7z9K2pUIz/y5ds4MLY6D+jVSJDN/BAwHVib0\nqQ4kDM0DS5gLSX8nkm33y+91+1EryceSbiAqdPe3fWPZNjmhuzYD0d/vatu/6ujxJhOP9Py0Qi0G\nXOU6zFJeuppI+Jy5bJ+6TF67AC8RVRhr1JMOk7ZTrYKL+/h7km4jbrp9CKNnWuBXxRV9IXCfIon8\nceLG8WLjOfMG0SaWBpYqIcbPiGu5CbCw7VcdjS7XA26z/XtCu+RfwJ6SprN9ft3wgQwttoXiSZ5T\n0m8IQ+ctQiPsZOAg4AzbP7b9hqTVy2G7AVfl97r9NKQtrKSQGgE4lLgXVknmPYvn/kjCy7MQkcyf\ndCHS89NAQ8LhxoR+ySDgGdunSdoF+LXtucs+9dXbJsBrtke7CSdtQ9J8tgcX1/6/iBvAfuW1jYmb\nwhZEtdx7wB+J8va85u2g0TOj6HO2q+3flhvt/UQZ77Pl9cOIG28/wti/jVAoz+veRlrxJM9OtLfZ\nCljC9n/L9seB+2z3K8/PJAzU7Zxiee1CNc2j8nwRInw4BWHkv2T7KEmnAPMCP62Hs8oxC9j+V0eO\nO5n4pOcHUGiRHAwtMv53J6ortid6Qx0jaQvbFwCfl0RDKKuFcuzteTNoO1UibOVpU/S/eV3SZrb/\nTayAR3ZEdlQYLQAsY3sYcAywZXXNG5Ojk9ZR6zpJ0wDHStrAoTJ+JpFLBYDt44mQ7zbANbbPsP1i\nJniOG9Var5Tni5Tn7xBG5KdELlXFrkTV3PWSniQM/Y3T8Gk7irZCZwCHqmUJ+0HAxbY3JjzJaxZP\n/dGEMOFmtXNUEYB/lec5v3QhurXnR6FPcgywKaHT8Fvb75Ufy7GErsMWwHbED+YP5bi1gPuAWarV\nWtJ2JC1aNxIlzeJoQ0ExKn9qe+Hy/CPgPKJ6bjOixH1rF1FISe8DW9m+p4M/RqejFW/Pr4D/EF7N\nxyT9kriWS5XXPwEOJpL6hzoqjsZ4vqQlkma0/UHt+XrEvDKU0Dq6AhhMeH8WBnZyqYZTqGHPB/zP\n9msdPfbOjKQ9gJ2JdirnAYMc3dMXJYyffxAyGE8QFbifleP6EeH11R0tiJKujO1u+SDcnhcA5xKt\nKBpfv49wi/4amKNsmxlYtPy9PyEzr2Z/ls7yILpMP0Qk085Sth1MuJ7r+w0mkjwhJqkRhKv6CsLr\nAyEfANC72Z9rUn80fkeJ3LRzgOsJpeZ3gBWJFgnPA/uW/TYjtGQuJ/rTVcf3aPZnmpQfhPryheUa\nL0J42PcC/ka0/ViZ0Ps6idCQWa5c573z+k6Qa39TNU80vDY58AYhzzBbbftWwLfL3ws0+zPko4O+\nK80eQNM+OMwNPF17/m1ipbVUef594E1g6vJ8FWIlsV+zx97ZHmWCPwv4OxGmguizBTAL0eV+m9r+\nOxH5PD3K8yeJ3J/q9bw5tO26C+jZsG2LYkweUtt2CnBR+Xsb4BNg8vJ8mvr5mv2ZJuUHo3qWPUcs\njpYFvlVem6/8DvYgWoFcAFwHbFFePwS4AZi22Z+jMz/K9/f58vfchKd4KyJfimKEvkKEuBaiyApQ\nFrVln5xfusGju4e9BhI31krFc0Yix+QY4FLgl8DiRAXMTMDJtq9tzmg7LwrF1FNtb1qetyg3VTR/\nPdD2guX5xkQuxJm295G0EtFIc26nimq7Kdox/Qgvz6eEEvYztncpr89N3LCXt/2aQk34BNc0klor\nEU5aImlFQpZhe4cGT+PrawKHA31tD5f0EvBPYHdgGDDMJQSTtJ2GIpXJiFDuIKJC61FgQaKK7l7b\nv5B0ErHoWpgQhzyh9TMnXZnu3t7ip8ARwMeEq/RtYrVwKHCT7T0kzUFUvdzZvGF2emYCZipVRNMA\nK5Ukw7mAX9g+U9Iuih45DxMG6A8o7ShsPyJpP+LGnbQDSQcCPyG8bjhE3Y4CrpV0iO33bQ+RNIBR\nfbtG06lKw6dNbA686ehjNjmhQu7azXlBYq75UlKllv1g2e/95g2781EWRGvYPrFm+PRwNI5eE1id\n0Er6zPazkrYFdpI0PRFq70loslX5PqkH1s3o0sZPSVy2W3FvlWTNZyVt61CzHfnlLzfa6kbwNtGc\nMRl/qmt4DfAu0XD0faI316WEiNgPgD2BjYHjK69DVapq+4xmDLyzUKsoqnvUliP0epavfbdncogZ\n3g38XdLxRChgEDCkfr40eNrNtxjVsPjrat6pXcdPCS/yY8T88hvbN3f4KLsGywErSFrf9t11DR/b\nLxAiqHUMvGv7IwBJX9v+rHaPSMOnm9Flw14N+jtLERPPO7Y/b0Vvo1dxQy/PqATQvWx/0pTBd1Kq\nG+aYqoDKavdlIo/kv6W0/TXgew4ht8lcWiFkJVHbaXD7z0fk67wq6duETMODRA7VooTBuRPwBeFZ\nuxw4t9wwkm+ApC2Iaq4tbP+rmlfKa32JXJ9PgPXcIAqZjJv6YrZ4jg8gkpiPsv1xw5wvwhiFECus\nmo/e1YyxJ5MeXVbnp/xAqgaB5wI/JyZ6GgyfyYElJV0HXAT8yfYOafi0nUavQ91oqevA2B5k+wuP\nkgc4krg5v1Nerwyf1nRokhqSJpPUG0Y2w+ylEGq7E7hQ0smEF2I3Ip/nNuBnRLXLUg6V7HOAVSvD\nJ3VMvjGPEh60EwFqhs8PiQ7gc9j+KA2f9lF9L13rnVVy/wYQFbh9y7Z6PzkToa+bgSG2l03DJ6nT\nZY2fYtT0A/5ue2Xga2A1ScvW93Oof75KZP33sX3ZaCdLxkrN67CdpNskHVo0TRoNoakkLSJpT0mP\nEV6II2x/0dr5ktYpq96bgXVrxuVewLy2FyfChzMRlUWP2z7Z9gNExeJ8FGOT0E6at+RPtFgUJO2n\nhMiPIcIxd0k6XNJdRKPMY23/o7kj7JzUQrY/kXSZpH0VDXfvIvKm1pS0QNmnfk+7AVjbpSdXGvdJ\nnS5n/EjarNwcviYquKaXdDtRyv5d209pVA+pSsHzQ0cn6pz820h9Iileh3OIFdiBRBnpr0qVV53h\nhA7Hd4lS651t/6dhwkrGQVn1vglsyCjX/qJELhW2BxE9iRYAZpG0tKSHiAT/nW3fV/b7L7CYa1Vd\nyTfDId65PtF2RURDzLVs/625I+u8KPqf3UHINJxCVMcdDfQiFgE9GOX9Gblwsv2p7fcVvQKV83tS\np1MnPKuhb0thf8IdejxRXfE94GiXai1JGxJlpQ9kaKX9VPkljqqhGQitjFfK4xrgh4Tx81vbL9eO\nUwnP/LVyPxfjU05Pz1gpxvyytu+ofef3JfpvrQ68DkxJCBVeVA67D/gd8GV5/QDbj5XzjcydcCsl\n2ck3w3b1e0jayRiqrqYBziBU+PclFrUrAJvavlLSU8AGkh60PbDxnDm/JK3R6VbcxYrvL2l6219K\nmqIkdlbeiDuJ8sbhRK7Dc8DkZb8zgP6MqshI2kktxLU5kUfyHaLyYmdCMfhbwEq2r5U0j0IqYGT4\nqwpxVXk9OTG1iTWAiyXNX33niZvA4sB2kuYiNKl+JOlnJen5QELG/0PbH9cMn5713IkkmRSoeeGr\nENeOklaVNFVZRD1EKLzPY3sBQstnpxLuupEw+p9qzuiTzkinMn5q5YwPAx8XY+cY4EpJC5YfTk9i\nVQBwGlFhsQfwV8LoWdX2Qx0/+s6JCrXnvRQdvs8DDrV9pe17CQ/DnbYPsD1M0v8RKrZztnbeNHra\nju2riT5Eu0nakajemgdYDPgfIao3mPB69iFaJcwD7OMG0bx0/SeTIrUqre+WENeuhGDkEcXYn5GQ\nB+hfDnmHaMeylO03bF+fc0rSHjpFqbukGYHpbb9enk8O3EEkyz4q6fdEzsPphKfnVmADR9dkJE0D\nTOnSPDNpG2pZej6d7Y/L36sT13gH2zeVbRsCR1FaghAT0/GOTuzJN0TS0sBfiOT8fW0/Ubb/GNgF\nOMb2w2XbXLb/U/5OvZ5kkkSjpDF6ECkYOxHtKU61faOk7xP6X7cSquRXE+HcZYEPgJNsP92c0Sed\nnUne81MMndWArSWtpFCnnR94mjB2sH0A4fo8kPAEPUYkG1Je/zQNn7YhaWpJ60OUnpcKrdOAqyTt\nJmlh2w8CZxMeNcq+dwHbEQ0dL7W9Rho+Ew7bzxAenX/bfkKj5AWuIZL711HoJlGSyJWGTzIpUvvu\njigLrBElHP4ZobA/W9n1b4RK82aEsbM3YST91fZPKsOn7plOkrYyyXp+1FJxeUMizAJwnO1zFDLl\nAwnvwvllv+8Sq4P5gPltv9mEoXdayvW7lhC9O64YQScBFxPtEU4meqHtQ1QSXQhcYvui1hIVx5C8\nmIwn5Tv/BHBYyamqVs4jPT1J0lmQtDfREuRp4G+2b1XoU4komHhf0S/tIOAp28c1HJ/GfTLeTHLG\nTy3xbWQMmIj1nkQkue1XeXEk/ZSo5FqgdvxC1GTMk7YjaX9CNOxKImfkOWIV9j+icmha4HPgcttX\nSNqXMISWLAnmyUSm/B/tBqxThXVrr+XNIJnkqFd1lr8nJzz0SxI5PGsB2xKe457AfsB9ZVE1GSEd\n8Gy1mG28RyTJ+DDJhb2q+ltJq0m6j/ghvEJoO3wA7FH78l8CDJX0x9rxL6fh0zYUKsHHSqrCVx8R\nSbNXAJMVb8L/iBDXBcA6xKrsp5JmJSosfpKGT8dh+1SiqmU0mYo0fJJJjeL9dTF8ZioGy2REKsMR\ntgfY/g3R4+8ohxDky8CmpYjlK9t32H6zbvSk4ZN8UyYJ40cNInfF29OfSHzb3iEJ/xLwLKEr06dU\nHa1KVAVk49HxowfRYHTHkls1HzAYeNj27WWfOYEpbN9UJpzPCCN0YdufOAXyOhzb29keMu49k6S5\nOPTAekg6FriryJJMRWmzUtv1eeCrci+4E7jA9msN50qDJ5lgNNX4USudqAuLEW7Om8t+k5ftdxI/\nmnOJfJ/5bT9t+4YOGnKnp0xE1QrqCyLH513gINvHEJoyG1dJz0Qy7fuSrpM0kPDC7eSUC2gqjQuG\nJJkUaEUaYwGiUmsyYEvbrxKLpyHA8pKWK7suD7xRkp8fy2KJZGIzSeT8SNqaCKncQIhZ7QKsYfsH\nVbm1pF6E8f9FKYF81CHzn7QRtez+/S3gPw7RvL7Ar4FtbL8g6VRgYaLM9Guium4H4PbK05P5JUmS\n1JFadFVfC1iJmNN/B+xICKLOB3xMLKL2JBZbnxJ5nfvafr7DB550SzrU+GklmXkOorkiwJ+JENYg\nIhnu30Qp9fXEzfd44AZn49F2oej8PblLGwNJswO/JYybocAlhEftVGA629sVQ/N5orrr7Lq7uZ68\n2LGfJEmSSR1J0wLfJxZLlxEq4ycT4fO7gFmI5OZ1bT9cqrl62/5rk4acdFM6zHWu6Bw9d0lm7lU2\nzw8MtL01sATRiXpASVj+BbAlcBNRvn5LGj7tQ9KCwHWEACSSpiO0kQbYXgPoTXS+n5pIXv62pE1K\nAvNJMFpXdlXJix37SZIkmdRQ613S9wOOBO61fWnx5GxNKOv3s70L0Yx0RoAS4vrrWM6XJBOFjmxs\n+l3gF5KeBVaTtDMR591E0jaEcudqtodLWsD2hZIuIlpVPOmiNJy0HduvSZqf6L31CKHN8wXwkqR7\ngbeILt8flHye+4huybfbPruV8zU/RpokySSBR+mwbUJUgd4HnEm0WJlB0jS2PyUqRiVpB0KmYTAh\nYNjq+ZKkI5honp96Ym3hKaAvsAGwd6lWeY2IAR9o+8Bi+GwD7Cdp7uJleDwNn7YhqbekeyUdJmmW\nsvlMQjIeorJrJeAPwOGlkm6Iog8XROfkn5Vzqf5vkiTdm6K5U3/+HUm3EekJqxAq+1MRqQpzASuW\nXb8i5p1NiXL27Wx/0mEDT5JWmCieH7VUZ656Qn1E3FxXAt4sCbN3SPo7YeysCSxNxISPylLe8WJ6\nQiRsZWAKSScCjwJrKXpDvUXE3Xs5eqLNQOT/9CEUVF8u+9S7sKe3J0m6MSVcfjzQS9JLtn9XXvoJ\ncLFDbfx8YHYinHUzkci8jqQXHe1WHrX9QO2cWTCRNJWJ4vkp2g5TSTobuF7SFcDXtg8u7/kLoLqp\nHgD8HhgG3GF7ddv3TYxxdUUkbV68ZThECYcQvc2+JiasVwmjqLft94A/AvNJuhEYQOj2rFMMnyRJ\nkpFIOpRoIj0MuB04WtJe5eUZgHUlPUrMIyvZHlS8OrcQeZyzAtgeVs43JnmTJOlQJki1V73EsTzv\nBVwD/As4AjiLiAmfRrhFLyKSmdcCBtu+8RsPopsi6SRCLOxK2xdL2pKIq29GxNUPJwQj77fdrxwz\nJdHGoqftwWVb9uFKkmQkpRr3P8BeVQ6gpH2APW0vJulmYDoijeG58vrWwCe2b5M0i7OhdDKJ8o09\nP5V8efl7nZLUtiDwJXCS7c+Ag4lwytq2BxAVSP2B/yNUm5N2Uou/Hw38CThdUh/gQcLonBc4FFiV\niLlvUMresT3M9hDbg6vcrDR8kiSpY/ttYvG0W23zl8Ct5e/rCA/zxpKWlXQt4dUfUo4fmjmDyaTK\neHl+JM1JaMK8VJ7PSiTKfo/IIfkA+AuR3/NOKW/vD8xre9viGZqx/LiSNlDKQLcE/mn7qVZeP5XQ\n0niQiLvfb/tBSYsSnrZ5gVUqT0+SJElFmV96OlTf69unAp4g9MC+IpqPHuGiwFyKJVYhBAzvt31y\nhw48ScaTdhk/5QdyFKHb8C7wIiFI2JdIZl6lpgB8M/AJ0M/RlO4somXFaCXUybiRNBuhd3QT0ffm\nk7rgYJmkDiCkAZYETrR9fjl2VuALZ8PXJEkaKIvZy4DftiY2WBT1ryfyBfdrNJDKPlNU2zOEnnQG\n2hz2krQ6UZo+C6EbsxOwLOHduRl4Dli7dsguwLTAaZKeKH//acIMu/tQSxB8l3A3L0FUZ1XdjUeU\nsFXVff0WYhV2QE1McqjtjxpLVZMk6b4omMzRJug14IdlkdWCkpN5B/Cpo71Qr8bzlO0ZQk86De25\nGX4MTAOcUoSrXpb0KrBmKXX8HXHDPd/2e7bfK8lvCxD36ezZMh4U42ZeIrdnBsLF/Lmk56uYeq0s\n/QPgIoWy82MOpeZ62XrqJSVJAoycF75StKT4N6EHdj/RaqiRI4CHJV1h+8lWzpMVXEmnos2eH9tP\nExVcx8HIUApE+SNEjs+zxE26Wg18Xkof0/BpI2q9W/fJwMe2tySk45ciEpkb209UXqIjbd/SAcNN\nkqQTI2l/QoD2c6LXX7+y2GpByTO8AFi8Y0eYJBOH9lZ7HQosJ+kqwg06qPyL7XeAK4FVJc2Z4njt\no7igRzYMrQwZRXuK2YjqOEoez/OEi3qe+jnqK6+sskiSpEKjK+5XkhfLA9vY/j2wEdFd/YdjCJHv\na/vyiT/aJJn4tMv4KQmzxwPrALva/nWp5Koa0t0PrFFiyEkbqeQCyrVcRdLlwK9LEuHrRAPYdWqH\n/AX4MdBX0uStnTONzyRJ6ouqMr98u7ZoErBxtW8RIrwYOIhWPDzleOXCKukKtFvnx/YFRHx4lcro\nqRLcin7MxxN2iF0fhyL2DJI2A44lGgSuT4hDAvwSOEPSEpLmItpX3Aw8avvLpgw6SZJJntqiaipJ\n5wJ3AzdI2rYUSfyJ0GGreIFQhF9P0hRjOl+HDD5JJiLjq/OzGVEauYLtVyf4qLo4rZWCFmmARQjX\n8l2SFgYuJcpPb5F0OhH+WpHQ3Dg2EwyTJGmkXgRRnu9L9E181vZpkn4K/JqQxehNLLYqwcKlCEmN\ny3N+Sboy46XwbPtWQsnz9Qk6mm6AoqFf1fR1vlrZ6NFAL6BHMY7+CdwJ7KiQid+XUFpdxfYxpQps\novRmS5Kk81EiUj1a8cx8DewMPA1g+xKi59+hJaz+Q0IVfjZgH9uX5fySdHUmSG+vpH1SzYlMAAAI\nwklEQVQoOqwfT0xKXwAH2v63pAuAqYHdbH8qaWrgSaLM9PqGZOh0PydJArT09khaCtgUuNv2E2Xb\nc8B1to8uz5cEHiWkSv7RcK6cX5IuT1r2HYykLYDTgTOBnxJhrD+Ulw8hBAw3Kiu4z4G+tq+ru6Cr\n5MUOHnqSJJMoJa9nSkm/B84DDPxG0ZUdYG/gMEmzl/2fAy6kdF2vKPNOzi9JlyeNn47nn8CPiEqL\nvxB5PetI2sr2+4SW0qGEBwiP6p+WFRZJkoyN7wNv2V4JGAwsBBwkaX7b9wP3AiNL1W3v49Kjq7Yt\n83ySbkGGvSYwNaHBMU4iRbvn98Bxth8vyc4r2Z6ter3E4pMkSUZSLYIaEppVPD+TE4um04HZgX0I\ngdRPHQ2l5yS8PT8oZe2jJUcnSXchPT8TCElzFKNlREkWnHksuy9LJC4/LmkhIq/nDUkLFbfz65ls\nmCRJnQY9sBmq7ZXxUmQvFgNms72R7ZeBj4CtJa1q+y3bG1eGT/3YJOlupOdnAiBpFqJ0tKftn0v6\nLSFC+GfgDtsPVLH02jEvEyGwFYDdbd/QjLEnSdJ5KN6dY4FFgT3cIChbFlMvAJsAawBTAffUw1ut\nSW0kSXcjjZ9vgKSpilBYlci8FdEs9hkivr4ZsAzwf7b/V1zWKp6hOQntjX+UXJ+clJIkGYmkGR3N\niqvnyxP9tW4DzrT9nzEctyeR//MuUbr+QdmeIa4kKaTxM55IWhuYzPbdikaAcxOqzLsDi9r+RNJi\nwFHAE7Z/1+j9qZ0rjZ4kSUYiaXFgFeBWYEZCdXkGYHOiIGJBYC7gC9v3Ns4hkqZ3tCNiTPNOknRn\nMq+kHUiaWVLf8vQLopT0TkIR9W2ieus1YOuyz7+I0NcPJC08pgkoDZ8kSSAWQuXPj4F1iTnlAuAr\nQgR1MeAeQiZjF+BuSXM1ziG2P6qJHqbhkyQNtNa5NxkzKwKXSlqRmJxmISalLW2/Jem/RKn6ppJu\nsf22pH8QCc3fJnJ8kiRJWlCFpGpGzCLEnAFwtO1/SHoK+AdRvVV5dW4C5gBGC4GVEFe69pOkFdLz\nMw7q+jolafAeYE/gLWAn4HNgWUm9HU1d7wfeJ9p/QLQA2b9RTyNJkqSips68sqQ/EQutHYHrgfUl\nzWz7K2LeGSZpB0kPAUOBQU0adpJ0WtL4GQtVaWnD5iOALYBlbP8NeALYhojHQ0xOjwCTS+oNUYKa\nIoVJklSUkFTPhm2bAw8ROYLH236e6Mc1O7BO2W0+QiR1C6I31y62h3fg0JOkS5AJz+NA0kzAwcSk\n9KTtIUVCfjFgYyL0dS1wN6Hf8xhwme23mzTkJEkmYep5OJKmAUaUVjZIGkgYP7uV572Bg4hu6z0J\nr/JJtl8sr4+sIO34T5IknZc0fsaCpH2IbsjXAXMCS9les3Rifxo4wfbFktYgdDWmAA4p7umsskiS\nZIxIOpCYX54H3rO9p6QNibzB+Wsl6nMQjUrnB35dxAxzfkmSb0AaP7S+eipdj/sSUvGLEjLxqwN7\n2z5L0s+BfsDqxRs0stQ09TSSJKlobT6Q9DMidLU3UcX1Z+BU4HzgKqKE/SetGThp9CTJN6fbGz8N\nLuiFgcWBO20PK2qqewE/AXYFlgeOBha0/YWky4Ejbb9WO18aPkmSAKPNLz1tfy1pMuAG4MJK2V3S\n9oTS+2pF4+c5YGlH9/X6+XJ+SZIJQLdMeJY0WS0ZeYSkXpJOAq4ghArPLcmHXwMbAFvYfpIoa5+L\nkJfH9nZ1w6dsy4kpSbo5VTJzmV96SzoVOFHShiUs/gqhCF9xFTCnpEVLovNqjYZPOV/OL0kyAeh2\nxk9pK3EzsG6tAmt7QjtjBWLFtQrQu6zYlgf2kbQ7ITq2OdHHqzpft7uGSZK0jqTVYZRwqaTVgHMJ\nvZ33CGHUPYFLgaUkbVMO3YvQ8HmlHP9wOT6rRJNkItDtRA6LGOGbwIZED67XiUTC4ZJuBQT8wPaz\n5ZCNgH2IaovDbD8No9zZGXtPkuT/27ufECurMI7j38dIy03kQjAEXYS1ihQEIfqDO5caCSWVi0Z3\nktAmymCgVVG0aSVCYKTRImiRuwoCISgosVwJUSTMRltEYlC/FudcuQxDhDBzh3u+n9XMvXde7mwO\nv/d5z3meqtpPuym6VVXPJ7lWVYeAc8DpJCf755aAfbTZf28Bx/rBiiXg9clhiQkrPdLqmPs9P73S\n82iSC1V1d++5cw+tGeH7Sc72kvSLwKEkX/a/2wPsSnK+qjZNemn4zF3SRK/MLNJukt5M8llVbUzy\nV3//Aq0R4ULfR7iTNpj0SJLvq2ozsCPJlcn1XF+k1TfCI5sngA+qamcPPhuBE7SNzUeqDSV9mzar\na1dVPVxVi7T9PxsApoLPSk0PJY3rflp/r6d68NkA/NNDDbTqzj5gL0CSn2nT1tN//3Mq+Li+SGtk\n7sNPko9pXZgXquoo8DWwndak8CbwbJLfaNPYHwLepW1qfizJR8uu5QBSSdNuALuBo1X1NG39OANc\nqqrDvZL8BfBhVS1W1WVaX5+fll/I9UVaO3P/2Augqh6hTUe+CpxI8l1//TBtMvLi1AbDLUmu95/v\nckGS9F966HmD1q/nPK0L8w5atec48Dtt5M1p4NN+mkvSDA0RfgD6vp6tSZ5b1nvjc+Ai8E6Sm/01\nW8ZL+t+qals/THHv1DryA3AsyTf9UfrjwIEkt2xUKM3WSOHnPtrjr1eTfDJZfKrqgSTXZv39JM2P\nqnoNeBJ4Kckv/YbqR+CFJN/O9ttJGib8AFTVy8ACsD/J0rL3vBOTdEf6RucHgYPAM7R+YaeS/DrV\n2fl2VUjSbA3V5yfJe1W1lxX+b4OPpDvVq8h/AFuAV5J8Bbdvqv7unzH4SOvEUJUfSVoL7huU1re5\nP+q+EkdSSFotk0aFBh9p/bLyI0mShmIFRJIkDcXwI0mShmL4kSRJQzH8SJKkoRh+JEnSUAw/kiRp\nKIYfSZI0FMOPJEkaiuFHkiQN5V8ydAwOfEnqFgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ec4d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1=df[df['Standard Major Group']=='Community and Personal Service Workers'].groupby(['Standard Submajor Group', pd.Grouper(freq='A')]).sum()\n",
    "stackedWorkVisasDatePlot('Community Work Visas Granted', df1, 'comm-work-visas-granted.png', left_adjust=0, bottom_adjust=0.4)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IHMTN6X0K+FBVP/HKbBORROBpb+WGcrjPk5aqW1kBYB0umH1BRMYANYFHgFmq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\nuJtgipD1rymNLMg1JrTvgTgRuRAX5K7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HA3sDrwCnA3dJWsX2J6Xbr4GtgZ2AUcCFwPXA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\niIiI6HES5EZEREREj5MgNyIiIiJ6nP8H/Avi/iRfiO0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf55e048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1=df[df['Standard Major Group']=='Managers'].groupby(['Standard Submajor Group', pd.Grouper(freq='A')]).sum()\n",
    "stackedWorkVisasDatePlot('Manager Work Visas Granted', df1, 'mgr-work-visas-granted.png', left_adjust=0, bottom_adjust=0.4)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OWJ+0nsCykLSVQMHzgPtxw1WPS0tLKxXvq+Tk5MB3Tp06dWjWrBnDhw/3OceC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X+TS2H5bCIrdLJD5ZZyjlb8rSRJX1BYZnyHaDq50faXau/FrsCttuc5NMcOJnwdxxI1QWNK/eEK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\nkvQ0GQwlSZIkSdLT/D/MJKbzwSMIxwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf35fac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1=df[df['Standard Major Group']=='Labourers'].groupby(['Standard Submajor Group', pd.Grouper(freq='A')]).sum()\n",
    "stackedWorkVisasDatePlot('Labourers Work Visas Granted', df1, 'lab-work-visas-granted.png', left_adjust=0, bottom_adjust=0.4)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-07-31</th>\n",
       "      <td>12220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-08-31</th>\n",
       "      <td>14144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-09-30</th>\n",
       "      <td>13377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-31</th>\n",
       "      <td>12903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-11-30</th>\n",
       "      <td>12936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>10238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-31</th>\n",
       "      <td>12577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-02-28</th>\n",
       "      <td>11619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-03-31</th>\n",
       "      <td>15256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-04-30</th>\n",
       "      <td>13663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-05-31</th>\n",
       "      <td>16027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-06-30</th>\n",
       "      <td>13954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-07-31</th>\n",
       "      <td>14878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-08-31</th>\n",
       "      <td>14795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-09-30</th>\n",
       "      <td>13818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-10-31</th>\n",
       "      <td>16074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-11-30</th>\n",
       "      <td>14588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>12833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-31</th>\n",
       "      <td>14701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-02-29</th>\n",
       "      <td>15219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-03-31</th>\n",
       "      <td>15638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-30</th>\n",
       "      <td>16946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-05-31</th>\n",
       "      <td>15903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-06-30</th>\n",
       "      <td>14178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-31</th>\n",
       "      <td>15251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-08-31</th>\n",
       "      <td>13307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-30</th>\n",
       "      <td>13787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-31</th>\n",
       "      <td>15734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-11-30</th>\n",
       "      <td>14518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>12939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-30</th>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>11446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-31</th>\n",
       "      <td>14888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28</th>\n",
       "      <td>14643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31</th>\n",
       "      <td>18238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-30</th>\n",
       "      <td>15448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-31</th>\n",
       "      <td>15908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-30</th>\n",
       "      <td>15819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07-31</th>\n",
       "      <td>17218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-31</th>\n",
       "      <td>17060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-30</th>\n",
       "      <td>18267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-31</th>\n",
       "      <td>20115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-30</th>\n",
       "      <td>16318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>12539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-31</th>\n",
       "      <td>15701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-29</th>\n",
       "      <td>17095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-31</th>\n",
       "      <td>20169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-30</th>\n",
       "      <td>18239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-31</th>\n",
       "      <td>18626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-30</th>\n",
       "      <td>18222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07-31</th>\n",
       "      <td>17885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-31</th>\n",
       "      <td>20918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-30</th>\n",
       "      <td>21308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-31</th>\n",
       "      <td>20072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-30</th>\n",
       "      <td>19106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>13104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-31</th>\n",
       "      <td>16901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-28</th>\n",
       "      <td>18523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31</th>\n",
       "      <td>23457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-30</th>\n",
       "      <td>14908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Number of Applications\n",
       "Month Decided                        \n",
       "2006-07-31                      12220\n",
       "2006-08-31                      14144\n",
       "2006-09-30                      13377\n",
       "2006-10-31                      12903\n",
       "2006-11-30                      12936\n",
       "2006-12-31                      10238\n",
       "2007-01-31                      12577\n",
       "2007-02-28                      11619\n",
