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']\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": {
      "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>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>ALLOCATION_2010</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",
       "    </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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </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",
       "      <td>OPEN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14WENERGIEAGWT4S</th>\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>gas</td>\n",
       "      <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",
       "      <td>OPEN</td>\n",
       "      <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",
       "</div>"
      ],
      "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": "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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['gas', 'hard_coal', 'biomass', 'other_fossil', 'lignite'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 21,
     "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": 22,
   "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 the UBA and added a treshold of plus minus 50%.\n",
    "\n",
    "UBA:\n",
    "https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/2020-04-01_climate-change_13-2020_strommix_2020_fin.pdf\n",
    "\n",
    "Some other comparison numbers:\n",
    "https://www.gegenwind-saarland.de/Materialien/Energiewende/071031--VdI---CO2-Emissionen%20der%20Stromerzeugung_01.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# emissions space per technology in [t CO2/MWh] \n",
    "\n",
    "emission_space = {\"lignite\": (1.635,0.545),\n",
    "                  \"hard_coal\": (1.230,0.410),\n",
    "                  \"gas\": (0.555,0.185),\n",
    "                  \"other_fossil\": (2.250,0.750)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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": 25,
   "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": "markdown",
   "metadata": {},
   "source": [
    "Limit the results to validated data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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": 27,
   "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",
    "\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)\n",
    "\n",
    "ax.set_xlabel(\"Production technology\", fontsize=22)\n",
    "ax.set_ylabel(\"CO2 intensity (g CO2/kWh)\" , fontsize=22)\n",
    "\n",
    "ax.tick_params(axis='x',labelsize=19)\n",
    "ax.tick_params(axis='y',labelsize=19)\n",
    "\n",
    "labels = ['Gas','Coal','Other fossil','Lignite']\n",
    "\n",
    "ax.set_xticklabels(labels)\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "generation_unit_info_validated.to_csv(processed_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": 30,
   "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": 31,
   "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": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </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>0.288711</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  0.288711  \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": 32,
     "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": 33,
   "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": 34,
   "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": 35,
   "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": 36,
   "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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       "  </thead>\n",
       "  <tbody>\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",
       "      <td>340026</td>\n",
       "      <td>218704</td>\n",
       "      <td>103553</td>\n",
       "      <td>OPEN</td>\n",
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       "      <td>DK</td>\n",
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       "      <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",
       "      <td>10Y1001A1001A796</td>\n",
       "      <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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       "      <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",
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       "      <td>1089604</td>\n",
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       "      <td>1060165.23</td>\n",
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       "      <td>0.727577</td>\n",
       "      <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>1158930</td>\n",
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       "      <td>1193633.83</td>\n",
       "      <td>924609.000000</td>\n",
       "      <td>0.774617</td>\n",
       "      <td>True</td>\n",
       "      <td>0.775840</td>\n",
       "      <td>0.751762</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ],
      "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  0.288711    0.344882  \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": 36,
     "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": 37,
   "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": 38,
   "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": 39,
   "metadata": {},
   "outputs": [
    {
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>region</th>\n",
       "      <th colspan=\"9\" halign=\"left\">AT</th>\n",
       "      <th>BE</th>\n",
       "      <th>...</th>\n",
       "      <th>SI</th>\n",
       "      <th colspan=\"9\" halign=\"left\">SK</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable</th>\n",
       "      <th>biomass</th>\n",
       "      <th>gas</th>\n",
       "      <th>hard_coal</th>\n",
       "      <th>hydro</th>\n",
       "      <th>other_fossil</th>\n",
       "      <th>other_renewable</th>\n",
       "      <th>solar</th>\n",
       "      <th>waste</th>\n",
       "      <th>wind_onshore</th>\n",
       "      <th>biomass</th>\n",
       "      <th>...</th>\n",
       "      <th>wind_onshore</th>\n",
       "      <th>biomass</th>\n",
       "      <th>gas</th>\n",
       "      <th>hard_coal</th>\n",
       "      <th>hydro</th>\n",
       "      <th>lignite</th>\n",
       "      <th>nuclear</th>\n",
       "      <th>other_fossil</th>\n",
       "      <th>other_renewable</th>\n",
       "      <th>solar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>utc_timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2018-01-01 00:00:00+00:00</th>\n",
       "      <td>316.0</td>\n",
       "      <td>85.185998</td>\n",
       "      <td>189.813350</td>\n",
       "      <td>3633.105979</td>\n",
       "      <td>376.712329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>832.0</td>\n",
       "      <td>310.564338</td>\n",
       "      <td>...</td>\n",
       "      <td>0.70</td>\n",
       "      <td>75.757569</td>\n",
       "      <td>223.815846</td>\n",
       "      <td>71.307423</td>\n",
       "      <td>490.635794</td>\n",
