orm_3_Registry.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The European Transaction Log (EUTL) is the backbone of the European Union Emissions Trading System (EUETS). It implements the transfer of emission allowances between parties active in the EUETS. The EUTL provides data on regulated installations, their emissions as well as transfers of allowances.  \n",
    "\n",
    "Assuming that the database has been successfully populated with the EUTL data (see 1_create_database.ipynb), this notebook illustrates how to analyze compliance and transactions on the registry level.\n",
    "\n",
    "Specifically, we consider the German registry with the identifier DE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "id_reg = \"DE\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Packages and options"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyeutl.orm import DataAccessLayer       # data access layer to access the database\n",
    "from pyeutl.orm import Country, Installation  # use country class to access registries\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "# %config InlineBackend.figure_formats = ['svg']\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Database connection settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "connectionSettings = dict(\n",
    "    user=\"postgres\", \n",
    "    host=\"localhost\", \n",
    "    db=\"eutl2024\", \n",
    "    passw=\"password\",\n",
    "    port=5432\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connect to database"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Connect to database and get a session:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "dal = DataAccessLayer(**connectionSettings)\n",
    "session = dal.session"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get registry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given the registry id, use the session to get the registry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DE: Germany\n"
     ]
    }
   ],
   "source": [
    "registry = session.get(Country, id_reg)\n",
    "print(registry.id + \": \" + registry.name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Installations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Low-level access: Get installation objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The country object has a property \"installations_in_registry\" which returns the query to get all installations registered in the country. The property \"installations_in_country\" returns all installations located in the country. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlalchemy.orm.dynamic.AppenderQuery at 0x233b9b47310>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inst = registry.installations_in_registry\n",
    "inst"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given the query we can either fetch the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<Installation('DE_222293', 'DE_222293', <Country('DE', 'Germany')>)>,\n",
       " <Installation('DE_200110', '201', <Country('DE', 'Germany')>)>,\n",
       " <Installation('DE_200022', '1776', <Country('DE', 'Germany')>)>,\n",
       " <Installation('DE_200060', '21912', <Country('DE', 'Germany')>)>,\n",
       " <Installation('DE_200408', '25067', <Country('DE', 'Germany')>)>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inst.first()          # get only first results\n",
    "inst.all()            # get all results\n",
    "inst.limit(5).all()   # get first 5 results "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could also further filter the results, e.g., getting all installations under activity 1 or 20 (combustion of fuels):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of combustion installations:  1536\n"
     ]
    }
   ],
   "source": [
    "t_ = inst.filter(Installation.activity_id.in_([1, 20])).all()\n",
    "print(\"Number of combustion installations: \", len(t_))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More easy: get_installations()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The low-level access is useful to directly get the installation objects which allows constructing different filters. For convenience, get_installations() implements a method that returns all installations in the registry as a Pandas dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3131 entries, 0 to 3130\n",
      "Data columns (total 43 columns):\n",
      " #   Column                  Non-Null Count  Dtype         \n",
      "---  ------                  --------------  -----         \n",
      " 0   monitoringID            210 non-null    object        \n",
      " 1   addressSecondary        202 non-null    object        \n",
      " 2   latitudeEutl            11 non-null     float64       \n",
      " 3   latitudeGoogle          2858 non-null   float64       \n",
      " 4   isMaritimeOperator      3130 non-null   object        \n",
      " 5   name                    3131 non-null   object        \n",
      " 6   monitoringExpiry        0 non-null      object        \n",
      " 7   postalCode              3129 non-null   object        \n",
      " 8   longitudeGoogle         2858 non-null   float64       \n",
      " 9   shippingCompanyCountry  238 non-null    object        \n",
      " 10  id                      3131 non-null   object        \n",
