LSEG_SFI_Climate_CodeBook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LSEG's SFI Climate Data in Workspace: A use-case evaluating public companies' Climate track record using Python\n",
    "\n",
    "In this article, we will investigate Public Companies' Climate promises and whether they are on track to meet them. The data needed for such an investigation is not onboarded on [LSEG's Data Platform](https://developers.lseg.com/en/api-catalog/refinitiv-data-platform/refinitiv-data-platform-apis) yet; but, thankfully, it is on both (i) on LSEG's Sustainable Finance Investing (SFI) Snowflake and (ii) on Workspace. Thanks to the latter, we can call for this data on CodeBook. For more information on the Climate data we are collecting and the methodology, please refer to the article \"LSEG's SFI Snowflake Datawarehouse: A use-case evaluating public companies' Climate track record using Python and SQL\".\n",
    "\n",
    "LSEG usually collects data from a number of vendors, but when it comes to climate data, we rely on our analysts to retrieve the information directly from companies disclosures. The most exciting data onboarded has, recently, related to ESG and Climate topics. In this article, we will directly source the data we are after using the [Data Item Browser](https://developers.refinitiv.com/en/video-catalog/data-item-browser) and [CodeBook](https://developers.lseg.com/en/video-catalog/from-developer-articles-to-codebook).\n",
    "\n",
    "## Importing libraries and Authentifying ourselves to LSEG's services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re # We'll use the `re` library to seperate numbers from words in strings.\n",
    "import pandas as pd # this library is great for dataframe manipulations.\n",
    "import plotly.graph_objects as go # `plotly` and its modules are useful for us to plot graphs.\n",
    "import numpy as np # `numpy` in this case will be useful for us to plot graphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<lseg.data.session.Definition object at 0x1a9c5f5b850 {name='workspace'}>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import lseg.data as ld\n",
    "ld.open_session()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calling and tidying our data\n",
    "\n",
    "For more information on the reason why we are collecting this data, please refer to the article \"LSEG's SFI Snowflake Datawarehouse: A use-case evaluating public companies' Climate track record using Python and SQL\". With that said, it will be evident, during the article, why we collected this data.\n",
    "\n",
    "First, let's put in place the primary parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "RIC = \"MSFT.O\" # SHEL.L, AAPL.O\n",
    "scopeOfInterest = \"1\" # choice between \"1\", \"2\", \"3\", \"1 and 2\" or \"1, 2 and 3\"\n",
    "setOfInterest = 1 # choice from 1 to 5\n",
    "termOfInterest = \"LT\" # choice between \"ST\" and \"LT\"\n",
    "sourceOfInterest = \"LSEG\" # choice between \"LSEG\" and \"CDP\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need extra parameters for the logic we'll create below, I define them here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "scopeOfInterestFirstNumber = int(re.search(r'\\d+', scopeOfInterest).group())\n",
    "\n",
    "if termOfInterest == \"ST\":\n",
    "    termNotOfInterest = \"LT\"\n",
    "else:\n",
    "    termNotOfInterest = \"ST\"\n",
    "\n",
    "if sourceOfInterest == \"LSEG\":\n",
    "    _sourceOfInterest = \"\"\n",
    "elif sourceOfInterest == \"CDP\":\n",
    "    _sourceOfInterest = sourceOfInterest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can create the list of fields we're after from LSEG's services:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['TR.CO2EquivalentEmissionsTotalMarketbased', 'TR.CO2EmissionTotal', 'TR.CO2DirectScope1', 'TR.CO2IndirectScope1', 'TR.CO2DirectScope2', 'TR.CO2IndirectScope2', 'TR.CO2DirectScope3', 'TR.CO2IndirectScope3', 'TR.CO2EmissionTotal', 'TR.TotalCO2EquivalentEmissionsScope1and2and3', 'TR.TotalCO2EquivalentEmissionScope1and2and3Marketbased', 'TR.LTGHGEmissionPercentageReductionTargetedSet1', 'TR.LTPercentageofGHGEmissionCoveredbyTargetSet1', 'TR.LTGHGEmissionScopeSet1', 'TR.LTGHGEmissionBaseYearSet1', 'TR.LTGHGEmissionTargetYearSet1']\n"
     ]
    }
   ],
   "source": [
    "lstOfFlds = [\"TR.CO2EquivalentEmissionsTotalMarketbased\", \"TR.CO2EmissionTotal\"]\n",
    "\n",
    "for i in range(1,4):\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}CO2DirectScope{i}\")\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}CO2IndirectScope{i}\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}CO2EmissionTotal\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}TotalCO2EquivalentEmissionsScope1and2and3\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}TotalCO2EquivalentEmissionScope1and2and3Marketbased\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionPercentageReductionTargetedSet{setOfInterest}\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}PercentageofGHGEmissionCoveredbyTargetSet{setOfInterest}\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionScopeSet{setOfInterest}\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionBaseYearSet{setOfInterest}\")\n",
    "lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionTargetYearSet{setOfInterest}\")\n",
    "print(lstOfFlds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(lstOfFlds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we're cooking:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0 = ld.get_history(\n",
    "    universe=[RIC],\n",
    "    fields=lstOfFlds,\n",
    "    start=\"1990-01-01\",\n",
    "    end=\"2025-01-01\",\n",
    "    header_type=ld.HeaderType.NAME_AND_TITLE,\n",
    ").dropna(how='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>MSFT.O</th>\n",
       "      <th>TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based</th>\n",
       "      <th>TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total</th>\n",
       "      <th>TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1</th>\n",
       "      <th>TR.CO2INDIRECTSCOPE2|CO2 Equivalent Emissions Indirect, Scope 2</th>\n",
       "      <th>TR.CO2INDIRECTSCOPE3|CO2 Equivalent Emissions Indirect, Scope 3</th>\n",
       "      <th>TR.TOTALCO2EQUIVALENTEMISSIONSSCOPE1AND2AND3|Total CO2 Equivalent Emissions Scope 1, 2 and 3</th>\n",
       "      <th>TR.TOTALCO2EQUIVALENTEMISSIONSCOPE1AND2AND3MARKETBASED|Total CO2 Equivalent Emission Scope 1, 2 and 3 Market-based</th>\n",
       "      <th>TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1</th>\n",
       "      <th>TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>574219</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>12227000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>553109</td>\n",
       "      <td>5134371</td>\n",
       "      <td>123704</td>\n",
       "      <td>5010667</td>\n",
       "      <td>13839000</td>\n",
       "      <td>18973371</td>\n",
       "      <td>14392000</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-30</th>\n",
       "      <td>427442</td>\n",
       "      <td>6520663</td>\n",
       "      <td>139413</td>\n",
       "      <td>6381250</td>\n",
       "      <td>16111000</td>\n",
       "      <td>22631663</td>\n",
       "      <td>16538000</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MSFT.O      TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based  \\\n",
       "Date                                                                                                \n",
       "2020-06-30                                             574219                                       \n",
       "2021-06-30                                             553109                                       \n",
       "2022-06-30                                             427442                                       \n",
       "\n",
       "MSFT.O      TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total  \\\n",
       "Date                                                             \n",
       "2020-06-30                                               <NA>    \n",
       "2021-06-30                                            5134371    \n",
       "2022-06-30                                            6520663    \n",
       "\n",
       "MSFT.O      TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1  \\\n",
       "Date                                                                      \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                             123704             \n",
       "2022-06-30                                             139413             \n",
       "\n",
       "MSFT.O      TR.CO2INDIRECTSCOPE2|CO2 Equivalent Emissions Indirect, Scope 2  \\\n",
       "Date                                                                          \n",
       "2020-06-30                                               <NA>                 \n",
       "2021-06-30                                            5010667                 \n",
       "2022-06-30                                            6381250                 \n",
       "\n",
       "MSFT.O      TR.CO2INDIRECTSCOPE3|CO2 Equivalent Emissions Indirect, Scope 3  \\\n",