       "      <td>179.5</td>\n",
       "      <td>1819.3</td>\n",
       "      <td>478.8</td>\n",
       "      <td>41.4</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 01:00:00+00:00</th>\n",
       "      <td>316.0</td>\n",
       "      <td>83.986195</td>\n",
       "      <td>188.547928</td>\n",
       "      <td>3557.076855</td>\n",
       "      <td>376.712329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>926.0</td>\n",
       "      <td>205.181412</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>75.488926</td>\n",
       "      <td>220.374486</td>\n",
       "      <td>71.159174</td>\n",
       "      <td>497.114042</td>\n",
       "      <td>177.9</td>\n",
       "      <td>1816.7</td>\n",
       "      <td>475.8</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 02:00:00+00:00</th>\n",
       "      <td>316.0</td>\n",
       "      <td>82.786393</td>\n",
       "      <td>188.547928</td>\n",
       "      <td>3439.774779</td>\n",
       "      <td>376.712329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>692.0</td>\n",
       "      <td>178.621922</td>\n",
       "      <td>...</td>\n",
       "      <td>0.57</td>\n",
       "      <td>75.488926</td>\n",
       "      <td>206.609047</td>\n",
       "      <td>69.231947</td>\n",
       "      <td>552.469700</td>\n",
       "      <td>174.7</td>\n",
       "      <td>1808.7</td>\n",
       "      <td>469.5</td>\n",
       "      <td>40.8</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 03:00:00+00:00</th>\n",
       "      <td>316.0</td>\n",
       "      <td>86.385801</td>\n",
       "      <td>188.547928</td>\n",
       "      <td>3432.171866</td>\n",
       "      <td>376.712329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>453.0</td>\n",
       "      <td>175.522424</td>\n",
       "      <td>...</td>\n",
       "      <td>0.62</td>\n",
       "      <td>79.787227</td>\n",
       "      <td>178.823253</td>\n",
       "      <td>67.156471</td>\n",
       "      <td>632.576139</td>\n",
       "      <td>168.5</td>\n",
       "      <td>1803.6</td>\n",
       "      <td>455.6</td>\n",
       "      <td>39.4</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 04:00:00+00:00</th>\n",
       "      <td>316.0</td>\n",
       "      <td>89.985209</td>\n",
       "      <td>188.547928</td>\n",
       "      <td>3616.814024</td>\n",
       "      <td>376.712329</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>175.362106</td>\n",
       "      <td>...</td>\n",
       "      <td>0.56</td>\n",
       "      <td>79.249940</td>\n",
       "      <td>182.901901</td>\n",
       "      <td>68.787202</td>\n",
       "      <td>605.737684</td>\n",
       "      <td>170.6</td>\n",
       "      <td>1809.1</td>\n",
       "      <td>461.5</td>\n",
       "      <td>40.4</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 214 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  ...           SI  \\\n",
       "variable                  wind_onshore     biomass  ... wind_onshore   \n",
       "utc_timestamp                                       ...                \n",
       "2018-01-01 00:00:00+00:00        832.0  310.564338  ...         0.70   \n",
       "2018-01-01 01:00:00+00:00        926.0  205.181412  ...         0.61   \n",
       "2018-01-01 02:00:00+00:00        692.0  178.621922  ...         0.57   \n",
       "2018-01-01 03:00:00+00:00        453.0  175.522424  ...         0.62   \n",
       "2018-01-01 04:00:00+00:00        321.0  175.362106  ...         0.56   \n",
       "\n",
       "region                            SK                                     \\\n",
       "variable                     biomass         gas  hard_coal       hydro   \n",
       "utc_timestamp                                                             \n",
       "2018-01-01 00:00:00+00:00  75.757569  223.815846  71.307423  490.635794   \n",
       "2018-01-01 01:00:00+00:00  75.488926  220.374486  71.159174  497.114042   \n",
       "2018-01-01 02:00:00+00:00  75.488926  206.609047  69.231947  552.469700   \n",
       "2018-01-01 03:00:00+00:00  79.787227  178.823253  67.156471  632.576139   \n",
       "2018-01-01 04:00:00+00:00  79.249940  182.901901  68.787202  605.737684   \n",
       "\n",
       "region                                                                        \n",
       "variable                  lignite nuclear other_fossil other_renewable solar  \n",
       "utc_timestamp                                                                 \n",
       "2018-01-01 00:00:00+00:00   179.5  1819.3        478.8            41.4   0.0  \n",
       "2018-01-01 01:00:00+00:00   177.9  1816.7        475.8            41.0   0.0  \n",
       "2018-01-01 02:00:00+00:00   174.7  1808.7        469.5            40.8   0.0  \n",
       "2018-01-01 03:00:00+00:00   168.5  1803.6        455.6            39.4   0.0  \n",
       "2018-01-01 04:00:00+00:00   170.6  1809.1        461.5            40.4   0.0  \n",
       "\n",
       "[5 rows x 214 columns]"
      ]
     },
     "execution_count": 39,
     "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": 40,
   "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": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "entsoe_gen_type = entsoe_gen_type.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rename column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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": 43,
   "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": 44,
   "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": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen_data_comparison = entsoe_gen_type.merge(Powerplants_gen_type_year, on=['MapCode','ProductionTypeName'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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": 47,
   "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": 48,
   "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": "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": 49,
   "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": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set new index\n",
    "gen_data_comparison = gen_data_comparison.set_index(['MapCode','ProductionTypeName'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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": 52,
   "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": 53,
   "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": 54,
   "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>0.288711</td>\n",
       "      <td>True</td>\n",
       "      <td>68.0</td>\n",
       "      <td>288.71</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>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",
       "    <tr>\n",
       "      <th>lignite</th>\n",
       "      <td>0.928296</td>\n",
       "      <td>True</td>\n",
       "      <td>58.0</td>\n",
       "      <td>928.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  EF Verified_EF  Coverage  \\\n",
       "MapCode ProductionTypeName                                   \n",
