EF calculation bottom up method.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Introduction-(bottom-up-method)\" data-toc-modified-id=\"Introduction-(bottom-up-method)-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Introduction (bottom up method)</a></span></li><li><span><a href=\"#Script-setup\" data-toc-modified-id=\"Script-setup-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Script setup</a></span></li><li><span><a href=\"#Data-directory-preparention\" data-toc-modified-id=\"Data-directory-preparention-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Data directory preparention</a></span></li><li><span><a href=\"#Data-file-preparation\" data-toc-modified-id=\"Data-file-preparation-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Data file preparation</a></span><ul class=\"toc-item\"><li><span><a href=\"#input-directory-(all-general-raw-data-files)\" data-toc-modified-id=\"input-directory-(all-general-raw-data-files)-4.1\"><span class=\"toc-item-num\">4.1&nbsp;&nbsp;</span><code>input</code> directory (all general raw data files)</a></span></li><li><span><a href=\"#input/bottom_up_method-directory-(all-necessary-raw-data-files-for-the-bottom-up-method)\" data-toc-modified-id=\"input/bottom_up_method-directory-(all-necessary-raw-data-files-for-the-bottom-up-method)-4.2\"><span class=\"toc-item-num\">4.2&nbsp;&nbsp;</span><code>input/bottom_up_method</code> directory (all necessary raw data files for the bottom up method)</a></span></li></ul></li><li><span><a href=\"#Load-data-functions\" data-toc-modified-id=\"Load-data-functions-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Load data functions</a></span></li><li><span><a href=\"#Load-data-sets\" data-toc-modified-id=\"Load-data-sets-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Load data sets</a></span></li><li><span><a href=\"#Emission-factor-calculation-method\" data-toc-modified-id=\"Emission-factor-calculation-method-7\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>Emission factor calculation method</a></span><ul class=\"toc-item\"><li><span><a href=\"#Data-preperation\" data-toc-modified-id=\"Data-preperation-7.1\"><span class=\"toc-item-num\">7.1&nbsp;&nbsp;</span>Data preperation</a></span></li><li><span><a href=\"#Power-plant-side-generation-and-emissions\" data-toc-modified-id=\"Power-plant-side-generation-and-emissions-7.2\"><span class=\"toc-item-num\">7.2&nbsp;&nbsp;</span>Power plant side generation and emissions</a></span></li><li><span><a href=\"#Estimating-heat-via-Free-Allocation\" data-toc-modified-id=\"Estimating-heat-via-Free-Allocation-7.3\"><span class=\"toc-item-num\">7.3&nbsp;&nbsp;</span>Estimating heat via Free Allocation</a></span></li><li><span><a href=\"#Emission-factor-per-power-plant\" data-toc-modified-id=\"Emission-factor-per-power-plant-7.4\"><span class=\"toc-item-num\">7.4&nbsp;&nbsp;</span>Emission factor per power plant</a></span><ul class=\"toc-item\"><li><span><a href=\"#Validation-of-emission-factor-per-power-plant\" data-toc-modified-id=\"Validation-of-emission-factor-per-power-plant-7.4.1\"><span class=\"toc-item-num\">7.4.1&nbsp;&nbsp;</span>Validation of emission factor per power plant</a></span></li></ul></li><li><span><a href=\"#Emission-factor-per-technology-and-country\" data-toc-modified-id=\"Emission-factor-per-technology-and-country-7.5\"><span class=\"toc-item-num\">7.5&nbsp;&nbsp;</span>Emission factor per technology and country</a></span></li><li><span><a href=\"#Emission-factor-per-country\" data-toc-modified-id=\"Emission-factor-per-country-7.6\"><span class=\"toc-item-num\">7.6&nbsp;&nbsp;</span>Emission factor per country</a></span></li></ul></li><li><span><a href=\"#Validation-of-calculated-emission-factors\" data-toc-modified-id=\"Validation-of-calculated-emission-factors-8\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>Validation of calculated emission factors</a></span><ul class=\"toc-item\"><li><span><a href=\"#Validation-threshold-for-EF-per-technology-and-country\" data-toc-modified-id=\"Validation-threshold-for-EF-per-technology-and-country-8.1\"><span class=\"toc-item-num\">8.1&nbsp;&nbsp;</span>Validation threshold for EF per technology and country</a></span></li></ul></li><li><span><a href=\"#Evaluation-of-EF-data-set\" data-toc-modified-id=\"Evaluation-of-EF-data-set-9\"><span class=\"toc-item-num\">9&nbsp;&nbsp;</span>Evaluation of EF data set</a></span><ul class=\"toc-item\"><li><span><a href=\"#Evaluation-table\" data-toc-modified-id=\"Evaluation-table-9.1\"><span class=\"toc-item-num\">9.1&nbsp;&nbsp;</span>Evaluation table</a></span></li></ul></li><li><span><a href=\"#Export-final-EF-to-csv\" data-toc-modified-id=\"Export-final-EF-to-csv-10\"><span class=\"toc-item-num\">10&nbsp;&nbsp;</span>Export final EF to csv</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction (bottom up method)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this script, we determine country specific emission factors (EF) for different generation technologies. The calculated EF per technology are based on an bottom up method, that uses the hourly power plant generation data and yearly published emission data.\n",
    "\n",
    "The used method follows the idea to calculated a EF for individual power plants. In a late step the country specific EF per technology are determined by taking the EF from a representative sample of power plant emissions and generations in the respective country.\n",
    "\n",
    "The method was applied for data from year 2018."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Script setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.dates import DateFormatter \n",
    "\n",
    "%matplotlib inline\n",
    "plt.style.use('seaborn')\n",
    "plt.rcParams['figure.figsize'] = [15, 10]\n",
    "\n",
    "#helpers\n",
    "from helpers import load_timeseries_ENTSOE\n",
    "from helpers import change_ENTSOE_ProductionTypeName"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data directory preparention"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create input, processed and output folders if they don't exist.\n",
    "\n",
    "If the paths are relative, the corresponding folders will be created inside the current working directory.\n",
    "- input -> all needed input data\n",
    "- processed -> save point and exchange with other scripts\n",
    "- output -> final emission factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_directory_path = os.path.join('input')\n",
    "Bootom_up_method_input_directory_path = os.path.join('input', 'bootom_up_method')\n",
    "processed_directory_path = 'processed'\n",
    "output_directory_path = os.path.join('output')\n",
    "\n",
    "os.makedirs(input_directory_path, exist_ok=True)\n",
    "os.makedirs(Bootom_up_method_input_directory_path, exist_ok=True)\n",
    "os.makedirs(processed_directory_path, exist_ok=True)\n",
    "os.makedirs(output_directory_path, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data file preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `input` directory (all general raw data files)\n",
    "\n",
    "- 1) ENTSO-E production per type\n",
    "\n",
    "Production per type from ENTSO-E\n",
    "Original data: ENTSO-E Transparency Platform, Actual Generation per Production Type Available online: \n",
    "https://transparency.entsoe.eu/generation/r2/actualGenerationPerProductionType/show\n",
    "Processed with the following two script that converts the data to hourly resolution and scale the data to reported yearly data:\n",
    "\n",
    "- https://github.com/Open-Power-System-Data/time_series/tree/2020-10-06\n",
    "- https://github.com/INATECH-CIG/entso-e_GenerationOutputPerType\n",
    "\n",
    "File - > entso_gen_type_hourly_table_scaled.csv -> generation per technology\n",
    "\n",
    "\n",
    "- 2) ENTSO-E production per unit\n",
    "\n",
    "Production per Unit from ENTSO-E\n",
    "Original data: ENTSO-E Transparency Platform, Actual Generation per Generation Unit Available online: https://transparency.entsoe.eu/generation/r2/actualGenerationPerGenerationUnit/show (accessed on Apr 29, 2020).\n",
    "Processed with the following script that converts the data to hourly resolution:\n",
    "\n",
    "- https://github.com/INATECH-CIG/entso-e_GenerationOutputPerUnit\n",
    "\n",
    "File - > gen_data_2018.csv -> hourly generation data per unit\n",
    "\n",
    "File - > unit_data_2018.csv -> information about the generation units\n",
    "\n",
    "\n",
    "- 3) Matcher for power plants in ENTSO-E and EUTL data sets for Europe\n",
    "\n",
    "The matching was performed by a manual process (see description).\n",
    "\n",
    "File - > matching_ENTSOE_EU_ETS.csv\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['input\\\\bootom_up_method', 'input\\\\entsoe_gen_type_hourly_table.csv', 'input\\\\entsoe_gen_type_hourly_table_scaled.csv', 'input\\\\gen_data_2018.csv', 'input\\\\matching_ENTSOE_EU_ETS.csv', 'input\\\\top_down_method', 'input\\\\unit_data_2018.csv', 'input\\\\_old_entsoe_gen_type_hourly_table_scaled.csv']\n"
     ]
    }
   ],
   "source": [
    "# Checks if the the input directories are empty or not\n",
    "# Checks all filenames in the input directory\n",
    "if not os.listdir(input_directory_path) :\n",
    "    print(\"The directory for the bootom up method is empty. Please provide the data to the directory as described in the instructions above.\")\n",
    "\n",
    "filenames = [os.path.join(input_directory_path, fn) for fn in os.listdir(input_directory_path)]\n",
    "\n",
    "print(filenames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `input/bottom_up_method` directory (all necessary raw data files for the bottom up method)\n",
    "\n",
    "Based on the developed method the following data sets are needed:\n",
    "\n",
    "- 1) EU Emissions Data (EUTL)\n",
    "\n",
    "Data are provided in the report section of the following web side:\n",
    "https://ec.europa.eu/clima/policies/ets/registry_en#tab-0-1\n",
    "\n",
    "For example: ->Documentation->Reports->Verified Emissions for 2019\n",
    "\n",
    "File - > \"Verified Emissions for 2019\" -> verified_emissions_2018_en.xlsx -> converted to .csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['input\\\\bootom_up_method\\\\verified_emissions_2018_en.csv']\n"
     ]
    }
   ],
   "source": [
    "# Checks if the the input directories are empty or not\n",
    "# Checks all filenames in the input directory\n",
    "\n",
    "if not os.listdir(Bootom_up_method_input_directory_path) :\n",
    "    print(\"The directory for the bootom up method is empty. Please provide the data to the directory as described in the instructions above.\")\n",
    "\n",
    "\n",
    "filenames = [os.path.join(Bootom_up_method_input_directory_path, fn) for fn in os.listdir(Bootom_up_method_input_directory_path)]\n",
    "\n",
    "print(filenames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_matching_data_EU(path, fn):\n",
    "    \"\"\"\n",
    "    Load the matching list for EU power plants with ENTSO-E identifier and the EUTL identifier.\n",
    "        \n",
    "    Parameters\n",
    "    ----------\n",
    "    path: str\n",
    "        path to data\n",
    "    fn : str\n",
    "        filename\n",
    "        \n",
    "    \"\"\"\n",
    "    \n",
    "    df = pd.read_csv(os.path.join(path, fn), sep = ',', header = 0, index_col=0)\n",
    "\n",
    "    return df\n",
    "\n",
    "def load_EUTL_data(path, fn):\n",
    "    \"\"\"\n",
    "    Load the EU emission data (EUTL).\n",
    "        \n",
    "    Parameters\n",
    "    ----------\n",
    "    path: str\n",
    "        path to data\n",
    "    fn : str\n",
    "        filename\n",
    "        \n",
    "    \"\"\"\n",
    "    \n",
    "    df = pd.read_csv(os.path.join(path, fn),sep = ';', header = 13, encoding='ISO-8859-1')\n",
    "\n",
    "    return df\n",
    "\n",
    "def load_generation_per_unit(path, fn):\n",
    "    \"\"\"\n",
    "    Load the ENTSO-E gernation per unit data.\n",
    "        \n",
    "    Parameters\n",
    "    ----------\n",
    "    path: str\n",
    "        path to data\n",
    "    fn : str\n",
    "        filename\n",
    "        \n",
    "    \"\"\"\n",
    "    \n",
    "    generation = pd.read_csv(os.path.join(path, fn),sep = ',',index_col=0,parse_dates=True)\n",
    "    \n",
    "    return generation\n",
    "\n",
    "def load_unit_info(path, fn):\n",
    "    \"\"\"\n",
    "    Load the ENTSO-E generation unit information.\n",
    "        \n",
    "    Parameters\n",
    "    ----------\n",
    "    path: str\n",
    "        path to data\n",
    "    fn : str\n",
    "        filename\n",
    "        \n",
    "    \"\"\"\n",
    "    \n",
    "    df = pd.read_csv(os.path.join(path, fn),sep = ',',index_col=0)\n",
    "    \n",
    "    # Rename production type name according to own convention\n",
    "    df.ProductionTypeName = change_ENTSOE_ProductionTypeName(df.ProductionTypeName)\n",
    "    \n",
    "    # set name for the index\n",
    "    df.index.set_names('GenerationUnitEIC', inplace=True)\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data sets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load power plant generation data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_per_unit_2018 = load_generation_per_unit(input_directory_path, 'gen_data_2018.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load power plant unit inforamtion (capacity, name, etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info = load_unit_info(input_directory_path, 'unit_data_2018.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load CO2_emissions data from EUTL dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "EUTL_emissions = load_EUTL_data(Bootom_up_method_input_directory_path, 'verified_emissions_2018_en.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load machting information for power plant data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "unit_matching_EU = load_matching_data_EU(input_directory_path, 'matching_ENTSOE_EU_ETS.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Emission factor calculation method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following, the EF are calculated step by step. Starting with the matching of the data sets up to the short evaluation of the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preperation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Yearly power generation per unit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Store the yearly generation per power plant to the power plant information data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info['generation_2018'] = generation_per_unit_2018.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Matching ENTSO-E ID and EUTL ID"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Combining matching information (ENTSO-E ID and EUTL ID) to the generation unit info. Keep only matched information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_matched = pd.merge(generation_unit_info, unit_matching_EU, left_on='GenerationUnitEIC', right_on='eic_g', how='inner')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Connecting emissions data to the generation data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a unique identifier from the country code and the plant ID in the emission data set and generation unit data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_matched['Unique_ID'] = generation_unit_info_matched.EUTL_countrycode + generation_unit_info_matched.EUTL_ID.astype(str)\n",
    "EUTL_emissions['Unique_ID'] = EUTL_emissions.REGISTRY_CODE + EUTL_emissions.INSTALLATION_IDENTIFIER.astype(int).astype(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge both datasets and set index to EIC_P"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_matched = generation_unit_info_matched.merge(EUTL_emissions, left_on='Unique_ID', right_on='Unique_ID', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_matched.set_index('eic_g', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Power plant side generation and emissions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function is used to calculate the electricity generation per side. This is done due to the fact, that the EUTL data set has a spatial resolution on site level and not on power plant level it can happen, that power plants data need to be aggregated together in the emission calculation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_side_gen(df, year):\n",
    "    # calculate the electricity generation per side.\n",
    "    side_generation = df.groupby(['EUTL_countrycode','EUTL_ID']).sum()['generation_' + str(year)].reset_index()\n",
    "    \n",
    "    # add side generation to PP dataset\n",
    "    df['side_generation_' + str(year)] = df.apply(lambda x: side_generation.query('EUTL_countrycode == @x.EUTL_countrycode')\\\n",
    "                                                              .query('EUTL_ID == @x.EUTL_ID').iloc[0,2],axis = 1)\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# list for years to be calculated\n",
    "years = [2018]\n",
    "\n",
    "for i in years:\n",