       "Date                                                                          \n",
       "2020-06-30                                               <NA>                 \n",
       "2021-06-30                                           13839000                 \n",
       "2022-06-30                                           16111000                 \n",
       "\n",
       "MSFT.O      TR.TOTALCO2EQUIVALENTEMISSIONSSCOPE1AND2AND3|Total CO2 Equivalent Emissions Scope 1, 2 and 3  \\\n",
       "Date                                                                                                       \n",
       "2020-06-30                                               <NA>                                              \n",
       "2021-06-30                                           18973371                                              \n",
       "2022-06-30                                           22631663                                              \n",
       "\n",
       "MSFT.O      TR.TOTALCO2EQUIVALENTEMISSIONSCOPE1AND2AND3MARKETBASED|Total CO2 Equivalent Emission Scope 1, 2 and 3 Market-based  \\\n",
       "Date                                                                                                                             \n",
       "2020-06-30                                           12227000                                                                    \n",
       "2021-06-30                                           14392000                                                                    \n",
       "2022-06-30                                           16538000                                                                    \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1  \\\n",
       "Date                                                                                                             \n",
       "2020-06-30                                               <NA>                                                    \n",
       "2021-06-30                                                 75                                                    \n",
       "2022-06-30                                                 75                                                    \n",
       "\n",
       "MSFT.O      TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1  \\\n",
       "Date                                                                                                               \n",
       "2020-06-30                                               <NA>                                                      \n",
       "2021-06-30                                                100                                                      \n",
       "2022-06-30                                                100                                                      \n",
       "\n",
       "MSFT.O     TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1  \\\n",
       "Date                                                              \n",
       "2020-06-30                                                        \n",
       "2021-06-30                                      Scope 1 and 2     \n",
       "2022-06-30                                      Scope 1 and 2     \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1  \\\n",
       "Date                                                                      \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                               2013             \n",
       "2022-06-30                                               2013             \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1  \n",
       "Date                                                                         \n",
       "2020-06-30                                               <NA>                \n",
       "2021-06-30                                               2045                \n",
       "2022-06-30                                               2045                "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.tail(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As it happens, \"CO2 Equivalent Emissions Total\" is \"CO2 Equivalent Emissions Direct, Scope 1\"; I don't want to overwright the column names, so let's just add a new one:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "if scopeOfInterest == \"1 and 2\":\n",
    "    df0[f\"TR.{sourceOfInterest}CO2EQUIVALENTEMISSIONTOTAL|CO2 Equivalent Emissions Direct, Scope 1 and 2\"] = df0[f\"TR.{sourceOfInterest}CO2EQUIVALENTEMISSIONTOTAL|CO2 Equivalent Emissions Total\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based', 'TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total', 'TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1', 'TR.CO2INDIRECTSCOPE2|CO2 Equivalent Emissions Indirect, Scope 2', 'TR.CO2INDIRECTSCOPE3|CO2 Equivalent Emissions Indirect, Scope 3', 'TR.TOTALCO2EQUIVALENTEMISSIONSSCOPE1AND2AND3|Total CO2 Equivalent Emissions Scope 1, 2 and 3', 'TR.TOTALCO2EQUIVALENTEMISSIONSCOPE1AND2AND3MARKETBASED|Total CO2 Equivalent Emission Scope 1, 2 and 3 Market-based', 'TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1', 'TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1', 'TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1', 'TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1', 'TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1']\n"
     ]
    }
   ],
   "source": [
    "print(list(df0.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you see, there are several Scopes and Sets we may be interested in. Scope can be \"1\", \"2\", \"1+2\", \"3\" or \"1+2+3\". Scope can be anything from 1 to 5 (inclusive)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based',\n",
       " 'TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total',\n",
       " 'TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1',\n",
       " 'TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1',\n",
       " 'TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1',\n",
       " 'TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1',\n",
       " 'TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1',\n",
       " 'TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1']"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "if sourceOfInterest == \"LSEG\":\n",
    "    cols = [\n",
    "        col for col in df0.columns\n",
    "            if 'CO2EQUIVALENTEMISSIONSTOTALMARKETBASED' in col\n",
    "            or \"CO2EMISSIONTOTAL\" in col\n",
    "            or (\n",
    "                'CDP' not in col # not in\n",
    "                and f'Scope {scopeOfInterest}, ' not in col\n",
    "                and f'Scope {scopeOfInterest} and ' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber+1}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber+2}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber-1}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber-2}' not in col\n",
    "                and f'{termNotOfInterest}GHGEMISSION' not in col\n",
    "                and f'{termNotOfInterest}PERCENTAGE' not in col\n",
    "                and (\n",
    "                    f'Scope {scopeOfInterest}' in col\n",
    "                    or f'Set{setOfInterest}' in col))]\n",
    "\n",
    "if sourceOfInterest == \"CDP\":  # choice of \"LSEG or \"CDP\"\n",
    "    cols = [\n",
    "        col for col in df0.columns\n",
    "            if 'CO2EQUIVALENTEMISSIONSTOTALMARKETBASED' in col\n",
    "            or \"CO2EMISSIONTOTAL\" in col\n",
    "            or (\n",
    "                'CDP' in col # in\n",
    "                and f'Scope {scopeOfInterest}, ' not in col\n",
    "                and f'Scope {scopeOfInterest} and ' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber+1}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber+2}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber-1}' not in col\n",
    "                and f'Scope {scopeOfInterestFirstNumber-2}' not in col\n",
    "                and f'{termNotOfInterest}GHGEMISSION' not in col\n",
    "                and f'{termNotOfInterest}PERCENTAGE' not in col\n",
    "                and (\n",
    "                    f'Scope {scopeOfInterest}' in col\n",
    "                    or f'Set{setOfInterest}' in col))]\n",
    "\n",
    "print(len(cols))\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>MSFT.O</th>\n",
       "      <th>TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based</th>\n",
       "      <th>TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total</th>\n",
       "      <th>TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1</th>\n",
       "      <th>TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1</th>\n",
       "      <th>TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>4447016</td>\n",
       "      <td>118100</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>574219</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>553109</td>\n",
       "      <td>5134371</td>\n",
       "      <td>123704</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-30</th>\n",
       "      <td>427442</td>\n",
       "      <td>6520663</td>\n",
