{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example of How to Allocate Written Question Tagging\n",
    "\n",
    "Written Questions are tagged by several indexers in the Parliamentary library on a daily basis, tagging Written Questions tabled the day before. On any given day, each indexer will typically be responsible for tagging all the questions directed at a particular answering body.\n",
    "\n",
    "The following script shows how work can be fairly allocated to particular individuals based on the number of questions sent to each answering body.\n",
    "\n",
    "The allocation also allows particular answering bodies to be allocated to a specific individual, or to be kept away from a particular individual.\n",
    "\n",
    "User input is required in two places:\n",
    "\n",
    "- specifying the day or period questions to be allocated correspond to; (this can be set as a default - eg *yesterday*);\n",
    "- specifying the people available and any requirements on who must or must not tag questions for particular answering bodies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Supporting Code Area ...  NO NEED TO READ THIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Code for loading data in from a URL\n",
    "import requests\n",
    "\n",
    "#Get data from URL\n",
    "def getURL(url,quiet=False):\n",
    "    if not quiet: print(url)\n",
    "    r=requests.get(url)\n",
    "    if not quiet: print(r.status_code)\n",
    "    return r\n",
    "\n",
    "#Should build a proper recursive loader\n",
    "def loader(url,quiet=True):\n",
    "    items=[]\n",
    "    done=False\n",
    "    r=getURL(url,quiet)\n",
    "    while not done:\n",
    "        items=items+r.json()['result']['items']\n",
    "        if 'next' in r.json()['result']:\n",
    "            r=getURL(r.json()['result']['next']+'&_pageSize=500',quiet)\n",
    "        else: done=True\n",
    "    return items"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#A tabluar data analysis package that can make life easier...\n",
    "import pandas as pd\n",
    "\n",
    "#Support for inline charts\n",
    "%matplotlib inline\n",
    "\n",
    "#\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "#Support for prettier chart styling\n",
    "import seaborn as sns\n",
    "\n",
    "#Charts have stylefiles - like HTML has CSS stylesheets\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Utilities for expressing natural time\n",
    "import datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "\n",
    "def today(date=None,iso=False):\n",
    "    if date is None: date=datetime.date.today()\n",
    "    if iso: return date.isoformat()\n",
    "    else: return date\n",
    "\n",
    "def yesterday(date=None,iso=False):\n",
    "    if date is None: date=today()\n",
    "    yesterday = date.today() - relativedelta(days=1)\n",
    "    if iso: return yesterday.isoformat()\n",
    "    return yesterday\n",
    "\n",
    "def tomorrow(date=None,iso=False):\n",
    "    if date is None: date=today()\n",
    "    tomorrow=date.today() + relativedelta(days=1)\n",
    "    if iso: return tomorrow.isoformat()\n",
    "    return tomorrow\n",
    "\n",
    "def last_week(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    start_date = date + relativedelta(days=-date.weekday(), weeks=-1)\n",
    "    end_date = start_date + relativedelta(days=6)\n",
    "    if daterange:\n",
    "        if iso: return start_date.isoformat(),end_date.isoformat()\n",
    "        else: return start_date, end_date\n",
    "\n",
    "def this_week(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    start_date = date + relativedelta(days=-date.weekday())\n",
    "    end_date = start_date + relativedelta(days=6)\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date\n",
    "    \n",
    "def next_week(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    start_date = date + relativedelta(days=-date.weekday(), weeks=1)\n",
    "    end_date = start_date + relativedelta(days=6)\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date\n",
    "\n",
    "def later_this_week(date=None,incl=False,daterange=True,iso=False):\n",
    "    date=today(date)\n",
    "    start_date, end_date = this_week(date)\n",
    "    if not incl: start_date=tomorrow(date)\n",
    "    else: start_date=today(date)\n",
    "    #Really need to check if today is last day of week?\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date\n",
    "        \n",
    "def earlier_this_week(date=None,incl=False,daterange=True,iso=False):\n",
    "    date=today(date)\n",
    "    start_date, end_date = this_week(date)\n",
    "    if not incl: end_date=yesterday(date)\n",