       "AT      gas                 0.288711        True      68.0   \n",
       "        hard_coal           0.884070        True      39.0   \n",
       "BE      gas                 0.389641        True      64.0   \n",
       "CZ      hard_coal           0.985546        True      36.0   \n",
       "        lignite             0.928296        True      58.0   \n",
       "\n",
       "                            EF_round_in_gCO2_kwh  \n",
       "MapCode ProductionTypeName                        \n",
       "AT      gas                               288.71  \n",
       "        hard_coal                         884.07  \n",
       "BE      gas                               389.64  \n",
       "CZ      hard_coal                         985.55  \n",
       "        lignite                           928.30  "
      ]
     },
     "execution_count": 54,
     "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": 55,
   "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": 55,
     "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": 56,
   "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": 57,
   "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": 58,
   "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": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_cap.loc[\"Total\"] = eval_table_cap.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>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",
       "      <th>Coverage</th>\n",
       "      <th>EF_round_in_gCO2_kwh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(AT, gas)</th>\n",
       "      <td>3.508</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.902</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.902</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.288711</td>\n",
       "      <td>True</td>\n",
       "      <td>68.0</td>\n",
       "      <td>288.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(AT, hard_coal)</th>\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>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>884.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(BE, gas)</th>\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>True</td>\n",
       "      <td>64.0</td>\n",
       "      <td>389.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(CZ, hard_coal)</th>\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>True</td>\n",
       "      <td>36.0</td>\n",
       "      <td>985.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(CZ, lignite)</th>\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>True</td>\n",
       "      <td>58.0</td>\n",
       "      <td>928.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, gas)</th>\n",
       "      <td>8.427</td>\n",
       "      <td>21.0</td>\n",
       "      <td>17.977</td>\n",
       "      <td>58.0</td>\n",
       "      <td>16.972</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.334091</td>\n",
       "      <td>False</td>\n",
       "      <td>17.0</td>\n",
       "      <td>334.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, hard_coal)</th>\n",
       "      <td>17.724</td>\n",
       "      <td>38.0</td>\n",
       "      <td>24.395</td>\n",
       "      <td>51.0</td>\n",
       "      <td>22.794</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.871051</td>\n",
       "      <td>True</td>\n",
       "      <td>85.0</td>\n",
       "      <td>871.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, lignite)</th>\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>True</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1125.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, other_fossil)</th>\n",
       "      <td>0.825</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.925</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.341</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.619695</td>\n",
       "      <td>True</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1619.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DK, gas)</th>\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>False</td>\n",
       "      <td>10.0</td>\n",
       "      <td>329.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DK, hard_coal)</th>\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>True</td>\n",
       "      <td>69.0</td>\n",
       "      <td>775.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(EE, other_fossil)</th>\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>True</td>\n",
       "      <td>109.0</td>\n",
       "      <td>1057.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(ES, gas)</th>\n",
       "      <td>20.686</td>\n",
       "      <td>61.0</td>\n",
       "      <td>24.671</td>\n",
       "      <td>72.0</td>\n",
       "      <td>24.671</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.386506</td>\n",
       "      <td>True</td>\n",
       "      <td>48.0</td>\n",
       "      <td>386.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(ES, hard_coal)</th>\n",
       "      <td>6.744</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.535</td>\n",
       "      <td>26.0</td>\n",
       "      <td>9.535</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.975777</td>\n",
       "      <td>True</td>\n",
       "      <td>84.0</td>\n",
       "      <td>975.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FI, hard_coal)</th>\n",
       "      <td>1.571</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.274</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.274</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.674454</td>\n",
       "      <td>True</td>\n",
       "      <td>69.0</td>\n",
       "      <td>674.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FI, other_fossil)</th>\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>False</td>\n",
       "      <td>13.0</td>\n",
       "      <td>759.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FR, gas)</th>\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>True</td>\n",
       "      <td>49.0</td>\n",
       "      <td>396.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FR, hard_coal)</th>\n",
       "      <td>2.930</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.930</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.930</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.834945</td>\n",
       "      <td>True</td>\n",
       "      <td>97.0</td>\n",
       "      <td>834.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GB, gas)</th>\n",
       "      <td>23.875</td>\n",
       "      <td>47.0</td>\n",
       "      <td>32.981</td>\n",
       "      <td>77.0</td>\n",
       "      <td>34.515</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.467992</td>\n",
       "      <td>True</td>\n",
       "      <td>56.0</td>\n",
       "      <td>467.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GB, hard_coal)</th>\n",
       "      <td>7.718</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.981</td>\n",
       "      <td>25.0</td>\n",
       "      <td>13.223</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.103223</td>\n",
