{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Final project Part 3: Viz for others (Ian Chapman)\n", "# How much might renewable electricity generation reduce our carbon imprint?" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import bqplot\n", "import ipywidgets" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## I. WA total emissions per sector (bar chart)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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SourceSectorSubsectorCityCountyLocal Air Authority2012 total emissions (MTCO2e)2012 biogenic carbon dioxide (MTCO2e)2013 total emissions (MTCO2e)2013 biogenic carbon dioxide (MTCO2e)2014 total emissions (MTCO2e)2014 biogenic carbon dioxide (MTCO2e)2015 total emissions (MTCO2e)2015 biogenic carbon dioxide (MTCO2e)2016 total emissions (MTCO2e)2016 biogenic carbon dioxide (MTCO2e)2017 total emissions (MTCO2e)2017 biogenic carbon dioxide (MTCO2e)
0Agrium Kennewick Fertilizer Operations (KFO) -...ChemicalsNitric Acid ProductionKennewickBentonBenton Clean Air Agency146926.00.0154497.00.0132249.00.0155888.00.0151371.00.0144290.00.0
1Air Liquide - AnacortesChemicalsHydrogen ProductionAnacortesSkagitNorthwest Clean Air Agency63356.00.058995.00.064110.00.064413.00.060209.00.063461.00.0
2Alcoa Intalco Works - FerndaleMetalsAluminum ProductionFerndaleWhatcomEcology: Industrial Section1146835.00.01234637.00.01326684.00.01195786.00.01261364.00.01091665.00.0
3Alcoa Wenatchee Works - MalagaMetalsAluminum ProductionMalagaChelanEcology: Industrial Section306333.00.0318542.00.0354692.00.0331207.00.0898.00.00.00.0
4Alon Asphalt Company - SeattlePetroleum and Natural Gas SystemsOther Petroleum and Natural Gas SystemsSeattleKingPuget Sound Clean Air Agency15138.00.014336.00.016004.00.013688.00.014096.00.014818.00.0
5Ardagh Glass Inc. - SeattleMineralsGlass ProductionSeattleKingPuget Sound Clean Air Agency76257.00.080745.00.078044.00.076674.00.077845.00.075338.00.0
6Ascensus Specialties LLC - ElmaChemicalsOther ChemicalsElmaGrays HarborOlympic Region Clean Air Agency16809.00.017966.00.021231.00.017600.00.020802.00.021310.00.0
7Ash Grove Cement Company - SeattleMineralsCement ProductionSeattleKingPuget Sound Clean Air Agency305298.00.0354808.00.0522982.00.0495030.00.0383836.00.0355513.00.0
8Avista Corporation - WA State DOE Reporting - ...Petroleum and Natural Gas SystemsNatural Gas Local Distribution CompaniesSpokaneSpokaneSpokane Regional Clean Air Agency20992.00.016127.00.016420.00.022858.00.021120.00.023757.00.0
9Basic American Foods - Moses LakeFood ProductionPotato ProductsMoses LakeGrantEcology: Eastern Regional Office28205.00.028312.00.028982.00.031063.00.028977.00.030576.00.0
10Bio Energy Washington, LLC - Maple ValleyPower PlantsOther Power, Heating, or Cooling PlantsMaple ValleyKingPuget Sound Clean Air Agency13697.012800.028341.027018.028302.027006.030802.029306.029216.027510.028391.026962.0
11Boeing Commercial Airplanes - EverettManufacturingTransportationEverettSnohomishPuget Sound Clean Air Agency71463.00.073643.00.073522.00.066276.00.076191.00.080529.00.0
12Boeing Commercial Airplanes - Fabrication (Fre...ManufacturingTransportationPuyallupPiercePuget Sound Clean Air Agency22582.00.021969.00.021442.00.020833.00.019831.00.019893.00.0
13Boise Cascade Wood Products, LLC. Kettle Fall...Wood ProductsLumber MillsKettle FallsStevensEcology: Eastern Regional Office41052.040173.056886.056136.057413.056656.057294.056539.053752.053043.054397.053680.0
14Boise Cascade Wood Products, LLC. Kettle Fall...Wood ProductsEngineered WoodKettle FallsStevensEcology: Eastern Regional Office68360.064637.071186.068156.071069.068040.071151.068501.073564.070714.070889.054924.0
15Boise Paper - WallulaPulp and PaperKraft MillsWallulaWalla WallaEcology: Industrial Section925349.0791371.0830754.0727045.0887912.0765685.0855520.0717427.0804657.0645182.0681208.0528740.0
16Bonneville Power Administration - WA Only - st...Power PlantsUse of Electrical EquipmentVancouverClarkSouthwest Clean Air Agency26927.00.042114.00.012800.00.014245.00.017121.00.015069.00.0
17Boulder Park Generating Station - Spokane ValleyPower PlantsOther Power, Heating, or Cooling PlantsSpokane ValleySpokaneSpokane Regional Clean Air Agency2700.00.010795.00.07552.00.010952.00.09009.00.013286.00.0
18BP Cherry Point Refinery - BlaineRefineriesPetroleum RefineriesBlaineWhatcomNorthwest Clean Air Agency2223518.00.02552655.00.02301576.00.02093437.00.02418086.00.02131918.00.0
19Cardinal FG Company - WinlockMineralsGlass ProductionWinlockLewisSouthwest Clean Air Agency92356.00.0102904.00.0102813.00.0105009.00.0107291.00.0107590.00.0
20Cascade Natural Gas Corporation LDC - statewidePetroleum and Natural Gas SystemsNatural Gas Local Distribution CompaniesKennewickBentonBenton Clean Air Agency12622.00.012940.00.013506.00.022852.00.023616.00.026227.00.0
21Cathcart Landfill - SnohomishWasteMunicipal LandfillsSnohomishSnohomishPuget Sound Clean Air Agency27653.00.023893.00.022454.00.023520.00.017417.00.028273.00.0
22Central Washington University - EllensburgGovernmentEducationEllensburgKittitasEcology: Central Regional Office13358.00.013451.00.013673.00.012838.00.012449.00.013669.00.0
23CertainTeed Gypsum - SeattleManufacturingGypsum ManufacturingSeattleKingPuget Sound Clean Air Agency35650.00.035465.00.036299.00.038141.00.047948.00.050452.00.0
24Cheyne Landfill - ZillahWasteMunicipal LandfillsZillahYakimaYakima Regional Clean Air Agency30500.00.031807.00.033147.00.034450.00.035837.00.037331.00.0
26City of Tacoma Solid Waste Facility - TacomaWasteMunicipal LandfillsTacomaPiercePuget Sound Clean Air Agency31986.00.026643.00.020396.00.014812.00.014513.00.016417.00.0
27ConAgra Foods Lamb Weston - ConnellFood ProductionPotato ProductsConnellFranklinEcology: Eastern Regional Office39714.00.039841.00.038810.00.036801.00.037212.00.035862.00.0
28ConAgra Foods Lamb Weston - QuincyFood ProductionPotato ProductsQuincyGrantEcology: Eastern Regional Office39693.00.039846.00.038324.00.037922.00.040468.00.034928.00.0
29Cosmo Specialty Fibers Inc - CosmopolisPulp and PaperSulfite MillsCosmopolisGrays HarborEcology: Industrial Section1186972.01150934.01105362.01078626.01185707.01152820.01170393.01144912.0989316.0963065.0701686.0676644.0
30Cowlitz County Headquarters Landfill - Castle ...WasteMunicipal LandfillsCastle RockCowlitzSouthwest Clean Air Agency121597.0659.0129060.0556.0154619.01205.0190202.02097.0178854.07724.0218522.011096.0
.........................................................
