{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Who’s responsible?\n",
    "\n",
    "The National Archives of Australia's RecordSearch database divides government activities up into a [series of functions](harvesting_functions_from_recordsearch.ipynb). Over time, different agencies have been made responsible for these functions, and it can be interesting to track how these responsibilities have shifted.\n",
    "\n",
    "This notebook uses [data about functions](get_all_agencies_by_function.ipynb) harvested from RecordSearch to create a a simple visualisation of the agencies responsible for a selected function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display, HTML\n",
    "import json\n",
    "import altair as alt\n",
    "from altair import datum\n",
    "import pandas as pd\n",
    "\n",
    "alt.renderers.enable('notebook')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.OutputArea.prototype._should_scroll = function(lines) {return false}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "IPython.OutputArea.prototype._should_scroll = function(lines) {return false}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the harvested functions data from a JSON file\n",
    "with open('data/agencies_by_function.json', 'r') as json_file:\n",
    "    data = json.load(json_file)\n",
    "    \n",
    "def get_children(function, level):\n",
    "    '''\n",
    "    Gets the children of the supplied term.\n",
    "    Formats/indents the terms for the dropdown.\n",
    "    '''\n",
    "    f_list = []\n",
    "    if 'narrower' in function:\n",
    "        level += 1\n",
    "        for subf in function['narrower']:\n",
    "            f_list.append(('{}{} {}'.format(level * '  ', level * '-', subf['term']), subf))\n",
    "            f_list += get_children(subf, level=level)\n",
    "    return f_list\n",
    "\n",
    "def get_functions():\n",
    "    # Load the JSON file of functions we've previously harvested\n",
    "    with open('data/functions.json', 'r') as json_file:\n",
    "        functions = json.load(json_file)\n",
    "\n",
    "    # Make the list of options for the dropdown\n",
    "    functions_list = []\n",
    "    for function in functions:\n",
    "        functions_list.append((function['term'], function))\n",
    "        functions_list += get_children(function, level=0)\n",
    "    return functions_list\n",
    "\n",
    "def get_function_agencies(term):\n",
    "    for f in data:\n",
    "        if f['term'] == term:\n",
    "            return f['agencies']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f5ed105781c84eb1b8edc3a2722feb24",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Label(value='Select a function:'), Dropdown(options=(('administrative services', {'term': 'admi…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "46f46593db454c489df827b555c8b498",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output(layout=Layout(width='100%'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_chart(change):\n",
    "    # Clear current output\n",
    "    out.clear_output()\n",
    "    # Get the currently selected term from the dropdown\n",
    "    # term = change['new']\n",
    "    function = term.value\n",
    "    atype = agency_type.value\n",
    "    # Get the agencies responsible for the selected function\n",
    "    agencies = get_function_agencies(function['term'])\n",
    "    if agencies:\n",
    "        # Convert to a dataframe\n",
    "        df = pd.DataFrame(agencies)\n",
    "        # Set some defualts for missing dates\n",
    "        missing = {'agency_status': 'Not recorded', 'function_start_date': '1901-01-01', 'function_end_date': '2018-12-31'}\n",
    "        df = df.fillna(value=missing)\n",
    "        df['url'] = df.apply(lambda x: 'http://www.naa.gov.au/cgi-bin/Search?O=S&Number={}'.format(x['agency_id']), axis=1)\n",
    "        if change['owner'].description == 'Agency type:' and atype != 'All':\n",
    "            df = df.loc[df['agency_status'] == atype]\n",
    "        else:\n",
    "            agency_type.value = 'All'\n",
    "        # Create a Gannt style chart\n",
    "        chart = alt.Chart(df).mark_bar(size=20).encode(\n",
    "            x=alt.X('function_start_date:T', axis=alt.Axis(format='%Y', title='Dates agency was responsible for function'), scale=alt.Scale(nice=True)),\n",
    "            x2='function_end_date:T',\n",
    "            y=alt.Y('title', scale=alt.Scale(rangeStep=30), title='Agency'),\n",
    "            color=alt.Color('agency_status', legend=alt.Legend(title='Agency type')),\n",
    "            tooltip=[\n",
    "                alt.Tooltip('agency_id', title='Identifier'), \n",
    "                alt.Tooltip('title', title='Agency'),\n",
    "                alt.Tooltip('agency_status', title='Type'),\n",
    "                alt.Tooltip('location', title='Location'),\n",
    "                alt.Tooltip('function_start_date', title='From', timeUnit='year'), \n",
    "                alt.Tooltip('function_end_date', title='To', timeUnit='year')],\n",
    "            href='url:N'\n",
    "        ).properties(\n",
    "            width=600\n",
    "        )\n",
    "        with out:\n",
    "            display(HTML('<h3>Agencies responsible for &lsquo;{}&rsquo;</h3>'.format(function['term'])))\n",
    "            display(chart)\n",
    "    else:\n",
    "        with out:\n",
    "            display(HTML('<p>No agencies responsible for &lsquo;{}&rsquo;</p>'.format(function['term'])))\n",
    "\n",
    "# This is where the chart will be displayed\n",
    "out = widgets.Output(layout=widgets.Layout(width='100%'))\n",
    "\n",
    "# Create the dropdown\n",
    "term = widgets.Dropdown(\n",
    "    options=get_functions(),\n",
    "    value=None,\n",
    "    disabled=False,\n",
    ")\n",
    "\n",
    "agency_type = widgets.Dropdown(\n",
    "    options=['All', 'Department of State', 'Head Office', 'Regional or State Office', 'Local Office', 'Intergovernmental agency'],\n",
    "    value='All',\n",
    "    disabled=False,\n",
    "    description='Agency type:'\n",
    ")\n",
    "\n",
    "# Making a selection from the dropdown will automatically run 'make_chart'\n",
    "term.observe(make_chart, names='value')\n",
    "agency_type.observe(make_chart, names='value')\n",
    "\n",
    "display(widgets.HBox([widgets.Label('Select a function:'), term, agency_type]))\n",
    "display(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}