      " 11  monitoringFirstYear     210 non-null    object        \n",
      " 12  city                    3130 non-null   object        \n",
      " 13  nace15_id               2288 non-null   object        \n",
      " 14  euEntitlement           2250 non-null   float64       \n",
      " 15  shippingCompanyType     238 non-null    object        \n",
      " 16  registry_id             3131 non-null   object        \n",
      " 17  activity_id             3131 non-null   int64         \n",
      " 18  permitDateExpiry        622 non-null    datetime64[ns]\n",
      " 19  country_id              3130 non-null   object        \n",
      " 20  nace20_id               2484 non-null   object        \n",
      " 21  shippingCompany         238 non-null    object        \n",
      " 22  parentCompany           2788 non-null   object        \n",
      " 23  isAircraftOperator      3130 non-null   object        \n",
      " 24  nace_id                 2932 non-null   object        \n",
      " 25  imoID                   238 non-null    object        \n",
      " 26  subsidiaryCompany       2116 non-null   object        \n",
      " 27  ec748_2009Code          210 non-null    object        \n",
      " 28  region                  5 non-null      object        \n",
      " 29  tradingSystem_id        3131 non-null   object        \n",
      " 30  permitID                2682 non-null   object        \n",
      " 31  permitDateEntry         2682 non-null   datetime64[ns]\n",
      " 32  longitudeEutl           11 non-null     float64       \n",
      " 33  chEntitlement           9 non-null      float64       \n",
      " 34  eprtrID                 2892 non-null   object        \n",
      " 35  designatorICAO          210 non-null    object        \n",
      " 36  addressMain             3130 non-null   object        \n",
      " 37  registry                3131 non-null   object        \n",
      " 38  activity                3131 non-null   object        \n",
      " 39  activity_category       3130 non-null   object        \n",
      " 40  nace                    2932 non-null   object        \n",
      " 41  nace_category           2932 non-null   object        \n",
      " 42  country                 3130 non-null   object        \n",
      "dtypes: datetime64[ns](2), float64(6), int64(1), object(34)\n",
      "memory usage: 1.0+ MB\n"
     ]
    }
   ],
   "source": [
    "inst = registry.get_installations()\n",
    "inst.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get an overview about the number of activities we can use a simple groupby operation but need to to be aware that some installations do not have a Nace code assigned:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nace</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Steam and air conditioning supply</th>\n",
       "      <td>598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production of electricity</th>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Water transport</th>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Air transport</th>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    id\n",
       "nace                                  \n",
       "Steam and air conditioning supply  598\n",
       "Production of electricity          257\n",
       "Water transport                    238\n",
       "Air transport                      210\n",
       "NaN                                199"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inst.groupby(\"nace\", dropna=False)[[\"id\"]].count().sort_values(\"id\", ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most installations provide either heat or electricity (or both). The large number of NaN results from aircraft operators that do not have a nace code assigned: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>activity</th>\n",
       "      <th>activity_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Combustion of fuels</th>\n",
       "      <th>20</th>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production of bulk chemicals</th>\n",
       "      <th>42</th>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Combustion installations with a rated thermal input exceeding 20 MW</th>\n",
       "      <th>1</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production of paper or cardboard</th>\n",
       "      <th>36</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                                                id\n",
       "activity                                           activity_id    \n",
       "Combustion of fuels                                20           96\n",
       "Production of bulk chemicals                       42           58\n",
       "Combustion installations with a rated thermal i... 1             9\n",
       "Production of paper or cardboard                   36            7"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    inst[pd.isnull(inst.nace)]\n",
    "    .groupby([\"activity\", \"activity_id\"])[[\"id\"]]\n",
    "    .count()\n",
    "    .sort_values(\"id\", ascending=False)\n",
    "    .head(4)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The get_installation() method implements allows filtering installations based on installation attributes. For this, provide a dictionary with the installation attribute as key and a *list* as values. The dataframe returned only includes installations with attribute values as given in the respective list.\n",