       "      <td>139413</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MSFT.O      TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based  \\\n",
       "Date                                                                                                \n",
       "2019-06-30                                               <NA>                                       \n",
       "2020-06-30                                               <NA>                                       \n",
       "2020-06-30                                             574219                                       \n",
       "2021-06-30                                             553109                                       \n",
       "2022-06-30                                             427442                                       \n",
       "\n",
       "MSFT.O      TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total  \\\n",
       "Date                                                             \n",
       "2019-06-30                                               <NA>    \n",
       "2020-06-30                                            4447016    \n",
       "2020-06-30                                               <NA>    \n",
       "2021-06-30                                            5134371    \n",
       "2022-06-30                                            6520663    \n",
       "\n",
       "MSFT.O      TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1  \\\n",
       "Date                                                                      \n",
       "2019-06-30                                               <NA>             \n",
       "2020-06-30                                             118100             \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                             123704             \n",
       "2022-06-30                                             139413             \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1  \\\n",
       "Date                                                                                                             \n",
       "2019-06-30                                                 75                                                    \n",
       "2020-06-30                                                 75                                                    \n",
       "2020-06-30                                               <NA>                                                    \n",
       "2021-06-30                                                 75                                                    \n",
       "2022-06-30                                                 75                                                    \n",
       "\n",
       "MSFT.O      TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1  \\\n",
       "Date                                                                                                               \n",
       "2019-06-30                                                100                                                      \n",
       "2020-06-30                                                100                                                      \n",
       "2020-06-30                                               <NA>                                                      \n",
       "2021-06-30                                                100                                                      \n",
       "2022-06-30                                                100                                                      \n",
       "\n",
       "MSFT.O     TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1  \\\n",
       "Date                                                              \n",
       "2019-06-30                                      Scope 1 and 2     \n",
       "2020-06-30                                      Scope 1 and 2     \n",
       "2020-06-30                                                        \n",
       "2021-06-30                                      Scope 1 and 2     \n",
       "2022-06-30                                      Scope 1 and 2     \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1  \\\n",
       "Date                                                                      \n",
       "2019-06-30                                               2013             \n",
       "2020-06-30                                               2013             \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                               2013             \n",
       "2022-06-30                                               2013             \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1  \n",
       "Date                                                                         \n",
       "2019-06-30                                               2045                \n",
       "2020-06-30                                               2045                \n",
       "2020-06-30                                               <NA>                \n",
       "2021-06-30                                               2045                \n",
       "2022-06-30                                               2045                "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df0[cols]\n",
    "df1.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>MSFT.O</th>\n",
       "      <th>TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based</th>\n",
       "      <th>TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total</th>\n",
       "      <th>TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1</th>\n",
       "      <th>TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1</th>\n",
       "      <th>TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1</th>\n",
       "      <th>TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>574219</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>553109</td>\n",
       "      <td>5134371</td>\n",
       "      <td>123704</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-30</th>\n",
       "      <td>427442</td>\n",
       "      <td>6520663</td>\n",
       "      <td>139413</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2</td>\n",
       "      <td>2013</td>\n",
       "      <td>2045</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MSFT.O      TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED|CO2 Equivalent Emissions Total Market-based  \\\n",
       "Date                                                                                                \n",
       "2020-06-30                                             574219                                       \n",
       "2021-06-30                                             553109                                       \n",
       "2022-06-30                                             427442                                       \n",
       "\n",
       "MSFT.O      TR.CO2EMISSIONTOTAL|CO2 Equivalent Emissions Total  \\\n",
       "Date                                                             \n",
       "2020-06-30                                               <NA>    \n",
       "2021-06-30                                            5134371    \n",
       "2022-06-30                                            6520663    \n",
       "\n",
       "MSFT.O      TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1  \\\n",
       "Date                                                                      \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                             123704             \n",
       "2022-06-30                                             139413             \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|LT GHG Emission Percentage Reduction Targeted Set1  \\\n",
       "Date                                                                                                             \n",
       "2020-06-30                                               <NA>                                                    \n",
       "2021-06-30                                                 75                                                    \n",
       "2022-06-30                                                 75                                                    \n",
       "\n",
       "MSFT.O      TR.LTPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|LT Percentage of GHG Emission Covered by Target Set1  \\\n",
       "Date                                                                                                               \n",
       "2020-06-30                                               <NA>                                                      \n",
       "2021-06-30                                                100                                                      \n",
       "2022-06-30                                                100                                                      \n",
       "\n",
       "MSFT.O     TR.LTGHGEMISSIONSCOPESET1|LT GHG Emission Scope Set1  \\\n",
       "Date                                                              \n",
       "2020-06-30                                               <NA>     \n",