    "    generation_unit_info_matched = calc_side_gen(generation_unit_info_matched, i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimating heat via Free Allocation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To estimate the amount of CO2 allowances that can be allocated to the heat production of a power plant, the entry \"Free Allocation\" is used. The plant operators receive free allowances in relation to the amount of heat they produce. This share is reduced by 10% every year until 2020, starting with 100% for the year 2013. In 2020 they only receive 30% of the required allowances for heat production. Since the amount of CO2 is not directly determined by the produced heat, instead a standard emission factor (benchmark process) is used to determine the amount, which only provides a rough estimate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data type preparation \n",
    "for i in years:\n",
    "    generation_unit_info_matched['ALLOCATION_' + str(i)] = generation_unit_info_matched['ALLOCATION_' + str(i)].apply(str)\n",
    "    generation_unit_info_matched['ALLOCATION_' + str(i)].replace({'Excluded' : 0}, inplace = True)\n",
    "    generation_unit_info_matched['ALLOCATION_' + str(i)].replace({'-1' : 0}, inplace = True)\n",
    "    generation_unit_info_matched['ALLOCATION_' + str(i)] = generation_unit_info_matched['ALLOCATION_' + str(i)].apply(float)\n",
    "    generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)] = generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)].apply(str)\n",
    "    generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)].replace({'Excluded' : 0}, inplace = True)\n",
    "    generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)].replace({'-1' : 0}, inplace = True)\n",
    "    generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)] = generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)].apply(float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimating heat via Free Allocation, in 2018 only 50% was free for public heat generation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in years:\n",
    "    generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)] = generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)] - ((generation_unit_info_matched['ALLOCATION_' + str(i)] / 50) * 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Emission factor per power plant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculates emissions and EF for each PP."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in years:\n",
    "    generation_unit_info_matched['PP_emissions_' + str(i)] = (generation_unit_info_matched['VERIFIED_EMISSIONS_' + str(i)] / generation_unit_info_matched['side_generation_' + str(i)]) * generation_unit_info_matched['generation_' + str(i)] \n",
    "    generation_unit_info_matched['PP_EF' + str(i)] = generation_unit_info_matched['PP_emissions_' + str(i)] / generation_unit_info_matched['generation_' + str(i)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Show first 5 entries from data.\n",
    "\n",
    "Attention, the verified_emissions_* per power plant are always site-related (eic_p), if there are several power plants at one site, the emissions have to be distributed among the power plants. (see. PP_emissions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AreaCode</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>AreaTypeCode</th>\n",
       "      <th>InstalledGenCapacity</th>\n",
       "      <th>MapCode</th>\n",
       "      <th>PowerSystemResourceName</th>\n",
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       "      <th>ALLOCATION_2009</th>\n",
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       "      <th>ALLOCATION_2008</th>\n",
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       "      <th>side_generation_2018</th>\n",
       "      <th>PP_emissions_2018</th>\n",
       "      <th>PP_EF2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eic_g</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14W-GEN-LAU----Z</th>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>140.0</td>\n",
       "      <td>AT</td>\n",
       "      <td>Lau GuD</td>\n",
       "      <td>gas</td>\n",
       "      <td>14W-PROD-LAU---8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>304721</td>\n",
       "      <td>206265</td>\n",
       "      <td>304721</td>\n",
       "      <td>118982</td>\n",
       "      <td>304721</td>\n",
       "      <td>256284</td>\n",
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       "      <td>0.00</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>14WENERGIEAGWT4S</th>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
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       "      <td>400.0</td>\n",
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       "      <td>14WENERGIE--WT02</td>\n",
       "      <td>2.0</td>\n",
       "      <td>685235.67</td>\n",
       "      <td>...</td>\n",
       "      <td>681283</td>\n",
       "      <td>580029</td>\n",
       "      <td>681283</td>\n",
       "      <td>340026</td>\n",
       "      <td>218704</td>\n",
       "      <td>103553</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>685235.67</td>\n",
       "      <td>254778.000000</td>\n",
       "      <td>0.371811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14W-KW-DUE-EVN-A</th>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>332.0</td>\n",
       "      <td>AT</td>\n",
       "      <td>KW Dürnrohr Block 2</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>14W-KW-DU2-EVN-K</td>\n",
       "      <td>2.0</td>\n",
       "      <td>745290.41</td>\n",
       "      <td>...</td>\n",
       "      <td>1139438</td>\n",
       "      <td>1592747</td>\n",
       "      <td>1139438</td>\n",
       "      <td>899251</td>\n",
       "      <td>1139438</td>\n",
       "      <td>1435406</td>\n",
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       "      <td>745290.41</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14WENERGIEAGWR21</th>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>150.0</td>\n",
       "      <td>AT</td>\n",
       "      <td>KW Riedersbach 2 G2</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>14WENERGIEAGWR05</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>437140</td>\n",
       "      <td>310019</td>\n",
       "      <td>437140</td>\n",
       "      <td>342118</td>\n",
       "      <td>437140</td>\n",
       "      <td>730397</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000029I</th>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>250.0</td>\n",
       "      <td>DK</td>\n",
       "      <td>Avedoerevaerket 1</td>\n",
       "      <td>biomass</td>\n",
       "      <td>45V0000000000091</td>\n",
       "      <td>1.0</td>\n",
       "      <td>646873.95</td>\n",
       "      <td>...</td>\n",
       "      <td>1763671</td>\n",
       "      <td>1625381</td>\n",
       "      <td>1763671</td>\n",
       "      <td>1772512</td>\n",
       "      <td>1763673</td>\n",
       "      <td>1890106</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>2025224.37</td>\n",
       "      <td>-143410.918928</td>\n",
       "      <td>-0.221698</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
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      ],
      "text/plain": [
       "                          AreaCode      AreaName AreaTypeCode  \\\n",
       "eic_g                                                           \n",
       "14W-GEN-LAU----Z  10YAT-APG------L        APG CA          CTA   \n",
       "14WENERGIEAGWT4S  10YAT-APG------L        APG CA          CTA   \n",
       "14W-KW-DUE-EVN-A  10YAT-APG------L        APG CA          CTA   \n",
       "14WENERGIEAGWR21  10YAT-APG------L        APG CA          CTA   \n",
       "45W000000000029I  10Y1001A1001A796  Energinet CA          CTA   \n",
       "\n",
       "                  InstalledGenCapacity MapCode PowerSystemResourceName  \\\n",
       "eic_g                                                                    \n",
       "14W-GEN-LAU----Z                 140.0      AT                 Lau GuD   \n",
       "14WENERGIEAGWT4S                 400.0      AT  Kraftwerk Timelkam GUD   \n",
       "14W-KW-DUE-EVN-A                 332.0      AT     KW Dürnrohr Block 2   \n",
       "14WENERGIEAGWR21                 150.0      AT     KW Riedersbach 2 G2   \n",
       "45W000000000029I                 250.0      DK       Avedoerevaerket 1   \n",
       "\n",
       "                 ProductionTypeName ProductionUnitEIC  duplicate_count  \\\n",
       "eic_g                                                                    \n",
       "14W-GEN-LAU----Z                gas  14W-PROD-LAU---8              2.0   \n",
       "14WENERGIEAGWT4S                gas  14WENERGIE--WT02              2.0   \n",
       "14W-KW-DUE-EVN-A          hard_coal  14W-KW-DU2-EVN-K              2.0   \n",
       "14WENERGIEAGWR21          hard_coal  14WENERGIEAGWR05              2.0   \n",
       "45W000000000029I            biomass  45V0000000000091              1.0   \n",
       "\n",
       "                  generation_2018  ... ALLOCATION_2010  \\\n",
       "eic_g                              ...                   \n",
       "14W-GEN-LAU----Z             0.00  ...          304721   \n",
       "14WENERGIEAGWT4S        685235.67  ...          681283   \n",
       "14W-KW-DUE-EVN-A        745290.41  ...         1139438   \n",
       "14WENERGIEAGWR21             0.00  ...          437140   \n",
       "45W000000000029I        646873.95  ...         1763671   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2010  ALLOCATION_2009  \\\n",
       "eic_g                                                       \n",
       "14W-GEN-LAU----Z                  206265           304721   \n",
       "14WENERGIEAGWT4S                  580029           681283   \n",
       "14W-KW-DUE-EVN-A                 1592747          1139438   \n",
       "14WENERGIEAGWR21                  310019           437140   \n",
       "45W000000000029I                 1625381          1763671   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2009 ALLOCATION_2008  \\\n",
       "eic_g                                                      \n",
       "14W-GEN-LAU----Z                  118982          304721   \n",
       "14WENERGIEAGWT4S                  340026          218704   \n",
       "14W-KW-DUE-EVN-A                  899251         1139438   \n",
       "14WENERGIEAGWR21                  342118          437140   \n",
       "45W000000000029I                 1772512         1763673   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2008 ACCOUNT_CLOSURE  \\\n",
       "eic_g                                                      \n",
       "14W-GEN-LAU----Z                  256284            OPEN   \n",
       "14WENERGIEAGWT4S                  103553            OPEN   \n",
       "14W-KW-DUE-EVN-A                 1435406            OPEN   \n",
       "14WENERGIEAGWR21                  730397            OPEN   \n",
       "45W000000000029I                 1890106            OPEN   \n",
       "\n",
       "                  side_generation_2018 PP_emissions_2018  PP_EF2018  \n",
       "eic_g                                                                \n",
       "14W-GEN-LAU----Z                  0.00               NaN        NaN  \n",
       "14WENERGIEAGWT4S             685235.67     254778.000000   0.371811  \n",
       "14W-KW-DUE-EVN-A             745290.41          0.000000   0.000000  \n",
       "14WENERGIEAGWR21                  0.00               NaN        NaN  \n",
       "45W000000000029I            2025224.37    -143410.918928  -0.221698  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_matched.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "      <td>96.39419</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>46WGU0000000001C</th>\n",
       "      <td>10YSE-1--------K</td>\n",
       "      <td>SvK CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>250.0</td>\n",
       "      <td>SE</td>\n",
       "      <td>Rya KVV</td>\n",
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       "      <td>46WPU0000000062N</td>\n",
       "      <td>2.0</td>\n",
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      "text/plain": [
       "                          AreaCode AreaName AreaTypeCode  \\\n",
       "eic_g                                                      \n",
       "46WGU0000000018W  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU0000000019U  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU00000000062  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU0000000001C  10YSE-1--------K   SvK CA          CTA   \n",
       "\n",
       "                  InstalledGenCapacity MapCode PowerSystemResourceName  \\\n",
       "eic_g                                                                    \n",
       "46WGU0000000018W                 335.0      SE            Karlshamn G2   \n",
       "46WGU0000000019U                 335.0      SE            Karlshamn G3   \n",
       "46WGU00000000062                 130.0      SE       KVV6 Värtaverket    \n",
       "46WGU0000000001C                 250.0      SE                 Rya KVV   \n",
       "\n",
       "                 ProductionTypeName ProductionUnitEIC  duplicate_count  \\\n",
       "eic_g                                                                    \n",
       "46WGU0000000018W       other_fossil  46WPU0000000005Z              1.0   \n",
       "46WGU0000000019U       other_fossil  46WPU0000000005Z              1.0   \n",
       "46WGU00000000062          hard_coal  46WPU0000000023X              2.0   \n",
       "46WGU0000000001C                gas  46WPU0000000062N              2.0   \n",
       "\n",
       "                  generation_2018  ... ALLOCATION_2010  \\\n",
       "eic_g                              ...                   \n",
       "46WGU0000000018W           4729.4  ...               0   \n",
       "46WGU0000000019U           2967.9  ...               0   \n",
       "46WGU00000000062         378460.9  ...               0   \n",
       "46WGU0000000001C         408286.3  ...          587495   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2010  ALLOCATION_2009  \\\n",
       "eic_g                                                       \n",
       "46WGU0000000018W                     354                0   \n",
       "46WGU0000000019U                     354                0   \n",
       "46WGU00000000062                  883333                0   \n",
       "46WGU0000000001C                  501684           616194   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2009 ALLOCATION_2008  \\\n",
       "eic_g                                                      \n",
       "46WGU0000000018W                     110               0   \n",
       "46WGU0000000019U                     110               0   \n",
       "46WGU00000000062                  740342               0   \n",
       "46WGU0000000001C                  481717          612891   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2008 ACCOUNT_CLOSURE  \\\n",
       "eic_g                                                      \n",
       "46WGU0000000018W                     135            OPEN   \n",
       "46WGU0000000019U                     135            OPEN   \n",
       "46WGU00000000062                  610389            OPEN   \n",
       "46WGU0000000001C                  278444            OPEN   \n",
       "\n",
       "                  side_generation_2018 PP_emissions_2018  PP_EF2018  \n",
       "eic_g                                                                \n",
       "46WGU0000000018W                7697.3         153.60581   0.032479  \n",
       "46WGU0000000019U                7697.3          96.39419   0.032479  \n",
       "46WGU00000000062              378460.9      112022.00000   0.295994  \n",
       "46WGU0000000001C              408286.3      147720.00000   0.361805  \n",
       "\n",
       "[4 rows x 58 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_matched[generation_unit_info_matched.MapCode == 'SE']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Validation of emission factor per power plant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check and test the resulting EF. Drop EFs that are not plausible.\n",
    "\n",
    "Which technologies are covered in the data set?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['gas', 'hard_coal', 'biomass', 'other_fossil', 'lignite'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_matched.ProductionTypeName.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take only the following technologies:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "tech = ['gas', 'hard_coal', 'lignite', 'other_fossil']\n",
    "generation_unit_info_matched = generation_unit_info_matched.query('ProductionTypeName in @tech')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since not all emission factors are correctly calculated we limited the list of calculated EF by performing a plausibility check. We are using numbers from a review LCA study, that list an emission space for different electricity generation technologies.\n",
    "\n",
    "NREL Life Cycle Greenhouse Gas Emissions from Electricity Generation: Update. 2021.\n",
    "https://www.nrel.gov/analysis/life-cycle-assessment.html\n",
    "\n",
    "\n",
    "Some other comparison numbers:\n",
    "https://www.gegenwind-saarland.de/Materialien/Energiewende/071031--VdI---CO2-Emissionen%20der%20Stromerzeugung_01.pdf\n",
    "\n",