152Waste Management Greater Wenatchee Regional La...WasteMunicipal LandfillsEast WenatcheeDouglasEcology: Central Regional Office36141.00.031854.00.032740.00.031208.00.030653.00.027951.00.0
153WestRock CP, LLC - TacomaPulp and PaperKraft MillsTacomaPierceEcology: Industrial Section1082809.0940615.01039284.0925083.01173531.01059608.01135442.01011954.01134873.01011165.01124426.01000676.0
154Weyerhaeuser Raymond Lumber - RaymondWood ProductsLumber MillsRaymondPacificOlympic Region Clean Air Agency45768.044790.047339.046369.048445.047806.046229.045632.046747.046747.048561.047921.0
156Ascent Aviation Group IncTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN18223.00.015728.00.044724.00.066762.00.066269.00.045678.00.0
157Associated Petroleum Products, Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN1003689.00.01054993.036292.01325248.045274.01686102.058808.01990731.065716.02330279.076484.0
158Avfuel CorporationTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN41989.00.067999.00.083459.00.075236.00.032347.00.0103100.00.0
159BP West Coast Products LLCTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN7291311.00.06053769.00.05866602.00.06092051.00.05544958.00.04814803.00.0
160Chevron U.S.A. Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN2921033.0180260.03096698.0190620.03154826.0193502.03093693.0190217.03079994.0190121.03028590.0187837.0
161CHS INC.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN618830.029251.0613851.09449.0691788.037979.0705927.00.0713406.00.0707879.00.0
162CityServiceValcon LLCTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN174415.0394.0325002.015275.0358213.017373.0384845.019040.0396231.017935.0396100.01905.0
167Equilon Enterprises LLC dba Shell Oil Products USTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN3115901.0163141.03566781.00.03813545.00.04523704.00.05292512.00.05985748.00.0
168ExxonMobil Oil CorporationTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN789950.047558.0963246.061463.0859726.054950.0903301.058167.0831233.053419.0867077.055933.0
171IPC (USA), Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN198273.00.0321387.00.0395591.00.033803.00.014772.014.0NaNNaN
172PetroCard Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaNNaNNaNNaNNaNNaNNaN529844.00.0191708.07558.01066990.034044.0
174Phillips 66 CompanyTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN4416054.0218663.04941002.0268520.05276097.0290281.05252409.0285529.04761013.0266360.03907576.0225513.0
176RPMG, Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN452188.0452188.0371271.0371271.0338028.0338028.0401017.0401017.0448981.0448981.097522.097522.0
177SEI Fuel Services, Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN381994.025484.0358202.023907.0396729.026479.0312704.020572.0346741.020812.0316171.020344.0
178Sinclair Oil CorporationTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN15653.00.021056.00.057314.00.089794.00.0122139.00.0163446.00.0
179Southern Counties Oil Co LtdTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN111922.05812.0119268.06290.096845.04022.0106342.02231.097613.03327.068529.01554.0
180Targa Sound TerminalTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN81445.027441.019092.07800.019757.06378.014436.08114.017924.08021.014527.03411.0
181Tesoro Refining & Marketing Company LLCTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN6158377.00.05740456.00.05713367.00.05604007.0266252.05228903.0273546.05081912.0273012.0
182The Boeing CompanyTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN107661.00.0126519.00.0129491.00.0118525.00.0120830.00.0129232.00.0
183U.S. Oil & Refining Co.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN1159448.00.01175482.00.01310797.00.01292825.00.01288944.00.01177990.00.0
184United Parcel Service CoTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN62859.00.047767.00.050987.00.050052.00.056975.00.062975.00.0
185UPS Fuel Services, Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN31398.00.031599.00.032640.00.032845.00.033450.00.034518.00.0
186Valero Marketing and Supply CompanyTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN162579.010502.0126614.08077.0111391.07758.0110012.06829.033485.02205.027291.01797.0
187Vitol Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN725057.042882.0466188.027546.014658.0921.012307.0788.01551.0104.098.07.0
188Western Petroleum CompanyTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN63500.0457.019420.0685.021216.0463.011132.048.019449.0478.012906.0239.0
189Wilson Oil IncTransportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN1232072.050925.01197669.046854.01193047.047740.01157609.046220.01207292.049518.01251997.051446.0
190World Fuel Services, Inc.Transportation Fuel SupplierTransportation Fuel SupplierNaN(Statewide)NaN262127.04796.0235658.05443.0242219.05476.0326040.05479.0401673.05634.0314725.03016.0
\n", "

177 rows × 18 columns

\n", "
" ], "text/plain": [ " Source \\\n", "0 Agrium Kennewick Fertilizer Operations (KFO) -... \n", "1 Air Liquide - Anacortes \n", "2 Alcoa Intalco Works - Ferndale \n", "3 Alcoa Wenatchee Works - Malaga \n", "4 Alon Asphalt Company - Seattle \n", "5 Ardagh Glass Inc. - Seattle \n", "6 Ascensus Specialties LLC - Elma \n", "7 Ash Grove Cement Company - Seattle \n", "8 Avista Corporation - WA State DOE Reporting - ... \n", "9 Basic American Foods - Moses Lake \n", "10 Bio Energy Washington, LLC - Maple Valley \n", "11 Boeing Commercial Airplanes - Everett \n", "12 Boeing Commercial Airplanes - Fabrication (Fre... \n", "13 Boise Cascade Wood Products, LLC. Kettle Fall... \n", "14 Boise Cascade Wood Products, LLC. Kettle Fall... \n", "15 Boise Paper - Wallula \n", "16 Bonneville Power Administration - WA Only - st... \n", "17 Boulder Park Generating Station - Spokane Valley \n", "18 BP