       "2021-06-30                                      Scope 1 and 2     \n",
       "2022-06-30                                      Scope 1 and 2     \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONBASEYEARSET1|LT GHG Emission Base Year Set1  \\\n",
       "Date                                                                      \n",
       "2020-06-30                                               <NA>             \n",
       "2021-06-30                                               2013             \n",
       "2022-06-30                                               2013             \n",
       "\n",
       "MSFT.O      TR.LTGHGEMISSIONTARGETYEARSET1|LT GHG Emission Target Year Set1  \n",
       "Date                                                                         \n",
       "2020-06-30                                               <NA>                \n",
       "2021-06-30                                               2045                \n",
       "2022-06-30                                               2045                "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df1.replace('', pd._libs.missing.NA)\n",
    "df3 = df2.dropna(how='all')\n",
    "df3.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'GHGEmissionCoveredbyTarget' figures are above 80%. The higher this figure, the more reliable the results.\n",
      "In this case, we consider them to be high enough to be reliable.\n"
     ]
    }
   ],
   "source": [
    "df4 = df3.filter(like='PERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET')\n",
    "if df4.apply(pd.to_numeric, errors='coerce').dropna().gt(80).all().all():\n",
    "    print(\"'GHGEmissionCoveredbyTarget' figures are above 80%. The higher this figure, the more reliable the results.\")\n",
    "    print(\"In this case, we consider them to be high enough to be reliable.\")\n",
    "else:\n",
    "    print(\"Be weary of the fact that 'GHGEmissionCoveredbyTarget' is below 80%. The lower this figure, the less reliable the results.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df5 = df3.copy()\n",
    "df5.index = [np.int64(z) for z in pd.to_datetime(df5.index, errors='coerce').year.astype(object)] # keep only the years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "baseEmissionYear = 2013 & targetEmissionReductionYear = 2045\n",
      "baseEmission = 1355480 & targetReductionEmission = 1016610.0 & targetEmission = 338870.0\n"
     ]
    }
   ],
   "source": [
    "baseEmissionYear = int(df3.filter(like='GHGEMISSIONBASEYEARSET').iloc[-1].values[0])\n",
    "targetEmissionReductionYear = int(df3.filter(like='GHGEMISSIONTARGETYEARSET').iloc[-1].values[0])\n",
    "baseEmission = df3[df3.index.year == baseEmissionYear].filter(like='CO2EMISSIONTOTAL').values[0][0]\n",
    "targetReductionEmission = baseEmission * ((df3.filter(like='GHGEMISSIONPERCENTAGEREDUCTIONTARGETED').dropna().iloc[-1] / 100).iloc[0] * (df3.filter(like='PERCENTAGEOFGHGEMISSIONCOVEREDBYTARGET').dropna().iloc[-1] / 100).iloc[0])\n",
    "targetEmission = baseEmission - targetReductionEmission\n",
    "print(f\"baseEmissionYear = {baseEmissionYear} & targetEmissionReductionYear = {targetEmissionReductionYear}\")\n",
    "print(f\"baseEmission = {baseEmission} & targetReductionEmission = {targetReductionEmission} & targetEmission = {targetEmission}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
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        },
        "xaxis": {
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          "text": "Year"
         }
        },
        "yaxis": {
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   "source": [
    "start_year = df3.T.filter(like=str(baseEmissionYear)).columns.values[0]\n",
    "end_year = np.datetime64(\n",
    "    f\"{targetEmissionReductionYear}-{str(start_year)[5:7]}-{str(start_year)[8:10]}\")\n",
    "\n",
    "start_year = np.datetime64(start_year, 'ns')\n",
    "end_year = np.datetime64(end_year, 'ns')\n",
    "start_value = baseEmission\n",
    "end_value = targetEmission\n",
    "\n",
    "# Calculate the decay constant 'k' for exponential decay\n",
    "# We use the formula for exponential decay: y(t) = y0 * exp(-k * (t - t0))\n",
    "# Solve for 'k' using y(t) at the end point\n",
    "# time_difference_years = (end_year - start_year).astype('timedelta64[Y]').astype(float)\n",
    "# k = -np.log(end_value / start_value) / time_difference_years\n",
    "\n",
    "if end_value / start_value == 0:\n",
    "    k = -np.log(0.01) / (int(str(end_year)[:4]) - int(str(start_year)[:4]))  # Use a small value instead of zero to avoid log(0) issue\n",
    "else:\n",
    "    k = -np.log(end_value / start_value) / ((end_year - start_year).astype('timedelta64[Y]').astype(float))\n",
    "\n",
    "# Generate years and corresponding values using exponential decay\n",
    "years = np.arange(\n",
    "    start_year.astype('datetime64[Y]').astype(int) + 1970,\n",
    "    end_year.astype('datetime64[Y]').astype(int) + 1971)\n",
    "values = start_value * np.exp(\n",
    "    -k * (years - (start_year.astype('datetime64[Y]').astype(int) + 1970)))\n",
    "\n",
    "decayDf = pd.DataFrame(data=values, index=years, columns=[f'Exponential Decay to target of {int(targetEmission)}'])\n",
    "df6 = pd.concat([df5, decayDf])\n",
    "\n",
    "# Create the plot\n",
    "fig = go.Figure()\n",
    "\n",
    "# Add the exponential decay line trace\n",
    "fig.add_trace(\n",
    "    go.Scatter(\n",
    "        x=df6.index, y=df6[f'Exponential Decay to target of {int(targetEmission)}'], mode='lines',\n",
    "        name=f'Exponential Decay to target of {int(targetEmission)}'))\n",
    "\n",
    "# Set plot title and labels\n",
    "fig.update_layout(\n",
    "    title=f\"{RIC} GHG Emissions (Base in {baseEmissionYear} and Target in {targetEmissionReductionYear}) in CO2 Tons\",\n",
    "    xaxis_title=\"Year\",\n",
    "    yaxis_title=\"CO2 Tons\",\n",
    "    template=\"plotly_dark\"  # Optional: You can use different templates, such as 'plotly', 'ggplot2', etc.\n",
    ")\n",
    "\n",
    "# Add the dots representing the actual CO2 data from df3\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df6.index, \n",
    "    y=df6[df6.filter(like=\"CO2EMISSIONTOTAL\").columns[0]],\n",
    "    mode='lines+markers', \n",
    "    name='CO2 Equivalents Emission Total',\n",
    "    marker=dict(color='red', size=8)  # Customize the dot color and size\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df6.index, \n",
    "    y=df6[df6.filter(like=\"TR.CO2EQUIVALENTEMISSIONSTOTALMARKETBASED\").columns[0]],\n",
    "    mode='lines+markers', \n",
    "    name='CO2 Equivalent Emissions Total Market-based',\n",
    "    marker=dict(color='grey', size=8)  # Customize the dot color and size\n",
    "))\n",
    "\n",
    "# Show the plot\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "ld.close_session()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All together now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lseg.data as ld\n",
    "\n",
    "def GHGEmissionsBaseVsTargetUsingLSEGWorkspace(\n",
    "    RIC = \"MSFT.O\",\n",
    "    scope = \"1\", # choice between \"1\", \"2\", \"3\", \"1 and 2\" or \"1, 2 and 3\"\n",
    "    set = 1, # choice from 1 to 5\n",
    "    term = \"LT\", # choice between \"ST\" and \"LT\"\n",
    "    source = \"LSEG\", # choice between \"LSEG\" and \"CDP\"\n",
    "    suppressWarnings=True\n",
    "    ):\n",
    "\n",
    "    import warnings # This will be useful to warn users if the Scope they're after is not covered.\n",
    "    import re # We'll use the `re` library to seperate numbers from words in strings.\n",
    "    import pandas as pd # this library is great for dataframe manipulations.\n",
    "    import plotly.graph_objects as go # `plotly` and its modules are useful for us to plot graphs.\n",
    "    import numpy as np # `numpy` in this case will be useful for us to plot graphs.\n",
    "    from datetime import datetime # this is useful for us to collect data from LSEG up to today.\n",
    "    \n",
    "    # # # Calling and tidying our data\n",
    "    # For more information on the reason why we are collecting this data, please refer to the article \"LSEG's SFI Snowflake Datawarehouse: A use-case evaluating public companies' Climate track record using Python and SQL\". With that said, it will be evident, during the article, why we collected this data.\n",
    "    # First, let's put in place the primary parameters:\n",
    "\n",
    "    scopeOfInterest = scope\n",
    "    setOfInterest = set\n",
    "    termOfInterest = term\n",
    "    sourceOfInterest = source\n",
    "\n",
    "    # # We need extra parameters for the logic we'll create below, I define them here:\n",
    "\n",
    "    scopeOfInterestFirstNumber = int(re.search(r'\\d+', scopeOfInterest).group())\n",
    "\n",
    "    if termOfInterest == \"ST\":\n",
    "        termNotOfInterest = \"LT\"\n",
    "    else:\n",
    "        termNotOfInterest = \"ST\"\n",
    "\n",
    "    if sourceOfInterest == \"LSEG\":\n",
    "        _sourceOfInterest = \"\"\n",
    "        __sourceOfInterest = _sourceOfInterest\n",
    "    elif sourceOfInterest == \"CDP\":\n",
