diff --git a/Data/Bioenergy quantification.xlsx b/Data/Bioenergy quantification.xlsx
index 20f3097..4d96276 100644
Binary files a/Data/Bioenergy quantification.xlsx and b/Data/Bioenergy quantification.xlsx differ
diff --git a/Data/EnergyBalance/2019/all_countries_df.csv b/Data/EnergyBalance/2019/all_countries_df.csv
index d334a7c..2d43f2b 100644
--- a/Data/EnergyBalance/2019/all_countries_df.csv
+++ b/Data/EnergyBalance/2019/all_countries_df.csv
@@ -1,796 +1,796 @@
 ,Country (2019),Transactions(down)/Commodity(right),Primary Coal and Peat,Coal and Peat Products,Primary Oil,Oil Products,Natural Gas,Biofuels and Waste,Nuclear,Electricity,Heat,Total Energy,memo: Of which Renewables,All Coal,All Oil,All Inputs
-0,Samoa,Primary production,0.0,0.0,0.0,0.0,0.0,1464.0,0.0,265.0,3.0,1732.0,1732.0,0.0,0.0,1467.0
-1,Samoa,Imports,0.0,0.0,0.0,4813.0,0.0,0.0,0.0,0.0,0.0,4814.0,0.0,0.0,4813.0,4813.0
-2,Samoa,Exports,0.0,0.0,0.0,-42.0,0.0,0.0,0.0,0.0,0.0,-42.0,0.0,0.0,-42.0,-42.0
-3,Samoa,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-4,Samoa,International aviation bunkers,0.0,0.0,0.0,-532.0,0.0,0.0,0.0,0.0,0.0,-532.0,0.0,0.0,-532.0,-532.0
-5,Samoa,Stock changes,0.0,0.0,0.0,-275.0,0.0,0.0,0.0,0.0,0.0,-275.0,0.0,0.0,-275.0,-275.0
-6,Samoa,Total energy supply,0.0,0.0,0.0,3965.0,0.0,1464.0,0.0,265.0,3.0,5697.0,1732.0,0.0,3965.0,5432.0
-7,Samoa,Statistical differences,0.0,0.0,0.0,-2.0,0.0,0.0,0.0,0.0,0.0,-2.0,265.0,0.0,-2.0,-2.0
-8,Samoa,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-9,Samoa,Transformation,0.0,0.0,0.0,-903.0,0.0,-14.0,0.0,344.0,0.0,-573.0,-14.0,0.0,-903.0,-917.0
-10,Samoa,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-903.0,0.0,0.0,0.0,344.0,0.0,-559.0,0.0,0.0,-903.0,-903.0
-11,Samoa,Electricity Plants,0.0,0.0,0.0,-903.0,0.0,0.0,0.0,344.0,0.0,-559.0,0.0,0.0,-903.0,-903.0
-12,Samoa,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-13,Samoa,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-14,Samoa,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-15,Samoa,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-16,Samoa,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-17,Samoa,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-18,Samoa,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-19,Samoa,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-20,Samoa,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-21,Samoa,Other transformation,0.0,0.0,0.0,0.0,0.0,-14.0,0.0,0.0,0.0,-14.0,-14.0,0.0,0.0,-14.0
-22,Samoa,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-1.0,0.0,-1.0,0.0,0.0,0.0,0.0
-23,Samoa,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-62.0,0.0,-62.0,0.0,0.0,0.0,0.0
-24,Samoa,Final consumption,0.0,0.0,0.0,3064.0,0.0,1450.0,0.0,546.0,3.0,5063.0,1453.0,0.0,3064.0,4517.0
-25,Samoa,Final Energy Consumption,0.0,0.0,0.0,2943.0,0.0,1450.0,0.0,546.0,3.0,4942.0,1453.0,0.0,2943.0,4396.0
-26,Samoa,Manufacturing  const. and mining,0.0,0.0,0.0,301.0,0.0,0.0,0.0,35.0,0.0,336.0,0.0,0.0,301.0,301.0
-27,Samoa,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-28,Samoa,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-29,Samoa,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-30,Samoa,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-31,Samoa,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-32,Samoa,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-33,Samoa,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-34,Samoa,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-35,Samoa,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-36,Samoa,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-37,Samoa,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-38,Samoa,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-39,Samoa,Industry n.e.s,0.0,0.0,0.0,301.0,0.0,0.0,0.0,35.0,0.0,336.0,0.0,0.0,301.0,301.0
-40,Samoa,Transport,0.0,0.0,0.0,2275.0,0.0,0.0,0.0,0.0,0.0,2275.0,0.0,0.0,2275.0,2275.0
-41,Samoa,Road,0.0,0.0,0.0,1931.0,0.0,0.0,0.0,0.0,0.0,1931.0,0.0,0.0,1931.0,1931.0
-42,Samoa,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-43,Samoa,Domestic aviation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-44,Samoa,Domestic navigation,0.0,0.0,0.0,344.0,0.0,0.0,0.0,0.0,0.0,344.0,0.0,0.0,344.0,344.0
-45,Samoa,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-46,Samoa,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-47,Samoa,Other Consumption,0.0,0.0,0.0,367.0,0.0,1450.0,0.0,512.0,3.0,2332.0,1453.0,0.0,367.0,1820.0
-48,Samoa,Agriculture  forestry and fishing,0.0,0.0,0.0,44.0,0.0,5.0,0.0,0.0,0.0,49.0,5.0,0.0,44.0,49.0
-49,Samoa,Commerce and public services,0.0,0.0,0.0,178.0,0.0,0.0,0.0,354.0,3.0,535.0,3.0,0.0,178.0,181.0
-50,Samoa,Households,0.0,0.0,0.0,145.0,0.0,1445.0,0.0,157.0,0.0,1747.0,1445.0,0.0,145.0,1590.0
-51,Samoa,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-52,Samoa,Non-energy use,0.0,0.0,0.0,121.0,0.0,0.0,0.0,0.0,0.0,121.0,0.0,0.0,121.0,121.0
-53,Nauru,Primary production,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,4.0,4.0,0.0,0.0,0.0
-54,Nauru,Imports,0.0,0.0,0.0,1059.0,0.0,0.0,0.0,0.0,0.0,1059.0,0.0,0.0,1059.0,1059.0
-55,Nauru,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-56,Nauru,International marine bunkers,0.0,0.0,0.0,-162.0,0.0,0.0,0.0,0.0,0.0,-162.0,0.0,0.0,-162.0,-162.0
-57,Nauru,International aviation bunkers,0.0,0.0,0.0,-164.0,0.0,0.0,0.0,0.0,0.0,-164.0,0.0,0.0,-164.0,-164.0
-58,Nauru,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-59,Nauru,Total energy supply,0.0,0.0,0.0,734.0,0.0,0.0,0.0,4.0,0.0,737.0,4.0,0.0,734.0,734.0
-60,Nauru,Statistical differences,0.0,0.0,0.0,-6.0,0.0,0.0,0.0,0.0,0.0,-6.0,4.0,0.0,-6.0,-6.0
-61,Nauru,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-62,Nauru,Transformation,0.0,0.0,0.0,-343.0,0.0,0.0,0.0,130.0,0.0,-213.0,0.0,0.0,-343.0,-343.0
-63,Nauru,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-343.0,0.0,0.0,0.0,130.0,0.0,-213.0,0.0,0.0,-343.0,-343.0
-64,Nauru,Electricity Plants,0.0,0.0,0.0,-343.0,0.0,0.0,0.0,130.0,0.0,-213.0,0.0,0.0,-343.0,-343.0
-65,Nauru,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-66,Nauru,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-67,Nauru,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-68,Nauru,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-69,Nauru,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-70,Nauru,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-71,Nauru,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-72,Nauru,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-73,Nauru,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-74,Nauru,Other transformation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-75,Nauru,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-4.0,0.0,-4.0,0.0,0.0,0.0,0.0
-76,Nauru,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-16.0,0.0,-16.0,0.0,0.0,0.0,0.0
-77,Nauru,Final consumption,0.0,0.0,0.0,396.0,0.0,0.0,0.0,114.0,0.0,511.0,0.0,0.0,396.0,396.0
-78,Nauru,Final Energy Consumption,0.0,0.0,0.0,395.0,0.0,0.0,0.0,114.0,0.0,509.0,0.0,0.0,395.0,395.0
-79,Nauru,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,7.0,0.0,0.0,0.0,0.0
-80,Nauru,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-81,Nauru,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-82,Nauru,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-83,Nauru,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-84,Nauru,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-85,Nauru,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-86,Nauru,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-87,Nauru,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-88,Nauru,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-89,Nauru,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-90,Nauru,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-91,Nauru,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-92,Nauru,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,7.0,0.0,0.0,0.0,0.0
-93,Nauru,Transport,0.0,0.0,0.0,208.0,0.0,0.0,0.0,0.0,0.0,208.0,0.0,0.0,208.0,208.0
-94,Nauru,Road,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-95,Nauru,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-96,Nauru,Domestic aviation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-97,Nauru,Domestic navigation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-98,Nauru,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-99,Nauru,Transport n.e.s,0.0,0.0,0.0,208.0,0.0,0.0,0.0,0.0,0.0,208.0,0.0,0.0,208.0,208.0
-100,Nauru,Other Consumption,0.0,0.0,0.0,187.0,0.0,0.0,0.0,108.0,0.0,294.0,0.0,0.0,187.0,187.0
-101,Nauru,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-102,Nauru,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,47.0,0.0,47.0,0.0,0.0,0.0,0.0
-103,Nauru,Households,0.0,0.0,0.0,1.0,0.0,0.0,0.0,54.0,0.0,55.0,0.0,0.0,1.0,1.0
-104,Nauru,Other consumption n.e.s,0.0,0.0,0.0,186.0,0.0,0.0,0.0,6.0,0.0,192.0,0.0,0.0,186.0,186.0
-105,Nauru,Non-energy use,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,2.0,2.0
-106,Vanuatu,Primary production,0.0,0.0,0.0,0.0,0.0,840.0,0.0,70.0,0.0,909.0,909.0,0.0,0.0,840.0
-107,Vanuatu,Imports,0.0,0.0,0.0,2965.0,0.0,0.0,0.0,0.0,0.0,2965.0,0.0,0.0,2965.0,2965.0
-108,Vanuatu,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-109,Vanuatu,International marine bunkers,0.0,0.0,0.0,-222.0,0.0,0.0,0.0,0.0,0.0,-222.0,0.0,0.0,-222.0,-222.0
-110,Vanuatu,International aviation bunkers,0.0,0.0,0.0,-348.0,0.0,0.0,0.0,0.0,0.0,-348.0,0.0,0.0,-348.0,-348.0
-111,Vanuatu,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-112,Vanuatu,Total energy supply,0.0,0.0,0.0,2395.0,0.0,840.0,0.0,70.0,0.0,3304.0,909.0,0.0,2395.0,3235.0
-113,Vanuatu,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,0.0
-114,Vanuatu,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-115,Vanuatu,Transformation,0.0,0.0,0.0,-621.0,0.0,-25.0,0.0,227.0,0.0,-419.0,-25.0,0.0,-621.0,-646.0
-116,Vanuatu,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-621.0,0.0,-8.0,0.0,227.0,0.0,-402.0,-8.0,0.0,-621.0,-629.0
-117,Vanuatu,Electricity Plants,0.0,0.0,0.0,-621.0,0.0,-8.0,0.0,227.0,0.0,-402.0,-8.0,0.0,-621.0,-629.0
-118,Vanuatu,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-119,Vanuatu,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-120,Vanuatu,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-121,Vanuatu,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-122,Vanuatu,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-123,Vanuatu,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-124,Vanuatu,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-125,Vanuatu,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-126,Vanuatu,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-127,Vanuatu,Other transformation,0.0,0.0,0.0,0.0,0.0,-17.0,0.0,0.0,0.0,-17.0,-17.0,0.0,0.0,-17.0
-128,Vanuatu,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-7.0,0.0,-7.0,0.0,0.0,0.0,0.0
-129,Vanuatu,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-21.0,0.0,-21.0,0.0,0.0,0.0,0.0
-130,Vanuatu,Final consumption,0.0,0.0,0.0,1774.0,0.0,815.0,0.0,269.0,0.0,2858.0,815.0,0.0,1774.0,2589.0
-131,Vanuatu,Final Energy Consumption,0.0,0.0,0.0,1683.0,0.0,815.0,0.0,269.0,0.0,2767.0,815.0,0.0,1683.0,2498.0
-132,Vanuatu,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,103.0,0.0,103.0,0.0,0.0,0.0,0.0
-133,Vanuatu,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-134,Vanuatu,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-135,Vanuatu,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-136,Vanuatu,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-137,Vanuatu,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-138,Vanuatu,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-139,Vanuatu,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-140,Vanuatu,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-141,Vanuatu,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-142,Vanuatu,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-143,Vanuatu,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-144,Vanuatu,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-145,Vanuatu,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,103.0,0.0,103.0,0.0,0.0,0.0,0.0
-146,Vanuatu,Transport,0.0,0.0,0.0,1619.0,0.0,0.0,0.0,0.0,0.0,1619.0,0.0,0.0,1619.0,1619.0
-147,Vanuatu,Road,0.0,0.0,0.0,1458.0,0.0,0.0,0.0,0.0,0.0,1458.0,0.0,0.0,1458.0,1458.0
-148,Vanuatu,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-149,Vanuatu,Domestic aviation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-150,Vanuatu,Domestic navigation,0.0,0.0,0.0,161.0,0.0,0.0,0.0,0.0,0.0,161.0,0.0,0.0,161.0,161.0
-151,Vanuatu,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-152,Vanuatu,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-153,Vanuatu,Other Consumption,0.0,0.0,0.0,64.0,0.0,815.0,0.0,166.0,0.0,1045.0,815.0,0.0,64.0,879.0
-154,Vanuatu,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-155,Vanuatu,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,69.0,0.0,69.0,0.0,0.0,0.0,0.0