       "      <td>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1103.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GR, gas)</th>\n",
       "      <td>3.589</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.899</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4.899</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.332135</td>\n",
       "      <td>True</td>\n",
       "      <td>71.0</td>\n",
       "      <td>332.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GR, lignite)</th>\n",
       "      <td>3.359</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.905</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.905</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.401712</td>\n",
       "      <td>True</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1401.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(HU, gas)</th>\n",
       "      <td>1.761</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.761</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.761</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.371916</td>\n",
       "      <td>True</td>\n",
       "      <td>72.0</td>\n",
       "      <td>371.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(HU, lignite)</th>\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>True</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1355.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IE, gas)</th>\n",
       "      <td>2.476</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>0.347416</td>\n",
       "      <td>True</td>\n",
       "      <td>60.0</td>\n",
       "      <td>347.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IE, hard_coal)</th>\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>True</td>\n",
       "      <td>89.0</td>\n",
       "      <td>1032.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IT, gas)</th>\n",
       "      <td>21.204</td>\n",
       "      <td>46.0</td>\n",
       "      <td>27.572</td>\n",
       "      <td>69.0</td>\n",
       "      <td>28.462</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.387735</td>\n",
       "      <td>True</td>\n",
       "      <td>50.0</td>\n",
       "      <td>387.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IT, hard_coal)</th>\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>True</td>\n",
       "      <td>59.0</td>\n",
       "      <td>997.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(NL, gas)</th>\n",
       "      <td>7.336</td>\n",
       "      <td>18.0</td>\n",
       "      <td>12.707</td>\n",
       "      <td>34.0</td>\n",
       "      <td>13.371</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.353883</td>\n",
       "      <td>True</td>\n",
       "      <td>38.0</td>\n",
       "      <td>353.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(NL, hard_coal)</th>\n",
       "      <td>1.362</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.662</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.662</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.948562</td>\n",
       "      <td>True</td>\n",
       "      <td>43.0</td>\n",
       "      <td>948.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, gas)</th>\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>False</td>\n",
       "      <td>10.0</td>\n",
       "      <td>370.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, hard_coal)</th>\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>True</td>\n",
       "      <td>56.0</td>\n",
       "      <td>942.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, lignite)</th>\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>True</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1158.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PT, gas)</th>\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>True</td>\n",
       "      <td>42.0</td>\n",
       "      <td>430.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PT, hard_coal)</th>\n",
       "      <td>0.576</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.756</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.756</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.546439</td>\n",
       "      <td>True</td>\n",
       "      <td>27.0</td>\n",
       "      <td>546.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, gas)</th>\n",
       "      <td>0.353</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.428</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3.428</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.315028</td>\n",
       "      <td>False</td>\n",
       "      <td>17.0</td>\n",
       "      <td>315.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, hard_coal)</th>\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>True</td>\n",
       "      <td>72.0</td>\n",
       "      <td>1157.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, lignite)</th>\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>True</td>\n",
       "      <td>88.0</td>\n",
       "      <td>1000.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SE, gas)</th>\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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>361.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SK, hard_coal)</th>\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>True</td>\n",
       "      <td>65.0</td>\n",
       "      <td>903.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SK, lignite)</th>\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>True</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1295.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>205.161</td>\n",
       "      <td>554.0</td>\n",
       "      <td>280.371</td>\n",
       "      <td>797.0</td>\n",
       "      <td>290.612</td>\n",
       "      <td>852.0</td>\n",
       "      <td>31.200616</td>\n",
       "      <td>35</td>\n",
       "      <td>2351.0</td>\n",
       "      <td>31200.59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      sum_3  count_3    sum_2  count_2    sum_1  count_1  \\\n",
       "(AT, gas)             3.508      9.0    3.902     12.0    3.902     12.0   \n",
       "(AT, hard_coal)       0.200      1.0    0.682      3.0    0.682      3.0   \n",
       "(BE, gas)             3.936     17.0    4.506     19.0    4.646     20.0   \n",
       "(CZ, hard_coal)       0.561      3.0    0.748      4.0    0.748      4.0   \n",
       "(CZ, lignite)         4.119     18.0    5.772     25.0    4.494     21.0   \n",
       "(DE, gas)             8.427     21.0   17.977     58.0   16.972     53.0   \n",
       "(DE, hard_coal)      17.724     38.0   24.395     51.0   22.794     48.0   \n",
       "(DE, lignite)        19.238     34.0   19.590     35.0   19.590     35.0   \n",
       "(DE, other_fossil)    0.825      3.0    0.925      4.0    2.341     11.0   \n",
       "(DK, gas)             0.108      1.0    0.108      1.0    0.108      1.0   \n",
       "(DK, hard_coal)       2.151      6.0    2.895      8.0    2.523      7.0   \n",
       "(EE, other_fossil)    1.971     11.0    2.251     13.0    2.251     13.0   \n",
