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-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "127fded4-377c-48c9-8d30-33852dfbd0ab",
-   "metadata": {},
-   "source": [
-    "# Use examples of [premise](https://github.com/romainsacchi/premise) with user-generated scenarios\n",
-    "\n",
-    "Author: [romainsacchi](https://github.com/romainsacchi)\n",
-    "\n",
-    "This notebook shows examples on how to use `premise` to adapt the life cycle inventory database [ecoinvent](https://www.ecoinvent.org/) for prospective environmental impact assessment, using **user-generated scenarios**.\n",
-    "\n",
-    "User-generated scenario are scenarios built by the premise users community. They can be used on their own\n",
-    "or together with a global IAM scenario.\n",
-    "Public community scenarios are listed under the repository [Premise community scenario](https://github.com/premise-community-scenarios)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a7694ff4-917d-4027-afe1-d63bf8d5b387",
-   "metadata": {},
-   "source": [
-    "User-generated scenarios are \"packaged\" into [data packages](https://specs.frictionlessdata.io/data-package/)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f2c96741-8a52-4d5d-b2bf-fc091ad97d43",
-   "metadata": {},
-   "source": [
-    "Data packages ensure that the data used comes with all necessary metadata, resources (scenario data, inventories, etc.), and that the data is formatted in a correct way."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a9e4e85b-22eb-4a7e-928a-2ef7b5dd2814",
-   "metadata": {},
-   "source": [
-    "To fetch a data packge, you can use the `datapackage` library.\n",
-    "For exmaple, let's fetch the user-generated scenario about [Switzerland's future energy supply](https://github.com/premise-community-scenarios/energy-perspective-2050-switzerland)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "90c8da09-12b1-4c35-bb36-550be70a738e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from datapackage import Package"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "bda9c910-140b-4e65-9656-156158968c25",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# URL pointing to the raw datapackage.json file of the scenario\n",
-    "fp = \"https://raw.githubusercontent.com/premise-community-scenarios/cobalt-perspective-2050/main/datapackage.json\"\n",
-    "cobalt = Package(fp)\n",
-    "\n",
-    "fp = r\"https://raw.githubusercontent.com/premise-community-scenarios/ammonia-prospective-scenarios/main/datapackage.json\"\n",
-    "ammonia = Package(fp)\n",
-    "\n",
-    "#fp = \"https://raw.githubusercontent.com/premise-community-scenarios/energy-perspective-2050-switzerland/main/datapackage.json\"\n",
-    "fp = \"/Users/romain/Library/CloudStorage/Dropbox/EP2050/energy-perspective-2050-switzerland/datapackage.json\"\n",
-    "ep2050 = Package(fp)\n",
-    "\n",
-    "#fp = \"https://raw.githubusercontent.com/premise-community-scenarios/scenario-example-bread/main/datapackage.json\"\n",
-    "fp = \"/Users/romain/GitHub/scenario-example-bread-/datapackage.json\"\n",
-    "bread = Package(fp)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "05168dfa-b9c2-4f73-90fe-fb7523c15bc1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['scenario_data', 'inventories', 'config']"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bread.resource_names"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b615c6c4-6309-4b55-a375-f95f3446b8f5",
-   "metadata": {},
-   "source": [
-    "The datapackage has 3 resources: scenario data, inventories and a configuration file."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "b88cc08c-c6c2-4890-9c39-c52f51d5b98e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "scenario_data\n",
-      "inventories\n",
-      "config\n"
-     ]
-    }
-   ],
-   "source": [
-    "for resource in ep2050.resources:\n",
-    "    print(resource.name)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d4e664d6-19a2-4ed2-aeec-38bfa97dce8f",
-   "metadata": {},
-   "source": [
-    "or"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "a02895f5-adb8-4b7c-a5a1-a49ed936f140",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['scenario_data', 'inventories', 'config']"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "bread.resource_names"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "676f4a89-f709-46c1-8bc6-19f174ddff2f",
-   "metadata": {},
-   "source": [
-    "And you can directly read them (or look the resources up directly from the repo):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "c8814dca-0f42-4fb9-9169-025f1860f4b4",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
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-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>1</th>\n",
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-       "      <th>...</th>\n",
-       "      <th>11</th>\n",
-       "      <th>12</th>\n",
-       "      <th>13</th>\n",
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-       "      <th>19</th>\n",
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-       "  <tbody>\n",
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-       "      <th>0</th>\n",
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-       "      <td>Business As Usual</td>\n",
-       "      <td>BRA</td>\n",
-       "      <td>Efficiency|Baking|Bread|Activated Dough Develo...</td>\n",
-       "      <td>-</td>\n",
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-       "      <td>0.35</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
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-       "      <td>0.38</td>\n",
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-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
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-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>image</td>\n",
-       "      <td>SSP2-Base</td>\n",
-       "      <td>Business As Usual</td>\n",
-       "      <td>CAN</td>\n",
-       "      <td>Efficiency|Baking|Bread|Activated Dough Develo...</td>\n",
-       "      <td>-</td>\n",
-       "      <td>0.34</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>image</td>\n",
-       "      <td>SSP2-Base</td>\n",
-       "      <td>Business As Usual</td>\n",
-       "      <td>CEU</td>\n",
-       "      <td>Efficiency|Baking|Bread|Activated Dough Develo...</td>\n",
-       "      <td>-</td>\n",
-       "      <td>0.34</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "      <td>0.39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>image</td>\n",