    "\n",
    "As an example, filter again for installations related to combustion activities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of combustion installations:  1536\n"
     ]
    }
   ],
   "source": [
    "filt = {\"activity_id\": [1, 20]}\n",
    "t_ = registry.get_installations(filter=filt)\n",
    "print(\"Number of combustion installations: \", len(t_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([20,  1], dtype=int64)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "registry.get_installations(filter=filt).activity_id.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compliance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Low-level: Using installation objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given a list of installation objects, we can analyze each installation in same manner as outline in the previous notebook. \n",
    "\n",
    "As an example, consider getting all compliance data for combustion activities in the selected registry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of combustion installations:  1536\n"
     ]
    }
   ],
   "source": [
    "comb = registry.installations_in_registry.filter(Installation.activity_id.in_([1, 20])).all()\n",
    "print(\"Number of combustion installations: \", len(comb))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now follow the previous notebook and get the compliance data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\abrel\\AppData\\Local\\Temp\\ipykernel_32564\\1590394317.py:1: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df_comb = pd.concat([c.get_compliance() for c in comb])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 39936 entries, 0 to 25\n",
      "Data columns (total 17 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   year                    39936 non-null  int64  \n",
      " 1   euetsPhase              39936 non-null  object \n",
      " 2   allocatedNewEntrance    598 non-null    float64\n",
      " 3   allocated10c            0 non-null      object \n",
      " 4   verifiedCummulative     20392 non-null  float64\n",
      " 5   surrendered             19562 non-null  float64\n",
      " 6   balance                 0 non-null      object \n",
      " 7   reportedInSystem_id     39936 non-null  object \n",
      " 8   installation_id         39936 non-null  object \n",
      " 9   compliance_id           20799 non-null  object \n",
      " 10  allocatedFree           21433 non-null  float64\n",
      " 11  allocatedTotal          39936 non-null  int64  \n",
      " 12  verified                20085 non-null  float64\n",
      " 13  verifiedUpdated         39936 non-null  bool   \n",
      " 14  surrenderedCummulative  20734 non-null  float64\n",
      " 15  penalty                 0 non-null      object \n",
      " 16  compliance              20799 non-null  object \n",
      "dtypes: bool(1), float64(6), int64(2), object(8)\n",
      "memory usage: 5.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df_comb = pd.concat([c.get_compliance() for c in comb])\n",
    "df_comb.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accessing data in this way, has the advantage to be rather flexible in allowing to access that data for each installation. However, that comes at performance cost. Moreover, you either need to join installation information like names and activities or to further aggregate the data. \n",
    "\n",
    "Therefore, the country object provides further methods that already include these information and aggregations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## High level: get_compliance()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "get_compliance() returns a dataframe of compliance data related to the registry including limited installation details:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 83588 entries, 0 to 83587\n",
      "Data columns (total 15 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   installation_id       83588 non-null  object \n",
      " 1   installation_name     83588 non-null  object \n",
      " 2   activity_id           83588 non-null  int64  \n",
      " 3   activity              83588 non-null  object \n",
      " 4   nace_id               78432 non-null  object \n",
      " 5   nace                  78432 non-null  object \n",
      " 6   year                  83588 non-null  int64  \n",
      " 7   surrendered           33863 non-null  float64\n",
      " 8   verified              35275 non-null  float64\n",
      " 9   allocatedTotal        83588 non-null  int64  \n",
      " 10  allocatedFree         38448 non-null  float64\n",
      " 11  allocated10c          14 non-null     float64\n",
      " 12  allocatedNewEntrance  1256 non-null   float64\n",
      " 13  nace_category         83588 non-null  object \n",
      " 14  activity_category     83588 non-null  object \n",
      "dtypes: float64(5), int64(3), object(7)\n",
      "memory usage: 9.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df_comp = registry.get_compliance()\n",
