notebooks/2_analysis_by_fuel_and_sector.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Analysis by fuels and sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyam\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pyam.IamDataFrame(\"data/ngfs_data_analysis.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downselect to one model and global timeseries data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_remind = df.filter(model=\"REMIND-MAgPIE 2.1-4.2\", region=\"World\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_remind.scenario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scenarios = [\n",
    "    \"Current Policies \",\n",
    "    \"Net Zero 2050\",\n",
    "    \"Divergent Net Zero\",\n",
    "]\n",
    "\n",
    "df_remind.filter(scenario=scenarios, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_remind.filter(variable=\"Primary Energy|*\").variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "variables = [\n",
    "    \"Primary Energy|Biomass\",\n",
    "    \"Primary Energy|Oil\",\n",
    "    \"Primary Energy|Coal\",\n",
    "    \"Primary Energy|Gas\",\n",
    "    \"Primary Energy|Nuclear\",\n",
    "    \"Primary Energy|Non-Biomass Renewables\",\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1, 3, figsize=(10, 5), sharex=True, sharey=True)\n",
    "\n",
    "for i, s in enumerate(df_remind.scenario):\n",
    "    _df = df_remind.filter(scenario=s, variable=variables)\\\n",
    "        .plot.bar(ax=ax[i], stacked=True, legend=True if i == 2 else False)\n",
    "    ax[i].set_title(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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