-156,Vanuatu,Households,0.0,0.0,0.0,64.0,0.0,815.0,0.0,93.0,0.0,971.0,815.0,0.0,64.0,879.0
-157,Vanuatu,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,0.0,0.0,0.0,0.0
-158,Vanuatu,Non-energy use,0.0,0.0,0.0,91.0,0.0,0.0,0.0,0.0,0.0,91.0,0.0,0.0,91.0,91.0
-159,Palau,Primary production,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,7.0,7.0,0.0,0.0,0.0
-160,Palau,Imports,0.0,0.0,0.0,3659.0,0.0,0.0,0.0,0.0,0.0,3659.0,0.0,0.0,3659.0,3659.0
-161,Palau,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-162,Palau,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-163,Palau,International aviation bunkers,0.0,0.0,0.0,-618.0,0.0,0.0,0.0,0.0,0.0,-618.0,0.0,0.0,-618.0,-618.0
-164,Palau,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-165,Palau,Total energy supply,0.0,0.0,0.0,3041.0,0.0,0.0,0.0,7.0,0.0,3049.0,8.0,0.0,3041.0,3041.0
-166,Palau,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0
-167,Palau,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-168,Palau,Transformation,0.0,0.0,0.0,-1075.0,0.0,0.0,0.0,340.0,0.0,-735.0,0.0,0.0,-1075.0,-1075.0
-169,Palau,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-1075.0,0.0,0.0,0.0,340.0,0.0,-735.0,0.0,0.0,-1075.0,-1075.0
-170,Palau,Electricity Plants,0.0,0.0,0.0,-1075.0,0.0,0.0,0.0,340.0,0.0,-735.0,0.0,0.0,-1075.0,-1075.0
-171,Palau,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-172,Palau,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-173,Palau,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-174,Palau,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-175,Palau,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-176,Palau,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-177,Palau,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-178,Palau,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-179,Palau,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-180,Palau,Other transformation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-181,Palau,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-18.0,0.0,-18.0,0.0,0.0,0.0,0.0
-182,Palau,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-40.0,0.0,-40.0,0.0,0.0,0.0,0.0
-183,Palau,Final consumption,0.0,0.0,0.0,1966.0,0.0,0.0,0.0,290.0,0.0,2256.0,0.0,0.0,1966.0,1966.0
-184,Palau,Final Energy Consumption,0.0,0.0,0.0,1926.0,0.0,0.0,0.0,290.0,0.0,2216.0,0.0,0.0,1926.0,1926.0
-185,Palau,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,0.0,22.0,0.0,0.0,0.0,0.0
-186,Palau,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-187,Palau,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-188,Palau,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-189,Palau,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-190,Palau,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-191,Palau,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-192,Palau,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-193,Palau,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-194,Palau,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-195,Palau,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-196,Palau,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-197,Palau,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-198,Palau,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,0.0,22.0,0.0,0.0,0.0,0.0
-199,Palau,Transport,0.0,0.0,0.0,1834.0,0.0,0.0,0.0,0.0,0.0,1834.0,0.0,0.0,1834.0,1834.0
-200,Palau,Road,0.0,0.0,0.0,545.0,0.0,0.0,0.0,0.0,0.0,545.0,0.0,0.0,545.0,545.0
-201,Palau,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-202,Palau,Domestic aviation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-203,Palau,Domestic navigation,0.0,0.0,0.0,1289.0,0.0,0.0,0.0,0.0,0.0,1289.0,0.0,0.0,1289.0,1289.0
-204,Palau,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-205,Palau,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-206,Palau,Other Consumption,0.0,0.0,0.0,92.0,0.0,0.0,0.0,268.0,0.0,361.0,0.0,0.0,92.0,92.0
-207,Palau,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-208,Palau,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,158.0,0.0,158.0,0.0,0.0,0.0,0.0
-209,Palau,Households,0.0,0.0,0.0,92.0,0.0,0.0,0.0,85.0,0.0,177.0,0.0,0.0,92.0,92.0
-210,Palau,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,0.0,25.0,0.0,0.0,0.0,0.0
-211,Palau,Non-energy use,0.0,0.0,0.0,40.0,0.0,0.0,0.0,0.0,0.0,40.0,0.0,0.0,40.0,40.0
-212,Kiribati,Primary production,0.0,0.0,0.0,0.0,0.0,545.0,0.0,18.0,0.0,563.0,563.0,0.0,0.0,545.0
-213,Kiribati,Imports,0.0,0.0,0.0,1048.0,0.0,0.0,0.0,0.0,0.0,1048.0,0.0,0.0,1048.0,1048.0
-214,Kiribati,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-215,Kiribati,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-216,Kiribati,International aviation bunkers,0.0,0.0,0.0,-27.0,0.0,0.0,0.0,0.0,0.0,-27.0,0.0,0.0,-27.0,-27.0
-217,Kiribati,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-218,Kiribati,Total energy supply,0.0,0.0,0.0,1020.0,0.0,545.0,0.0,18.0,0.0,1583.0,563.0,0.0,1020.0,1565.0
-219,Kiribati,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,0.0,0.0,0.0
-220,Kiribati,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-221,Kiribati,Transformation,0.0,0.0,0.0,-305.0,0.0,-11.0,0.0,96.0,0.0,-219.0,-11.0,0.0,-305.0,-316.0
-222,Kiribati,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-305.0,0.0,0.0,0.0,96.0,0.0,-209.0,0.0,0.0,-305.0,-305.0
-223,Kiribati,Electricity Plants,0.0,0.0,0.0,-305.0,0.0,0.0,0.0,96.0,0.0,-209.0,0.0,0.0,-305.0,-305.0
-224,Kiribati,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-225,Kiribati,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-226,Kiribati,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-227,Kiribati,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-228,Kiribati,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-229,Kiribati,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-230,Kiribati,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-231,Kiribati,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-232,Kiribati,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-233,Kiribati,Other transformation,0.0,0.0,0.0,0.0,0.0,-11.0,0.0,0.0,0.0,-11.0,-11.0,0.0,0.0,-11.0
-234,Kiribati,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-5.0,0.0,-5.0,0.0,0.0,0.0,0.0
-235,Kiribati,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-17.0,0.0,-17.0,0.0,0.0,0.0,0.0
-236,Kiribati,Final consumption,0.0,0.0,0.0,715.0,0.0,534.0,0.0,93.0,0.0,1342.0,534.0,0.0,715.0,1249.0
-237,Kiribati,Final Energy Consumption,0.0,0.0,0.0,711.0,0.0,534.0,0.0,93.0,0.0,1338.0,534.0,0.0,711.0,1245.0
-238,Kiribati,Manufacturing  const. and mining,0.0,0.0,0.0,9.0,0.0,0.0,0.0,8.0,0.0,17.0,0.0,0.0,9.0,9.0
-239,Kiribati,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-240,Kiribati,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-241,Kiribati,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-242,Kiribati,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-243,Kiribati,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-244,Kiribati,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-245,Kiribati,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-246,Kiribati,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-247,Kiribati,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-248,Kiribati,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-249,Kiribati,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-250,Kiribati,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-251,Kiribati,Industry n.e.s,0.0,0.0,0.0,9.0,0.0,0.0,0.0,8.0,0.0,17.0,0.0,0.0,9.0,9.0
-252,Kiribati,Transport,0.0,0.0,0.0,449.0,0.0,0.0,0.0,0.0,0.0,449.0,0.0,0.0,449.0,449.0
-253,Kiribati,Road,0.0,0.0,0.0,353.0,0.0,0.0,0.0,0.0,0.0,353.0,0.0,0.0,353.0,353.0
-254,Kiribati,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-255,Kiribati,Domestic aviation,0.0,0.0,0.0,36.0,0.0,0.0,0.0,0.0,0.0,36.0,0.0,0.0,36.0,36.0
-256,Kiribati,Domestic navigation,0.0,0.0,0.0,60.0,0.0,0.0,0.0,0.0,0.0,60.0,0.0,0.0,60.0,60.0
-257,Kiribati,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-258,Kiribati,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-259,Kiribati,Other Consumption,0.0,0.0,0.0,253.0,0.0,534.0,0.0,85.0,0.0,872.0,534.0,0.0,253.0,787.0
-260,Kiribati,Agriculture  forestry and fishing,0.0,0.0,0.0,119.0,0.0,0.0,0.0,0.0,0.0,119.0,0.0,0.0,119.0,119.0
-261,Kiribati,Commerce and public services,0.0,0.0,0.0,32.0,0.0,0.0,0.0,46.0,0.0,78.0,0.0,0.0,32.0,32.0
-262,Kiribati,Households,0.0,0.0,0.0,102.0,0.0,534.0,0.0,38.0,0.0,675.0,534.0,0.0,102.0,636.0
-263,Kiribati,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-264,Kiribati,Non-energy use,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,4.0,4.0
-265,Cook Islands,Primary production,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,0.0,36.0,36.0,0.0,0.0,0.0
-266,Cook Islands,Imports,0.0,0.0,0.0,1552.0,0.0,0.0,0.0,0.0,0.0,1552.0,0.0,0.0,1552.0,1552.0
-267,Cook Islands,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-268,Cook Islands,International marine bunkers,0.0,0.0,0.0,-65.0,0.0,0.0,0.0,0.0,0.0,-65.0,0.0,0.0,-65.0,-65.0
-269,Cook Islands,International aviation bunkers,0.0,0.0,0.0,-338.0,0.0,0.0,0.0,0.0,0.0,-338.0,0.0,0.0,-338.0,-338.0
-270,Cook Islands,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-271,Cook Islands,Total energy supply,0.0,0.0,0.0,1149.0,0.0,0.0,0.0,36.0,0.0,1185.0,36.0,0.0,1149.0,1149.0
-272,Cook Islands,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,0.0,0.0,0.0
-273,Cook Islands,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-274,Cook Islands,Transformation,0.0,0.0,0.0,-322.0,0.0,0.0,0.0,104.0,0.0,-219.0,0.0,0.0,-322.0,-322.0
-275,Cook Islands,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-322.0,0.0,0.0,0.0,104.0,0.0,-219.0,0.0,0.0,-322.0,-322.0
-276,Cook Islands,Electricity Plants,0.0,0.0,0.0,-322.0,0.0,0.0,0.0,104.0,0.0,-219.0,0.0,0.0,-322.0,-322.0
-277,Cook Islands,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-278,Cook Islands,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-279,Cook Islands,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-280,Cook Islands,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-281,Cook Islands,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-282,Cook Islands,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-283,Cook Islands,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-284,Cook Islands,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-285,Cook Islands,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-286,Cook Islands,Other transformation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-287,Cook Islands,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-288,Cook Islands,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-289,Cook Islands,Final consumption,0.0,0.0,0.0,827.0,0.0,0.0,0.0,139.0,0.0,966.0,0.0,0.0,827.0,827.0
-290,Cook Islands,Final Energy Consumption,0.0,0.0,0.0,827.0,0.0,0.0,0.0,139.0,0.0,966.0,0.0,0.0,827.0,827.0
-291,Cook Islands,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-292,Cook Islands,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-293,Cook Islands,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-294,Cook Islands,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-295,Cook Islands,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-296,Cook Islands,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-297,Cook Islands,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-298,Cook Islands,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-299,Cook Islands,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-300,Cook Islands,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-301,Cook Islands,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-302,Cook Islands,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-303,Cook Islands,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-304,Cook Islands,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-305,Cook Islands,Transport,0.0,0.0,0.0,827.0,0.0,0.0,0.0,0.0,0.0,827.0,0.0,0.0,827.0,827.0
-306,Cook Islands,Road,0.0,0.0,0.0,353.0,0.0,0.0,0.0,0.0,0.0,353.0,0.0,0.0,353.0,353.0
-307,Cook Islands,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-308,Cook Islands,Domestic aviation,0.0,0.0,0.0,85.0,0.0,0.0,0.0,0.0,0.0,85.0,0.0,0.0,85.0,85.0
-309,Cook Islands,Domestic navigation,0.0,0.0,0.0,97.0,0.0,0.0,0.0,0.0,0.0,97.0,0.0,0.0,97.0,97.0
-310,Cook Islands,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-311,Cook Islands,Transport n.e.s,0.0,0.0,0.0,292.0,0.0,0.0,0.0,0.0,0.0,292.0,0.0,0.0,292.0,292.0
-312,Cook Islands,Other Consumption,0.0,0.0,0.0,0.0,0.0,0.0,0.0,139.0,0.0,139.0,0.0,0.0,0.0,0.0
-313,Cook Islands,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-314,Cook Islands,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-315,Cook Islands,Households,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-316,Cook Islands,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,139.0,0.0,139.0,0.0,0.0,0.0,0.0