    "df_comp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the installation data contain a special installation, that represent the Effort Sharing performance of the respective registry. This installation is always named after the two-digit country identifier and then esd. This approach was chosen to fit the ESD data into the general data model. It allows to easily access the ESD compliance of the registry. We next use the ESD identifier to separate EUETS compliance data from those under the ESD:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>installation_id</th>\n",
       "      <th>installation_name</th>\n",
       "      <th>activity_id</th>\n",
       "      <th>activity</th>\n",
       "      <th>nace_id</th>\n",
       "      <th>nace</th>\n",
       "      <th>year</th>\n",
       "      <th>surrendered</th>\n",
       "      <th>verified</th>\n",
       "      <th>allocatedTotal</th>\n",
       "      <th>allocatedFree</th>\n",
       "      <th>allocated10c</th>\n",
       "      <th>allocatedNewEntrance</th>\n",
       "      <th>nace_category</th>\n",
       "      <th>activity_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DE_1501</td>\n",
       "      <td>Heizkraftwerk Mitte (Allerheiligenstraße)</td>\n",
       "      <td>20</td>\n",
       "      <td>Combustion of fuels</td>\n",
       "      <td>35.30</td>\n",
       "      <td>Steam and air conditioning supply</td>\n",
       "      <td>2024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2700</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Energy: Steam and air conditioning supply</td>\n",
       "      <td>Combustion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DE_1501</td>\n",
       "      <td>Heizkraftwerk Mitte (Allerheiligenstraße)</td>\n",
       "      <td>20</td>\n",
       "      <td>Combustion of fuels</td>\n",
       "      <td>35.30</td>\n",
       "      <td>Steam and air conditioning supply</td>\n",
       "      <td>2025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2625</td>\n",
       "      <td>2625.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Energy: Steam and air conditioning supply</td>\n",
       "      <td>Combustion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DE_1501</td>\n",
       "      <td>Heizkraftwerk Mitte (Allerheiligenstraße)</td>\n",
       "      <td>20</td>\n",
       "      <td>Combustion of fuels</td>\n",
       "      <td>35.30</td>\n",
       "      <td>Steam and air conditioning supply</td>\n",
       "      <td>2026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Energy: Steam and air conditioning supply</td>\n",
       "      <td>Combustion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DE_1501</td>\n",
       "      <td>Heizkraftwerk Mitte (Allerheiligenstraße)</td>\n",
       "      <td>20</td>\n",
       "      <td>Combustion of fuels</td>\n",
       "      <td>35.30</td>\n",
       "      <td>Steam and air conditioning supply</td>\n",
       "      <td>2027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Energy: Steam and air conditioning supply</td>\n",
       "      <td>Combustion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DE_1501</td>\n",
       "      <td>Heizkraftwerk Mitte (Allerheiligenstraße)</td>\n",
       "      <td>20</td>\n",
       "      <td>Combustion of fuels</td>\n",
       "      <td>35.30</td>\n",
       "      <td>Steam and air conditioning supply</td>\n",
       "      <td>2028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Energy: Steam and air conditioning supply</td>\n",
       "      <td>Combustion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83575</th>\n",
       "      <td>DE_200312</td>\n",
       "      <td>2758</td>\n",
       "      <td>10</td>\n",
       "      <td>Aircraft operator activities</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>2026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>Aircrafts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83576</th>\n",
       "      <td>DE_200312</td>\n",
       "      <td>2758</td>\n",
       "      <td>10</td>\n",
       "      <td>Aircraft operator activities</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>2027</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>Aircrafts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83577</th>\n",
       "      <td>DE_200312</td>\n",
       "      <td>2758</td>\n",
       "      <td>10</td>\n",
       "      <td>Aircraft operator activities</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>2028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>Aircrafts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83578</th>\n",
       "      <td>DE_200312</td>\n",
       "      <td>2758</td>\n",
       "      <td>10</td>\n",
       "      <td>Aircraft operator activities</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>2029</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>Aircrafts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83579</th>\n",
       "      <td>DE_200312</td>\n",
       "      <td>2758</td>\n",
       "      <td>10</td>\n",
       "      <td>Aircraft operator activities</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>2030</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Air transport</td>\n",
       "      <td>Aircrafts</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83580 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      installation_id                          installation_name  activity_id  \\\n",