    "        _sourceOfInterest = sourceOfInterest\n",
    "        __sourceOfInterest = _sourceOfInterest + \" \"\n",
    "\n",
    "    # # Now, we can create the list of fields we're after from LSEG's services:\n",
    "\n",
    "    lstOfFlds = []\n",
    "\n",
    "    def testBaseYearData(RIC, testField, _sourceOfInterest, termOfInterest, setOfInterest):\n",
    "        dfTestBaseYear = ld.get_data(\n",
    "            universe=[RIC],\n",
    "            fields=[f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionBaseYearSet{setOfInterest}\"])\n",
    "        valueTestBaseYear = dfTestBaseYear.values[0][1]\n",
    "        dfTestBaseYearData = ld.get_history(\n",
    "            universe=[RIC],\n",
    "            fields=[testField],\n",
    "            start=\"1990-01-01\",\n",
    "            end=datetime.now().strftime(\"%Y-%m-%d\"))\n",
    "        try:\n",
    "            valueTestBaseYearData = dfTestBaseYearData[\n",
    "                dfTestBaseYearData.index.year == int(valueTestBaseYear)].values[0][0]\n",
    "        except:\n",
    "            warnings.warn(\n",
    "                f\"No results returned for `ld.get_history(universe=['{RIC}'], fields=['{testField}'], start='{valueTestBaseYear}-01-01', end='{valueTestBaseYear}-12-31')`. This may be because `ld.get_data(universe=[{RIC}], fields=['TR.{_sourceOfInterest}{termOfInterest}GHGEmissionBaseYearSet{setOfInterest}'])` returned {str(dfTestBaseYearData)}\")\n",
    "        dfTestScope = ld.get_data(\n",
    "            universe=[RIC],\n",
    "            fields=[testField])\n",
    "        valueTestScope = dfTestScope.values[0][1]\n",
    "        return dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope\n",
    "\n",
    "    if scope == \"1\":\n",
    "        baseFieldOfInterest = f\"TR.{_sourceOfInterest}CO2DirectScope1\"\n",
    "        lstOfFlds.append(baseFieldOfInterest)\n",
    "        try:\n",
    "            dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope = testBaseYearData(\n",
    "            RIC=RIC, _sourceOfInterest=_sourceOfInterest, termOfInterest=termOfInterest, setOfInterest=setOfInterest, testField=baseFieldOfInterest)\n",
    "        except:\n",
    "            raise Exception(f\"No data for Scope {scopeOfInterest} is available for {RIC}, scope {scope}, set {set}, term {term}, source {source}.\")\n",
    "    \n",
    "    if scope == \"2\":\n",
    "        baseFieldOfInterest = f\"TR.{_sourceOfInterest}CO2IndirectScope2\"\n",
    "        lstOfFlds.append(baseFieldOfInterest)\n",
    "        try:\n",
    "            dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope = testBaseYearData(\n",
    "            RIC=RIC, _sourceOfInterest=_sourceOfInterest, termOfInterest=termOfInterest, setOfInterest=setOfInterest, testField=baseFieldOfInterest)\n",
    "        except:\n",
    "            raise Exception(f\"No data for Scope {scopeOfInterest} is available for {RIC}.\")\n",
    "\n",
    "    if scope == \"3\":\n",
    "        baseFieldOfInterest = f\"TR.{_sourceOfInterest}CO2IndirectScope3\"\n",
    "        lstOfFlds.append(baseFieldOfInterest)\n",
    "        try:\n",
    "            dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope = testBaseYearData(\n",
    "            RIC=RIC, _sourceOfInterest=_sourceOfInterest, termOfInterest=termOfInterest, setOfInterest=setOfInterest, testField=baseFieldOfInterest)\n",
    "        except:\n",
    "            raise Exception(f\"No data for Scope {scopeOfInterest} is available for {RIC}.\")\n",
    "\n",
    "    if scope == \"1 and 2\":\n",
    "        baseFieldOfInterest = f\"TR.{_sourceOfInterest}CO2EmissionTotal\"\n",
    "        lstOfFlds.append(baseFieldOfInterest)\n",
    "        marketBasedFieldOfInterest = f\"TR.{_sourceOfInterest}CO2EquivalentEmissionsTotalMarketbased\"\n",
    "        lstOfFlds.append(marketBasedFieldOfInterest)\n",
    "        try:\n",
    "            dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope = testBaseYearData(\n",
    "            RIC=RIC, _sourceOfInterest=_sourceOfInterest, termOfInterest=termOfInterest, setOfInterest=setOfInterest, testField=baseFieldOfInterest)\n",
    "        except:\n",
    "            raise Exception(f\"No data for Scope {scopeOfInterest} is available for {RIC}.\")\n",
    "\n",
    "    if scope == \"1, 2 and 3\":\n",
    "        baseFieldOfInterest = f\"TR.{_sourceOfInterest}TotalCO2EquivalentEmissionsScope1and2and3\"\n",
    "        lstOfFlds.append(baseFieldOfInterest)\n",
    "        marketBasedFieldOfInterest = f\"TR.{_sourceOfInterest}TotalCO2EquivalentEmissionScope1and2and3Marketbased\"\n",
    "        lstOfFlds.append(marketBasedFieldOfInterest)\n",
    "        try:\n",
    "            dfTestBaseYear, valueTestBaseYear, dfTestBaseYearData, valueTestBaseYearData, dfTestScope, valueTestScope = testBaseYearData(\n",
    "            RIC=RIC, _sourceOfInterest=_sourceOfInterest, termOfInterest=termOfInterest, setOfInterest=setOfInterest, testField=baseFieldOfInterest)\n",
    "        except:\n",
    "            raise Exception(f\"No data for Scope {scopeOfInterest} is available for {RIC}.\")\n",
    "\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionPercentageReductionTargetedSet{setOfInterest}\")\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}PercentageofGHGEmissionCoveredbyTargetSet{setOfInterest}\")\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionScopeSet{setOfInterest}\")\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionBaseYearSet{setOfInterest}\")\n",
    "    lstOfFlds.append(f\"TR.{_sourceOfInterest}{termOfInterest}GHGEmissionTargetYearSet{setOfInterest}\")\n",
    "\n",
    "\n",
    "    if suppressWarnings:\n",
    "        warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "        warnings.simplefilter(action='ignore', category=UserWarning)\n",
    "\n",
    "    df1 = ld.get_history(\n",
    "        universe=[RIC],\n",
    "        fields=lstOfFlds,\n",
    "        start=\"1990-01-01\",\n",
    "        end=datetime.now().strftime(\"%Y-%m-%d\"),\n",
    "        header_type=ld.HeaderType.NAME_AND_TITLE,\n",
    "    ).dropna(how='all')\n",
    "\n",
    "    df2 = df1.replace('', pd._libs.missing.NA)\n",
    "    df3 = df2.dropna(how='all')\n",
    "\n",
    "    df4 = df3.filter(like='PERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET')\n",
    "    if df4.apply(pd.to_numeric, errors='coerce').dropna().gt(80).all().all():\n",
    "        print(\"'GHGEmissionCoveredbyTarget' figures are above 80%. The higher this figure, the more reliable the results.\")\n",
    "        print(\"In this case, we consider them to be high enough to be reliable.\")\n",
    "    else:\n",
    "        print(\"Be weary of the fact that 'GHGEmissionCoveredbyTarget' is below 80%. The lower this figure, the less reliable the results.\")\n",
    "\n",
    "\n",
    "    # # # Plotting the results\n",
    "\n",
    "    df5 = df3.copy()\n",
    "    df5.index = [np.int64(z) for z in pd.to_datetime(df5.index, errors='coerce').year.astype(object)] # keep only the years\n",
    "\n",
    "    baseEmissionYear = valueTestBaseYear\n",
    "    targetEmissionReductionYear = int(df3.filter(like='GHGEMISSIONTARGETYEARSET').iloc[-1].values[0])\n",
    "    baseEmission = df3[df3.index.year == int(baseEmissionYear)].filter(like=baseFieldOfInterest.upper()).dropna().values[0][0]\n",
    "    targetReductionEmission = baseEmission * ((df3.filter(like='GHGEMISSIONPERCENTAGEREDUCTIONTARGETED').dropna().iloc[-1] / 100).iloc[0] * (df3.filter(like='PERCENTAGEOFGHGEMISSIONCOVEREDBYTARGET').dropna().iloc[-1] / 100).iloc[0])\n",
    "    targetEmission = baseEmission - targetReductionEmission\n",
    "    print(f\"baseEmissionYear = {baseEmissionYear} & targetEmissionReductionYear = {targetEmissionReductionYear}\")\n",
    "    print(f\"baseEmission = {baseEmission} & targetReductionEmission = {targetReductionEmission} & targetEmission = {targetEmission}\")\n",
    "\n",
    "    start_year = np.datetime64(\n",
    "        df3.T.filter(like=str(baseEmissionYear)).columns.values[0], 'ns')\n",
    "    end_year = np.datetime64(\n",
    "        f\"{targetEmissionReductionYear}-{str(start_year)[5:7]}-{str(start_year)[8:10]}\", 'ns')\n",
    "    start_value, end_value = baseEmission, targetEmission\n",
    "\n",
    "    # Calculate the decay constant 'k' for exponential decay\n",
    "    # We use the formula for exponential decay: y(t) = y0 * exp(-k * (t - t0))\n",
    "    # Solve for 'k' using y(t) at the end point\n",
    "    if end_value / start_value == 0:\n",
    "        k = -np.log(0.01) / (int(str(end_year)[:4]) - int(str(start_year)[:4]))  # Use a small value instead of zero to avoid log(0) issue\n",
    "    else:\n",
    "        k = -np.log(end_value / start_value) / ((end_year - start_year).astype('timedelta64[Y]').astype(float))\n",
    "\n",
    "    # Generate years and corresponding values using exponential decay\n",
    "    years = np.arange(\n",
    "        start_year.astype('datetime64[Y]').astype(int) + 1970,\n",
    "        end_year.astype('datetime64[Y]').astype(int) + 1971)\n",
    "    values = start_value * np.exp(\n",
    "        -k * (years - (start_year.astype('datetime64[Y]').astype(int) + 1970)))\n",