-317,Cook Islands,Non-energy use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-318,Solomon Islands,Primary production,0.0,0.0,0.0,0.0,0.0,3310.0,0.0,18.0,0.0,3328.0,3328.0,0.0,0.0,3310.0
-319,Solomon Islands,Imports,0.0,0.0,0.0,4684.0,0.0,0.0,0.0,0.0,0.0,4684.0,0.0,0.0,4684.0,4684.0
-320,Solomon Islands,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-321,Solomon Islands,International marine bunkers,0.0,0.0,0.0,-240.0,0.0,0.0,0.0,0.0,0.0,-240.0,0.0,0.0,-240.0,-240.0
-322,Solomon Islands,International aviation bunkers,0.0,0.0,0.0,-170.0,0.0,0.0,0.0,0.0,0.0,-170.0,0.0,0.0,-170.0,-170.0
-323,Solomon Islands,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-324,Solomon Islands,Total energy supply,0.0,0.0,0.0,4274.0,0.0,3310.0,0.0,18.0,0.0,7602.0,3328.0,0.0,4274.0,7584.0
-325,Solomon Islands,Statistical differences,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.0,0.0,7.0,18.0,0.0,4.0,4.0
-326,Solomon Islands,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-327,Solomon Islands,Transformation,0.0,0.0,0.0,-1027.0,0.0,-73.0,0.0,368.0,0.0,-732.0,-73.0,0.0,-1027.0,-1100.0
-328,Solomon Islands,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-1027.0,0.0,-36.0,0.0,368.0,0.0,-695.0,-36.0,0.0,-1027.0,-1063.0
-329,Solomon Islands,Electricity Plants,0.0,0.0,0.0,-1027.0,0.0,-36.0,0.0,368.0,0.0,-695.0,-36.0,0.0,-1027.0,-1063.0
-330,Solomon Islands,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-331,Solomon Islands,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-332,Solomon Islands,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-333,Solomon Islands,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-334,Solomon Islands,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-335,Solomon Islands,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-336,Solomon Islands,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-337,Solomon Islands,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-338,Solomon Islands,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-339,Solomon Islands,Other transformation,0.0,0.0,0.0,0.0,0.0,-37.0,0.0,0.0,0.0,-37.0,-37.0,0.0,0.0,-37.0
-340,Solomon Islands,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-341,Solomon Islands,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-65.0,0.0,-65.0,0.0,0.0,0.0,0.0
-342,Solomon Islands,Final consumption,0.0,0.0,0.0,3243.0,0.0,3237.0,0.0,318.0,0.0,6797.0,3237.0,0.0,3243.0,6480.0
-343,Solomon Islands,Final Energy Consumption,0.0,0.0,0.0,3180.0,0.0,3237.0,0.0,318.0,0.0,6734.0,3237.0,0.0,3180.0,6417.0
-344,Solomon Islands,Manufacturing  const. and mining,0.0,0.0,0.0,268.0,0.0,0.0,0.0,146.0,0.0,414.0,0.0,0.0,268.0,268.0
-345,Solomon Islands,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-346,Solomon Islands,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-347,Solomon Islands,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-348,Solomon Islands,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-349,Solomon Islands,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-350,Solomon Islands,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-351,Solomon Islands,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-352,Solomon Islands,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-353,Solomon Islands,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-354,Solomon Islands,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-355,Solomon Islands,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-356,Solomon Islands,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-357,Solomon Islands,Industry n.e.s,0.0,0.0,0.0,268.0,0.0,0.0,0.0,146.0,0.0,414.0,0.0,0.0,268.0,268.0
-358,Solomon Islands,Transport,0.0,0.0,0.0,2681.0,0.0,0.0,0.0,0.0,0.0,2681.0,0.0,0.0,2681.0,2681.0
-359,Solomon Islands,Road,0.0,0.0,0.0,2285.0,0.0,0.0,0.0,0.0,0.0,2285.0,0.0,0.0,2285.0,2285.0
-360,Solomon Islands,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-361,Solomon Islands,Domestic aviation,0.0,0.0,0.0,37.0,0.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,37.0,37.0
-362,Solomon Islands,Domestic navigation,0.0,0.0,0.0,360.0,0.0,0.0,0.0,0.0,0.0,360.0,0.0,0.0,360.0,360.0
-363,Solomon Islands,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-364,Solomon Islands,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-365,Solomon Islands,Other Consumption,0.0,0.0,0.0,231.0,0.0,3237.0,0.0,172.0,0.0,3639.0,3237.0,0.0,231.0,3468.0
-366,Solomon Islands,Agriculture  forestry and fishing,0.0,0.0,0.0,217.0,0.0,0.0,0.0,0.0,0.0,217.0,0.0,0.0,217.0,217.0
-367,Solomon Islands,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,73.0,0.0,73.0,0.0,0.0,0.0,0.0
-368,Solomon Islands,Households,0.0,0.0,0.0,13.0,0.0,3237.0,0.0,63.0,0.0,3313.0,3237.0,0.0,13.0,3250.0
-369,Solomon Islands,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,0.0
-370,Solomon Islands,Non-energy use,0.0,0.0,0.0,63.0,0.0,0.0,0.0,0.0,0.0,63.0,0.0,0.0,63.0,63.0
-371,Tonga,Primary production,0.0,0.0,0.0,0.0,0.0,19.0,0.0,23.0,0.0,42.0,42.0,0.0,0.0,19.0
-372,Tonga,Imports,0.0,0.0,0.0,2050.0,0.0,0.0,0.0,0.0,0.0,2050.0,0.0,0.0,2050.0,2050.0
-373,Tonga,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-374,Tonga,International marine bunkers,0.0,0.0,0.0,-16.0,0.0,0.0,0.0,0.0,0.0,-16.0,0.0,0.0,-16.0,-16.0
-375,Tonga,International aviation bunkers,0.0,0.0,0.0,-159.0,0.0,0.0,0.0,0.0,0.0,-159.0,0.0,0.0,-159.0,-159.0
-376,Tonga,Stock changes,0.0,0.0,0.0,364.0,0.0,0.0,0.0,0.0,0.0,364.0,0.0,0.0,364.0,364.0
-377,Tonga,Total energy supply,0.0,0.0,0.0,2239.0,0.0,19.0,0.0,23.0,0.0,2281.0,42.0,0.0,2239.0,2258.0
-378,Tonga,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,23.0,0.0,0.0,0.0
-379,Tonga,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-380,Tonga,Transformation,0.0,0.0,0.0,-602.0,0.0,-6.0,0.0,231.0,0.0,-377.0,-6.0,0.0,-602.0,-608.0
-381,Tonga,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-602.0,0.0,0.0,0.0,231.0,0.0,-371.0,0.0,0.0,-602.0,-602.0
-382,Tonga,Electricity Plants,0.0,0.0,0.0,-602.0,0.0,0.0,0.0,231.0,0.0,-371.0,0.0,0.0,-602.0,-602.0
-383,Tonga,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-384,Tonga,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-385,Tonga,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-386,Tonga,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-387,Tonga,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-388,Tonga,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-389,Tonga,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-390,Tonga,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-391,Tonga,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-392,Tonga,Other transformation,0.0,0.0,0.0,0.0,0.0,-6.0,0.0,0.0,0.0,-6.0,-6.0,0.0,0.0,-6.0
-393,Tonga,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-7.0,0.0,-7.0,0.0,0.0,0.0,0.0
-394,Tonga,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-21.0,0.0,-21.0,0.0,0.0,0.0,0.0
-395,Tonga,Final consumption,0.0,0.0,0.0,1637.0,0.0,12.0,0.0,226.0,0.0,1876.0,12.0,0.0,1637.0,1649.0
-396,Tonga,Final Energy Consumption,0.0,0.0,0.0,1627.0,0.0,12.0,0.0,226.0,0.0,1866.0,12.0,0.0,1627.0,1639.0
-397,Tonga,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-398,Tonga,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-399,Tonga,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-400,Tonga,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-401,Tonga,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-402,Tonga,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-403,Tonga,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-404,Tonga,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-405,Tonga,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-406,Tonga,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-407,Tonga,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-408,Tonga,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-409,Tonga,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-410,Tonga,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-411,Tonga,Transport,0.0,0.0,0.0,1523.0,0.0,0.0,0.0,0.0,0.0,1523.0,0.0,0.0,1523.0,1523.0
-412,Tonga,Road,0.0,0.0,0.0,1099.0,0.0,0.0,0.0,0.0,0.0,1099.0,0.0,0.0,1099.0,1099.0
-413,Tonga,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-414,Tonga,Domestic aviation,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,4.0,4.0
-415,Tonga,Domestic navigation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-416,Tonga,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-417,Tonga,Transport n.e.s,0.0,0.0,0.0,420.0,0.0,0.0,0.0,0.0,0.0,420.0,0.0,0.0,420.0,420.0
-418,Tonga,Other Consumption,0.0,0.0,0.0,104.0,0.0,12.0,0.0,226.0,0.0,343.0,12.0,0.0,104.0,116.0
-419,Tonga,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-420,Tonga,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,75.0,0.0,75.0,0.0,0.0,0.0,0.0
-421,Tonga,Households,0.0,0.0,0.0,104.0,0.0,12.0,0.0,81.0,0.0,198.0,12.0,0.0,104.0,116.0
-422,Tonga,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,70.0,0.0,70.0,0.0,0.0,0.0,0.0
-423,Tonga,Non-energy use,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,10.0,10.0
-424,New Caledonia,Primary production,0.0,0.0,0.0,0.0,0.0,124.0,0.0,1647.0,141.0,1912.0,1912.0,0.0,0.0,265.0
-425,New Caledonia,Imports,26739.0,0.0,0.0,38116.0,0.0,1.0,0.0,0.0,0.0,64856.0,1.0,26739.0,38116.0,64856.0
-426,New Caledonia,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-427,New Caledonia,International marine bunkers,0.0,0.0,0.0,-391.0,0.0,0.0,0.0,0.0,0.0,-391.0,0.0,0.0,-391.0,-391.0
-428,New Caledonia,International aviation bunkers,0.0,0.0,0.0,-1191.0,0.0,0.0,0.0,0.0,0.0,-1191.0,0.0,0.0,-1191.0,-1191.0
-429,New Caledonia,Stock changes,706.0,0.0,0.0,-231.0,0.0,0.0,0.0,0.0,0.0,475.0,0.0,706.0,-231.0,475.0
-430,New Caledonia,Total energy supply,27445.0,0.0,0.0,36304.0,0.0,125.0,0.0,1647.0,141.0,65661.0,1913.0,27445.0,36304.0,64015.0
-431,New Caledonia,Statistical differences,-676.0,0.0,0.0,-185.0,0.0,0.0,0.0,-347.0,0.0,-1208.0,1647.0,-676.0,-185.0,-861.0
-432,New Caledonia,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-433,New Caledonia,Transformation,-18820.0,0.0,0.0,-16397.0,0.0,-22.0,0.0,10352.0,0.0,-24887.0,-22.0,-18820.0,-16397.0,-35239.0
-434,New Caledonia,Electricity  CHP & Heat Plants,-18820.0,0.0,0.0,-16397.0,0.0,-5.0,0.0,10352.0,0.0,-24870.0,-5.0,-18820.0,-16397.0,-35222.0
-435,New Caledonia,Electricity Plants,-18820.0,0.0,0.0,-16397.0,0.0,-5.0,0.0,10352.0,0.0,-24870.0,-5.0,-18820.0,-16397.0,-35222.0
-436,New Caledonia,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-437,New Caledonia,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-438,New Caledonia,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-439,New Caledonia,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-440,New Caledonia,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-441,New Caledonia,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-442,New Caledonia,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-443,New Caledonia,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-444,New Caledonia,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-445,New Caledonia,Other transformation,0.0,0.0,0.0,0.0,0.0,-16.0,0.0,0.0,0.0,-16.0,-16.0,0.0,0.0,-16.0
-446,New Caledonia,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-15.0,0.0,-15.0,0.0,0.0,0.0,0.0
-447,New Caledonia,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-204.0,0.0,-204.0,0.0,0.0,0.0,0.0
-448,New Caledonia,Final consumption,9300.0,0.0,0.0,20092.0,0.0,103.0,0.0,12128.0,141.0,41764.0,244.0,9300.0,20092.0,29636.0
-449,New Caledonia,Final Energy Consumption,3733.0,0.0,0.0,19270.0,0.0,103.0,0.0,12128.0,141.0,35374.0,244.0,3733.0,19270.0,23247.0
-450,New Caledonia,Manufacturing  const. and mining,3733.0,0.0,0.0,9592.0,0.0,0.0,0.0,9373.0,0.0,22698.0,0.0,3733.0,9592.0,13325.0
-451,New Caledonia,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-452,New Caledonia,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-453,New Caledonia,Non-ferrous metals,0.0,0.0,0.0,2937.0,0.0,0.0,0.0,8916.0,0.0,11853.0,0.0,0.0,2937.0,2937.0
-454,New Caledonia,Non-metallic minerals,3733.0,0.0,0.0,3163.0,0.0,0.0,0.0,0.0,0.0,6896.0,0.0,3733.0,3163.0,6896.0
-455,New Caledonia,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-456,New Caledonia,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-457,New Caledonia,Mining and quarrying,0.0,0.0,0.0,2915.0,0.0,0.0,0.0,112.0,0.0,3027.0,0.0,0.0,2915.0,2915.0
-458,New Caledonia,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-459,New Caledonia,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-460,New Caledonia,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-461,New Caledonia,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-462,New Caledonia,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-463,New Caledonia,Industry n.e.s,0.0,0.0,0.0,577.0,0.0,0.0,0.0,346.0,0.0,922.0,0.0,0.0,577.0,577.0
-464,New Caledonia,Transport,0.0,0.0,0.0,8946.0,0.0,0.0,0.0,0.0,0.0,8946.0,0.0,0.0,8946.0,8946.0
-465,New Caledonia,Road,0.0,0.0,0.0,7948.0,0.0,0.0,0.0,0.0,0.0,7948.0,0.0,0.0,7948.0,7948.0
