Traduction one one

Conversion-Script/Convert_Wiliam_result_IAMC-format.ipynb

@@ -161,13 +161,24 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Check for duplicate rows\n",
+    "duplicate_rows = scenario_variable_df[scenario_variable_df.duplicated()]\n",
+    "\n",
+    "# Display duplicate rows\n",
+    "print(\"Duplicate Rows:\")\n",
+    "print(duplicate_rows)\n",
+    "\n",
+    "# Count the number of duplicate rows\n",
+    "num_duplicate_rows = duplicate_rows.shape[0]\n",
+    "print(\"Number of Duplicate Rows:\", num_duplicate_rows)\n",
+    "\n",
     "# Read the CSV file into a pandas DataFrame\n",
-    "data_name_df = pd.read_excel('Variable_Reference/Variable_name_IAMC.xlsx')\n",
+    "data_name_df = pd.read_excel(\"Variable_Reference/Variable_name_IAMC.xlsx\")\n",
     "# Remplacer les tirets du bas par des espaces dans la colonne\n",
     "# data_name_df['WILIAM_variable'] = data_name_df['WILIAM_variable'].str.replace('_', ' ')\n",
     "# Drop rows with NaN values which corresponds to values not conserv for the final upload of data in IAMC format\n",
-    "data_name_df.dropna(subset=['IAMC_variable'],inplace=True)\n",
-    "data_name_df"
+    "data_name_df.dropna(subset=[\"IAMC_variable\"], inplace=True)\n",
+    "data_name_df\n"
    ]
   },
   {
@@ -184,7 +195,7 @@
     "\n",
     "# Keep only the rows where the value in column 'Variable' belongs to the list of wanted values \n",
     "variable_required_list = data_name_df['IAMC_variable'].to_list()\n",
-    "scenario_variable_df = scenario_variable_df[scenario_variable_df['Variable'].isin(variable_required_list)]"
+    "# scenario_variable_df = scenario_variable_df[scenario_variable_df['Variable'].isin(variable_required_list)]\n"
    ]
   },
   {
@@ -273,39 +284,79 @@
    "outputs": [],
    "source": [
     "# Dict used to check if the subscripts are a country\n",
-    "country_dict= {'EU27':1, 'UK':1,'CHINA':1,'EASOC':1,'INDIA':1,'LATAM':1,'RUSSIA':1,'USMCA':1,'LROW':1,'AUSTRIA':1,'BELGIUM':1,'BULGARIA':1,'CROATIA':1,'CYPRUS':1,'CZECH_REPUBLIC':1,'DENMARK':1,'ESTONIA':1,'FINLAND':1,'FRANCE':1,'GERMANY':1,'GREECE':1,'HUNGARY':1,'IRELAND':1,'ITALY':1,'LATVIA':1,'LITHUANIA':1,'LUXEMBOURG':1,'MALTA':1,'NETHERLANDS':1,'POLAND':1,'PORTUGAL':1,'ROMANIA':1,'SLOVAKIA':1,'SLOVENIA':1,'SPAIN':1,'SWEDEN':1}\n",
-    "\n",
-    "# Aggregate the subscripts at the end of the variable \n",
+    "country_dict = {\n",
+    "    \"EU27\": 1,\n",
+    "    \"UK\": 1,\n",
+    "    \"CHINA\": 1,\n",
+    "    \"EASOC\": 1,\n",
+    "    \"INDIA\": 1,\n",
+    "    \"LATAM\": 1,\n",
+    "    \"RUSSIA\": 1,\n",
+    "    \"USMCA\": 1,\n",
+    "    \"LROW\": 1,\n",
+    "    \"AUSTRIA\": 1,\n",
+    "    \"BELGIUM\": 1,\n",
+    "    \"BULGARIA\": 1,\n",
+    "    \"CROATIA\": 1,\n",
+    "    \"CYPRUS\": 1,\n",
+    "    \"CZECH_REPUBLIC\": 1,\n",
+    "    \"DENMARK\": 1,\n",
+    "    \"ESTONIA\": 1,\n",
+    "    \"FINLAND\": 1,\n",
+    "    \"FRANCE\": 1,\n",
+    "    \"GERMANY\": 1,\n",
+    "    \"GREECE\": 1,\n",
+    "    \"HUNGARY\": 1,\n",
+    "    \"IRELAND\": 1,\n",
+    "    \"ITALY\": 1,\n",
+    "    \"LATVIA\": 1,\n",
+    "    \"LITHUANIA\": 1,\n",
+    "    \"LUXEMBOURG\": 1,\n",
+    "    \"MALTA\": 1,\n",
+    "    \"NETHERLANDS\": 1,\n",
+    "    \"POLAND\": 1,\n",
+    "    \"PORTUGAL\": 1,\n",
+    "    \"ROMANIA\": 1,\n",