       "2007-03-31                      15256\n",
       "2007-04-30                      13663\n",
       "2007-05-31                      16027\n",
       "2007-06-30                      13954\n",
       "2007-07-31                      14878\n",
       "2007-08-31                      14795\n",
       "2007-09-30                      13818\n",
       "2007-10-31                      16074\n",
       "2007-11-30                      14588\n",
       "2007-12-31                      12833\n",
       "2008-01-31                      14701\n",
       "2008-02-29                      15219\n",
       "2008-03-31                      15638\n",
       "2008-04-30                      16946\n",
       "2008-05-31                      15903\n",
       "2008-06-30                      14178\n",
       "2008-07-31                      15251\n",
       "2008-08-31                      13307\n",
       "2008-09-30                      13787\n",
       "2008-10-31                      15734\n",
       "2008-11-30                      14518\n",
       "2008-12-31                      12939\n",
       "...                               ...\n",
       "2014-11-30                      14721\n",
       "2014-12-31                      11446\n",
       "2015-01-31                      14888\n",
       "2015-02-28                      14643\n",
       "2015-03-31                      18238\n",
       "2015-04-30                      15448\n",
       "2015-05-31                      15908\n",
       "2015-06-30                      15819\n",
       "2015-07-31                      17218\n",
       "2015-08-31                      17060\n",
       "2015-09-30                      18267\n",
       "2015-10-31                      20115\n",
       "2015-11-30                      16318\n",
       "2015-12-31                      12539\n",
       "2016-01-31                      15701\n",
       "2016-02-29                      17095\n",
       "2016-03-31                      20169\n",
       "2016-04-30                      18239\n",
       "2016-05-31                      18626\n",
       "2016-06-30                      18222\n",
       "2016-07-31                      17885\n",
       "2016-08-31                      20918\n",
       "2016-09-30                      21308\n",
       "2016-10-31                      20072\n",
       "2016-11-30                      19106\n",
       "2016-12-31                      13104\n",
       "2017-01-31                      16901\n",
       "2017-02-28                      18523\n",
       "2017-03-31                      23457\n",
       "2017-04-30                      14908\n",
       "\n",
       "[130 rows x 1 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df.groupby([pd.Grouper(freq='M')]).sum()\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x12d0a2e8>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wOO9NwEvBZ9Y90q+foHE0W9GUzmHB/r6Z5bO5MWiX7vXeSPveaAntd9Cn/L8Cx6TZ98mo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\nFoZhGIZhpIYJC8MwDMMwUuP/A4sLqsWWazj3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12dcb748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.plot()\n",
    "fig = plt.gcf()\n",
    "ax=plt.gca()\n",
    "ax.legend().remove()\n",
    "fig.autofmt_xdate()\n",
    "plt.title(\"Work Visas Granted 2007-2017\")\n",
    "plt.xlabel(\"Period Granted\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x133e93c8>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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z2WY2wMwapcpsYmYjzexHM5tmZjebmZIlERGpt5Yu9dEgxxwDjRvX/P6rMo9F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\nCIIgCCpGGBZBEARBEFSM/wdB8sHGL4RG6gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x137eaf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = df1.rolling(window=12)\n",
    "r.mean().plot()\n",
    "fig = plt.gcf()\n",
    "ax=plt.gca()\n",
    "ax.legend().remove()\n",
    "fig.autofmt_xdate()\n",
    "plt.title(\"12 Month Moving Average of Work Visas 2007-2017\")\n",
    "plt.xlabel('Period Granted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Teaching Professionals</th>\n",
       "      <td>2607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Professionals</th>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life Science and Health Professionals</th>\n",
       "      <td>4798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Legal, Social and Welfare Professionals</th>\n",
       "      <td>5743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physical, Mathematical and Engineering Science Professionals</th>\n",
       "      <td>5827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education Professionals</th>\n",
       "      <td>12800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business, Human Resource and Marketing Professionals</th>\n",
       "      <td>14951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health Professionals</th>\n",
       "      <td>25818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICT Professionals</th>\n",
       "      <td>26423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Design, Engineering, Science and Transport Professionals</th>\n",
       "      <td>28263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arts and Media Professionals</th>\n",
       "      <td>30311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Number of Applications\n",
       "Standard Submajor Group                                                   \n",
       "Teaching Professionals                                                2607\n",
       "Other Professionals                                                   3382\n",
       "Life Science and Health Professionals                                 4798\n",
       "Legal, Social and Welfare Professionals                               5743\n",
       "Physical, Mathematical and Engineering Science ...                    5827\n",
       "Education Professionals                                              12800\n",
       "Business, Human Resource and Marketing Professi...                   14951\n",
       "Health Professionals                                                 25818\n",
       "ICT Professionals                                                    26423\n",
       "Design, Engineering, Science and Transport Prof...                   28263\n",
       "Arts and Media Professionals                                         30311"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Standard Major Group']=='Professionals'].groupby('Standard Submajor Group').sum().sort_values('Number of Applications')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Minor Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Database and Systems Administrators, and ICT Security Specialists</th>\n",
       "      <td>1525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICT Network and Support Professionals</th>\n",
       "      <td>5714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business and Systems Analysts, and Programmers</th>\n",
       "      <td>19184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Number of Applications\n",
       "Standard Minor Group                                                      \n",
       "Database and Systems Administrators, and ICT Se...                    1525\n",
       "ICT Network and Support Professionals                                 5714\n",
       "Business and Systems Analysts, and Programmers                       19184"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Standard Submajor Group']=='ICT Professionals'].groupby('Standard Minor Group').sum().sort_values('Number of Applications')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Unit Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Multimedia Specialists and Web Developers</th>\n",
       "      <td>3875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICT Business and Systems Analysts</th>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Software and Applications Programmers</th>\n",
       "      <td>11341</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Number of Applications\n",
       "Standard Unit Group                                              \n",
       "Multimedia Specialists and Web Developers                    3875\n",
       "ICT Business and Systems Analysts                            3968\n",
       "Software and Applications Programmers                       11341"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Standard Minor Group']=='Business and Systems Analysts, and Programmers'].groupby('Standard Unit Group').sum().sort_values('Number of Applications')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Precision Trades Workers</th>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Craft and Related Trades Workers</th>\n",
       "      <td>1322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Building Trades Workers</th>\n",
       "      <td>3566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metal and Machinery Trades Workers</th>\n",
       "      <td>3645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Number of Applications\n",
       "Standard Submajor Group                                       \n",
       "Precision Trades Workers                                   356\n",