-466,New Caledonia,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-467,New Caledonia,Domestic aviation,0.0,0.0,0.0,265.0,0.0,0.0,0.0,0.0,0.0,265.0,0.0,0.0,265.0,265.0
-468,New Caledonia,Domestic navigation,0.0,0.0,0.0,733.0,0.0,0.0,0.0,0.0,0.0,733.0,0.0,0.0,733.0,733.0
-469,New Caledonia,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-470,New Caledonia,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-471,New Caledonia,Other Consumption,0.0,0.0,0.0,732.0,0.0,103.0,0.0,2754.0,141.0,3730.0,244.0,0.0,732.0,976.0
-472,New Caledonia,Agriculture  forestry and fishing,0.0,0.0,0.0,224.0,0.0,0.0,0.0,0.0,0.0,224.0,0.0,0.0,224.0,224.0
-473,New Caledonia,Commerce and public services,0.0,0.0,0.0,146.0,0.0,0.0,0.0,1690.0,141.0,1977.0,141.0,0.0,146.0,287.0
-474,New Caledonia,Households,0.0,0.0,0.0,362.0,0.0,103.0,0.0,1065.0,0.0,1529.0,103.0,0.0,362.0,465.0
-475,New Caledonia,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-476,New Caledonia,Non-energy use,5568.0,0.0,0.0,822.0,0.0,0.0,0.0,0.0,0.0,6390.0,0.0,5568.0,822.0,6390.0
-477,French Polynesia,Primary production,0.0,0.0,0.0,0.0,0.0,43.0,0.0,716.0,80.0,839.0,839.0,0.0,0.0,123.0
-478,French Polynesia,Imports,0.0,0.0,0.0,12634.0,0.0,7.0,0.0,0.0,0.0,12641.0,7.0,0.0,12634.0,12641.0
-479,French Polynesia,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-480,French Polynesia,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-481,French Polynesia,International aviation bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-482,French Polynesia,Stock changes,0.0,0.0,0.0,-260.0,0.0,0.0,0.0,0.0,0.0,-260.0,0.0,0.0,-260.0,-260.0
-483,French Polynesia,Total energy supply,0.0,0.0,0.0,12374.0,0.0,49.0,0.0,716.0,80.0,13220.0,845.0,0.0,12374.0,12503.0
-484,French Polynesia,Statistical differences,0.0,0.0,0.0,43.0,0.0,0.0,0.0,0.0,0.0,43.0,716.0,0.0,43.0,43.0
-485,French Polynesia,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-486,French Polynesia,Transformation,0.0,0.0,0.0,-4378.0,0.0,-14.0,0.0,1777.0,0.0,-2615.0,-14.0,0.0,-4378.0,-4392.0
-487,French Polynesia,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-4378.0,0.0,0.0,0.0,1777.0,0.0,-2601.0,0.0,0.0,-4378.0,-4378.0
-488,French Polynesia,Electricity Plants,0.0,0.0,0.0,-4378.0,0.0,0.0,0.0,1777.0,0.0,-2601.0,0.0,0.0,-4378.0,-4378.0
-489,French Polynesia,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-490,French Polynesia,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-491,French Polynesia,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-492,French Polynesia,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-493,French Polynesia,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-494,French Polynesia,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-495,French Polynesia,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-496,French Polynesia,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-497,French Polynesia,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-498,French Polynesia,Other transformation,0.0,0.0,0.0,0.0,0.0,-14.0,0.0,0.0,0.0,-14.0,-14.0,0.0,0.0,-14.0
-499,French Polynesia,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-500,French Polynesia,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-146.0,0.0,-146.0,0.0,0.0,0.0,0.0
-501,French Polynesia,Final consumption,0.0,0.0,0.0,7954.0,0.0,36.0,0.0,2347.0,80.0,10416.0,115.0,0.0,7954.0,8070.0
-502,French Polynesia,Final Energy Consumption,0.0,0.0,0.0,7837.0,0.0,36.0,0.0,2347.0,80.0,10299.0,115.0,0.0,7837.0,7953.0
-503,French Polynesia,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-504,French Polynesia,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-505,French Polynesia,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-506,French Polynesia,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-507,French Polynesia,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-508,French Polynesia,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-509,French Polynesia,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-510,French Polynesia,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-511,French Polynesia,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-512,French Polynesia,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-513,French Polynesia,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-514,French Polynesia,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-515,French Polynesia,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-516,French Polynesia,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-517,French Polynesia,Transport,0.0,0.0,0.0,6906.0,0.0,0.0,0.0,0.0,0.0,6906.0,0.0,0.0,6906.0,6906.0
-518,French Polynesia,Road,0.0,0.0,0.0,5492.0,0.0,0.0,0.0,0.0,0.0,5492.0,0.0,0.0,5492.0,5492.0
-519,French Polynesia,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-520,French Polynesia,Domestic aviation,0.0,0.0,0.0,603.0,0.0,0.0,0.0,0.0,0.0,603.0,0.0,0.0,603.0,603.0
-521,French Polynesia,Domestic navigation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-522,French Polynesia,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-523,French Polynesia,Transport n.e.s,0.0,0.0,0.0,812.0,0.0,0.0,0.0,0.0,0.0,812.0,0.0,0.0,812.0,812.0
-524,French Polynesia,Other Consumption,0.0,0.0,0.0,931.0,0.0,36.0,0.0,2347.0,80.0,3393.0,115.0,0.0,931.0,1047.0
-525,French Polynesia,Agriculture  forestry and fishing,0.0,0.0,0.0,460.0,0.0,0.0,0.0,0.0,0.0,460.0,0.0,0.0,460.0,460.0
-526,French Polynesia,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1056.0,0.0,1056.0,0.0,0.0,0.0,0.0
-527,French Polynesia,Households,0.0,0.0,0.0,472.0,0.0,36.0,0.0,1291.0,80.0,1877.0,115.0,0.0,472.0,588.0
-528,French Polynesia,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-529,French Polynesia,Non-energy use,0.0,0.0,0.0,117.0,0.0,0.0,0.0,0.0,0.0,117.0,0.0,0.0,117.0,117.0
-530,Micronesia,Primary production,0.0,0.0,0.0,0.0,0.0,25.0,0.0,15.0,0.0,40.0,40.0,0.0,0.0,25.0
-531,Micronesia,Imports,0.0,0.0,0.0,2574.0,0.0,0.0,0.0,0.0,0.0,2574.0,0.0,0.0,2574.0,2574.0
-532,Micronesia,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-533,Micronesia,International marine bunkers,0.0,0.0,0.0,-142.0,0.0,0.0,0.0,0.0,0.0,-142.0,0.0,0.0,-142.0,-142.0
-534,Micronesia,International aviation bunkers,0.0,0.0,0.0,-295.0,0.0,0.0,0.0,0.0,0.0,-295.0,0.0,0.0,-295.0,-295.0
-535,Micronesia,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-536,Micronesia,Total energy supply,0.0,0.0,0.0,2138.0,0.0,25.0,0.0,15.0,0.0,2177.0,40.0,0.0,2138.0,2163.0
-537,Micronesia,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,0.0,0.0,0.0
-538,Micronesia,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-539,Micronesia,Transformation,0.0,0.0,0.0,-826.0,0.0,-10.0,0.0,233.0,0.0,-602.0,-10.0,0.0,-826.0,-836.0
-540,Micronesia,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-826.0,0.0,0.0,0.0,233.0,0.0,-592.0,0.0,0.0,-826.0,-826.0
-541,Micronesia,Electricity Plants,0.0,0.0,0.0,-826.0,0.0,0.0,0.0,233.0,0.0,-592.0,0.0,0.0,-826.0,-826.0
-542,Micronesia,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-543,Micronesia,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-544,Micronesia,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-545,Micronesia,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-546,Micronesia,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-547,Micronesia,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-548,Micronesia,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-549,Micronesia,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-550,Micronesia,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-551,Micronesia,Other transformation,0.0,0.0,0.0,0.0,0.0,-10.0,0.0,0.0,0.0,-10.0,-10.0,0.0,0.0,-10.0
-552,Micronesia,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-9.0,0.0,-9.0,0.0,0.0,0.0,0.0
-553,Micronesia,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-74.0,0.0,-74.0,0.0,0.0,0.0,0.0
-554,Micronesia,Final consumption,0.0,0.0,0.0,1312.0,0.0,15.0,0.0,166.0,0.0,1492.0,15.0,0.0,1312.0,1327.0
-555,Micronesia,Final Energy Consumption,0.0,0.0,0.0,1219.0,0.0,15.0,0.0,166.0,0.0,1400.0,15.0,0.0,1219.0,1234.0
-556,Micronesia,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,53.0,0.0,53.0,0.0,0.0,0.0,0.0
-557,Micronesia,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-558,Micronesia,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-559,Micronesia,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-560,Micronesia,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-561,Micronesia,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-562,Micronesia,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-563,Micronesia,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-564,Micronesia,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-565,Micronesia,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-566,Micronesia,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-567,Micronesia,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-568,Micronesia,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-569,Micronesia,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,53.0,0.0,53.0,0.0,0.0,0.0,0.0
-570,Micronesia,Transport,0.0,0.0,0.0,1175.0,0.0,0.0,0.0,0.0,0.0,1175.0,0.0,0.0,1175.0,1175.0
-571,Micronesia,Road,0.0,0.0,0.0,714.0,0.0,0.0,0.0,0.0,0.0,714.0,0.0,0.0,714.0,714.0
-572,Micronesia,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-573,Micronesia,Domestic aviation,0.0,0.0,0.0,46.0,0.0,0.0,0.0,0.0,0.0,46.0,0.0,0.0,46.0,46.0
-574,Micronesia,Domestic navigation,0.0,0.0,0.0,415.0,0.0,0.0,0.0,0.0,0.0,415.0,0.0,0.0,415.0,415.0
-575,Micronesia,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-576,Micronesia,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-577,Micronesia,Other Consumption,0.0,0.0,0.0,45.0,0.0,15.0,0.0,113.0,0.0,172.0,15.0,0.0,45.0,60.0
-578,Micronesia,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-579,Micronesia,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,52.0,0.0,52.0,0.0,0.0,0.0,0.0
-580,Micronesia,Households,0.0,0.0,0.0,0.0,0.0,4.0,0.0,61.0,0.0,64.0,4.0,0.0,0.0,4.0
-581,Micronesia,Other consumption n.e.s,0.0,0.0,0.0,45.0,0.0,11.0,0.0,0.0,0.0,56.0,11.0,0.0,45.0,56.0
-582,Micronesia,Non-energy use,0.0,0.0,0.0,92.0,0.0,0.0,0.0,0.0,0.0,92.0,0.0,0.0,92.0,92.0
-583,Niue,Primary production,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,16.0,18.0,18.0,0.0,0.0,17.0
-584,Niue,Imports,0.0,0.0,0.0,110.0,0.0,0.0,0.0,0.0,0.0,110.0,0.0,0.0,110.0,110.0
-585,Niue,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-586,Niue,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-587,Niue,International aviation bunkers,0.0,0.0,0.0,-21.0,0.0,0.0,0.0,0.0,0.0,-21.0,0.0,0.0,-21.0,-21.0
-588,Niue,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-589,Niue,Total energy supply,0.0,0.0,0.0,89.0,0.0,1.0,0.0,2.0,16.0,107.0,18.0,0.0,89.0,106.0
-590,Niue,Statistical differences,0.0,0.0,0.0,-1.0,0.0,0.0,0.0,0.0,0.0,-1.0,2.0,0.0,-1.0,-1.0
-591,Niue,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-592,Niue,Transformation,0.0,0.0,0.0,-39.0,0.0,0.0,0.0,13.0,0.0,-26.0,0.0,0.0,-39.0,-39.0
-593,Niue,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-39.0,0.0,0.0,0.0,13.0,0.0,-26.0,0.0,0.0,-39.0,-39.0
-594,Niue,Electricity Plants,0.0,0.0,0.0,-39.0,0.0,0.0,0.0,13.0,0.0,-26.0,0.0,0.0,-39.0,-39.0
-595,Niue,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-596,Niue,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-597,Niue,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-598,Niue,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-599,Niue,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-600,Niue,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-601,Niue,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-602,Niue,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-603,Niue,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-604,Niue,Other transformation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-605,Niue,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-606,Niue,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-1.0,0.0,-1.0,0.0,0.0,0.0,0.0
-607,Niue,Final consumption,0.0,0.0,0.0,51.0,0.0,0.0,0.0,12.0,16.0,80.0,16.0,0.0,51.0,67.0
-608,Niue,Final Energy Consumption,0.0,0.0,0.0,51.0,0.0,0.0,0.0,12.0,16.0,80.0,16.0,0.0,51.0,67.0
-609,Niue,Manufacturing  const. and mining,0.0,0.0,0.0,2.0,0.0,0.0,0.0,3.0,0.0,5.0,0.0,0.0,2.0,2.0
-610,Niue,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-611,Niue,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-612,Niue,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-613,Niue,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-614,Niue,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-615,Niue,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-616,Niue,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-617,Niue,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-618,Niue,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-619,Niue,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-620,Niue,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-621,Niue,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-622,Niue,Industry n.e.s,0.0,0.0,0.0,2.0,0.0,0.0,0.0,3.0,0.0,5.0,0.0,0.0,2.0,2.0
