{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a309a7d0",
   "metadata": {},
   "source": [
    "# You can't manage what you can't map: City of Melbourne council energy and water\n",
    "\n",
    "The City of Melbourne publishes its own electricity, gas and water bills: a table of rows that name an asset (\"Garden -\n",
    "Treasury\", \"Library - East Melbourne\") with a start date, an end date and an amount. The bills are for the financial year\n",
    "1 July 2013 to 30 June 2014, the newest metered data the council publishes. A third of the assets have no position in the\n",
    "council's asset register, so the table cannot be put on a map as it is.\n",
    "\n",
    "The shapes in `data/geometry/` were made in [Plotlay](https://www.getplotlay.com) for the 60 assets that use 90% of each\n",
    "of electricity, gas and water: council property parcels and 2023 building footprints picked from the council's own open\n",
    "layers, boulevards drawn as lines along the street, and points for sites with no outline. Each shape carries the\n",
    "council's asset name as its key. The bills were spread over their days in Plotlay and kept to the financial year.\n",
    "\n",
    "This notebook reads only the files in `../data` and works out every number it shows. It is a method demonstration for\n",
    "facilities and asset managers with real council data, not a statement about the council's assets today."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7f4dfcb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json, warnings\n",
    "warnings.filterwarnings('ignore', message='No data for colormapping')\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "DATA = '../data'\n",
    "pd.set_option('display.width', 160)\n",
    "INK, RED, ORANGE, MUTED = '#1d4f91', '#cf3b26', '#e07b00', '#5b6573'\n",
    "plt.rcParams.update({'figure.dpi': 110, 'axes.spines.top': False, 'axes.spines.right': False, 'font.size': 10})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86d1df72",
   "metadata": {},
   "source": [
    "## Sources and licence\n",
    "\n",
    "Bills (\"Environmental resources consumed\"), the asset register (\"Assets for environmental reporting\"), the 2023 building\n",
    "footprints, property boundaries and road corridors: City of Melbourne Open Data, licensed under CC BY 4.0. Shapes made in\n",
    "Plotlay from those layers; nothing comes from OpenStreetMap or from aerial imagery. Full credits are in `NOTICE`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dffc259c",
   "metadata": {},
   "source": [
    "## Load\n",
    "\n",
    "`assets.csv` has one row per asset: the register's fields, how its shape was made and its size. `usage_monthly.csv` is\n",
    "Plotlay's linked data export (one row per asset, measure and day, in `usage_daily.csv`) totalled by month. Electricity\n",
    "(kWh), gas (MJ) and water (kL) are kept apart: they are never added together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4ab1ffc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60 assets, 52 shapes, 52 assets with bills on the map\n",
      "measure      unit\n",
      "Electricity  kWh      9698626.0\n",
      "Gas          MJ      19558151.0\n",
      "Water        kL        832872.0\n",
      "Name: amount, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "assets = pd.read_csv(f'{DATA}/assets/assets.csv')\n",
    "usage = pd.read_csv(f'{DATA}/usage/usage_monthly.csv')\n",
    "shapes = gpd.read_file(f'{DATA}/geometry/council_assets.geojson')\n",
    "assert assets.asset_name.is_unique and shapes.key.is_unique\n",
    "assert set(usage.measure) == {'Electricity', 'Gas', 'Water'}\n",
    "assert usage.month.min() == '2013-07' and usage.month.max() == '2014-06'\n",
    "print(len(assets), 'assets,', len(shapes), 'shapes,', usage.asset_name.nunique(), 'assets with bills on the map')\n",
    "print(usage.groupby(['measure', 'unit']).amount.sum().round(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd494f75",
   "metadata": {},
   "source": [
    "## A third had no location\n",
    "\n",
    "The register's position for each of the 60, and how each got its shape in Plotlay. A \"shared stand-in\" is one point the\n",
    "register gives to several network assets at once (Swanston Street, by the Town Hall)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "521d77fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "register_position\n",
      "point              38\n",
      "none               17\n",
      "shared stand-in     4\n",
      "not in register     1\n",
      "Name: count, dtype: int64\n",
      "shape_basis        2023 building footprint  council property parcel  line along the street  no shape  point\n",
      "register_position                                                                                          \n",
