{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m project at `c:\\Users\\lilang\\OneDrive\\OneDrive - Danmarks Tekniske Universitet\\General (RECs review)\\Studies\\2. Energy Systems Analysis\\KPIs\\visualization`\n"
     ]
    }
   ],
   "source": [
    "using Pkg\n",
    "Pkg.activate(pwd())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "using CSV, DataFrames, CairoMakie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "supLine (generic function with 1 method)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#used functions\n",
    "import CairoMakie.subscript\n",
    "subscript(i::Integer) = i<0 ? error(\"$i is negative\") : join('₀'+d for d in reverse(digits(i)))\n",
    "\n",
    "function supLine(p1, p2; x=0,y=8)\n",
    "    [p1 .+ Point2f(x,y), p1, p2, p2 .+ Point2f(x,y)]\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capacity figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>15×48 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">Study</th><th style = \"text-align: left;\">KPIs</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal2</th><th style = \"text-align: left;\">annual_WYCO2</th><th style = \"text-align: left;\">annual_DE</th><th style = \"text-align: left;\">annual_NL</th><th style = \"text-align: left;\">annual_IE</th><th style = \"text-align: left;\">annual_DK</th><th style = \"text-align: left;\">emissions_Cal</th><th style = \"text-align: left;\">emissions_WYCO</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal2</th><th style = \"text-align: left;\">hourly_WYCO2</th><th style = \"text-align: left;\">hourly_DE</th><th style = \"text-align: left;\">hourly_NL</th><th style = \"text-align: left;\">hourly_IE</th><th style = \"text-align: left;\">hourly_DK</th><th style = \"text-align: left;\">free_DE</th><th style = \"text-align: left;\">free_NL</th><th style = \"text-align: left;\">free_CZ</th><th style = \"text-align: left;\">free_ES</th><th style = \"text-align: left;\">free_PL</th><th style = \"text-align: left;\">free_PT</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Any\" style = \"text-align: left;\">Any</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0.0003</td><td style = \"text-align: right;\">0.0002</td><td style = \"text-align: right;\">-0.0005</td><td style = \"text-align: right;\">0.0286</td><td style = \"text-align: right;\">0.0006</td><td style = \"text-align: right;\">-0.0012</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0128</td><td style = \"text-align: right;\">0.3134</td><td style = \"text-align: right;\">0.2143</td><td style = \"text-align: right;\">0.0112</td><td style = \"text-align: right;\">0.096</td><td style = \"text-align: right;\">0.0019</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">2</td><td style = \"text-align: right;\">631.345</td><td style = \"text-align: right;\">-2537.6</td><td style = \"text-align: right;\">-4007.64</td><td style = \"text-align: right;\">1226.14</td><td style = \"text-align: right;\">-3125.5</td><td style = \"text-align: right;\">401.249</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-1539.89</td><td style = \"text-align: right;\">-1453.87</td><td style = \"text-align: right;\">-2517.69</td><td style = \"text-align: right;\">-3.11574e5</td><td style = \"text-align: right;\">-2119.34</td><td style = \"text-align: right;\">-6888.44</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.1866</td><td style = \"text-align: right;\">-0.544</td><td style = \"text-align: right;\">1.9891</td><td style = \"text-align: right;\">35.0431</td><td style = \"text-align: right;\">-1.8224</td><td style = \"text-align: right;\">-0.4735</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-19.7608</td><td style = \"text-align: right;\">-455.637</td><td style = \"text-align: right;\">-539.588</td><td style = \"text-align: right;\">-3486.62</td><td style = \"text-align: right;\">-203.41</td><td style = \"text-align: right;\">-12.9977</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: left;\">Zeyen et al. [48]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: left;\">Zeyen et al. 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text-align: right;\">14</td><td style = \"text-align: left;\">Xu et al. 2024 [20]</td><td style = \"text-align: right;\">2</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-1042.04</td><td style = \"text-align: right;\">234.451</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-1564.02</td><td style = \"text-align: right;\">-4313.28</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-889.443</td><td style = \"text-align: right;\">-1901.06</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15</td><td style = \"text-align: left;\">Xu et al. 2024 [20]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.3022</td><td style = \"text-align: right;\">-0.3344</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.3076</td><td style = \"text-align: right;\">-5.0296</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-504.373</td><td style = \"text-align: right;\">-1259.47</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& Study & KPIs & annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & \\\\\n",
       "\t\\hline\n",
       "\t& Any & Int64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & Ricks et al. [33] & 1 & 0.0003 & 0.0002 & -0.0005 & 0.0286 & $\\dots$ \\\\\n",
       "\t2 & Ricks et al. [33] & 2 & 631.345 & -2537.6 & -4007.64 & 1226.14 & $\\dots$ \\\\\n",
       "\t3 & Ricks et al. [33] & 3 & 0.1866 & -0.544 & 1.9891 & 35.0431 & $\\dots$ \\\\\n",
       "\t4 & Zeyen et al. [48] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t5 & Zeyen et al. [48] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t6 & Zeyen et al. [48] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t7 & Riepin and Brown [45] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t8 & Riepin and Brown [45] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t9 & Riepin and Brown [45] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t10 & Xu et al. 2022 [69] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t11 & Xu et al. 2022 [69] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t12 & Xu et al. 2022 [69] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t13 & Xu et al. 2024 [20] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t14 & Xu et al. 2024 [20] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t15 & Xu et al. 2024 [20] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m15×48 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m Study                 \u001b[0m\u001b[1m KPIs  \u001b[0m\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW \u001b[0m\u001b[1m a\u001b[0m ⋯\n",
       "     │\u001b[90m Any                   \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Float64     \u001b[0m\u001b[90m Float64       \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m F\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ Ricks et al. [33]          1       0.0003         0.0002     -0.0005    ⋯\n",
       "   2 │ Ricks et al. [33]          2     631.345      -2537.6     -4007.64\n",
       "   3 │ Ricks et al. [33]          3       0.1866        -0.544       1.9891\n",
       "   4 │ Zeyen et al. [48]          1       0.0            0.0         0.0\n",
       "   5 │ Zeyen et al. [48]          2       0.0            0.0         0.0       ⋯\n",
       "   6 │ Zeyen et al. [48]          3       0.0            0.0         0.0\n",
       "   7 │ Riepin and Brown [45]      1       0.0            0.0         0.0\n",
       "   8 │ Riepin and Brown [45]      2       0.0            0.0         0.0\n",
       "   9 │ Riepin and Brown [45]      3       0.0            0.0         0.0       ⋯\n",
       "  10 │ Xu et al. 2022 [69]        1       0.0            0.0         0.0\n",
       "  11 │ Xu et al. 2022 [69]        2       0.0            0.0         0.0\n",
       "  12 │ Xu et al. 2022 [69]        3       0.0            0.0         0.0\n",
       "  13 │ Xu et al. 2024 [20]        1       0.0            0.0         0.0       ⋯\n",
       "  14 │ Xu et al. 2024 [20]        2       0.0            0.0         0.0\n",
       "  15 │ Xu et al. 2024 [20]        3       0.0            0.0         0.0\n",
       "\u001b[36m                                                              43 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "KPIs_cap = CSV.read(\"Overall_KPIs_cap.csv\", DataFrame; header=1, footerskip=3)\n",
    "# Extract xticks\n",
    "xticks_cap = CSV.read(\"Overall_KPIs_cap.csv\", DataFrame; header=1, skipto=19)\n",
    "xticks_cap = xticks_cap[:, 3:end-6]\n",
    "\n",
    "# replace missing values with 0\n",
    "mapcols!(col -> replace(col, missing => 0), KPIs_cap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>1×40 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal2</th><th style = \"text-align: left;\">annual_WYCO2</th><th style = \"text-align: left;\">annual_DE</th><th style = \"text-align: left;\">annual_NL</th><th style = \"text-align: left;\">annual_IE</th><th style = \"text-align: left;\">annual_DK</th><th style = \"text-align: left;\">emissions_Cal</th><th style = \"text-align: left;\">emissions_WYCO</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal2</th><th style = \"text-align: left;\">hourly_WYCO2</th><th style = \"text-align: left;\">hourly_DE</th><th style = \"text-align: left;\">hourly_NL</th><th style = \"text-align: left;\">hourly_IE</th><th style = \"text-align: left;\">hourly_DK</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">1</td><td style = \"text-align: left;\">NMAZ</td><td style = \"text-align: left;\">NorCal</td><td style = \"text-align: left;\">PNW</td><td style = \"text-align: left;\">SoCal</td><td style = \"text-align: left;\">WeccN</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">CZ</td><td style = \"text-align: left;\">ES</td><td style = \"text-align: left;\">PL</td><td style = \"text-align: left;\">PT</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">IE</td><td style = \"text-align: left;\">DK</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">NMAZ</td><td style = \"text-align: left;\">NorCal</td><td style = \"text-align: left;\">PNW</td><td style = \"text-align: left;\">SoCal</td><td style = \"text-align: left;\">WeccN</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">CZ</td><td style = \"text-align: left;\">ES</td><td style = \"text-align: left;\">PL</td><td style = \"text-align: left;\">PT</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">IE</td><td style = \"text-align: left;\">DK</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & annual\\_WeccN & annual\\_WYCO & \\\\\n",
       "\t\\hline\n",
       "\t& String7 & String7 & String3 & String7 & String7 & String7 & \\\\\n",
       "\t\\hline\n",
       "\t1 & NMAZ & NorCal & PNW & SoCal & WeccN & WYCO & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m1×40 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW \u001b[0m\u001b[1m annual_SoCal \u001b[0m\u001b[1m annual_WeccN \u001b[0m\u001b[1m ann\u001b[0m ⋯\n",
       "     │\u001b[90m String7     \u001b[0m\u001b[90m String7       \u001b[0m\u001b[90m String3    \u001b[0m\u001b[90m String7      \u001b[0m\u001b[90m String7      \u001b[0m\u001b[90m Str\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ NMAZ         NorCal         PNW         SoCal         WeccN         WYC ⋯\n",