-623,Niue,Transport,0.0,0.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,44.0,0.0,0.0,44.0,44.0
-624,Niue,Road,0.0,0.0,0.0,43.0,0.0,0.0,0.0,0.0,0.0,43.0,0.0,0.0,43.0,43.0
-625,Niue,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-626,Niue,Domestic aviation,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,1.0
-627,Niue,Domestic navigation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-628,Niue,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-629,Niue,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-630,Niue,Other Consumption,0.0,0.0,0.0,5.0,0.0,0.0,0.0,10.0,16.0,31.0,16.0,0.0,5.0,21.0
-631,Niue,Agriculture  forestry and fishing,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,1.0
-632,Niue,Commerce and public services,0.0,0.0,0.0,1.0,0.0,0.0,0.0,5.0,0.0,6.0,0.0,0.0,1.0,1.0
-633,Niue,Households,0.0,0.0,0.0,2.0,0.0,0.0,0.0,5.0,16.0,23.0,16.0,0.0,2.0,18.0
-634,Niue,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-635,Niue,Non-energy use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-636,Tuvalu,Primary production,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,7.0,7.0,0.0,0.0,0.0
-637,Tuvalu,Imports,0.0,0.0,0.0,132.0,0.0,0.0,0.0,0.0,0.0,132.0,0.0,0.0,132.0,132.0
-638,Tuvalu,Exports,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-639,Tuvalu,International marine bunkers,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-640,Tuvalu,International aviation bunkers,0.0,0.0,0.0,-9.0,0.0,0.0,0.0,0.0,0.0,-9.0,0.0,0.0,-9.0,-9.0
-641,Tuvalu,Stock changes,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-642,Tuvalu,Total energy supply,0.0,0.0,0.0,122.0,0.0,0.0,0.0,7.0,0.0,130.0,7.0,0.0,122.0,122.0
-643,Tuvalu,Statistical differences,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0
-644,Tuvalu,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-645,Tuvalu,Transformation,0.0,0.0,0.0,-73.0,0.0,0.0,0.0,24.0,0.0,-49.0,0.0,0.0,-73.0,-73.0
-646,Tuvalu,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-73.0,0.0,0.0,0.0,24.0,0.0,-49.0,0.0,0.0,-73.0,-73.0
-647,Tuvalu,Electricity Plants,0.0,0.0,0.0,-73.0,0.0,0.0,0.0,24.0,0.0,-49.0,0.0,0.0,-73.0,-73.0
-648,Tuvalu,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-649,Tuvalu,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-650,Tuvalu,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-651,Tuvalu,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-652,Tuvalu,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-653,Tuvalu,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-654,Tuvalu,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-655,Tuvalu,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-656,Tuvalu,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-657,Tuvalu,Other transformation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-658,Tuvalu,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-659,Tuvalu,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-4.0,0.0,-4.0,0.0,0.0,0.0,0.0
-660,Tuvalu,Final consumption,0.0,0.0,0.0,49.0,0.0,0.0,0.0,27.0,0.0,76.0,0.0,0.0,49.0,49.0
-661,Tuvalu,Final Energy Consumption,0.0,0.0,0.0,49.0,0.0,0.0,0.0,27.0,0.0,76.0,0.0,0.0,49.0,49.0
-662,Tuvalu,Manufacturing  const. and mining,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-663,Tuvalu,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-664,Tuvalu,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-665,Tuvalu,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-666,Tuvalu,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-667,Tuvalu,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-668,Tuvalu,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-669,Tuvalu,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-670,Tuvalu,Food and tobacco,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-671,Tuvalu,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-672,Tuvalu,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-673,Tuvalu,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-674,Tuvalu,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-675,Tuvalu,Industry n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-676,Tuvalu,Transport,0.0,0.0,0.0,38.0,0.0,0.0,0.0,0.0,0.0,38.0,0.0,0.0,38.0,38.0
-677,Tuvalu,Road,0.0,0.0,0.0,25.0,0.0,0.0,0.0,0.0,0.0,25.0,0.0,0.0,25.0,25.0
-678,Tuvalu,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-679,Tuvalu,Domestic aviation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-680,Tuvalu,Domestic navigation,0.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,13.0,0.0,0.0,13.0,13.0
-681,Tuvalu,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-682,Tuvalu,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-683,Tuvalu,Other Consumption,0.0,0.0,0.0,11.0,0.0,0.0,0.0,27.0,0.0,38.0,0.0,0.0,11.0,11.0
-684,Tuvalu,Agriculture  forestry and fishing,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,4.0,4.0
-685,Tuvalu,Commerce and public services,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,0.0,15.0,0.0,0.0,0.0,0.0
-686,Tuvalu,Households,0.0,0.0,0.0,8.0,0.0,0.0,0.0,12.0,0.0,19.0,0.0,0.0,8.0,8.0
-687,Tuvalu,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-688,Tuvalu,Non-energy use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-689,PNG,Primary production,0.0,0.0,43214.0,0.0,105639.0,72141.0,0.0,3347.0,16000.0,240341.0,91488.0,0.0,43214.0,236994.0
-690,PNG,Imports,0.0,0.0,58732.0,59360.0,0.0,0.0,0.0,0.0,0.0,118092.0,0.0,0.0,118092.0,118092.0
-691,PNG,Exports,0.0,0.0,-43214.0,-17299.0,-90762.0,0.0,0.0,0.0,0.0,-151275.0,0.0,0.0,-60513.0,-151275.0
-692,PNG,International marine bunkers,0.0,0.0,0.0,-308.0,0.0,0.0,0.0,0.0,0.0,-308.0,0.0,0.0,-308.0,-308.0
-693,PNG,International aviation bunkers,0.0,0.0,0.0,-2602.0,0.0,0.0,0.0,0.0,0.0,-2602.0,0.0,0.0,-2602.0,-2602.0
-694,PNG,Stock changes,0.0,0.0,-2198.0,-528.0,0.0,0.0,0.0,0.0,0.0,-2726.0,0.0,0.0,-2726.0,-2726.0
-695,PNG,Total energy supply,0.0,0.0,56534.0,38624.0,14877.0,72141.0,0.0,3347.0,16000.0,201523.0,91488.0,0.0,95158.0,198176.0
-696,PNG,Statistical differences,0.0,0.0,572.0,359.0,0.0,0.0,0.0,0.0,0.0,930.0,4947.0,0.0,931.0,931.0
-697,PNG,Transfers and recycled products,0.0,0.0,0.0,88.0,0.0,0.0,0.0,0.0,0.0,88.0,0.0,0.0,88.0,88.0
-698,PNG,Transformation,0.0,0.0,-55963.0,17628.0,-6331.0,-352.0,0.0,14140.0,-16000.0,-46877.0,-14752.0,0.0,-38335.0,-61018.0
-699,PNG,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-35565.0,-6331.0,-88.0,0.0,14140.0,-16000.0,-43843.0,-14488.0,0.0,-35565.0,-57984.0
-700,PNG,Electricity Plants,0.0,0.0,0.0,-35565.0,-6331.0,-88.0,0.0,14140.0,-16000.0,-43843.0,-14488.0,0.0,-35565.0,-57984.0
-701,PNG,CHP plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-702,PNG,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-703,PNG,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-704,PNG,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-705,PNG,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-706,PNG,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-707,PNG,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-708,PNG,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-709,PNG,Oil refineries,0.0,0.0,-55963.0,53193.0,0.0,0.0,0.0,0.0,0.0,-2770.0,0.0,0.0,-2770.0,-2770.0
-710,PNG,Other transformation,0.0,0.0,0.0,0.0,0.0,-264.0,0.0,0.0,0.0,-264.0,-264.0,0.0,0.0,-264.0
-711,PNG,Energy industries own use,0.0,0.0,0.0,0.0,-8546.0,0.0,0.0,-210.0,0.0,-8757.0,0.0,0.0,0.0,-8546.0
-712,PNG,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-1099.0,0.0,-1099.0,0.0,0.0,0.0,0.0
-713,PNG,Final consumption,0.0,0.0,0.0,55981.0,0.0,71789.0,0.0,16178.0,0.0,143948.0,71789.0,0.0,55981.0,127770.0
-714,PNG,Final Energy Consumption,0.0,0.0,0.0,55981.0,0.0,71789.0,0.0,16178.0,0.0,143948.0,71789.0,0.0,55981.0,127770.0
-715,PNG,Manufacturing  const. and mining,0.0,0.0,0.0,25058.0,0.0,2989.0,0.0,11870.0,0.0,39917.0,2989.0,0.0,25058.0,28047.0
-716,PNG,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-717,PNG,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-718,PNG,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-719,PNG,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-720,PNG,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-721,PNG,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-722,PNG,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-723,PNG,Food and tobacco,0.0,0.0,0.0,0.0,0.0,897.0,0.0,0.0,0.0,897.0,897.0,0.0,0.0,897.0
-724,PNG,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-725,PNG,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-726,PNG,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-727,PNG,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-728,PNG,Industry n.e.s,0.0,0.0,0.0,25058.0,0.0,2093.0,0.0,11870.0,0.0,39020.0,2093.0,0.0,25058.0,27151.0
-729,PNG,Transport,0.0,0.0,0.0,23911.0,0.0,0.0,0.0,0.0,0.0,23911.0,0.0,0.0,23911.0,23911.0
-730,PNG,Road,0.0,0.0,0.0,20618.0,0.0,0.0,0.0,0.0,0.0,20618.0,0.0,0.0,20618.0,20618.0
-731,PNG,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-732,PNG,Domestic aviation,0.0,0.0,0.0,3293.0,0.0,0.0,0.0,0.0,0.0,3293.0,0.0,0.0,3293.0,3293.0
-733,PNG,Domestic navigation,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-734,PNG,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-735,PNG,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-736,PNG,Other Consumption,0.0,0.0,0.0,7013.0,0.0,68800.0,0.0,4308.0,0.0,80121.0,68800.0,0.0,7013.0,75813.0
-737,PNG,Agriculture  forestry and fishing,0.0,0.0,0.0,4484.0,0.0,0.0,0.0,258.0,0.0,4743.0,0.0,0.0,4484.0,4484.0
-738,PNG,Commerce and public services,0.0,0.0,0.0,1023.0,0.0,10331.0,0.0,388.0,0.0,11741.0,10331.0,0.0,1023.0,11354.0
-739,PNG,Households,0.0,0.0,0.0,1506.0,0.0,58469.0,0.0,3662.0,0.0,63637.0,58469.0,0.0,1506.0,59975.0
-740,PNG,Other consumption n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-741,PNG,Non-energy use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-742,Fiji,Primary production,0.0,0.0,0.0,0.0,0.0,4593.0,0.0,2071.0,0.0,6664.0,6664.0,0.0,0.0,4593.0
-743,Fiji,Imports,0.0,0.0,0.0,38412.0,0.0,1.0,0.0,0.0,0.0,38412.0,1.0,0.0,38412.0,38413.0
-744,Fiji,Exports,0.0,0.0,0.0,-14587.0,0.0,0.0,0.0,0.0,0.0,-14587.0,0.0,0.0,-14587.0,-14587.0
-745,Fiji,International marine bunkers,0.0,0.0,0.0,-2567.0,0.0,0.0,0.0,0.0,0.0,-2567.0,0.0,0.0,-2567.0,-2567.0
-746,Fiji,International aviation bunkers,0.0,0.0,0.0,-1345.0,0.0,0.0,0.0,0.0,0.0,-1345.0,0.0,0.0,-1345.0,-1345.0
-747,Fiji,Stock changes,0.0,0.0,0.0,-441.0,0.0,0.0,0.0,0.0,0.0,-441.0,0.0,0.0,-441.0,-441.0
-748,Fiji,Total energy supply,0.0,0.0,0.0,19471.0,0.0,4594.0,0.0,2071.0,0.0,26136.0,6665.0,0.0,19471.0,24065.0
-749,Fiji,Statistical differences,0.0,0.0,0.0,-43.0,0.0,-1.0,0.0,1.0,0.0,-43.0,2071.0,0.0,-43.0,-44.0
-750,Fiji,Transfers and recycled products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-751,Fiji,Transformation,0.0,0.0,0.0,-4157.0,0.0,-506.0,0.0,1794.0,0.0,-2869.0,-506.0,0.0,-4157.0,-4663.0
-752,Fiji,Electricity  CHP & Heat Plants,0.0,0.0,0.0,-4157.0,0.0,-443.0,0.0,1794.0,0.0,-2806.0,-443.0,0.0,-4157.0,-4600.0
-753,Fiji,Electricity Plants,0.0,0.0,0.0,-4157.0,0.0,-18.0,0.0,1794.0,0.0,-2381.0,-18.0,0.0,-4157.0,-4175.0
-754,Fiji,CHP plants,0.0,0.0,0.0,0.0,0.0,-425.0,0.0,0.0,0.0,-425.0,-425.0,0.0,0.0,-425.0
-755,Fiji,Heat plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-756,Fiji,Coke ovens,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-757,Fiji,Briquetting plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-758,Fiji,Liquefaction plants,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-759,Fiji,Gas works,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-760,Fiji,Blast furnaces,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-761,Fiji,NGL & gas blending,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-762,Fiji,Oil refineries,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-763,Fiji,Other transformation,0.0,0.0,0.0,0.0,0.0,-63.0,0.0,0.0,0.0,-63.0,-63.0,0.0,0.0,-63.0
-764,Fiji,Energy industries own use,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-45.0,0.0,-45.0,0.0,0.0,0.0,0.0
-765,Fiji,Losses,0.0,0.0,0.0,0.0,0.0,0.0,0.0,-400.0,0.0,-400.0,0.0,0.0,0.0,0.0
-766,Fiji,Final consumption,0.0,0.0,0.0,15357.0,0.0,4088.0,0.0,3420.0,0.0,22865.0,4088.0,0.0,15357.0,19445.0
-767,Fiji,Final Energy Consumption,0.0,0.0,0.0,15076.0,0.0,4088.0,0.0,3420.0,0.0,22584.0,4088.0,0.0,15076.0,19164.0
-768,Fiji,Manufacturing  const. and mining,0.0,0.0,0.0,3368.0,0.0,3830.0,0.0,817.0,0.0,8016.0,3830.0,0.0,3368.0,7198.0
-769,Fiji,Iron and steel,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-770,Fiji,Chemical and petrochemical,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-771,Fiji,Non-ferrous metals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-772,Fiji,Non-metallic minerals,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-773,Fiji,Transport equipment,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-774,Fiji,Machinery,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-775,Fiji,Mining and quarrying,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-776,Fiji,Food and tobacco,0.0,0.0,0.0,0.0,0.0,3830.0,0.0,0.0,0.0,3830.0,3830.0,0.0,0.0,3830.0
