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Fix vanadium in wind turbines
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@alvarojhahn
alvarojhahn committed Oct 17, 2024
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Binary file added premise/data/metals/SI_2_Material_requirements.xlsx
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298 changes: 298 additions & 0 deletions premise/data/metals/intensities_xls_to_csv.ipynb
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"execution_count": 1,
"id": "670e8412-b0fc-4fe0-9ec0-e2e104e4827d",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3d2a97e4-5fca-48f3-84db-2e65e839de55",
"metadata": {},
"outputs": [],
"source": [
"file_path = 'SI_2_Material_requirements.xlsx'\n",
"xls = pd.ExcelFile(file_path)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "8bdf6ed4-ae0d-44d1-b0cf-537b4d27f976",
"metadata": {},
"outputs": [],
"source": [
"sheets_to_exclude = [\"Materials\", \"Technologies\", \"References\"]\n",
"sheets_to_include = [sheet for sheet in xls.sheet_names if sheet not in sheets_to_exclude]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "b7d94a6b-95ea-45ab-80e1-8f95b1ff5bd3",
"metadata": {},
"outputs": [],
"source": [
"combined_df = pd.DataFrame(columns=[\"metal\", \"unit\", \"year\", \"mean\", \"median\", \"min\", \"max\", \"origin_var\"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "2b2520af-a5fb-43d5-a9c4-60db6b5531de",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\hahnme_a\\AppData\\Local\\Temp\\ipykernel_20220\\936690025.py:8: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
" combined_df = pd.concat([combined_df, df], ignore_index=True)\n"
]
},
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>metal</th>\n",
" <th>unit</th>\n",
" <th>year</th>\n",
" <th>mean</th>\n",
" <th>median</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" <th>origin_var</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Aluminium</td>\n",
" <td>kg metal/kg vehicle</td>\n",
" <td>2020.0</td>\n",
" <td>0.245611</td>\n",
" <td>0.245611</td>\n",
" <td>2.456112e-01</td>\n",
" <td>0.245611</td>\n",
" <td>ICEV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Antimony</td>\n",
" <td>kg metal/kg vehicle</td>\n",
" <td>2020.0</td>\n",
" <td>0.001169</td>\n",
" <td>0.001134</td>\n",
" <td>7.428823e-04</td>\n",
" <td>0.001660</td>\n",
" <td>ICEV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Beryllium</td>\n",
" <td>kg metal/kg vehicle</td>\n",
" <td>2020.0</td>\n",
" <td>0.000003</td>\n",
" <td>0.000003</td>\n",
" <td>1.620822e-06</td>\n",
" <td>0.000004</td>\n",
" <td>ICEV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Cerium</td>\n",
" <td>kg metal/kg vehicle</td>\n",
" <td>2020.0</td>\n",
" <td>0.000016</td>\n",
" <td>0.000013</td>\n",
" <td>1.550000e-07</td>\n",
" <td>0.000049</td>\n",
" <td>ICEV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Cobalt</td>\n",
" <td>kg metal/kg vehicle</td>\n",
" <td>2020.0</td>\n",
" <td>0.003039</td>\n",
" <td>0.003562</td>\n",
" <td>1.948080e-03</td>\n",
" <td>0.003737</td>\n",
" <td>ICEV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>236</th>\n",
" <td>Praseodimium</td>\n",
" <td>kg/MW</td>\n",
" <td>2020.0</td>\n",
" <td>8.784196</td>\n",
" <td>8.784196</td>\n",
" <td>8.784196e+00</td>\n",
" <td>8.784196</td>\n",
" <td>HTEL - Yttrium</td>\n",
" </tr>\n",
" <tr>\n",
" <th>237</th>\n",
" <td>Strontium</td>\n",
" <td>kg/MW</td>\n",
" <td>2020.0</td>\n",
" <td>2.737974</td>\n",
" <td>2.396332</td>\n",
" <td>1.616888e+00</td>\n",
" <td>4.200702</td>\n",
" <td>HTEL - Yttrium</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>Yttrium</td>\n",
" <td>kg/MW</td>\n",
" <td>2020.0</td>\n",
" <td>50.875605</td>\n",
" <td>65.997099</td>\n",
" <td>1.156334e+01</td>\n",
" <td>75.066370</td>\n",
" <td>HTEL - Yttrium</td>\n",
" </tr>\n",
" <tr>\n",
" <th>239</th>\n",
" <td>Zirconium</td>\n",
" <td>kg/MW</td>\n",
" <td>2020.0</td>\n",
" <td>242.987230</td>\n",
" <td>271.390647</td>\n",
" <td>6.822289e+01</td>\n",
" <td>389.348155</td>\n",
" <td>HTEL - Yttrium</td>\n",
" </tr>\n",
" <tr>\n",
" <th>240</th>\n",
" <td>Yttrium</td>\n",
" <td>kg/MW</td>\n",
" <td>2050.0</td>\n",
" <td>6.016672</td>\n",
" <td>6.016672</td>\n",
" <td>4.700000e-01</td>\n",
" <td>11.563345</td>\n",
" <td>HTEL - Yttrium</td>\n",
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"text/plain": [
" metal unit year mean median \\\n",
"0 Aluminium kg metal/kg vehicle 2020.0 0.245611 0.245611 \n",
"1 Antimony kg metal/kg vehicle 2020.0 0.001169 0.001134 \n",
"2 Beryllium kg metal/kg vehicle 2020.0 0.000003 0.000003 \n",
"3 Cerium kg metal/kg vehicle 2020.0 0.000016 0.000013 \n",
"4 Cobalt kg metal/kg vehicle 2020.0 0.003039 0.003562 \n",
".. ... ... ... ... ... \n",
"236 Praseodimium kg/MW 2020.0 8.784196 8.784196 \n",
"237 Strontium kg/MW 2020.0 2.737974 2.396332 \n",
"238 Yttrium kg/MW 2020.0 50.875605 65.997099 \n",
"239 Zirconium kg/MW 2020.0 242.987230 271.390647 \n",
"240 Yttrium kg/MW 2050.0 6.016672 6.016672 \n",
"\n",
" min max origin_var \n",
"0 2.456112e-01 0.245611 ICEV \n",
"1 7.428823e-04 0.001660 ICEV \n",
"2 1.620822e-06 0.000004 ICEV \n",
"3 1.550000e-07 0.000049 ICEV \n",
"4 1.948080e-03 0.003737 ICEV \n",
".. ... ... ... \n",
"236 8.784196e+00 8.784196 HTEL - Yttrium \n",
"237 1.616888e+00 4.200702 HTEL - Yttrium \n",
"238 1.156334e+01 75.066370 HTEL - Yttrium \n",
"239 6.822289e+01 389.348155 HTEL - Yttrium \n",
"240 4.700000e-01 11.563345 HTEL - Yttrium \n",
"\n",
"[241 rows x 8 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"for sheet in sheets_to_include:\n",
" df = pd.read_excel(file_path, sheet_name=sheet, skiprows=2, header=None, usecols=\"A:G\")\n",
" df.columns = ['metal', 'unit', 'year', 'mean', 'median', 'min', 'max']\n",
" df = df.dropna(how='all')\n",
" df = df[df['metal'] != 'mean']\n",
" df[\"origin_var\"] = sheet\n",
" \n",
" combined_df = pd.concat([combined_df, df], ignore_index=True)\n",
" \n",
"combined_df"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "6bc56cef-de5e-48a6-983c-17f4519dd7c1",
"metadata": {},
"outputs": [],
"source": [
"output_file = 'metals_db.csv'\n",
"combined_df.to_csv(output_file, index=False)"
]
}
],
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