       "\u001b[36m                                                              35 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xticks_cap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>5×40 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal2</th><th style = \"text-align: left;\">annual_WYCO2</th><th style = \"text-align: left;\">annual_DE</th><th style = \"text-align: left;\">annual_NL</th><th style = \"text-align: left;\">annual_IE</th><th style = \"text-align: left;\">annual_DK</th><th style = \"text-align: left;\">emissions_Cal</th><th style = \"text-align: left;\">emissions_WYCO</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal2</th><th style = \"text-align: left;\">hourly_WYCO2</th><th style = \"text-align: left;\">hourly_DE</th><th style = \"text-align: left;\">hourly_NL</th><th style = \"text-align: left;\">hourly_IE</th><th style = \"text-align: left;\">hourly_DK</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">0.1866</td><td style = \"text-align: right;\">-0.544</td><td style = \"text-align: right;\">1.9891</td><td style = \"text-align: right;\">35.0431</td><td style = \"text-align: right;\">-1.8224</td><td style = \"text-align: right;\">-0.4735</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-19.7608</td><td style = \"text-align: right;\">-455.637</td><td style = \"text-align: right;\">-539.588</td><td style = \"text-align: right;\">-3486.62</td><td style = \"text-align: right;\">-203.41</td><td style = \"text-align: right;\">-12.9977</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">4</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-328.757</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-773.045</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.3022</td><td style = \"text-align: right;\">-0.3344</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.3076</td><td style = \"text-align: right;\">-5.0296</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-504.373</td><td style = \"text-align: right;\">-1259.47</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & annual\\_WeccN & annual\\_WYCO & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 0.1866 & -0.544 & 1.9891 & 35.0431 & -1.8224 & -0.4735 & $\\dots$ \\\\\n",
       "\t2 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t3 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t4 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t5 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m5×40 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW \u001b[0m\u001b[1m annual_SoCal \u001b[0m\u001b[1m annual_WeccN \u001b[0m\u001b[1m ann\u001b[0m ⋯\n",
       "     │\u001b[90m Float64     \u001b[0m\u001b[90m Float64       \u001b[0m\u001b[90m Float64    \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Flo\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │      0.1866         -0.544      1.9891       35.0431       -1.8224      ⋯\n",
       "   2 │      0.0             0.0        0.0           0.0           0.0\n",
       "   3 │      0.0             0.0        0.0           0.0           0.0\n",
       "   4 │      0.0             0.0        0.0           0.0           0.0\n",
       "   5 │      0.0             0.0        0.0           0.0           0.0         ⋯\n",
       "\u001b[36m                                                              35 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# filter separate KPIs and erase free value\n",
    "label_cap = filter(:KPIs => x -> x == 1, KPIs_cap)[:, 1:1]\n",
    "KPI_1_cap = filter(:KPIs => x -> x == 1, KPIs_cap)[:, 3:end-6]\n",
    "KPI_2_cap = filter(:KPIs => x -> x == 2, KPIs_cap)[:, 3:end-6]\n",
    "KPI_3_cap = filter(:KPIs => x -> x == 3, KPIs_cap)[:, 3:end-6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Indicator 1 CAP\n",
    "fig1, ax, pltobj1 = barplot(Matrix(KPI_1_cap)[1,:], color = \"navyblue\",\n",
    "                           figure = (resolution = (1210, 530), fontsize = 25),\n",
    "                           label = Matrix(label_cap)[1,:],\n",
    "                           strokewidth=1\n",
    "                            )\n",
    "\n",
    "p_blue = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"royalblue2\", direction=Vec2f(1));    \n",
    "elem_p_blue = [PolyElement(color = p_blue, strokecolor = :black, strokewidth = 1)]\n",
    "p_green_1 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"olivedrab\", direction=[Vec2f(1), Vec2f(1, -1)]);    \n",
    "elem_p_green_1 = [PolyElement(color = p_green_1, strokecolor = :black, strokewidth = 1)]                      \n",
    "p_green_2 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"mediumseagreen\", direction=Vec2f(1, -1));  \n",
    "elem_p_green_2 = [PolyElement(color = p_green_2, strokecolor = :black, strokewidth = 1)]\n",
    "\n",
    "barplot!(Matrix(KPI_1_cap)[2,:], color = p_blue, label = Matrix(label_cap)[2,:], strokewidth=1)\n",
    "pltobj3 = barplot!(Matrix(KPI_1_cap)[4,:], color = \"darkgreen\", label = Matrix(label_cap)[4,:], strokewidth=1)\n",
    "barplot!(Matrix(KPI_1_cap)[5,:], color = p_green_1, label = Matrix(label_cap)[5,:], strokewidth=1)\n",
    "barplot!(Matrix(KPI_1_cap)[3,:], color = p_green_2, label = Matrix(label_cap)[3,:], strokewidth=1)\n",
    "vlines!(ax, 12.5, color = :black)\n",
    "vlines!(ax, 19.5, color = :black)\n",
    "vlines!(ax, 21.5, color = :black)\n",
    "vlines!(ax, 33.5, color = :black)\n",
    "#vlines!(ax, 38.5, color = :black)\n",
    "\n",
    "ax.xticks = (1:40, vec(Array(xticks_cap)))\n",
    "ax.xticklabelsize = 25\n",
    "ax.xticklabelrotation = pi/2\n",
    "ax.yticks = 0:0.2:1.2\n",
    "ax.title = \"Indicator 1: REG per REC [capacity]\"\n",
    "limits!(ax, 0, 41, -0.15, 1.3)\n",
    "#axislegend(ax, position = :rt, bgcolor = :white, framecolor = :black, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig1[2,1], supLine(Point2f(1,.9), Point2f(13,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 5.8, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig1[2,1], supLine(Point2f(13.2,.9), Point2f(22.2,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 16.5, 0.48; text=\"C&I\")\n",
    "lines!(fig1[2,1], supLine(Point2f(22.4,.9), Point2f(34.2,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 26, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig1[2,1], supLine(Point2f(34.4,.9), Point2f(42,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 37, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig1[2,1], supLine(Point2f(1,.4), Point2f(20.2,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 9, -.01; text=\"Annual\")\n",
    "lines!(fig1[2,1], supLine(Point2f(20.4,.4), Point2f(22.2,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 19.2, -.01; text=\"Emissions\")\n",
    "lines!(fig1[2,1], supLine(Point2f(22.4,.4), Point2f(42,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 29, -.01; text=\"Hourly\")\n",
    "\n",
    "\n",
    "ga = fig1[1,1] = GridLayout()\n",
    "gb = fig1[2,1] = GridLayout()\n",
    "\n",
    "rowgap!(fig1.layout, 3)\n",
    "rowsize!(fig1.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, .5, 42, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "axislegend(ax, [pltobj1, elem_p_blue, pltobj3, elem_p_green_1, elem_p_green_2], [Matrix(label_cap)[1,:], Matrix(label_cap)[2,:], Matrix(label_cap)[4,:],Matrix(label_cap)[5,:],Matrix(label_cap)[3,:]], position = :ct, orientation = :horizontal, labelsize=20)\n",
    "fig1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_1_cap.png\", fig1, px_per_unit = 20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Indicator 3 CAP\n",
    "fig1 = Figure(resolution = (1210, 530), fontsize = 25)\n",
    "ax = Axis(fig1[1,1], \n",
    "                xticks = (1:40, vec(Array(xticks_cap))), \n",
    "                xticklabelsize = 25,\n",
    "                xticklabelrotation = pi/2,\n",
    "                #yticks = 0:0.2:1.4,\n",
    "                ylabel= rich(\"[tCO\", subscript(2), \"e per MW\", subscript(\"e\"), \"]\"),\n",
    "                title = \"Indicator 3: Reduced emissions per REC [capacity]\",\n",
    "                )\n",
    "\n",
    "p_blue = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"royalblue2\", direction=Vec2f(1));    \n",
    "elem_p_blue = [PolyElement(color = p_blue, strokecolor = :black, strokewidth = 1)]\n",
    "p_green_1 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"olivedrab\", direction=[Vec2f(1), Vec2f(1, -1)]);    \n",
    "elem_p_green_1 = [PolyElement(color = p_green_1, strokecolor = :black, strokewidth = 1)]                      \n",
    "p_green_2 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"mediumseagreen\", direction=Vec2f(1, -1));  \n",
    "elem_p_green_2 = [PolyElement(color = p_green_2, strokecolor = :black, strokewidth = 1)]\n",
    "\n",
    "pltobj1= barplot!(-Matrix(KPI_3_cap)[1,:], color = \"navyblue\", label = Matrix(label_cap)[1,:], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_cap)[2,:], color = p_blue, label = Matrix(label_cap)[2,:], strokewidth = 1)\n",
    "pltobj3= barplot!(-Matrix(KPI_3_cap)[4,:], color = \"darkgreen\", label = Matrix(label_cap)[4,:], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_cap)[5,:], color = p_green_1, label = Matrix(label_cap)[5,:], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_cap)[3,:], color = p_green_2, label = Matrix(label_cap)[3,:], strokewidth = 1)\n",
    "vlines!(ax, 12.5, color = :black)\n",
    "vlines!(ax, 19.5, color = :black)\n",
    "vlines!(ax, 21.5, color = :black)\n",
    "vlines!(ax, 33.5, color = :black)\n",
    "#vlines!(ax, 38.5, color = :black)\n",
    "limits!(ax, 0, 41, -100, 3600)\n",
    "#axislegend(ax, position = :rt, bgcolor = :white, framecolor = :black, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig1[2,1], supLine(Point2f(1,.9), Point2f(13,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 5.8, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig1[2,1], supLine(Point2f(13.2,.9), Point2f(22.2,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 16.5, 0.48; text=\"C&I\")\n",
    "lines!(fig1[2,1], supLine(Point2f(22.4,.9), Point2f(34.2,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 26, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig1[2,1], supLine(Point2f(34.4,.9), Point2f(42,.9);y=.1), color = :black)\n",
    "text!(fig1[2,1], 37, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig1[2,1], supLine(Point2f(1,.4), Point2f(20.2,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 9, -.01; text=\"Annual\")\n",
    "lines!(fig1[2,1], supLine(Point2f(20.4,.4), Point2f(22.2,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 19.2, -.01; text=\"Emissions\")\n",
    "lines!(fig1[2,1], supLine(Point2f(22.4,.4), Point2f(42,.4); y=.1), color = :black)\n",
    "text!(fig1[2,1], 29, -.01; text=\"Hourly\")\n",
    "\n",
    "\n",
    "ga = fig1[1,1] = GridLayout()\n",
    "gb = fig1[2,1] = GridLayout()\n",
    "\n",
    "rowgap!(fig1.layout, 3)\n",
    "rowsize!(fig1.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, .5, 42, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "axislegend(ax, [pltobj1, elem_p_blue, pltobj3, elem_p_green_1, elem_p_green_2], [Matrix(label_cap)[1,:], Matrix(label_cap)[2,:], Matrix(label_cap)[4,:],Matrix(label_cap)[5,:],Matrix(label_cap)[3,:]], position = :rt,  labelsize=20)\n",
    "\n",