    "    else: end_date=today(date)\n",
    "    #Really need to check if today is first day of week?\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date\n",
    "    \n",
    "def last_month(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    end_date = date.replace(day=1)- relativedelta(days=1)\n",
    "    start_date = end_date.replace(day=1)\n",
    "    if daterange:\n",
    "        if iso: return start_date.isoformat(),end_date.isoformat()\n",
    "        else: return start_date, end_date\n",
    "\n",
    "def next_month(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    end_date = date+ relativedelta(months=2)\n",
    "    end_date=end_date.replace(day=1)- relativedelta(days=1)\n",
    "    start_date = end_date.replace(day=1)\n",
    "    if daterange:\n",
    "        if iso: return start_date.isoformat(),end_date.isoformat()\n",
    "        else: return start_date, end_date\n",
    "\n",
    "def this_month(date=None,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    end_date = next_month(date)[0]- relativedelta(days=1)\n",
    "    start_date = end_date.replace(day=1)\n",
    "    if daterange:\n",
    "        if iso: return start_date.isoformat(),end_date.isoformat()\n",
    "        else: return start_date, end_date\n",
    "\n",
    "def earlier_this_month(date=None,incl=False,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    start_date, end_date = this_month(date)\n",
    "    if not incl: end_date=yesterday(date)\n",
    "    else: end_date=today(date)\n",
    "    #Really need to check if today is first day of month?\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date\n",
    "    \n",
    "def later_this_month(date=None,incl=False,daterange=True,iso=False):\n",
    "    if date is None: date=today()\n",
    "    start_date, end_date = this_month(date)\n",
    "    if not incl: start_date=tomorrow(date)\n",
    "    else: start_date=today(date)\n",
    "    #Really need to check if today is last day of month?\n",
    "    if daterange:\n",
    "        if iso:\n",
    "            return start_date.isoformat(), end_date.isoformat()\n",
    "        else:\n",
    "            return start_date, end_date   \n",
    "\n",
    "#via http://stackoverflow.com/a/2384407/454773\n",
    "MON, TUE, WED, THU, FRI, SAT, SUN = range(7)\n",
    "def day_lastweek(day=MON,date=None,iso=False):\n",
    "    if date is None: date=today()\n",
    "    qday= last_week()[0] + relativedelta(days=day)\n",
    "    if iso: return qday.isoformat()\n",
    "    return qday\n",
    "\n",
    "def day_thisweek(day=MON,date=None,iso=False):\n",
    "    if date is None: date=today()\n",
    "    qday= this_week()[0] + relativedelta(days=day)\n",
    "    if iso: return qday.isoformat()\n",
    "    return qday\n",
    "\n",
    "def day_nextweek(day=MON,date=None,iso=False):\n",
    "    if date is None: date=today()\n",
    "    qday= next_week()[0] + relativedelta(days=day)\n",
    "    if iso: return qday.isoformat()\n",
    "    return qday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "last_week(iso=True):\t('2017-03-20', '2017-03-26')\n",
      "last_week(iso=True)[0]:\t2017-03-20\n",
      "yesterday(iso=True):\t2017-03-26\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Example of using the date functions\n",
    "print('''\n",
    "last_week(iso=True):\\t{}\n",
    "last_week(iso=True)[0]:\\t{}\n",
    "yesterday(iso=True):\\t{}\n",
    "'''.format(last_week(iso=True), last_week(iso=True)[0], yesterday(iso=True)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Identifying the Period You Want to Tag Questions For\n",
    "\n",
    "Department allocation will be based on questions asked on a particular day or since a particular date (and inclusive of that date. (We could also generalise to a period - particular week or month or Parliamentary session.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "PERIOD = last_week(iso=True)[0] #Last week returns the date of the first day (Monday) and last day (Sunday); pick the first\n",
    "#PERIOD = yesterday(iso=True)\n",
    "\n",
    "#If today is Monday, we maybe need a \"last working day\" or \"since last working day\".\n",
    "#One heuristic may be - if today is not Monday, use yesterday, else use last Friday\n",
    "#PERIOD= yesterday(iso=True) if today().strftime('%a')!='Mon' else day_lastweek(day=FRI,iso=True)\n",
    "\n",
    "\n",
    "#If SINCE is True, lookup questions since that date and inclusive of it\n",
    "#If SINCE is False, only lookup questions on that date\n",
    "SINCE=True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate the API URL and Load the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Quick peek at the API\n",
    "\n",