       "0             DE_1501  Heizkraftwerk Mitte (Allerheiligenstraße)           20   \n",
       "1             DE_1501  Heizkraftwerk Mitte (Allerheiligenstraße)           20   \n",
       "2             DE_1501  Heizkraftwerk Mitte (Allerheiligenstraße)           20   \n",
       "3             DE_1501  Heizkraftwerk Mitte (Allerheiligenstraße)           20   \n",
       "4             DE_1501  Heizkraftwerk Mitte (Allerheiligenstraße)           20   \n",
       "...               ...                                        ...          ...   \n",
       "83575       DE_200312                                       2758           10   \n",
       "83576       DE_200312                                       2758           10   \n",
       "83577       DE_200312                                       2758           10   \n",
       "83578       DE_200312                                       2758           10   \n",
       "83579       DE_200312                                       2758           10   \n",
       "\n",
       "                           activity nace_id  \\\n",
       "0               Combustion of fuels   35.30   \n",
       "1               Combustion of fuels   35.30   \n",
       "2               Combustion of fuels   35.30   \n",
       "3               Combustion of fuels   35.30   \n",
       "4               Combustion of fuels   35.30   \n",
       "...                             ...     ...   \n",
       "83575  Aircraft operator activities    51.0   \n",
       "83576  Aircraft operator activities    51.0   \n",
       "83577  Aircraft operator activities    51.0   \n",
       "83578  Aircraft operator activities    51.0   \n",
       "83579  Aircraft operator activities    51.0   \n",
       "\n",
       "                                    nace  year  surrendered  verified  \\\n",
       "0      Steam and air conditioning supply  2024          NaN       NaN   \n",
       "1      Steam and air conditioning supply  2025          NaN       NaN   \n",
       "2      Steam and air conditioning supply  2026          NaN       NaN   \n",
       "3      Steam and air conditioning supply  2027          NaN       NaN   \n",
       "4      Steam and air conditioning supply  2028          NaN       NaN   \n",
       "...                                  ...   ...          ...       ...   \n",
       "83575                      Air transport  2026          NaN       NaN   \n",
       "83576                      Air transport  2027          NaN       NaN   \n",
       "83577                      Air transport  2028          NaN       NaN   \n",
       "83578                      Air transport  2029          NaN       NaN   \n",
       "83579                      Air transport  2030          NaN       NaN   \n",
       "\n",
       "       allocatedTotal  allocatedFree  allocated10c  allocatedNewEntrance  \\\n",
       "0                2700         2700.0           NaN                   NaN   \n",
       "1                2625         2625.0           NaN                   NaN   \n",
       "2                   0            NaN           NaN                   NaN   \n",
       "3                   0            NaN           NaN                   NaN   \n",
       "4                   0            NaN           NaN                   NaN   \n",
       "...               ...            ...           ...                   ...   \n",
       "83575               0            NaN           NaN                   NaN   \n",
       "83576               0            NaN           NaN                   NaN   \n",
       "83577               0            NaN           NaN                   NaN   \n",
       "83578               0            NaN           NaN                   NaN   \n",
       "83579               0            NaN           NaN                   NaN   \n",
       "\n",
       "                                   nace_category activity_category  \n",
       "0      Energy: Steam and air conditioning supply        Combustion  \n",
       "1      Energy: Steam and air conditioning supply        Combustion  \n",
       "2      Energy: Steam and air conditioning supply        Combustion  \n",
       "3      Energy: Steam and air conditioning supply        Combustion  \n",
       "4      Energy: Steam and air conditioning supply        Combustion  \n",
       "...                                          ...               ...  \n",
       "83575                              Air transport         Aircrafts  \n",
       "83576                              Air transport         Aircrafts  \n",
       "83577                              Air transport         Aircrafts  \n",
       "83578                              Air transport         Aircrafts  \n",
       "83579                              Air transport         Aircrafts  \n",
       "\n",
       "[83580 rows x 15 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_inst_esd = f\"{id_reg}_esd\"\n",
    "df_comp_esd = df_comp[df_comp.installation_id == id_inst_esd].copy()\n",
    "df_comp_euets = df_comp[df_comp.installation_id != id_inst_esd].copy()\n",
    "df_comp_euets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The frame allows to easily aggregate compliance data by the respective dimension. As an example, plot verified emissions by NACE category over time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x233f18395d0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (\n",