      "none                                     2                       10                      3         2      0\n",
      "not in register                          0                        0                      0         1      0\n",
      "point                                   19                       12                      2         1      4\n",
      "shared stand-in                          0                        0                      0         4      0\n",
      "15 assets with no location were placed; 8 stay in the table with no shape:\n",
      "                           asset_name                                                                    shape_note\n",
      "Information - Parking Signage Network                                a network or many small sites: no single place\n",
      "   Parking Meters - Melbourne Network                                a network or many small sites: no single place\n",
      "              Reserve - Buncle Street                             no council parcel by that name near Buncle Street\n",
      " Security Cameras - Melbourne Network                                a network or many small sites: no single place\n",
      "  Street Lighting - Docklands Network                                a network or many small sites: no single place\n",
      "  Street Lighting - Melbourne Network                                a network or many small sites: no single place\n",
      "  Street Reserve - Investigator Drive no street of that name in the council road corridors, street names or parcels\n",
      "       Street Reserve - Miscellaneous                                a network or many small sites: no single place\n"
     ]
    }
   ],
   "source": [
    "print(assets.register_position.value_counts())\n",
    "print(assets.groupby(['register_position', 'shape_basis']).size().unstack(fill_value=0))\n",
    "found = assets[assets.register_position.isin(['none', 'not in register']) & assets.placed]\n",
    "left = assets[~assets.placed]\n",
    "print(f\"{len(found)} assets with no location were placed; {len(left)} stay in the table with no shape:\")\n",
    "print(left[['asset_name', 'shape_note']].to_string(index=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb2a2ad6",
   "metadata": {},
   "source": [
    "## Check the areas\n",
    "\n",
    "Plotlay's `area_m2` against the same shapes measured in GDA2020 MGA zone 55 (EPSG:7855)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1624de21",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "largest difference: 0.083%\n"
     ]
    }
   ],
   "source": [
    "areas = shapes[shapes.geometry.geom_type.str.contains('Polygon')].copy()\n",
    "areas['area_mga'] = areas.to_crs(7855).area\n",
    "print('largest difference:', f\"{(abs(areas.area_m2 - areas.area_mga) / areas.area_mga).max():.3%}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb91ef0f",
   "metadata": {},
   "source": [
    "## The placed assets with no location used almost a third of the water\n",
    "\n",
    "Water for the year, by asset, from the export."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5caf3128",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30.7% of the mapped water\n",
      "asset_name\n",
      "Lease - Fitzroy Gardens Pavilion Cafe    38105.0\n",
      "Park - Birrarung Marr                    33424.0\n",
      "Garden Alexandra                         32168.0\n",
      "Garden - Flagstaff                       31016.0\n",
      "Garden - Treasury                        28688.0\n",
      "Garden - Queen Victoria                  20442.0\n",
      "Name: Water, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "year = usage.groupby(['asset_name', 'measure']).amount.sum().unstack()\n",
    "water = year.Water.dropna()\n",
    "share = water[water.index.isin(found.asset_name)].sum() / water.sum()\n",
    "print(f\"{share:.1%} of the mapped water\")\n",
    "print(water[water.index.isin(found.asset_name)].sort_values(ascending=False).head(6).round(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e001bbc3",
   "metadata": {},
   "source": [
    "## Summer water is park water\n",
    "\n",
    "Water by month for parks, gardens, reserves and boulevards (category Open Space) against buildings. The ratio is checked\n",
    "again with only the parks whose water bills cover every day of the year, so a billing gap cannot make the pattern."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "49d78d8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "category  Building  Open Space\n",
      "month                         \n",
      "2013-07        6.1        17.0\n",
      "2013-08        6.2        21.2\n",
      "2013-09        6.0        23.1\n",
      "2013-10        6.2        28.8\n",
      "2013-11       10.3       100.9\n",
      "2013-12       13.4       124.1\n",
      "2014-01       13.4       127.6\n",
      "2014-02       10.9        74.7\n",