-       "      <td>SSP2-Base</td>\n",
-       "      <td>Business As Usual</td>\n",
-       "      <td>CHN</td>\n",
-       "      <td>Efficiency|Baking|Bread|Activated Dough Develo...</td>\n",
-       "      <td>-</td>\n",
-       "      <td>0.32</td>\n",
-       "      <td>0.33</td>\n",
-       "      <td>0.34</td>\n",
-       "      <td>0.34</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>image</td>\n",
-       "      <td>SSP2-Base</td>\n",
-       "      <td>Business As Usual</td>\n",
-       "      <td>EAF</td>\n",
-       "      <td>Efficiency|Baking|Bread|Activated Dough Develo...</td>\n",
-       "      <td>-</td>\n",
-       "      <td>0.33</td>\n",
-       "      <td>0.34</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>0.35</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.36</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.37</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "      <td>0.38</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      0          1                  2    3   \\\n",
-       "0  image  SSP2-Base  Business As Usual  BRA   \n",
-       "1  image  SSP2-Base  Business As Usual  CAN   \n",
-       "2  image  SSP2-Base  Business As Usual  CEU   \n",
-       "3  image  SSP2-Base  Business As Usual  CHN   \n",
-       "4  image  SSP2-Base  Business As Usual  EAF   \n",
-       "\n",
-       "                                                  4  5     6     7     8   \\\n",
-       "0  Efficiency|Baking|Bread|Activated Dough Develo...  -  0.33  0.34  0.35   \n",
-       "1  Efficiency|Baking|Bread|Activated Dough Develo...  -  0.34  0.35  0.36   \n",
-       "2  Efficiency|Baking|Bread|Activated Dough Develo...  -  0.34  0.35  0.36   \n",
-       "3  Efficiency|Baking|Bread|Activated Dough Develo...  -  0.32  0.33  0.34   \n",
-       "4  Efficiency|Baking|Bread|Activated Dough Develo...  -  0.33  0.34  0.35   \n",
-       "\n",
-       "     9   ...    11    12    13    14    15    16    17    18    19    20  \n",
-       "0  0.35  ...  0.36  0.37  0.37  0.37  0.37  0.38  0.38  0.38  0.38  0.38  \n",
-       "1  0.36  ...  0.37  0.38  0.38  0.38  0.38  0.39  0.39  0.39  0.39  0.39  \n",
-       "2  0.36  ...  0.37  0.38  0.38  0.38  0.38  0.39  0.39  0.39  0.39  0.39  \n",
-       "3  0.34  ...  0.35  0.36  0.36  0.36  0.36  0.37  0.37  0.37  0.37  0.37  \n",
-       "4  0.35  ...  0.36  0.37  0.37  0.37  0.37  0.38  0.38  0.38  0.38  0.38  \n",
-       "\n",
-       "[5 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "data = bread.get_resource(\"scenario_data\").read()\n",
-    "pd.DataFrame(data).head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "952e8dfe-71ee-4649-80ac-a6e3934cfa1f",
-   "metadata": {},
-   "source": [
-    "The datapackage can also be locally stored (i.e., on your computer), in which case you only\n",
-    "need to provide the filepath to the `datapackage.json` file."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "09760b15-e129-46b8-85d2-80aefa5c2a0c",
-   "metadata": {},
-   "source": [
-    "Once the datapackage is loaded, you just need to pass it (in a list) to the `NewDatabase` instance of `premise`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "f15e00e7-4086-4312-8090-ad432ea368d6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "import bw2data\n",
-    "bw2data.projects.set_current(\"ei39\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "b0408c8e-ce9e-4d6c-8e4b-a6a0db1ff384",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "premise v.(1, 5, 0, 'alpha')\n",
-      "+------------------------------------------------------------------+\n",
-      "| Warning                                                          |\n",
-      "+------------------------------------------------------------------+\n",
-      "| Because some of the scenarios can yield LCI databases            |\n",
-      "| containing net negative emission technologies (NET),             |\n",
-      "| it is advised to account for biogenic CO2 flows when calculating |\n",
-      "| Global Warming potential indicators.                             |\n",
-      "| `premise_gwp` provides characterization factors for such flows.  |\n",
-      "| It also provides factors for hydrogen emissions to air.          |\n",
-      "|                                                                  |\n",
-      "| Within your bw2 project:                                         |\n",
-      "| from premise_gwp import add_premise_gwp                          |\n",
-      "| add_premise_gwp()                                                |\n",
-      "+------------------------------------------------------------------+\n",
-      "+--------------------------------+----------------------------------+\n",
-      "| Utils functions                | Description                      |\n",
-      "+--------------------------------+----------------------------------+\n",
-      "| clear_cache()                  | Clears the cache folder. Useful  |\n",
-      "|                                | when updating `premise`or        |\n",
-      "|                                | encountering issues with         |\n",
-      "|                                | inventories.                     |\n",
-      "+--------------------------------+----------------------------------+\n",
-      "| get_regions_definition(model)  | Retrieves the list of countries  |\n",
-      "|                                | for each region of the model.    |\n",
-      "+--------------------------------+----------------------------------+\n",
-      "| ndb.NewDatabase(...)           | Generates a summary of the most  |\n",
-      "| ndb.generate_scenario_report() | important scenarios' variables.  |\n",
-      "+--------------------------------+----------------------------------+\n",
-      "Keep uncertainty data?\n",
-      "NewDatabase(..., keep_uncertainty_data=True)\n",
-      "\n",
-      "Hide these messages?\n",
-      "NewDatabase(..., quiet=True)\n",
-      "\n",
-      "//////////////////// EXTRACTING SOURCE DATABASE ////////////////////\n",
-      "Done!\n",
-      "\n",
-      "////////////////// IMPORTING DEFAULT INVENTORIES ///////////////////\n",
-      "Done!\n",
-      "\n",
-      "/////////////////////// EXTRACTING IAM DATA ////////////////////////\n",
-      "Done!\n"
-     ]
-    }
-   ],
-   "source": [
-    "scenarios = [\n",
-    "    {\"model\": \"image\", \"pathway\":\"SSP2-Base\", \"year\": 2040},\n",
-    "    {\"model\": \"image\", \"pathway\":\"SSP2-Base\", \"year\": 2025},\n",
-    "    {\"model\": \"image\", \"pathway\":\"SSP2-Base\", \"year\": 2035},\n",