    "fig1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_3_cap.png\", fig1, px_per_unit = 20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generation figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>14×44 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">Study</th><th style = \"text-align: left;\">KPIs</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_DE</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal_1</th><th style = \"text-align: left;\">annual_WYCO_1</th><th style = \"text-align: left;\">annual_US</th><th style = \"text-align: left;\">emissions_Cal</th><th style = \"text-align: left;\">emissions_WYCO</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_DE</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal_1</th><th style = \"text-align: left;\">hourly_WYCO_1</th><th style = \"text-align: left;\">hourly_US</th><th style = \"text-align: left;\">free_DE</th><th style = \"text-align: left;\">free_NL</th><th style = \"text-align: left;\">free_CZ</th><th style = \"text-align: left;\">free_ES</th><th style = \"text-align: left;\">free_PL</th><th style = \"text-align: left;\">free_PT</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Any\" style = \"text-align: left;\">Any</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">-0.0109145</td><td style = \"text-align: right;\">-0.00569091</td><td style = \"text-align: right;\">-0.00738641</td><td style = \"text-align: right;\">-0.00613363</td><td style = \"text-align: right;\">-0.0121564</td><td style = \"text-align: right;\">0.00476553</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0110493</td><td style = \"text-align: right;\">0.30079</td><td style = \"text-align: right;\">0.285568</td><td style = \"text-align: right;\">0.661625</td><td style = \"text-align: right;\">0.0857182</td><td style = \"text-align: right;\">0.00391859</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">2</td><td style = \"text-align: right;\">-0.00500783</td><td style = \"text-align: right;\">0.0351986</td><td style = \"text-align: right;\">-0.105868</td><td style = \"text-align: right;\">-2.08392</td><td style = \"text-align: right;\">0.0418753</td><td style = \"text-align: right;\">-0.0228001</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.480414</td><td style = \"text-align: right;\">-0.569596</td><td style = \"text-align: right;\">-0.654105</td><td style = \"text-align: right;\">-0.603986</td><td style = \"text-align: right;\">-0.671322</td><td style = \"text-align: right;\">-0.772335</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: left;\">Ricks et al. [33]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">5.47e-5</td><td style = \"text-align: right;\">-0.000200312</td><td style = \"text-align: right;\">0.000781985</td><td style = \"text-align: right;\">0.012782</td><td style = \"text-align: right;\">-0.000509054</td><td style = \"text-align: right;\">-0.000108654</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.00530823</td><td style = \"text-align: right;\">-0.171329</td><td style = \"text-align: right;\">-0.186792</td><td style = \"text-align: right;\">-0.399613</td><td style = \"text-align: right;\">-0.0575445</td><td style = \"text-align: right;\">-0.00302646</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: left;\">Zeyen et al. [48]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1.20926</td><td style = \"text-align: right;\">1.23763</td><td style = \"text-align: right;\">1.2155</td><td style = \"text-align: right;\">1.39537</td><td style = \"text-align: right;\">1.19961</td><td style = \"text-align: right;\">1.33417</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1.17416</td><td style = \"text-align: right;\">0.793166</td><td style = \"text-align: right;\">1.21006</td><td style = \"text-align: right;\">1.14895</td><td style = \"text-align: right;\">1.20335</td><td style = \"text-align: right;\">1.13326</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">5.75233</td><td style = \"text-align: right;\">2.28652</td><td style = \"text-align: right;\">2.57362</td><td style = \"text-align: right;\">4.68303</td><td style = \"text-align: right;\">3.72859</td><td style = \"text-align: right;\">3.79071</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: left;\">Zeyen et al. [48]</td><td style = \"text-align: right;\">2</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.37486</td><td style = \"text-align: right;\">-0.349582</td><td style = \"text-align: right;\">-0.434502</td><td style = \"text-align: right;\">-0.2687</td><td style = \"text-align: right;\">-0.492292</td><td style = \"text-align: right;\">-0.286382</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.334815</td><td style = \"text-align: right;\">-0.341638</td><td style = \"text-align: right;\">-0.413717</td><td style = \"text-align: right;\">-0.250653</td><td style = \"text-align: right;\">-0.476681</td><td style = \"text-align: right;\">-0.283772</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.505462</td><td style = \"text-align: right;\">0.713841</td><td style = \"text-align: right;\">1.48235</td><td style = \"text-align: right;\">0.276096</td><td style = \"text-align: right;\">0.89072</td><td style = \"text-align: right;\">0.385384</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: left;\">Zeyen et al. [48]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.453301</td><td style = \"text-align: right;\">-0.432655</td><td style = \"text-align: right;\">-0.528138</td><td style = \"text-align: right;\">-0.374937</td><td style = \"text-align: right;\">-0.590557</td><td style = \"text-align: right;\">-0.382082</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.393126</td><td style = \"text-align: right;\">-0.270975</td><td style = \"text-align: right;\">-0.500623</td><td style = \"text-align: right;\">-0.287988</td><td style = \"text-align: right;\">-0.573616</td><td style = \"text-align: right;\">-0.321587</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">2.90758</td><td style = \"text-align: right;\">1.63221</td><td style = \"text-align: right;\">3.81499</td><td style = \"text-align: right;\">1.29297</td><td style = \"text-align: right;\">3.32113</td><td style = \"text-align: right;\">1.46088</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: left;\">Ruhnau &amp; Schiele 2023</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.13</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.7</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: left;\">Xu et al. 2022 [69]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.235487</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.662919</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: left;\">Xu et al. 2022 [69]</td><td style = \"text-align: right;\">2</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.51602</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.31131</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: left;\">Xu et al. 2022 [69]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.121516</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.206373</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: left;\">Xu et al. 2024 [20]</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0090988</td><td style = \"text-align: right;\">-0.00720533</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0116294</td><td style = \"text-align: right;\">-0.0221199</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.568216</td><td style = \"text-align: right;\">0.595564</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">13</td><td style = \"text-align: left;\">Xu et al. 2024 [20]</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.00010205</td><td style = \"text-align: right;\">-7.48e-5</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.000107856</td><td style = \"text-align: right;\">-0.0010942</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.181863</td><td style = \"text-align: right;\">-0.395497</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">14</td><td style = \"text-align: left;\">Heeter et al. 2021</td><td style = \"text-align: right;\">3</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.34</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.36</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& Study & KPIs & annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & \\\\\n",
       "\t\\hline\n",
       "\t& Any & Int64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & Ricks et al. [33] & 1 & -0.0109145 & -0.00569091 & -0.00738641 & -0.00613363 & $\\dots$ \\\\\n",
       "\t2 & Ricks et al. [33] & 2 & -0.00500783 & 0.0351986 & -0.105868 & -2.08392 & $\\dots$ \\\\\n",
       "\t3 & Ricks et al. [33] & 3 & 5.47e-5 & -0.000200312 & 0.000781985 & 0.012782 & $\\dots$ \\\\\n",
       "\t4 & Zeyen et al. [48] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t5 & Zeyen et al. [48] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t6 & Zeyen et al. [48] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t7 & Ruhnau \\& Schiele 2023 & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t8 & Xu et al. 2022 [69] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t9 & Xu et al. 2022 [69] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t10 & Xu et al. 2022 [69] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t11 & Xu et al. 2024 [20] & 1 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t12 & Xu et al. 2024 [20] & 2 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t13 & Xu et al. 2024 [20] & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t14 & Heeter et al. 2021 & 3 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m14×44 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m Study                 \u001b[0m\u001b[1m KPIs  \u001b[0m\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW   \u001b[0m\u001b[1m\u001b[0m ⋯\n",
       "     │\u001b[90m Any                   \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Float64     \u001b[0m\u001b[90m Float64       \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ Ricks et al. [33]          1  -0.0109145    -0.00569091   -0.00738641   ⋯\n",
       "   2 │ Ricks et al. [33]          2  -0.00500783    0.0351986    -0.105868\n",
       "   3 │ Ricks et al. [33]          3   5.47e-5      -0.000200312   0.000781985\n",
       "   4 │ Zeyen et al. [48]          1   0.0           0.0           0.0\n",
       "   5 │ Zeyen et al. [48]          2   0.0           0.0           0.0          ⋯\n",
       "   6 │ Zeyen et al. [48]          3   0.0           0.0           0.0\n",
       "   7 │ Ruhnau & Schiele 2023      3   0.0           0.0           0.0\n",
       "   8 │ Xu et al. 2022 [69]        1   0.0           0.0           0.0\n",
       "   9 │ Xu et al. 2022 [69]        2   0.0           0.0           0.0          ⋯\n",
       "  10 │ Xu et al. 2022 [69]        3   0.0           0.0           0.0\n",
       "  11 │ Xu et al. 2024 [20]        1   0.0           0.0           0.0\n",
       "  12 │ Xu et al. 2024 [20]        2   0.0           0.0           0.0\n",
       "  13 │ Xu et al. 2024 [20]        3   0.0           0.0           0.0          ⋯\n",
       "  14 │ Heeter et al. 2021         3   0.0           0.0           0.0\n",
       "\u001b[36m                                                              39 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "KPIs_gen = CSV.read(\"Overall_KPIs_gen.csv\", DataFrame; header=1, footerskip=3)\n",
    "# Extract xticks\n",
    "xticks_gen_raw = CSV.read(\"Overall_KPIs_gen.csv\", DataFrame; header=1, skipto=18)\n",
    "xticks_gen_3 = xticks_gen_raw[:, 3:end-6]\n",
    "xticks_gen = select!(xticks_gen_raw[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\"]))\n",
    "xticks_gen_blog = select!(xticks_gen_raw[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\", \"emissions_Cal\", \"emissions_WYCO\"]))\n",
    "\n",
    "# replace missing values with 0\n",
    "mapcols!(col -> replace(col, missing => 0), KPIs_gen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>6×30 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal_1</th><th style = \"text-align: left;\">annual_WYCO_1</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal_1</th><th style = \"text-align: left;\">hourly_WYCO_1</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">5.47e-5</td><td style = \"text-align: right;\">-0.000200312</td><td style = \"text-align: right;\">0.000781985</td><td style = \"text-align: right;\">0.012782</td><td style = \"text-align: right;\">-0.000509054</td><td style = \"text-align: right;\">-0.000108654</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.00530823</td><td style = \"text-align: right;\">-0.171329</td><td style = \"text-align: right;\">-0.186792</td><td style = \"text-align: right;\">-0.399613</td><td style = \"text-align: right;\">-0.0575445</td><td style = \"text-align: right;\">-0.00302646</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">4</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.121516</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.206373</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.00010205</td><td style = \"text-align: right;\">-7.48e-5</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">-0.181863</td><td style = \"text-align: right;\">-0.395497</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & annual\\_WeccN & annual\\_WYCO & \\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 5.47e-5 & -0.000200312 & 0.000781985 & 0.012782 & -0.000509054 & -0.000108654 & $\\dots$ \\\\\n",
