units.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d96fa055",
   "metadata": {},
   "source": [
    "# Map Objects to their Units\n",
    "\n",
    "Some units are already defined in `model/units.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "15ce632a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gt Unit(symbol=\"Gt\", name=\"gigatonne\", dimension=Dimension(kg=1, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=9, symbol=\"G\", name=\"giga\"), factor=Fraction(1000, 1))\n",
      "\n",
      "Mt Unit(symbol=\"Mt\", name=\"megatonne\", dimension=Dimension(kg=1, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=6, symbol=\"M\", name=\"mega\"), factor=Fraction(1000, 1))\n",
      "\n",
      "kt Unit(symbol=\"kt\", name=\"kilotonne\", dimension=Dimension(kg=1, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=3, symbol=\"k\", name=\"kilo\"), factor=Fraction(1000, 1))\n",
      "\n",
      "ppm Unit(symbol=\"ppm\", name=\"parts per million\", dimension=Dimension(kg=0, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=0, symbol=\"\", name=\"\"), factor=Fraction(1, 1000000))\n",
      "\n",
      "ppb Unit(symbol=\"ppb\", name=\"parts per billion\", dimension=Dimension(kg=0, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=0, symbol=\"\", name=\"\"), factor=Fraction(1, 1000000000))\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from model.units import Gt, Mt, kt, ppm, ppb\n",
    "\n",
    "for unit in [Gt, Mt, kt, ppm, ppb]:\n",
    "    print(unit, repr(unit), end=\"\\n\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "439e410b",
   "metadata": {},
   "source": [
    "## SI Units\n",
    "are already defined in the modules `base`, `derived`, and `accepted`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "556ffa84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "base:  kg: kilogram  m: metre  s: second  A: ampere  K: kelvin  cd: candela  mol: mole  \n",
      "\n",
      "derived:  rad: radian  sr: steradian  Hz: hertz  N: newton  Pa: pascal  J: joule  W: watt  C: coulomb  V: volt  F: farad  Ω: ohm  S: siemens  Wb: weber  T: tesla  H: henry  °C: degree Celsius  lm: lumen  lx: lux  Bq: becquerel  Gy: gray  Sv: sievert  kat: katal  \n",
      "\n",
      "accepted:  min: minute  h: hour  d: day  au: astronomical unit  ha: hectare  l: litre  t: tonne  "
     ]
    }
   ],
   "source": [
    "from unitsofmeasure import base, derived, accepted\n",
    "\n",
    "print(\"base:  \", end=\"\")\n",
    "for unit in base.units.values():\n",
    "    print(unit.symbol + \": \" + unit.name, end=\"  \")\n",
    "\n",
    "print(\"\\n\\nderived:  \", end=\"\")\n",
    "for unit in derived.units.values():\n",
    "    print(unit.symbol + \": \" + unit.name, end=\"  \")\n",
    "\n",
    "print(\"\\n\\naccepted:  \", end=\"\")\n",
    "for unit in accepted.units.values():\n",
    "    print(unit.symbol + \": \" + unit.name, end=\"  \")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0be04d03",
   "metadata": {},
   "source": [
    "The symbols are attributes, so you can reference them directly without the dictionary. One exception is `°C` which is not a Python identifier and is therefore mapped to the attribute `degC`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "df616ffd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kg °C t\n"
     ]
    }
   ],
   "source": [
    "print(base.kg, derived.degC, accepted.t)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70c43da4",
   "metadata": {},
   "source": [
    "## Additional Units\n",
    "\n",
    "If you need addtional units, then you can add them to `units.py` and you can re-use the dimensions of the pre-defined SI units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b3d57b55",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GWh Unit(symbol=\"GWh\", name=\"gigawatt-hour\", dimension=Dimension(kg=1, m=2, s=-2, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=9, symbol=\"G\", name=\"giga\"), factor=Fraction(3600, 1))\n",
      "\n",
      "MWh Unit(symbol=\"MWh\", name=\"megawatt-hour\", dimension=Dimension(kg=1, m=2, s=-2, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=6, symbol=\"M\", name=\"mega\"), factor=Fraction(3600, 1))\n",
      "\n",
      "kWh Unit(symbol=\"kWh\", name=\"kilowatt-hour\", dimension=Dimension(kg=1, m=2, s=-2, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=3, symbol=\"k\", name=\"kilo\"), factor=Fraction(3600, 1))\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from fractions import Fraction\n",
    "from unitsofmeasure import decprefix, Unit\n",
    "from unitsofmeasure.derived import J\n",
    "\n",
    "_FRACTION_3K6 = Fraction(3600, 1)\n",
    "\n",
    "# energy (with dimension from SI unit)\n",
    "GWh = Unit(\"GWh\", \"gigawatt-hour\", J.dimension, decprefix.G, _FRACTION_3K6)\n",
    "MWh = Unit(\"MWh\", \"megawatt-hour\", J.dimension, decprefix.M, _FRACTION_3K6)\n",
    "kWh = Unit(\"kWh\", \"kilowatt-hour\", J.dimension, decprefix.k, _FRACTION_3K6)\n",
    "for unit in [GWh, MWh, kWh]:\n",
    "    print(unit, repr(unit), end=\"\\n\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61d1caef",
   "metadata": {},
   "source": [
    "## Map Functions to their Units\n",
    "\n",
    "You can decorate functions with `@map_to_unit(unit)` to map them to their units. This maps the function definition (and not the return value of the function) to the unit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76c5f53e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mass: 1.0 Mt\n"
     ]
    }
   ],
   "source": [
    "from model.units import get_unit, map_to_unit\n",
    "\n",
    "@map_to_unit(Mt)\n",
    "def get_mass():\n",