    "https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/2020-04-01_climate-change_13-2020_strommix_2020_fin.pdf\n",
    "\n",
    "https://pubs.acs.org/doi/abs/10.1021/acs.energyfuels.0c02139?casa_token=_4Oq5U-mprsAAAAA:zIU2Hy1aNDXoX7poLUfG34AhUPykjiwvg75JLaoJAC0F_uvwH7YGc_QnP6X9qBwjlge7Y_FrbJ3kiic\n",
    "\n",
    "https://www.sciencedirect.com/science/article/abs/pii/S1364032113005534"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# emissions space per technology in [t CO2/MWh] \n",
    "\n",
    "emission_space = {\"lignite\": (1.700,0.675),\n",
    "                  \"hard_coal\": (1.700,0.675),\n",
    "                  \"gas\": (1.000,0.300),\n",
    "                  \"other_fossil\": (1.700,0.300)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function for EF check\n",
    "def check_EF (PP_EF, ProductionTypeName):\n",
    "    if PP_EF > emission_space[ProductionTypeName][1] and PP_EF < emission_space[ProductionTypeName][0]:\n",
    "        return True\n",
    "    else:\n",
    "        return False  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# apply check_EF function for EF validation\n",
    "for i in years:\n",
    "    generation_unit_info_matched['EF_' + str(i) + '_validation'] = generation_unit_info_matched.apply(lambda x: check_EF(x['PP_EF' + str(i)], x['ProductionTypeName']), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AreaCode</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>AreaTypeCode</th>\n",
       "      <th>InstalledGenCapacity</th>\n",
       "      <th>MapCode</th>\n",
       "      <th>PowerSystemResourceName</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>ProductionUnitEIC</th>\n",
       "      <th>duplicate_count</th>\n",
       "      <th>generation_2018</th>\n",
       "      <th>...</th>\n",
       "      <th>VERIFIED_EMISSIONS_2010</th>\n",
       "      <th>ALLOCATION_2009</th>\n",
       "      <th>VERIFIED_EMISSIONS_2009</th>\n",
       "      <th>ALLOCATION_2008</th>\n",
       "      <th>VERIFIED_EMISSIONS_2008</th>\n",
       "      <th>ACCOUNT_CLOSURE</th>\n",
       "      <th>side_generation_2018</th>\n",
       "      <th>PP_emissions_2018</th>\n",
       "      <th>PP_EF2018</th>\n",
       "      <th>EF_2018_validation</th>\n",
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       "    <tr>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46WGU0000000018W</th>\n",
       "      <td>10YSE-1--------K</td>\n",
       "      <td>SvK CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>335.0</td>\n",
       "      <td>SE</td>\n",
       "      <td>Karlshamn G2</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>46WPU0000000005Z</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4729.4</td>\n",
       "      <td>...</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>110</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>7697.3</td>\n",
       "      <td>153.60581</td>\n",
       "      <td>0.032479</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
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       "      <td>10YSE-1--------K</td>\n",
       "      <td>SvK CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>335.0</td>\n",
       "      <td>SE</td>\n",
       "      <td>Karlshamn G3</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>46WPU0000000005Z</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2967.9</td>\n",
       "      <td>...</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>110</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>7697.3</td>\n",
       "      <td>96.39419</td>\n",
       "      <td>0.032479</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46WGU00000000062</th>\n",
       "      <td>10YSE-1--------K</td>\n",
       "      <td>SvK CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>130.0</td>\n",
       "      <td>SE</td>\n",
       "      <td>KVV6 Värtaverket</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>46WPU0000000023X</td>\n",
       "      <td>2.0</td>\n",
       "      <td>378460.9</td>\n",
       "      <td>...</td>\n",
       "      <td>883333</td>\n",
       "      <td>0</td>\n",
       "      <td>740342</td>\n",
       "      <td>0</td>\n",
       "      <td>610389</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>378460.9</td>\n",
       "      <td>112022.00000</td>\n",
       "      <td>0.295994</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>46WGU0000000001C</th>\n",
       "      <td>10YSE-1--------K</td>\n",
       "      <td>SvK CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>250.0</td>\n",
       "      <td>SE</td>\n",
       "      <td>Rya KVV</td>\n",
       "      <td>gas</td>\n",
       "      <td>46WPU0000000062N</td>\n",
       "      <td>2.0</td>\n",
       "      <td>408286.3</td>\n",
       "      <td>...</td>\n",
       "      <td>501684</td>\n",
       "      <td>616194</td>\n",
       "      <td>481717</td>\n",
       "      <td>612891</td>\n",
       "      <td>278444</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>408286.3</td>\n",
       "      <td>147720.00000</td>\n",
       "      <td>0.361805</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          AreaCode AreaName AreaTypeCode  \\\n",
       "eic_g                                                      \n",
       "46WGU0000000018W  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU0000000019U  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU00000000062  10YSE-1--------K   SvK CA          CTA   \n",
       "46WGU0000000001C  10YSE-1--------K   SvK CA          CTA   \n",
       "\n",
       "                  InstalledGenCapacity MapCode PowerSystemResourceName  \\\n",
       "eic_g                                                                    \n",
       "46WGU0000000018W                 335.0      SE            Karlshamn G2   \n",
       "46WGU0000000019U                 335.0      SE            Karlshamn G3   \n",
       "46WGU00000000062                 130.0      SE       KVV6 Värtaverket    \n",
       "46WGU0000000001C                 250.0      SE                 Rya KVV   \n",
       "\n",
       "                 ProductionTypeName ProductionUnitEIC  duplicate_count  \\\n",
       "eic_g                                                                    \n",
       "46WGU0000000018W       other_fossil  46WPU0000000005Z              1.0   \n",
       "46WGU0000000019U       other_fossil  46WPU0000000005Z              1.0   \n",
       "46WGU00000000062          hard_coal  46WPU0000000023X              2.0   \n",
       "46WGU0000000001C                gas  46WPU0000000062N              2.0   \n",
       "\n",
       "                  generation_2018  ... VERIFIED_EMISSIONS_2010  \\\n",
       "eic_g                              ...                           \n",
       "46WGU0000000018W           4729.4  ...                     354   \n",
       "46WGU0000000019U           2967.9  ...                     354   \n",
       "46WGU00000000062         378460.9  ...                  883333   \n",
       "46WGU0000000001C         408286.3  ...                  501684   \n",
       "\n",
       "                 ALLOCATION_2009  VERIFIED_EMISSIONS_2009 ALLOCATION_2008  \\\n",
       "eic_g                                                                       \n",
       "46WGU0000000018W               0                      110               0   \n",
       "46WGU0000000019U               0                      110               0   \n",
       "46WGU00000000062               0                   740342               0   \n",
       "46WGU0000000001C          616194                   481717          612891   \n",
       "\n",
       "                 VERIFIED_EMISSIONS_2008 ACCOUNT_CLOSURE side_generation_2018  \\\n",
       "eic_g                                                                           \n",
       "46WGU0000000018W                     135            OPEN               7697.3   \n",
       "46WGU0000000019U                     135            OPEN               7697.3   \n",
       "46WGU00000000062                  610389            OPEN             378460.9   \n",
       "46WGU0000000001C                  278444            OPEN             408286.3   \n",
       "\n",
       "                  PP_emissions_2018 PP_EF2018  EF_2018_validation  \n",
       "eic_g                                                              \n",
       "46WGU0000000018W          153.60581  0.032479               False  \n",
       "46WGU0000000019U           96.39419  0.032479               False  \n",
       "46WGU00000000062       112022.00000  0.295994               False  \n",
       "46WGU0000000001C       147720.00000  0.361805                True  \n",
       "\n",
       "[4 rows x 59 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_matched[generation_unit_info_matched.MapCode == 'SE']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Limit the results to validated data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for more years using -> & [(generation_unit_info_matched.EF_2016_validation == True) & (generation_unit_info_matched.EF_2018_validation == True)]\n",
    "generation_unit_info_validated = generation_unit_info_matched[(generation_unit_info_matched.EF_2018_validation == True)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the calculation is based on some assumptions, as a result, the EF may be incorrect. In the following we list the three most important points:\n",
    "\n",
    "1.) Match of generation and emission data is not correct\n",
    "\n",
    "2.) Data is wrong or incomplete\n",
    "\n",
    "3.) Match is correct, but it's a highly aggregated facility such like a steel manufacturing factory, where both process-CO2 AND the emissions from the power plant running the process accounts into the number given in the dataset.\n",
    "\n",
    "4.) the facility contains more smaller power plants which are not covered by ENTSO-E (<100MW) but nevertheless produce emissions which need to be paid for.\n",
    "\n",
    "5.) if the number of the carbon-intensity is negative, then the dataset is explained as \" -1 = blank (No allocation has been made / No Emissions have been Verified)\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot EF per technology"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "generation_unit_info_validated_plot = generation_unit_info_validated[['ProductionTypeName','PP_EF2018','EUTL_countrycode']].copy()\n",
    "\n",
    "# convert to g CO2 / kWh\n",
    "generation_unit_info_validated_plot.PP_EF2018 = generation_unit_info_validated_plot.PP_EF2018 * 1000\n",
    "\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "ax = sns.boxplot(x=\"ProductionTypeName\", y=\"PP_EF2018\", data=generation_unit_info_validated_plot, orient=\"v\",\n",
    "                 linewidth=4, dodge=True, showfliers=False, showbox=True, showmeans=False, meanline=False,\n",
    "                order=['gas','hard_coal','lignite','other_fossil'])\n",
    "\n",
    "ax = sns.stripplot(x=\"ProductionTypeName\", y=\"PP_EF2018\", data=generation_unit_info_validated_plot, color=\".25\", orient=\"v\", size=7, jitter=0.28, palette=['#91bfdb'],edgecolor='black',\n",
    "                  linewidth=1, dodge=True, order=['gas','hard_coal','lignite','other_fossil'])\n",
    "\n",
    "ax.set_xlabel(\"Production technology\", fontsize=26)\n",
    "ax.set_ylabel(\"CO2 intensity (g CO2/kWh)\" , fontsize=26)\n",
    "\n",
    "ax.tick_params(axis='x',labelsize=24)\n",
    "ax.tick_params(axis='y',labelsize=24)\n",
    "\n",
    "labels = ['Gas','Coal','Lignite','Other fossil']\n",
    "\n",
    "ax.set_xticklabels(labels)\n",
    "\n",
    "fig.tight_layout()\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>PP_EF2018</th>\n",
       "      <th>EUTL_countrycode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eic_g</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14WENERGIEAGWT4S</th>\n",
       "      <td>gas</td>\n",
       "      <td>371.810767</td>\n",
       "      <td>AT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000032T</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>922.057307</td>\n",
       "      <td>DK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000033R</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>922.057307</td>\n",
       "      <td>DK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000034P</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>727.577153</td>\n",
       "      <td>DK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000040U</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>774.616953</td>\n",
       "      <td>DK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48W00000EGGPS-4R</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1095.419625</td>\n",
       "      <td>GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48W00000EGGPS-3T</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1095.419625</td>\n",
       "      <td>GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48W00000EGGPS-2V</th>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1095.419625</td>\n",
       "      <td>GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48W000000SUTB-1P</th>\n",
       "      <td>gas</td>\n",
       "      <td>550.843115</td>\n",
       "      <td>GB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48W000000DEEP-1N</th>\n",
       "      <td>gas</td>\n",
       "      <td>432.746829</td>\n",
       "      <td>GB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>595 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ProductionTypeName    PP_EF2018 EUTL_countrycode\n",
       "eic_g                                                            \n",
       "14WENERGIEAGWT4S                gas   371.810767               AT\n",
       "45W000000000032T          hard_coal   922.057307               DK\n",
       "45W000000000033R          hard_coal   922.057307               DK\n",
       "45W000000000034P          hard_coal   727.577153               DK\n",
       "45W000000000040U          hard_coal   774.616953               DK\n",
       "...                             ...          ...              ...\n",
       "48W00000EGGPS-4R          hard_coal  1095.419625               GB\n",
       "48W00000EGGPS-3T          hard_coal  1095.419625               GB\n",
       "48W00000EGGPS-2V          hard_coal  1095.419625               GB\n",
       "48W000000SUTB-1P                gas   550.843115               GB\n",
       "48W000000DEEP-1N                gas   432.746829               GB\n",
       "\n",
       "[595 rows x 3 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_validated_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig(os.path.join(output_directory_path + '/_CO2_intensity_by_technology.png'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_validated.to_csv(processed_directory_path + '/generation_unit_EF_bottom_up_method.csv')\n",
    "generation_unit_info_validated.to_csv(output_directory_path + '/generation_unit_EF_bottom_up_method.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Emission factor per technology and country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following section we calculate a mean EFs for each technology in all countries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### EF per technology and country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grouping generation\n",
    "generation_per_tech_country = generation_unit_info_validated.groupby(['EUTL_countrycode','ProductionTypeName']).sum()[['generation_2018','PP_emissions_2018']]\n",
    "# cal. EF per tech and country\n",
    "EF_per_tech_country = generation_per_tech_country.PP_emissions_2018 / generation_per_tech_country.generation_2018"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add technology specific EF for each country to the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset index\n",
    "generation_unit_info_validated.reset_index(inplace=True)\n",
    "\n",
    "# set new index for maping function \n",
    "generation_unit_info_EF_tech = generation_unit_info_validated.set_index(['EUTL_countrycode','ProductionTypeName'])\n",
    "\n",
    "# map the EF to the data set\n",
    "generation_unit_info_EF_tech['Tech_EF'] = generation_unit_info_EF_tech.index.map(EF_per_tech_country.to_dict())\n",
    "\n",
    "#reset index\n",
    "generation_unit_info_EF_tech.reset_index(inplace=True)\n",
    "\n",
    "#set old index\n",
    "generation_unit_info_EF_tech.set_index(['eic_g'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EUTL_countrycode</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>AreaCode</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>AreaTypeCode</th>\n",
       "      <th>InstalledGenCapacity</th>\n",
       "      <th>MapCode</th>\n",
       "      <th>PowerSystemResourceName</th>\n",
       "      <th>ProductionUnitEIC</th>\n",
       "      <th>duplicate_count</th>\n",
       "      <th>...</th>\n",
       "      <th>ALLOCATION_2009</th>\n",
       "      <th>VERIFIED_EMISSIONS_2009</th>\n",
       "      <th>ALLOCATION_2008</th>\n",
       "      <th>VERIFIED_EMISSIONS_2008</th>\n",
       "      <th>ACCOUNT_CLOSURE</th>\n",
       "      <th>side_generation_2018</th>\n",
       "      <th>PP_emissions_2018</th>\n",
       "      <th>PP_EF2018</th>\n",
       "      <th>EF_2018_validation</th>\n",