    "#http://lda.data.parliament.uk/commonswrittenquestions.json?_view=Written+Questions&_pageSize=10&_page=0\n",
    "stub='http://lda.data.parliament.uk'.strip('/')\n",
    "\n",
    "if SINCE:\n",
    "    url='{}/{}.json?{}'.format(stub,'commonswrittenquestions','min-dateTabled={}'.format(PERIOD))\n",
    "else:\n",
    "    url='{}/{}.json?dateTabled={}'.format(stub,'commonswrittenquestions',PERIOD)\n",
    "\n",
    "#The API returns a list of written questions on/since the specified date\n",
    "items=loader(url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Count by Answering Body\n",
    "\n",
    "We can now work through the answers and identify the answering body associated with each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def getAnsweringBody(item):\n",
    "    rel=[]\n",
    "    for body in item['AnsweringBody']:\n",
    "        rel.append(body['_value'])\n",
    "    return rel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "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>Answering Body</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Attorney General</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cabinet Office</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HM Treasury</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HM Treasury</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HM Treasury</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HM Treasury</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Department for Communities and Local Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Department for Communities and Local Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Department for Communities and Local Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Department for Communities and Local Government</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Answering Body\n",
       "0                                 Attorney General\n",
       "1                                   Cabinet Office\n",
       "2                                      HM Treasury\n",
       "3                                      HM Treasury\n",
       "4                                      HM Treasury\n",
       "5                                      HM Treasury\n",
       "6  Department for Communities and Local Government\n",
       "7  Department for Communities and Local Government\n",
       "8  Department for Communities and Local Government\n",
       "9  Department for Communities and Local Government"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Structurally in the API data, it may be the case that a question is directed at several Answering Bodies.\n",
    "#We could treat these as multiple separate requests requiring tagging, once for each body:\n",
    "#rels=[rel for s in [getAnsweringBody(q) for q in items] for rel in s]\n",
    "\n",
    "#Or by default we just go with the first named body\n",
    "rels=[rel for s in [getAnsweringBody(q) for q in items] for rel in s]\n",
    "\n",
    "#Also flag where there were multiple bodies?\n",
    "#multibody=[m for m in [getAnsweringBody(q)  for q in items] if len(m)>1]\n",
    "#if multibody: print(\"Some requests appear to be targeted at multiple bodies:\", m)\n",
    "\n",
    "#Display the answering body for the first few questions\n",
    "df=pd.DataFrame(rels)\n",
    "df.columns=['Answering Body']\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to count the number of question referred to each answering body and allocate on that basis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Answering Body</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Ministry of Defence</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Ministry of Justice</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Department of Health</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Department for Education</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Department for Communities and Local Government</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Answering Body  Count\n",
       "18                              Ministry of Defence     25\n",
       "19                              Ministry of Justice     21\n",
       "13                             Department of Health     21\n",
       "6                          Department for Education     19\n",
       "4   Department for Communities and Local Government     15"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfc=df.groupby('Answering Body').size().rename('Count').reset_index().sort_values('Count',ascending=False)\n",
    "dfc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#This is a bit of utility code that helps us count how work is allocated\n",