+    "    \"SLOVAKIA\": 1,\n",
+    "    \"SLOVENIA\": 1,\n",
+    "    \"SPAIN\": 1,\n",
+    "    \"SWEDEN\": 1,\n",
+    "}\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "# Aggregate the subscripts at the end of the variable\n",
     "def aggregate_variable_name(row, counter):\n",
     "    for k in range(counter):\n",
-    "        subscript=row[\"Subscript \"+str(k)]\n",
-    "    \n",
-    "        if k==0 :\n",
-    "            if country_dict.get(subscript)==1: \n",
-    "                #Give the name of the region for that variable\n",
-    "                row[\"Region\"]=subscript\n",
-    "                \n",
-    "                row[\"Subscript 0\"]=np.nan\n",
+    "        subscript = row[\"Subscript \" + str(k)]\n",
+    "\n",
+    "        if k == 0:\n",
+    "            if country_dict.get(subscript) == 1:\n",
+    "                # Give the name of the region for that variable\n",
+    "                row[\"Region\"] = subscript\n",
+    "\n",
+    "                row[\"Subscript 0\"] = np.nan\n",
     "                continue\n",
-    "        \n",
+    "\n",
     "        if not pd.isnull(subscript):\n",
-    "            \n",
     "            if energy_dict.get(subscript, None) is not None:\n",
-    "                \n",
     "                subscript = energy_dict[subscript]\n",
-    "            elif rest_dict.get(subscript,None): \n",
+    "            elif rest_dict.get(subscript, None):\n",
     "                subscript = rest_dict[subscript]\n",
-    "            \n",
-    "            row[\"Variable\"]=row[\"Variable\"]+\"|\"+subscript\n",
-    "            \n",
-    "    return row \n",
     "\n",
+    "            row[\"Variable\"] = row[\"Variable\"] + \"|\" + subscript\n",
+    "\n",
+    "    return row\n",
     "\n",
-    "# Apply the previous function on all the lines \n",
-    "scenario_variable_df= scenario_variable_df.apply(aggregate_variable_name, args=(counter,),axis=1)\n",
+    "\n",
+    "# Apply the previous function on all the lines\n",
+    "scenario_variable_df = scenario_variable_df.apply(\n",
+    "    aggregate_variable_name, args=(counter,), axis=1\n",
+    ")\n",
     "\n",
     "# Remove the subscript columns once they have been added at the end of the variable name\n",
-    "drop_columns_list=[\"Subscript \" + str(k) for k in range(counter)]\n",
+    "drop_columns_list = [\"Subscript \" + str(k) for k in range(counter)]\n",
     "scenario_variable_df.drop(columns=drop_columns_list, inplace=True)\n",
     "\n",
     "scenario_variable_df"
@@ -359,7 +410,26 @@
     "\n",
     "# Capitalize each variable's name\n",
     "scenario_variable_df['Variable'] = scenario_variable_df['Variable'].apply(transform_string)\n",
-    "scenario_variable_df"
+    "scenario_variable_df.head(60)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import csv\n",
+    "\n",
+    "\n",
+    "# Step 1: Write to the first column\n",
+    "data_first_column = scenario_variable_df[\"Variable\"].to_list()\n",
+    "\n",
+    "# Open the CSV file in write mode and write the first column\n",
+    "with open(\"example.csv\", \"w\", newline=\"\") as csvfile:\n",
+    "    csvwriter = csv.writer(csvfile)\n",
+    "    for row in data_first_column:\n",
+    "        csvwriter.writerow([row])\n"
    ]
   },
   {
@@ -645,7 +715,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,