       "\t2 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t3 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t4 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t5 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\t6 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m6×30 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW  \u001b[0m\u001b[1m annual_SoCal \u001b[0m\u001b[1m annual_WeccN \u001b[0m\u001b[1m an\u001b[0m ⋯\n",
       "     │\u001b[90m Float64     \u001b[0m\u001b[90m Float64       \u001b[0m\u001b[90m Float64     \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Float64      \u001b[0m\u001b[90m Fl\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │     5.47e-5   -0.000200312  0.000781985      0.012782  -0.000509054  -0 ⋯\n",
       "   2 │     0.0        0.0          0.0              0.0        0.0           0\n",
       "   3 │     0.0        0.0          0.0              0.0        0.0           0\n",
       "   4 │     0.0        0.0          0.0              0.0        0.0           0\n",
       "   5 │     0.0        0.0          0.0              0.0        0.0           0 ⋯\n",
       "   6 │     0.0        0.0          0.0              0.0        0.0           0\n",
       "\u001b[36m                                                              25 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# filter separate KPIs and erase free value\n",
    "label_gen = filter(:KPIs => x -> x == 3, KPIs_gen)[:, 1:1]\n",
    "KPI_1_gen = select!(filter(:KPIs => x -> x == 1, KPIs_gen)[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\"]))\n",
    "KPI_2_gen = select!(filter(:KPIs => x -> x == 2, KPIs_gen)[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\"]))\n",
    "KPI_3_gen = filter(:KPIs => x -> x == 3, KPIs_gen)[:, 3:end-6]\n",
    "KPI_3_gen_short = select!(filter(:KPIs => x -> x == 3, KPIs_gen)[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\"]))\n",
    "KPI_3_gen_short_blog = select!(filter(:KPIs => x -> x == 3, KPIs_gen)[:, 3:end-6], Not([\"annual_DE\", \"hourly_DE\", \"annual_US\", \"hourly_US\", \"emissions_Cal\", \"emissions_WYCO\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>1×32 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">annual_NMAZ</th><th style = \"text-align: left;\">annual_NorCal</th><th style = \"text-align: left;\">annual_PNW</th><th style = \"text-align: left;\">annual_SoCal</th><th style = \"text-align: left;\">annual_WeccN</th><th style = \"text-align: left;\">annual_WYCO</th><th style = \"text-align: left;\">annual_20_DE</th><th style = \"text-align: left;\">annual_20_NL</th><th style = \"text-align: left;\">annual_20_CZ</th><th style = \"text-align: left;\">annual_20_ES</th><th style = \"text-align: left;\">annual_20_PL</th><th style = \"text-align: left;\">annual_20_PT</th><th style = \"text-align: left;\">annual_Cal</th><th style = \"text-align: left;\">annual_Cal_1</th><th style = \"text-align: left;\">annual_WYCO_1</th><th style = \"text-align: left;\">emissions_Cal</th><th style = \"text-align: left;\">emissions_WYCO</th><th style = \"text-align: left;\">hourly_NMAZ</th><th style = \"text-align: left;\">hourly_NorCal</th><th style = \"text-align: left;\">hourly_PNW</th><th style = \"text-align: left;\">hourly_SoCal</th><th style = \"text-align: left;\">hourly_WeccN</th><th style = \"text-align: left;\">hourly_WYCO</th><th style = \"text-align: left;\">hourly_20_DE</th><th style = \"text-align: left;\">hourly_20_NL</th><th style = \"text-align: left;\">hourly_20_CZ</th><th style = \"text-align: left;\">hourly_20_ES</th><th style = \"text-align: left;\">hourly_20_PL</th><th style = \"text-align: left;\">hourly_20_PT</th><th style = \"text-align: left;\">hourly_Cal</th><th style = \"text-align: left;\">hourly_Cal_1</th><th style = \"text-align: left;\">hourly_WYCO_1</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String3\" style = \"text-align: left;\">String3</th><th title = \"String7\" style = \"text-align: left;\">String7</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">NMAZ</td><td style = \"text-align: left;\">NorCal</td><td style = \"text-align: left;\">PNW</td><td style = \"text-align: left;\">SoCal</td><td style = \"text-align: left;\">WeccN</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">CZ</td><td style = \"text-align: left;\">ES</td><td style = \"text-align: left;\">PL</td><td style = \"text-align: left;\">PT</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">NMAZ</td><td style = \"text-align: left;\">NorCal</td><td style = \"text-align: left;\">PNW</td><td style = \"text-align: left;\">SoCal</td><td style = \"text-align: left;\">WeccN</td><td style = \"text-align: left;\">WYCO</td><td style = \"text-align: left;\">DE</td><td style = \"text-align: left;\">NL</td><td style = \"text-align: left;\">CZ</td><td style = \"text-align: left;\">ES</td><td style = \"text-align: left;\">PL</td><td style = \"text-align: left;\">PT</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">Cal</td><td style = \"text-align: left;\">WYCO</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& annual\\_NMAZ & annual\\_NorCal & annual\\_PNW & annual\\_SoCal & annual\\_WeccN & annual\\_WYCO & \\\\\n",
       "\t\\hline\n",
       "\t& String7 & String7 & String3 & String7 & String7 & String7 & \\\\\n",
       "\t\\hline\n",
       "\t1 & NMAZ & NorCal & PNW & SoCal & WeccN & WYCO & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m1×32 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m annual_NMAZ \u001b[0m\u001b[1m annual_NorCal \u001b[0m\u001b[1m annual_PNW \u001b[0m\u001b[1m annual_SoCal \u001b[0m\u001b[1m annual_WeccN \u001b[0m\u001b[1m ann\u001b[0m ⋯\n",
       "     │\u001b[90m String7     \u001b[0m\u001b[90m String7       \u001b[0m\u001b[90m String3    \u001b[0m\u001b[90m String7      \u001b[0m\u001b[90m String7      \u001b[0m\u001b[90m Str\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ NMAZ         NorCal         PNW         SoCal         WeccN         WYC ⋯\n",
       "\u001b[36m                                                              27 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xticks_gen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = Figure(resolution = (1210, 530), fontsize = 25)\n",
    "ax = Axis(fig2[1,1], \n",
    "                xticks = (1:32, vec(Array(xticks_gen))), \n",
    "                xticklabelsize = 25,\n",
    "                xticklabelrotation = pi/2,\n",
    "                yticks = 0:0.2:1.6,\n",
    "                title = \"Indicator 1: REG per REC [generation]\",\n",
    "                )\n",
    "\n",
    "p_blue = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"royalblue2\", direction=Vec2f(1));    \n",
    "elem_p_blue = [PolyElement(color = p_blue, strokecolor = :black, strokewidth = 1)]\n",
    "p_green_1 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"olivedrab\", direction=[Vec2f(1), Vec2f(1, -1)]);    \n",
    "elem_p_green_1 = [PolyElement(color = p_green_1, strokecolor = :black, strokewidth = 1)]                      \n",
    "\n",
    "pltobj1= barplot!(Matrix(KPI_1_gen)[1,:], color = \"navyblue\", label = Matrix(label_gen)[1,:], strokewidth = 1)\n",
    "barplot!(Matrix(KPI_1_gen)[2,:], color = p_blue, label = Matrix(label_gen)[2,:], strokewidth = 1)\n",
    "pltobj3= barplot!(Matrix(KPI_1_gen)[3,:], color = \"darkgreen\", label = Matrix(label_gen)[4,:], strokewidth = 1)\n",
    "barplot!(Matrix(KPI_1_gen)[4,:], color = p_green_1, label = Matrix(label_gen)[5,:], strokewidth = 1)\n",
    "vlines!(ax, 12.5, color = :black)\n",
    "vlines!(ax, 15.5, color = :black)\n",
    "vlines!(ax, 17.5, color = :black)\n",
    "vlines!(ax, 29.5, color = :black)\n",
    "limits!(ax, 0, 33, -0.05, 1.7)\n",
    "\n",
    "#axislegend(ax, position = :lt, bgcolor = :white, framecolor = :black, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig2[2,1], supLine(Point2f(2.2,.9), Point2f(14,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 7, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2[2,1], supLine(Point2f(14.2,.9), Point2f(19.2,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 16.2, 0.48; text=\"C&I\")\n",
    "lines!(fig2[2,1], supLine(Point2f(19.4,.9), Point2f(31.4,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 24.5, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2[2,1], supLine(Point2f(31.6,.9), Point2f(34.5,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 32.5, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig2[2,1], supLine(Point2f(2.2,.4), Point2f(17.2,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 9, -.01; text=\"Annual\")\n",
    "lines!(fig2[2,1], supLine(Point2f(17.4,.4), Point2f(19.2,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 16.7, -.01; text=\"Emissions\")\n",
    "lines!(fig2[2,1], supLine(Point2f(19.4,.4), Point2f(34.5,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 24, -.01; text=\"Hourly\")\n",
    "\n",
    "\n",
    "ga = fig2[1,1] = GridLayout()\n",
    "gb = fig2[2,1] = GridLayout()\n",
    "\n",
    "rowgap!(fig2.layout, 3)\n",
    "rowsize!(fig2.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, 1.5, 35, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "axislegend(ax, [pltobj1, elem_p_blue, pltobj3, elem_p_green_1], [Matrix(label_cap)[1,:], Matrix(label_cap)[2,:], Matrix(label_cap)[4,:],Matrix(label_cap)[5,:]], position = :ct, orientation = :horizontal, labelsize=20)\n",
    "\n",
    "\n",
    "fig2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_1_gen.png\", fig2, px_per_unit = 20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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z5tOnT1wul/RHQUwmMz8/H1vmHwofbyyqra0tLy/H3/PBdXbUzaNHj7q7u79///7gwYPh4eEIoeDgYHt7e+Kf+UWgrKxMHOCxvr4+KyuLzWaXl5cvWLDA19cXH+WC+GPrhx9+EFhaTk6O+CdRCPLnl2RtkSSuOvL7IqLRaIqKivw58RaJTlm6dOmjR4+w5YyMjAMHDhw4cEBDQ2PatGnz5s2bNWsWHlqQz8lPnGte+L0vZsV48IwVRPxvdnY2sRcl+fOFOn/Pos7cX0R2dnYXLlwQWGC/fv3w5b59++bl5SGEysvLWSwW/ocwSWEymVgwhvhOd//+/XV0dPC1SNS7AJG4MEQrWeDJEueBL5CY3wIdfnYAei14dxEAIFhlZSW+zDNYBY1GI/MzmlhChy8XJSQkmJubr1279ubNm3l5eVwul0qlDhkyhGRta2tr8T+u8w+tQWyk4n/JByEkMFQQjkqljhgx4saNG/jg7PhrRSIbNWrUC4LU1NSkpCS8bvjEjwgh7N0h4Wpra7HfrxjRTqIQ5M8vydrW1NSIf9WR31eH2US2du3aS5cu8UxXUFFRERQUNGfOHCsrq+Li4s7m5CfmNS+pjyCcjIwMz7CoxIrV1taKfL5EuGfJ319ECgoKpu0gfhb8WHG5XJ6mM1x+fj6+9862nmF9ZbFl/vldeZpGu+4uEK1k/pMl5gO/vf123R0BQG8GrYsAAMEGDhyILxcUFBBXMRgMfDZqIXR0dKSkpLBfRXgzlEAsFmv58uVYzx8tLa2tW7fa29tbWFjk5uaSnJVeS0tLSUkJG5wDH3MCRxyFgqcdjKRPnz7hw1rs3LlTXV0dW6bT6ZaWlllZWQghkj+gO2XIkCHjxo3DhpMh/s0e6+qJiYmJaa8fHfE3k2gnEYe9wEZMIX9+SdZWSUlJ/KuO/L46LEocK1euXLly5YsXL8LDwyMjI4nzeicnJ2/ZsgV/84p8Th5dfc2LXDGilpaWsrIyYiscsao88+B9+fPV3v0lAjs7u6tXr2LLvr6+AoPP9evXY0ME0el0kq9H4rS1tWk0GtbTFXtUEuGtapiuuwskUrL4D3yBuvqOAKDXgnARACCYjo6OnJwc9psmPDx81apV+Cp8NmrhaDTawIEDsZmv4+Pjd+7cia+6fft2UFAQQkhJSSkgICAtLQ1vB/Pw8MD3lZKSQr7CgwcPxkZKiIyMPHToEHEmQHxouwEDBpAcRJGHjIzM8ePHseUJEyZMnz4dX4VP7d1FEzrjP7xaWlqampqw+hN/Z8vIyPD028RxudzOnkR8dPv6+nomk4n3yEpNTSW+HIU6c35J1hZJ4qojv68uUlNTg4/YMWbMmDFjxhw9ejQ9PT0kJOTEiRP19fUIIayfJ/mc7emia178ihGFh4cT5za4desWtkCn03l+tX+V8yXw/hLBggULXF1dW1paEEJ+fn4bNmzgaZvNyMh48uQJtmxhYSFkGgmBpKSk9PX1sefk/fv3iaM0PXnyhOf9uq67CyRSskQe+AJ16bcAAL0WdEYFAAhGoVDwgfhu37596dIlbDkzM3P37t0kCxk3bhy28M8//9y+fRtbrq2t/fXXX8PCwsLCwurq6tB/uzXi7/xUV1e7u7sLL5/FYuHL+ASAKSkpf/75J57u7e2NT8wwbdo0kjXnoa2tjbco7t27F+uRxeVyPTw8kpKSsHRLS0s8//Hjx5f/D/YLUmTEzfEWCUNDQ11dXWyZOJo/QmjTpk3W1tbW1tY//fSTCCcRnwOAy+XiLSQVFRU8g8FiSJ5fkrVFkrjqyO+rizQ1NTn+D14BU1PT/fv341PzYX3zyOdsTxdd8+JXjOjAgQP4ACQ3b94MCQnBKy8lJfXVz5fA+4snQ1H7amtrsWwaGhpr167FlhkMxpgxY8LCwhobGxFCXC43Kipq5syZTCYTy4Dn7BR8uNqEhAR8GpL8/PwNGzbw5Oy6oyqRkiXywBeoS78FAOi9vsp4rACAL6DDiTRqamqI+fHGMWyOOy6Xm56eTpxL0NTU1NbWljgAJupoIo3i4mL8ZyWNRnNwcFi2bBk+xTOFQomJicGy4dvKyMg4ODgsXLiQZyiCO3fu4FUljlnv5eX18uVLLpfb1NREnO7M3Nx86dKlxD9+a2hoECdmEHIoOjyesrKyw4cPJ85V3adPn6KiIjwzcfL6hoYGIcV2OI04cS444oTRV65cwdPHjRt38OBBV1fX0aNH44nYSe/USeRyuQkJCcRVgwcPHjVqFM8f4/GJNEieX/K1FaHC/MjvC2+iodFoxBLw04dPF47BO1U6OztjKQIve3w8FSqVOnv27N9///