    "    return 1.0\n",
    "\n",
    "value = get_mass()\n",
    "unit = get_unit(get_mass)\n",
    "print(\"mass:\", value, unit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77feb381",
   "metadata": {},
   "source": [
    "## Do not map immutable Values to Units\n",
    "\n",
    "Variables bound to constant types like `int` and `float` should not be mapped to units, because this would map the variable value (and not the variable) to the unit. Currently, this raises a `TypeError`, because it cannot be weakly referenced either."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d2252191",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cannot create weak reference to 'int' object\n"
     ]
    }
   ],
   "source": [
    "from model.units import set_unit\n",
    "\n",
    "v1 = 1\n",
    "v2 = 2\n",
    "v3 = 1\n",
    "v4 = 2\n",
    "\n",
    "assert id(v1) == id(v3) # different variables can be bound to the same value\n",
    "\n",
    "try:\n",
    "    set_unit(v1, \"u1\")\n",
    "    set_unit(v2, \"u2\")\n",
    "    set_unit(v3, \"u3\")\n",
    "    set_unit(v4, \"u4\")\n",
    "except TypeError as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33b6aa4d",
   "metadata": {},
   "source": [
    "## Map DataFrames or Series to Units\n",
    "\n",
    "You can map user-defined objects like `DataFrame` or `Series` to units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "523f5cdd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bike Infrastructure: CO2eq reduced per year in Mt\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>World</th>\n",
       "      <th>OECD90</th>\n",
       "      <th>Eastern Europe</th>\n",
       "      <th>Asia (Sans Japan)</th>\n",
       "      <th>Middle East and Africa</th>\n",
       "      <th>Latin America</th>\n",
       "      <th>China</th>\n",
       "      <th>India</th>\n",
       "      <th>EU</th>\n",
       "      <th>USA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</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>2014</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>53.721251</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>61.193581</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>68.509277</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>75.674445</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>82.695188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>89.577611</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>96.327820</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2027</th>\n",
       "      <td>102.951919</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2028</th>\n",
       "      <td>109.456011</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2029</th>\n",
       "      <td>115.846203</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>122.128598</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2031</th>\n",
       "      <td>128.309302</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2032</th>\n",
       "      <td>134.394418</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2033</th>\n",
       "      <td>140.390052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2034</th>\n",
       "      <td>146.302308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2035</th>\n",
       "      <td>152.137291</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2036</th>\n",
       "      <td>157.901105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2037</th>\n",
       "      <td>163.599855</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2038</th>\n",
       "      <td>169.239646</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2039</th>\n",
       "      <td>174.826583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>180.366769</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041</th>\n",
       "      <td>185.866309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2042</th>\n",
       "      <td>191.331309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2043</th>\n",
       "      <td>196.767873</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2044</th>\n",
       "      <td>202.182105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2045</th>\n",
       "      <td>207.580111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2046</th>\n",
       "      <td>212.967994</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2047</th>\n",
       "      <td>218.351859</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2048</th>\n",
       "      <td>223.737811</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2049</th>\n",
       "      <td>229.131956</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2050</th>\n",
       "      <td>234.540396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2051</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2052</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2053</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2054</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2055</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2056</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2057</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2058</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2059</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           World  OECD90  Eastern Europe  Asia (Sans Japan)  Middle East and Africa  Latin America  China  India   EU  USA\n",
       "Year                                                                                                                      \n",