Conversion-Script/Create_Variable_Dict/aggregation.txt

@@ -0,0 +1,4 @@
+{
+    ('world_PE_by_commodity|PE_waste', 'world_PE_by_commodity|PE_solar'): 'Primary Energy|New',
+    ('C', 'D', 'E'): 'Y'
+}

Conversion-Script/Create_Variable_Dict/economy_dashboard_dict.txt

@@ -0,0 +1,37 @@
+{'DB CAPITAL STOCK': 'Capital Stock',
+ 'DB CONSUMPTION FIXED CAPITAL': 'Value Added|Consumption Fixed Capital',
+ 'DB DISPOSABLE INCOME PER CAPITA': 'Households|Consumer Price [index]',
+ 'DB EMPLOYMENT': 'Employment',
+ 'DB EXPORTS': 'Trade|Value|Exports',
+ 'DB GDP': 'GDP|PPP',
+ 'DB GDP PER CAPITA': 'Revenue|Households|Disposable [per capita]',
+ 'DB GOV BALANCE': 'Government|Budget Balance',
+ 'DB GOV BALANCE TO GDP': 'Government|Budget Balance to GDP',
+ 'DB GOV CONSUMPTION': 'Public Consumption',
+ 'DB GOV DEBT': 'Debt|Public',
+ 'DB GOV DEBT TO GDP': 'Revenues|Households|Disposable income',
+ 'DB GOV EXPENDITURE': 'Expenditure|Government',
+ 'DB GOV REVENUE': 'Revenue|Government',
+ 'DB GROSS FIXED CAPITAL FORMATION': 'Capital Formation',
+ 'DB GVA AGRICULTURE': 'Value Added|Agriculture',
+ 'DB GVA ENERGY': 'Value Added|Industry|Energy',
+ 'DB GVA EXTRACTION': 'Value Added|Extraction',
+ 'DB GVA INDUSTRY': 'Value Added|Industry',
+ 'DB GVA SERVICES': 'Value Added|Services',
+ 'DB GVA TAXES PRODUCTS TOTAL': 'Value Added|Taxes on products',
+ 'DB HH CONSUMPTION': 'Expenditure|Household',
+ 'DB HH CONSUMPTION COICOP': 'Households|Savings|Real',
+ 'DB HH CONSUMPTION COICOP NOMINAL': 'Households|Savings',
+ 'DB HH DISPOSABLE INCOME': 'Households|Consumption|COICOP',
+ 'DB HH DISPOSABLE INCOME NOMINAL': 'Households|Consumption nominal|COICOP',
+ 'DB HH SAVINGS': 'Revenues|Households|Disposable income|Nominal',
+ 'DB HH SAVINGS NOMINAL': 'GDP|Country [per capita]',
+ 'DB IMPORTS': 'Trade|Value|Imports',
+ 'DB LABOUR COMPENSATION': 'Value Added|Labour Compensation',
+ 'DB LABOUR FORCE': 'Labour Supply',
+ 'DB NET OPERATING SURPLUS': 'Value Added|Net Operating Surplus',
+ 'DB OTHER FINAL DEMAND': 'Final Demand|Other',
+ 'DB OUTPUT': 'Output',
+ 'DB TAXES PRODUCTION': 'Value Added|Taxes on production',
+ 'DB TRADE BALANCE': 'Trade|Value|Balance',
+ 'DB UNEMPLOYMENT RATE': 'Unemployment|Rate'}