       "(ES, gas)            20.686     61.0   24.671     72.0   24.671     72.0   \n",
       "(ES, hard_coal)       6.744     17.0    9.535     26.0    9.535     26.0   \n",
       "(FI, hard_coal)       1.571      9.0    2.274     12.0    2.274     12.0   \n",
       "(FI, other_fossil)    0.120      1.0    0.120      1.0    1.641     10.0   \n",
       "(FR, gas)             4.881     11.0    6.120     18.0    6.521     19.0   \n",
       "(FR, hard_coal)       2.930      5.0    2.930      5.0    2.930      5.0   \n",
       "(GB, gas)            23.875     47.0   32.981     77.0   34.515     84.0   \n",
       "(GB, hard_coal)       7.718     15.0   12.981     25.0   13.223     27.0   \n",
       "(GR, gas)             3.589     11.0    4.899     14.0    4.899     14.0   \n",
       "(GR, lignite)         3.359     12.0    3.905     14.0    3.905     14.0   \n",
       "(HU, gas)             1.761     10.0    1.761     10.0    1.761     10.0   \n",
       "(HU, lignite)         0.613      3.0    0.613      3.0    0.613      3.0   \n",
       "(IE, gas)             2.476      7.0    3.730     16.0    3.730     16.0   \n",
       "(IE, hard_coal)       0.855      3.0    0.855      3.0    0.855      3.0   \n",
       "(IT, gas)            21.204     46.0   27.572     69.0   28.462     72.0   \n",
       "(IT, hard_coal)       5.081     15.0    6.926     18.0    6.926     18.0   \n",
       "(NL, gas)             7.336     18.0   12.707     34.0   13.371     37.0   \n",
       "(NL, hard_coal)       1.362      2.0    4.662      6.0    4.662      6.0   \n",
       "(PL, gas)             0.332      2.0    0.457      3.0    1.572      5.0   \n",
       "(PL, hard_coal)      12.056     52.0   14.901     56.0   19.861     82.0   \n",
       "(PL, lignite)         5.576     13.0    7.064     19.0    8.678     26.0   \n",
       "(PT, gas)             2.838      7.0    3.828     10.0    3.828     10.0   \n",
       "(PT, hard_coal)       0.576      2.0    1.756      6.0    1.756      6.0   \n",
       "(RO, gas)             0.353      3.0    3.428     21.0    3.428     21.0   \n",
       "(RO, hard_coal)       0.743      4.0    1.133      6.0    1.133      6.0   \n",
       "(RO, lignite)         3.068     11.0    4.011     14.0    4.011     14.0   \n",
       "(SE, gas)             0.250      1.0    0.250      1.0    0.250      1.0   \n",
       "(SK, hard_coal)       0.220      2.0    0.220      2.0    0.220      2.0   \n",
       "(SK, lignite)         0.220      2.0    0.330      3.0    0.330      3.0   \n",
       "Total               205.161    554.0  280.371    797.0  290.612    852.0   \n",
       "\n",
       "                           EF Verified_EF  Coverage  EF_round_in_gCO2_kwh  \n",
       "(AT, gas)            0.288711        True      68.0                288.71  \n",
       "(AT, hard_coal)      0.884070        True      39.0                884.07  \n",
       "(BE, gas)            0.389641        True      64.0                389.64  \n",
       "(CZ, hard_coal)      0.985546        True      36.0                985.55  \n",
       "(CZ, lignite)        0.928296        True      58.0                928.30  \n",
       "(DE, gas)            0.334091       False      17.0                334.09  \n",
       "(DE, hard_coal)      0.871051        True      85.0                871.05  \n",
       "(DE, lignite)        1.125560        True      96.0               1125.56  \n",
       "(DE, other_fossil)   1.619695        True      50.0               1619.69  \n",
       "(DK, gas)            0.329783       False      10.0                329.78  \n",
       "(DK, hard_coal)      0.775840        True      69.0                775.84  \n",
       "(EE, other_fossil)   1.057973        True     109.0               1057.97  \n",
       "(ES, gas)            0.386506        True      48.0                386.51  \n",
       "(ES, hard_coal)      0.975777        True      84.0                975.78  \n",
       "(FI, hard_coal)      0.674454        True      69.0                674.45  \n",
       "(FI, other_fossil)   0.759814       False      13.0                759.81  \n",
       "(FR, gas)            0.396985        True      49.0                396.98  \n",
       "(FR, hard_coal)      0.834945        True      97.0                834.94  \n",
       "(GB, gas)            0.467992        True      56.0                467.99  \n",
       "(GB, hard_coal)      1.103223        True      39.0               1103.22  \n",
       "(GR, gas)            0.332135        True      71.0                332.13  \n",
       "(GR, lignite)        1.401712        True      90.0               1401.71  \n",
       "(HU, gas)            0.371916        True      72.0                371.92  \n",
       "(HU, lignite)        1.355619        True      81.0               1355.62  \n",
       "(IE, gas)            0.347416        True      60.0                347.42  \n",
       "(IE, hard_coal)      1.032204        True      89.0               1032.20  \n",
       "(IT, gas)            0.387735        True      50.0                387.74  \n",
       "(IT, hard_coal)      0.997673        True      59.0                997.67  \n",
       "(NL, gas)            0.353883        True      38.0                353.88  \n",
       "(NL, hard_coal)      0.948562        True      43.0                948.56  \n",
       "(PL, gas)            0.370311       False      10.0                370.31  \n",
       "(PL, hard_coal)      0.942409        True      56.0                942.41  \n",
       "(PL, lignite)        1.158647        True      78.0               1158.65  \n",
       "(PT, gas)            0.430328        True      42.0                430.33  \n",
       "(PT, hard_coal)      0.546439        True      27.0                546.44  \n",
       "(RO, gas)            0.315028       False      17.0                315.03  \n",
       "(RO, hard_coal)      1.157439        True      72.0               1157.44  \n",
       "(RO, lignite)        1.000763        True      88.0               1000.76  \n",
       "(SE, gas)            0.361805         NaN       NaN                361.80  \n",
       "(SK, hard_coal)      0.903090        True      65.0                903.09  \n",
       "(SK, lignite)        1.295547        True      87.0               1295.55  \n",
       "Total               31.200616          35    2351.0              31200.59  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_table_cap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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": 62,
   "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": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen.loc[\"Total\"] = eval_table_gen.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "      <th>Coverage</th>\n",
       "      <th>EF_round_in_gCO2_kwh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(AT, gas)</th>\n",
       "      <td>6660.371</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7457.226</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7457.226</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.288711</td>\n",