Cherry Point Refinery - Blaine \n", "19 Cardinal FG Company - Winlock \n", "20 Cascade Natural Gas Corporation LDC - statewide \n", "21 Cathcart Landfill - Snohomish \n", "22 Central Washington University - Ellensburg \n", "23 CertainTeed Gypsum - Seattle \n", "24 Cheyne Landfill - Zillah \n", "26 City of Tacoma Solid Waste Facility - Tacoma \n", "27 ConAgra Foods Lamb Weston - Connell \n", "28 ConAgra Foods Lamb Weston - Quincy \n", "29 Cosmo Specialty Fibers Inc - Cosmopolis \n", "30 Cowlitz County Headquarters Landfill - Castle ... \n", ".. ... \n", "152 Waste Management Greater Wenatchee Regional La... \n", "153 WestRock CP, LLC - Tacoma \n", "154 Weyerhaeuser Raymond Lumber - Raymond \n", "156 Ascent Aviation Group Inc \n", "157 Associated Petroleum Products, Inc. \n", "158 Avfuel Corporation \n", "159 BP West Coast Products LLC \n", "160 Chevron U.S.A. Inc. \n", "161 CHS INC. \n", "162 CityServiceValcon LLC \n", "167 Equilon Enterprises LLC dba Shell Oil Products US \n", "168 ExxonMobil Oil Corporation \n", "171 IPC (USA), Inc. \n", "172 PetroCard Inc. \n", "174 Phillips 66 Company \n", "176 RPMG, Inc. \n", "177 SEI Fuel Services, Inc. \n", "178 Sinclair Oil Corporation \n", "179 Southern Counties Oil Co Ltd \n", "180 Targa Sound Terminal \n", "181 Tesoro Refining & Marketing Company LLC \n", "182 The Boeing Company \n", "183 U.S. Oil & Refining Co. \n", "184 United Parcel Service Co \n", "185 UPS Fuel Services, Inc. \n", "186 Valero Marketing and Supply Company \n", "187 Vitol Inc. \n", "188 Western Petroleum Company \n", "189 Wilson Oil Inc \n", "190 World Fuel Services, Inc. \n", "\n", " Sector \\\n", "0 Chemicals \n", "1 Chemicals \n", "2 Metals \n", "3 Metals \n", "4 Petroleum and Natural Gas Systems \n", "5 Minerals \n", "6 Chemicals \n", "7 Minerals \n", "8 Petroleum and Natural Gas Systems \n", "9 Food Production \n", "10 Power Plants \n", "11 Manufacturing \n", "12 Manufacturing \n", "13 Wood Products \n", "14 Wood Products \n", "15 Pulp and Paper \n", "16 Power Plants \n", "17 Power Plants \n", "18 Refineries \n", "19 Minerals \n", "20 Petroleum and Natural Gas Systems \n", "21 Waste \n", "22 Government \n", "23 Manufacturing \n", "24 Waste \n", "26 Waste \n", "27 Food Production \n", "28 Food Production \n", "29 Pulp and Paper \n", "30 Waste \n", ".. ... \n", "152 Waste \n", "153 Pulp and Paper \n", "154 Wood Products \n", "156 Transportation Fuel Supplier \n", "157 Transportation Fuel Supplier \n", "158 Transportation Fuel Supplier \n", "159 Transportation Fuel Supplier \n", "160 Transportation Fuel Supplier \n", "161 Transportation Fuel Supplier \n", "162 Transportation Fuel Supplier \n", "167 Transportation Fuel Supplier \n", "168 Transportation Fuel Supplier \n", "171 Transportation Fuel Supplier \n", "172 Transportation Fuel Supplier \n", "174 Transportation Fuel Supplier \n", "176 Transportation Fuel Supplier \n", "177 Transportation Fuel Supplier \n", "178 Transportation Fuel Supplier \n", "179 Transportation Fuel Supplier \n", "180 Transportation Fuel Supplier \n", "181 Transportation Fuel Supplier \n", "182 Transportation Fuel Supplier \n", "183 Transportation Fuel Supplier \n", "184 Transportation Fuel Supplier \n", "185 Transportation Fuel Supplier \n", "186 Transportation Fuel Supplier \n", "187 Transportation Fuel Supplier \n", "188 Transportation Fuel Supplier \n", "189 Transportation Fuel Supplier \n", "190 Transportation Fuel Supplier \n", "\n", " Subsector City County \\\n", "0 Nitric Acid Production Kennewick Benton \n", "1 Hydrogen Production Anacortes Skagit \n", "2 Aluminum Production Ferndale Whatcom \n", "3 Aluminum Production Malaga Chelan \n", "4 Other Petroleum and Natural Gas Systems Seattle King \n", "5 Glass Production Seattle King \n", "6 Other Chemicals Elma Grays Harbor \n", "7 Cement Production Seattle King \n", "8 Natural Gas Local Distribution Companies Spokane Spokane \n", "9 Potato Products Moses Lake Grant \n", "10 Other Power, Heating, or Cooling Plants Maple Valley King \n", "11 Transportation Everett Snohomish \n", "12 Transportation Puyallup Pierce \n", "13 Lumber Mills Kettle Falls Stevens \n", "14 Engineered Wood Kettle Falls Stevens \n", "15 Kraft Mills Wallula Walla Walla \n", "16 Use of Electrical Equipment Vancouver Clark \n", "17 Other Power, Heating, or Cooling Plants Spokane Valley Spokane \n", "18 Petroleum Refineries Blaine Whatcom \n", "19 Glass Production Winlock Lewis \n", "20 Natural Gas Local Distribution Companies Kennewick Benton \n", "21 Municipal Landfills Snohomish Snohomish \n", "22 Education Ellensburg Kittitas \n", "23 Gypsum Manufacturing Seattle King \n", "24 Municipal Landfills Zillah Yakima \n", "26 Municipal Landfills Tacoma Pierce \n", "27 Potato Products Connell Franklin \n", "28 Potato Products Quincy Grant \n", "29 Sulfite Mills Cosmopolis Grays Harbor \n", "30 Municipal Landfills Castle Rock Cowlitz \n", ".. ... ... ... \n", "152 Municipal Landfills East Wenatchee Douglas \n", "153 Kraft Mills Tacoma Pierce \n", "154 Lumber Mills Raymond Pacific \n", "156 Transportation Fuel Supplier NaN (Statewide) \n", "157 Transportation Fuel Supplier NaN (Statewide) \n", "158 Transportation Fuel Supplier NaN (Statewide) \n", "159 Transportation Fuel Supplier NaN (Statewide) \n", "160 Transportation Fuel Supplier NaN (Statewide) \n", "161 Transportation Fuel Supplier NaN (Statewide) \n", "162 Transportation Fuel Supplier NaN (Statewide) \n", "167 Transportation Fuel Supplier NaN (Statewide) \n", "168 Transportation Fuel Supplier NaN (Statewide) \n", "171 Transportation Fuel Supplier NaN (Statewide) \n", "172 Transportation Fuel Supplier NaN (Statewide) \n", "174 Transportation Fuel Supplier NaN (Statewide) \n", "176 Transportation Fuel Supplier NaN (Statewide) \n", "177 Transportation Fuel Supplier NaN (Statewide) \n", "178 