Conversion-Script/Create_Variable_Dict/energy_dict.txt

@@ -2,9 +2,9 @@
  'FE_gas': 'Gas',
  'FE_heat': 'Heat',
  'FE_hydrogen': 'Hydrogen',
- 'FE_liquid': 'Liquid',
- 'FE_solid_bio': 'Solid|Biomass',
- 'FE_solid_fossil': 'Solid|Fossil',
+ 'FE_liquid': 'Liquids',
+ 'FE_solid_bio': 'Solids|Biomass',
+ 'FE_solid_fossil': 'Solids|Fossil',
  'PE_agriculture_products': 'Agriculture Products',
  'PE_coal': 'Coal',
  'PE_forestry_products': 'Forestry Products',
@@ -17,44 +17,44 @@
  'PE_solar': 'Solar',
  'PE_waste': 'Waste',
  'PE_wind': 'Wind',
- 'PROTRA_CHP_gas_fuels': 'Electricity and Heat|gas fuels|w/o CCS',
- 'PROTRA_CHP_gas_fuels_CCS': 'Electricity and Heat|gas fuels|w/ CCS',
+ 'PROTRA_CHP_gas_fuels': 'Electricity and Heat|Gas fuels|w/o CCS',
+ 'PROTRA_CHP_gas_fuels_CCS': 'Electricity and Heat|Gas fuels|w/ CCS',
  'PROTRA_CHP_geothermal_DEACTIVATED': 'Electricity and '
-                                      'Heat|geothermal|DEACTIVATED',
- 'PROTRA_CHP_liquid_fuels': 'Electricity and Heat|liquid fuels|w/o CCS',
- 'PROTRA_CHP_liquid_fuels_CCS': 'Electricity and Heat|liquid fuels|w/ CCS',
- 'PROTRA_CHP_solid_bio': 'Electricity and Heat|solid|biomass|w/o CCS',
- 'PROTRA_CHP_solid_bio_CCS': 'Electricity and Heat|solid|biomass|w/ CCS',
- 'PROTRA_CHP_solid_fossil': 'Electricity and Heat|solid|fossil|w/o CCS',
- 'PROTRA_CHP_solid_fossil_CCS': 'Electricity and Heat|solid|fossil|w/ CCS',
- 'PROTRA_CHP_waste': 'Electricity and Heat|waste',
- 'PROTRA_HP_gas_fuels': 'Heat|gas fuels',
- 'PROTRA_HP_geothermal': 'Heat|geothermal',
- 'PROTRA_HP_liquid_fuels': 'Heat|liquid fuels',
- 'PROTRA_HP_solar_DEACTIVATED': 'Heat|solar|DEACTIVATED',
- 'PROTRA_HP_solid_bio': 'Heat|solid|biomass',
- 'PROTRA_HP_solid_fossil': 'Heat|solid|fossil',
- 'PROTRA_HP_waste': 'Heat|waste',
- 'PROTRA_PP_gas_fuels': 'Electricity|gas fuels|w/o CCS',
- 'PROTRA_PP_gas_fuels_CCS': 'Electricity|gas fuels|w/ CCS',
- 'PROTRA_PP_geothermal': 'Electricity|geothermal',
- 'PROTRA_PP_hydropower_dammed': 'Electricity|hydro|dammed',
- 'PROTRA_PP_hydropower_run_of_river': 'Electricity|hydro|run of river',
- 'PROTRA_PP_liquid_fuels': 'Electricity|liquid fuels|w/o CCS',
- 'PROTRA_PP_liquid_fuels_CCS': 'Electricity|liquid fuels|w/ CCS',
- 'PROTRA_PP_nuclear': 'Electricity|nuclear',
- 'PROTRA_PP_oceanic': 'Electricity|ocean',
- 'PROTRA_PP_solar_CSP': 'Electricity|solar|CSP',
- 'PROTRA_PP_solar_open_space_PV': 'Electricity|solar|open space|PV',
- 'PROTRA_PP_solar_urban_PV': 'Electricity|solar|urban|PV',
- 'PROTRA_PP_solid_bio': 'Electricity|solid|biomass|w/o CCS',
- 'PROTRA_PP_solid_bio_CCS': 'Electricity|solid|biomass|w/ CCS',
- 'PROTRA_PP_solid_fossil': 'Electricity|solid|fossil|w/o CCS',
- 'PROTRA_PP_solid_fossil_CCS': 'Electricity|solid|fossil|w/ CCS',
- 'PROTRA_PP_waste': 'Electricity|waste|w/o CCS',
- 'PROTRA_PP_waste_CCS': 'Electricity|waste|w/ CCS',
- 'PROTRA_PP_wind_offshore': 'Electricity|wind|offshore',
- 'PROTRA_PP_wind_onshore': 'Electricity|wind|onshore',
+                                      'Heat|Geothermal|Deactivated',