    "#https://github.com/timdiels/chicken_turtle_util/blob/master/chicken_turtle_util/algorithms.py\n",
    "class _handler(object):\n",
    "    def __init__(self,_name):\n",
    "        self._name = _name\n",
    "        self._items = []\n",
    "        self._itemCounts = []\n",
    "        self._count_sum = 0\n",
    "        \n",
    "    def add(self, item, count):\n",
    "        self._items.append(item)\n",
    "        self._itemCounts.append((item,count))\n",
    "        self._count_sum += count\n",
    "    \n",
    "    @property\n",
    "    def name(self):\n",
    "        return self._name\n",
    "    \n",
    "    @property\n",
    "    def items(self):\n",
    "        return (self._items, self._count_sum)\n",
    "    \n",
    "    @property\n",
    "    def itemCounts(self):\n",
    "        return (self._itemCounts, self._count_sum)\n",
    "    \n",
    "    @property\n",
    "    def count_sum(self):\n",
    "        return self._count_sum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### YOUR TURN...\n",
    "\n",
    "Who's doing the work? Are there any preferences?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#List of names of folk doing the work\n",
    "handlers=['Ann','Brian','Claire','David']\n",
    "\n",
    "#Are there any requirements as to whom particular targeted answering bodies will specifically be allocated to?\n",
    "handlerPrefs={'Ann':['Department of Health','Attorney General'],\n",
    "              'David':['Ministry of Defence']}\n",
    "#We should perhaps also check that there are no collisions in prefs\n",
    "#For example, if two or more people have the same pref, randomly pick who will get it?\n",
    "\n",
    "\n",
    "#Are there any requirements as to which particular targeted answering bodies must not be allocated to a particular person?\n",
    "handlerAvoid={'Brian':['HM Treasury']}\n",
    "##We should probably check that a body is not completely avoided... i.e. at least one person exists to handle it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## From here on in, it's the machine...\n",
    "\n",
    "Allocate heuristically - sort from largest job to lowest; give next job to person with least load overall.\n",
    "\n",
    "If there are only a few questions in total, may want to allocate to a single person?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#This bit of code handles the allocation\n",
    "handlerJobs=[_handler(h) for h in handlers]\n",
    "handled=[]\n",
    "\n",
    "#First of all, allocate according the preferences (actually, we treat these as *required* allocations)\n",
    "for handler_ in handlerJobs: \n",
    "    if handler_.name in handlerPrefs:\n",
    "        for ix,row in dfc[dfc['Answering Body'].isin(handlerPrefs[handler_.name])].iterrows():\n",
    "            #Add a start to an answering body name of the allocation was required\n",
    "            handler_.add(row['Answering Body']+'*',row['Count'])\n",
    "            handled.append(row['Answering Body'])\n",
    "\n",
    "#Allocating the work is an example of a multi-way partition problem.\n",
    "#This sort of problem can be quite hard to solve exactly, but there are heuristics\n",
    "#Eg allocate from largest job to lowest; give next job to person with least load overall\n",
    "for ix,row in dfc[~dfc['Answering Body'].isin(handled)].iterrows():\n",
    "    #Note the 'if not' tweak to the allocation so someone who wants to avoid an answering body actually does so...\n",
    "    handler_ = min(handlerJobs, key=lambda handler_: handler_._count_sum if not (handler_.name in handlerAvoid and row['Answering Body'] in handlerAvoid[handler_.name])  else float('inf')  ) \n",
    "    handler_.add(row['Answering Body'],row['Count'])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ann 56 [('Department of Health*', 21), ('Attorney General*', 1), ('Department for International Trade', 15), ('Department for Transport', 9), ('Foreign and Commonwealth Office', 8), ('Leader of the House', 1), ('Northern Ireland Office', 1)] \n",
      "\n",
      "Brian 56 [('Ministry of Justice', 21), ('Department for Environment, Food and Rural Affairs', 15), ('Department for Business, Energy and Industrial Strategy', 12), ('Women and Equalities', 4), ('Department for International Development', 3), ('Scotland Office', 1)] \n",
      "\n",
      "Claire 55 [('Department for Education', 19), ('Department for Communities and Local Government', 15), ('Home Office', 13), ('Department for Work and Pensions', 5), ('Department for Exiting the European Union', 3)] \n",
      "\n",