       "      <td>True</td>\n",
       "      <td>68.0</td>\n",
       "      <td>288.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(AT, hard_coal)</th>\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>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>884.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(BE, gas)</th>\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>True</td>\n",
       "      <td>64.0</td>\n",
       "      <td>389.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(CZ, hard_coal)</th>\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>True</td>\n",
       "      <td>36.0</td>\n",
       "      <td>985.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(CZ, lignite)</th>\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>True</td>\n",
       "      <td>58.0</td>\n",
       "      <td>928.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, gas)</th>\n",
       "      <td>14844.429</td>\n",
       "      <td>21.0</td>\n",
       "      <td>29445.917</td>\n",
       "      <td>58.0</td>\n",
       "      <td>29024.315</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.334091</td>\n",
       "      <td>False</td>\n",
       "      <td>17.0</td>\n",
       "      <td>334.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, hard_coal)</th>\n",
       "      <td>61792.600</td>\n",
       "      <td>38.0</td>\n",
       "      <td>78632.750</td>\n",
       "      <td>51.0</td>\n",
       "      <td>73274.329</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.871051</td>\n",
       "      <td>True</td>\n",
       "      <td>85.0</td>\n",
       "      <td>871.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, lignite)</th>\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>True</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1125.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DE, other_fossil)</th>\n",
       "      <td>3303.138</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3759.405</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6423.292</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.619695</td>\n",
       "      <td>True</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1619.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DK, gas)</th>\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>False</td>\n",
       "      <td>10.0</td>\n",
       "      <td>329.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(DK, hard_coal)</th>\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>True</td>\n",
       "      <td>69.0</td>\n",
       "      <td>775.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(EE, other_fossil)</th>\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>True</td>\n",
       "      <td>109.0</td>\n",
       "      <td>1057.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(ES, gas)</th>\n",
       "      <td>25976.040</td>\n",
       "      <td>61.0</td>\n",
       "      <td>26795.465</td>\n",
       "      <td>72.0</td>\n",
       "      <td>26795.465</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.386506</td>\n",
       "      <td>True</td>\n",
       "      <td>48.0</td>\n",
       "      <td>386.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(ES, hard_coal)</th>\n",
       "      <td>27162.324</td>\n",
       "      <td>17.0</td>\n",
       "      <td>35004.169</td>\n",
       "      <td>26.0</td>\n",
       "      <td>35004.169</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.975777</td>\n",
       "      <td>True</td>\n",
       "      <td>84.0</td>\n",
       "      <td>975.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FI, hard_coal)</th>\n",
       "      <td>4093.411</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5099.777</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5099.777</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.674454</td>\n",
       "      <td>True</td>\n",
       "      <td>69.0</td>\n",
       "      <td>674.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FI, other_fossil)</th>\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>False</td>\n",
       "      <td>13.0</td>\n",
       "      <td>759.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FR, gas)</th>\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>True</td>\n",
       "      <td>49.0</td>\n",
       "      <td>396.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(FR, hard_coal)</th>\n",
       "      <td>5651.195</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5651.195</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5651.195</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.834945</td>\n",
       "      <td>True</td>\n",
       "      <td>97.0</td>\n",
       "      <td>834.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GB, gas)</th>\n",
       "      <td>72157.153</td>\n",
       "      <td>47.0</td>\n",
       "      <td>88668.614</td>\n",
       "      <td>77.0</td>\n",
       "      <td>91207.961</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.467992</td>\n",
       "      <td>True</td>\n",
       "      <td>56.0</td>\n",
       "      <td>467.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GB, hard_coal)</th>\n",
       "      <td>6589.546</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11004.849</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11004.849</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.103223</td>\n",
       "      <td>True</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1103.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GR, gas)</th>\n",
       "      <td>10755.974</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15146.233</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15146.233</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.332135</td>\n",
       "      <td>True</td>\n",
       "      <td>71.0</td>\n",
       "      <td>332.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(GR, lignite)</th>\n",
       "      <td>13763.479</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15188.996</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15188.996</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.401712</td>\n",
       "      <td>True</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1401.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(HU, gas)</th>\n",
       "      <td>4497.068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4497.068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4497.068</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.371916</td>\n",
       "      <td>True</td>\n",
       "      <td>72.0</td>\n",
       "      <td>371.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(HU, lignite)</th>\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>True</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1355.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IE, gas)</th>\n",
       "      <td>8978.536</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>0.347416</td>\n",
       "      <td>True</td>\n",
       "      <td>60.0</td>\n",