-    "    {\"model\": \"image\", \"pathway\":\"SSP2-RCP26\", \"year\": 2045},\n",
-    "]\n",
-    "\n",
-    "ndb = NewDatabase(\n",
-    "        scenarios = scenarios,        \n",
-    "        source_db=\"ecoinvent 3.9 cutoff\",\n",
-    "        source_version=\"3.9\",\n",
-    "        key='tUePmX_S5B8ieZkkM7WUU2CnO8SmShwmAeWK9x2rTFo=',\n",
-    "        external_scenarios=[\n",
-    "            bread,\n",
-    "            cobalt,\n",
-    "            ammonia,\n",
-    "            ep2050\n",
-    "        ]\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "560b5cc3-11c8-4499-b553-d79ec5203e3e",
-   "metadata": {},
-   "source": [
-    "To integrate the projections of the user-generated scenario, call `update_external_scenario()`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "51dd0dd9-86bf-42f3-bded-d3da98178b7e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "\n",
-      "//////////////// IMPORTING USER-DEFINED INVENTORIES ////////////////\n",
-      "Extracted 1 worksheets in 0.00 seconds\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Applying strategy: migrate_datasets\n",
-      "Applying strategy: migrate_exchanges\n",
-      "migration_38_39\n",
-      "List of unlinked exchanges:\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "|                         Name                         | Reference product |          Location          | Categories |     Unit    |     Type     |      File      |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "| treatment of wastewater, average, capacity 1E9l/year |        None       | Europe without Switzerland |    None    | cubic meter | technosphere | lci-EP2050.csv |\n",
-      "+------------------------------------------------------+-------------------+----------------------------+------------+-------------+--------------+----------------+\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Create custom markets.\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "Cannot find ->  transmission network construction, long-distance transmission network, long-distance ['CH', 'UN-EUROPE', 'RER', 'Europe without Austria', 'Europe, without Russia and Turkey', 'RER w/o RU', 'ENTSO-E', 'RER w/o DE+NL+RU', 'RER w/o DE+NL+NO+RU', 'Europe without NORDEL (NCPA)', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'WEU', 'CH', 'RER', 'Europe without Switzerland', 'RoW', 'GLO', 'AD', 'AE', 'AF', 'AG', 'AI', 'AL', 'AM', 'AO', 'AQ', 'AR', 'AS', 'AT', 'AU', 'AUS-AC', 'AUS-ACT', 'AUS-IOT', 'AUS-NSW', 'AUS-NTR', 'AUS-QNS', 'AUS-SAS', 'AUS-TSM', 'AUS-VCT', 'AUS-WAS', 'AW', 'AX', 'AZ', 'Akrotiri', 'Asia without China', 'BA', 'BALTSO', 'BB', 'BD', 'BE', 'BF', 'BG', 'BH', 'BI', 'BJ', 'BL', 'BM', 'BN', 'BO', 'BQ', 'BR', 'BR-AC', 'BR-AL', 'BR-AM', 'BR-AP', 'BR-BA', 'BR-CE', 'BR-DF', 'BR-ES', 'BR-GO', 'BR-MA', 'BR-MG', 'BR-MS', 'BR-MT', 'BR-Mid-western grid', 'BR-North-eastern grid', 'BR-Northern grid', 'BR-PA', 'BR-PB', 'BR-PE', 'BR-PI', 'BR-PR', 'BR-RJ', 'BR-RN', 'BR-RO', 'BR-RR', 'BR-RS', 'BR-SC', 'BR-SE', 'BR-SP', 'BR-South-eastern grid', 'BR-Southern grid', 'BR-TO', 'BS', 'BT', 'BV', 'BW', 'BY', 'BZ', 'Bajo Nuevo', 'CA', 'CA-AB', 'CA-BC', 'CA-MB', 'CA-NB', 'CA-NF', 'CA-NS', 'CA-NT', 'CA-NU', 'CA-ON', 'CA-PE', 'CA-QC', 'CA-SK', 'CA-YK', 'CD', 'CENTREL', 'CF', 'CG', 'CH', 'CI', 'CK', 'CL', 'CM', 'CN', 'CN-AH', 'CN-BJ', 'CN-CQ', 'CN-CSG', 'CN-FJ', 'CN-GD', 'CN-GS', 'CN-GX', 'CN-GZ', 'CN-HA', 'CN-HB', 'CN-HE', 'CN-HL', 'CN-HN', 'CN-HU', 'CN-JL', 'CN-JS', 'CN-JX', 'CN-LN', 'CN-NM', 'CN-NX', 'CN-QH', 'CN-SA', 'CN-SC', 'CN-SD', 'CN-SGCC', 'CN-SH', 'CN-SX', 'CN-TJ', 'CN-XJ', 'CN-XZ', 'CN-YN', 'CN-ZJ', 'CO', 'CR', 'CS', 'CU', 'CV', 'CW', 'CY', 'CZ', 'Canada without Alberta', 'Canada without Alberta and Quebec', 'Canada without Quebec', 'Canary Islands', 'Central Asia', 'China w/o Inner Mongol', 'Clipperton Island', 'Coral Sea Islands', 'Cyprus No Mans Area', 'DE', 'DJ', 'DK', 'DM', 'DO', 'DZ', 'Dhekelia Base', 'EC', 'EE', 'EG', 'EH', 'ENTSO-E', 'ER', 'ES', 'ET', 'Europe without Austria', 'Europe without NORDEL (NCPA)', 'Europe without Switzerland', 'Europe without Switzerland and Austria', 'Europe without Switzerland and France', 'Europe, without Russia and Turkey', 'FI', 'FJ', 'FK', 'FM', 'FO', 'FR', 'FSU', 'France, including overseas territories', 'GA', 'GB', 'GD', 'GE', 'GF', 'GG', 'GH', 'GI', 'GL', 'GM', 'GN', 'GP', 'GQ', 'GR', 'GS', 'GT', 'GU', 'GW', 'GY', 'Guantanamo Bay', 'HK', 'HM', 'HN', 'HR', 'HT', 'HU', 'IAI Area, Africa', 'IAI Area, Asia, without China and GCC', 'IAI Area, EU27 & EFTA', 'IAI Area, Gulf Cooperation Council', 'IAI Area, North America', 'IAI Area, North America, without Quebec', 'IAI Area, Russia & RER w/o EU27 & EFTA', 'IAI Area, South America', 'ID', 'IE', 'IL', 'IM', 'IN', 'IN-AN', 'IN-AP', 'IN-AR', 'IN-AS', 'IN-BR', 'IN-CH', 'IN-CT', 'IN-DD', 'IN-DL', 'IN-DN', 'IN-Eastern grid', 'IN-GA', 'IN-GJ', 'IN-HP', 'IN-HR', 'IN-Islands', 'IN-JH', 'IN-JK', 'IN-KA', 'IN-KL', 'IN-LD', 'IN-MH', 'IN-ML', 'IN-MN', 'IN-MP', 'IN-MZ', 'IN-NL', 'IN-North-eastern grid', 'IN-Northern grid', 'IN-OR', 'IN-PB', 'IN-PY', 'IN-RJ', 'IN-SK', 'IN-Southern grid', 'IN-TN', 'IN-TR', 'IN-UP', 'IN-UT', 'IN-WB', 'IN-Western grid', 'IO', 'IQ', 'IR', 'IS', 'IT', 'JE', 'JM', 'JO', 'JP', 'KE', 'KG', 'KH', 'KI', 'KM', 'KN', 'KP', 'KR', 'KW', 'KY', 'KZ', 'LA', 'LB', 'LC', 'LI', 'LK', 'LR', 'LS', 'LT', 'LU', 'LV', 'LY', 'MA', 'MC', 'MD', 'ME', 'MF', 'MG', 'MH', 'MK', 'ML', 'MM', 'MN', 'MO', 'MP', 'MQ', 'MR', 'MRO', 'MS', 'MT', 'MU', 'MV', 'MW', 'MX', 'MY', 'MZ', 'NA', 'NAFTA', 'NC', 'NE', 'NF', 'NG', 'NI', 'NL', 'NO', 'NORDEL', 'NP', 'NPCC', 'NR', 'NU', 'NZ', 'North America without Quebec', 'Northern Cyprus', 'OM', 'PA', 'PE', 'PF', 'PG', 'PH', 'PK', 'PL', 'PM', 'PN', 'PR', 'PS', 'PT', 'PW', 'PY', 'QA', 'Québec, HQ distribution network', 'RAF', 'RAS', 'RE', 'RER', 'RER w/o AT+BE+CH+DE+FR+IT', 'RER w/o CH+DE', 'RER w/o DE+NL+NO', 'RER w/o DE+NL+NO+RU', 'RER w/o DE+NL+RU', 'RER w/o RU', 'RLA', 'RME', 'RNA', 'RO', 'RS', 'RU', 'RW', 'Russia (Asia)', 'Russia (Europe)', 'SA', 'SAS', 'SB', 'SC', 'SD', 'SE', 'SG', 'SH', 'SI', 'SJ', 'SK', 'SL', 'SM', 'SN', 'SO', 'SR', 'SS', 'ST', 'SV', 'SX', 'SY', 'SZ', 'Scarborough Reef', 'Serranilla Bank', 'Siachen Glacier', 'Somaliland', 'Spratly Islands', 'TC', 'TD', 'TF', 'TG', 'TH', 'TJ', 'TK', 'TL', 'TM', 'TN', 'TO', 'TR', 'TT', 'TV', 'TW', 'TZ', 'UA', 'UCTE', 'UCTE without France', 'UCTE without Germany', 'UCTE without Germany and France', 'UG', 'UM', 'UN-AMERICAS', 'UN-ASIA', 'UN-AUSTRALIANZ', 'UN-CAMERICA', 'UN-CARIBBEAN', 'UN-EAFRICA', 'UN-EASIA', 'UN-EEUROPE', 'UN-EUROPE', 'UN-MAFRICA', 'UN-MELANESIA', 'UN-MICRONESIA', 'UN-NAFRICA', 'UN-NEUROPE', 'UN-OCEANIA', 'UN-POLYNESIA', 'UN-SAMERICA', 'UN-SASIA', 'UN-SEASIA', 'UN-SEUROPE', 'UN-WAFRICA', 'UN-WASIA', 'US', 'US-AK', 'US-AL', 'US-AR', 'US-ASCC', 'US-AZ', 'US-CA', 'US-CO', 'US-CT', 'US-DC', 'US-DE', 'US-FL', 'US-FRCC', 'US-GA', 'US-HI', 'US-HICC', 'US-IA', 'US-ID', 'US-IL', 'US-IN', 'US-KS', 'US-KY', 'US-LA', 'US-MA', 'US-MD', 'US-ME', 'US-MI', 'US-MN', 'US-MO', 'US-MRO', 'US-MS', 'US-MT', 'US-NC', 'US-ND', 'US-NE', 'US-NH', 'US-NJ', 'US-NM', 'US-NPCC', 'US-NV', 'US-NY', 'US-OH', 'US-OK', 'US-OR', 'US-PA', 'US-PR', 'US-RFC', 'US-RI', 'US-SC', 'US-SD', 'US-SERC', 'US-SPP', 'US-TN', 'US-TRE', 'US-TX', 'US-UT', 'US-VA', 'US-VT', 'US-WA', 'US-WECC', 'US-WI', 'US-WV', 'US-WY', 'UY', 'UZ', 'VA', 'VC', 'VE', 'VG', 'VI', 'VN', 'VU', 'WECC', 'WEU', 'WF', 'WS', 'XK', 'YE', 'YT', 'ZA', 'ZM', 'ZW', 'GLO', None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]\n",