      "David 55 [('Ministry of Defence*', 25), ('HM Treasury', 14), ('Department for Culture, Media and Sport', 8), ('Cabinet Office', 5), ('Wales Office', 2), ('Church Commissioners', 1)] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Quick look at the results\n",
    "for h in handlerJobs:\n",
    "    print(h.name, h.itemCounts[1],h.itemCounts[0],'\\n')                   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----\n",
      "Ann needs to answer 56 questions:\n",
      "\t- 21 for the Department of Health*\n",
      "\t- 1 for the Attorney General*\n",
      "\t- 15 for the Department for International Trade\n",
      "\t- 9 for the Department for Transport\n",
      "\t- 8 for the Foreign and Commonwealth Office\n",
      "\t- 1 for the Leader of the House\n",
      "\t- 1 for the Northern Ireland Office\n",
      "----\n",
      "Brian needs to answer 56 questions:\n",
      "\t- 21 for the Ministry of Justice\n",
      "\t- 15 for the Department for Environment, Food and Rural Affairs\n",
      "\t- 12 for the Department for Business, Energy and Industrial Strategy\n",
      "\t- 4 for the Women and Equalities\n",
      "\t- 3 for the Department for International Development\n",
      "\t- 1 for the Scotland Office\n",
      "----\n",
      "Claire needs to answer 55 questions:\n",
      "\t- 19 for the Department for Education\n",
      "\t- 15 for the Department for Communities and Local Government\n",
      "\t- 13 for the Home Office\n",
      "\t- 5 for the Department for Work and Pensions\n",
      "\t- 3 for the Department for Exiting the European Union\n",
      "----\n",
      "David needs to answer 55 questions:\n",
      "\t- 25 for the Ministry of Defence*\n",
      "\t- 14 for the HM Treasury\n",
      "\t- 8 for the Department for Culture, Media and Sport\n",
      "\t- 5 for the Cabinet Office\n",
      "\t- 2 for the Wales Office\n",
      "\t- 1 for the Church Commissioners\n"
     ]
    }
   ],
   "source": [
    "#Or more prettily...\n",
    "for h in handlerJobs:\n",
    "    abtxt=''.join(['\\n\\t- {} for the {}'.format(b[1], b[0]) for b in h.itemCounts[0]])\n",
    "    print('----\\n{} needs to tag {} questions:{}'.format(h.name, h.itemCounts[1],abtxt))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## General Reports\n",
    "\n",
    "A set of general reports. These grab data from the API and then start to display reports off the back of the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Session to date\n",
    "\n",
    "Reports for the current session to date (we could probably automate the disocveru of the session text).\n",
    "\n",
    "We could also do things like:\n",
    "\n",
    "- last calendar month\n",
    "- this month to date\n",
    "- last week\n",
    "- this week to date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "url='{}/{}.json?session={}'.format(stub,'commonswrittenquestions','2016/17')\n",
    "items=loader(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Zs2cDkJeXxwsvvICPjw++vr5lfq1FixbZpAm/fv16evbsed1/nvfs2cOePXtuacwXX3yR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11004b438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rels=[rel for s in [getAnsweringBody(q) for q in items] for rel in s]\n",
    "\n",
    "df=pd.DataFrame(rels)\n",
    "df.columns=['Answering Body']\n",
    "g=df.groupby('Answering Body').size().rename('Count').sort_values(ascending=True).plot(kind='barh', figsize=(20,10));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Last Week\n",
    "\n",
    "Example of report for last week."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://lda.data.parliament.uk/commonswrittenquestions.json?min-dateTabled=2017-03-20&max-dateTabled=2017-03-26\n",
      "200\n",
      "http://lda.data.parliament.uk/commonswrittenquestions.json?max-dateTabled=2017-03-26&_page=1&min-dateTabled=2017-03-20&_pageSize=500\n",
      "200\n"
     ]
    }
   ],
   "source": [
    "PERIOD_START,PERIOD_END=last_week(iso=True)\n",
    "url='{}/{}.json?{}'.format(stub,'commonswrittenquestions','min-dateTabled={}&max-dateTabled={}'.format(PERIOD_START,PERIOD_END))\n",
    "items=loader(url,quiet=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wqu+budOZzWaCgoLsXYZItXOjv3xRCCx2lZGRQXh4OE5OTlgsFsaMGUPz5s1p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\nmTIFgNOnTzN//nzGj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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10bb794a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rels=[rel for s in [getAnsweringBody(q) for q in items] for rel in s]\n",
    "\n",
    "df=pd.DataFrame(rels)\n",
    "df.columns=['Answering Body']\n",
    "g=df.groupby('Answering Body').size().rename('Count').sort_values(ascending=True).plot(kind='barh', figsize=(20,10));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}