3XX3+dOnUq3tbx448/djanwB116prv1L1PvmICESfSQAhJSUmNGTNmyJAh+OY0Gi0lJaWz56uz9yxX1PuLfE9R/ErgcrkNDQ083WupVKqenh7P1Ttr1izi3CT82ptIIzc3F5/KBSFkZmY2duxYnhFZ8HtTIkeV/8IgX7KQYiXywBf/jhDhs3NhIg3QK0G4CECPJX64yOVyT548yT/7/IABA/AeXMLDRS6XGxgYyPNrCXfo0CE8m8AJshctWoQvnzlzBs+Mz+aMwX8hPXnyRFtbW+C++vbte//+/faOD5mfnhwOhzjXApGMjExYWBgxswTDReJoqw8ePMDT29raeI5De8eW/EnE4C1IRPPmzeOfd5FL+vySr60IFeZBfl9dFC5++PBByKg82tra+KR55HO2d3+Rv+Y7de+Tr5hAeLioqKjI/zYalUo9fvy4COerK8JFgfeXaOEil8v9/Pkzz0iwPGxsbDqseXvhIpfL9fT0JHawxKirq+OxFn5vSuSoCvxSIFmy8JMl/gNf/DtChM/OhXAR9ErQGRUAIMzmzZvv3LmDD0AiLS09efLkly9fkh9Uc9WqVe/evZs0aRLeDEWlUq2trWNjY4mv3/j7+69ZswYfnX/w4MEhISFXr17Fm6oOHDjAYDCwZS8vr5kzZ/JHFPb29qmpqc7Ozv3798cT+/Xrt2rVqrS0NDH7IFGp1Pv371+4cGHgwIH4LzZFRcV58+alpKTgXSglbubMmfgysUcohUK5evVqcHCwqakpfiioVOq0adNiYmKIx7azJ/Hy5cubNm3C2zG0tLR27tzZ3rgmJM8v+dqKUGEendpXVxg6dOjbt283b96MTy+OUVJS2rx587///otPmkc+Z3u66JoXv2IYGo129+7diRMn4ikGBgb37t3btm0bnvJ1z1d795do+vfv//r1ay8vL55pBmk0mqWl5a1btxISEvgH7STv999/j4yMNDExwR5BdDp90qRJ//77L3+A1HVHVSIlS+SBL1CXfgsA0DtRuGJPdPMFvH///urVq9nZ2dLS0iNGjFi5ciWxD1iHEhISHjx4kJaWpqCgYG5uvmDBArxjAwCADC6Xm5eX19DQYGZmJvJ8YlwuNz8/H+uv1d6UVgwGIycnp3///viLgkJwOJzKyko5OTlFRUX+WeCwaST09fV5ZtOSiMbGxuzsbHV1dfw1nq+LyWRmZGQoKCjw93zDdfYkstns7OxsOTk5kg9MMueXfG1FqLA4++o6NTU1nz9/ZrPZOjo6wieCJ5+zPV10zYtQsa1bt2JToquoqGBv95WUlBQVFfXp08fQ0JC/fQz31c+XBOXn5xcUFGDdIwcNGkTsRyrclStXVqxYgRDS0dEpKioSmKeuri4/P9/ExAQ7SmZmZunp6QghNze3vXv38mTuuqMqZskSfOAL1BV3hJ2d3fPnz1E7hxqAHukbCBcPHDhw8OBB4oh8KioqV69eJY5M2B4Gg+Hk5MTzR3FZWdk//viD/FgdAAAAACCPP1wE5LUXLkZERGAHU0lJidiZs7KyUltbm81mI4Ru3749a9asL17lXgTCRdALdfeJNAIDA/fv348QWrx48Zw5c6qqqgIDA1+/fr1o0aI3b96YmpoK33zTpk03b96Uk5PbsmWLnZ0dg8G4devW9evX9+zZY2BgsHTp0i/xGQAAAAAAOqmuru63335DCA0dOnT16tWhoaHBwcHYqjNnzqxbt45Op5eUlKxYsQKLFeXl5ceMGfM1a9xz3b59G5sHhX9GRwB6vq/43mSHmpubse7469evxxPr6+uHDRuGOhqWjcvlYhNnI4R43mzeunUrQsjAwKBLKg0AAAD0bvhQNyoqKl+7Lt8efKgb3A8//MDlcpOTk/v06YMnKigoGBsbE+dvvHbt2teue4/FM9gvgqFuQG/SrYe6iYmJKSkpkZKS8vT0xBOVlJQOHjyIEAoPD8dmNGrP69evEUL9+/fnebMZm+/o06dPxJl/AAAAAAC6LQsLi8ePH8+cORN7c4/BYGRlZWHtiqNHj7579+7ixYu/dh0BAD1Qt+6M+vDhQ4SQvb09z8hskydPlpWVZTKZ8fHxxNHqedTX1yOE+IfSwodMqK+vJ/N2NQAAAADI++GHH7BRoIQPegQEWr58+fLlywWusrCwuHPnTlFRUVpaWkFBAZvNHjBgwMCBA3kGYgUS5+3t7e3t/bVrAcDX0a3DxdTUVISQra0tT7q8vPzw4cNfvnyZlpYmJFzE5sYpLCyMi4tzcHDA04OCghBCurq6MD4qAAAAIHEODg7Er10gWbq6ut1kTGYAQG/QrTuj5ufnI4QEDn+MJQp/4Xjo0KHY8Kdz5sw5cuTIkydPoqKi1q9f7+7uLi0tfeHCBZJz+AAAAAAAAABAL9StWxexVxOJL3bj1NTU8AxCHD58WFFRcffu3cR5Y+Xk5B49eiRw9LDHjx8/fvyYmFJZWVlTU6Ovr9/56gMAAAAAAABAd1FQUDBq1Chs4E+SunXrIovFQggpKCjwr1JUVEQIMZlM4SVcuXLFw8MDIaSrqzt16lR7e3tlZeXm5mYnJ6cPHz6QqUN2dnZBQUGnq/6VMBgM7K13yWpoaCDOeykRXC4Xe7lUsjgcTod/RBABm81uamqSeLEsFqvDa1gETCazpaVF4sU2NTW1trZKvNjGxkY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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# with Ruhnau and Heeter\n",
    "\n",
    "fig3 = Figure(resolution = (1210, 530), fontsize = 25)\n",
    "ax = Axis(fig3[1,1], \n",
    "                xticks = (1:36, vec(Array(xticks_gen_3))), \n",
    "                xticklabelsize = 25,\n",
    "                xticklabelrotation = pi/2,\n",
    "                yticks = 0:0.2:1.4,\n",
    "                ylabel= rich(\"[tCO\", subscript(2), \"e per MWh\", subscript(\"e\"), \"]\"),\n",
    "                title = \"Indicator 3: Reduced emissions per REC [generation]\",\n",
    "                )\n",
    "\n",
    "p1 = Makie.LinePattern(width=15, tilesize=(20,20), linecolor=:turquoise, background_color=:white);\n",
    "p2 = Makie.LinePattern(width=15, tilesize=(20,20), linecolor=:teal, background_color=:white);\n",
    "\n",
    "barplot!(-Matrix(KPI_3_gen)[1,:], color = \"navyblue\", label = Matrix(label_gen)[1,:])\n",
    "barplot!(Matrix(KPI_3_gen)[3,:], color = :turquoise, label = Matrix(label_gen)[3,:])\n",
    "barplot!(Matrix(KPI_3_gen)[3,:], color = p1)\n",
    "barplot!(-Matrix(KPI_3_gen)[2,:], color = \"royalblue2\", label = Matrix(label_gen)[2,:])\n",
    "barplot!(-Matrix(KPI_3_gen)[4,:], color = \"darkgreen\", label = Matrix(label_gen)[4,:])\n",
    "barplot!(-Matrix(KPI_3_gen)[5,:], color = \"olivedrab\", label = Matrix(label_gen)[5,:])\n",
    "barplot!(-Matrix(KPI_3_gen)[6,:], color = :teal, label = Matrix(label_gen)[6,:])\n",
    "barplot!(-Matrix(KPI_3_gen)[6,:], color = p2)\n",
    "vlines!(ax, 13.5, color = :black) \n",
    "vlines!(ax, 17.5, color = :black)\n",
    "vlines!(ax, 30.5, color = :black)\n",
    "vlines!(ax, 34.5, color = :black)\n",
    "limits!(ax, -1, 37, -0.05, .8)\n",
    "\n",
    "axislegend(ax, position = :lt, bgcolor = :transparent, framecolor = :transparent, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig3[2,1], supLine(Point2f(2.2,.9), Point2f(14.2,.9);y=.1), color = :black)\n",
    "text!(fig3[2,1], 7, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig3[2,1], supLine(Point2f(14.4,.9), Point2f(18.2,.9);y=.1), color = :black)\n",
    "text!(fig3[2,1], 15.7, 0.48; text=\"C&I\")\n",
    "lines!(fig3[2,1], supLine(Point2f(18.4,.9), Point2f(30.7,.9);y=.1), color = :black)\n",
    "text!(fig3[2,1], 22.5, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig3[2,1], supLine(Point2f(30.9,.9), Point2f(36.7,.9);y=.1), color = :black)\n",
    "text!(fig3[2,1], 33, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig3[2,1], supLine(Point2f(2.2,.4), Point2f(18.2,.4); y=.1), color = :black)\n",
    "text!(fig3[2,1], 9, -.01; text=\"Annual\")\n",
    "lines!(fig3[2,1], supLine(Point2f(18.4,.4), Point2f(34.6,.4); y=.1), color = :black)\n",
    "text!(fig3[2,1], 24, -.01; text=\"Hourly\")\n",
    "lines!(fig3[2,1], supLine(Point2f(34.8,.4), Point2f(36.7,.4); y=.1), color = :black)\n",
    "text!(fig3[2,1], 33.2, -.01; text=\"Emissions\")\n",
    "\n",
    "rowgap!(fig3.layout, 3)\n",
    "rowsize!(fig3.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, .5, 37, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "fig3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_3_gen.png\", fig3, px_per_unit = 15);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# without Ruhnau and Heeter\n",
    "\n",
    "fig2 = Figure(resolution = (1210, 530), fontsize = 25)\n",
    "ax = Axis(fig2[1,1], \n",
    "                xticks = (1:32, vec(Array(xticks_gen))), \n",
    "                xticklabelsize = 25,\n",
    "                xticklabelrotation = pi/2,\n",
    "                yticks = 0:0.2:1.4,\n",
    "                ylabel= rich(\"[tCO\", subscript(2), \"e per MWh\", subscript(\"e\"), \"]\"),\n",
    "                title = \"Indicator 3: Reduced emissions per REC [generation]\",\n",
    "                )\n",
    "                \n",
    "p_blue = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"royalblue2\", direction=Vec2f(1));    \n",
    "elem_p_blue = [PolyElement(color = p_blue, strokecolor = :black, strokewidth = 1)]\n",
    "p_green_1 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"olivedrab\", direction=[Vec2f(1), Vec2f(1, -1)]);    \n",
    "elem_p_green_1 = [PolyElement(color = p_green_1, strokecolor = :black, strokewidth = 1)]   \n",
    "\n",
    "pltobj1= barplot!(-Matrix(KPI_3_gen_short)[1,:], color = \"navyblue\", label = Matrix(label_gen)[1,:], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_gen_short)[2,:], color = p_blue, label = Matrix(label_gen)[2,:], strokewidth = 1)\n",
    "pltobj3= barplot!(-Matrix(KPI_3_gen_short)[4,:], color = \"darkgreen\", label = Matrix(label_gen)[4,:], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_gen_short)[5,:], color = p_green_1, label = Matrix(label_gen)[5,:], strokewidth = 1)\n",
    "vlines!(ax, 12.5, color = :black)\n",
    "vlines!(ax, 15.5, color = :black)\n",
    "vlines!(ax, 17.5, color = :black)\n",
    "vlines!(ax, 29.5, color = :black)\n",
    "limits!(ax, 0, 33, -0.03, .73)\n",
    "\n",
    "#axislegend(ax, position = :lt, bgcolor = :white, framecolor = :black, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig2[2,1], supLine(Point2f(2.2,.9), Point2f(14,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 7, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2[2,1], supLine(Point2f(14.2,.9), Point2f(19.2,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 16.2, 0.48; text=\"C&I\")\n",
    "lines!(fig2[2,1], supLine(Point2f(19.4,.9), Point2f(31.4,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 24.5, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2[2,1], supLine(Point2f(31.6,.9), Point2f(34.5,.9);y=.1), color = :black)\n",
    "text!(fig2[2,1], 32.5, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig2[2,1], supLine(Point2f(2.2,.4), Point2f(17.2,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 9, -.01; text=\"Annual\")\n",
    "lines!(fig2[2,1], supLine(Point2f(17.4,.4), Point2f(19.2,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 16.7, -.01; text=\"Emissions\")\n",
    "lines!(fig2[2,1], supLine(Point2f(19.4,.4), Point2f(34.5,.4); y=.1), color = :black)\n",
    "text!(fig2[2,1], 24, -.01; text=\"Hourly\")\n",
    "\n",
    "\n",
    "ga = fig2[1,1] = GridLayout()\n",
    "gb = fig2[2,1] = GridLayout()\n",
    "\n",
    "rowgap!(fig2.layout, 3)\n",
    "rowsize!(fig2.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, 1.5, 35, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "axislegend(ax, [pltobj1, elem_p_blue, pltobj3, elem_p_green_1], [Matrix(label_cap)[1,:], Matrix(label_cap)[2,:], Matrix(label_cap)[4,:],Matrix(label_cap)[5,:]], position = :ct, orientation = :horizontal, labelsize=20)\n",
    "\n",
    "fig2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_3_gen.png\", fig2, px_per_unit = 20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Ricks et al. (2023)\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label_gen_blog[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xOjdKdSfFiY2N7devHzu7nj173rt3T6Ea18IeZXF1dZUyf1lZmYmJCcn1HHzTi/oNnJQ4pbQp9ni6mZmZ+Ldr37597Gi1n3c/evQoERkYGBQWFspUkKZ9eqrAQ8vloSzeGi8ChxLx891D4JDj66c5w0WR8hoUAocS8RY4VFoQn41XiTAZVeMYGxv/+eef/fv3X7x4cVZWlrIOW1lZyQ7OpdjZ2RHRkydP2rRpw1IGDx58586dlJQUbuk2Wbm7u48dO9bb29vJyUnhKjdOpSdVUVEREBCwadOmqqoqIyOjdevWLV26VL7tIhswatQogUAQExOzd+/ezz77rNH8a9asefPmzTvvvCP3Q/AvX75cvHixeArb+ys+Pl4ivaqqSr4i3N3d5X6vKiilTbm5uY0cOfLChQsDBgzYsmULuwT88ssviWjQoEGdO3cWzxwTE8PuIM6dO7d58+YyFaRpn54q8NMdqbos/htvAxA4pKTqM0LgaBqBQ1kNCoFDiXgLHCotSKMChwzUOFR9CyUnJ8+ePfubb76RJvPt27e5dZMUL/rEiRNENHXqVC7l1KlTRLR582Yu5YcffiCiEydOyHTk7Oxsf39/iQbToUOHGTNmBAUFvXz5UvHK10d1J/X8+XNuR1QXF5cbN25kSUeOs5g3bx4RGRgYNDr55OLFi+w5h19//VWOgvi8+8gbPttUfHx87e109fT0Ll26xOX59ddfJ0+e3KxZMyJq3ry5+M1IDaSum8Sqa7k8l8VP40XgUCKVfh8QOLQicPDcoBA4lIW3wKHqgnhrvEqkue0ZRCJRbm7uqVOnTp06pfihUlNTdXV1DQ0NIyMjuRQiGjRoEJfHz8+PiK5cuSJfEcnJyTt37hw/frz4UlE6Ojo9e/b86quvLl26JLGXkeJUd1J8Bsi8vDz29I6Jicnq1auLiopq5yksLFy+fLmBgQER9ezZs9GtXev06NGjAXKRoyyNpWCbyszMfO+991hQJ6I2bdpIbNTLLXjo6uqakJCgjCqr0PPnzwMCAnbt2sVzuTx0R/yUxVvjlQkCRwNUekYIHE0ycCjeoBA4lIK3wKHqgjQzcDRMR1RrOxHQNMnJyex3cAV99NFHx44d09XVnTx5Mts61tnZ+eHDhwsWLBg7duzt27fXrl0rEAieP3/eqlUrRQqqrq6+fft2WFhYaGjo3bt3hUIhSzc2Nh48eLC3t7e3t3e3bt0UPyNS2UndunXLw8NDjvrI16ASExOHDx/OVkm2srIaMWJEly5dHB0d9fT0EhISEhISLl68+PLlSyKyt7e/evVq+/bt5SiFNxUVFWxtN1nZ29srvTKqUFlZ+ejRI319fUdHR+4KgHnvvfeMjY29vLxmzpzJOnq5iUSilJSU+Pj4srKyHj16ODo66urqKlZxDcJbd6TqsjS28SJw8H9GCByKQOBA4GgUb92RqgvSvsar1sEqNCQrK2vr1q3scXmlHLCoqGjcuHFE1K9fP5by999/S/QjX3/9tVLK4uTn5x87duyzzz6TWP6uffv2Sjm+ik6KxS05yH0ieXl5fn5+tdfU5ujq6k6ZMqWgoEDuInijrslLQqHwxo0btWd3fP311zNmzDhw4EBmZqaCRfAmNjbWzc1N/MNxdna+ffu2ioqrqalJSko6e/ZscHDw48ePhUKhigri8NkdqbosjWq8CByNUt0ZIXAoQi2BoylFDRECh/K6Ix4K0q7Gi+GixikoKNi3b5+Xl5f4NlNKPH5GRsa1a9e4f/79998eHh5WVlZubm7btm2rqalRYlniXr58uWnTJvGthJR4cHWdlNI9efJkxYoV/fr1MzMzY5+Sqampm5vb8uXLHz9+rO7aSYv/qF9TU7Np06a2bdsS0ZYtWyRenTJlCju+sbExb9+H6upquecvpaamGhkZ1f589PX1VbE2Gs9XGOL4bLmqLku9jReBQ1ZNJmqI1P3dUxaeA4cGRg0RAod0eGu8PBSkLY0Xk1E1RXl5+blz54KCgv7555+KigouvXfv3pMnT/7iiy/UWDe5JSQkRERERERE3Lhxg62ixmnTpk12dra6KqYV2NpcElNWlIhN/bpz505aWlp+fr5AIGjRokWXLl3c3d0VXIBLKBRya6k3LDo62t/fn3033Nzc2JrjsiopKfHz82MbYRPRnj175syZI57hzz//3L59+/3799n0tjFjxpw5c0bWUmJiYiZOnGhnZxcaGiqeHh8ff/LkSQcHB/Ykg3itWO8vRx87ceLEEydOmJqabty4cfTo0QKBICQk5IsvvsjPz3d3d5f7oqpOz549c3Jy4vZG5+jr69+7d0/NS7FpLVU3Xg4CB0hA4JAGP1GDEDhAFrwFDnmoebj61quurg4JCfnkk0+4+wqMs7Pz999/n5SUpO4KyqaioiIiImLTpk1jxoypPZ/b0tJy/Pjx27dvf/TokbprKg+hUHjy5MmFCxdGRERwiYGBgR988MH+/fu16G50eXn5999/38BUeGdnZ4kH8ZXuzZs3X375JfslxMTEZPPmzdXV1fId6quvvmLVnj9/fgN347KzsydPnsxyBgUFyVoKb5uP1dTUsDvE+/fvF08/ffo0O6Byp6ZMmDCBiExNTQMDA9PT0zMzM/ft29eiRQsicnd3V2JBoEQIHFoEgUOJlBU4+IkaIgQOaCowXFSbyMjIBQsWSCyvzGL/woUL1V07GZSWlp49e3b58uUDBw6s/Yi2mZnZe++99/PPP7O7dOqurPxycnI8PT3ZSYlPFAkICGCJPj4+dS5vpWlevHghvlyEubm5s7PzqFGj2JPW4hsNjR8/XkWLcYWFhXEL6Pv6+tbeqlh6aWlp7FsXGBgoTX62RViHDh1kvcjgLeqnpaURkb6+flVVlcRLbPW869evy3rM+vB8hQGKQ+DQLggcSqSswMFb1BAhcEBTgeEi3+Li4lauXGljYyMeGh0dHVetWhUbG7t9+3YiWr58uXILVenD3LVnOBgZGXl5ea1fv/7WrVty/2TUKJ6fUJ84cSIRmZiYLF68OD09nUtPTU0NCAiwsLAgoqVLlypSBA9nVFZW1rVrVyLS09ObPHnygwcPaucJDQ0dMmQI+1NOmTJFwRIl5OXlTZ8+nR3cysrq0KFDCh7wwIEDRNSjRw8pb9IXFxezO6BPnz6VqSDeov6tW7eIyNbWtvZL7EGRCxcuyHrM+vB5hcHhs+XyVpaqC0LgUAr+1zVB4FAK5QYO3qKGCIFDeZpMZ66ushSE4SKvJGbY29nZff3119HR0VwGpUd9Hh7mZr1hs2bNBg0atGbNmvDwcFXvD8P/E+qPHz9mVzP1zYZKSEgwMDDQ19eX76Yab2fEbmnr6Oj8/fffDedcu3YtK/Ty5ctyFychKCiIW7Ji2rRpeXl5ih9z1apVRPTFF19I/5bBgwcT0fnz52UqiLeo38AOyAMGDFBu1OfzCkPEb8vlrSweCkLgUJxa1jVB4FAKpQcO3qKGCIFDGZpSZ66WspQCw0VecfdTe/Towe3+KU65Ub+4uPi9997jLjL27NkjkeHgwYNubm7cSnpjxoyRo5Ts7OyLFy++efNGGVVuHD8nJSE4OJiIZs2a1UCeDz74gIjq/LM2jM8zYjN5VqxY0WhOoVA4YsQIIpo6darcxXHS0tK4c7Sxsbl48aLix2TYLedt27bJ+pYdO3bIVFCTjPp8lsXn95y3svgpCIFDQWqJGiIEDoWpKHDwFjVECBwKa2KdOf9lKQuGi7wSn37TsmXL+fPnSwQJ5UZ93h7m5pNaTor9XdauXdtAHrau2vHjx2U9OG9nlJmZyd7+5MkTafIfPHiQiKytreUoiyMUCrdu3WpqakpEenp6S5cuVe4F4pIlS4joxx9/lP4tY8eOJaI///xTpoIQ9RXEZ8vlrSw+l1lC4JCbus4IgUNuKg0cvEUNEQKHwppYZ85/WcqC4SKvKioqgoODR48era+vz4V/Ozu7tWvXsjnxSoz6vD3MXV5e/lQumnxSEq5cuUJEY8eObSBP3759iUjWtfv4PKP79+8TkYmJiZRLR8TFxRGRgYGBrAVxYmNj2XbhRNSzZ8979+7Jfaj67Ny5k4hGjx4tZf7q6mq29OKNGzdkKghRXxF8fs95K4u3ghA4FAkc6ooaIgQOeak6cPAWNUQIHIppep05z2UpEYaL6vHq1atdu3YNGDBAR0eHC//u7u7s52mlRH2elwCRgyaflISioiKBQMB2Maozw19//UVEpqamsi7ipwnP3DdQltx/qfLy8lWrVrGrWyMjo40bN9Z+Jl4pXrx4oaurKxAI/v33X2ny//DDD0TUsmVLjV0ZlRVkYWExtxb2nMN7771X+6W5c+fKWlADJyVSdtTn83vOW1n8d0cIHHI0KHVFDRECh+z4CRy8RQ0RAodimmRnrsYeSREC+fprUJClpaW/v7+/v/+zZ8+CgoIOHz4cHx/Pnh4mouDgYAsLi8mTJ3fu3FnuIp4+fUpEI0aMEL+waICpqamzs/O1a9cSExPt7e3lLlel1HVSZmZmP/7445dffjl+/PiZM2fOnj3b3t6+efPmJSUlSUlJ//3vf3///Xci2rBhg66urkxHbpJ/phcvXnh6erI9lF1cXAIDA+3s7PLy8hp9I4tqMmnfvv3kyZMPHz48YcKEyMhItnxffcLCwlavXk1E/v7+3FMBmqmgoGDPnj11vsRtLS1h9+7d8pWVk5Pj7+8vkZicnExE27dv59ZGV6QsPr/nvJXFf+NF4JCDGs8IgUMmvAWOpho1CIFDGzpzLW28GC6qmbW19cqVK1euXBkTE3Po0KEjR45kZmY+e/ZsxYoVK1eu7N+//8cff/zRRx/V3rm4Uc+fPycima4bbGxsrl27lpqaKlNBbm5u+fn50uSMjo729/dnwYAtnyUr3k6qtmXLlj1+/Hjfvn07d+5kU1kMDQ3Ly8u5DDNmzPjPf/4j62HVeEaqk5GRwf7KRPTgwYOBAwdK+UaRSCRHcVu2bLl27VpGRkbv3r0//fTTZcuWvfPOOxJ5UlJSvvvuu0OHDgmFwi5duqxcuVKOgojo5cuXbGYIh51pfHy8RHpVVZV8RZibmw8fPly+98qHhysMPr/nvJWlxsaLwCE99faxCBzS4zNw8Bk1CIHjfzQ2cDTJCKVcGC5qCldXV1dX102bNl25cuXw4cMnTpwoKiqKiIiIiIhYtGiRHD2IpaUlEb1580b6txQUFBCRubm5TAXp6emxzaMaUFpaum7dus2bNwuFQhMTk4CAgIULF8pUCsPbSdXp999/nzNnztq1a2/dulVYWMhCvrGxsZub27fffsttOSUT9Z5R02BlZXX16lUfH5+nT59u3759165dDg4O1tbW1tbWAoEgJSUlOTk5KSmpurqaiLp06fLvv/+Kbyotk/z8/K1bt9ZOT01NrTNdDl27dr106ZJSDtUo3q4w+Pye81aWJjReBI5Gqf3PhMChgfiMGoTAIa8m2ZlraePFcFGz6OrqDh8+fPjw4Tt37vz7778PHz584cKFyspKOQ7l4OBARJGRkVLmFwqFERERRCSxE7TiLl26NHfu3JSUFCLy9fXdvXu33HOl1H5S/fr1CwkJIaKXL19mZGS0a9euffv2ihyQ/zPKzc1dtmyZNDnlvs3Zq1evjIwM+d4rHxsbmwcPHqxfv37nzp35+fmPHz9mO56JMzMz8/f3//bbb42MjOQfxgdkAAAgAElEQVQoonnz5uypjKaEtysMPr/nvJWl9u6Ig8DRAE04IwQOafAcOHiIGoTAoZgm2ZlrQo8kDzU+NwnSePXq1e7du+V4I58Pc9cnLy+P7VZERFZWVocOHVLwgOo9KaFQePLkyYULF0ZERHCJgYGBH3zwwf79++XbR5X/Z+6bdi9RVlZ26tSpZcuWjRo1ysPDo2/fvj4+PgsWLAgKCioqKlJ37d5efH7PeStLE/rY+iBwcNR+RggcGg5RQ2M1yc5c7T2SfLSmPYMcpkyZQkQWFhbx8fEN57x48SJ7hnvVqlXKKj0oKMjKyoqFjWnTpuXl5SnlsOo6qZycHE9PT3Y6p06d4tIDAgJYoo+Pj3yhhbczevjwYT+5yFEWgAQ+Wy5vZam3j1WRphc41HhGCBwAimiSnbk2Bg4MF/lWJRf5ynr58mWnTp2IyMjI6PPPP09LS6udJzk5efr06ezr2KVLF6XshJuWlsYWdiciGxubixcvKn5MjrpOauLEiURkYmKyePHi9PR0Lj01NTUgIIA9hLN06VI5jqyuMwLgE5/fc97K4q0gBA5FqLGPReAAUETT68x5LktZdERyLUUI8rl165aHh4ccb5T7z5Samsoe5iYigUDQ6MPcHTp0kK8gpqamZseOHatWrSopKdHT01u0aFFAQIAiD4jXieeTIqInT5507drVyMgoKirKycmpdobExES2i05ubq4cjyPzf0YA/OPze85bWTwUhMChOLX0sQgcAIprSp25WspSDvWOVt82ankGoLS0dNWqVWyXzzqZmZl9+eWXpaWlCp5dbGxsv3792DF79ux57949BQ/YAN5OigkODiaiWbNmNZDngw8+IKLIyEj5iuD5jADUgs/vOW9lqbogBA6l4L+PReAAUIom05mrqyzF4ddFXnE3ifX09IYMGfLRRx9xYbJhrq6uChZdXl4eEhISERHx+PHj169fC4XCFi1aODg49O/f//333zczM1Pk4BUVFQEBAZs2baqqqjIyMlq3bt3SpUsFApWvu6vSkxK3Y8eOzz//fO3atevWrasvz9y5c//73/8eP358woQJchfE2xkBqBGf33PeylJdQQgcSsTndw+BA0CJmkBnrt6yFIHhIq+Kiop279599OjRe/fusZTOnTt/+OGHH330kXzb1ktPJBIJhUJdXV1dXV3lHvnFixeenp5sz1kXF5fAwEA7Oztp3ti2bVvl1kR1wsPDhw0bNnbs2NOnT9eXp1+/fnfu3Hn06FGdk47qk52dXVVVxWaxA4AW4a3xInCIQ+AgBA4AraWtjVe9P26+tVJSUjZs2NC7d2/uD2FjY/PVV1/dvXtXRSX++uuvROTq6qr0I2vIKtthYWEbN2709/cfPXr0nDlzfvrpp/DwcGUdvKioSCAQCASCkJCQOjP89ddfRGRqaioUCmU68s2bN01NTX/++We516UAALXgv/EicCg3cKg0aogQOACgFi1tvBguqllKSsrGjRv79OnDxUJbW9vly5cr/fmNI0eOEJGxsbF8uzw1QO1R//r16/VNzfL09IyJiVFKKT/99BMRGRkZzZ8//969e4WFhSKRqLi4ODo6et68ec2aNSOiHTt2yHpY7tPr0aPHzZs3lVJVAOCBGhsvAoeC+IkaIgQOAPj/tLTxYjKqpkhJSTl27NixY8e46Ub29vZsupHiz58QUUVFhaur65MnTw4ePDht2jTFD8iprKx8+fKlHG/s2LGj4qXHxcX17du3vLxcX1/fx8fHzs6ubdu22dnZT548CQsLq6mpsbS0fPDggVLKmj179r59+7h/GhoalpeXc/+cMWPG/v37ZT3m69evZ82adebMGSLS0dH57LPPNmzY0MCjzwCgITSh8SJwyIHPqEEIHAAgRlsbr7rHqyApOTlZYrqRo6OjUo784sWLPn36WFhY7Nmzp7KyUinHVC+hUMie9/D29hbf0op58uQJu/s+fPhwZZV469YtHx8f8RXPjY2NhwwZouAUptDQ0K5du7IDtm7d+s8//1RWhQFApTSk8SJwSIn/qCFC4ACA/0/rGi9+XdRcN27cmDlzZlJSEimwfRansLDwP//5T3V19enTpysqKgQCQbt27SwtLWvnjImJka8IkUiUkpISHx9fVlbWo0cPR0dHpa+OIIHtamVtbR0bG1vn+lGZmZndunUrKCgoKCiQY1erBrx8+TIjI6Ndu3bt27dXygGrqqp27Njx7bffFhYWEpGnp+euXbscHR2VcnAAUB2NarwIHA1TY9QgBA4A+B8ta7xqHaxCHXJycnbu3Dl06FAuZLZq1Urxw2ZlZan0KxEbGyuxRp+zs/Pt27cVr3kD2DoBc+bMaSDP+++/T0TKXcBAdXJycmbPns3+9AYGBmvWrCkrK1N3pQCgceptvAgcUmp6UUOk7u8eAMhNWxovfl3UFK9fvz558mRwcPCVK1eEQiERtWjRYvz48X5+fp6enopvRVVZWXnt2jVpcnp5ecl68GfPnjk5OZWVlUmk6+vr37t3z9nZWdYDSmn37t3z5s1bsWLFDz/8UF+emTNnHjhw4PTp02PHjlW8xLy8vKNHj0ZGRmZnZ5eUlFy6dMnU1DQoKGjcuHHGxsaKH5+JiopauHAhex7a1ta2Z8+etfMcP35cWcUBgLLw3HgROGTFf9QgBA4AaJAWNF51j1ffdgUFBQcOHBg5cqS+vj77i5ibm0+bNu3cuXNa9JQI21/Y1NQ0MDAwPT09MzNz37597Mldd3d31ZV748YNIhoyZEh9GWpqat59910iSklJUby4P//8U+Jx5Pz8fJFIZGBgYG5ufv78ecWL4FRWVg4bNgwtF0Dr8NB4ETjkxnPUECFwAIAUNLzx4tdF9SgpKTl79mxwcHBISEhlZSURmZqajhkzxs/Pz8fHx8DAQN0VlIFIJDIxMSkrK9u/f/+MGTO49DNnzowbN46IVPEECFNSUmJlZVVeXr5r1y5/f//aGb777ru1a9e2bt06JydHwbJOnz49YcKEmpqarl27jho1Kjw8PCoqKj8/38LCon///jdv3tTT0wsJCZHjFntt165d+89//vPw4UMisre3F1++gsOmVAGARlFp40XgUByfUYMQOABAClrQeNU7Wn3blJeXHz16dMKECUZGRuzzNzY2/vDDD48fP15aWspbNZS7N3FaWhoR6evr195ytGXLlkR0/fp1xerbkMDAQPZJ+vr6njhxIjY2Njs7Ozo6+q+//ho8eDB76eTJkwqWUl1dbW1tTUT+/v7s5v2UKVPofzeJRSLR999/T0S9evVScHeyrKysqVOnsmrr6+uvXLlSM2exA4AE1TVeBA7l4idqiBA4AKAx2tJ4MVzkFbc7p66u7rBhw3bt2vX8+fN8KSirAqrYm/jWrVtEZGtrW/sltobBhQsXFK54QxYsWFDfSnr6+vrr1q1TvIjLly8TUdeuXbmJXhJRXyQSdevWjYiePn0qXxHV1dVbt25t3rw5q7m7u3tcXJziNQcAVVN140XgUDoeooYIgQMA6qddjVfR5+BBPjU1NVeuXLly5cq8efOkyS9SxpzhuLi4ESNG1Lc38eXLlz09PeXYm5jVjXuERlyzZs0Ur3ajtm/fPnfu3PXr10dHRz979qyiosLIyMjW1rZv377ffPONra2t4kUkJiYSkY+PT52nyfTv3//Ro0eJiYn29vayHj8yMnL+/PkPHjwgIjMzsx9++GH+/Pmq3oYEABTHZ+NF4FAWHqIGIXAAQD20rvFiuPi2qKmpmTRpUnl5ube392+//dapUyfxVxMSEqZOnRoVFTVjxoxLly6pq5Jy6969+5EjR4iopqYmPz/f0tJSR0dHicc3NDQkooaXGay9vp80ioqKFi9efODAAXbxNGbMmMDAQFkvvACAf29D423CgUPVUYMQOACgFi1tvBgu8qpnz55Pnz5VS9GJiYnx8fHW1tbHjx+vvTdxly5dzpw5061bt3///bewsFBFK9PwQFdXlz33oly9evUioitXrohEojovKaqrq9ncKldXV5mOHB8fv3//fiJq167dtm3bJk6cqIz6AoDK8dZ4EThUSkVRgxA4AKAWLW28GC7yysDAQI4JJ0rBfvL29vauHfKZ9u3bDxw48Ny5czExMUOGDOG3dsp069atu3fvCgQCNzc3V1dXxXceIyInJ6cOHTrcu3cvICBgzZo1Eq+KRKK1a9cmJSXZ29u3b99e1oPr6OjMmTNn48aNWnqxBfDW4qfxInComiqiBiFwAEBdtLHxYrj4tsjPzyeihu+htmrViogKCgrkOH5OTk7tRcmTk5OJaPv27adPn679lt27d8tREHPy5MkLFy7ExcWxW7NMSUmJn5/fP//8w6X06tXr5MmTnTt3lrsgRk9P7/Dhw8OHD1+7du2///47adIktsZ6RETEixcv/vjjj8jISD09vQMHDsh65NatW1+7dm3gwIEK1hAAePY2NN6mFDh4jhqEwAEAtWhp48W+i7yqqKjIyMiQ442K31qOiIgYOHDgkCFDwsPD68wgEomcnJyePHmSkpJiY2Mj/ZFv3brl4eEhR5Xk++6VlpbOmzfv4MGDRKSnp1ddXc29NG7cuDNnzhCRiYlJy5Yt09PTiahVq1aPHj1q3bq1HGVJ+OOPP5YtW5aXl1f7pRYtWvz888+zZs2S9ZilpaVCobC+O/cAoLF4a7wIHBIlyvoWNUYNQuAAADFa2njx6yKvoqOj+RxZiXNxcTE0NLx69eru3bvr3Js4ICDgyZMnrVu3linkE5G5ufnw4cMVrJ70fvzxx4MHD+ro6EyePFl87tPdu3dZ1J86depvv/1mYGCQlJQ0duzY+Pj4n3/+edOmTYoXPX369PHjx2/ZsiUyMvLp06fPnz9v166dg4NDv379vvjiC0tLSzmOGRsbO2jQoD59+gwbNmzYsGEDBgwwNjZWvKoAoGq8NV4EDgWpMWoQAgcAiNHWxsvrth1vPW77LLX8mXjbm1h1Xr58aWpqSkR//fWXxEvsUuadd94R37c6KiqKiExMTN68ecNvTaUl8ZXQ19cfOHDg6tWrL1++rJlbtQIAw1vjReBQRNOLGiIEDgCtpaWNF8NFXlVXV0uzt3J+fv7ly5cdHR3Zl8nNzU1ZFeBnb2LVOXToEBENHz689kvW1tZEtGbNGon07t27E1FsbKxMBb1586aoqEj+ikotOzt7yZIl/fr1q73VmIGBwdChQ7/99ttr165VVFTwUBkAkB5vjReBQxG8RQ0RAgcANEZLGy+GixrnzZs3X375pZ6eHrvBuXnz5urqaiUePy4ubtKkSV26dDEwMCAiIyOjbt26zZw5Mzk5WYmlqMh3331HRD///LNEOrfKfHR0tMRLo0ePJqIzZ87IVNDNmzcFAoG7u/uKFSsuXrzIw23msrKy69evb9q0ady4cW3atJHoRIyMjLy8vNavXx8ZGVlVVaXqygCA9DSh8SJw1Ie3qCFC4AAAqWlX48VwUbOEhYXZ2tqy74qvr++zZ89UV5ZQKMzLy6upqVFdEUo3e/ZsIjp+/LhE+s6dO4nIysqq9ulMnz6diAIDA2UqSO2zBZKTkw8ePOjv79+jRw+J+/qmpqa+vr481AEA5MB/40XgaABvUUOEwAEA8tLwxovhoqbIy8tjIYoFsEOHDqm7Rppo6dKlRHTgwAGJ9PHjxxORn59f7bd4enoS0dGjR2UqSKNmCxQVFYWFhX3zzTdWVlZcNXgoFwAUpOrGi8DRKN6ihgiBAwCUQQMbL1ZG1QhHjhxZtGhRbm4uEU2bNm3Lli0N73MlDTWuva46Dg4ORBQTE8NdIRFReXl5WFgYEXl5edV+S2JiIhFxt96l1KZNm82bN7ODR0VF3bx5MzIy8ubNmzk5ORUVFeHh4eHh4WvXrjUyMhowYABb3srNzU1ZmzuLS09PDw0NDQkJuXTpUlFRkdKPDwAqourGi8AhDd6iBiFwAIDCNLTxqne0Cmlpae+99x77W9jY2Fy8eFFZR1bvYnoqcufOHSIyMzPLzs7mEvft28dqXnsK1tGjR4nIwMCgsLBQKRXgZ7ZAWVlZaGjokiVLunbtKl6EhYXFxIkT9+7dm56erpSCAEC5+Gm8CBzSU3vUECFwAECDNL/xam4X3+QJhcKtW7eyBb719PSWLl2q3Mfim17UZ0aOHElEdnZ2Z8+ezcjIOH36NLuhPmjQIImc0dHR77zzDhEtXLhQFTVR+myBhISErVu3jhw50sjIiDugrq6um5vb6tWrIyIilLt2BQAoC2+NF4FDDpoTNUQIHADwP1rUeHVECm/jC3KIi4v77LPPbt++TUQ9e/b87bffevXqpdwihEJhcXGxNDmjo6P9/f3Z9Bs3Nzd2L1ZjPX78eOjQoS9fvhRP1NPTCw0N5TZ93rp16+3bt0+cOFFZWdm8efPExMTaq04pqL7ZArI2qIqKitDQ0AsXLoSEhDx79oxLb9u2rbe3t6+vr7e3t+ITzABA6fhvvAgc8tGQqEEIHABvPW1tvGoerr59ysvLV61apa+vT0RGRkYbN25U4wq5ql57XUUyMzPfe+89bi2BNm3aHD58WDwD19JcXV0TEhKUVa4qZguI38vX19cfOnTohg0bai/sDgCahs/Gi8ChIHVFDRECBwCI0dLGi6VuePXixQtPT092O9bFxSUwMNDOzi4vL6/RN7Zt21bplbl06dLcuXNTUlKIyNfXd/fu3Z07d1Z6KarQrl278+fPV1ZWPnr0SF9f39HRUWIZur59+xobG3t5ec2cOZPtEqaIxMTEkJCQkJCQ8PDwsrIylqirq9u7d29fX19fX99+/fqxKycFubu7jx071tvb28nJSfGjAQBvVNp4ETgUx3PUIAQOAGiMNjVedY9X3y4a8lgI1l5vVHl5+ZkzZ/z9/a2trcX/EG3btv3kk0+CgoLy8vKUUlB2dra/v7/EEnwdOnSYMWNGUFDQy5cvlVIKACgdb40XgUNbIHAAQMO0tPHi2UVe3bp1y8PDQ443KvHPpIq115se8b+Uvr7+gAEDfH19fXx8XF1dVVRiSkpKaGhoWFjY5cuXCwsLWaKOjo6rq+uIESO8vb0HDhyolHveAKBcqm68CBzaAoEDAKSkXY0Xw0VeVVZWSjxtL6WOHTsqXnp6evq8efP++ecfIrKxsdmzZ8+IESMUP2yTJB71Bw0a9MEHH/A2W6C6uvr27dthYWGhoaF3794VCoUs3djYePDgwd7e3t7e3t26deOhJgAgExU1XgQObYHAAQCy0orGi+HiW6GmpmbHjh2rVq0qKSnR09NbtGhRQECAsbGxuuuluXJyctatW3fx4kX2iA7ToUMHdsvHy8tLfA101SkoKLh06dLFixfDwsLEV9Bq3779ixcveKgAAMinCTReBA5ZIXAAgCI0tvFiuNj08bD2ehOmIbMFcnNzDxw48NNPP7HJYKTUaWYAoDpa2ngROBSBwAEAitC0xovhYlNWUVEREBCwadOmqqoqIyOjdevWLV26VCDAcrjy4H+2QEJCQkRERERExI0bN9iiiJw2bdpkZ2crsSwAUCKtbrwIHEqEwAEAUtLkxovhYpNV59rr0rxRFWuvNzEqmi1QWVkZFRXFeorIyEiJhfItLS2HDBni6enp6empBWsuA7xNmkzjReBQHQQOABCnRY0Xw8UmSxMW02vyFJ8tUFZWdunSJXY/6e7duxUVFeKvmpmZDRo0iHUWLi4uurq6Sqs6ACimSTZeBA4eIHAAvLW0tPFiegmAbBqeLSDr0R48eDBmzBjxFCMjowEDBgwbNmz48OF9+vRRyj7OAKB0aLwgPQQOACCtbbwYLjZZvXr1ysjIUHctmgIeZgs0a9asX79+w4YN8/T09PDwaNasmTIqDgAq18QaLwKHsiBwAEB9tK7xYjIqQB14my2Qk5MTGxs7YMAALE8PoF3QeEECAgcANExLGy+GiwB1qP0Aj1bMFgAAAHVB4ACAJgmTUQHqpXWzBQAAQL0QOACgicGviwB10NLZAgAAoC4IHADQJGG4CAAAAAAAAHXQlA09AAAAAAAAQKNguMiH7t27T5w4Ud21AABQoQkTJjg7O4unPHv2TEdH58CBA2qqkdbo1KnT7NmzxVOCg4N1dHQeP36srioBAKjFtGnT7OzsxFNevnypo6Ozc+dOdVVJk/ETZzFcBAAAAAAAgDpguAgAAAAAAAB1wHARAAAAAAAA6oDhIgAAAAAAANRBoO4KvC1yc3PDw8PVXQsAAFXJy8urM/3Jkyfo/RpWUVFRZ/rdu3dzcnJ4rgwAgBrV1+k9ffoUoaS27OxsPooRgep169aNj78lAIBade/eXbzrS01NVXeNtMasWbPEP7q//vpL3TUCAFAPW1tb8f4Qd80atX//fpUOZPDrIh/279//5s0bddcCAEC1TE1Nxf/Ztm3bK1euqKsy2qVdu3bi//T09MRHBwBvJyMjI/F/tmjRAv1hw959912VHl9HJBKptAAAAAAAAADQRvh1EUALREVFVVdX29nZWVlZ1ZmhuLj40aNHRNS7d299fX3FS0xISMjPz7e3t2/VqpXiRwPgU1ZW1pkzZ5KSkl69etWpUycHB4chQ4a88847Sjn48+fPnz9/bmJi4uzsrJQDAkjgv8Mn9PkA/4MIUgeVTnUFAKUwNzcnor1799aX4fr166xFZ2VlKaXEUaNGEdGff/6plKMB8CM3N3fatGm6upKLfhsYGCxfvry4uLi+Nz58+PCbb76ZOHHikiVLwsPDGyhi1apVROTi4qKC6gOIROro8EXo8wEQQeqHXxcBAKApePbs2ZAhQ9LT0/X09EaNGjVgwAATE5Nnz55dunQpLi5u48aNDx8+/Pvvv3V0dCTeuG3btmXLllVVVbF/btmy5auvvtq4cSPvZwAAAOqBCNIA7LsIAABar7y83MfHJz093cLCIjQ09Ny5cytWrFi4cOHmzZsfPHiwY8cOIjp//vwvv/wi8cY7d+4sXbrUxMTk7Nmzubm5Z86csbS03LRp09WrV9VxHgAAwDdEkIZhuAgAAFpv/fr1iYmJRkZGERERw4cPF39JR0fnP//5z/z584nol19+Ef3/Bd5OnjwpFAoXL148evToVq1ajRkzZvny5UR04cIFPusPAADqggjSMExGBWiCSkpKSkpKDAwMWrRoIfFSRUVFfn6+rq5u69atucTMzMy7d++mpaVZW1uPGDFCYg1rIqqsrHz9+rWRkZG5uXllZeXp06ezsrIWLlwoPivjzZs3sbGxsbGxLVq0cHFxcXBwqP0AAJOSknL16tXi4mJHR0cvLy+BQFBQUFBeXt6yZUvxZRuEQuHjx4/v379fUVHh6Og4cOBAPT292rUyNDS0sLAgooiIiNjYWIFA4OTkNGDAALk+OdBK5eXlgYGBRDR79mwnJ6c68yxYsGDnzp3Z2dmRkZHiX4/09HQiMjMz41LatGlD9W8VDaBpZO3wSRl9vtI7fEKfD2qCCNI4dT88CQCNk3Xlg5MnTxJRu3btampqJHKuWLGCiHx9fdk/S0pKPv74Y/E+oU2bNlFRURLLHoSFhRHRlClTXrx40bVrV5azqqqKO+yuXbsMDQ3Fj9OtW7e4uDiJ0qurq5ctWyaezd7ePiYmhhV38+ZNLufVq1c7duwontPGxubUqVPiR2O1mjBhQkZGRr9+/cQz9+3bNyMjQ+YPGrTTqVOniEggEDx79qyBbHv27NmyZUtUVJR44rZt24iof//+rLFUVFR4eHgQ0bZt2+o8iJYuVABaRHUdvkhJfb7SO3wR+nxQH0SQRmG4CKAFZL16KCsrY/e6rl+/Lp6tpqbG2tqaiIKCgkQiUUVFRY8ePYhIV1d3+PDhy5YtGz16tJGRkampKcsmceng5+fXp08fIjI2NnZxcREKhezVzz//nJU+ePDgr7/++rPPPuvcuTMRGRoaSlRg3LhxRKSvrz9+/PjVq1ePHz++WbNmrVu3dnV1Fb96+OOPP9hN5V69ei1btmzhwoVsC1pdXV3xhftYrUaOHNmtW7fWrVsvWbJk165dc+fOZXeshw8froSPHrTBl19+SURdu3aV470lJSVshfRvv/02MzNz2LBhRNS9e/eysrI682tpsActoqIOX6SkPl/pHb4IfT6oFSJIozBcBNAC7Ophzpw5R+qxbt068asHkUjE7h8vWrRI/DjsIqN58+alpaWi/90VMzY2PnPmDJfnzp073GZfEpcOBgYGFhYWBw4cEL+H/fDhQzYHKTAwkEssLCz09vYmIg8PDy4xNDSUiExNTS9fvswlXr582cTEhBXHrh4KCwvZxl/r1q3jCqqsrJw7dy4RtWjRIjc3V7xWOjo6Dg4O4veVg4KCWHpRUZEiHztoC/ZjxciRI+V7++XLl3V1dXV0dFhD8/LyevXqVX2ZtTTYgxZRUYcvUkafr/QOX4Q+H9QNEaRRGC4CaAHWB0mDu3o4ffo0EXXq1El8aOfv709Es2fPZv9kM+xXrFghUdyuXbvqvHQgoj179khknjx5MhH5+PhIpKelpQkEAiIKCwtjKWy6/1dffSWRc+nSpeJXD+xKaPDgwRLZKioq2P1m7jKFq5XEhKWqqioDAwMievjwYQOfKjQZbPLPvHnz5Ht7TExM+/bt2Xep9vdTgpYGe9AiKurwRcro85Xe4YvQ54O6IYI0CiujAmiNHj16jKpH//79JTL7+vqam5tnZGTcvn2bpVRVVR07doyIPvnkEyLKzMxkj2JzM4s4M2bMqL3yAREJBIIZM2ZIJEZHRxPRnDlzJNLfeecdHx8fIrp//z4RCYXCO3fuENGnn34qkXPWrFni/4yMjCSiSZMmSWRr1qzZ+++/z2Xg6Ovrjx49WqKebCEE0f9fwQyaKqFQSETsalVW33//fZ8+fbKzs11cXIgoKCiIW6Lg2rVrf/31V3Z2thKrCiAl5Xb4pKQ+X+kdPqHPB3VDBCFeSPwAABpASURBVGkUVkYF0Bqff/557dDL3LhxY9CgQeIpBgYGY8eOPXjw4LFjx9zd3YkoJCTk1atXNjY2LGdSUhIRmZubt2vXTuJohoaGNjY28fHxEunt2rVr1qyZeEpNTU1qaioROTg41K6Vvb09EbEMaWlpVVVVenp6NjY2Etns7Ox0dHS4MP/06VMiOnnyZEREhETOhIQEIpLofK2trSVWz4O3DVsQMiUlRdY3Llmy5Ndff23VqhVrJoMGDYqKivrggw+uXLnSrFmzpUuX3rt3Ly4urm3btiqoNUBDlNvhkzL6fFV0+IQ+H9QNEaRRGC4CNFl+fn4HDx48ceIE21j28OHDRDR16lS2EnpeXh4R1deLtWvXrvalg6WlpURKfn5+RUUFEUms0s6wg7948YKIMjIyiKhFixa1b+AZGhqam5sXFBSwfz5//pyILl26VN95lZSUiP/T2Ni4vpzwlrC3tw8NDU1OTm44259//hkaGtqpU6cff/yRiG7evPnrr78aGRldvnzZ2dmZiE6ePNmnT5/IyMj58+dv3rw5Pj5eIBA4OjrycQ4Aimm4wydl9Pmq6PAJfT6oGyJIozAZFaDJ8vLysrCwSEtLi4qKKi4uPnv2LBFNmzaNvdqpUyciyszMrPO9Uk6fsLS0ZFOY6szPEtmdbPbf169fV1VVSWSrqKgoLCzk/slynjt3Lr8eDVxVwNuJzc1LSkpiv2zUZ/v27YcPH+a+q8HBwUQ0a9YsFumJqFOnTseOHRMIBL///vuYMWPKyspGjx4t8Ys6gGZquMMnZfT5qujwCX0+qBsiSKMwXARospo1azZ+/HgiOn78+KlTp8rKyjw8PLhJRLa2tkRUXFyclpYm8cby8vKGO02Ojo4OOw6bMiThyZMn9L8ZSra2tgKBoKamhk2IEpecnCw+MYnlf/HihUU9TE1NpTp/eGuMHj3a1NS0urr622+/rS9PTk4Oe6pq6NChLIVdN0tMqxs8ePDmzZuJ6OrVq0S0cuVKldUaQJka7vBJGX2+Kjp8Qp8P6oYI0igMFwGasg8//JCIjh8/ziYmTZ8+nXupZcuWXbp0ISLWtYn7/fffS0tLpSyib9++RLRz506J9MTERLaKnZubGxEJBILevXsT0Z49eyRy7t27V/yfbPPlgwcP1i6rf//+hoaGbM10AI6ZmRlbBPLQoUP1/RCxdOlSoVBoZGTEVvwnIrZZ1r179yRyfv755+xLa2hoyJ5pAdAKDXT4pKQ+X+kdPqHPB3VDBGmcOpdlBQDpyLprM6eyspI9fKKjo2NgYJCfny/+Kruk0NfX37dvH5d47do17nkViUXV61z6OSkpiW2R/N1333GJmZmZrLv09PTkEi9cuEBEhoaGJ0+e5BL//vtvbkW+W7duiUSiV69esTXuVq1aVV1dzeVcv349ETVv3rykpKTRWrH14uPi4ur7xKCJefPmDXtERE9Pb8OGDVVVVdxLJSUlS5YsYd+xbdu2celHjx5l+S9dusQlVlZWcgv9E1H37t2Li4vFC9LSZdBBi6iowxcpo89XeocvQp8PGgARpGEYLgJoAbmvHkQiEbe23sSJEyVeEgqFnp6e7FUXF5cZM2YMGjRIX1/f2Nh43LhxUg4XRSLR2rVr2UG6du06c+bMMWPGsNjfokWLmJgY8Zzs5reOjk7//v3nzJkzePBgPT293r17s7X7oqOjWbbffvuNLXxnb28/bdq0OXPmdO/enfXL586d446GSwcQl56ezi0qYGho2K9fv2nTpg0ZMoS7FB4zZoz4rnRCoZBtDaenpzd9+vSdO3euX7++a9euRNSyZctjx46xb9G4cePE36WlwR60iIo6fJGS+nyld/gi9PmgARBBGoDhIoAWUOTq4eLFi+yls2fP1n5jVVXVsmXL2N1ixtra+tq1awEBAdIPF0Ui0fHjx62srEjMsGHD0tPTJbIJhcJVq1aJF/fhhx/m5+ezTXITExO5nNeuXWMPyXB69uzJbQDdaK1w6fB2KikpWbFiRe0lfNu3b3/48OHa+Z8/f+7r6yuR2d3dPSEhQSQSXb9+nX1X161bx71FS4M9aBHVdfgiJfX5Su/wRejzQQMggtTn/219AwBNT3h4+LBhw6ysrDIzM+vbhbaioiI2NjYlJaVjx44eHh66uvI81SwSiVJTU+Pi4szNzV1dXdn95jqVlZVFRUXl5OS4urqyRQ46dOiQlZX15s0bia2inz9//uDBAyJydHS0t7fnVoQHaEB1dfXNmzdTU1OLi4s7d+7s6OjIFt6oL/+NGzeio6OfPXvWvHnzgQMHDhs2TL4mAKB20nT4pIw+XxUdPqHPBw2ACFIbhosATdyUKVOCgoIWLly4detW9dZk7969L168mDBhArfqNPPo0SNnZ2d7e/vExER11Q0AoAlAhw8ASlfvWBkAmoCEhITjx49TrSXy1CI2NnbHjh0xMTGnTp3i7hlXVFQsW7ZMJBKxJeABAEA+6PABQBXw6yJA07Rp06aYmJgrV65kZ2d7eXmxRz7UKyEhwd3dvaCgYOjQoZMmTWrZsmVycvLBgwfj4+MtLS2fPHki8TAMAABIAx0+AKgOhot82LlzZ6tWrT766CN1VwTeIpMmTQoODiYiW1vb8PDwTp06qbtGRESRkZELFiyIjo4WT+zevfuhQ4dcXFzUVSsA9dqyZYudnd2YMWO4lEePHh07dmzBggWtWrVSY8VAW6DDB3g7FRQU/Prrr+PGjXN1dVVdKRgu8qF79+7vvvsumyICwI+UlJTw8PDmzZu///77hoaG6q7O/3Pv3r2nT5++fv26c+fO9vb2jo6OWM8A3madOnXy9vb+/fffuZTg4OBJkybFx8ezZdkBGoYOH+Dt9OzZMxsbm/3798+YMUN1peDZRYCmydbWVmJRcs3Ru3fv3r17q7sWAABNBDp8AFCdprbSKwAAAAAAACgFhosAAAAAAABQBwwXAQAAAAAAoA54dpEnV69eHTp0qLprAQAAGic3N7fO9OnTpxsbG/NcGQAA0Bbl5eU8lILhIh/c3NxSU1PVXQsAANBE7u7u7777rnhK69athwwZoq76AACAVjA0NBwyZEjbtm1VWgo20gAAAAAAAIA64NdFAC1TWVl5//59ItLT03Nzc1N3deSXn5+fkJDQvHlzJycndddFIUVFRfHx8SYmJs7OzuquCwBonKioqOrqajs7OysrqzozFBcXP3r0iIh69+6tr6/Pb+2aTlcsDXTXAHLAUjcAWub06dMeHh4eHh59+/ZlVxha6urVqx4eHnPmzFF3RRR1584dDw+PadOmNZrz6NGjkyZNmjRpUmFhIQ8VAwBN4OXl5eHhcebMmfoyPHjwgPXqr1694rNiTJPpiqWB7hpADhguAmiZw4cPc/9/5MgRNdakifn000/HjRun0seMY2Njg4ODg4ODy8rKVFcKAECTp+oeG901AAfDRQBt8vr165CQECJiE2mCgoLUXaOmIyQk5MyZMyq9kWxkZGRubm5ubq6ri74XAEB+qu6x0V0DcNAGALTJ0aNHKysrLS0t9+zZQ0Spqak3b95Ud6VAWqtWrSooKCgoKGjdurW66wIAAPVCdw3AwVI3ANqEzUT18/Pz8PCwtbVNSUk5cuSIh4eHRLbKysrXr18bGhpaWFgQUURERGxsrEAgcHJyGjBggKzZiKisrKywsJDLKS47O5uI2rRpo6OjI56elpYWHR39/PlzAwODjh079u/f39zcXI5TrqqqevXqFSu6vLw8NDQ0NTXV3Nx8xIgRHTt2ZHkyMjKioqKysrIcHBw8PT319PQkDtJwZQoLC8vKympqaojo1atX2dnZFhYWhoaGXIaSkpL79+/HxcW1bt26R48eXbp0qa+2QqHw2rVr8fHxzZo169q164ABA8Q/FvaB6+vrt2zZkmT5/DkpKSlXr14tLi52dHT08vISCAQFBQXl5eUtW7bkf4UMAFC1N2/exMbGxsbGtmjRwsXFxcHBQeLHLuk7Z9bhsB/NKisrT58+nZWVtXDhQol3lZSUlJSUGBgYtGjRQuKlioqK/Px8XV3d+kZQSumuia8eW6bumtBjw9tMBABaIjU1lQWzyMhIkUj09ddfE1GbNm2qq6slcoaFhRHRhAkTMjIy+vXrJ97k+/btm5GRIVM2kUi0d+9eIho7dqxEQdxDHcXFxVxiUVGRn5+fxEWAmZlZQECA+HtPnTpFRAMGDGj4rK9fv84qGRkZ2aFDB+6AAoHgt99+Ky0t9fPzEy/I2dk5MzNTpspIHIGIjhw5wr36yy+/SMR1Pz+/nJwciU/bxcUlISFBYrU9Nze358+f184p6+cvEomqq6uXLVsmnsfe3j4mJmbUqFFEdPPmzYY/RgBQFzbU2bt3b30ZWC9HRFlZWeLpu3btEh8FEVG3bt3i4uLE80jfObMOZ8qUKS9evOjatSt7taqqSqIrPnnyJBG1a9eupqZG4pgrVqwgIl9f34ZPRO7uWqT6Hlvu7lqEHhveYvh1EUBrBAUFiUQiOzs79nOin5/fhg0bcnJy/v33X29v79r5S0tLfX19c3NzlyxZ4ujoGBMTs2/fvjt37syYMePSpUuyZpPe9OnTT506ZWBgMGnSpC5dupSWll69evXmzZurV6+2sbGZMmWKHMdMTk4eOXKkg4PD4sWLRSLRnj17kpOT/f399+7dGxUVNXv27N69e8fGxu7duzcuLu7rr7/+448/pK+Mp6enqanpkSNHSktLx48fb2lpaWdnx94+e/bsffv2CQSCMWPGuLq6ZmRkHDlyJDg4+NWrVxcvXhS/Ff3q1avhw4cLhcIvvvjCwcEhKirqjz/+uHv37qxZs0JDQxs4NSk//4kTJ54+fVpfX//999/v3r37w4cPz58/7+3t3b59ezk+TwDQcAsXLty+fTsRDR48uH///qzPefTokZubW1hY2MCBA+U7bHV19dixYx8/fmxsbFz7t0oiGjlypJmZWVZWVkREhHgpIpGILa72ySefNFyE3N018dVjy91dE3pseDupd7QKANJjm2KtWbOGS3FwcCCi6dOnS+RkN0F1dHQcHBzEb3mypXF0dHSKioqkzyaS5QZ2RkYGEenq6rKfQDmffvopEU2cOJFLkenXRSIaN25cVVUVS8zJyTEzM2Pp586d4zL/8MMPRNS5c2dZKyMSidi98OjoaC7l1q1bRGRoaHjhwgUu8eHDhyYmJkR08uRJlsI+RiLq2rWr+J3y33//nYgEAkFZWZl4TolfF6X5/NkVjKmp6eXLl7lsly9fZjUh3KsG0GDs18U5c+Ycqce6detYQ+Z+XXz48CEbyAUGBnLHKSwsZHcGPTw8uERZf100MDCwsLA4cOAA9+Nh7a74448/JqJFixaJH5B1xc2bNy8tLa3vTBXprkW89Nhyd9ci9NjwFsNwEUA7REdHszCTmJjIJa5atYrFby7CMVxEPHXqlHh6VVWVgYEBET18+FD6bCJZrkiuX7/er1+/KVOmSOQ8e/YsEfXp04dLkXW4mJ6eLp4+YsQIIho9erR4ItuIUiAQyFoZUV0XHz4+PkQ0f/58ibcvWrSIiBYuXMj+yX2MZ8+eFc9WWlrKplQlJSWJ55QYLkrz+bMHY7766iuJmixduhQXHwAaTvrHtrnh4uTJk4nIx8dH4lBpaWkCgYCIwsLCWIqsw0Ui2rNnj3jO2l3x6dOniahTp07i81H9/f2JaPbs2Q2cqSLdtYiXHlvu7lqEHhveYpiMCqAdDh06RETu7u7sF0XGz89v/fr1RUVF586dmzhxosRb9PX1R48eLZ4iEAgsLCzYUxyyZpPSwIED2S1eCezKQI4DMu3bt+/UqZN4iqWlJRG5u7vXTuRKUbAy7L2zZ8+WSP/iiy+GDh0qsdhDs2bN2EMpHCMjI1NT08LCwoYLavTzFwqFd+7cISJ2i13crFmzNm/e3PBZAIAm6NGjh0QnxsnPz4+MjBRPYfcH58yZI5HznXfe8fHxOX/+/P379728vOSohkAgmDFjRsN5fH19zc3NMzIybt++zfrYqqqqY8eOkRQzUUne7pp47LHl7q4JPTa8lTBcBNACNTU17KERS0vLHTt2iL9kZmZWXFwcFBRUe7hobW1d56Jz8mWTVVpa2oMHD54+fZqUlHT//n0WPuXGzWWS0Lx5cxVVJjc3l+3oZW9vL/FSp06dal/2de7cWb7tuRr9/NPS0qqqqvT09GxsbCResrOz09HRkXsQDgC8+fzzz2uPH5gbN24MGjSI+2dNTQ3bfV785iCH9Uhyb0/frl27Zs2aNZzHwMBg7NixBw8ePHbsGBvjhYSEvHr1ysbGRrye9VGwuybV99hyd9eEHhveShguAmiBK1euZGZmEtE///zzzz//1M7wzz//FBYWSkx5MjY2lubgUmaT3vnz51esWBEXF8eltG7desiQIVevXlVuQSqtTHp6OhEZGhpKeYkj98fY6BvZ8zwtWrRgk9DEGRoampubFxQUyFc0AGig/Pz8iooKIqpzv4q2bdsS0YsXL+Q7OPtNr1F+fn4HDx48ceLEL7/8Qv/bw2nq1KkSGyYpHT89tiJRDz02vIUwXATQAixUW1tb115AvKysbNu2bRUVFSdPnpw5cybPFSsuLpZIOXfu3NixY2tqagYMGDB+/Pg+ffp06dKlbdu2ISEh/A8XFakMuyYrLy8vKSkxNTXlpb51a9euHRG9fv26qqpKYoH4iooKdkMdAJoMS0tLIyOjsrKy7OzsNm3aSLzKdlNk3UIDanfOMvHy8rKwsEhLS4uKiurSpQt7enDatGmKHLNR6LEBNBOGiwCarry8/MSJE0Q0d+5ctteihMuXLz98+DAoKIj/4WJycrJEyg8//FBTU7NgwQK2BDyHW3eBT4pUpn379sbGxqWlpUlJSa6uruIvPXv27NChQ5aWlvPnz1dyjetia2srEAiqq6uTkpK43dKY5ORkzGsCaGJ0dHRsbW0fPXqUkJDg4uIi8eqTJ0+orimXEmp3zjJp1qzZ+PHj9+/ff/z4cScnp7KyMg8PjzonxyoRemwAzSTn1G0A4M25c+eKiop0dHTYWnm1sZ8cr1y5kpOTo6I6sAlIL1++lEhnT1SKS0pKIqKxY8dKpKtlJqoildHR0XFzcyOi//73vxIvHT58ePXq1f/++6+SqtkIgUDQu3dvItqzZ4/ES2xRRABoYvr27UtEO3fulEhPTExk63Oy3olk6Zxl9eGHHxLR8ePH2fSW6dOnK3jARqHHBtBMGC4CaDoWqvv379+5c+c6M0yaNImIhEJhcHCwiupga2tLRHfv3r137x6XeOnSpdrh0Nramohu374tnhgcHBwYGEhEPD+zIUdlcnNzuf//9ttviWjfvn1Hjx7lEhMTE3/++WciklgcT6XYtmx79uxhS94z586d4z5/VT9QBAB8WrVqlb6+/tWrVwMCArjErKysqVOn1tTUeHp6Dh06lCVK3znLysvLy9LSMjk5OSwszMDAoPajEEqHHhtAM2G4CKDR8vPz2do2bN/kOtnb27N7mYrfTq5P3759ra2tq6urBw8e7O/vHxAQMGHCBF9f32HDhr377rviOadOnUpE69at+/jjjzds2PDVV1+5u7tPmjTJ29tbT08vOTn5/fffV3CVVOnJVJmWLVsS0ezZsydOnMhuZg8ZMmT69OkVFRV+fn4eHh7+/v4TJ07s0aNHQUGBj48PD/faOb6+vh9++GF5efmECRMGDBgwd+7cIUOGjBs3zsnJiS1UyHb9AoCmwc7ObuXKlUS0Zs0aJyenWbNmjR071snJ6e7duy1atBDfjEH6zllW+vr6H3zwARGJRKLRo0dbWFgoeFKNQo8NoKH43+oRAKTHbkYKBILc3NwGsv3000+sRbNHI2rvL8xhCyfExcVJn42JiYkRf4pGV1d3xowZJSUl3bp1I7GdoGtqapYvXy4eC62srA4ePCgSiQICAlj64cOHRXXtDV0ntu9zly5dJNLZre7t27eLJ2ZlZRGRnp6erJURiUTHjx/n1n8/cuQId8xt27aZmJhwRxAIBEuWLGHbczENfIxsrdqnT5/WmVOmz18oFLIfHLiafPjhh/n5+R4eHkSUmJjY8McIAOrC+oG9e/fWl4Hb3T4rK0s8/fjx41ZWVuLXbMOGDUtPT5d4u5Sdc30dTgNd8cWLF9kxJTa1b/hE5OuuRbz02HJ31w2/Fz02NG3Y/gUApFVTUxMbG5ucnKyvr9+rV6+OHTvWlzM3NzcuLq6goMDFxcXOzo5LLywszM/PZzOOeCN9ZcrKytLT083Nzdu0aSM+WUgoFD5+/PjJkyft27d3cnLi4S57fcrKyqKionJyclxdXdlaFx06dMjKynrz5o2RkZG6agUAKiISiVJTU+Pi4szNzV1dXevrfKTvnGUSHh4+bNgwKyurzMzM2ttCqAh6bABNg+EiAICm27t374sXLyZMmODs7Cye/ujRI2dnZ3t7+8TERHXVDQCaqilTpgQFBS1cuHDr1q3qros2QY8NTQw20gAA0HSxsbE7duyIiYk5deoUdxO9oqJi2bJlIpFo/Pjx6q0eADQ9CQkJx48fJ17WRG1i0GNDE4NfFwEANF1CQoK7u3tBQcHQoUMnTZrUsmXL5OTkgwcPxsfHW1paPnnyROIBJwAAuW3atCkmJubKlSvZ2dleXl7smT2QHnpsaGIwXAQA0AKRkZELFiyIjo4WT+zevfuhQ4dqb+QNACC3SZMmsW2ZbG1tw8PDO3XqpO4aaR/02NCUYLgIAAAAAAAAdcC+iwAAAAAAAFAHDBcBAAAAAACgDhguAgAAAAAAQB0wXAQAAAAAAIA6YLgIAAAAAAAAdcBwEQAAAAAAAOqA4SIAAAAAAADUAcNFAAAAAAAAqAOGiwAAAAAAAFAHDBcBAAAAAACgDhguAgAAAAAAQB0wXAQAAAAAAIA6YLgIAAAAAAAAdcBwEQAAAAAAAOqA4SIAAAAAAADU4f8Af3ixrMzpt0oAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Edinburgh blog post figure\n",
    "label_gen_blog= [\"Ricks et al. (2023)\", \"Zeyen et al. (2024)\", \"Xu et al. (2022)\", \"Xu et al. (2024)\"]\n",
    "\n",
    "fig2_blog = Figure(resolution = (1210, 530), fontsize = 25)\n",
    "ax = Axis(fig2_blog[1,1], \n",
    "                xticks = (1:30, vec(Array(xticks_gen_blog))), \n",
    "                xticklabelsize = 25,\n",
    "                xticklabelrotation = pi/2,\n",
    "                yticks = 0:0.2:1.4,\n",
    "                ylabel= rich(\"[tCO\", subscript(2), \"e per MWh\", subscript(\"e\"), \"]\"),\n",
    "                title = \"Reduced emissions per REC [generation]\",\n",
    "                )\n",
    "                \n",
    "p_blue = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"royalblue2\", direction=Vec2f(1));    \n",