    "    df_comp_euets\n",
    "    .query(\"year < 2024\")\n",
    "    .groupby([\"year\", \"nace_category\"], as_index=False)\n",
    "    .verified\n",
    "    .sum()\n",
    "    .pivot_table(\"verified\", \"year\", \"nace_category\", dropna=False)\n",
    "    .div(1000000)\n",
    "    .plot(kind=\"bar\", stacked=True,  figsize=(12,6), ylabel=\"Million tCO$_2$\", grid=True)\n",
    ")\n",
    "ax.legend(bbox_to_anchor=(0.9, -0.2), loc=0, ncol=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Likewise, by activity category:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x233f1ee5c90>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (\n",
    "    df_comp_euets\n",
    "    .query(\"year < 2023\").groupby([\"year\", \"activity_category\"], as_index=False)\n",
    "    .verified.sum()\n",
    "    .pivot_table(\"verified\", \"year\", \"activity_category\", dropna=False).div(1000000)\n",
    "    .plot(kind=\"bar\", stacked=True,  figsize=(12,6), ylabel=\"Million tCO$_2$\", grid=True)\n",
    ")\n",
    "ax.legend(bbox_to_anchor=(1, -0.2), loc=0, ncol=6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effort Sharing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the effort sharing system we have only one installation and can directly plot emissions together with allocated and surrendered Assigned Amount Units (AAU)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = ( \n",
    "    df_comp_esd\n",
    "    .set_index(\"year\")\n",
    "    [[\"allocatedTotal\", \"verified\", \"surrendered\"]]\n",
    "    .div(1000000)\n",
    "    .plot(kind=\"bar\", stacked=False,  figsize=(12,6), ylabel=\"Million tCO$_2$\", grid=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>installation_id</th>\n",
       "      <th>installation_name</th>\n",
       "      <th>activity_id</th>\n",
       "      <th>activity</th>\n",
       "      <th>nace_id</th>\n",
       "      <th>nace</th>\n",
       "      <th>surrendered</th>\n",
       "      <th>verified</th>\n",
       "      <th>allocatedTotal</th>\n",
       "      <th>allocatedFree</th>\n",
       "      <th>allocated10c</th>\n",
       "      <th>allocatedNewEntrance</th>\n",
       "      <th>nace_category</th>\n",
       "      <th>activity_category</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>472527651.0</td>\n",
       "      <td>460204908.0</td>\n",
       "      <td>472527651</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>436790185.0</td>\n",
       "      <td>436790185.0</td>\n",
       "      <td>465830461</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>500496290.0</td>\n",
       "      <td>444080615.0</td>\n",
       "      <td>459133271</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>454157411.0</td>\n",
       "      <td>454157411.0</td>\n",
       "      <td>452436081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>466857281.0</td>\n",
       "      <td>466857281.0</td>\n",
       "      <td>432348857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>434047773.0</td>\n",
       "      <td>434047773.0</td>\n",
       "      <td>425202158</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>444262722.0</td>\n",
       "      <td>444262722.0</td>\n",
       "      <td>418055459</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>DE_esd</td>\n",
       "      <td>Effort Sharing Installation: Germany</td>\n",
       "      <td>1000</td>\n",
       "      <td>EU Effort Sharing</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>407410808.0</td>\n",
       "      <td>407410808.0</td>\n",
       "      <td>410908761</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not provided</td>\n",
       "      <td>not provided</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     installation_id                     installation_name  activity_id  \\\n",
       "year                                                                      \n",
       "2013          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2014          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2015          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2016          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2017          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2018          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2019          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "2020          DE_esd  Effort Sharing Installation: Germany         1000   \n",
       "\n",
       "               activity nace_id  nace  surrendered     verified  \\\n",
       "year                                                              \n",
       "2013  EU Effort Sharing    None  None  472527651.0  460204908.0   \n",
       "2014  EU Effort Sharing    None  None  436790185.0  436790185.0   \n",
       "2015  EU Effort Sharing    None  None  500496290.0  444080615.0   \n",
       "2016  EU Effort Sharing    None  None  454157411.0  454157411.0   \n",
       "2017  EU Effort Sharing    None  None  466857281.0  466857281.0   \n",
       "2018  EU Effort Sharing    None  None  434047773.0  434047773.0   \n",
       "2019  EU Effort Sharing    None  None  444262722.0  444262722.0   \n",
       "2020  EU Effort Sharing    None  None  407410808.0  407410808.0   \n",
       "\n",