       "Other Craft and Related Trades Workers                    1322\n",
       "Building Trades Workers                                   3566\n",
       "Metal and Machinery Trades Workers                        3645"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Standard Major Group']=='Trades Workers'].groupby('Standard Submajor Group').sum().sort_values('Number of Applications')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Skilled Animal and Horticultural Workers</th>\n",
       "      <td>3269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electrotechnology and Telecommunications Trades Workers</th>\n",
       "      <td>7322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Technicians and Trades Workers</th>\n",
       "      <td>12397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engineering, ICT and Science Technicians</th>\n",
       "      <td>15802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Automotive and Engineering Trades Workers</th>\n",
       "      <td>17179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Construction Trades Workers</th>\n",
       "      <td>17905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Food Trades Workers</th>\n",
       "      <td>41901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Number of Applications\n",
       "Standard Submajor Group                                                   \n",
       "Skilled Animal and Horticultural Workers                              3269\n",
       "Electrotechnology and Telecommunications Trades...                    7322\n",
       "Other Technicians and Trades Workers                                 12397\n",
       "Engineering, ICT and Science Technicians                             15802\n",
       "Automotive and Engineering Trades Workers                            17179\n",
       "Construction Trades Workers                                          17905\n",
       "Food Trades Workers                                                  41901"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Standard Major Group']=='Technicians and Trades Workers'].groupby('Standard Submajor Group').sum().sort_values('Number of Applications')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "not_recorded = df[df['Standard Major Group'] == '(not recorded)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "      <th>Application Category</th>\n",
       "      <th>Application Type</th>\n",
       "      <th>Application Criteria</th>\n",
       "      <th>Application Stream</th>\n",
       "      <th>Application Substream</th>\n",
       "      <th>Branch Location</th>\n",
       "      <th>Decision Type</th>\n",
       "      <th>Job Offer?</th>\n",
       "      <th>Applicant Type</th>\n",
       "      <th>...</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Financial Year Decided</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Occupation Standard</th>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th>Standard Minor Group</th>\n",
       "      <th>Standard Unit Group</th>\n",
       "      <th>Region</th>\n",
       "      <th>Period</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-05-01</th>\n",
       "      <td>1</td>\n",
       "      <td>Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Work experience for student</td>\n",
       "      <td>Work</td>\n",
       "      <td>Other</td>\n",
       "      <td>Onshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Male</td>\n",
       "      <td>2010/11</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-01</th>\n",
       "      <td>1</td>\n",
       "      <td>Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Work experience for student</td>\n",
       "      <td>Work</td>\n",
       "      <td>Other</td>\n",
       "      <td>Onshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Female</td>\n",
       "      <td>2011/12</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-10-01</th>\n",
       "      <td>1</td>\n",
       "      <td>Visa</td>\n",
       "      <td>Work</td>\n",
       "      <td>Work experience for student</td>\n",
       "      <td>Work</td>\n",
       "      <td>Other</td>\n",
       "      <td>Onshore</td>\n",
       "      <td>Approved</td>\n",
       "      <td>No Job Offer</td>\n",
       "      <td>Principal Applicant/ Application</td>\n",
       "      <td>...</td>\n",
       "      <td>Male</td>\n",
       "      <td>2014/15</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(not recorded)</td>\n",
       "      <td>(unknown)</td>\n",
       "      <td>01JUL2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Number of Applications Application Category Application Type  \\\n",
       "Month Decided                                                                 \n",
       "2011-05-01                          1                 Visa             Work   \n",
       "2011-12-01                          1                 Visa             Work   \n",
       "2014-10-01                          1                 Visa             Work   \n",
       "\n",
       "                      Application Criteria Application Stream  \\\n",
       "Month Decided                                                   \n",
       "2011-05-01     Work experience for student               Work   \n",
       "2011-12-01     Work experience for student               Work   \n",
       "2014-10-01     Work experience for student               Work   \n",
       "\n",
       "              Application Substream Branch Location Decision Type  \\\n",
       "Month Decided                                                       \n",
       "2011-05-01                    Other         Onshore      Approved   \n",
       "2011-12-01                    Other         Onshore      Approved   \n",
       "2014-10-01                    Other         Onshore      Approved   \n",
       "\n",
       "                 Job Offer?                    Applicant Type    ...      \\\n",
       "Month Decided                                                    ...       \n",
       "2011-05-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "2011-12-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "2014-10-01     No Job Offer  Principal Applicant/ Application    ...       \n",
       "\n",
       "               Gender Financial Year Decided      Occupation  \\\n",
       "Month Decided                                                  \n",
       "2011-05-01       Male                2010/11  (not recorded)   \n",
       "2011-12-01     Female                2011/12  (not recorded)   \n",
       "2014-10-01       Male                2014/15  (not recorded)   \n",
       "\n",
       "              Occupation Standard Standard Major Group  \\\n",
       "Month Decided                                            \n",
       "2011-05-01                    NaN       (not recorded)   \n",
       "2011-12-01                    NaN       (not recorded)   \n",
       "2014-10-01                    NaN       (not recorded)   \n",
       "\n",
       "              Standard Submajor Group Standard Minor Group  \\\n",
       "Month Decided                                                \n",
       "2011-05-01             (not recorded)       (not recorded)   \n",
       "2011-12-01             (not recorded)       (not recorded)   \n",
       "2014-10-01             (not recorded)       (not recorded)   \n",
       "\n",
       "              Standard Unit Group     Region     Period  \n",
       "Month Decided                                            \n",
       "2011-05-01         (not recorded)  (unknown)  01JUL2010  \n",
       "2011-12-01         (not recorded)  (unknown)  01JUL2010  \n",
       "2014-10-01         (not recorded)  (unknown)  01JUL2010  \n",
       "\n",
       "[3 rows x 22 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_recorded.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Application Criteria</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Partnership</th>\n",
       "      <td>165363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partner of a worker</th>\n",
       "      <td>156119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Graduate Job Search</th>\n",
       "      <td>121425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Kingdom Working Holiday Scheme</th>\n",
       "      <td>116095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany Working Holiday Scheme</th>\n",
       "      <td>104843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Recognised Seasonal Employer</th>\n",
       "      <td>80086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France Working Holiday Scheme</th>\n",
       "      <td>55597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States Working Holiday Scheme</th>\n",
       "      <td>33271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Section 61</th>\n",
       "      <td>31713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Specific Purpose or event</th>\n",
       "      <td>24209</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Number of Applications\n",
       "Application Criteria                                         \n",
       "Partnership                                            165363\n",