-777,Fiji,Paper  pulp and printing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-778,Fiji,Wood and wood products,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-779,Fiji,Textile and leather,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-780,Fiji,Construction,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-781,Fiji,Industry n.e.s,0.0,0.0,0.0,3368.0,0.0,0.0,0.0,817.0,0.0,4186.0,0.0,0.0,3368.0,3368.0
-782,Fiji,Transport,0.0,0.0,0.0,10176.0,0.0,0.0,0.0,0.0,0.0,10176.0,0.0,0.0,10176.0,10176.0
-783,Fiji,Road,0.0,0.0,0.0,8063.0,0.0,0.0,0.0,0.0,0.0,8063.0,0.0,0.0,8063.0,8063.0
-784,Fiji,Rail,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-785,Fiji,Domestic aviation,0.0,0.0,0.0,551.0,0.0,0.0,0.0,0.0,0.0,551.0,0.0,0.0,551.0,551.0
-786,Fiji,Domestic navigation,0.0,0.0,0.0,1562.0,0.0,0.0,0.0,0.0,0.0,1562.0,0.0,0.0,1562.0,1562.0
-787,Fiji,Pipeline transport,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-788,Fiji,Transport n.e.s,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-789,Fiji,Other Consumption,0.0,0.0,0.0,1531.0,0.0,258.0,0.0,2603.0,0.0,4392.0,258.0,0.0,1531.0,1789.0
-790,Fiji,Agriculture  forestry and fishing,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
-791,Fiji,Commerce and public services,0.0,0.0,0.0,95.0,0.0,0.0,0.0,1537.0,0.0,1632.0,0.0,0.0,95.0,95.0
-792,Fiji,Households,0.0,0.0,0.0,1295.0,0.0,258.0,0.0,961.0,0.0,2513.0,258.0,0.0,1295.0,1553.0
-793,Fiji,Other consumption n.e.s,0.0,0.0,0.0,142.0,0.0,0.0,0.0,104.0,0.0,246.0,0.0,0.0,142.0,142.0
-794,Fiji,Non-energy use,0.0,0.0,0.0,281.0,0.0,0.0,0.0,0.0,0.0,281.0,0.0,0.0,281.0,281.0
+0,Samoa,Primary production,0,0,0,0,0,1464,0,265,3,1732,1732,0,0,1467
+1,Samoa,Imports,0,0,0,4813,0,0,0,0,0,4814,0,0,4813,4813
+2,Samoa,Exports,0,0,0,-42,0,0,0,0,0,-42,0,0,-42,-42
+3,Samoa,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+4,Samoa,International aviation bunkers,0,0,0,-532,0,0,0,0,0,-532,0,0,-532,-532
+5,Samoa,Stock changes,0,0,0,-275,0,0,0,0,0,-275,0,0,-275,-275
+6,Samoa,Total energy supply,0,0,0,3965,0,1464,0,265,3,5697,1732,0,3965,5432
+7,Samoa,Statistical differences,0,0,0,-2,0,0,0,0,0,-2,265,0,-2,-2
+8,Samoa,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+9,Samoa,Transformation,0,0,0,-903,0,-14,0,344,0,-573,-14,0,-903,-917
+10,Samoa,Electricity  CHP & Heat Plants,0,0,0,-903,0,0,0,344,0,-559,0,0,-903,-903
+11,Samoa,Electricity Plants,0,0,0,-903,0,0,0,344,0,-559,0,0,-903,-903
+12,Samoa,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+13,Samoa,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+14,Samoa,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+15,Samoa,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+16,Samoa,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+17,Samoa,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+18,Samoa,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+19,Samoa,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+20,Samoa,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+21,Samoa,Other transformation,0,0,0,0,0,-14,0,0,0,-14,-14,0,0,-14
+22,Samoa,Energy industries own use,0,0,0,0,0,0,0,-1,0,-1,0,0,0,0
+23,Samoa,Losses,0,0,0,0,0,0,0,-62,0,-62,0,0,0,0
+24,Samoa,Final consumption,0,0,0,3064,0,1450,0,546,3,5063,1453,0,3064,4517
+25,Samoa,Final Energy Consumption,0,0,0,2943,0,1450,0,546,3,4942,1453,0,2943,4396
+26,Samoa,Manufacturing  const. and mining,0,0,0,301,0,0,0,35,0,336,0,0,301,301
+27,Samoa,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+28,Samoa,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+29,Samoa,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+30,Samoa,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+31,Samoa,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+32,Samoa,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+33,Samoa,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+34,Samoa,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+35,Samoa,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+36,Samoa,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+37,Samoa,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+38,Samoa,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+39,Samoa,Industry n.e.s,0,0,0,301,0,0,0,35,0,336,0,0,301,301
+40,Samoa,Transport,0,0,0,2275,0,0,0,0,0,2275,0,0,2275,2275
+41,Samoa,Road,0,0,0,1931,0,0,0,0,0,1931,0,0,1931,1931
+42,Samoa,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+43,Samoa,Domestic aviation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+44,Samoa,Domestic navigation,0,0,0,344,0,0,0,0,0,344,0,0,344,344
+45,Samoa,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+46,Samoa,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+47,Samoa,Other Consumption,0,0,0,367,0,1450,0,512,3,2332,1453,0,367,1820
+48,Samoa,Agriculture  forestry and fishing,0,0,0,44,0,5,0,0,0,49,5,0,44,49
+49,Samoa,Commerce and public services,0,0,0,178,0,0,0,354,3,535,3,0,178,181
+50,Samoa,Households,0,0,0,145,0,1445,0,157,0,1747,1445,0,145,1590
+51,Samoa,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+52,Samoa,Non-energy use,0,0,0,121,0,0,0,0,0,121,0,0,121,121
+53,Nauru,Primary production,0,0,0,0,0,0,0,4,0,4,4,0,0,0
+54,Nauru,Imports,0,0,0,1059,0,0,0,0,0,1059,0,0,1059,1059
+55,Nauru,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+56,Nauru,International marine bunkers,0,0,0,-162,0,0,0,0,0,-162,0,0,-162,-162
+57,Nauru,International aviation bunkers,0,0,0,-164,0,0,0,0,0,-164,0,0,-164,-164
+58,Nauru,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+59,Nauru,Total energy supply,0,0,0,734,0,0,0,4,0,737,4,0,734,734
+60,Nauru,Statistical differences,0,0,0,-6,0,0,0,0,0,-6,4,0,-6,-6
+61,Nauru,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+62,Nauru,Transformation,0,0,0,-343,0,0,0,130,0,-213,0,0,-343,-343
+63,Nauru,Electricity  CHP & Heat Plants,0,0,0,-343,0,0,0,130,0,-213,0,0,-343,-343
+64,Nauru,Electricity Plants,0,0,0,-343,0,0,0,130,0,-213,0,0,-343,-343
+65,Nauru,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+66,Nauru,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+67,Nauru,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+68,Nauru,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+69,Nauru,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+70,Nauru,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+71,Nauru,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+72,Nauru,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+73,Nauru,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+74,Nauru,Other transformation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+75,Nauru,Energy industries own use,0,0,0,0,0,0,0,-4,0,-4,0,0,0,0
+76,Nauru,Losses,0,0,0,0,0,0,0,-16,0,-16,0,0,0,0
+77,Nauru,Final consumption,0,0,0,396,0,0,0,114,0,511,0,0,396,396
+78,Nauru,Final Energy Consumption,0,0,0,395,0,0,0,114,0,509,0,0,395,395
+79,Nauru,Manufacturing  const. and mining,0,0,0,0,0,0,0,7,0,7,0,0,0,0
+80,Nauru,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+81,Nauru,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+82,Nauru,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+83,Nauru,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+84,Nauru,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+85,Nauru,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+86,Nauru,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+87,Nauru,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+88,Nauru,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+89,Nauru,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+90,Nauru,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+91,Nauru,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+92,Nauru,Industry n.e.s,0,0,0,0,0,0,0,7,0,7,0,0,0,0
+93,Nauru,Transport,0,0,0,208,0,0,0,0,0,208,0,0,208,208
+94,Nauru,Road,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+95,Nauru,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+96,Nauru,Domestic aviation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+97,Nauru,Domestic navigation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+98,Nauru,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+99,Nauru,Transport n.e.s,0,0,0,208,0,0,0,0,0,208,0,0,208,208
+100,Nauru,Other Consumption,0,0,0,187,0,0,0,108,0,294,0,0,187,187
+101,Nauru,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+102,Nauru,Commerce and public services,0,0,0,0,0,0,0,47,0,47,0,0,0,0
+103,Nauru,Households,0,0,0,1,0,0,0,54,0,55,0,0,1,1
+104,Nauru,Other consumption n.e.s,0,0,0,186,0,0,0,6,0,192,0,0,186,186
+105,Nauru,Non-energy use,0,0,0,2,0,0,0,0,0,2,0,0,2,2
+106,Vanuatu,Primary production,0,0,0,0,0,840,0,70,0,909,909,0,0,840
+107,Vanuatu,Imports,0,0,0,2965,0,0,0,0,0,2965,0,0,2965,2965
+108,Vanuatu,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+109,Vanuatu,International marine bunkers,0,0,0,-222,0,0,0,0,0,-222,0,0,-222,-222
+110,Vanuatu,International aviation bunkers,0,0,0,-348,0,0,0,0,0,-348,0,0,-348,-348
+111,Vanuatu,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+112,Vanuatu,Total energy supply,0,0,0,2395,0,840,0,70,0,3304,909,0,2395,3235
+113,Vanuatu,Statistical differences,0,0,0,0,0,0,0,0,0,0,70,0,0,0
+114,Vanuatu,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+115,Vanuatu,Transformation,0,0,0,-621,0,-25,0,227,0,-419,-25,0,-621,-646
+116,Vanuatu,Electricity  CHP & Heat Plants,0,0,0,-621,0,-8,0,227,0,-402,-8,0,-621,-629
+117,Vanuatu,Electricity Plants,0,0,0,-621,0,-8,0,227,0,-402,-8,0,-621,-629
+118,Vanuatu,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+119,Vanuatu,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+120,Vanuatu,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+121,Vanuatu,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+122,Vanuatu,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+123,Vanuatu,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+124,Vanuatu,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+125,Vanuatu,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+126,Vanuatu,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+127,Vanuatu,Other transformation,0,0,0,0,0,-17,0,0,0,-17,-17,0,0,-17
+128,Vanuatu,Energy industries own use,0,0,0,0,0,0,0,-7,0,-7,0,0,0,0
+129,Vanuatu,Losses,0,0,0,0,0,0,0,-21,0,-21,0,0,0,0
+130,Vanuatu,Final consumption,0,0,0,1774,0,815,0,269,0,2858,815,0,1774,2589
+131,Vanuatu,Final Energy Consumption,0,0,0,1683,0,815,0,269,0,2767,815,0,1683,2498
+132,Vanuatu,Manufacturing  const. and mining,0,0,0,0,0,0,0,103,0,103,0,0,0,0
+133,Vanuatu,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+134,Vanuatu,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+135,Vanuatu,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+136,Vanuatu,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+137,Vanuatu,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+138,Vanuatu,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+139,Vanuatu,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+140,Vanuatu,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+141,Vanuatu,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+142,Vanuatu,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+143,Vanuatu,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+144,Vanuatu,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+145,Vanuatu,Industry n.e.s,0,0,0,0,0,0,0,103,0,103,0,0,0,0
+146,Vanuatu,Transport,0,0,0,1619,0,0,0,0,0,1619,0,0,1619,1619
+147,Vanuatu,Road,0,0,0,1458,0,0,0,0,0,1458,0,0,1458,1458
+148,Vanuatu,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+149,Vanuatu,Domestic aviation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+150,Vanuatu,Domestic navigation,0,0,0,161,0,0,0,0,0,161,0,0,161,161
+151,Vanuatu,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+152,Vanuatu,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+153,Vanuatu,Other Consumption,0,0,0,64,0,815,0,166,0,1045,815,0,64,879
+154,Vanuatu,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+155,Vanuatu,Commerce and public services,0,0,0,0,0,0,0,69,0,69,0,0,0,0
+156,Vanuatu,Households,0,0,0,64,0,815,0,93,0,971,815,0,64,879
+157,Vanuatu,Other consumption n.e.s,0,0,0,0,0,0,0,5,0,5,0,0,0,0
+158,Vanuatu,Non-energy use,0,0,0,91,0,0,0,0,0,91,0,0,91,91
+159,Palau,Primary production,0,0,0,0,0,0,0,7,0,7,7,0,0,0
+160,Palau,Imports,0,0,0,3659,0,0,0,0,0,3659,0,0,3659,3659
+161,Palau,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+162,Palau,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+163,Palau,International aviation bunkers,0,0,0,-618,0,0,0,0,0,-618,0,0,-618,-618
+164,Palau,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+165,Palau,Total energy supply,0,0,0,3041,0,0,0,7,0,3049,8,0,3041,3041
+166,Palau,Statistical differences,0,0,0,0,0,0,0,0,0,0,7,0,0,0
+167,Palau,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+168,Palau,Transformation,0,0,0,-1075,0,0,0,340,0,-735,0,0,-1075,-1075
+169,Palau,Electricity  CHP & Heat Plants,0,0,0,-1075,0,0,0,340,0,-735,0,0,-1075,-1075