       "      <th>Tech_EF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eic_g</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <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",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14WENERGIEAGWT4S</th>\n",
       "      <td>AT</td>\n",
       "      <td>gas</td>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>400.0</td>\n",
       "      <td>AT</td>\n",
       "      <td>Kraftwerk Timelkam GUD</td>\n",
       "      <td>14WENERGIE--WT02</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>681283</td>\n",
       "      <td>340026</td>\n",
       "      <td>218704</td>\n",
       "      <td>103553</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>685235.67</td>\n",
       "      <td>254778.000000</td>\n",
       "      <td>0.371811</td>\n",
       "      <td>True</td>\n",
       "      <td>0.398292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000032T</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>147.0</td>\n",
       "      <td>DK</td>\n",
       "      <td>Asnaesvaerket 2</td>\n",
       "      <td>45V000000000011E</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1765314</td>\n",
       "      <td>2430356</td>\n",
       "      <td>1765318</td>\n",
       "      <td>2484733</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>770018.30</td>\n",
       "      <td>202216.305002</td>\n",
       "      <td>0.922057</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000033R</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>640.0</td>\n",
       "      <td>DK</td>\n",
       "      <td>Asnaesvaerket 5</td>\n",
       "      <td>45V000000000011E</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1765314</td>\n",
       "      <td>2430356</td>\n",
       "      <td>1765318</td>\n",
       "      <td>2484733</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>770018.30</td>\n",
       "      <td>507784.694998</td>\n",
       "      <td>0.922057</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000034P</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>250.0</td>\n",
       "      <td>DK</td>\n",
       "      <td>Amagervaerket 3</td>\n",
       "      <td>45V000000000012C</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1250992</td>\n",
       "      <td>1684995</td>\n",
       "      <td>1250995</td>\n",
       "      <td>1089604</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>1060165.23</td>\n",
       "      <td>771352.000000</td>\n",
       "      <td>0.727577</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000040U</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>377.0</td>\n",
       "      <td>DK</td>\n",
       "      <td>Esbjergvaerket 3</td>\n",
       "      <td>45V0000000000164</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1051487</td>\n",
       "      <td>1318927</td>\n",
       "      <td>1051489</td>\n",
       "      <td>1158930</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>1193633.83</td>\n",
       "      <td>924609.000000</td>\n",
       "      <td>0.774617</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 EUTL_countrycode ProductionTypeName          AreaCode  \\\n",
       "eic_g                                                                    \n",
       "14WENERGIEAGWT4S               AT                gas  10YAT-APG------L   \n",
       "45W000000000032T               DK          hard_coal  10Y1001A1001A796   \n",
       "45W000000000033R               DK          hard_coal  10Y1001A1001A796   \n",
       "45W000000000034P               DK          hard_coal  10Y1001A1001A796   \n",
       "45W000000000040U               DK          hard_coal  10Y1001A1001A796   \n",
       "\n",
       "                      AreaName AreaTypeCode  InstalledGenCapacity MapCode  \\\n",
       "eic_g                                                                       \n",
       "14WENERGIEAGWT4S        APG CA          CTA                 400.0      AT   \n",
       "45W000000000032T  Energinet CA          CTA                 147.0      DK   \n",
       "45W000000000033R  Energinet CA          CTA                 640.0      DK   \n",
       "45W000000000034P  Energinet CA          CTA                 250.0      DK   \n",
       "45W000000000040U  Energinet CA          CTA                 377.0      DK   \n",
       "\n",
       "                 PowerSystemResourceName ProductionUnitEIC  duplicate_count  \\\n",
       "eic_g                                                                         \n",
       "14WENERGIEAGWT4S  Kraftwerk Timelkam GUD  14WENERGIE--WT02              2.0   \n",
       "45W000000000032T         Asnaesvaerket 2  45V000000000011E              1.0   \n",
       "45W000000000033R         Asnaesvaerket 5  45V000000000011E              1.0   \n",
       "45W000000000034P         Amagervaerket 3  45V000000000012C              1.0   \n",
       "45W000000000040U        Esbjergvaerket 3  45V0000000000164              1.0   \n",
       "\n",
       "                  ...  ALLOCATION_2009 VERIFIED_EMISSIONS_2009  \\\n",
       "eic_g             ...                                            \n",
       "14WENERGIEAGWT4S  ...           681283                  340026   \n",
       "45W000000000032T  ...          1765314                 2430356   \n",
       "45W000000000033R  ...          1765314                 2430356   \n",
       "45W000000000034P  ...          1250992                 1684995   \n",
       "45W000000000040U  ...          1051487                 1318927   \n",
       "\n",
       "                  ALLOCATION_2008 VERIFIED_EMISSIONS_2008 ACCOUNT_CLOSURE  \\\n",
       "eic_g                                                                       \n",
       "14WENERGIEAGWT4S           218704                  103553            OPEN   \n",
       "45W000000000032T          1765318                 2484733            OPEN   \n",
       "45W000000000033R          1765318                 2484733            OPEN   \n",
       "45W000000000034P          1250995                 1089604            OPEN   \n",
       "45W000000000040U          1051489                 1158930            OPEN   \n",
       "\n",
       "                 side_generation_2018 PP_emissions_2018  PP_EF2018  \\\n",
       "eic_g                                                                \n",
       "14WENERGIEAGWT4S            685235.67     254778.000000   0.371811   \n",
       "45W000000000032T            770018.30     202216.305002   0.922057   \n",
       "45W000000000033R            770018.30     507784.694998   0.922057   \n",
       "45W000000000034P           1060165.23     771352.000000   0.727577   \n",
       "45W000000000040U           1193633.83     924609.000000   0.774617   \n",
       "\n",
       "                 EF_2018_validation   Tech_EF  \n",
       "eic_g                                          \n",
       "14WENERGIEAGWT4S               True  0.398292  \n",
       "45W000000000032T               True  0.775840  \n",
       "45W000000000033R               True  0.775840  \n",
       "45W000000000034P               True  0.775840  \n",
       "45W000000000040U               True  0.775840  \n",
       "\n",
       "[5 rows x 60 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_EF_tech.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_EF_tech.to_csv(processed_directory_path + '/generation_unit_EF_bottom_up_method.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Emission factor per country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following section we calculate a mean EFs for each country."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### EF per technology and country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grouping generation\n",
    "generation_per_country = generation_unit_info_validated.groupby(['EUTL_countrycode']).sum()[['generation_2018','PP_emissions_2018']]\n",
    "# cal. EF per country\n",
    "EF_per_country = generation_per_country.PP_emissions_2018 / generation_per_country.generation_2018"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add country specific EF to the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset index\n",
    "generation_unit_info_EF_tech.reset_index(inplace=True)\n",
    "\n",
    "# set new index for maping function \n",
    "generation_unit_info_EF_country = generation_unit_info_EF_tech.set_index(['MapCode'])\n",
    "\n",
    "# map the EF to the data set\n",
    "generation_unit_info_EF_country['Country_EF'] = generation_unit_info_EF_country.index.map(EF_per_country.to_dict())\n",
    "\n",
    "#reset index\n",
    "generation_unit_info_EF_country.reset_index(inplace=True)\n",
    "\n",
    "#set old index\n",
    "generation_unit_info_EF_country.set_index(['eic_g'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MapCode</th>\n",
       "      <th>EUTL_countrycode</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>AreaCode</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>AreaTypeCode</th>\n",
       "      <th>InstalledGenCapacity</th>\n",
       "      <th>PowerSystemResourceName</th>\n",
       "      <th>ProductionUnitEIC</th>\n",
       "      <th>duplicate_count</th>\n",
       "      <th>...</th>\n",
       "      <th>VERIFIED_EMISSIONS_2009</th>\n",
       "      <th>ALLOCATION_2008</th>\n",
       "      <th>VERIFIED_EMISSIONS_2008</th>\n",
       "      <th>ACCOUNT_CLOSURE</th>\n",
       "      <th>side_generation_2018</th>\n",
       "      <th>PP_emissions_2018</th>\n",
       "      <th>PP_EF2018</th>\n",
       "      <th>EF_2018_validation</th>\n",
       "      <th>Tech_EF</th>\n",
       "      <th>Country_EF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eic_g</th>\n",
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       "      <th>14WENERGIEAGWT4S</th>\n",
       "      <td>AT</td>\n",
       "      <td>AT</td>\n",
       "      <td>gas</td>\n",
       "      <td>10YAT-APG------L</td>\n",
       "      <td>APG CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>400.0</td>\n",
       "      <td>Kraftwerk Timelkam GUD</td>\n",
       "      <td>14WENERGIE--WT02</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>218704</td>\n",
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       "      <td>685235.67</td>\n",
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       "      <th>45W000000000032T</th>\n",
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       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>147.0</td>\n",
       "      <td>Asnaesvaerket 2</td>\n",
       "      <td>45V000000000011E</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2430356</td>\n",
       "      <td>1765318</td>\n",
       "      <td>2484733</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>770018.30</td>\n",
       "      <td>202216.305002</td>\n",
       "      <td>0.922057</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "      <td>0.751762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45W000000000033R</th>\n",
       "      <td>DK</td>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
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       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>640.0</td>\n",
       "      <td>Asnaesvaerket 5</td>\n",
       "      <td>45V000000000011E</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
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       "      <th>45W000000000034P</th>\n",
       "      <td>DK</td>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>10Y1001A1001A796</td>\n",
       "      <td>Energinet CA</td>\n",
       "      <td>CTA</td>\n",
       "      <td>250.0</td>\n",
       "      <td>Amagervaerket 3</td>\n",
       "      <td>45V000000000012C</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1684995</td>\n",
       "      <td>1250995</td>\n",
       "      <td>1089604</td>\n",
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       "      <td>True</td>\n",
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       "      <td>DK</td>\n",
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       "      <td>CTA</td>\n",
       "      <td>377.0</td>\n",
       "      <td>Esbjergvaerket 3</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>1193633.83</td>\n",
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       "      <td>True</td>\n",
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       "<p>5 rows × 61 columns</p>\n",
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      ],
      "text/plain": [
       "                 MapCode EUTL_countrycode ProductionTypeName  \\\n",
       "eic_g                                                          \n",
       "14WENERGIEAGWT4S      AT               AT                gas   \n",
       "45W000000000032T      DK               DK          hard_coal   \n",
       "45W000000000033R      DK               DK          hard_coal   \n",
       "45W000000000034P      DK               DK          hard_coal   \n",
       "45W000000000040U      DK               DK          hard_coal   \n",
       "\n",
       "                          AreaCode      AreaName AreaTypeCode  \\\n",
       "eic_g                                                           \n",
       "14WENERGIEAGWT4S  10YAT-APG------L        APG CA          CTA   \n",
       "45W000000000032T  10Y1001A1001A796  Energinet CA          CTA   \n",
       "45W000000000033R  10Y1001A1001A796  Energinet CA          CTA   \n",
       "45W000000000034P  10Y1001A1001A796  Energinet CA          CTA   \n",
       "45W000000000040U  10Y1001A1001A796  Energinet CA          CTA   \n",
       "\n",
       "                  InstalledGenCapacity PowerSystemResourceName  \\\n",
       "eic_g                                                            \n",
       "14WENERGIEAGWT4S                 400.0  Kraftwerk Timelkam GUD   \n",
       "45W000000000032T                 147.0         Asnaesvaerket 2   \n",
       "45W000000000033R                 640.0         Asnaesvaerket 5   \n",
       "45W000000000034P                 250.0         Amagervaerket 3   \n",
       "45W000000000040U                 377.0        Esbjergvaerket 3   \n",
       "\n",
       "                 ProductionUnitEIC  duplicate_count  ...  \\\n",
       "eic_g                                                ...   \n",
       "14WENERGIEAGWT4S  14WENERGIE--WT02              2.0  ...   \n",
       "45W000000000032T  45V000000000011E              1.0  ...   \n",
       "45W000000000033R  45V000000000011E              1.0  ...   \n",
       "45W000000000034P  45V000000000012C              1.0  ...   \n",
       "45W000000000040U  45V0000000000164              1.0  ...   \n",
       "\n",
       "                  VERIFIED_EMISSIONS_2009 ALLOCATION_2008  \\\n",
       "eic_g                                                       \n",
       "14WENERGIEAGWT4S                   340026          218704   \n",
       "45W000000000032T                  2430356         1765318   \n",
       "45W000000000033R                  2430356         1765318   \n",
       "45W000000000034P                  1684995         1250995   \n",
       "45W000000000040U                  1318927         1051489   \n",
       "\n",
       "                  VERIFIED_EMISSIONS_2008 ACCOUNT_CLOSURE  \\\n",
       "eic_g                                                       \n",
       "14WENERGIEAGWT4S                   103553            OPEN   \n",
       "45W000000000032T                  2484733            OPEN   \n",
       "45W000000000033R                  2484733            OPEN   \n",
       "45W000000000034P                  1089604            OPEN   \n",
       "45W000000000040U                  1158930            OPEN   \n",
       "\n",
       "                 side_generation_2018 PP_emissions_2018 PP_EF2018  \\\n",
       "eic_g                                                               \n",
       "14WENERGIEAGWT4S            685235.67     254778.000000  0.371811   \n",
       "45W000000000032T            770018.30     202216.305002  0.922057   \n",
       "45W000000000033R            770018.30     507784.694998  0.922057   \n",
       "45W000000000034P           1060165.23     771352.000000  0.727577   \n",
       "45W000000000040U           1193633.83     924609.000000  0.774617   \n",
       "\n",
       "                  EF_2018_validation   Tech_EF  Country_EF  \n",
       "eic_g                                                       \n",
       "14WENERGIEAGWT4S                True  0.398292    0.507803  \n",
       "45W000000000032T                True  0.775840    0.751762  \n",
       "45W000000000033R                True  0.775840    0.751762  \n",
       "45W000000000034P                True  0.775840    0.751762  \n",
       "45W000000000040U                True  0.775840    0.751762  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generation_unit_info_EF_country.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_EF_country.to_csv(processed_directory_path + '/generation_unit_EF_bottom_up_method.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Validation of calculated emission factors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section we checking if the underlying generation data that we have used for EF calculation represents the country production adequately. By comparing the used power plant production with the production per production type from ENTSO-E (scaled with ENTSO-E Factsheet data) of each country, we can get an idea how trustful is our resulting EF."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load ENTSO-E generation per type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "entsoe_gen_type = pd.read_csv(input_directory_path+'/entsoe_gen_type_hourly_table_scaled.csv', index_col=[0], header=[0, 1], parse_dates=True).dropna(how=\"all\", axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Show the head of the data (the data is using a multi index for the columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2018-01-01 00:00:00+00:00</th>\n",