Transportation Fuel Supplier NaN (Statewide) \n", "179 Transportation Fuel Supplier NaN (Statewide) \n", "180 Transportation Fuel Supplier NaN (Statewide) \n", "181 Transportation Fuel Supplier NaN (Statewide) \n", "182 Transportation Fuel Supplier NaN (Statewide) \n", "183 Transportation Fuel Supplier NaN (Statewide) \n", "184 Transportation Fuel Supplier NaN (Statewide) \n", "185 Transportation Fuel Supplier NaN (Statewide) \n", "186 Transportation Fuel Supplier NaN (Statewide) \n", "187 Transportation Fuel Supplier NaN (Statewide) \n", "188 Transportation Fuel Supplier NaN (Statewide) \n", "189 Transportation Fuel Supplier NaN (Statewide) \n", "190 Transportation Fuel Supplier NaN (Statewide) \n", "\n", " Local Air Authority 2012 total emissions (MTCO2e) \\\n", "0 Benton Clean Air Agency 146926.0 \n", "1 Northwest Clean Air Agency 63356.0 \n", "2 Ecology: Industrial Section 1146835.0 \n", "3 Ecology: Industrial Section 306333.0 \n", "4 Puget Sound Clean Air Agency 15138.0 \n", "5 Puget Sound Clean Air Agency 76257.0 \n", "6 Olympic Region Clean Air Agency 16809.0 \n", "7 Puget Sound Clean Air Agency 305298.0 \n", "8 Spokane Regional Clean Air Agency 20992.0 \n", "9 Ecology: Eastern Regional Office 28205.0 \n", "10 Puget Sound Clean Air Agency 13697.0 \n", "11 Puget Sound Clean Air Agency 71463.0 \n", "12 Puget Sound Clean Air Agency 22582.0 \n", "13 Ecology: Eastern Regional Office 41052.0 \n", "14 Ecology: Eastern Regional Office 68360.0 \n", "15 Ecology: Industrial Section 925349.0 \n", "16 Southwest Clean Air Agency 26927.0 \n", "17 Spokane Regional Clean Air Agency 2700.0 \n", "18 Northwest Clean Air Agency 2223518.0 \n", "19 Southwest Clean Air Agency 92356.0 \n", "20 Benton Clean Air Agency 12622.0 \n", "21 Puget Sound Clean Air Agency 27653.0 \n", "22 Ecology: Central Regional Office 13358.0 \n", "23 Puget Sound Clean Air Agency 35650.0 \n", "24 Yakima Regional Clean Air Agency 30500.0 \n", "26 Puget Sound Clean Air Agency 31986.0 \n", "27 Ecology: Eastern Regional Office 39714.0 \n", "28 Ecology: Eastern Regional Office 39693.0 \n", "29 Ecology: Industrial Section 1186972.0 \n", "30 Southwest Clean Air Agency 121597.0 \n", ".. ... ... \n", "152 Ecology: Central Regional Office 36141.0 \n", "153 Ecology: Industrial Section 1082809.0 \n", "154 Olympic Region Clean Air Agency 45768.0 \n", "156 NaN 18223.0 \n", "157 NaN 1003689.0 \n", "158 NaN 41989.0 \n", "159 NaN 7291311.0 \n", "160 NaN 2921033.0 \n", "161 NaN 618830.0 \n", "162 NaN 174415.0 \n", "167 NaN 3115901.0 \n", "168 NaN 789950.0 \n", "171 NaN 198273.0 \n", "172 NaN NaN \n", "174 NaN 4416054.0 \n", "176 NaN 452188.0 \n", "177 NaN 381994.0 \n", "178 NaN 15653.0 \n", "179 NaN 111922.0 \n", "180 NaN 81445.0 \n", "181 NaN 6158377.0 \n", "182 NaN 107661.0 \n", "183 NaN 1159448.0 \n", "184 NaN 62859.0 \n", "185 NaN 31398.0 \n", "186 NaN 162579.0 \n", "187 NaN 725057.0 \n", "188 NaN 63500.0 \n", "189 NaN 1232072.0 \n", "190 NaN 262127.0 \n", "\n", " 2012 biogenic carbon dioxide (MTCO2e) 2013 total emissions (MTCO2e) \\\n", "0 0.0 154497.0 \n", "1 0.0 58995.0 \n", "2 0.0 1234637.0 \n", "3 0.0 318542.0 \n", "4 0.0 14336.0 \n", "5 0.0 80745.0 \n", "6 0.0 17966.0 \n", "7 0.0 354808.0 \n", "8 0.0 16127.0 \n", "9 0.0 28312.0 \n", "10 12800.0 28341.0 \n", "11 0.0 73643.0 \n", "12 0.0 21969.0 \n", "13 40173.0 56886.0 \n", "14 64637.0 71186.0 \n", "15 791371.0 830754.0 \n", "16 0.0 42114.0 \n", "17 0.0 10795.0 \n", "18 0.0 2552655.0 \n", "19 0.0 102904.0 \n", "20 0.0 12940.0 \n", "21 0.0 23893.0 \n", "22 0.0 13451.0 \n", "23 0.0 35465.0 \n", "24 0.0 31807.0 \n", "26 0.0 26643.0 \n", "27 0.0 39841.0 \n", "28 0.0 39846.0 \n", "29 1150934.0 1105362.0 \n", "30 659.0 129060.0 \n", ".. ... ... \n", "152 0.0 31854.0 \n", "153 940615.0 1039284.0 \n", "154 44790.0 47339.0 \n", "156 0.0 15728.0 \n", "157 0.0 1054993.0 \n", "158 0.0 67999.0 \n", "159 0.0 6053769.0 \n", "160 180260.0 3096698.0 \n", "161 29251.0 613851.0 \n", "162 394.0 325002.0 \n", "167 163141.0 3566781.0 \n", "168 47558.0 963246.0 \n", "171 0.0 321387.0 \n", "172 NaN NaN \n", "174 218663.0 4941002.0 \n", "176 452188.0 371271.0 \n", "177 25484.0 358202.0 \n", "178 0.0 21056.0 \n", "179 5812.0 119268.0 \n", "180 27441.0 19092.0 \n", "181 0.0 5740456.0 \n", "182 0.0 126519.0 \n", "183 0.0 1175482.0 \n", "184 0.0 47767.0 \n", "185 0.0 31599.0 \n", "186 10502.0 126614.0 \n", "187 42882.0 466188.0 \n", "188 457.0 19420.0 \n", "189 50925.0 1197669.0 \n", "190 4796.0 235658.0 \n", "\n", " 2013 biogenic carbon dioxide (MTCO2e) 2014 total emissions (MTCO2e) \\\n", "0 0.0 132249.0 \n", "1 0.0 64110.0 \n", "2 0.0 1326684.0 \n", "3 0.0 354692.0 \n", "4 0.0 16004.0 \n", "5 0.0 78044.0 \n", "6 0.0 21231.0 \n", "7 0.0 522982.0 \n", "8 0.0 16420.0 \n", "9 0.0 28982.0 \n", "10 27018.0 28302.0 \n", "11 0.0 73522.0 \n", "12 0.0 21442.0 \n", "13 56136.0 57413.0 \n", "14 68156.0 71069.0 \n", "15 727045.0 887912.0 \n", "16 0.0 12800.0 \n", "17 0.0 7552.0 \n", "18 0.0 2301576.0 \n", "19 0.0 102813.0 \n", "20 0.0 13506.0 \n", "21 0.0 22454.0 \n", "22 0.0 13673.0 \n", "23 0.0 36299.0 \n", "24 0.0 33147.0 \n", "26 0.0 20396.0 \n", "27 0.0 38810.0 \n", "28 0.0 38324.0 \n", "29 1078626.0 1185707.0 \n", "30 556.0 154619.0 \n", ".. ... ... \n", "152 0.0 32740.0 \n", "153 925083.0 1173531.0 \n", "154 46369.0 48445.0 \n", "156 0.0 44724.0 \n", "157 36292.0 1325248.0 \n", "158 0.0 83459.0 \n", "159 0.0 5866602.0 \n", "160 190620.0 3154826.0 \n", "161 9449.0 691788.0 \n", "162 15275.0 358213.0 \n", "167 0.0 3813545.0 \n", "168 61463.0 859726.0 \n", "171 0.0 395591.0 \n", "172 NaN NaN \n", "174 268520.0 5276097.0 \n", "176 371271.0 338028.0 \n", "177 23907.0 396729.0 \n", "178 0.0 57314.0 \n", "179 6290.0 96845.0 \n", "180 7800.0 19757.0 \n", "181 0.0 5713367.0 \n", "182 0.0 129491.0 \n", "183 0.0 1310797.0 \n", "184 0.0 50987.0 \n", "185 0.0 32640.0 \n", "186 8077.0 111391.0 \n", "187 27546.0 14658.0 \n", "188 685.0 21216.0 \n", "189 46854.0 1193047.0 \n", "190 5443.0 242219.0 \n", "\n", " 2014 biogenic carbon dioxide (MTCO2e) 2015 total emissions (MTCO2e) \\\n", "0 0.0 155888.0 \n", "1 0.0 64413.0 \n", "2 0.0 1195786.0 \n", "3 0.0 331207.0 \n", "4 0.0 13688.0 \n", "5 0.0 76674.0 \n", "6 0.0 17600.0 \n", "7 0.0 495030.0 \n", "8 0.0 22858.0 \n", "9 0.0 31063.0 \n", "10 27006.0 30802.0 \n", "11 0.0 66276.0 \n", "12 0.0 20833.0 \n", "13 56656.0 57294.0 \n", "14 68040.0 71151.0 \n", "15 765685.0 855520.0 \n", "16 0.0 14245.0 \n", "17 0.0 10952.0 \n", "18 0.0 2093437.0 \n", "19 0.0 105009.0 \n", "20 0.0 22852.0 \n", "21 0.0 23520.0 \n", "22 0.0 12838.0 \n", "23 0.0 38141.0 \n", "24 0.0 34450.0 \n", "26 0.0 14812.0 \n", "27 0.0 36801.0 \n", "28 0.0 37922.0 \n", "29 1152820.0 1170393.0 \n", "30 1205.0 190202.0 \n", ".. ... ... \n", "152 0.0 31208.0 \n", "153 1059608.0 1135442.0 \n", "154 47806.0 46229.0 \n", "156 0.0 66762.0 \n", "157 45274.0 1686102.0 \n", "158 0.0 75236.0 \n", "159 0.0 6092051.0 \n", "160 193502.0 3093693.0 \n", "161 37979.0 705927.0 \n", "162 17373.0 384845.0 \n", "167 0.0 4523704.0 \n", "168 54950.0 903301.0 \n", "171 0.0 33803.0 \n", "172 NaN 529844.0 \n", "174 290281.0 5252409.0 \n", "176 338028.0 401017.0 \n", "177 26479.0 312704.0 \n", "178 0.0 89794.0 \n", "179 4022.0 106342.0 \n", "180 6378.0 14436.0 \n", "181 0.0 5604007.0 \n", "182 0.0 118525.0 \n", "183 0.0 1292825.0 \n", "184 0.0 50052.0 \n", "185 0.0 32845.0 \n", "186 7758.0 110012.0 \n", "187 921.0 12307.0 \n", "188 463.0 11132.0 \n", "189 47740.0 1157609.0 \n", "190 5476.0 326040.0 \n", "\n", " 2015 biogenic carbon dioxide (MTCO2e) 2016 total emissions (MTCO2e) \\\n", "0 0.0 151371.0 \n", "1 0.0 60209.0 \n", "2 0.0 1261364.0 \n", "3 0.0 898.0 \n", "4 0.0 14096.0 \n", "5 0.0 77845.0 \n", "6 0.0 20802.0 \n", "7 0.0 383836.0 \n", "8 0.0 21120.0 \n", "9 0.0 28977.0 \n", "10 29306.0 29216.0 \n", "11 0.0 76191.0 \n", "12 0.0 19831.0 \n", "13 56539.0 53752.0 \n", "14 68501.0 73564.0 \n", "15 717427.0 804657.0 \n", "16 0.0 17121.0 \n", "17 0.0 9009.0 \n", "18 0.0 2418086.0 \n", "19 0.0 107291.0 \n", "20 0.0 23616.0 \n", "21 0.0 17417.0 \n", "22 0.0 12449.0 \n", "23 0.0 47948.0 \n", "24 0.0 35837.0 \n", "26 0.0 14513.0 \n", "27 0.0 37212.0 \n", "28 0.0 40468.0 \n", "29 1144912.0 989316.0 \n", "30 2097.0 178854.0 \n", ".. ... ... \n", "152 0.0 30653.0 \n", "153 1011954.0 1134873.0 \n", "154 45632.0 46747.0 \n", "156 0.0 66269.0 \n", "157 58808.0 1990731.0 \n", "158 0.0 32347.0 \n", "159 0.0 5544958.0 \n", "160 190217.0 3079994.0 \n", "161 0.0 713406.0 \n", "162 19040.0 396231.0 \n", "167 0.0 5292512.0 \n", "168 58167.0 831233.0 \n", "171 0.0 14772.0 \n", "172 0.0 191708.0 \n", "174 285529.0 4761013.0 \n", "176 401017.0 448981.0 \n", "177 20572.0 346741.0 \n", "178 0.0 122139.0 \n", "179 2231.0 97613.0 \n", "180 8114.0 17924.0 \n", "181 266252.0 5228903.0 \n", "182 0.0 120830.0 \n", "183 0.0 1288944.0 \n", "184 0.0 56975.0 \n", "185 0.0 33450.0 \n", "186 6829.0 33485.0 \n", "187 788.0 1551.0 \n", "188 48.0 19449.0 \n", "189 46220.0 1207292.0 \n", "190 5479.0 401673.0 \n", "\n", " 2016 biogenic carbon dioxide (MTCO2e) 2017 total emissions (MTCO2e) \\\n", "0 0.0 144290.0 \n", "1 0.0 63461.0 \n", "2 0.0 1091665.0 \n", "3 0.0 0.0 \n", "4 0.0 14818.0 \n", "5 0.0 75338.0 \n", "6 0.0 21310.0 \n", "7 0.0 355513.0 \n", "8 0.0 23757.0 \n", "9 0.0 30576.0 \n", "10 27510.0 28391.0 \n", "11 0.0 80529.0 \n", "12 0.0 19893.0 \n", "13 53043.0 54397.0 \n", "14 70714.0 70889.0 \n", "15 645182.0 681208.0 \n", "16 0.0 15069.0 \n", "17 0.0 13286.0 \n", "18 0.0 2131918.0 \n", "19 0.0 107590.0 \n", "20 0.0 26227.0 \n", "21 0.0 28273.0 \n", "22 0.0 13669.0 \n", "23 0.0 50452.0 \n", "24 0.0 37331.0 \n", "26 0.0 16417.0 \n", "27 0.0 35862.0 \n", "28 0.0 34928.0 \n", "29 963065.0 701686.0 \n", "30 7724.0 218522.0 \n", ".. ... ... \n", "152 0.0 27951.0 \n", "153 1011165.0 1124426.0 \n", "154 46747.0 48561.0 \n", "156 0.0 45678.0 \n", "157 65716.0 2330279.0 \n", "158 0.0 103100.0 \n", "159 0.0 4814803.0 \n", "160 190121.0 3028590.0 \n", "161 0.0 707879.0 \n", "162 17935.0 396100.0 \n", "167 0.0 5985748.0 \n", "168 53419.0 867077.0 \n", "171 14.0 NaN \n", "172 7558.0 1066990.0 \n", "174 266360.0 3907576.0 \n", "176 448981.0 97522.0 \n", "177 20812.0 316171.0 \n", "178 0.0 163446.0 \n", "179 3327.0 68529.0 \n", "180 8021.0 14527.0 \n", "181 273546.0 5081912.0 \n", "182 0.0 129232.0 \n", "183 0.0 1177990.0 \n", "184 0.0 62975.0 \n", "185 0.0 34518.0 \n", "186 2205.0 27291.0 \n", "187 104.0 98.0 \n", "188 478.0 12906.0 \n", "189 49518.0 1251997.0 \n", "190 5634.0 314725.0 \n", "\n", " 2017 biogenic carbon dioxide (MTCO2e) \n", "0 0.0 \n", "1 0.0 \n", "2 0.0 \n", "3 0.0 \n", "4 0.0 \n", "5 0.0 \n", "6 0.0 \n", "7 0.0 \n", "8 0.0 \n", "9 0.0 \n", "10 26962.0 \n", "11 0.0 \n", "12 0.0 \n", "13 53680.0 \n", "14 54924.0 \n", "15 528740.0 \n", "16 0.0 \n", "17 0.0 \n", "18 0.0 \n", "19 0.0 \n", "20 0.0 \n", "21 0.0 \n", "22 0.0 \n", "23 0.0 \n", "24 0.0 \n", "26 0.0 \n", "27 0.0 \n", "28 0.0 \n", "29 676644.0 \n", "30 11096.0 \n", ".. ... \n", "152 0.0 \n", "153 1000676.0 \n", "154 47921.0 \n", "156 0.0 \n", "157 76484.0 \n", "158 0.0 \n", "159 0.0 \n", "160 187837.0 \n", "161 0.0 \n", "162 1905.0 \n", "167 0.0 \n", "168 55933.0 \n", "171 NaN \n", "172 34044.0 \n", "174 225513.0 \n", "176 97522.0 \n", "177 20344.0 \n", "178 0.0 \n", "179 1554.0 \n", "180 3411.0 \n", "181 273012.0 \n", "182 0.0 \n", "183 0.0 \n", "184 0.0 \n", "185 0.0 \n", "186 1797.0 \n", "187 7.0 \n", "188 239.0 \n", "189 51446.0 \n", "190 3016.0 \n", "\n", "[177 rows x 18 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ghg = pd.read_csv('WA_GHG_Reporting_Multi-Year_Dataset(county_mod).csv',\n", " na_values = {'2016 total emissions (MTCO2e)': ''})\n", "\n", "ghg = ghg.dropna(axis=0, subset=['2016 total emissions (MTCO2e)'])\n", "\n", "ghg\n", "\n", "\n", "# I have modified the ghg dataset as follows:\n", "# In the \"County\" column, \"NA\" is changed to \"(Statewide)\".