      "2014-03       10.6        76.1\n",
      "2014-04       10.1        72.9\n",
      "2014-05        8.3        38.4\n",
      "2014-06        6.6        19.8\n",
      "parks, January over July: 7.5\n",
      "parks billed every day of the year, January over July: 8.0\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 990x385 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = usage[usage.measure == 'Water'].merge(assets[['asset_name', 'category', 'water_days_billed']], on='asset_name')\n",
    "by = w.groupby(['month', 'category']).amount.sum().unstack()\n",
    "print((by / 1000).round(1))\n",
    "osp = by['Open Space']\n",
    "print('parks, January over July:', round(osp['2014-01'] / osp['2013-07'], 1))\n",
    "full = w[(w.category == 'Open Space') & (w.water_days_billed == 365)].groupby('month').amount.sum()\n",
    "print('parks billed every day of the year, January over July:', round(full['2014-01'] / full['2013-07'], 1))\n",
    "ax = (by / 1000).plot(kind='bar', stacked=True, color=[MUTED, INK], figsize=(9, 3.5))\n",
    "ax.set_ylabel('thousand kL'); ax.set_xlabel(''); ax.set_title('Water by month, mapped assets')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31edcd24",
   "metadata": {},
   "source": [
    "## Water per park, and two bills to query\n",
    "\n",
    "The year's water divided by the council parcel each park was placed on gives a depth in millimetres. It is over the whole\n",
    "parcel (paths, lawns and beds), not the irrigated area. Two stand out, and the bills explain why: Parliament Reserve's\n",
    "water bills cover only part of the year, with a gap from November to February and then most of its year's water in three\n",
    "months; Southbank Promenade is billed on several meters at once. Both are bills to query before anyone treats them as\n",
    "watering rates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b7f1a16c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                   mm  days billed\n",
      "asset_name                                        \n",
      "Garden - Carlton South          662.0        365.0\n",
      "Garden - Fitzroy                203.0        365.0\n",
      "Garden - Flagstaff              422.0        365.0\n",
      "Garden - Queen Victoria         421.0        365.0\n",
      "Garden - Treasury               491.0        365.0\n",
      "Garden Alexandra                616.0        365.0\n",
      "Park - Birrarung Marr           420.0        365.0\n",
      "Park - Fawkner                  199.0        365.0\n",
      "Park - JJ Holland                58.0        365.0\n",
      "Park - Kings Domain             403.0        365.0\n",
      "Park - Parliament              3710.0        211.0\n",
      "Park - Princes Park             211.0        365.0\n",
      "Park - Royal Park                 6.0        365.0\n",
      "Park - Shrine                   615.0        365.0\n",
      "Reserve - Darling Square        622.0        365.0\n",
      "Reserve - Jolimont              649.0        365.0\n",
      "Reserve - Lincoln Square        232.0        365.0\n",
      "Reserve - Point Park            695.0        365.0\n",
      "Reserve - Powlett               340.0        365.0\n",
      "Reserve - Southbank Promenade  1979.0        365.0\n",
      "median 421.5\n",
      "       asset_name measure unit billing_start billing_end       amount\n",
      "Park - Parliament   Water   kL    2013-07-01  2013-07-31   945.321839\n",
      "Park - Parliament   Water   kL    2013-08-01  2013-08-15   457.413793\n",
      "Park - Parliament   Water   kL    2013-08-16  2013-11-14   740.000000\n",
      "Park - Parliament   Water   kL    2014-03-01  2014-03-31 10521.041599\n",
      "Park - Parliament   Water   kL    2014-04-01  2014-04-30 10181.653160\n",
      "Park - Parliament   Water   kL    2014-05-01  2014-05-13  4412.049703\n"
     ]
    }
   ],
   "source": [
    "parks = assets[(assets.category == 'Open Space') & assets.property_id.notna() & ~assets.asset_name.str.startswith('Lease')].set_index('asset_name')\n",
    "depth = (year.Water.reindex(parks.index) / parks.area_m2 * 1000).round(0).sort_values(ascending=False)\n",
    "print(pd.DataFrame({'mm': depth, 'days billed': parks.water_days_billed}).to_string())\n",
    "print('median', depth.median())\n",
    "bills = pd.read_csv(f'{DATA}/usage/bills.csv')\n",
    "print(bills[(bills.asset_name == 'Park - Parliament') & (bills.measure == 'Water')].to_string(index=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6da76bfd",
   "metadata": {},
   "source": [
    "## Electricity per square metre of floor\n",
    "\n",
    "For buildings with their own footprint: the year's grid electricity over an estimated floor area, the footprint picked in\n",
    "Plotlay times the floors above ground in the council's 2014 building census (CLUE). An estimate, so read it as a ranking\n",