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       "      <th>2018-01-01 01:00:00+00:00</th>\n",
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       "      <td>177.9</td>\n",
       "      <td>1816.7</td>\n",
       "      <td>475.8</td>\n",
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       "      <td>0.146956</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>164.244759</td>\n",
       "      <td>94.123328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 219 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "region                         AT                                      \\\n",
       "variable                  biomass        gas   hard_coal        hydro   \n",
       "utc_timestamp                                                           \n",
       "2018-01-01 00:00:00+00:00   316.0  85.185998  189.813350  3633.105979   \n",
       "2018-01-01 01:00:00+00:00   316.0  83.986195  188.547928  3557.076855   \n",
       "2018-01-01 02:00:00+00:00   316.0  82.786393  188.547928  3439.774779   \n",
       "2018-01-01 03:00:00+00:00   316.0  86.385801  188.547928  3432.171866   \n",
       "2018-01-01 04:00:00+00:00   316.0  89.985209  188.547928  3616.814024   \n",
       "\n",
       "region                                                               \\\n",
       "variable                  other_fossil other_renewable solar  waste   \n",
       "utc_timestamp                                                         \n",
       "2018-01-01 00:00:00+00:00   376.712329             0.0   0.0  100.0   \n",
       "2018-01-01 01:00:00+00:00   376.712329             0.0   0.0  100.0   \n",
       "2018-01-01 02:00:00+00:00   376.712329             0.0   0.0  100.0   \n",
       "2018-01-01 03:00:00+00:00   376.712329             0.0   0.0  100.0   \n",
       "2018-01-01 04:00:00+00:00   376.712329             0.0   0.0  100.0   \n",
       "\n",
       "region                                          BE  ...      SK          \\\n",
       "variable                  wind_onshore     biomass  ... lignite nuclear   \n",
       "utc_timestamp                                       ...                   \n",
       "2018-01-01 00:00:00+00:00        832.0  310.564338  ...   179.5  1819.3   \n",
       "2018-01-01 01:00:00+00:00        926.0  205.181412  ...   177.9  1816.7   \n",
       "2018-01-01 02:00:00+00:00        692.0  178.621922  ...   174.7  1808.7   \n",
       "2018-01-01 03:00:00+00:00        453.0  175.522424  ...   168.5  1803.6   \n",
       "2018-01-01 04:00:00+00:00        321.0  175.362106  ...   170.6  1809.1   \n",
       "\n",
       "region                                                                 SE  \\\n",
       "variable                  other_fossil other_renewable solar      biomass   \n",
       "utc_timestamp                                                               \n",
       "2018-01-01 00:00:00+00:00        478.8            41.4   0.0  1359.856555   \n",
       "2018-01-01 01:00:00+00:00        475.8            41.0   0.0  1368.550363   \n",
       "2018-01-01 02:00:00+00:00        469.5            40.8   0.0  1276.057900   \n",
       "2018-01-01 03:00:00+00:00        455.6            39.4   0.0  1272.797722   \n",
       "2018-01-01 04:00:00+00:00        461.5            40.4   0.0  1272.918469   \n",
       "\n",
       "region                                                                      \n",
       "variable                        gas  hard_coal other_renewable       waste  \n",
       "utc_timestamp                                                               \n",
       "2018-01-01 00:00:00+00:00  0.000000  78.739970      177.034950  101.343265  \n",
       "2018-01-01 01:00:00+00:00  0.000000  56.544811      178.126795  101.959602  \n",
       "2018-01-01 02:00:00+00:00  0.000000   0.000000      164.712693   94.387472  \n",
       "2018-01-01 03:00:00+00:00  0.000000   0.000000      164.244759   94.123328  \n",
       "2018-01-01 04:00:00+00:00  0.146956   0.000000      164.244759   94.123328  \n",
       "\n",
       "[5 rows x 219 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entsoe_gen_type.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Filter the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking only countries that are covert from our method and use the generation from one year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#country filter\n",
    "entsoe_gen_type = entsoe_gen_type[generation_unit_info_validated.EUTL_countrycode.unique()]\n",
    "# take the sum of the generation\n",
    "entsoe_gen_type = entsoe_gen_type.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reset the multiindex from pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "entsoe_gen_type = entsoe_gen_type.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rename column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "entsoe_gen_type = entsoe_gen_type.rename(columns={0:'generation_per_type_2018_ENTSO-E','region':'MapCode','variable':'ProductionTypeName'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Production for each technology form power plant generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "Powerplants_gen_type_year = pd.DataFrame(generation_unit_info_validated.groupby(['MapCode','ProductionTypeName']).sum()['generation_2018'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reset the multiindex from pandas and drop not used columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "Powerplants_gen_type_year = Powerplants_gen_type_year.reset_index()\n",
    "Powerplants_gen_type_year = Powerplants_gen_type_year.rename(columns={'generation_2018':'verified_generation_per_unit_2018_ENTSO-E'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Merge power plant generation and ENTSO-E per type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen_data_comparison = entsoe_gen_type.merge(Powerplants_gen_type_year, on=['MapCode','ProductionTypeName'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen_data_comparison['missing_generation'] = gen_data_comparison['generation_per_type_2018_ENTSO-E'] - gen_data_comparison['verified_generation_per_unit_2018_ENTSO-E']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen_data_comparison['covered_generation'] = round((100 / gen_data_comparison['generation_per_type_2018_ENTSO-E']) * gen_data_comparison['verified_generation_per_unit_2018_ENTSO-E'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot covered generation per country and generation type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "ax = sns.barplot(x=\"MapCode\", y=\"covered_generation\", hue=\"ProductionTypeName\", data=gen_data_comparison)\n",
    "ax.plot([-1, 19], [25, 25], 'r--')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"Country\", fontsize=22)\n",
    "ax.set_ylabel(\"Covered generation (%)\" , fontsize=22)\n",
    "\n",
    "ax.tick_params(axis='x',labelsize=19)\n",
    "ax.tick_params(axis='y',labelsize=19)\n",
    "\n",
    "pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If some technology coverages are above 100%, this is often explained by the fact that the generation units have been assigned to the wrong technology. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig(os.path.join(output_directory_path + '/_covered_generation_per_country_threshold.png'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Validation threshold for EF per technology and country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add validation identifier to countries and technologies where at least 25 % of the generation is connected to CO2 emissions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "## add identifier\n",
    "gen_data_comparison['Coverage'] = round(gen_data_comparison['covered_generation'])\n",
    "gen_data_comparison['Verified_EF'] = (round(gen_data_comparison['covered_generation']) > 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set new index\n",
    "gen_data_comparison = gen_data_comparison.set_index(['MapCode','ProductionTypeName'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# take the calculated EF from 7.3 and reset the used index\n",
    "EF_per_tech_country = EF_per_tech_country.reset_index().rename(columns={0:'EF','EUTL_countrycode':'MapCode'}).set_index(['MapCode','ProductionTypeName'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transfer the verification of EF too the result\n",
    "EF_per_tech_country['Verified_EF'] = gen_data_comparison['Verified_EF']\n",
    "EF_per_tech_country['Coverage'] = gen_data_comparison['Coverage']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# EF in gCO2 per kWh\n",
    "EF_per_tech_country['EF_round_in_gCO2_kwh'] = (EF_per_tech_country.EF * 1000).round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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></th>\n",
       "      <th>EF</th>\n",
       "      <th>Verified_EF</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>EF_round_in_gCO2_kwh</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MapCode</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AT</th>\n",
       "      <th>gas</th>\n",
       "      <td>0.398292</td>\n",
       "      <td>False</td>\n",
       "      <td>24.0</td>\n",
       "      <td>398.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hard_coal</th>\n",
       "      <td>0.884070</td>\n",
       "      <td>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>884.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <th>gas</th>\n",
       "      <td>0.389641</td>\n",
       "      <td>True</td>\n",
       "      <td>64.0</td>\n",
       "      <td>389.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">CZ</th>\n",
       "      <th>gas</th>\n",
       "      <td>0.780843</td>\n",
       "      <td>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>780.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hard_coal</th>\n",
       "      <td>0.985546</td>\n",
       "      <td>True</td>\n",
       "      <td>36.0</td>\n",
       "      <td>985.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  EF  Verified_EF  Coverage  \\\n",
       "MapCode ProductionTypeName                                    \n",
       "AT      gas                 0.398292        False      24.0   \n",
       "        hard_coal           0.884070         True      39.0   \n",
       "BE      gas                 0.389641         True      64.0   \n",
       "CZ      gas                 0.780843         True      39.0   \n",
       "        hard_coal           0.985546         True      36.0   \n",
       "\n",
       "                            EF_round_in_gCO2_kwh  \n",
       "MapCode ProductionTypeName                        \n",
       "AT      gas                               398.29  \n",
       "        hard_coal                         884.07  \n",
       "BE      gas                               389.64  \n",
       "CZ      gas                               780.84  \n",
       "        hard_coal                         985.55  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EF_per_tech_country.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation of EF data set "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following section generates some information to better assess the quality of the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['eic_g', 'AreaCode', 'AreaName', 'AreaTypeCode', 'InstalledGenCapacity',\n",
       "       'MapCode', 'PowerSystemResourceName', 'ProductionTypeName',\n",
       "       'ProductionUnitEIC', 'duplicate_count', 'generation_2018', 'eic_p',\n",
       "       'EUTL_countrycode', 'EUTL_ID', 'Unique_ID', 'REGISTRY_CODE',\n",
       "       'IDENTIFIER_IN_REG', 'INSTALLATION_NAME', 'INSTALLATION_IDENTIFIER',\n",
       "       'PERMIT_IDENTIFIER', 'MAIN_ACTIVITY_TYPE_CODE', 'ALLOCATION_2018',\n",
       "       'ALLOCATION_RESERVE_2018', 'ALLOCATION_TRANSITIONAL_2018',\n",
       "       'VERIFIED_EMISSIONS_2018', 'ALLOCATION_2017', 'ALLOCATION_RESERVE_2017',\n",
       "       'ALLOCATION_TRANSITIONAL_2017', 'VERIFIED_EMISSIONS_2017',\n",
       "       'ALLOCATION_2016', 'ALLOCATION_RESERVE_2016',\n",
       "       'ALLOCATION_TRANSITIONAL_2016', 'VERIFIED_EMISSIONS_2016',\n",
       "       'ALLOCATION_2015', 'ALLOCATION_RESERVE_2015',\n",
       "       'ALLOCATION_TRANSITIONAL_2015', 'VERIFIED_EMISSIONS_2015',\n",
       "       'ALLOCATION_2014', 'ALLOCATION_RESERVE_2014',\n",
       "       'ALLOCATION_TRANSITIONAL_2014', 'VERIFIED_EMISSIONS_2014',\n",
       "       'ALLOCATION_2013', 'ALLOCATION_RESERVE_2013',\n",
       "       'ALLOCATION_TRANSITIONAL_2013', 'VERIFIED_EMISSIONS_2013',\n",
       "       'ALLOCATION_2012', 'VERIFIED_EMISSIONS_2012', 'ALLOCATION_2011',\n",
       "       'VERIFIED_EMISSIONS_2011', 'ALLOCATION_2010', 'VERIFIED_EMISSIONS_2010',\n",
       "       'ALLOCATION_2009', 'VERIFIED_EMISSIONS_2009', 'ALLOCATION_2008',\n",
       "       'VERIFIED_EMISSIONS_2008', 'ACCOUNT_CLOSURE', 'side_generation_2018',\n",
       "       'PP_emissions_2018', 'PP_EF2018', 'EF_2018_validation'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show the columns in the last data set \n",
    "generation_unit_info_validated.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_eval_table(generation, matched_generation, validated_generation, val_type):\n",
    "    \n",
    "    check_1 = generation.groupby(['MapCode', 'ProductionTypeName']).agg(['sum', 'count'])[val_type]\n",
    "    check_1.rename(columns={\"count\": \"count_1\", \"sum\":\"sum_1\"}, inplace=True)\n",
    "    \n",
    "    check_2 = generation_unit_info_matched.groupby(['MapCode', 'ProductionTypeName']).agg(['sum', 'count'])[val_type]\n",
    "    check_2.rename(columns={\"count\": \"count_2\",  \"sum\":\"sum_2\"}, inplace=True)\n",
    "    \n",
    "    check_3 = generation_unit_info_validated.groupby(['MapCode', 'ProductionTypeName']).agg(['sum', 'count'])[val_type]\n",
    "    check_3.rename(columns={\"count\": \"count_3\",  \"sum\":\"sum_3\"}, inplace=True)\n",
    "    \n",
    "    check_table = check_3.join(check_2).join(check_1)\n",
    "    \n",
    "    check_table.sum_3 = (check_table.sum_3 / 1000)\n",
    "    check_table.sum_2 = (check_table.sum_2 / 1000)\n",
    "    check_table.sum_1 = (check_table.sum_1 / 1000)\n",
    "    \n",
    "    check_table = check_table.round(3)\n",
    "    \n",
    "    return check_table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Evaluation atvle for capacity \n",
    "eval_table_cap = gen_eval_table(generation_unit_info, generation_unit_info_matched, generation_unit_info_validated, 'InstalledGenCapacity')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Join the calculated EF to the evaluation table\n",
    "eval_table_cap = eval_table_cap.join(EF_per_tech_country)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_cap = eval_table_cap[['EF_round_in_gCO2_kwh', 'Coverage', 'sum_3', 'count_3', 'sum_2', 'count_2', 'sum_1', 'count_1', 'EF', 'Verified_EF']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_cap.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_cap.loc[\"Total\"] = eval_table_cap[['sum_3', 'count_3', 'sum_2', 'count_2', 'sum_1', 'count_1']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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>MapCode</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>EF_round_in_gCO2_kwh</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>sum_3</th>\n",
       "      <th>count_3</th>\n",
       "      <th>sum_2</th>\n",
       "      <th>count_2</th>\n",
       "      <th>sum_1</th>\n",
       "      <th>count_1</th>\n",
       "      <th>EF</th>\n",
       "      <th>Verified_EF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AT</td>\n",
       "      <td>gas</td>\n",
       "      <td>398.29</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.954</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.902</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.902</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.398292</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AT</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>884.07</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.200</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.682</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.682</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.884070</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE</td>\n",
       "      <td>gas</td>\n",
       "      <td>389.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>3.936</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.506</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.646</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.389641</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CZ</td>\n",
       "      <td>gas</td>\n",