       "Partner of a worker                                    156119\n",
       "Graduate Job Search                                    121425\n",
       "United Kingdom Working Holiday Scheme                  116095\n",
       "Germany Working Holiday Scheme                         104843\n",
       "Recognised Seasonal Employer                            80086\n",
       "France Working Holiday Scheme                           55597\n",
       "United States Working Holiday Scheme                    33271\n",
       "Section 61                                              31713\n",
       "Specific Purpose or event                               24209"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=not_recorded.groupby('Application Criteria').sum().sort_values('Number of Applications', ascending=False)\n",
    "df2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Partnership',\n",
       " 'Partner of a worker',\n",
       " 'Graduate Job Search',\n",
       " 'United Kingdom Working Holiday Scheme',\n",
       " 'Germany Working Holiday Scheme',\n",
       " 'Recognised Seasonal Employer',\n",
       " 'France Working Holiday Scheme',\n",
       " 'United States Working Holiday Scheme',\n",
       " 'Section 61',\n",
       " 'Specific Purpose or event']"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "major_cols=df2.index.tolist()[0:10]\n",
    "major_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Application Criteria</th>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">France Working Holiday Scheme</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>3325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>4303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>5662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>8215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>9167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>10182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>2929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Germany Working Holiday Scheme</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>6561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>7199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>7139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>8437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>11715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>12968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>15538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>2952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Graduate Job Search</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>3695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>9246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>10893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>11202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>11952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>9324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>7761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>8096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>12859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>19356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>7833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Partner of a worker</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>5742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>14266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>16643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>15542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>13835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>11663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>11891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>12437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>15425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>18302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>6428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Partnership</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>8193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>16627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>16187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>18256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>18000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>14269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>13802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>13067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>14425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>4181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"11\" valign=\"top\">Recognised Seasonal Employer</th>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>5935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>7543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>7107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>7883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>7908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>8567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>8913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>9582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>10464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>5434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Section 61</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>4042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>4071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>2610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>2665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>2492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>2298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Specific Purpose or event</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>1159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>3452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>3635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>3711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>2758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">United Kingdom Working Holiday Scheme</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>9244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>9830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>10350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>9677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>9776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>10672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>11632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>12670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>13858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>4576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">United States Working Holiday Scheme</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>1034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>2276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>2629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>2604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>2656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>2968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>3566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>3900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>4898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>1647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     Number of Applications\n",
       "Application Criteria                  Month Decided                        \n",
       "France Working Holiday Scheme         2006-12-31                        637\n",
       "                                      2007-12-31                       1632\n",
       "                                      2008-12-31                       2221\n",
       "                                      2009-12-31                       3329\n",
       "                                      2010-12-31                       3325\n",
       "                                      2011-12-31                       3995\n",
       "                                      2012-12-31                       4303\n",
       "                                      2013-12-31                       5662\n",
       "                                      2014-12-31                       8215\n",
       "                                      2015-12-31                       9167\n",
       "                                      2016-12-31                      10182\n",
       "                                      2017-12-31                       2929\n",
       "Germany Working Holiday Scheme        2006-12-31                       2860\n",
       "                                      2007-12-31                       5677\n",
       "                                      2008-12-31                       6561\n",
       "                                      2009-12-31                       7199\n",
       "                                      2010-12-31                       7139\n",
       "                                      2011-12-31                       8437\n",
       "                                      2012-12-31                       9077\n",
       "                                      2013-12-31                      11715\n",