-      "Log file of exchanges saved under /Users/romain/GitHub/premise/premise/data/logs.\n"
-     ]
-    }
-   ],
-   "source": [
-    "ndb.update(\"external\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2dde9ff3-fed8-4b42-9c2d-ba71e87ca932",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "37d05dd0-e5a1-4ff5-a91c-8c9c342da322",
-   "metadata": {},
-   "source": [
-    "You can combine the user-generated scenario with any, all or none of the projections for the IAM model.\n",
-    "For example, here with the electricity projections of the IMAGE SSP2-Base scenario:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "15c2e1f4-2d8c-47b5-b0ab-f641f1ebbf47",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "scenarios = [\n",
-    "    {\"model\": \"image\", \"pathway\":\"SSP2-Base\", \"year\": 2040},\n",
-    "]\n",
-    "\n",
-    "ndb = NewDatabase(\n",
-    "        scenarios = scenarios,        \n",
-    "        source_db=\"ecoinvent 3.8 cutoff\",\n",
-    "        source_version=\"3.8\",\n",
-    "        key='xxxxx',\n",
-    "        external_scenarios=[\n",
-    "            switzerland_2050,\n",
-    "        ]\n",
-    ")\n",
-    "\n",
-    "ndb.update(\n",
-    "    [\n",
-    "        \"electricity\",\n",
-    "        \"external\"\n",
-    "    ]\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "30f6dffc-766d-442d-a93d-d53a2b127e72",
-   "metadata": {},
-   "source": [
-    "Once the projections are integrated, you can export the database(s) back to your Brightway2 project, to\n",
-    "a CSV Simapro file, or as a set of sparse amtrices (see main exmaples notebook for more details)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c71a9cd5-e547-409e-868f-03cf6fe09cbf",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/examples/.ipynb_checkpoints/examples-checkpoint.ipynb b/examples/.ipynb_checkpoints/examples-checkpoint.ipynb
deleted file mode 100644
index 3c7e5430..00000000
--- a/examples/.ipynb_checkpoints/examples-checkpoint.ipynb
+++ /dev/null
@@ -1,850 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Use examples of [premise](https://github.com/romainsacchi/premise)\n",
-    "\n",
-    "Author: [romainsacchi](https://github.com/romainsacchi)\n",
-    "\n",
-    "This notebook shows examples on how to use `premise` to adapt the life cycle inventory database [ecoinvent](https://www.ecoinvent.org/) for prospective environmental impact assessment.\n",
-    "\n",
-    "This library extract useful information from IAM model output files (such as those of REMIND or IMAGE) and aligns inventories in the ecoinvent database accordingly.\n",
-    "\n",
-    "With version 1.5.0, the following transformation are available:\n",
-    "\n",
-    "* `update_biomass()`: create regional biomass markets, adjusting the share of residual vs. purpose-grown boimass for use in heat and power generation\n",
-    "* `update_electricity()`: create regional electricity markets and adjust efficiency of power plants, including that of photovoltaic panels\n",
-    "* `update_cement()`: creates regional markets for clinker production and adjust clinker production efficiency\n",
-    "* `update_steel()`: creates regional markets for steel and adjust steel production efficiency and the supply of secondary steel\n",
-    "* `update_dac()`: creates region- and scenario-specific inventories for Direct Air Capture (DAC) and Carbon Storage (DACCS) systems.\n",
-    "* `update_fuels()`: creates regional markets for liquid and gaseous fuels\n",
-    "* `update_heat()`: regionalize some heat and steam generation datasets (working on diesel, biomass and natural gas)\n",
-    "* `update_emissions`: adjust emission of pollutants (PM, NOx, VOCs) for various activities, based on GAINS model projections.\n",
-    "* `update_two_wheelers()`: imports two-wheelers (bicycles, motorbikes, etc.)\n",
-    "* `update_cars()`: produces fleet average cars and relinks to activities consuming pasenger car transport\n",
-    "* `update_trucks()`: produces fleet average trucks and relinks to activities consuming lorry trnasport\n",
-    "* `update_buses()`: imports buses (urban and coach buses, single-deckers and double-deckers)\n",
-    "\n",
-    "Alternatively, `update_all()` performs all the above-mentioned transformations (with the exception of `update_two_wheelers()`, `update_cars()` and `update_buses()`).\n",
-    "\n",
-    "There is also the possibility to integrate user-defined scenarios,\n",
-    "for which we have a separate notebook.\n",
-    "\n",
-    "Additional documentation on the methodology is available [here](https://premise.readthedocs.io/en/latest/introduction.html).\n",
-    "\n",
-    "There's also a **publication** about `premise` [here](https://www.sciencedirect.com/science/article/pii/S136403212200226X?via%3Dihub).\n",
-    "\n",
-    "## Requirements\n",
-    "\n",
-    "* **Pyhton 3.9 or higher (up to 3.11) is highly recommended**\n",
-    "* a user license for ecoinvent v.3\n",
-    "* a **decryption key**, to be asked from [Romain Sacchi](mailto:romain.sacchi@psi.ch)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Use case with [brightway2](https://brightway.dev/)\n",
-    "\n",
-    "`brightway2` is an open source LCA framework for Python.\n",
-    "To use `premise` from `brightway2`, it requires that you have an activated `brightway2` project with a `biosphere3` database as well as an ecoinvent v.3 cut-off or consequential database registered in that project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "import bw2data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### List of available scenarios\n",
-    "\n",
-    "Some scenarios come installed with the library.\n",