       "      <td>780.84</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.847</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.847</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.847</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.780843</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CZ</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>985.55</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.561</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.748</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.748</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.985546</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CZ</td>\n",
       "      <td>lignite</td>\n",
       "      <td>928.30</td>\n",
       "      <td>58.0</td>\n",
       "      <td>4.119</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5.772</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4.494</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.928296</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DE</td>\n",
       "      <td>gas</td>\n",
       "      <td>354.60</td>\n",
       "      <td>17.0</td>\n",
       "      <td>11.287</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.977</td>\n",
       "      <td>58.0</td>\n",
       "      <td>16.972</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.354596</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>DE</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>934.14</td>\n",
       "      <td>94.0</td>\n",
       "      <td>20.107</td>\n",
       "      <td>42.0</td>\n",
       "      <td>24.395</td>\n",
       "      <td>51.0</td>\n",
       "      <td>22.794</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.934135</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DE</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1125.56</td>\n",
       "      <td>96.0</td>\n",
       "      <td>19.238</td>\n",
       "      <td>34.0</td>\n",
       "      <td>19.590</td>\n",
       "      <td>35.0</td>\n",
       "      <td>19.590</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.125560</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DE</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>1401.10</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.600</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.925</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.341</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.401101</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>DK</td>\n",
       "      <td>gas</td>\n",
       "      <td>329.78</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.108</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.108</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.108</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.329783</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>775.84</td>\n",
       "      <td>69.0</td>\n",
       "      <td>2.151</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.895</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.523</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.775840</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>EE</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>1057.97</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.971</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.251</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.251</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.057973</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ES</td>\n",
       "      <td>gas</td>\n",
       "      <td>390.43</td>\n",
       "      <td>49.0</td>\n",
       "      <td>21.496</td>\n",
       "      <td>63.0</td>\n",
       "      <td>24.671</td>\n",
       "      <td>72.0</td>\n",
       "      <td>24.671</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.390428</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ES</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1044.87</td>\n",
       "      <td>99.0</td>\n",
       "      <td>7.622</td>\n",
       "      <td>19.0</td>\n",
       "      <td>9.535</td>\n",
       "      <td>26.0</td>\n",
       "      <td>9.535</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.044871</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>FI</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>754.59</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0.930</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.274</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.274</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.754586</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>FI</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>759.81</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.120</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.120</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.641</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.759814</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>FR</td>\n",
       "      <td>gas</td>\n",
       "      <td>396.98</td>\n",
       "      <td>49.0</td>\n",
       "      <td>4.881</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.120</td>\n",
       "      <td>18.0</td>\n",
       "      <td>6.521</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.396985</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>FR</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>928.83</td>\n",
       "      <td>73.0</td>\n",
       "      <td>2.335</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.930</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.930</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.928832</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>GB</td>\n",
       "      <td>gas</td>\n",
       "      <td>488.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>29.855</td>\n",
       "      <td>57.0</td>\n",
       "      <td>32.981</td>\n",
       "      <td>77.0</td>\n",
       "      <td>34.515</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.488643</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>GB</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1125.00</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.679</td>\n",
       "      <td>19.0</td>\n",
       "      <td>12.981</td>\n",
       "      <td>25.0</td>\n",
       "      <td>13.223</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.124997</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GR</td>\n",
       "      <td>gas</td>\n",
       "      <td>457.38</td>\n",
       "      <td>65.0</td>\n",
       "      <td>3.279</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.899</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4.899</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.457378</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>GR</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1429.22</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3.905</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.905</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.905</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.429216</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>HU</td>\n",
       "      <td>gas</td>\n",
       "      <td>379.65</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.652</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.761</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.761</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.379650</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>HU</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1355.62</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.613</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.613</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.613</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.355619</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>IE</td>\n",
       "      <td>gas</td>\n",
       "      <td>392.88</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1.846</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.730</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3.730</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.392880</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>IE</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1032.20</td>\n",
       "      <td>89.0</td>\n",
       "      <td>0.855</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.855</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.855</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.032204</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>IT</td>\n",
       "      <td>gas</td>\n",
       "      <td>395.17</td>\n",
       "      <td>52.0</td>\n",
       "      <td>23.148</td>\n",
       "      <td>53.0</td>\n",
       "      <td>27.572</td>\n",
       "      <td>69.0</td>\n",
       "      <td>28.462</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.395166</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>IT</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>997.67</td>\n",
       "      <td>59.0</td>\n",
       "      <td>5.081</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.926</td>\n",
       "      <td>18.0</td>\n",
       "      <td>6.926</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.997673</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>IT</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>458.37</td>\n",
       "      <td>106.0</td>\n",
       "      <td>3.479</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.940</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.034</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0.458371</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NL</td>\n",
       "      <td>gas</td>\n",
       "      <td>393.24</td>\n",
       "      <td>40.0</td>\n",
       "      <td>7.578</td>\n",
       "      <td>19.0</td>\n",
       "      <td>12.707</td>\n",
       "      <td>34.0</td>\n",
       "      <td>13.371</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.393243</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>NL</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1183.07</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.731</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.662</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.662</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.183066</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>PL</td>\n",
       "      <td>gas</td>\n",
       "      <td>370.31</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.332</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.457</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.572</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.370311</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>PL</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>942.41</td>\n",
       "      <td>56.0</td>\n",
       "      <td>12.056</td>\n",
       "      <td>52.0</td>\n",
       "      <td>14.901</td>\n",
       "      <td>56.0</td>\n",
       "      <td>19.861</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.942409</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>PL</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1158.65</td>\n",
       "      <td>78.0</td>\n",
       "      <td>5.576</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.064</td>\n",
       "      <td>19.0</td>\n",
       "      <td>8.678</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.158647</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>PT</td>\n",
       "      <td>gas</td>\n",
       "      <td>430.33</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.838</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.828</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.828</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.430328</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>RO</td>\n",
       "      <td>gas</td>\n",
       "      <td>426.42</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1.108</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.428</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3.428</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.426421</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>RO</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1157.44</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.743</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.133</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.133</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.157439</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>RO</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1000.76</td>\n",
       "      <td>88.0</td>\n",
       "      <td>3.068</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.011</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4.011</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.000763</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>SE</td>\n",
       "      <td>gas</td>\n",
       "      <td>361.80</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.250</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.250</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.250</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.361805</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>SK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>903.09</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.220</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.220</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.220</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.903090</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SK</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1295.55</td>\n",
       "      <td>87.0</td>\n",
       "      <td>0.220</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.330</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.330</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.295547</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>222.575</td>\n",
       "      <td>595.0</td>\n",
       "      <td>287.402</td>\n",
       "      <td>812.0</td>\n",
       "      <td>304.737</td>\n",
       "      <td>890.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      MapCode ProductionTypeName  EF_round_in_gCO2_kwh  Coverage    sum_3  \\\n",
       "0          AT                gas                398.29      24.0    1.954   \n",
       "1          AT          hard_coal                884.07      39.0    0.200   \n",
       "2          BE                gas                389.64      64.0    3.936   \n",
       "3          CZ                gas                780.84      39.0    0.847   \n",
       "4          CZ          hard_coal                985.55      36.0    0.561   \n",
       "5          CZ            lignite                928.30      58.0    4.119   \n",
       "6          DE                gas                354.60      17.0   11.287   \n",
       "7          DE          hard_coal                934.14      94.0   20.107   \n",
       "8          DE            lignite               1125.56      96.0   19.238   \n",
       "9          DE       other_fossil               1401.10      30.0    0.600   \n",
       "10         DK                gas                329.78      10.0    0.108   \n",
       "11         DK          hard_coal                775.84      69.0    2.151   \n",
       "12         EE       other_fossil               1057.97     100.0    1.971   \n",
       "13         ES                gas                390.43      49.0   21.496   \n",
       "14         ES          hard_coal               1044.87      99.0    7.622   \n",
       "15         FI          hard_coal                754.59      47.0    0.930   \n",
       "16         FI       other_fossil                759.81      13.0    0.120   \n",
       "17         FR                gas                396.98      49.0    4.881   \n",
       "18         FR          hard_coal                928.83      73.0    2.335   \n",
       "19         GB                gas                488.64      64.0   29.855   \n",
       "20         GB          hard_coal               1125.00      46.0    9.679   \n",
       "21         GR                gas                457.38      65.0    3.279   \n",
       "22         GR            lignite               1429.22     100.0    3.905   \n",
       "23         HU                gas                379.65      65.0    1.652   \n",
       "24         HU            lignite               1355.62      81.0    0.613   \n",
       "25         IE                gas                392.88      44.0    1.846   \n",
       "26         IE          hard_coal               1032.20      89.0    0.855   \n",
       "27         IT                gas                395.17      52.0   23.148   \n",
       "28         IT          hard_coal                997.67      59.0    5.081   \n",
       "29         IT       other_fossil                458.37     106.0    3.479   \n",
       "30         NL                gas                393.24      40.0    7.578   \n",
       "31         NL          hard_coal               1183.07      15.0    0.731   \n",
       "32         PL                gas                370.31      10.0    0.332   \n",
       "33         PL          hard_coal                942.41      56.0   12.056   \n",
       "34         PL            lignite               1158.65      78.0    5.576   \n",