       "      <td>347.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IE, hard_coal)</th>\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>True</td>\n",
       "      <td>89.0</td>\n",
       "      <td>1032.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IT, gas)</th>\n",
       "      <td>61986.934</td>\n",
       "      <td>46.0</td>\n",
       "      <td>72774.603</td>\n",
       "      <td>69.0</td>\n",
       "      <td>73504.645</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.387735</td>\n",
       "      <td>True</td>\n",
       "      <td>50.0</td>\n",
       "      <td>387.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(IT, hard_coal)</th>\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>True</td>\n",
       "      <td>59.0</td>\n",
       "      <td>997.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(NL, gas)</th>\n",
       "      <td>27115.014</td>\n",
       "      <td>18.0</td>\n",
       "      <td>36881.050</td>\n",
       "      <td>34.0</td>\n",
       "      <td>38298.322</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.353883</td>\n",
       "      <td>True</td>\n",
       "      <td>38.0</td>\n",
       "      <td>353.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(NL, hard_coal)</th>\n",
       "      <td>7229.582</td>\n",
       "      <td>2.0</td>\n",
       "      <td>27130.255</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27130.255</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.948562</td>\n",
       "      <td>True</td>\n",
       "      <td>43.0</td>\n",
       "      <td>948.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, gas)</th>\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>False</td>\n",
       "      <td>10.0</td>\n",
       "      <td>370.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, hard_coal)</th>\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>True</td>\n",
       "      <td>56.0</td>\n",
       "      <td>942.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PL, lignite)</th>\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>True</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1158.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PT, gas)</th>\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>True</td>\n",
       "      <td>42.0</td>\n",
       "      <td>430.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(PT, hard_coal)</th>\n",
       "      <td>3065.689</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11165.454</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11165.454</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.546439</td>\n",
       "      <td>True</td>\n",
       "      <td>27.0</td>\n",
       "      <td>546.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, gas)</th>\n",
       "      <td>1790.651</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6987.634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6987.634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.315028</td>\n",
       "      <td>False</td>\n",
       "      <td>17.0</td>\n",
       "      <td>315.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, hard_coal)</th>\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>True</td>\n",
       "      <td>72.0</td>\n",
       "      <td>1157.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RO, lignite)</th>\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>True</td>\n",
       "      <td>88.0</td>\n",
       "      <td>1000.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SE, gas)</th>\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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>361.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SK, hard_coal)</th>\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>True</td>\n",
       "      <td>65.0</td>\n",
       "      <td>903.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(SK, lignite)</th>\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>True</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1295.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>689045.689</td>\n",
       "      <td>554.0</td>\n",
       "      <td>851948.368</td>\n",
       "      <td>797.0</td>\n",
       "      <td>880548.791</td>\n",
       "      <td>852.0</td>\n",
       "      <td>31.200616</td>\n",
       "      <td>35</td>\n",
       "      <td>2351.0</td>\n",
       "      <td>31200.59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         sum_3  count_3       sum_2  count_2       sum_1  \\\n",
       "(AT, gas)             6660.371      9.0    7457.226     12.0    7457.226   \n",
       "(AT, hard_coal)        693.857      1.0    1439.148      3.0    1439.148   \n",
       "(BE, gas)            14216.707     17.0   16372.357     19.0   17181.875   \n",
       "(CZ, hard_coal)       1243.426      3.0    1243.426      4.0    1243.426   \n",
       "(CZ, lignite)        19775.004     18.0   26607.733     25.0   21876.551   \n",
       "(DE, gas)            14844.429     21.0   29445.917     58.0   29024.315   \n",
       "(DE, hard_coal)      61792.600     38.0   78632.750     51.0   73274.329   \n",
       "(DE, lignite)       129230.488     34.0  129230.488     35.0  129230.488   \n",
       "(DE, other_fossil)    3303.138      3.0    3759.405      4.0    6423.292   \n",
       "(DK, gas)              273.443      1.0     273.443      1.0     273.443   \n",
       "(DK, hard_coal)       4792.089      6.0    6332.337      8.0    5562.213   \n",
       "(EE, other_fossil)    9592.431     11.0    9592.431     13.0    9592.431   \n",
       "(ES, gas)            25976.040     61.0   26795.465     72.0   26795.465   \n",
       "(ES, hard_coal)      27162.324     17.0   35004.169     26.0   35004.169   \n",
       "(FI, hard_coal)       4093.411      9.0    5099.777     12.0    5099.777   \n",
       "(FI, other_fossil)     725.116      1.0     725.116      1.0    3397.165   \n",
       "(FR, gas)            15259.900     11.0   19720.563     18.0   20270.423   \n",
       "(FR, hard_coal)       5651.195      5.0    5651.195      5.0    5651.195   \n",
       "(GB, gas)            72157.153     47.0   88668.614     77.0   91207.961   \n",
       "(GB, hard_coal)       6589.546     15.0   11004.849     25.0   11004.849   \n",
       "(GR, gas)            10755.974     11.0   15146.233     14.0   15146.233   \n",
       "(GR, lignite)        13763.479     12.0   15188.996     14.0   15188.996   \n",
       "(HU, gas)             4497.068     10.0    4497.068     10.0    4497.068   \n",
       "(HU, lignite)         3850.490      3.0    3850.490      3.0    3850.490   \n",
       "(IE, gas)             8978.536      7.0   12047.551     16.0   12047.551   \n",
       "(IE, hard_coal)       1894.775      3.0    1894.775      3.0    1894.775   \n",
       "(IT, gas)            61986.934     46.0   72774.603     69.0   73504.645   \n",
       "(IT, hard_coal)      17039.711     15.0   25848.683     18.0   25848.683   \n",
       "(NL, gas)            27115.014     18.0   36881.050     34.0   38298.322   \n",
       "(NL, hard_coal)       7229.582      2.0   27130.255      6.0   27130.255   \n",