-    "They are stored in `data/iam_ouput_files` from the root directory.\n",
-    "They are all within the same Shared Socio-Economic Pathway (SSP): SSP2 (nicknamed \"middle of the road\"), which describes a future world (in terms of GDP and demographics development, education, intergovernmental collaboration) very much in line with what has been observed historically..\n",
-    "\n",
-    "But they are proposed in combination with different climate mitigation targets, called Representative Concentration Pathways (RCP).\n",
-    "Read more about SSPs and RCPs, [here](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change).\n",
-    "\n",
-    "With REMIND, we have the following SSP/RCP scenarios:\n",
-    "* \"SSP1-Base\"\n",
-    "* \"SSP5-Base\"\n",
-    "* \"SSP2-Base\"\n",
-    "* \"SSP2-NPi\"\n",
-    "* \"SSP2-NDC\"\n",
-    "* \"SSP2-PkBudg1150\"\n",
-    "* \"SSP2-PkBudg500\"\n",
-    "\n",
-    "With IMAGE, we have the following SSP/RCP scenarios:\n",
-    "* \"SSP2-Base\"\n",
-    "* \"SSP2-RCP26\"\n",
-    "* \"SSP2-RCP19\"\n",
-    "\n",
-    "Refer to [the documentation](https://premise.readthedocs.io/en/latest/extract.html#current-iam-scenarios) for the meaning of thses scenarios, or have a look at our **[scenario explorer](https://premisedash-6f5a0259c487.herokuapp.com/)**.\n",
-    "Additionally, [this blog](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/) is a good reading material to understand SSPs and RCPs.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Database creation from default scenarios\n",
-    "\n",
-    "To create a scenario using REMIND's SSP2 Base pathway, from ecoinvent 3.5 for the year 2028, one would execute the following cell. This leads to the extraction of the database, some cleanup as well as importing a few additional inventories."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bw2data.projects.set_current(\"premise\")\n",
-    "bw2data.databases"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The first time you create a premise database, *premise* will store a copy of the ecoinvent database and external inventories, to be able to skip that time-consuming step next time. If you wish to clear this cache (which is only encourage if updating premise or if encountering issues with inventories), do:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "clear_cache()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "    scenarios=[\n",
-    "        {\"model\":\"image\", \"pathway\":\"SSP2-RCP19\", \"year\":2050},\n",
-    "        {\"model\":\"remind\", \"pathway\":\"SSP2-PkBudg500\", \"year\":2050},\n",
-    "    ],\n",
-    "    source_db=\"ecoinvent 3.8 cutoff\", # <-- name of the database in the BW2 project. Must be a string.\n",
-    "    source_version=\"3.8\", # <-- version of ecoinvent. Can be \"3.5\", \"3.6\", \"3.7\" or \"3.8\". Must be a string.\n",
-    "    key='xxxxxxxxxxxxxxxxxxxxxxxxx', # <-- decryption key\n",
-    "    # to be requested from the library maintainers if you want ot use default scenarios included in `premise`\n",
-    "    use_multiprocessing=True, # True by default, set to False if multiprocessing is causing troubles\n",
-    "    keep_uncertainty_data=False # False by default, set to True if you want to keep ecoinvent's uncertainty data\n",
-    "    use_absolute_efficiency=True, # False by default, set to True if you want to use the IAM's absolute efficiency for power plants\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If you do not want to integrate the IAM projections in the database, but only wish to have the additional inventories, you can stop here and export the database back to Brightway or other destinations, by using the `write_db_to` methods, like so:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "However, if you wish first to proceed with the IAM integration, you need to use the `update_` methods, like so for the electricity sector:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.update(\"electricity\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "or here with ecoinvent 3.7.1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "        scenarios=[\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2028}\n",
-    "            ],\n",
-    "        source_db=\"ecoinvent 3.7 cutoff\", # <-- this is NEW.\n",
-    "        source_version=\"3.7.1\", # <-- this is NEW\n",
-    "        key='xxxxxxxxxxxxxxxxxxxxxxxxx'\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If you want to create multiple databases at once, just populate the `scenarios` list."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "            scenarios=[\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2020},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2030},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2040},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2050},\n",
-    "            ],\n",
-    "            source_db=\"ecoinvent 3.7 cutoff\", # <-- name of the database. Must be a string.\n",
-    "            source_version=\"3.7.1\", # <-- version of ecoinvent. Can be \"3.5\", \"3.6\", \"3.7\" or \"3.7.1\"\n",
-    "            key='xxxxxxxxxxxxxxxxxxxxxxxxx'\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "When the database is loaded and the additional inventories imported, you can apply a transformation function.\n",
-    "For example here, we adjust the efficiency of the power plants to the two scenarios we have loaded.\n",
-    "We go more in details later."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.update(\"electricity\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Or you can proceed instead to doing all the sectoral transformations available, like so:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.update() # <- updates all sectors"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "And then, we register these two databases back into brightway2."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Consequential\n",
-    "\n",
-    "`premise` can read in the consequential version of ecoinvent (v.3.8 and 3.9 only).\n",
-    "Based on the publication of Maes et al. 2023 (https://doi.org/10.1016/j.rser.2023.113830), `premise` builds marginal market mixes for electricity and fuels.\n",
-    "The identification of marginal suppliers can be influenced by passing a series of arguments to `NewDatabase()`.\n",
-    "Additionally, `premise` removes secondary steel technologies from steel markets."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "from datapackage import Package\n",
-    "import brightway2 as bw\n",
-    "bw.projects.set_current(\"new4\")\n",
-    "\n",