    "\n",
    "    decayDf = pd.DataFrame(data=values, index=years, columns=[f'Exponential Decay to target of {int(targetEmission)}'])\n",
    "    df6 = pd.concat([df5, decayDf])\n",
    "\n",
    "    # Create the plot\n",
    "    fig0 = go.Figure()\n",
    "\n",
    "    # Add the exponential decay line trace\n",
    "    fig0.add_trace(\n",
    "        go.Scatter(\n",
    "            x=df6.index,\n",
    "            y=df6[f'Exponential Decay to target of {int(targetEmission)}'],\n",
    "            mode='lines+markers',\n",
    "            name=f'Exponential Decay to target of {int(targetEmission)}'))\n",
    "\n",
    "    # Set plot title and labels\n",
    "    fig0.update_layout(\n",
    "        title=f\"{RIC} GHG Emissions scope {scope}, set {set}, term {term} & source {source} ({baseEmissionYear} Base & {targetEmissionReductionYear} Target)\",\n",
    "        xaxis_title=\"Year\",\n",
    "        yaxis_title=\"CO2 Tons\",\n",
    "        template=\"plotly_dark\"  # Optional: You can use different templates, such as 'plotly', 'ggplot2', etc.\n",
    "    )\n",
    "\n",
    "    # Add the dots representing the actual CO2 data from df3\n",
    "    fig0.add_trace(go.Scatter(\n",
    "        x=df6.index, \n",
    "        y=df6[df6.filter(like=baseFieldOfInterest.upper()).columns[0]],\n",
    "        mode='lines+markers', \n",
    "        name='CO2 Equivalents Emission Total',\n",
    "        marker=dict(color='grey', size=8)  # Customize the dot color and size\n",
    "    ))\n",
    "\n",
    "    if scope == \"1 and 2\" or scope == \"1, 2 and 3\":\n",
    "        fig0.add_trace(go.Scatter(\n",
    "            x=df6.index,\n",
    "            y=df6[df6.filter(like=f\"CO2EQUIVALENTEMISSIONSTOTALMARKETBASED\").columns[0]],\n",
    "            mode='lines+markers', \n",
    "            name='CO2 Equivalent Emissions Total Market-Based',\n",
    "            marker=dict(color='red', size=8)\n",
    "            ))\n",
    "\n",
    "    # Show the plot\n",
    "    fig0.show()\n",
    "\n",
    "    return df6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'GHGEmissionCoveredbyTarget' figures are above 80%. The higher this figure, the more reliable the results.\n",
      "In this case, we consider them to be high enough to be reliable.\n",
      "baseEmissionYear = 2016 & targetEmissionReductionYear = 2025\n",
      "baseEmission = 72000000 & targetReductionEmission = 6480000.0 & targetEmission = 65520000.0\n"
     ]
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        "title": {
         "text": "SHEL.L GHG Emissions scope 1, set 1, term ST & source LSEG (2016 Base & 2025 Target)"
        },
        "xaxis": {
         "title": {
          "text": "Year"
         }
        },
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   ],
   "source": [
    "ld.open_session()\n",
    "df = GHGEmissionsBaseVsTargetUsingLSEGWorkspace(\n",
    "    RIC=\"SHEL.L\", # MSFT.O, AAPL.O, SHEL.L, LVMH.PA\n",
    "    scope=\"1\", # choice between \"1\", \"2\", \"3\", \"1 and 2\" or \"1, 2 and 3\"\n",
    "    set=1, # choice from 1 to 5\n",
    "    term=\"ST\", # choice between \"ST\" and \"LT\"\n",
    "    source=\"LSEG\") # choice between \"LSEG\" and \"CDP\"\n",
    "ld.close_session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1</th>\n",
       "      <th>TR.STGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|ST GHG Emission Percentage Reduction Targeted Set1</th>\n",
       "      <th>TR.STPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|ST Percentage of GHG Emission Covered by Target Set1</th>\n",
       "      <th>TR.STGHGEMISSIONSCOPESET1|ST GHG Emission Scope Set1</th>\n",
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       "      <th>TR.STGHGEMISSIONTARGETYEARSET1|ST GHG Emission Target Year Set1</th>\n",
       "      <th>Exponential Decay to target of 65520000</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>106000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
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       "      <th>2003</th>\n",
       "      <td>112000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>112000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>105000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>98000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>82000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>75000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>69000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>76000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>74000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>72000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>73000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>76000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>72000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
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       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>72000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>73000000</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>71000000</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>70000000</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2021</td>\n",
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       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>63000000</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2021</td>\n",
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       "      <th>2021</th>\n",
       "      <td>60000000</td>\n",
       "      <td>6</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2023</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>51000000</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2025</td>\n",
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       "    </tr>\n",
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       "      <th>2023</th>\n",
       "      <td>50000000</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>Scope 1 and 2 and 3</td>\n",
       "      <td>2016</td>\n",
       "      <td>2025</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>7.200000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>7.115619e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>7.032226e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.949811e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.868362e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.787868e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.708316e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.629698e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.552000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>6.475213e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      TR.CO2DIRECTSCOPE1|CO2 Equivalent Emissions Direct, Scope 1  \\\n",
       "2002                                          106000000             \n",
       "2003                                          112000000             \n",
       "2004                                          112000000             \n",
       "2005                                          105000000             \n",
       "2006                                           98000000             \n",
       "2007                                           82000000             \n",
       "2008                                           75000000             \n",
       "2009                                           69000000             \n",
       "2010                                           76000000             \n",
       "2011                                           74000000             \n",
       "2012                                           72000000             \n",
       "2013                                           73000000             \n",
       "2014                                           76000000             \n",
       "2015                                           72000000             \n",
       "2016                                           72000000             \n",
       "2017                                           73000000             \n",
       "2018                                           71000000             \n",
       "2019                                           70000000             \n",
       "2020                                           63000000             \n",
       "2021                                           60000000             \n",
       "2022                                           51000000             \n",
       "2023                                           50000000             \n",
       "2016                                               <NA>             \n",
       "2017                                               <NA>             \n",
       "2018                                               <NA>             \n",
       "2019                                               <NA>             \n",
       "2020                                               <NA>             \n",
       "2021                                               <NA>             \n",
       "2022                                               <NA>             \n",
       "2023                                               <NA>             \n",