       "                                      2014-12-31                      12968\n",
       "                                      2015-12-31                      14720\n",
       "                                      2016-12-31                      15538\n",
       "                                      2017-12-31                       2952\n",
       "Graduate Job Search                   2006-12-31                       3695\n",
       "                                      2007-12-31                       9246\n",
       "                                      2008-12-31                      10893\n",
       "                                      2009-12-31                      11202\n",
       "                                      2010-12-31                      11952\n",
       "                                      2011-12-31                       9324\n",
       "                                      2012-12-31                       9208\n",
       "                                      2013-12-31                       7761\n",
       "                                      2014-12-31                       8096\n",
       "                                      2015-12-31                      12859\n",
       "                                      2016-12-31                      19356\n",
       "                                      2017-12-31                       7833\n",
       "Partner of a worker                   2006-12-31                       5742\n",
       "                                      2007-12-31                      14266\n",
       "                                      2008-12-31                      16643\n",
       "                                      2009-12-31                      15542\n",
       "                                      2010-12-31                      13835\n",
       "                                      2011-12-31                      11663\n",
       "                                      2012-12-31                      11891\n",
       "                                      2013-12-31                      12437\n",
       "                                      2014-12-31                      13945\n",
       "                                      2015-12-31                      15425\n",
       "                                      2016-12-31                      18302\n",
       "                                      2017-12-31                       6428\n",
       "Partnership                           2006-12-31                       8193\n",
       "                                      2007-12-31                      16627\n",
       "                                      2008-12-31                      16187\n",
       "                                      2009-12-31                      18256\n",
       "                                      2010-12-31                      18000\n",
       "                                      2011-12-31                      14269\n",
       "                                      2012-12-31                      13802\n",
       "                                      2013-12-31                      13067\n",
       "                                      2014-12-31                      13740\n",
       "                                      2015-12-31                      14616\n",
       "                                      2016-12-31                      14425\n",
       "                                      2017-12-31                       4181\n",
       "Recognised Seasonal Employer          2007-12-31                        750\n",
       "                                      2008-12-31                       5935\n",
       "                                      2009-12-31                       7543\n",
       "                                      2010-12-31                       7107\n",
       "                                      2011-12-31                       7883\n",
       "                                      2012-12-31                       7908\n",
       "                                      2013-12-31                       8567\n",
       "                                      2014-12-31                       8913\n",
       "                                      2015-12-31                       9582\n",
       "                                      2016-12-31                      10464\n",
       "                                      2017-12-31                       5434\n",
       "Section 61                            2006-12-31                       2524\n",
       "                                      2007-12-31                       4042\n",
       "                                      2008-12-31                       4071\n",
       "                                      2009-12-31                       3086\n",
       "                                      2010-12-31                       2610\n",
       "                                      2011-12-31                       3118\n",
       "                                      2012-12-31                       2665\n",
       "                                      2013-12-31                       2492\n",
       "                                      2014-12-31                       2298\n",
       "                                      2015-12-31                       2154\n",
       "                                      2016-12-31                       2068\n",
       "                                      2017-12-31                        585\n",
       "Specific Purpose or event             2006-12-31                       1159\n",
       "                                      2007-12-31                       3452\n",
       "                                      2008-12-31                       3635\n",
       "                                      2009-12-31                       3083\n",
       "                                      2010-12-31                       3711\n",
       "                                      2011-12-31                       3274\n",
       "                                      2012-12-31                       2758\n",
       "                                      2013-12-31                        926\n",
       "                                      2014-12-31                        601\n",
       "                                      2015-12-31                        701\n",
       "                                      2016-12-31                        699\n",
       "                                      2017-12-31                        210\n",
       "United Kingdom Working Holiday Scheme 2006-12-31                       4388\n",
       "                                      2007-12-31                       9244\n",
       "                                      2008-12-31                       9830\n",
       "                                      2009-12-31                      10350\n",
       "                                      2010-12-31                       9677\n",
       "                                      2011-12-31                       9776\n",
       "                                      2012-12-31                       9422\n",
       "                                      2013-12-31                      10672\n",
       "                                      2014-12-31                      11632\n",
       "                                      2015-12-31                      12670\n",
       "                                      2016-12-31                      13858\n",
       "                                      2017-12-31                       4576\n",
       "United States Working Holiday Scheme  2006-12-31                       1034\n",
       "                                      2007-12-31                       2276\n",
       "                                      2008-12-31                       2321\n",
       "                                      2009-12-31                       2772\n",
       "                                      2010-12-31                       2629\n",
       "                                      2011-12-31                       2604\n",
       "                                      2012-12-31                       2656\n",
       "                                      2013-12-31                       2968\n",
       "                                      2014-12-31                       3566\n",
       "                                      2015-12-31                       3900\n",
       "                                      2016-12-31                       4898\n",
       "                                      2017-12-31                       1647"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_recorded[not_recorded['Application Criteria'].isin(major_cols)].groupby(['Application Criteria',pd.Grouper(freq='A')]).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Submajor Group</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(not recorded)</th>\n",
       "      <td>1272511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Number of Applications\n",
       "Standard Submajor Group                        \n",
       "(not recorded)                          1272511"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_recorded.groupby('Standard Submajor Group').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Standard Major Group</th>\n",