-    "args = {\"range time\":2, \"duration\":False, \"foresight\":False, \"lead time\":True, \"capital replacement rate\":False, \"measurement\": 0, \"weighted slope start\": 0.75, \"weighted slope end\": 1.00}\n",
-    "\n",
-    "ndb = NewDatabase(\n",
-    "            scenarios=[\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2020},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2030},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2040},\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2050},\n",
-    "            ],\n",
-    "            source_db=\"ecoinvent 3.8 consequential\", # <-- Must point to the consequential database.\n",
-    "            source_version=\"3.8\", # <-- Can only be 3.8.\n",
-    "            key='xxxxxxxxxxxxxxxxxxxxxxxxx',\n",
-    "            system_model=\"consequential\", # <-- Must specify \"consequential\"\n",
-    "            system_model_args=args # Optional. Arguments.\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Database creation from non-default scenarios\n",
-    "\n",
-    "If you have some specific IAM scenarios (one that is not included in `premise`) you would like to build a database from, you can specify the directory to those.\n",
-    "\n",
-    "**Important remark**: your scenario file must begin with \"remind_\" or \"image_\". When using a non-default scenario that you provide yourself, you do not have to provide a decryption key."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "import bw2data\n",
-    "\n",
-    "bw2data.projects.set_current(\"new\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "    scenarios = [{\"model\":\"newiam\", \"pathway\":\"path1-Base\", \"year\":2028,\n",
-    "                  \"filepath\":\"/Users/romain/Documents\"}],        \n",
-    "    source_db=\"ecoinvent 3.8 cutoff\", # <-- name of the database\n",
-    "    source_version=\"3.8\", # <-- version of ecoinvent\n",
-    " )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Adding inventories\n",
-    "Upon the database extraction, you can import some of your Brightway2-compatible inventories like so:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "            scenarios=[\n",
-    "                {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2030},\n",
-    "            ],\n",
-    "            source_db=\"ecoinvent 3.7 cutoff\", \n",
-    "            source_version=\"3.7.1\",\n",
-    "            key='xxxxxxxxxxxxxxxxxxxxxxxxx'\n",
-    "            additional_inventories= [ # <-- this is NEW\n",
-    "                {\"filepath\": r\"filepath\\to\\excel_file.xlsx\", \"ecoinvent version\": \"3.7\"}, # <-- this is NEW\n",
-    "                {\"filepath\": r\"filepath\\to\\another_excel_file.xlsx\", \"ecoinvent version\": \"3.7\"}, # <-- this is NEW\n",
-    "            ] # <-- this is NEW\n",
-    "                 )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Use case with ecospold2\n",
-    "\n",
-    "The source database does not have to be from a brightway2 project.\n",
-    "It can be directly extracted from the bunch of ecospold2 files one gets when downloaded from the [ecoinvent website](https://ecoinvent.org).\n",
-    "\n",
-    "For this, one needs to specify the argument `source_db = \"ecospold\"` as well as `source_file_path`, which is the directory leading to the ecospold files.\n",
-    "\n",
-    "For example, here we combine the use of a specific (non-default) IAM scenario file with the use of ecospold2 files as data source (ecoinvent 3.5 in this case)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "        scenarios = [\n",
-    "            {\"model\":\"remind\", \"pathway\":\"my_special_scenario\", \"year\":2028,\n",
-    "             \"filepath\":r\"C:\\filepath\\to\\your\\scenario\\folder\"}\n",
-    "        ],        \n",
-    "        source_type=\"ecospold\", # <--- this is NEW\n",
-    "        source_file_path=r\"C:\\filepath\\to\\your\\ecosposld\\folder\\datasets\", # <-- this is NEW\n",
-    "        source_version=\"3.5\",\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Transformation functions\n",
-    "\n",
-    "These functions modify the extracted database:\n",
-    "\n",
-    "* **update(\"electricity\")**: alignment of regional electricity production mixes as well as efficiencies for a number of electricity production technologies, including Carbon Capture and Storage technologies and photovoltaic panels. Also updated the natural gas extraction datasets.\n",
-    "\n",
-    "* **update(\"cement\")**: adjustment of technologies for cement production (dry, semi-dry, wet, with pre-heater or not), fuel efficiency of kilns, fuel mix of kilns (including biomass and waste fuels).\n",
-    "\n",
-    "* **update(\"steel\")**: adjustment of process efficiency, fuel mix and share of secondary steel in steel markets.\n",
-    "\n",
-    "* **update(\"dac\")**: creates region- and scenario-specific inventories for DAC and DACCS systems. Applies a learning rate on energy and infrastructure needs if the IAM provides the variable.\n",
-    "\n",
-    "* **update(\"fuels\")**: creates regional markets for liquid and gaseous fuels and relinks fuel-conusming activities to them.\n",
-    "\n",
-    "* **update(\"heat\")**: creates regionalized versions of heat and steam production datasets and relink them to heat-consuming activities.\n",
-    "\n",
-    "* **update(\"emissions\")**: adjusts emission of local air pollutants according to GAINS projections.\n",
-    "\n",
-    "* **update(\"cars\")**: creates updated inventories for fleet average passenger cars and links back to activities that consume transport.\n",
-    "\n",
-    "* **update(\"trucks\")**: creates updated inventories for fleet average lorry trucks and links back to activities that consume transport.\n",
-    "\n",
-    "* **update(\"two_wheelers\")**: create inventories for two-wheelers.\n",
-    "\n",
-    "* **update(\"buses\")**: create inventories for buses.\n",
-    "\n",
-    "A look at the documentation is advised.\n",
-    "\n",
-    "\n",
-    "These functions can be applied *separately*, *consecutively* or *altogether* (using instead **.update()** without arguments).\n",
-    "\n",
-    "They will apply to all the scenario-specific databases listed in `scenarios`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "import bw2data\n",
-    "bw2data.projects.set_current(\"some project\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb = NewDatabase(\n",
-    "            scenarios=[\n",
-    "                {'model':'remind','pathway':'SSP2-Base','year':'2020'},\n",