\n", "# This allows data not ascribed to a given county to be included in the heatmap below.\n", "\n", "# Citation: Method for removing nulls in selected column adapted from: \n", "# https://stackoverflow.com/questions/49291740/delete-rows-if-there-are-null-values-in-a-specific-column-in-pandas-dataframe\n", "# (viewed 4/13/19)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": false }, "outputs": [], "source": [ "x = ghg['Sector']\n", "y = ghg['2016 total emissions (MTCO2e)']\n", "\n", "xnames = x.unique()\n", "ynames = y.unique()\n", "\n", "for i,xn in enumerate(xnames):\n", " mask = (x == xn)\n", " ynames[i] = y[mask].sum()\n", "\n", "x_sc = bqplot.OrdinalScale()\n", "y_sc = bqplot.LinearScale()\n", "\n", "x_ax = bqplot.Axis(scale = x_sc, \n", " label = 'Sector',\n", " label_offset = '60px',\n", " tick_rotate = 70,\n", " tick_style = {'font-size':'12px'},\n", " offset = {'scale':x_sc, 'value':'60px'})\n", "y_ax = bqplot.Axis(scale = y_sc, \n", " orientation = 'vertical', \n", " side = 'left',\n", " label = 'Emissions (MT CO2e)',\n", " label_offset = '50px')\n", "\n", "sect_bar = bqplot.Bars(x = xnames,\n", " y = ynames,\n", " color_mode = 'element',\n", " scales = {'x': x_sc, 'y': y_sc},\n", " opacities = [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5],\n", " interactions = {'click': 'select'},\n", " anchor_style = {'fill':'red'}, \n", " selected_style = {'fill':'red','opacity': 0.5},\n", " unselected_style = {'opacity': 1.0})\n", "\n", "\n", "fig_sect = bqplot.Figure(marks = [sect_bar],\n", " axes = [x_ax, y_ax],\n", " fig_margin = {'top':60, 'bottom':120, 'left':70, 'right':40},\n", " title = \"WA greenhouse gas emissions by sector, 2016\")\n", "\n", "# I have set \"opacities\" in bqplot.Bars to 0.5 for each of the 13 bars\n", "# (apparently you need to do them individually), to make the intruding tick labels visible. \n", "# But this has not worked: the bars remain fully opaque.\n", "# Setting \"opacity\" to 0.5 under \"unselected style\" does make the selected bar translucent." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interaction: Breakdown of sectors into subsectors (bar chart)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "x2 = ghg['Subsector'].values\n", "y2 = ghg['2016 total emissions (MTCO2e)'].values\n", "\n", "x2_sc = bqplot.OrdinalScale() \n", "y2_sc = bqplot.LinearScale()\n", "\n", "x2_ax = bqplot.Axis(scale = x2_sc,\n", " label = 'Subsector',\n", " label_offset = '70px',\n", " tick_values = x2,\n", " tick_rotate = 45,\n", " tick_style = {'font-size':'12px'})\n", "y2_ax = bqplot.Axis(scale = y2_sc,\n", " label = 'Emissions (MT CO2e)',\n", " label_offset = '50px',\n", " orientation = 'vertical',\n", " side = 'left')\n", "\n", "i = 0\n", "mask = (x.values == xnames[i])\n", "subsect = x2[mask]\n", "emis2 = y2[mask]\n", "\n", "emis2 = emis2[~pd.isnull(subsect)]\n", "subsect = subsect[~pd.isnull(subsect)]\n", "\n", "subsectu = np.unique(subsect)\n", "emis2u = [emis2[subsect == subsect[i]].sum() for i in range(len(subsectu)) ]\n", "\n", "subsect_bar = bqplot.Bars(x = subsectu,\n", " y = emis2u,\n", " color_mode = 'element',\n", " scales = {'x': x2_sc, 'y': y2_sc})\n", "\n", "fig_subsect = bqplot.Figure(marks = [subsect_bar], \n", " axes = [x2_ax, y2_ax],\n", " fig_margin = {'top':60, 'bottom':120, 'left':70, 'right':60},\n", " title = \"Emissions by subsector\")\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "63948300.0" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "emis_tot = ghg['2016 total emissions (MTCO2e)'].sum()\n", "emis_tot" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": false }, "outputs": [], "source": [ "mySelectedLabel1a = ipywidgets.Label()\n", "mySelectedLabel1b = ipywidgets.Label()\n", "\n", "def get_data_value(change):\n", " if change['owner'].selected is not None:\n", " i = change['owner'].selected[0]\n", " mask = (x.values == xnames[i])\n", " subsect = x2[mask]\n", " emis2 = y2[mask]\n", " emis2 = emis2[~pd.isnull(subsect)]\n", " subsect = subsect[~pd.isnull(subsect)]\n", " subsectu = np.unique(subsect)\n", " emis2 = [emis2[subsect == subsectu[b]].sum() for b in range(len(subsectu)) ]\n", " emis2 = np.array(emis2)\n", " v = emis2.sum()\n", " pct = v/emis_tot*100\n", " mySelectedLabel1a.value = 'Sector GHG emissions = ' + str(v)\n", " mySelectedLabel1b.value = 'Percentage of total = ' + str(round(pct,1))\n", " subsect_bar.x = subsectu\n", " subsect_bar.y = emis2\n", "\n", "sect_bar.observe(get_data_value, 'selected')\n", "\n", "fig_sect.layout.max_width = '500px'\n", "fig_sect.layout.max_height= '500px'\n", "fig_subsect.layout.max_width='300px'\n", "fig_subsect.layout.max_height='400px'\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## II. Comparison: US GHG sector breakdown" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "epa_raw = pd.read_csv('EPA sectors 1990-2017.csv')\n", "\n", "exclude = ['Total', 'U.S. territories']\n", "\n", "epa = epa_raw[~epa_raw['Economic Sector'].isin(exclude)]\n", "\n", "# Citation: Pandas dataframe filter method adapted from:\n", "# https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isin.html\n", "# (viewed 4/18/19)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "xE = epa['Economic Sector']\n", "yE = epa['2016']\n", "\n", "xEnames = xE.unique()\n", "yEnames = yE.unique()\n", "\n", "for i,xEn in enumerate(xEnames):\n", " maskE = (xE == xEn)\n", " yEnames[i] = yE[maskE].sum()\n", "\n", "xE_sc = bqplot.OrdinalScale()\n", "yE_sc = bqplot.LinearScale()\n", "\n", "xE_ax = bqplot.Axis(scale = xE_sc, \n", " label = 'Sector',\n", " label_offset = '60px',\n", " tick_rotate = 45,\n", "# tick_style = {'font-size':'10px', 'tick_offset':'100px','text_anchor':'top'})\n", " tick_style = {'font-size':'12px'},\n", " offset = {'scale':x_sc, 'value':'60px'})\n", "yE_ax = bqplot.Axis(scale = yE_sc, \n", " orientation = 'vertical', \n", " side = 'left',\n", " label = 'Emissions (MT CO2e)',\n", " label_offset = '50px')\n", "\n", "epa_bar = bqplot.Bars(x = xEnames,\n", " y = yEnames,\n", " color_mode = 'element',\n", " scales = {'x': xE_sc, 'y': yE_sc},\n", " interactions = {'click': 'select'},\n", " anchor_style = {'fill':'red'}, \n", " selected_style = {'fill':'red','opacity': 0.5},\n", " unselected_style = {'opacity': 1.0})\n", "\n", "\n", "fig_epa = bqplot.Figure(marks = [epa_bar],\n", " axes = [xE_ax, yE_ax],\n", " fig_margin = {'top':60, 'bottom':120, 'left':70, 'right':60},\n", " title = \"US greenhouse gas emissions by sector, 2016\")\n", "\n", "\n", "fig_epa.layout.max_width = '500px'\n", "fig_epa.layout.max_height= '500px'\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interaction: Selected Label" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": false }, "outputs": [], "source": [ "emisE_tot = epa['2016'].sum()\n", "emisE_tot\n", "\n", "mySelectedLabelEa = ipywidgets.Label()\n", "mySelectedLabelEb = ipywidgets.Label()\n", "\n", "\n", "def get_data_valueE(change):\n", " if change['owner'].selected is not None:\n", " i = change['owner'].selected[0]\n", " maskE = (xE.values == xEnames[i])\n", " sectE = xE[maskE]\n", " emisE = yE[maskE]\n", " emisE = emisE[~pd.isnull(sectE)]\n", " sectE = sectE[~pd.isnull(sectE)]\n", " sectEu = np.unique(sectE)\n", " emisEu = [emisE[sectE == sectEu[b]].sum() for b in range(len(sectEu)) ]\n", " emisEu = np.array(emisEu)\n", " vE = emisEu.sum()\n", " pctE = vE/emisE_tot*100\n", " mySelectedLabelEa.value = 'US sector GHG emissions = ' + str(vE)\n", " mySelectedLabelEb.value = 'Percentage of total = ' + str(round(pctE,1))\n", " \n", "epa_bar.observe(get_data_valueE, 'selected')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## III. WA economic sector, county, emissions (heat map)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "x3 = ghg['Sector']\n", "y3 = ghg['County']\n", "z3 = ghg['2016 total emissions (MTCO2e)']\n", "\n", "x3names = x3.unique()\n", "y3names = y3.unique()\n", "z3names = np.zeros([len(x3names),len(y3names)])\n", "\n", "for i,x3n in enumerate(x3names):\n", " for j, y3n in enumerate(y3names):\n", " mask3 = (x3 == x3n) & (y3 == y3n)\n", " z3names[i,j] = z3[mask3].sum()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Ian\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:21: RuntimeWarning: divide by zero encountered in log10\n" ] } ], "source": [ "col_sc = bqplot.ColorScale(scheme=\"RdPu\")\n", "x3_sc = bqplot.OrdinalScale()\n", "y3_sc = bqplot.OrdinalScale()\n", "\n", "c_ax = bqplot.ColorAxis(scale = col_sc, \n", " orientation = 'vertical', \n", " side = 'right')\n", "\n", "x3_ax = bqplot.Axis(scale = x3_sc,\n", " label='County',\n", " label_offset = '50px',\n", " tick_rotate=90,\n", " tick_style = {'font-size':'12px'},\n", " offset = {'scale':x3_sc, 'value':'50'})\n", "y3_ax = bqplot.Axis(scale = y3_sc, \n", " orientation = 'vertical', \n", " label = 'Sector',\n", " label_offset = '120px',\n", " tick_style = {'font-size':'12px'})\n", "\n", "heat_map = bqplot.GridHeatMap(color = np.log10(z3names),\n", " row = x3names, \n", " column = y3names,\n", " scales = {'color': col_sc,\n", " 'row': y3_sc,\n", " 'column': x3_sc},\n", " interactions = {'click': 'select'},\n", " anchor_style = {'fill':'blue'}, \n", " selected_style = {'opacity': 1.0},\n", " unselected_style = {'opacity': 1.0})\n", "\n", "fig_hm = bqplot.Figure(marks = [heat_map],\n", " axes = [c_ax, y3_ax, x3_ax], \n", " fig_margin = dict(top=60, bottom=80, left=200, right=50),\n", " title = \"WA greenhouse gas emissions by sector and county, 2016\")\n", "\n", "fig_hm.layout.width = '900px'\n", "fig_hm.layout.height= '500px'\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interaction: Emissions per subsector per county (bar chart)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "x4 = ghg['Subsector'].values\n", "y4 = ghg['2016 total emissions (MTCO2e)'].values\n", "\n", "x4_sc = bqplot.OrdinalScale() \n", "y4_sc = bqplot.LinearScale()\n", "\n", "x4_ax = bqplot.Axis(scale=x4_sc,\n", " label='Subsector',\n", " label_offset = '40px',\n", " tick_rotate=10,\n", " tick_style={'font-size':'12px'})\n", "y4_ax = bqplot.Axis(scale=y4_sc,\n", " label='Emissions (MT CO2e)',\n", " label_offset = '50px',\n", " orientation='vertical') \n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "i,j = 0,0\n", "mask3 = (x3.values == x3names[i]) & (y3.values == y3names[j])\n", "subsect4 = x4[mask3]\n", "emis4 = y4[mask3]\n", "\n", "emis4 = emis4[~pd.isnull(subsect4)]\n", "subsect4 = subsect4[~pd.isnull(subsect4)]\n", "\n", "subsect4u = np.unique(subsect4)\n", "emis4u = [emis4[subsect4 == subsect4[i]].sum() for i in range(len(subsect4u)) ]" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "bar4 = bqplot.Bars(x = subsect4u,\n", " y = emis4u,\n", " color_mode = 'element',\n", " scales = {'x': x4_sc, 'y': y4_sc})\n", "\n", "fig_bar4 = bqplot.Figure(marks = [bar4],\n", " axes = [x4_ax, y4_ax],\n", " fig_margin = {'top':60, 'bottom':120, 'left':70, 'right':50},\n", " title = 'County emissions by subsector')\n", "\n", "fig_bar4.layout.max_width='300px'\n", "fig_bar4.layout.max_height='400px'\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "scrolled": false }, "outputs": [], "source": [ "mySelectedLabel2 = ipywidgets.Label()\n", "\n", "def get_data_value3(change):\n", " i,j = change['owner'].selected[0]\n", " mask3 = (x3.values == x3names[i]) & (y3.values == y3names[j])\n", " subsect4 = x4[mask3]\n", " emis4 = y4[mask3]\n", " emis4 = emis4[~pd.isnull(subsect4)]\n", " subsect4 = subsect4[~pd.isnull(subsect4)]\n", " subsect4u = np.unique(subsect4)\n", " emis4u = [emis4[subsect4 == subsect4u[b]].sum() for b in range(len(subsect4u)) ]\n", " emis4u = np.array(emis4u)\n", " v = emis4u.sum(),\n", " mySelectedLabel2.value = 'Sector GHG emissions for county = ' + str(v)\n", " bar4.x = subsect4u\n", " bar4.y = emis4u\n", " \n", "heat_map.observe(get_data_value3, 'selected')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Greenhouse gas generation: reading the data\n", "\n", "Nationally, power generation through fossil fuels is a major contributor to global warming. What impact might we expect from the wide scale adoption of renewable power sources? We look at the data from Washington, a state in which renewables - largely hydroelectricity - already account for 90% of electricity production. \n", "\n", "All data is from the year 2016, the most recent for which comparative datasets are available. Emissions are calculated in metric tons (MT) of carbon dioxide equivalents (CO2e), a measure which converts all greenhouse gases to an equivalent volume of carbon dioxide, to provide a basis for direct comparison.\n", "\n", "### 1. Breakdown by sector of Washington state's greenhouse gas emissions \n", "We begin by looking at Washington state's greenhouse gas emission profile. The visualization shows that electricity generation (power plants) accounts for almost 16% of the state's greenhouse gas production. This is a distant second to transportation fuel supply (51%); combined with the related industry of refining (10%), oil production and use production account for 61% of the state's emissions.\n", "\n", "How much variation is there within each sector? Click on the bar for a given sector to see the contributions of individual subsectors. For example, the \"Power plants\" breakdown shows that coal plants still account for the largest proportion of fossil-fuel power generation, though natural gas plants are catching up.\n", "\n", "Data is provided by the Washington Department of Ecology (available at: https://data.wa.gov/Natural-Resources-Environment/WA-GHG-Reporting-Multi-Year-Dataset/jbe2-ek4r). \n", "\n", " " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4a783499cac447649d4181dbd87ff486", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(Label(value=''), Label(value=''), HBox(children=(Figure(axes=[Axis(label='Sector', label_offset…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ipywidgets.VBox([mySelectedLabel1a, mySelectedLabel1b, ipywidgets.HBox([fig_sect, fig_subsect])])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2. Comparison with national averages\n", "How does Washington state's greenhouse gas profile compare with the US average? Differences in the structure of state and national datasets make precise comparison difficult. But one stark point of contrast leaps out: whereas in Washington state the carbon footprint of power plants is less than a third of that of the transport industry, nationally the two sectors run head-to-head as the biggest greenhouse gas emitters. This demonstrates the sizable scale of emissions reduction made possible by switching to green power generation. \n", "\n", "Data is provided by the United States Environmental Protection Agency (EPA) (available at:\n", "https://cfpub.epa.gov/ghgdata/inventoryexplorer/)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c64834fc3d5a49379e8bec457e5077af", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(Label(value=''), Label(value=''), Figure(axes=[Axis(label='Sector', label_offset='60px', offset…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ipywidgets.VBox([mySelectedLabelEa, mySelectedLabelEb, fig_epa])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3. Washington state: regional variation \n", "\n", "How consistent are industry practices across the state? Which regions and sectors should be targeted for further carbon footprint reductions? This heatmap and accompanying bar chart reveal considerable regional variation. If we look at power plants, we can see from the heatmap that Lewis county has the highest emissions. The interactive bar chart reveals this county is home to state's last surviving coal plant. Checking again the breakdown of power plant emissions statewide (first visualization), we see this single coal plant produces higher emissions than all other fossil-fuel power plants combined.\n", "\n", "Data is again from the Washington Department of Ecology dataset, cited above." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8190bdaef7b04038bb0461383294ee7d", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(Label(value=''), HBox(children=(Figure(axes=[ColorAxis(orientation='vertical', scale=ColorScale…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ipywidgets.VBox([mySelectedLabel2, ipywidgets.HBox([fig_hm, fig_bar4])])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![CountyMap](WashingtonMap.gif \"CountyMap\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Acknowledgements\n", "These visualizations adapt design features and a substantial amount of code from class examples and from the solution to the Assignment 6 problem provided by Dr. Jill Naiman (\"hwex.ipynb\", personal communication, 3/15/2019). I also thank Dr. Naiman for helping with numerous individual problems, and 590 DVO classmates for their valuable suggestions.\n", "\n", "Washington county map: http://www.dva.wa.gov/benefits/county-map (accessed 4/23/19)\n", "\n", "Code for embedding git file adapted from: https://stackoverflow.com/questions/51527868/how-do-i-embed-a-gif-in-jupyter-notebook (accessed 4/23/19)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 2 }