+170,Palau,Electricity Plants,0,0,0,-1075,0,0,0,340,0,-735,0,0,-1075,-1075
+171,Palau,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+172,Palau,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+173,Palau,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+174,Palau,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+175,Palau,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+176,Palau,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+177,Palau,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+178,Palau,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+179,Palau,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+180,Palau,Other transformation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+181,Palau,Energy industries own use,0,0,0,0,0,0,0,-18,0,-18,0,0,0,0
+182,Palau,Losses,0,0,0,0,0,0,0,-40,0,-40,0,0,0,0
+183,Palau,Final consumption,0,0,0,1966,0,0,0,290,0,2256,0,0,1966,1966
+184,Palau,Final Energy Consumption,0,0,0,1926,0,0,0,290,0,2216,0,0,1926,1926
+185,Palau,Manufacturing  const. and mining,0,0,0,0,0,0,0,22,0,22,0,0,0,0
+186,Palau,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+187,Palau,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+188,Palau,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+189,Palau,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+190,Palau,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+191,Palau,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+192,Palau,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+193,Palau,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+194,Palau,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+195,Palau,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+196,Palau,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+197,Palau,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+198,Palau,Industry n.e.s,0,0,0,0,0,0,0,22,0,22,0,0,0,0
+199,Palau,Transport,0,0,0,1834,0,0,0,0,0,1834,0,0,1834,1834
+200,Palau,Road,0,0,0,545,0,0,0,0,0,545,0,0,545,545
+201,Palau,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+202,Palau,Domestic aviation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+203,Palau,Domestic navigation,0,0,0,1289,0,0,0,0,0,1289,0,0,1289,1289
+204,Palau,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+205,Palau,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+206,Palau,Other Consumption,0,0,0,92,0,0,0,268,0,361,0,0,92,92
+207,Palau,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+208,Palau,Commerce and public services,0,0,0,0,0,0,0,158,0,158,0,0,0,0
+209,Palau,Households,0,0,0,92,0,0,0,85,0,177,0,0,92,92
+210,Palau,Other consumption n.e.s,0,0,0,0,0,0,0,25,0,25,0,0,0,0
+211,Palau,Non-energy use,0,0,0,40,0,0,0,0,0,40,0,0,40,40
+212,Kiribati,Primary production,0,0,0,0,0,545,0,18,0,563,563,0,0,545
+213,Kiribati,Imports,0,0,0,1048,0,0,0,0,0,1048,0,0,1048,1048
+214,Kiribati,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+215,Kiribati,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+216,Kiribati,International aviation bunkers,0,0,0,-27,0,0,0,0,0,-27,0,0,-27,-27
+217,Kiribati,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+218,Kiribati,Total energy supply,0,0,0,1020,0,545,0,18,0,1583,563,0,1020,1565
+219,Kiribati,Statistical differences,0,0,0,0,0,0,0,0,0,0,18,0,0,0
+220,Kiribati,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+221,Kiribati,Transformation,0,0,0,-305,0,-11,0,96,0,-219,-11,0,-305,-316
+222,Kiribati,Electricity  CHP & Heat Plants,0,0,0,-305,0,0,0,96,0,-209,0,0,-305,-305
+223,Kiribati,Electricity Plants,0,0,0,-305,0,0,0,96,0,-209,0,0,-305,-305
+224,Kiribati,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+225,Kiribati,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+226,Kiribati,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+227,Kiribati,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+228,Kiribati,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+229,Kiribati,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+230,Kiribati,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+231,Kiribati,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+232,Kiribati,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+233,Kiribati,Other transformation,0,0,0,0,0,-11,0,0,0,-11,-11,0,0,-11
+234,Kiribati,Energy industries own use,0,0,0,0,0,0,0,-5,0,-5,0,0,0,0
+235,Kiribati,Losses,0,0,0,0,0,0,0,-17,0,-17,0,0,0,0
+236,Kiribati,Final consumption,0,0,0,715,0,534,0,93,0,1342,534,0,715,1249
+237,Kiribati,Final Energy Consumption,0,0,0,711,0,534,0,93,0,1338,534,0,711,1245
+238,Kiribati,Manufacturing  const. and mining,0,0,0,9,0,0,0,8,0,17,0,0,9,9
+239,Kiribati,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+240,Kiribati,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+241,Kiribati,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+242,Kiribati,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+243,Kiribati,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+244,Kiribati,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+245,Kiribati,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+246,Kiribati,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+247,Kiribati,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+248,Kiribati,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+249,Kiribati,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+250,Kiribati,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+251,Kiribati,Industry n.e.s,0,0,0,9,0,0,0,8,0,17,0,0,9,9
+252,Kiribati,Transport,0,0,0,449,0,0,0,0,0,449,0,0,449,449
+253,Kiribati,Road,0,0,0,353,0,0,0,0,0,353,0,0,353,353
+254,Kiribati,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+255,Kiribati,Domestic aviation,0,0,0,36,0,0,0,0,0,36,0,0,36,36
+256,Kiribati,Domestic navigation,0,0,0,60,0,0,0,0,0,60,0,0,60,60
+257,Kiribati,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+258,Kiribati,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+259,Kiribati,Other Consumption,0,0,0,253,0,534,0,85,0,872,534,0,253,787
+260,Kiribati,Agriculture  forestry and fishing,0,0,0,119,0,0,0,0,0,119,0,0,119,119
+261,Kiribati,Commerce and public services,0,0,0,32,0,0,0,46,0,78,0,0,32,32
+262,Kiribati,Households,0,0,0,102,0,534,0,38,0,675,534,0,102,636
+263,Kiribati,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+264,Kiribati,Non-energy use,0,0,0,4,0,0,0,0,0,4,0,0,4,4
+265,Cook Islands,Primary production,0,0,0,0,0,0,0,36,0,36,36,0,0,0
+266,Cook Islands,Imports,0,0,0,1552,0,0,0,0,0,1552,0,0,1552,1552
+267,Cook Islands,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+268,Cook Islands,International marine bunkers,0,0,0,-65,0,0,0,0,0,-65,0,0,-65,-65
+269,Cook Islands,International aviation bunkers,0,0,0,-338,0,0,0,0,0,-338,0,0,-338,-338
+270,Cook Islands,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+271,Cook Islands,Total energy supply,0,0,0,1149,0,0,0,36,0,1185,36,0,1149,1149
+272,Cook Islands,Statistical differences,0,0,0,0,0,0,0,0,0,0,36,0,0,0
+273,Cook Islands,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+274,Cook Islands,Transformation,0,0,0,-322,0,0,0,104,0,-219,0,0,-322,-322
+275,Cook Islands,Electricity  CHP & Heat Plants,0,0,0,-322,0,0,0,104,0,-219,0,0,-322,-322
+276,Cook Islands,Electricity Plants,0,0,0,-322,0,0,0,104,0,-219,0,0,-322,-322
+277,Cook Islands,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+278,Cook Islands,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+279,Cook Islands,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+280,Cook Islands,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+281,Cook Islands,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+282,Cook Islands,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+283,Cook Islands,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+284,Cook Islands,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+285,Cook Islands,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+286,Cook Islands,Other transformation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+287,Cook Islands,Energy industries own use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+288,Cook Islands,Losses,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+289,Cook Islands,Final consumption,0,0,0,827,0,0,0,139,0,966,0,0,827,827
+290,Cook Islands,Final Energy Consumption,0,0,0,827,0,0,0,139,0,966,0,0,827,827
+291,Cook Islands,Manufacturing  const. and mining,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+292,Cook Islands,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+293,Cook Islands,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+294,Cook Islands,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+295,Cook Islands,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+296,Cook Islands,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+297,Cook Islands,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+298,Cook Islands,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+299,Cook Islands,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+300,Cook Islands,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+301,Cook Islands,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+302,Cook Islands,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+303,Cook Islands,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+304,Cook Islands,Industry n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+305,Cook Islands,Transport,0,0,0,827,0,0,0,0,0,827,0,0,827,827
+306,Cook Islands,Road,0,0,0,353,0,0,0,0,0,353,0,0,353,353
+307,Cook Islands,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+308,Cook Islands,Domestic aviation,0,0,0,85,0,0,0,0,0,85,0,0,85,85
+309,Cook Islands,Domestic navigation,0,0,0,97,0,0,0,0,0,97,0,0,97,97
+310,Cook Islands,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+311,Cook Islands,Transport n.e.s,0,0,0,292,0,0,0,0,0,292,0,0,292,292
+312,Cook Islands,Other Consumption,0,0,0,0,0,0,0,139,0,139,0,0,0,0
+313,Cook Islands,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+314,Cook Islands,Commerce and public services,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+315,Cook Islands,Households,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+316,Cook Islands,Other consumption n.e.s,0,0,0,0,0,0,0,139,0,139,0,0,0,0
+317,Cook Islands,Non-energy use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+318,Solomon Islands,Primary production,0,0,0,0,0,3310,0,18,0,3328,3328,0,0,3310
+319,Solomon Islands,Imports,0,0,0,4684,0,0,0,0,0,4684,0,0,4684,4684
+320,Solomon Islands,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+321,Solomon Islands,International marine bunkers,0,0,0,-240,0,0,0,0,0,-240,0,0,-240,-240
+322,Solomon Islands,International aviation bunkers,0,0,0,-170,0,0,0,0,0,-170,0,0,-170,-170
+323,Solomon Islands,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+324,Solomon Islands,Total energy supply,0,0,0,4274,0,3310,0,18,0,7602,3328,0,4274,7584
+325,Solomon Islands,Statistical differences,0,0,0,4,0,0,0,3,0,7,18,0,4,4
+326,Solomon Islands,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+327,Solomon Islands,Transformation,0,0,0,-1027,0,-73,0,368,0,-732,-73,0,-1027,-1100
+328,Solomon Islands,Electricity  CHP & Heat Plants,0,0,0,-1027,0,-36,0,368,0,-695,-36,0,-1027,-1063
+329,Solomon Islands,Electricity Plants,0,0,0,-1027,0,-36,0,368,0,-695,-36,0,-1027,-1063
+330,Solomon Islands,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+331,Solomon Islands,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+332,Solomon Islands,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+333,Solomon Islands,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+334,Solomon Islands,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+335,Solomon Islands,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+336,Solomon Islands,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+337,Solomon Islands,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+338,Solomon Islands,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+339,Solomon Islands,Other transformation,0,0,0,0,0,-37,0,0,0,-37,-37,0,0,-37
+340,Solomon Islands,Energy industries own use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+341,Solomon Islands,Losses,0,0,0,0,0,0,0,-65,0,-65,0,0,0,0
+342,Solomon Islands,Final consumption,0,0,0,3243,0,3237,0,318,0,6797,3237,0,3243,6480
+343,Solomon Islands,Final Energy Consumption,0,0,0,3180,0,3237,0,318,0,6734,3237,0,3180,6417
+344,Solomon Islands,Manufacturing  const. and mining,0,0,0,268,0,0,0,146,0,414,0,0,268,268
+345,Solomon Islands,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+346,Solomon Islands,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+347,Solomon Islands,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+348,Solomon Islands,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+349,Solomon Islands,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+350,Solomon Islands,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+351,Solomon Islands,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+352,Solomon Islands,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+353,Solomon Islands,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+354,Solomon Islands,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+355,Solomon Islands,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+356,Solomon Islands,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+357,Solomon Islands,Industry n.e.s,0,0,0,268,0,0,0,146,0,414,0,0,268,268