-    "                {\"model\":\"image\", \"pathway\":\"SSP2-Base\", \"year\":2034},\n",
-    "            ],\n",
-    "            key='xxxxxxxxxxxxxxxxxxxxxxxxx',\n",
-    "            source_db=\"ecoinvent 3.7 cutoff\",\n",
-    "            source_version=\"3.7\", \n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.update()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can also give your datababases a custom name."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway(name=[\"my_custom_name_1\", \"my_custom_name_2\"])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Export"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a Brightway2 database"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Export the modified database to brightway2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a sparse matrix representation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Or export it as a sparse matrix representation.\n",
-    "\n",
-    "This will export four files:\n",
-    "\n",
-    "* \"A_matrix.csv\": matrix coordinates and values of shape (index of activity; index of product; value) for the technosphere\n",
-    "* \"A_matrix_index.csv\": labels for indices for A matrix of shape (name of activity, reference product, unit, location, index)\n",
-    "* \"B_matrix.csv\": matrix coordinates and values of shape (index of activity; index of biosphere flow; value) for the biosphere\n",
-    "* \"B_matrix_index.csv\": labels for indices for B matrix of shape (name of biosphere flow, main compartment, sub-compartmnet, unit, index)\n",
-    "\n",
-    "As a convenience, you can specifiy a directory where to store the exported matrices.\n",
-    "If the directory does not exist, it will be created.\n",
-    "If you leave it unspecified, they will be stored in **data/matrices** in the root folder of the library."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_matrices(filepath=r\"C:/Users/sacchi_r/Downloads/exported_matrices\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Here is an example on how to claculate GWP scores using the set of sparse matrices\n",
-    "export by `premise`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from scipy import sparse\n",
-    "#from pypardiso import spsolve <-- use pypardiso if you use an Intel chip, it's much faster!\n",
-    "from scipy.sparse.linalg import spsolve\n",
-    "from pathlib import Path\n",
-    "from csv import reader\n",
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# the directory to the set of files produced by premise\n",
-    "DIR = Path(r\"/Users/romain/GitHub/premise/premise/data/export/remind/SSP2-PkBudg1150/2040\") \n",
-    "\n",
-    "# creates dict of activities <--> indices in A matrix\n",
-    "A_inds = dict()\n",
-    "with open(DIR / \"A_matrix_index.csv\", 'r') as read_obj:\n",
-    "    csv_reader = reader(read_obj, delimiter=\";\")\n",
-    "    for row in csv_reader:\n",
-    "        A_inds[(row[0], row[1], row[2], row[3])] = row[4]\n",
-    "\n",
-    "A_inds_rev = {int(v):k for k, v in A_inds.items()}\n",
-    "\n",
-    "# creates dict of bio flow <--> indices in B matrix\n",
-    "B_inds = dict()\n",
-    "with open(DIR / \"B_matrix_index.csv\", 'r') as read_obj:\n",
-    "    csv_reader = reader(read_obj, delimiter=\";\")\n",
-    "    for row in csv_reader:\n",
-    "        B_inds[(row[0], row[1], row[2], row[3])] = row[4]\n",
-    "        \n",
-    "B_inds_rev = {int(v):k for k, v in B_inds.items()}\n",
-    "\n",
-    "# create a sparse A matrix\n",
-    "A_coords = np.genfromtxt(DIR / \"A_matrix.csv\", delimiter=\";\", skip_header=1)\n",
-    "I = A_coords[:, 0].astype(int)\n",
-    "J = A_coords[:, 1].astype(int)\n",
-    "A = sparse.csr_matrix((A_coords[:,2], (J, I)))\n",
-    "\n",
-    "# create a sparse B matrix\n",
-    "B_coords = np.genfromtxt(DIR / \"B_matrix.csv\", delimiter=\";\", skip_header=1)\n",
-    "I = B_coords[:, 0].astype(int)\n",
-    "J = B_coords[:, 1].astype(int)\n",
-    "B = sparse.csr_matrix((B_coords[:,2] * -1, (I, J)), shape=(A.shape[0], len(B_inds)))\n",
-    "\n",
-    "# a vector with a few GWP CFs\n",
-    "gwp = np.zeros(B.shape[1])\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, non-fossil, resource correction\"]] = -1\n",
-    "#gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Hydrogen\"]] = 5\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, in air\"]] = -1\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, non-fossil\"]] = 1\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, fossil\"]] = 1\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, from soil or biomass stock\"]] = 1\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon dioxide, to soil or biomass stock\"]] = -1\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Carbon monoxide, fossil\"]] = 4.06\n",
-    "gwp[[int(B_inds[x]) for x in B_inds if x[0]==\"Methane, fossil\"]] = 29.6\n",
-    "\n",
-    "l_res = []\n",
-    "#for v in range(0, A.shape[0]):\n",
-    "# let's limit this to the first 3 activities of the matrix\n",
-    "for v in range(0, 3):\n",
-    "    f = np.float64(np.zeros(A.shape[0]))\n",
-    "    f[v] = 1\n",
-    "    A_inv = spsolve(A, f) # <-- this is too slow\n",
-    "    C = A_inv * B\n",
-    "    l_res.append((C * gwp).sum())"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Print the results together with the name of the activity"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "[(k, v) for k, v in zip(l_res, list(A_inds_rev.values())[:10])]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a SimaPro CSV file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_simapro(filepath=r\"C:/Users/sacchi_r/Downloads/exported_simapro_file\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a SimaPro CSV file for OpenLCA"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_db_to_olca(filepath=r\"C:/Users/sacchi_r/Downloads/exported_simapro_file\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a Superstructure database\n",
-    "A superstructure database is a database that can accomodate several scenarios, as described [here](https://github.com/dgdekoning/brightway-superstructure), to be then used in [Activity-Browser](https://github.com/LCA-ActivityBrowser/activity-browser).\n",
-    "This function will export the superstructure database as well as produce a \"scenario difference file\". Hence, even though you create multiple scenarios, **you only need to write to disk one database**."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_superstructure_db_to_brightway()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_superstructure_db_to_brightway(name=\"my_db\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### As a data package\n",