       "      <th>Month Decided</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">(not recorded)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>49490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>111029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>119645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>118173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>113575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>105249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>104334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>107509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>116680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>130661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>147405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>48761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Agriculture and Fishery Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>1807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Clerical and Administrative Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Clerks</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Community and Personal Service Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>8599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>9403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>8264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>8041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>8332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>9730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>10779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>12346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>3747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Elementary Occupations (incl Residuals)</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Labourers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>5476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>3999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>3380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>4028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>5445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>7102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>2937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Legislators, Administrators and Managers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Machinery Operators and Drivers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>10400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>14668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>15634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>15121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>13694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>13623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>16249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>17158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>16106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>6155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Response Outside Scope/Not Stated</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Responses outside of the current definition of the labour force</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>1218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>1162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">Sales Workers</th>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>1565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Service and Sales Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>6042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>14033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>2280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Technicians and Associate Professionals</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>4668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>9588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"11\" valign=\"top\">Technicians and Trades Workers</th>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>11098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>11804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>10792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>9238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>9734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>11721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>5886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Trades Workers</th>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>2613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>5434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                  Number of Applications\n",
       "Standard Major Group                               Month Decided                        \n",
       "(not recorded)                                     2006-12-31                      49490\n",
       "                                                   2007-12-31                     111029\n",
       "                                                   2008-12-31                     119645\n",
       "                                                   2009-12-31                     118173\n",
       "                                                   2010-12-31                     113575\n",
       "                                                   2011-12-31                     105249\n",
       "                                                   2012-12-31                     104334\n",
       "                                                   2013-12-31                     107509\n",
       "                                                   2014-12-31                     116680\n",
       "                                                   2015-12-31                     130661\n",
       "                                                   2016-12-31                     147405\n",
       "                                                   2017-12-31                      48761\n",
       "Agriculture and Fishery Workers                    2006-12-31                       1807\n",
       "                                                   2007-12-31                       5742\n",
       "                                                   2008-12-31                        949\n",
       "Clerical and Administrative Workers                2008-12-31                       2037\n",
       "                                                   2009-12-31                       2152\n",
       "                                                   2010-12-31                       1905\n",
       "                                                   2011-12-31                       1687\n",
       "                                                   2012-12-31                       1588\n",
       "                                                   2013-12-31                       1698\n",
       "                                                   2014-12-31                       1874\n",
       "                                                   2015-12-31                       2190\n",
       "                                                   2016-12-31                       2567\n",
       "                                                   2017-12-31                        983\n",
       "Clerks                                             2006-12-31                        840\n",
       "                                                   2007-12-31                       1863\n",
       "                                                   2008-12-31                        260\n",
       "Community and Personal Service Workers             2008-12-31                       8599\n",
       "                                                   2009-12-31                       8849\n",
       "                                                   2010-12-31                       9403\n",
       "                                                   2011-12-31                       8264\n",
       "                                                   2012-12-31                       8041\n",
       "                                                   2013-12-31                       8332\n",
       "                                                   2014-12-31                       9730\n",
       "                                                   2015-12-31                      10779\n",
       "                                                   2016-12-31                      12346\n",
       "                                                   2017-12-31                       3747\n",
       "Elementary Occupations (incl Residuals)            2006-12-31                        793\n",
       "                                                   2007-12-31                       1816\n",
       "                                                   2008-12-31                        268\n",
       "Labourers                                          2008-12-31                       5476\n",
       "                                                   2009-12-31                       4555\n",