    "to start questions, not a rating. Two leases share a building with others and are not compared."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5cd168b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "asset_name\n",
      "Recreation Centre - North Melbourne                  282.7\n",
      "Administration - Council House 1                     147.6\n",
      "Library - East Melbourne                             142.5\n",
      "Library - North Melbourne                            133.6\n",
      "Community Centre - Southbank                         114.5\n",
      "Recreation Centre - City Baths                        97.4\n",
      "Lease - 225 Bourke St - City Village                  93.2\n",
      "Community Centre - Docklands Hub                      91.0\n",
      "Administration - Melbourne Town Hall                  88.7\n",
      "Administration - Council House 2                      86.3\n",
      "Arts Centre - Nth Melb Town Hall                      63.4\n",
      "Lease - Melbourne Town Hall                           57.9\n",
      "Lease - Multicultural Hub                             53.0\n",
      "Lease - Car Park Elgin Street                         28.6\n",
      "Library - City                                        28.4\n",
      "Administration - 602 Little Bourke Street Storage     28.2\n",
      "Arts Centre - Meat Market                             26.3\n",
      "Community Centre - North Melbourne                    21.2\n",
      "Sports Pavilion - Fawkner Park South                  13.6\n",
      "median of the rest: 86.3\n"
     ]
    }
   ],
   "source": [
    "b = assets[assets.floor_m2_est.notna()].set_index('asset_name')\n",
    "kwh = (year.Electricity.reindex(b.index) / b.floor_m2_est).dropna().round(1).sort_values(ascending=False)\n",
    "shared = ['Library - City', 'Lease - 225 Bourke St - City Village']\n",
    "print(kwh.to_string())\n",
    "print('median of the rest:', kwh.drop(shared, errors='ignore').median())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "192101a8",
   "metadata": {},
   "source": [
    "## The map, January 2014\n",
    "\n",
    "Every mapped asset coloured by its water that month. Lines are boulevards; points are sites with no outline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d7b6b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 880x880 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "jan = usage[(usage.measure == 'Water') & (usage.month == '2014-01')].set_index('asset_name').amount\n",
    "s = shapes.to_crs(7855).copy(); s['kl'] = s.key.map(jan)\n",
    "ax = s.plot(column='kl', cmap='Blues', norm=plt.matplotlib.colors.LogNorm(10, 20000), legend=True, figsize=(8, 8), missing_kwds={'color': '#ddd'}, linewidth=2,\n",
    "            legend_kwds={'label': 'water, January 2014 (kL)', 'shrink': .6})\n",
    "ax.set_axis_off(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f548370",
   "metadata": {},
   "source": [
    "## Rows with no shape still count\n",
    "\n",
    "Six network assets (street lighting, cameras, parking meters, signs, many small street reserves) have no single place, and\n",
    "two reserves are not named in any council layer. They stay in the table: the totals above include them only where the\n",
    "council's own bills are summed, not on the map. Street lighting alone is about a quarter of the council's electricity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f3d7027c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "measure                                Electricity    Water\n",
      "asset_name                                                 \n",
      "Information - Parking Signage Network     163467.0      0.0\n",
      "Parking Meters - Melbourne Network        107627.0      0.0\n",
      "Reserve - Buncle Street                        0.0   4901.0\n",
      "Security Cameras - Melbourne Network      159825.0      0.0\n",
      "Street Lighting - Docklands Network      1972690.0      0.0\n",
      "Street Lighting - Melbourne Network      1674243.0      0.0\n",
      "Street Reserve - Investigator Drive            0.0   5697.0\n",
      "Street Reserve - Miscellaneous               678.0  62048.0\n"
     ]
    }
   ],
   "source": [
    "bills['start'] = pd.to_datetime(bills.billing_start); bills['end'] = pd.to_datetime(bills.billing_end)\n",
    "fy0, fy1 = pd.Timestamp('2013-07-01'), pd.Timestamp('2014-06-30')\n",
    "days = (bills.end - bills.start).dt.days + 1\n",
    "inside = ((bills.end.clip(upper=fy1) - bills.start.clip(lower=fy0)).dt.days + 1).clip(lower=0)\n",
    "bills['fy'] = bills.amount * inside / days\n",
    "net = bills[bills.asset_name.isin(left.asset_name)].groupby(['asset_name', 'measure']).fy.sum().unstack().fillna(0).round(0)\n",
    "print(net.to_string())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}