-    "Export a data package, which can be shared. Data packages cna be read by [unfold](https://github.com/polca/unfold) and databases can be reproduced on other computers."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.write_datapackage()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Reports"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Scenario report\n",
-    "\n",
-    "You can generate a spreadsheet report showing the main variables of the scenario you have selected to create your databases.\n",
-    "The report is saved in your working directory. Note that this report is generated automatically when exporting a database."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.generate_scenario_report()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Changes report"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can generate a spreadsheet report of the changes made to the original database.\n",
-    "It gives an overview on:\n",
-    "\n",
-    "* the datasets created\n",
-    "* the datasets modified\n",
-    "* some performance indicators\n",
-    "* scaling factors used to scale certain exchanges\n",
-    "\n",
-    "There is also a \"Validation\" tab that shows any datasets which contains values or efficiencies that may seem incorrect.\n",
-    "\n",
-    "The report is saved in your working directory. Note that this report is generated automatically when exporting a database."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ndb.generate_change_report()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
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index 8597dda9..00000000
Binary files a/premise/iam_variables_mapping/new image variables.xlsx and /dev/null differ
diff --git a/tests/.ipynb_checkpoints/validation-checkpoint.ipynb b/tests/.ipynb_checkpoints/validation-checkpoint.ipynb
deleted file mode 100644
index 99a5fa1c..00000000
--- a/tests/.ipynb_checkpoints/validation-checkpoint.ipynb
+++ /dev/null
@@ -1,165 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "id": "7d337bc8-b655-43ae-a5cd-d6ce66c5772a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from premise import *\n",
-    "import bw2data, bw2calc\n",
-    "import pandas as pd\n",
-    "bw2data.projects.set_current(\"ei39\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 85,
-   "id": "60d8be19-df7d-480d-96ab-306a2acaf4dc",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1930\n"
-     ]
-    }
-   ],
-   "source": [
-    "FU = [\n",
-    "    {a: 1} for a in\n",
-    "    bw2data.Database(\"test8\")\n",
-    "    if a[\"name\"].startswith(\"electricity production\") and a[\"unit\"] == \"kilowatt hour\"\n",
-    "]\n",
-    "\n",
-    "print(len(FU))\n",
-    "\n",
-    "list_meth = [\n",
-    "    ('IPCC 2021', 'climate change', 'GWP 100a, incl. H'),\n",
-    "    ('IPCC 2021', 'climate change', 'GWP 100a, incl. H and bio CO2'),\n",
-    "    ('selected LCI results', 'resource', 'land occupation'),\n",
-    "    ('EN15804', 'inventory indicators ISO21930', 'use of net fresh water'),\n",
-    "    ('Cumulative Energy Demand (CED)', 'total', 'energy content (HHV)'),\n",
-    "    ('USEtox', 'ecotoxicity', 'total')\n",
-    "]\n",
-    "import bw2calc\n",
-    "bw2data.calculation_setups['multiLCA'] = {'inv': FU, 'ia': list_meth}\n",
-    "myMultiLCA = bw2calc.MultiLCA('multiLCA')\n",
-    "df = pd.DataFrame(columns = [\", \".join(i) for i in list_meth],\n",
-    "     data = myMultiLCA.results,\n",
-    "     index=[k[\"name\"] + \", \" + k[\"location\"] for i in FU for k in i]\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "id": "c75dc85d-2795-429b-bd66-cbc5d6e973b5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x800 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "# Plot with labels only on the bottom row and shading for IQR\n",
-    "fig, axs = plt.subplots(3, 2, figsize=(12, 8))\n",
-    "axs = axs.flatten()  # Flatten to iterate easily\n",
-    "\n",
-    "for i, column in enumerate(df.columns):\n",
-    "    sorted_df = df.sort_values(by=column)\n",
-    "    axs[i].plot(sorted_df.index, sorted_df[column], 'o', label='Values', zorder=1, markersize=0.5)\n",
-    "    mean_value = sorted_df[column].mean()\n",
-    "    median_value = sorted_df[column].median()\n",
-    "    axs[i].axhline(mean_value, color='r', linestyle='-', label=f'Mean: {mean_value:.4f}', zorder=2)\n",
-    "    axs[i].axhline(median_value, color='g', linestyle='--', label=f'Median: {median_value:.4f}', zorder=3)\n",
-    "    \n",
-    "    # Calculate and shade the IQR\n",
-    "    Q1 = sorted_df[column].quantile(0.25)\n",
-    "    Q3 = sorted_df[column].quantile(0.75)\n",
-    "    IQR = Q3 - Q1\n",
-    "    lower_bound = Q1 - 1.5 * IQR\n",
-    "    upper_bound = Q3 + 1.5 * IQR\n",
-    "    axs[i].fill_between(sorted_df.index, lower_bound, upper_bound, color='yellow', alpha=0.3, zorder=0, label='IQR Range')\n",
-    "    axs[i].set_xticklabels([])\n",
-    "    axs[i].set_title(column)\n",
-    "    axs[i].legend()\n",
-    "\n",
-    "plt.tight_layout()\n",
-    "plt.show()\n",
-    "\n",
-    "# Calculate the deviation of outliers from the mean instead of their absolute value\n",
-    "outliers_info_with_deviation = []\n",
-    "\n",
-    "for column in df.columns:\n",
-    "    mean_value = df[column].mean()\n",
-    "    Q1 = df[column].quantile(0.25)\n",
-    "    Q3 = df[column].quantile(0.75)\n",
-    "    IQR = Q3 - Q1\n",
-    "    lower_bound = Q1 - 1.5 * IQR\n",
-    "    upper_bound = Q3 + 1.5 * IQR\n",
-    "    outliers_temp = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
-    "    for _, row in outliers_temp.iterrows():\n",
-    "        deviation_from_mean = row[column] / mean_value\n",
-    "        outliers_info_with_deviation.append({\n",
-    "            \"Activity Name\": row.name,\n",
-    "            \"Impact Category\": column,\n",
-    "            \"Deviation from Mean\": deviation_from_mean,\n",
-    "            \"Value\": row[column]\n",
-    "        })\n",
-    "\n",
-    "outliers_df_with_deviation = pd.DataFrame(outliers_info_with_deviation)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 88,
-   "id": "e144bfec-7e45-49b1-a2fb-6faa6770cb8c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "outliers_df_with_deviation.to_excel(\"outliers.xlsx\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "667171e0-00a4-4ec7-8105-cb14f6545018",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.18"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}