       "2024                                               <NA>             \n",
       "2025                                               <NA>             \n",
       "\n",
       "      TR.STGHGEMISSIONPERCENTAGEREDUCTIONTARGETEDSET1|ST GHG Emission Percentage Reduction Targeted Set1  \\\n",
       "2002                                               <NA>                                                    \n",
       "2003                                               <NA>                                                    \n",
       "2004                                               <NA>                                                    \n",
       "2005                                               <NA>                                                    \n",
       "2006                                               <NA>                                                    \n",
       "2007                                               <NA>                                                    \n",
       "2008                                               <NA>                                                    \n",
       "2009                                               <NA>                                                    \n",
       "2010                                               <NA>                                                    \n",
       "2011                                               <NA>                                                    \n",
       "2012                                               <NA>                                                    \n",
       "2013                                               <NA>                                                    \n",
       "2014                                               <NA>                                                    \n",
       "2015                                               <NA>                                                    \n",
       "2016                                               <NA>                                                    \n",
       "2017                                               <NA>                                                    \n",
       "2018                                                  2                                                    \n",
       "2019                                                  2                                                    \n",
       "2020                                                  2                                                    \n",
       "2021                                                  6                                                    \n",
       "2022                                                  9                                                    \n",
       "2023                                                  9                                                    \n",
       "2016                                               <NA>                                                    \n",
       "2017                                               <NA>                                                    \n",
       "2018                                               <NA>                                                    \n",
       "2019                                               <NA>                                                    \n",
       "2020                                               <NA>                                                    \n",
       "2021                                               <NA>                                                    \n",
       "2022                                               <NA>                                                    \n",
       "2023                                               <NA>                                                    \n",
       "2024                                               <NA>                                                    \n",
       "2025                                               <NA>                                                    \n",
       "\n",
       "      TR.STPERCENTAGEOFGHGEMISSIONCOVEREDBYTARGETSET1|ST Percentage of GHG Emission Covered by Target Set1  \\\n",
       "2002                                               <NA>                                                      \n",
       "2003                                               <NA>                                                      \n",
       "2004                                               <NA>                                                      \n",
       "2005                                               <NA>                                                      \n",
       "2006                                               <NA>                                                      \n",
       "2007                                               <NA>                                                      \n",
       "2008                                               <NA>                                                      \n",
       "2009                                               <NA>                                                      \n",
       "2010                                               <NA>                                                      \n",
       "2011                                               <NA>                                                      \n",
       "2012                                               <NA>                                                      \n",
       "2013                                               <NA>                                                      \n",
       "2014                                               <NA>                                                      \n",
       "2015                                               <NA>                                                      \n",
       "2016                                               <NA>                                                      \n",
       "2017                                               <NA>                                                      \n",
       "2018                                                100                                                      \n",
       "2019                                                100                                                      \n",
       "2020                                               <NA>                                                      \n",
       "2021                                                100                                                      \n",
       "2022                                                100                                                      \n",
       "2023                                                100                                                      \n",
       "2016                                               <NA>                                                      \n",
       "2017                                               <NA>                                                      \n",
       "2018                                               <NA>                                                      \n",
       "2019                                               <NA>                                                      \n",
       "2020                                               <NA>                                                      \n",
       "2021                                               <NA>                                                      \n",
       "2022                                               <NA>                                                      \n",
       "2023                                               <NA>                                                      \n",
       "2024                                               <NA>                                                      \n",
       "2025                                               <NA>                                                      \n",
       "\n",
       "     TR.STGHGEMISSIONSCOPESET1|ST GHG Emission Scope Set1  \\\n",
       "2002                                               <NA>     \n",
       "2003                                               <NA>     \n",
       "2004                                               <NA>     \n",
       "2005                                               <NA>     \n",
       "2006                                               <NA>     \n",
       "2007                                               <NA>     \n",
       "2008                                               <NA>     \n",
       "2009                                               <NA>     \n",
       "2010                                               <NA>     \n",
       "2011                                               <NA>     \n",
       "2012                                               <NA>     \n",
       "2013                                               <NA>     \n",
       "2014                                               <NA>     \n",
       "2015                                               <NA>     \n",