+ 'PROTRA_CHP_liquid_fuels': 'Electricity and Heat|Liquid fuels|w/o CCS',
+ 'PROTRA_CHP_liquid_fuels_CCS': 'Electricity and Heat|Liquid fuels|w/ CCS',
+ 'PROTRA_CHP_solid_bio': 'Electricity and Heat|Solid|Biomass|w/o CCS',
+ 'PROTRA_CHP_solid_bio_CCS': 'Electricity and Heat|Solid|Biomass|w/ CCS',
+ 'PROTRA_CHP_solid_fossil': 'Electricity and Heat|Solid|Fossil|w/o CCS',
+ 'PROTRA_CHP_solid_fossil_CCS': 'Electricity and Heat|Solid|Fossil|w/ CCS',
+ 'PROTRA_CHP_waste': 'Electricity and Heat|Waste',
+ 'PROTRA_HP_gas_fuels': 'Heat|Gas fuels',
+ 'PROTRA_HP_geothermal': 'Heat|Geothermal',
+ 'PROTRA_HP_liquid_fuels': 'Heat|Liquid fuels',
+ 'PROTRA_HP_solar_DEACTIVATED': 'Heat|Solar|Deactivated',
+ 'PROTRA_HP_solid_bio': 'Heat|Solid|Biomass',
+ 'PROTRA_HP_solid_fossil': 'Heat|Solid|Fossil',
+ 'PROTRA_HP_waste': 'Heat|Waste',
+ 'PROTRA_PP_gas_fuels': 'Electricity|Gas fuels|w/o CCS',
+ 'PROTRA_PP_gas_fuels_CCS': 'Electricity|Gas fuels|w/ CCS',
+ 'PROTRA_PP_geothermal': 'Electricity|Geothermal',
+ 'PROTRA_PP_hydropower_dammed': 'Electricity|Hydro|Dammed',
+ 'PROTRA_PP_hydropower_run_of_river': 'Electricity|Hydro|Run of River',
+ 'PROTRA_PP_liquid_fuels': 'Electricity|Liquid fuels|w/o CCS',
+ 'PROTRA_PP_liquid_fuels_CCS': 'Electricity|Liquid fuels|w/ CCS',
+ 'PROTRA_PP_nuclear': 'Electricity|Nuclear',
+ 'PROTRA_PP_oceanic': 'Electricity|Ocean',
+ 'PROTRA_PP_solar_CSP': 'Electricity|Solar|Csp',
+ 'PROTRA_PP_solar_open_space_PV': 'Electricity|Solar|PV|Open Land',
+ 'PROTRA_PP_solar_urban_PV': 'Electricity|Solar|PV|Urban',
+ 'PROTRA_PP_solid_bio': 'Electricity|Solid|Biomass|w/o CCS',
+ 'PROTRA_PP_solid_bio_CCS': 'Electricity|Solid|Biomass|w/ CCS',
+ 'PROTRA_PP_solid_fossil': 'Electricity|Solid|Fossil|w/o CCS',
+ 'PROTRA_PP_solid_fossil_CCS': 'Electricity|Solid|Fossil|w/ CCS',
+ 'PROTRA_PP_waste': 'Electricity|Waste|w/o CCS',
+ 'PROTRA_PP_waste_CCS': 'Electricity|Waste|w/ CCS',
+ 'PROTRA_PP_wind_offshore': 'Electricity|Wind|Offshore',
+ 'PROTRA_PP_wind_onshore': 'Electricity|Wind|Onshore',
  'PROTRA_blending_gas_fuels': 'Gas Fuels',
  'PROTRA_blending_liquid_fuels': 'Liquid Fuels',
  'PROTRA_no_process_TI_hydrogen': 'Hydrogen',
@@ -64,6 +64,6 @@
  'TO_gas': 'Gas',
  'TO_heat': 'Heat',
  'TO_hydrogen': 'Hydrogen',
- 'TO_liquid': 'Liquid',
- 'TO_solid_bio': 'Solid Biomass',
- 'TO_solid_fossil': 'Solid Fossil'}
+ 'TO_liquid': 'Liquids',
+ 'TO_solid_bio': 'Solids|Biomass',
+ 'TO_solid_fossil': 'Solids|Fossil'}

Conversion-Script/Create_Variable_Dict/land_dict.txt

@@ -0,0 +1,12 @@
+{'CROPLAND IRRIGATED': 'Cropland|Irrigated',
+ 'CROPLAND RAINFED': 'Cropland|Rainfed',
+ 'FOREST MANAGED': 'Forest|Managed',
+ 'FOREST PLANTATIONS': 'Forest|Forestry|Harvested Area',
+ 'FOREST PRIMARY': 'Forest|Natural Forest',
+ 'GRASSLAND': 'Grassland',
+ 'OTHER LAND': 'Other',
+ 'SHRUBLAND': 'Shrubland',
+ 'SNOW ICE WATERBODIES': 'Snow and Ice Land',
+ 'SOLAR LAND': 'Built-up Area|Solar',
+ 'URBAN LAND': 'Built-up Area',
+ 'WETLAND': 'Water Ecosystems|Wetlands'}