       "35         PT                gas                430.33      42.0    2.838   \n",
       "36         RO                gas                426.42      28.0    1.108   \n",
       "37         RO          hard_coal               1157.44      72.0    0.743   \n",
       "38         RO            lignite               1000.76      88.0    3.068   \n",
       "39         SE                gas                361.80      68.0    0.250   \n",
       "40         SK          hard_coal                903.09      65.0    0.220   \n",
       "41         SK            lignite               1295.55      87.0    0.220   \n",
       "Total     NaN                NaN                   NaN       NaN  222.575   \n",
       "\n",
       "       count_3    sum_2  count_2    sum_1  count_1        EF  Verified_EF  \n",
       "0          7.0    3.902     12.0    3.902     12.0  0.398292          0.0  \n",
       "1          1.0    0.682      3.0    0.682      3.0  0.884070          1.0  \n",
       "2         17.0    4.506     19.0    4.646     20.0  0.389641          1.0  \n",
       "3          1.0    0.847      1.0    0.847      1.0  0.780843          1.0  \n",
       "4          3.0    0.748      4.0    0.748      4.0  0.985546          1.0  \n",
       "5         18.0    5.772     25.0    4.494     21.0  0.928296          1.0  \n",
       "6         29.0   17.977     58.0   16.972     53.0  0.354596          0.0  \n",
       "7         42.0   24.395     51.0   22.794     48.0  0.934135          1.0  \n",
       "8         34.0   19.590     35.0   19.590     35.0  1.125560          1.0  \n",
       "9          2.0    0.925      4.0    2.341     11.0  1.401101          1.0  \n",
       "10         1.0    0.108      1.0    0.108      1.0  0.329783          0.0  \n",
       "11         6.0    2.895      8.0    2.523      7.0  0.775840          1.0  \n",
       "12        11.0    2.251     13.0    2.251     13.0  1.057973          1.0  \n",
       "13        63.0   24.671     72.0   24.671     72.0  0.390428          1.0  \n",
       "14        19.0    9.535     26.0    9.535     26.0  1.044871          1.0  \n",
       "15         4.0    2.274     12.0    2.274     12.0  0.754586          1.0  \n",
       "16         1.0    0.120      1.0    1.641     10.0  0.759814          0.0  \n",
       "17        11.0    6.120     18.0    6.521     19.0  0.396985          1.0  \n",
       "18         4.0    2.930      5.0    2.930      5.0  0.928832          1.0  \n",
       "19        57.0   32.981     77.0   34.515     84.0  0.488643          1.0  \n",
       "20        19.0   12.981     25.0   13.223     27.0  1.124997          1.0  \n",
       "21        10.0    4.899     14.0    4.899     14.0  0.457378          1.0  \n",
       "22        14.0    3.905     14.0    3.905     14.0  1.429216          1.0  \n",
       "23         9.0    1.761     10.0    1.761     10.0  0.379650          1.0  \n",
       "24         3.0    0.613      3.0    0.613      3.0  1.355619          1.0  \n",
       "25         7.0    3.730     16.0    3.730     16.0  0.392880          1.0  \n",
       "26         3.0    0.855      3.0    0.855      3.0  1.032204          1.0  \n",
       "27        53.0   27.572     69.0   28.462     72.0  0.395166          1.0  \n",
       "28        15.0    6.926     18.0    6.926     18.0  0.997673          1.0  \n",
       "29         8.0    7.940     20.0   15.034     43.0  0.458371          1.0  \n",
       "30        19.0   12.707     34.0   13.371     37.0  0.393243          1.0  \n",
       "31         1.0    4.662      6.0    4.662      6.0  1.183066          0.0  \n",
       "32         2.0    0.457      3.0    1.572      5.0  0.370311          0.0  \n",
       "33        52.0   14.901     56.0   19.861     82.0  0.942409          1.0  \n",
       "34        13.0    7.064     19.0    8.678     26.0  1.158647          1.0  \n",
       "35         7.0    3.828     10.0    3.828     10.0  0.430328          1.0  \n",
       "36         9.0    3.428     21.0    3.428     21.0  0.426421          1.0  \n",
       "37         4.0    1.133      6.0    1.133      6.0  1.157439          1.0  \n",
       "38        11.0    4.011     14.0    4.011     14.0  1.000763          1.0  \n",
       "39         1.0    0.250      1.0    0.250      1.0  0.361805          1.0  \n",
       "40         2.0    0.220      2.0    0.220      2.0  0.903090          1.0  \n",
       "41         2.0    0.330      3.0    0.330      3.0  1.295547          1.0  \n",
       "Total    595.0  287.402    812.0  304.737    890.0       NaN          NaN  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_table_cap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>EF_round_in_gCO2_kwh</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>sum_3</th>\n",
       "      <th>count_3</th>\n",
       "      <th>sum_2</th>\n",
       "      <th>count_2</th>\n",
       "      <th>sum_1</th>\n",
       "      <th>count_1</th>\n",
       "      <th>EF</th>\n",
       "      <th>Verified_EF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ProductionTypeName</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>gas</th>\n",
       "      <td>7136.38</td>\n",
       "      <td>730.0</td>\n",
       "      <td>116.395</td>\n",
       "      <td>303.0</td>\n",
       "      <td>149.744</td>\n",
       "      <td>436.0</td>\n",
       "      <td>153.483</td>\n",
       "      <td>448.0</td>\n",
       "      <td>7.136394</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hard_coal</th>\n",
       "      <td>13648.77</td>\n",
       "      <td>859.0</td>\n",
       "      <td>63.271</td>\n",
       "      <td>175.0</td>\n",
       "      <td>85.137</td>\n",
       "      <td>225.0</td>\n",
       "      <td>88.366</td>\n",
       "      <td>249.0</td>\n",
       "      <td>13.648762</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lignite</th>\n",
       "      <td>8293.66</td>\n",
       "      <td>588.0</td>\n",
       "      <td>36.739</td>\n",
       "      <td>95.0</td>\n",
       "      <td>41.285</td>\n",
       "      <td>113.0</td>\n",
       "      <td>41.621</td>\n",
       "      <td>116.0</td>\n",
       "      <td>8.293648</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_fossil</th>\n",
       "      <td>3677.25</td>\n",
       "      <td>249.0</td>\n",
       "      <td>6.170</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.236</td>\n",
       "      <td>38.0</td>\n",
       "      <td>21.267</td>\n",
       "      <td>77.0</td>\n",
       "      <td>3.677259</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    EF_round_in_gCO2_kwh  Coverage    sum_3  count_3    sum_2  \\\n",
       "ProductionTypeName                                                              \n",
       "gas                              7136.38     730.0  116.395    303.0  149.744   \n",
       "hard_coal                       13648.77     859.0   63.271    175.0   85.137   \n",
       "lignite                          8293.66     588.0   36.739     95.0   41.285   \n",
       "other_fossil                     3677.25     249.0    6.170     22.0   11.236   \n",
       "\n",
       "                    count_2    sum_1  count_1         EF  Verified_EF  \n",
       "ProductionTypeName                                                     \n",
       "gas                   436.0  153.483    448.0   7.136394         13.0  \n",
       "hard_coal             225.0   88.366    249.0  13.648762         13.0  \n",
       "lignite               113.0   41.621    116.0   8.293648          7.0  \n",
       "other_fossil           38.0   21.267     77.0   3.677259          3.0  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_table_cap.groupby('ProductionTypeName').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Evaluation table for genertaion\n",
    "eval_table_gen = gen_eval_table(generation_unit_info, generation_unit_info_matched, generation_unit_info_validated, 'generation_2018')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Join the calculated EF to the evaluation table\n",
    "eval_table_gen = eval_table_gen.join(EF_per_tech_country)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen = eval_table_gen[['EF_round_in_gCO2_kwh', 'Coverage', 'sum_3', 'count_3', 'sum_2', 'count_2', 'sum_1', 'count_1', 'EF', 'Verified_EF']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen.loc[\"Total\"] = eval_table_gen[['sum_3', 'count_3', 'sum_2', 'count_2', 'sum_1', 'count_1']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MapCode</th>\n",
       "      <th>ProductionTypeName</th>\n",
       "      <th>EF_round_in_gCO2_kwh</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>sum_3</th>\n",
       "      <th>count_3</th>\n",
       "      <th>sum_2</th>\n",
       "      <th>count_2</th>\n",
       "      <th>sum_1</th>\n",
       "      <th>count_1</th>\n",
       "      <th>EF</th>\n",
       "      <th>Verified_EF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AT</td>\n",
       "      <td>gas</td>\n",
       "      <td>398.29</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2384.014</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7457.226</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7457.226</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.398292</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AT</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>884.07</td>\n",
       "      <td>39.0</td>\n",
       "      <td>693.857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1439.148</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1439.148</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.884070</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE</td>\n",
       "      <td>gas</td>\n",
       "      <td>389.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>14216.707</td>\n",
       "      <td>17.0</td>\n",
       "      <td>16372.357</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17181.875</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.389641</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CZ</td>\n",
       "      <td>gas</td>\n",
       "      <td>780.84</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1729.036</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1729.036</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1729.036</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.780843</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CZ</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>985.55</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1243.426</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1243.426</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1243.426</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.985546</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CZ</td>\n",
       "      <td>lignite</td>\n",
       "      <td>928.30</td>\n",
       "      <td>58.0</td>\n",
       "      <td>19775.004</td>\n",
       "      <td>18.0</td>\n",
       "      <td>26607.733</td>\n",
       "      <td>25.0</td>\n",
       "      <td>21876.551</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.928296</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DE</td>\n",
       "      <td>gas</td>\n",
       "      <td>354.60</td>\n",
       "      <td>17.0</td>\n",
       "      <td>15235.146</td>\n",
       "      <td>29.0</td>\n",
       "      <td>29445.917</td>\n",
       "      <td>58.0</td>\n",
       "      <td>29024.315</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.354596</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>DE</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>934.14</td>\n",
       "      <td>94.0</td>\n",
       "      <td>68655.321</td>\n",
       "      <td>42.0</td>\n",
       "      <td>78632.750</td>\n",
       "      <td>51.0</td>\n",
       "      <td>73274.329</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.934135</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DE</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1125.56</td>\n",
       "      <td>96.0</td>\n",
       "      <td>129230.488</td>\n",
       "      <td>34.0</td>\n",
       "      <td>129230.488</td>\n",
       "      <td>35.0</td>\n",
       "      <td>129230.488</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.125560</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DE</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>1401.10</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1971.580</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3759.405</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6423.292</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.401101</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>DK</td>\n",
       "      <td>gas</td>\n",
       "      <td>329.78</td>\n",
       "      <td>10.0</td>\n",
       "      <td>273.443</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.443</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.443</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.329783</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>775.84</td>\n",
       "      <td>69.0</td>\n",
       "      <td>4792.089</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6332.337</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5562.213</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.775840</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>EE</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>1057.97</td>\n",
       "      <td>100.0</td>\n",
       "      <td>9592.431</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9592.431</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9592.431</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.057973</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ES</td>\n",
       "      <td>gas</td>\n",
       "      <td>390.43</td>\n",
       "      <td>49.0</td>\n",
       "      <td>26209.431</td>\n",
       "      <td>63.0</td>\n",
       "      <td>26795.465</td>\n",
       "      <td>72.0</td>\n",
       "      <td>26795.465</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.390428</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ES</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1044.87</td>\n",
       "      <td>99.0</td>\n",
       "      <td>32138.250</td>\n",
       "      <td>19.0</td>\n",
       "      <td>35004.169</td>\n",
       "      <td>26.0</td>\n",
       "      <td>35004.169</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.044871</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>FI</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>754.59</td>\n",
       "      <td>47.0</td>\n",
       "      <td>2816.937</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5099.777</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5099.777</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.754586</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>FI</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>759.81</td>\n",
       "      <td>13.0</td>\n",
       "      <td>725.116</td>\n",
       "      <td>1.0</td>\n",
       "      <td>725.116</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3397.165</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.759814</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>FR</td>\n",
       "      <td>gas</td>\n",
       "      <td>396.98</td>\n",
       "      <td>49.0</td>\n",
       "      <td>15259.900</td>\n",
       "      <td>11.0</td>\n",
       "      <td>19720.563</td>\n",
       "      <td>18.0</td>\n",
       "      <td>20270.423</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.396985</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>FR</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>928.83</td>\n",
       "      <td>73.0</td>\n",
       "      <td>4256.081</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5651.195</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5651.195</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.928832</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>GB</td>\n",
       "      <td>gas</td>\n",
       "      <td>488.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>83317.830</td>\n",
       "      <td>57.0</td>\n",
       "      <td>88668.614</td>\n",
       "      <td>77.0</td>\n",
       "      <td>91207.961</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.488643</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>GB</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1125.00</td>\n",
       "      <td>46.0</td>\n",
       "      <td>7652.145</td>\n",
       "      <td>19.0</td>\n",
       "      <td>11004.849</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11004.849</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.124997</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GR</td>\n",
       "      <td>gas</td>\n",
       "      <td>457.38</td>\n",
       "      <td>65.0</td>\n",
       "      <td>9928.104</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15146.233</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15146.233</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.457378</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>GR</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1429.22</td>\n",
       "      <td>100.0</td>\n",