       "(PL, gas)             1294.905      2.0    2216.311      3.0    7245.647   \n",
       "(PL, hard_coal)      44401.449     52.0   45302.785     56.0   64890.861   \n",
       "(PL, lignite)        35099.139     13.0   41691.758     19.0   45574.123   \n",
       "(PT, gas)             6169.294      7.0   10187.982     10.0   10187.982   \n",
       "(PT, hard_coal)       3065.689      2.0   11165.454      6.0   11165.454   \n",
       "(RO, gas)             1790.651      3.0    6987.634     21.0    6987.634   \n",
       "(RO, hard_coal)        852.205      4.0     852.205      6.0     852.205   \n",
       "(RO, lignite)        12869.138     11.0   12869.138     14.0   12869.138   \n",
       "(SE, gas)              408.286      1.0     408.286      1.0     408.286   \n",
       "(SK, hard_coal)        782.936      2.0     782.936      2.0     782.936   \n",
       "(SK, lignite)         1167.766      2.0    1167.766      3.0    1167.766   \n",
       "Total               689045.689    554.0  851948.368    797.0  880548.791   \n",
       "\n",
       "                    count_1         EF Verified_EF  Coverage  \\\n",
       "(AT, gas)              12.0   0.288711        True      68.0   \n",
       "(AT, hard_coal)         3.0   0.884070        True      39.0   \n",
       "(BE, gas)              20.0   0.389641        True      64.0   \n",
       "(CZ, hard_coal)         4.0   0.985546        True      36.0   \n",
       "(CZ, lignite)          21.0   0.928296        True      58.0   \n",
       "(DE, gas)              53.0   0.334091       False      17.0   \n",
       "(DE, hard_coal)        48.0   0.871051        True      85.0   \n",
       "(DE, lignite)          35.0   1.125560        True      96.0   \n",
       "(DE, other_fossil)     11.0   1.619695        True      50.0   \n",
       "(DK, gas)               1.0   0.329783       False      10.0   \n",
       "(DK, hard_coal)         7.0   0.775840        True      69.0   \n",
       "(EE, other_fossil)     13.0   1.057973        True     109.0   \n",
       "(ES, gas)              72.0   0.386506        True      48.0   \n",
       "(ES, hard_coal)        26.0   0.975777        True      84.0   \n",
       "(FI, hard_coal)        12.0   0.674454        True      69.0   \n",
       "(FI, other_fossil)     10.0   0.759814       False      13.0   \n",
       "(FR, gas)              19.0   0.396985        True      49.0   \n",
       "(FR, hard_coal)         5.0   0.834945        True      97.0   \n",
       "(GB, gas)              84.0   0.467992        True      56.0   \n",
       "(GB, hard_coal)        27.0   1.103223        True      39.0   \n",
       "(GR, gas)              14.0   0.332135        True      71.0   \n",
       "(GR, lignite)          14.0   1.401712        True      90.0   \n",
       "(HU, gas)              10.0   0.371916        True      72.0   \n",
       "(HU, lignite)           3.0   1.355619        True      81.0   \n",
       "(IE, gas)              16.0   0.347416        True      60.0   \n",
       "(IE, hard_coal)         3.0   1.032204        True      89.0   \n",
       "(IT, gas)              72.0   0.387735        True      50.0   \n",
       "(IT, hard_coal)        18.0   0.997673        True      59.0   \n",
       "(NL, gas)              37.0   0.353883        True      38.0   \n",
       "(NL, hard_coal)         6.0   0.948562        True      43.0   \n",
       "(PL, gas)               5.0   0.370311       False      10.0   \n",
       "(PL, hard_coal)        82.0   0.942409        True      56.0   \n",
       "(PL, lignite)          26.0   1.158647        True      78.0   \n",
       "(PT, gas)              10.0   0.430328        True      42.0   \n",
       "(PT, hard_coal)         6.0   0.546439        True      27.0   \n",
       "(RO, gas)              21.0   0.315028       False      17.0   \n",
       "(RO, hard_coal)         6.0   1.157439        True      72.0   \n",
       "(RO, lignite)          14.0   1.000763        True      88.0   \n",
       "(SE, gas)               1.0   0.361805         NaN       NaN   \n",
       "(SK, hard_coal)         2.0   0.903090        True      65.0   \n",
       "(SK, lignite)           3.0   1.295547        True      87.0   \n",
       "Total                 852.0  31.200616          35    2351.0   \n",
       "\n",
       "                    EF_round_in_gCO2_kwh  \n",
       "(AT, gas)                         288.71  \n",
       "(AT, hard_coal)                   884.07  \n",
       "(BE, gas)                         389.64  \n",
       "(CZ, hard_coal)                   985.55  \n",
       "(CZ, lignite)                     928.30  \n",
       "(DE, gas)                         334.09  \n",
       "(DE, hard_coal)                   871.05  \n",
       "(DE, lignite)                    1125.56  \n",
       "(DE, other_fossil)               1619.69  \n",
       "(DK, gas)                         329.78  \n",
       "(DK, hard_coal)                   775.84  \n",
       "(EE, other_fossil)               1057.97  \n",
       "(ES, gas)                         386.51  \n",
       "(ES, hard_coal)                   975.78  \n",
       "(FI, hard_coal)                   674.45  \n",
       "(FI, other_fossil)                759.81  \n",
       "(FR, gas)                         396.98  \n",
       "(FR, hard_coal)                   834.94  \n",
       "(GB, gas)                         467.99  \n",
       "(GB, hard_coal)                  1103.22  \n",
       "(GR, gas)                         332.13  \n",
       "(GR, lignite)                    1401.71  \n",
       "(HU, gas)                         371.92  \n",
       "(HU, lignite)                    1355.62  \n",
       "(IE, gas)                         347.42  \n",
       "(IE, hard_coal)                  1032.20  \n",
       "(IT, gas)                         387.74  \n",
       "(IT, hard_coal)                   997.67  \n",
       "(NL, gas)                         353.88  \n",
       "(NL, hard_coal)                   948.56  \n",
       "(PL, gas)                         370.31  \n",
       "(PL, hard_coal)                   942.41  \n",
       "(PL, lignite)                    1158.65  \n",
       "(PT, gas)                         430.33  \n",
       "(PT, hard_coal)                   546.44  \n",
       "(RO, gas)                         315.03  \n",
       "(RO, hard_coal)                  1157.44  \n",
       "(RO, lignite)                    1000.76  \n",
       "(SE, gas)                         361.80  \n",
       "(SK, hard_coal)                   903.09  \n",
       "(SK, lignite)                    1295.55  \n",
       "Total                           31200.59  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_table_gen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_table_gen.to_csv(output_directory_path + '/evaluation_table_capacities.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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": 67,
   "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')"
   ]
  }
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