       "                                                   2010-12-31                       3999\n",
       "                                                   2011-12-31                       3573\n",
       "                                                   2012-12-31                       3380\n",
       "                                                   2013-12-31                       4028\n",
       "                                                   2014-12-31                       5445\n",
       "                                                   2015-12-31                       6155\n",
       "                                                   2016-12-31                       7102\n",
       "                                                   2017-12-31                       2937\n",
       "Legislators, Administrators and Managers           2006-12-31                       2710\n",
       "                                                   2007-12-31                       5754\n",
       "                                                   2008-12-31                        794\n",
       "                                                   2009-12-31                          2\n",
       "                                                   2010-12-31                          1\n",
       "Machinery Operators and Drivers                    2008-12-31                       1876\n",
       "                                                   2009-12-31                       1532\n",
       "                                                   2010-12-31                       1502\n",
       "                                                   2011-12-31                       1366\n",
       "...                                                                                  ...\n",
       "Professionals                                      2006-12-31                       4690\n",
       "                                                   2007-12-31                      10400\n",
       "                                                   2008-12-31                      14668\n",
       "                                                   2009-12-31                      15634\n",
       "                                                   2010-12-31                      15121\n",
       "                                                   2011-12-31                      13694\n",
       "                                                   2012-12-31                      13623\n",
       "                                                   2013-12-31                      16249\n",
       "                                                   2014-12-31                      17158\n",
       "                                                   2015-12-31                      16106\n",
       "                                                   2016-12-31                      17425\n",
       "                                                   2017-12-31                       6155\n",
       "Response Outside Scope/Not Stated                  2006-12-31                        134\n",
       "                                                   2007-12-31                        133\n",
       "                                                   2008-12-31                         11\n",
       "Responses outside of the current definition of ... 2008-12-31                        110\n",
       "                                                   2009-12-31                        255\n",
       "                                                   2010-12-31                        296\n",
       "                                                   2011-12-31                        521\n",
       "                                                   2012-12-31                        820\n",
       "                                                   2013-12-31                       1363\n",
       "                                                   2014-12-31                       1276\n",
       "                                                   2015-12-31                       1218\n",
       "                                                   2016-12-31                       1162\n",
       "                                                   2017-12-31                        510\n",
       "Sales Workers                                      2008-12-31                       1477\n",
       "                                                   2009-12-31                       1702\n",
       "                                                   2010-12-31                       1565\n",
       "                                                   2011-12-31                       1454\n",
       "                                                   2012-12-31                       1696\n",
       "                                                   2013-12-31                       1687\n",
       "                                                   2014-12-31                       1869\n",
       "                                                   2015-12-31                       2367\n",
       "                                                   2016-12-31                       2841\n",
       "                                                   2017-12-31                        981\n",
       "Service and Sales Workers                          2006-12-31                       6042\n",
       "                                                   2007-12-31                      14033\n",
       "                                                   2008-12-31                       2280\n",
       "                                                   2009-12-31                          8\n",
       "                                                   2014-12-31                          1\n",
       "Technicians and Associate Professionals            2006-12-31                       4668\n",
       "                                                   2007-12-31                       9588\n",
       "                                                   2008-12-31                       1591\n",
       "                                                   2009-12-31                        325\n",
       "                                                   2010-12-31                         59\n",
       "Technicians and Trades Workers                     2007-12-31                          1\n",
       "                                                   2008-12-31                      11098\n",
       "                                                   2009-12-31                      11804\n",
       "                                                   2010-12-31                      10792\n",
       "                                                   2011-12-31                       9238\n",
       "                                                   2012-12-31                       9734\n",
       "                                                   2013-12-31                      11721\n",
       "                                                   2014-12-31                      13485\n",
       "                                                   2015-12-31                      14975\n",
       "                                                   2016-12-31                      17041\n",
       "                                                   2017-12-31                       5886\n",
       "Trades Workers                                     2006-12-31                       2613\n",
       "                                                   2007-12-31                       5434\n",
       "                                                   2008-12-31                        839\n",
       "                                                   2009-12-31                          3\n",
       "\n",
       "[140 rows x 1 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df.groupby(['Standard Major Group',pd.Grouper(freq='A')]).sum()\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Number of Applications'], dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex(levels=[[u'(not recorded)', u'Agriculture and Fishery Workers', u'Clerical and Administrative Workers', u'Clerks', u'Community and Personal Service Workers', u'Elementary Occupations (incl Residuals)', u'Labourers', u'Legislators, Administrators and Managers', u'Machinery Operators and Drivers', u'Managers', u'Plant and Machine Operators and Assemblers', u'Professionals', u'Response Outside Scope/Not Stated', u'Responses outside of the current definition of the labour force', u'Sales Workers', u'Service and Sales Workers', u'Technicians and Associate Professionals', u'Technicians and Trades Workers', u'Trades Workers'], [2006-12-31 00:00:00, 2007-12-31 00:00:00, 2008-12-31 00:00:00, 2009-12-31 00:00:00, 2010-12-31 00:00:00, 2011-12-31 00:00:00, 2012-12-31 00:00:00, 2013-12-31 00:00:00, 2014-12-31 00:00:00, 2015-12-31 00:00:00, 2016-12-31 00:00:00, 2017-12-31 00:00:00]],\n",
       "           labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 8, 0, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2, 3]],\n",
       "           names=[u'Standard Major Group', u'Month Decided'])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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