       "2016                                               <NA>     \n",
       "2017                                               <NA>     \n",
       "2018                                Scope 1 and 2 and 3     \n",
       "2019                                Scope 1 and 2 and 3     \n",
       "2020                                Scope 1 and 2 and 3     \n",
       "2021                                Scope 1 and 2 and 3     \n",
       "2022                                Scope 1 and 2 and 3     \n",
       "2023                                Scope 1 and 2 and 3     \n",
       "2016                                               <NA>     \n",
       "2017                                               <NA>     \n",
       "2018                                               <NA>     \n",
       "2019                                               <NA>     \n",
       "2020                                               <NA>     \n",
       "2021                                               <NA>     \n",
       "2022                                               <NA>     \n",
       "2023                                               <NA>     \n",
       "2024                                               <NA>     \n",
       "2025                                               <NA>     \n",
       "\n",
       "      TR.STGHGEMISSIONBASEYEARSET1|ST GHG Emission Base Year Set1  \\\n",
       "2002                                               <NA>             \n",
       "2003                                               <NA>             \n",
       "2004                                               <NA>             \n",
       "2005                                               <NA>             \n",
       "2006                                               <NA>             \n",
       "2007                                               <NA>             \n",
       "2008                                               <NA>             \n",
       "2009                                               <NA>             \n",
       "2010                                               <NA>             \n",
       "2011                                               <NA>             \n",
       "2012                                               <NA>             \n",
       "2013                                               <NA>             \n",
       "2014                                               <NA>             \n",
       "2015                                               <NA>             \n",
       "2016                                               <NA>             \n",
       "2017                                               <NA>             \n",
       "2018                                               2016             \n",
       "2019                                               2016             \n",
       "2020                                               2016             \n",
       "2021                                               2016             \n",
       "2022                                               2016             \n",
       "2023                                               2016             \n",
       "2016                                               <NA>             \n",
       "2017                                               <NA>             \n",
       "2018                                               <NA>             \n",
       "2019                                               <NA>             \n",
       "2020                                               <NA>             \n",
       "2021                                               <NA>             \n",
       "2022                                               <NA>             \n",
       "2023                                               <NA>             \n",
       "2024                                               <NA>             \n",
       "2025                                               <NA>             \n",
       "\n",
       "      TR.STGHGEMISSIONTARGETYEARSET1|ST GHG Emission Target Year Set1  \\\n",
       "2002                                               <NA>                 \n",
       "2003                                               <NA>                 \n",
       "2004                                               <NA>                 \n",
       "2005                                               <NA>                 \n",
       "2006                                               <NA>                 \n",
       "2007                                               <NA>                 \n",
       "2008                                               <NA>                 \n",
       "2009                                               <NA>                 \n",
       "2010                                               <NA>                 \n",
       "2011                                               <NA>                 \n",
       "2012                                               <NA>                 \n",
       "2013                                               <NA>                 \n",
       "2014                                               <NA>                 \n",
       "2015                                               <NA>                 \n",
       "2016                                               <NA>                 \n",
       "2017                                               <NA>                 \n",
       "2018                                               2021                 \n",
       "2019                                               2021                 \n",
       "2020                                               2021                 \n",
       "2021                                               2023                 \n",
       "2022                                               2025                 \n",
       "2023                                               2025                 \n",
       "2016                                               <NA>                 \n",
       "2017                                               <NA>                 \n",
       "2018                                               <NA>                 \n",
       "2019                                               <NA>                 \n",
       "2020                                               <NA>                 \n",
       "2021                                               <NA>                 \n",
       "2022                                               <NA>                 \n",
       "2023                                               <NA>                 \n",
       "2024                                               <NA>                 \n",
       "2025                                               <NA>                 \n",
       "\n",
       "      Exponential Decay to target of 65520000  \n",
       "2002                                      NaN  \n",
       "2003                                      NaN  \n",
       "2004                                      NaN  \n",
       "2005                                      NaN  \n",
       "2006                                      NaN  \n",
       "2007                                      NaN  \n",
       "2008                                      NaN  \n",
       "2009                                      NaN  \n",
       "2010                                      NaN  \n",
       "2011                                      NaN  \n",
       "2012                                      NaN  \n",
       "2013                                      NaN  \n",
       "2014                                      NaN  \n",
       "2015                                      NaN  \n",
       "2016                                      NaN  \n",
       "2017                                      NaN  \n",
       "2018                                      NaN  \n",
       "2019                                      NaN  \n",
       "2020                                      NaN  \n",
       "2021                                      NaN  \n",
       "2022                                      NaN  \n",
       "2023                                      NaN  \n",
       "2016                             7.200000e+07  \n",
       "2017                             7.115619e+07  \n",
       "2018                             7.032226e+07  \n",
       "2019                             6.949811e+07  \n",
       "2020                             6.868362e+07  \n",
       "2021                             6.787868e+07  \n",
       "2022                             6.708316e+07  \n",
       "2023                             6.629698e+07  \n",
       "2024                             6.552000e+07  \n",
       "2025                             6.475213e+07  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "As you can see, it is rather simple to make a target vs. actual emissions graph using both Snowflake and, in this case, Workspace/CodeBook!\n",
    "\n",
    "Please note that this is not production code and is not to be used in production for investment tools, or used in investment decisions. It is only shown/published for educational purposes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
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