    "elem_p_blue = [PolyElement(color = p_blue, strokecolor = :black, strokewidth = 1)]\n",
    "p_green_1 = Makie.LinePattern(width=3, tilesize=(20,20), linecolor=:white, background_color=\"olivedrab\", direction=[Vec2f(1), Vec2f(1, -1)]);    \n",
    "elem_p_green_1 = [PolyElement(color = p_green_1, strokecolor = :black, strokewidth = 1)]   \n",
    "\n",
    "pltobj1= barplot!(-Matrix(KPI_3_gen_short_blog)[1,:], color = \"navyblue\", label = label_gen_blog[1], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_gen_short_blog)[2,:], color = p_blue, label = label_gen_blog[2], strokewidth = 1)\n",
    "pltobj3= barplot!(-Matrix(KPI_3_gen_short_blog)[4,:], color = \"darkgreen\", label = label_gen_blog[3], strokewidth = 1)\n",
    "barplot!(-Matrix(KPI_3_gen_short_blog)[5,:], color = p_green_1, label = label_gen_blog[4], strokewidth = 1)\n",
    "vlines!(ax, 12.5, color = :black)\n",
    "vlines!(ax, 15.5, color = :black)\n",
    "#vlines!(ax, 17.5, color = :black)\n",
    "vlines!(ax, 27.5, color = :black)\n",
    "limits!(ax, 0, 31, -0.03, .73)\n",
    "\n",
    "#axislegend(ax, position = :lt, bgcolor = :white, framecolor = :black, labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = lines(fig2_blog[2,1], supLine(Point2f(2.2,.9), Point2f(15,.9);y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 8, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2_blog[2,1], supLine(Point2f(15.2,.9), Point2f(18.2,.9);y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 16.2, 0.48; text=\"C&I\")\n",
    "lines!(fig2_blog[2,1], supLine(Point2f(18.4,.9), Point2f(31.4,.9);y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 23.5, 0.48; text=\"Hydrogen\")\n",
    "lines!(fig2_blog[2,1], supLine(Point2f(31.6,.9), Point2f(34.5,.9);y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 32.5, 0.48; text=\"C&I\")\n",
    "# time\n",
    "lines!(fig2_blog[2,1], supLine(Point2f(2.2,.4), Point2f(18.2,.4); y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 8, -.01; text=\"Annual matching\")\n",
    "#lines!(fig2_blog[2,1], supLine(Point2f(17.4,.4), Point2f(19.2,.4); y=.1), color = :black)\n",
    "#text!(fig2_blog[2,1], 16.7, -.01; text=\"Emissions\")\n",
    "lines!(fig2_blog[2,1], supLine(Point2f(18.4,.4), Point2f(34.5,.4); y=.1), color = :black)\n",
    "text!(fig2_blog[2,1], 23, -.01; text=\"Hourly matching\")\n",
    "\n",
    "\n",
    "ga = fig2_blog[1,1] = GridLayout()\n",
    "gb = fig2_blog[2,1] = GridLayout()\n",
    "\n",
    "rowgap!(fig2_blog.layout, 3)\n",
    "rowsize!(fig2_blog.layout, 2, Fixed(65))\n",
    "\n",
    "limits!(ax2, 1.5, 35, 0, 1)\n",
    "hidespines!(ax2)\n",
    "hidedecorations!(ax2)\n",
    "\n",
    "axislegend(ax, [pltobj1, elem_p_blue, pltobj3, elem_p_green_1], label_gen_blog, position = :ct, orientation = :horizontal, labelsize=20)\n",
    "\n",
    "fig2_blog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use CairoMakie for pdf\n",
    "save(\"KPI_3_gen_blog.svg\", fig2_blog, px_per_unit = 20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Marginal emission figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>6×8 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">Column1</th><th style = \"text-align: left;\">Heeter et al. (2021)</th><th style = \"text-align: left;\">Heeter et al. (2021)_1</th><th style = \"text-align: left;\">Heeter et al. (2021)_2</th><th style = \"text-align: left;\">Heeter et al. (2021)_3</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)_1</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)_2</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Any\" style = \"text-align: left;\">Any</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">min</td><td style = \"text-align: right;\">0.252</td><td style = \"text-align: right;\">0.254</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">-0.02</td><td style = \"text-align: right;\">1.13</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: left;\">max</td><td style = \"text-align: right;\">0.415</td><td style = \"text-align: right;\">0.407</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.153</td><td style = \"text-align: right;\">1.62</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: left;\">mean</td><td style = \"text-align: right;\">0.3335</td><td style = \"text-align: right;\">0.3305</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.0665</td><td style = \"text-align: right;\">1.38</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: left;\">Solar</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.331</td><td style = \"text-align: right;\">0.362</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: left;\">Wind</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.354</td><td style = \"text-align: right;\">0.349</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.06</td><td style = \"text-align: right;\">1.4</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: left;\">Solar +Wind</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.13</td><td style = \"text-align: right;\">0.7</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccc}\n",
       "\t& Column1 & Heeter et al. (2021) & Heeter et al. (2021)\\_1 & Heeter et al. (2021)\\_2 & \\\\\n",
       "\t\\hline\n",
       "\t& Any & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & min & 0.252 & 0.254 & 0.0 & $\\dots$ \\\\\n",
       "\t2 & max & 0.415 & 0.407 & 0.0 & $\\dots$ \\\\\n",
       "\t3 & mean & 0.3335 & 0.3305 & 0.0 & $\\dots$ \\\\\n",
       "\t4 & Solar & 0.0 & 0.0 & 0.331 & $\\dots$ \\\\\n",
       "\t5 & Wind & 0.0 & 0.0 & 0.354 & $\\dots$ \\\\\n",
       "\t6 & Solar +Wind & 0.0 & 0.0 & 0.0 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m6×8 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m Column1     \u001b[0m\u001b[1m Heeter et al. (2021) \u001b[0m\u001b[1m Heeter et al. (2021)_1 \u001b[0m\u001b[1m Heeter et al\u001b[0m ⋯\n",
       "     │\u001b[90m Any         \u001b[0m\u001b[90m Float64              \u001b[0m\u001b[90m Float64                \u001b[0m\u001b[90m Float64     \u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ min                        0.252                   0.254                ⋯\n",
       "   2 │ max                        0.415                   0.407\n",
       "   3 │ mean                       0.3335                  0.3305\n",
       "   4 │ Solar                      0.0                     0.0\n",
       "   5 │ Wind                       0.0                     0.0                  ⋯\n",
       "   6 │ Solar +Wind                0.0                     0.0\n",
       "\u001b[36m                                                               5 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "KPI_3_marg = CSV.read(\"marginal.csv\", DataFrame; header=1, footerskip=1)\n",
    "# Extract xticks\n",
    "xticks_marg = CSV.read(\"marginal.csv\", DataFrame; header=1, skipto=8)\n",
    "xticks_marg = xticks_marg[:, 2:end]\n",
    "\n",
    "# replace missing values with 0\n",
    "mapcols!(col -> replace(col, missing => 0), KPI_3_marg)\n",
    "\n",
    "# reorder columns\n",
    "#KPIs_cap = KPIs_cap[:, vcat([1:2...], [20:36...], [3:19...], [37:42...])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>1×7 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">Heeter et al. (2021)</th><th style = \"text-align: left;\">Heeter et al. (2021)_1</th><th style = \"text-align: left;\">Heeter et al. (2021)_2</th><th style = \"text-align: left;\">Heeter et al. (2021)_3</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)_1</th><th style = \"text-align: left;\">Ruhnau and Schiele (2023)_2</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"String15\" style = \"text-align: left;\">String15</th><th title = \"String15\" style = \"text-align: left;\">String15</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th><th title = \"String7\" style = \"text-align: left;\">String7</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">2020 PPAs</td><td style = \"text-align: left;\">2020 PPAs</td><td style = \"text-align: left;\">Annual</td><td style = \"text-align: left;\">Hourly</td><td style = \"text-align: left;\">Island</td><td style = \"text-align: left;\">Annual</td><td style = \"text-align: left;\">Hourly</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccc}\n",
       "\t& Heeter et al. (2021) & Heeter et al. (2021)\\_1 & Heeter et al. (2021)\\_2 & Heeter et al. (2021)\\_3 & \\\\\n",
       "\t\\hline\n",
       "\t& String15 & String15 & String7 & String7 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 2020 PPAs & 2020 PPAs & Annual & Hourly & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m1×7 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m Heeter et al. (2021) \u001b[0m\u001b[1m Heeter et al. (2021)_1 \u001b[0m\u001b[1m Heeter et al. (2021)_2 \u001b[0m\u001b[1m H\u001b[0m ⋯\n",
       "     │\u001b[90m String15             \u001b[0m\u001b[90m String15               \u001b[0m\u001b[90m String7                \u001b[0m\u001b[90m S\u001b[0m ⋯\n",
       "─────┼──────────────────────────────────────────────────────────────────────────\n",
       "   1 │ 2020 PPAs             2020 PPAs               Annual                  H ⋯\n",
       "\u001b[36m                                                               4 columns omitted\u001b[0m"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xticks_marg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4 = Figure(resolution = (900, 400), fontsize = 20, title = \"Reduced emissions [generation]\")\n",
    "ax = Axis(fig4[1,1:2], \n",
    "                xticks = (1:3, [\"(ii) PPAs\", \"(iii) Annual\", \"(iii) Hourly\"]), \n",
    "                ylabel= rich(\"[tCO\", subscript(2), \"e per MWh\", subscript(\"e\"), \"]\"),\n",
    "                title = \"Heeter et al. (2021)\"\n",
    "                )\n",
    "\n",
    "hlines!(ax, 0.727, color = :brown, linestyle = :dash, label=\"Lignite\", linewidth=2) \n",
    "hlines!(ax, 0.404, color = :gray, linestyle = :dash, label=\"Natural gas\", linewidth=2) \n",
    "errorbars!(ax, [.85, 1.15], Matrix(KPI_3_marg)[3,2:3], (Matrix(KPI_3_marg)[2,2:3] -Matrix(KPI_3_marg)[1,2:3])/2, \n",
    "            color = [:gold, :skyblue3], whiskerwidth = 18, linewidth=4,\n",
    ")\n",
    "scatter!(2:3, Float32.(Matrix(KPI_3_marg)[4,4:5]), marker='O', markersize=25, color=:gold, label=\"PV\", strokewidth=2, strokecolor=:gold)\n",
    "scatter!(2:3, Float32.(Matrix(KPI_3_marg)[5,4:5]), marker='X', markersize=22, color=:skyblue3, label=\"Wind\", strokewidth=2, strokecolor=:skyblue3)\n",
    "limits!(ax, 0.5, 3.5, -0.1, 1.7)\n",
    "axislegend(ax, position = :rt,  labelsize=20)\n",
    "\n",
    "ax2, pltobj2 = errorbars(fig4[1,3], [1, 2], Matrix(KPI_3_marg)[3,7:8], (Matrix(KPI_3_marg)[2,7:8] -Matrix(KPI_3_marg)[1,7:8])/2, \n",
    "                            color = :skyblue3, whiskerwidth = 18, linewidth=4,\n",
    ")\n",
    "\n",
    "hlines!(ax2, 0.727, color = :brown, linestyle = :dash, linewidth=2) \n",
    "hlines!(ax2, 0.404, color = :gray, linestyle = :dash, linewidth=2) \n",
    "scatter!(1:2, Float32.(Matrix(KPI_3_marg)[6,7:8]), marker=:cross, markersize=25, strokewidth = 2, \n",
    "            color=:gold, strokecolor=:skyblue3, label=\"PV+Wind\")\n",
    "ax2.title = \"Ruhnau & Schiele (2023)\"\n",
    "ax2.xticks = (1:2, [\"Annual\", \"Hourly\"])\n",
    "ax2.yticklabelsvisible = :false\n",
    "limits!(ax2, 0.5, 2.5, -0.1, 1.7)\n",
    "axislegend(ax2, position = :lt, labelsize=20)\n",
    "\n",
    "ax3 = Axis(fig4[2,1]) \n",
    "text!(fig4[2,1], .34, .2; text=\"(100 MW)\")\n",
    "limits!(ax3, 0, 2, 0, 2)\n",
    "hidespines!(ax3)\n",
    "hidedecorations!(ax3)\n",
    "rowgap!(fig4.layout, 3)\n",
    "rowsize!(fig4.layout, 2, Fixed(22))\n",
    "\n",
    "fig4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "save(\"KPI_3_marg.png\", fig4, px_per_unit = 15);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.7.3",
   "language": "julia",
   "name": "julia-1.7"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.7.3"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