       "      allocatedTotal  allocatedFree  allocated10c  allocatedNewEntrance  \\\n",
       "year                                                                      \n",
       "2013       472527651            NaN           NaN                   NaN   \n",
       "2014       465830461            NaN           NaN                   NaN   \n",
       "2015       459133271            NaN           NaN                   NaN   \n",
       "2016       452436081            NaN           NaN                   NaN   \n",
       "2017       432348857            NaN           NaN                   NaN   \n",
       "2018       425202158            NaN           NaN                   NaN   \n",
       "2019       418055459            NaN           NaN                   NaN   \n",
       "2020       410908761            NaN           NaN                   NaN   \n",
       "\n",
       "     nace_category activity_category  \n",
       "year                                  \n",
       "2013  not provided      not provided  \n",
       "2014  not provided      not provided  \n",
       "2015  not provided      not provided  \n",
       "2016  not provided      not provided  \n",
       "2017  not provided      not provided  \n",
       "2018  not provided      not provided  \n",
       "2019  not provided      not provided  \n",
       "2020  not provided      not provided  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_comp_esd.query(\"year < 2021\").set_index(\"year\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Whole EUETS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we look at emissions at the full EUETS level by activity and industry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "registries = [i[0] for i in session.query(Country.id).all()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\abrel\\AppData\\Local\\Temp\\ipykernel_32564\\4051259630.py:12: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df_comp = pd.concat(lst_df)\n"
     ]
    }
   ],
   "source": [
    "lst_df = []\n",
    "for reg in session.query(Country).all():\n",
    "    id_inst_esd = f\"{reg.id}_esd\"\n",
    "    df = (\n",
    "        reg\n",
    "        .get_compliance()\n",
    "        .query(\"year < 2024\")\n",
    "        .query(f\"installation_id != '{id_inst_esd}'\")\n",
    "        [[\"year\", \"nace_category\", \"activity_category\", \"verified\"]]\n",
    "    )\n",
    "    lst_df.append(df)\n",
    "df_comp = pd.concat(lst_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_ = (\n",
    "    df_comp\n",
    "    .groupby([\"year\", \"nace_category\"], as_index=False)\n",
    "    [[\"verified\"]]\n",
    "    .sum()\n",
    "    .pivot_table(\"verified\", \"year\", \"nace_category\", dropna=False)\n",
    "    .div(1000000)\n",
    "    \n",
    ")\n",
    "cm = plt.get_cmap('Spectral')\n",
    "colors = [cm(1.*i/len(df_.columns)) for i in range(len(df_.columns))]\n",
    "colors = {\n",
    "    \"Agriculture and mining\": \"aquamarine\",\n",
    "    \"Air transport\": \"yellow\",\n",
    "    \"Construction and services\": \"cyan\",\n",
    "    \"Energy: Electricity generation\": \"navy\",\n",
    "    \"Energy: Gas production and distribution\": \"blue\",\n",
    "    \"Energy: General\": \"mediumslateblue\",\n",
    "    \"Energy: Steam and air conditioning supply\": \"indigo\",\n",
    "    \"Manufacturing: Cars and other\": \"mistyrose\",\n",
    "    \"Manufacturing: Food, beverages, tabacco\": \"orangered\",\n",
    "    \"Manufacturing: Glas, ceramic, and stones\": \"chocolate\",\n",
    "    \"Manufacturing: Metals and machineries\": \"saddlebrown\",\n",
    "    \"Manufacturing: Paper and printing\": \"bisque\",\n",
    "    \"Manufacturing: Refineries, chemicals, and  pharmaceuticals\": \"darkorange\",\n",
    "    \"Manufacturing: Textiles, leather, and wood\": \"darkgoldenrod\",\n",
    "    \"not provided\": \"gray\",\n",
    "}\n",
    "ax = df_.plot(kind=\"bar\", stacked=True,  figsize=(12,6), \n",
    "         ylabel=\"Million tCO$_2$\", xlabel=\"Year\",\n",
    "         grid=True, color=colors, title=\"EU ETS verified emissions by NACE category\")\n",
    "ax.set_ylim(0,None)\n",
    "# move legend to the left outside the plot\n",
    "plt.legend(bbox_to_anchor=(-0.1, -0.18), loc='upper left', ncol=3, frameon=False)\n",
    "plt.savefig(\"EUETS_NACE_category.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And by activity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_ = (\n",
    "    df_comp\n",
    "    .groupby([\"year\", \"activity_category\"], as_index=False)\n",
    "    [[\"verified\"]]\n",
    "    .sum()\n",
    "    .pivot_table(\"verified\", \"year\", \"activity_category\", dropna=False)\n",
    "    .div(1000000)\n",
    ")\n",
    "cm = plt.get_cmap('jet')\n",
    "colors = [cm(1.*i/len(df_.columns)) for i in range(len(df_.columns))]\n",
    "ax = df_.plot(\n",
    "    kind=\"bar\", stacked=True,  figsize=(12,6), \n",
    "    ylabel=\"Million tCO$_2$\", xlabel=\"Year\",\n",
    "    grid=True,  title=\"EU ETS verified emissions by activity category\",\n",
    "    color=colors)\n",
    "ax.legend(bbox_to_anchor=(1, -0.17), loc=0, ncol=6, frameon=False)\n",
    "plt.savefig(\"EUETS_activity_category.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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