       "2014    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2015    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2016    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2017    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2018    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2019    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2020   53.721251     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2021   61.193581     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2022   68.509277     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2023   75.674445     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2024   82.695188     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2025   89.577611     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2026   96.327820     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2027  102.951919     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2028  109.456011     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2029  115.846203     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2030  122.128598     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2031  128.309302     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2032  134.394418     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2033  140.390052     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2034  146.302308     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2035  152.137291     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2036  157.901105     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2037  163.599855     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2038  169.239646     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2039  174.826583     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2040  180.366769     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2041  185.866309     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2042  191.331309     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2043  196.767873     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2044  202.182105     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2045  207.580111     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2046  212.967994     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2047  218.351859     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2048  223.737811     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2049  229.131956     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2050  234.540396     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2051    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2052    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2053    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2054    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2055    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2056    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2057    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2058    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2059    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0\n",
       "2060    0.000000     0.0             0.0                0.0                     0.0            0.0    0.0    0.0  0.0  0.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from solution import factory\n",
    "\n",
    "bikeinfra_pds2 = factory.load_scenario(\"bikeinfrastructure\", \"PDS2\") # Units: Megatons of CO2-eq emissions\n",
    "bi_co2e = bikeinfra_pds2.c2.co2eq_mmt_reduced() # DataFrame\n",
    "set_unit(bi_co2e, Mt)\n",
    "print(\"Bike Infrastructure: CO2eq reduced per year in\", get_unit(bi_co2e))\n",
    "bi_co2e"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7eee8872",
   "metadata": {},
   "source": [
    "## Label Chart Axes\n",
    "\n",
    "with units of series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4784eaa3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bi_co2e_world = bi_co2e[\"World\"] # Series\n",
    "set_unit(bi_co2e_world, Mt)\n",
    "bi_co2e_world.loc[2020:2050].plot(title=\"Bike Infrastructure:\\nCO2eq reduced per year\", ylabel=get_unit(bi_co2e_world))\n",
    "pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78f9e9e5",
   "metadata": {},
   "source": [
    "## Decorated Functions\n",
    "\n",
    "Some functions are already mapped to units, but the IDs of class and object methods are different."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a1c2f96d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mt\n",
      "KeyError\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Unit(symbol=\"Mt\", name=\"megatonne\", dimension=Dimension(kg=1, m=0, s=0, A=0, K=0, cd=0, mol=0), prefix=Prefix(base=10, exponent=6, symbol=\"M\", name=\"mega\"), factor=Fraction(1000, 1))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from model.co2calcs import CO2Calcs\n",
    "cmid = id(CO2Calcs.co2eq_mmt_reduced) # class method ID\n",
    "omid = id(bikeinfra_pds2.c2.co2eq_mmt_reduced) # object method ID\n",
    "assert cmid != omid\n",
    "cmu = get_unit(CO2Calcs.co2eq_mmt_reduced) # class method unit\n",
    "print(cmu)\n",
    "try:\n",
    "    omu = get_unit(bikeinfra_pds2.c2.co2eq_mmt_reduced) # object method unit\n",
    "    print(omu)\n",
    "except KeyError as e:\n",
    "    print(e.__class__.__name__)\n",
    "cmu"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "856bf884",
   "metadata": {},
   "source": [
    "If a function or class method is not mapped to a unit, then `get_unit` raises a `KeyError` as in the example above. You can fix this easily by decorating the function or class method with `@map_to_unit`."
   ]
  }
 ],
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