       "      <td>15188.996</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15188.996</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15188.996</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.429216</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>HU</td>\n",
       "      <td>gas</td>\n",
       "      <td>379.65</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4081.735</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4497.068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4497.068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.379650</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>HU</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1355.62</td>\n",
       "      <td>81.0</td>\n",
       "      <td>3850.490</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3850.490</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3850.490</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.355619</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>IE</td>\n",
       "      <td>gas</td>\n",
       "      <td>392.88</td>\n",
       "      <td>44.0</td>\n",
       "      <td>6552.647</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12047.551</td>\n",
       "      <td>16.0</td>\n",
       "      <td>12047.551</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.392880</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>IE</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1032.20</td>\n",
       "      <td>89.0</td>\n",
       "      <td>1894.775</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1894.775</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1894.775</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.032204</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>IT</td>\n",
       "      <td>gas</td>\n",
       "      <td>395.17</td>\n",
       "      <td>52.0</td>\n",
       "      <td>64447.804</td>\n",
       "      <td>53.0</td>\n",
       "      <td>72774.603</td>\n",
       "      <td>69.0</td>\n",
       "      <td>73504.645</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.395166</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>IT</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>997.67</td>\n",
       "      <td>59.0</td>\n",
       "      <td>17039.711</td>\n",
       "      <td>15.0</td>\n",
       "      <td>25848.683</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25848.683</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.997673</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>IT</td>\n",
       "      <td>other_fossil</td>\n",
       "      <td>458.37</td>\n",
       "      <td>106.0</td>\n",
       "      <td>13726.939</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23804.910</td>\n",
       "      <td>20.0</td>\n",
       "      <td>36286.053</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0.458371</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NL</td>\n",
       "      <td>gas</td>\n",
       "      <td>393.24</td>\n",
       "      <td>40.0</td>\n",
       "      <td>28718.568</td>\n",
       "      <td>19.0</td>\n",
       "      <td>36881.050</td>\n",
       "      <td>34.0</td>\n",
       "      <td>38298.322</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.393243</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>NL</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1183.07</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4080.723</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27130.255</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27130.255</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.183066</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>PL</td>\n",
       "      <td>gas</td>\n",
       "      <td>370.31</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1294.905</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2216.311</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7245.647</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.370311</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>PL</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>942.41</td>\n",
       "      <td>56.0</td>\n",
       "      <td>44401.449</td>\n",
       "      <td>52.0</td>\n",
       "      <td>45302.785</td>\n",
       "      <td>56.0</td>\n",
       "      <td>64890.861</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.942409</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>PL</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1158.65</td>\n",
       "      <td>78.0</td>\n",
       "      <td>35099.139</td>\n",
       "      <td>13.0</td>\n",
       "      <td>41691.758</td>\n",
       "      <td>19.0</td>\n",
       "      <td>45574.123</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.158647</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>PT</td>\n",
       "      <td>gas</td>\n",
       "      <td>430.33</td>\n",
       "      <td>42.0</td>\n",
       "      <td>6169.294</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10187.982</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10187.982</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.430328</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>RO</td>\n",
       "      <td>gas</td>\n",
       "      <td>426.42</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2991.592</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6987.634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6987.634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.426421</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>RO</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>1157.44</td>\n",
       "      <td>72.0</td>\n",
       "      <td>852.205</td>\n",
       "      <td>4.0</td>\n",
       "      <td>852.205</td>\n",
       "      <td>6.0</td>\n",
       "      <td>852.205</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.157439</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>RO</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1000.76</td>\n",
       "      <td>88.0</td>\n",
       "      <td>12869.138</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12869.138</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12869.138</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.000763</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>SE</td>\n",
       "      <td>gas</td>\n",
       "      <td>361.80</td>\n",
       "      <td>68.0</td>\n",
       "      <td>408.286</td>\n",
       "      <td>1.0</td>\n",
       "      <td>408.286</td>\n",
       "      <td>1.0</td>\n",
       "      <td>408.286</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.361805</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>SK</td>\n",
       "      <td>hard_coal</td>\n",
       "      <td>903.09</td>\n",
       "      <td>65.0</td>\n",
       "      <td>782.936</td>\n",
       "      <td>2.0</td>\n",
       "      <td>782.936</td>\n",
       "      <td>2.0</td>\n",
       "      <td>782.936</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.903090</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SK</td>\n",
       "      <td>lignite</td>\n",
       "      <td>1295.55</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1167.766</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1167.766</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1167.766</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.295547</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>717715.434</td>\n",
       "      <td>595.0</td>\n",
       "      <td>866316.860</td>\n",
       "      <td>812.0</td>\n",
       "      <td>907398.426</td>\n",
       "      <td>890.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      MapCode ProductionTypeName  EF_round_in_gCO2_kwh  Coverage       sum_3  \\\n",
       "0          AT                gas                398.29      24.0    2384.014   \n",
       "1          AT          hard_coal                884.07      39.0     693.857   \n",
       "2          BE                gas                389.64      64.0   14216.707   \n",
       "3          CZ                gas                780.84      39.0    1729.036   \n",
       "4          CZ          hard_coal                985.55      36.0    1243.426   \n",
       "5          CZ            lignite                928.30      58.0   19775.004   \n",
       "6          DE                gas                354.60      17.0   15235.146   \n",
       "7          DE          hard_coal                934.14      94.0   68655.321   \n",
       "8          DE            lignite               1125.56      96.0  129230.488   \n",
       "9          DE       other_fossil               1401.10      30.0    1971.580   \n",
       "10         DK                gas                329.78      10.0     273.443   \n",
       "11         DK          hard_coal                775.84      69.0    4792.089   \n",
       "12         EE       other_fossil               1057.97     100.0    9592.431   \n",
       "13         ES                gas                390.43      49.0   26209.431   \n",
       "14         ES          hard_coal               1044.87      99.0   32138.250   \n",
       "15         FI          hard_coal                754.59      47.0    2816.937   \n",
       "16         FI       other_fossil                759.81      13.0     725.116   \n",
       "17         FR                gas                396.98      49.0   15259.900   \n",
       "18         FR          hard_coal                928.83      73.0    4256.081   \n",
       "19         GB                gas                488.64      64.0   83317.830   \n",
       "20         GB          hard_coal               1125.00      46.0    7652.145   \n",
       "21         GR                gas                457.38      65.0    9928.104   \n",
       "22         GR            lignite               1429.22     100.0   15188.996   \n",
       "23         HU                gas                379.65      65.0    4081.735   \n",
       "24         HU            lignite               1355.62      81.0    3850.490   \n",
       "25         IE                gas                392.88      44.0    6552.647   \n",
       "26         IE          hard_coal               1032.20      89.0    1894.775   \n",
       "27         IT                gas                395.17      52.0   64447.804   \n",
       "28         IT          hard_coal                997.67      59.0   17039.711   \n",
       "29         IT       other_fossil                458.37     106.0   13726.939   \n",
       "30         NL                gas                393.24      40.0   28718.568   \n",
       "31         NL          hard_coal               1183.07      15.0    4080.723   \n",
       "32         PL                gas                370.31      10.0    1294.905   \n",
       "33         PL          hard_coal                942.41      56.0   44401.449   \n",
       "34         PL            lignite               1158.65      78.0   35099.139   \n",
       "35         PT                gas                430.33      42.0    6169.294   \n",
       "36         RO                gas                426.42      28.0    2991.592   \n",
       "37         RO          hard_coal               1157.44      72.0     852.205   \n",
       "38         RO            lignite               1000.76      88.0   12869.138   \n",
       "39         SE                gas                361.80      68.0     408.286   \n",
       "40         SK          hard_coal                903.09      65.0     782.936   \n",
       "41         SK            lignite               1295.55      87.0    1167.766   \n",
       "Total     NaN                NaN                   NaN       NaN  717715.434   \n",
       "\n",
       "       count_3       sum_2  count_2       sum_1  count_1        EF  \\\n",
       "0          7.0    7457.226     12.0    7457.226     12.0  0.398292   \n",
       "1          1.0    1439.148      3.0    1439.148      3.0  0.884070   \n",
       "2         17.0   16372.357     19.0   17181.875     20.0  0.389641   \n",
       "3          1.0    1729.036      1.0    1729.036      1.0  0.780843   \n",
       "4          3.0    1243.426      4.0    1243.426      4.0  0.985546   \n",
       "5         18.0   26607.733     25.0   21876.551     21.0  0.928296   \n",
       "6         29.0   29445.917     58.0   29024.315     53.0  0.354596   \n",
       "7         42.0   78632.750     51.0   73274.329     48.0  0.934135   \n",
       "8         34.0  129230.488     35.0  129230.488     35.0  1.125560   \n",
       "9          2.0    3759.405      4.0    6423.292     11.0  1.401101   \n",
       "10         1.0     273.443      1.0     273.443      1.0  0.329783   \n",
       "11         6.0    6332.337      8.0    5562.213      7.0  0.775840   \n",
       "12        11.0    9592.431     13.0    9592.431     13.0  1.057973   \n",
       "13        63.0   26795.465     72.0   26795.465     72.0  0.390428   \n",
       "14        19.0   35004.169     26.0   35004.169     26.0  1.044871   \n",
       "15         4.0    5099.777     12.0    5099.777     12.0  0.754586   \n",
       "16         1.0     725.116      1.0    3397.165     10.0  0.759814   \n",
       "17        11.0   19720.563     18.0   20270.423     19.0  0.396985   \n",
       "18         4.0    5651.195      5.0    5651.195      5.0  0.928832   \n",
       "19        57.0   88668.614     77.0   91207.961     84.0  0.488643   \n",
       "20        19.0   11004.849     25.0   11004.849     27.0  1.124997   \n",
       "21        10.0   15146.233     14.0   15146.233     14.0  0.457378   \n",
       "22        14.0   15188.996     14.0   15188.996     14.0  1.429216   \n",
       "23         9.0    4497.068     10.0    4497.068     10.0  0.379650   \n",
       "24         3.0    3850.490      3.0    3850.490      3.0  1.355619   \n",
       "25         7.0   12047.551     16.0   12047.551     16.0  0.392880   \n",
       "26         3.0    1894.775      3.0    1894.775      3.0  1.032204   \n",
       "27        53.0   72774.603     69.0   73504.645     72.0  0.395166   \n",
       "28        15.0   25848.683     18.0   25848.683     18.0  0.997673   \n",
       "29         8.0   23804.910     20.0   36286.053     43.0  0.458371   \n",
       "30        19.0   36881.050     34.0   38298.322     37.0  0.393243   \n",
       "31         1.0   27130.255      6.0   27130.255      6.0  1.183066   \n",
       "32         2.0    2216.311      3.0    7245.647      5.0  0.370311   \n",
       "33        52.0   45302.785     56.0   64890.861     82.0  0.942409   \n",
       "34        13.0   41691.758     19.0   45574.123     26.0  1.158647   \n",
       "35         7.0   10187.982     10.0   10187.982     10.0  0.430328   \n",
       "36         9.0    6987.634     21.0    6987.634     21.0  0.426421   \n",
       "37         4.0     852.205      6.0     852.205      6.0  1.157439   \n",
       "38        11.0   12869.138     14.0   12869.138     14.0  1.000763   \n",
       "39         1.0     408.286      1.0     408.286      1.0  0.361805   \n",
       "40         2.0     782.936      2.0     782.936      2.0  0.903090   \n",
       "41         2.0    1167.766      3.0    1167.766      3.0  1.295547   \n",
       "Total    595.0  866316.860    812.0  907398.426    890.0       NaN   \n",
       "\n",
       "       Verified_EF  \n",
       "0              0.0  \n",
       "1              1.0  \n",
       "2              1.0  \n",
       "3              1.0  \n",
       "4              1.0  \n",
       "5              1.0  \n",
       "6              0.0  \n",
       "7              1.0  \n",
       "8              1.0  \n",
       "9              1.0  \n",
       "10             0.0  \n",
       "11             1.0  \n",
       "12             1.0  \n",
       "13             1.0  \n",
       "14             1.0  \n",
       "15             1.0  \n",
       "16             0.0  \n",
       "17             1.0  \n",
       "18             1.0  \n",
       "19             1.0  \n",
       "20             1.0  \n",
       "21             1.0  \n",
       "22             1.0  \n",
       "23             1.0  \n",
       "24             1.0  \n",
       "25             1.0  \n",
       "26             1.0  \n",
       "27             1.0  \n",
       "28             1.0  \n",
       "29             1.0  \n",
       "30             1.0  \n",
       "31             0.0  \n",
       "32             0.0  \n",
       "33             1.0  \n",
       "34             1.0  \n",
       "35             1.0  \n",
       "36             1.0  \n",
       "37             1.0  \n",
       "38             1.0  \n",
       "39             1.0  \n",
       "40             1.0  \n",
       "41             1.0  \n",
       "Total          NaN  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_table_gen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen.to_csv(output_directory_path + '/evaluation_table_capacities.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_cap.to_csv(output_directory_path + '/evaluation_table_generation.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Export final EF to csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "EF_per_tech_country.to_csv(processed_directory_path + '/EF_bottom_up_method.csv')\n",
    "EF_per_tech_country.to_csv(output_directory_path + '/EF_bottom_up_method.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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