+358,Solomon Islands,Transport,0,0,0,2681,0,0,0,0,0,2681,0,0,2681,2681
+359,Solomon Islands,Road,0,0,0,2285,0,0,0,0,0,2285,0,0,2285,2285
+360,Solomon Islands,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+361,Solomon Islands,Domestic aviation,0,0,0,37,0,0,0,0,0,37,0,0,37,37
+362,Solomon Islands,Domestic navigation,0,0,0,360,0,0,0,0,0,360,0,0,360,360
+363,Solomon Islands,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+364,Solomon Islands,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+365,Solomon Islands,Other Consumption,0,0,0,231,0,3237,0,172,0,3639,3237,0,231,3468
+366,Solomon Islands,Agriculture  forestry and fishing,0,0,0,217,0,0,0,0,0,217,0,0,217,217
+367,Solomon Islands,Commerce and public services,0,0,0,0,0,0,0,73,0,73,0,0,0,0
+368,Solomon Islands,Households,0,0,0,13,0,3237,0,63,0,3313,3237,0,13,3250
+369,Solomon Islands,Other consumption n.e.s,0,0,0,0,0,0,0,36,0,36,0,0,0,0
+370,Solomon Islands,Non-energy use,0,0,0,63,0,0,0,0,0,63,0,0,63,63
+371,Tonga,Primary production,0,0,0,0,0,19,0,23,0,42,42,0,0,19
+372,Tonga,Imports,0,0,0,2050,0,0,0,0,0,2050,0,0,2050,2050
+373,Tonga,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+374,Tonga,International marine bunkers,0,0,0,-16,0,0,0,0,0,-16,0,0,-16,-16
+375,Tonga,International aviation bunkers,0,0,0,-159,0,0,0,0,0,-159,0,0,-159,-159
+376,Tonga,Stock changes,0,0,0,364,0,0,0,0,0,364,0,0,364,364
+377,Tonga,Total energy supply,0,0,0,2239,0,19,0,23,0,2281,42,0,2239,2258
+378,Tonga,Statistical differences,0,0,0,0,0,0,0,0,0,0,23,0,0,0
+379,Tonga,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+380,Tonga,Transformation,0,0,0,-602,0,-6,0,231,0,-377,-6,0,-602,-608
+381,Tonga,Electricity  CHP & Heat Plants,0,0,0,-602,0,0,0,231,0,-371,0,0,-602,-602
+382,Tonga,Electricity Plants,0,0,0,-602,0,0,0,231,0,-371,0,0,-602,-602
+383,Tonga,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+384,Tonga,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+385,Tonga,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+386,Tonga,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+387,Tonga,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+388,Tonga,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+389,Tonga,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+390,Tonga,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+391,Tonga,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+392,Tonga,Other transformation,0,0,0,0,0,-6,0,0,0,-6,-6,0,0,-6
+393,Tonga,Energy industries own use,0,0,0,0,0,0,0,-7,0,-7,0,0,0,0
+394,Tonga,Losses,0,0,0,0,0,0,0,-21,0,-21,0,0,0,0
+395,Tonga,Final consumption,0,0,0,1637,0,12,0,226,0,1876,12,0,1637,1649
+396,Tonga,Final Energy Consumption,0,0,0,1627,0,12,0,226,0,1866,12,0,1627,1639
+397,Tonga,Manufacturing  const. and mining,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+398,Tonga,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+399,Tonga,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+400,Tonga,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+401,Tonga,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+402,Tonga,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+403,Tonga,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+404,Tonga,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+405,Tonga,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+406,Tonga,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+407,Tonga,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+408,Tonga,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+409,Tonga,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+410,Tonga,Industry n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+411,Tonga,Transport,0,0,0,1523,0,0,0,0,0,1523,0,0,1523,1523
+412,Tonga,Road,0,0,0,1099,0,0,0,0,0,1099,0,0,1099,1099
+413,Tonga,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+414,Tonga,Domestic aviation,0,0,0,4,0,0,0,0,0,4,0,0,4,4
+415,Tonga,Domestic navigation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+416,Tonga,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+417,Tonga,Transport n.e.s,0,0,0,420,0,0,0,0,0,420,0,0,420,420
+418,Tonga,Other Consumption,0,0,0,104,0,12,0,226,0,343,12,0,104,116
+419,Tonga,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+420,Tonga,Commerce and public services,0,0,0,0,0,0,0,75,0,75,0,0,0,0
+421,Tonga,Households,0,0,0,104,0,12,0,81,0,198,12,0,104,116
+422,Tonga,Other consumption n.e.s,0,0,0,0,0,0,0,70,0,70,0,0,0,0
+423,Tonga,Non-energy use,0,0,0,10,0,0,0,0,0,10,0,0,10,10
+424,New Caledonia,Primary production,0,0,0,0,0,124,0,1647,141,1912,1912,0,0,265
+425,New Caledonia,Imports,26739,0,0,38116,0,1,0,0,0,64856,1,26739,38116,64856
+426,New Caledonia,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+427,New Caledonia,International marine bunkers,0,0,0,-391,0,0,0,0,0,-391,0,0,-391,-391
+428,New Caledonia,International aviation bunkers,0,0,0,-1191,0,0,0,0,0,-1191,0,0,-1191,-1191
+429,New Caledonia,Stock changes,706,0,0,-231,0,0,0,0,0,475,0,706,-231,475
+430,New Caledonia,Total energy supply,27445,0,0,36304,0,125,0,1647,141,65661,1913,27445,36304,64015
+431,New Caledonia,Statistical differences,-676,0,0,-185,0,0,0,-347,0,-1208,1647,-676,-185,-861
+432,New Caledonia,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+433,New Caledonia,Transformation,-18820,0,0,-16397,0,-22,0,10352,0,-24887,-22,-18820,-16397,-35239
+434,New Caledonia,Electricity  CHP & Heat Plants,-18820,0,0,-16397,0,-5,0,10352,0,-24870,-5,-18820,-16397,-35222
+435,New Caledonia,Electricity Plants,-18820,0,0,-16397,0,-5,0,10352,0,-24870,-5,-18820,-16397,-35222
+436,New Caledonia,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+437,New Caledonia,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+438,New Caledonia,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+439,New Caledonia,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+440,New Caledonia,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+441,New Caledonia,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+442,New Caledonia,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+443,New Caledonia,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+444,New Caledonia,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+445,New Caledonia,Other transformation,0,0,0,0,0,-16,0,0,0,-16,-16,0,0,-16
+446,New Caledonia,Energy industries own use,0,0,0,0,0,0,0,-15,0,-15,0,0,0,0
+447,New Caledonia,Losses,0,0,0,0,0,0,0,-204,0,-204,0,0,0,0
+448,New Caledonia,Final consumption,9300,0,0,20092,0,103,0,12128,141,41764,244,9300,20092,29636
+449,New Caledonia,Final Energy Consumption,3733,0,0,19270,0,103,0,12128,141,35374,244,3733,19270,23247
+450,New Caledonia,Manufacturing  const. and mining,3733,0,0,9592,0,0,0,9373,0,22698,0,3733,9592,13325
+451,New Caledonia,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+452,New Caledonia,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+453,New Caledonia,Non-ferrous metals,0,0,0,2937,0,0,0,8916,0,11853,0,0,2937,2937
+454,New Caledonia,Non-metallic minerals,3733,0,0,3163,0,0,0,0,0,6896,0,3733,3163,6896
+455,New Caledonia,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+456,New Caledonia,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+457,New Caledonia,Mining and quarrying,0,0,0,2915,0,0,0,112,0,3027,0,0,2915,2915
+458,New Caledonia,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+459,New Caledonia,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+460,New Caledonia,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+461,New Caledonia,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+462,New Caledonia,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+463,New Caledonia,Industry n.e.s,0,0,0,577,0,0,0,346,0,922,0,0,577,577
+464,New Caledonia,Transport,0,0,0,8946,0,0,0,0,0,8946,0,0,8946,8946
+465,New Caledonia,Road,0,0,0,7948,0,0,0,0,0,7948,0,0,7948,7948
+466,New Caledonia,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+467,New Caledonia,Domestic aviation,0,0,0,265,0,0,0,0,0,265,0,0,265,265
+468,New Caledonia,Domestic navigation,0,0,0,733,0,0,0,0,0,733,0,0,733,733
+469,New Caledonia,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+470,New Caledonia,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+471,New Caledonia,Other Consumption,0,0,0,732,0,103,0,2754,141,3730,244,0,732,976
+472,New Caledonia,Agriculture  forestry and fishing,0,0,0,224,0,0,0,0,0,224,0,0,224,224
+473,New Caledonia,Commerce and public services,0,0,0,146,0,0,0,1690,141,1977,141,0,146,287
+474,New Caledonia,Households,0,0,0,362,0,103,0,1065,0,1529,103,0,362,465
+475,New Caledonia,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+476,New Caledonia,Non-energy use,5568,0,0,822,0,0,0,0,0,6390,0,5568,822,6390
+477,French Polynesia,Primary production,0,0,0,0,0,43,0,716,80,839,839,0,0,123
+478,French Polynesia,Imports,0,0,0,12634,0,7,0,0,0,12641,7,0,12634,12641
+479,French Polynesia,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+480,French Polynesia,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+481,French Polynesia,International aviation bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+482,French Polynesia,Stock changes,0,0,0,-260,0,0,0,0,0,-260,0,0,-260,-260
+483,French Polynesia,Total energy supply,0,0,0,12374,0,49,0,716,80,13220,845,0,12374,12503
+484,French Polynesia,Statistical differences,0,0,0,43,0,0,0,0,0,43,716,0,43,43
+485,French Polynesia,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+486,French Polynesia,Transformation,0,0,0,-4378,0,-14,0,1777,0,-2615,-14,0,-4378,-4392
+487,French Polynesia,Electricity  CHP & Heat Plants,0,0,0,-4378,0,0,0,1777,0,-2601,0,0,-4378,-4378
+488,French Polynesia,Electricity Plants,0,0,0,-4378,0,0,0,1777,0,-2601,0,0,-4378,-4378
+489,French Polynesia,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+490,French Polynesia,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+491,French Polynesia,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+492,French Polynesia,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+493,French Polynesia,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+494,French Polynesia,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+495,French Polynesia,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+496,French Polynesia,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+497,French Polynesia,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+498,French Polynesia,Other transformation,0,0,0,0,0,-14,0,0,0,-14,-14,0,0,-14
+499,French Polynesia,Energy industries own use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+500,French Polynesia,Losses,0,0,0,0,0,0,0,-146,0,-146,0,0,0,0
+501,French Polynesia,Final consumption,0,0,0,7954,0,36,0,2347,80,10416,115,0,7954,8070
+502,French Polynesia,Final Energy Consumption,0,0,0,7837,0,36,0,2347,80,10299,115,0,7837,7953
+503,French Polynesia,Manufacturing  const. and mining,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+504,French Polynesia,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+505,French Polynesia,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+506,French Polynesia,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+507,French Polynesia,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+508,French Polynesia,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+509,French Polynesia,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+510,French Polynesia,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+511,French Polynesia,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+512,French Polynesia,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+513,French Polynesia,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+514,French Polynesia,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+515,French Polynesia,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+516,French Polynesia,Industry n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+517,French Polynesia,Transport,0,0,0,6906,0,0,0,0,0,6906,0,0,6906,6906
+518,French Polynesia,Road,0,0,0,5492,0,0,0,0,0,5492,0,0,5492,5492
+519,French Polynesia,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+520,French Polynesia,Domestic aviation,0,0,0,603,0,0,0,0,0,603,0,0,603,603
+521,French Polynesia,Domestic navigation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+522,French Polynesia,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+523,French Polynesia,Transport n.e.s,0,0,0,812,0,0,0,0,0,812,0,0,812,812
+524,French Polynesia,Other Consumption,0,0,0,931,0,36,0,2347,80,3393,115,0,931,1047
+525,French Polynesia,Agriculture  forestry and fishing,0,0,0,460,0,0,0,0,0,460,0,0,460,460
+526,French Polynesia,Commerce and public services,0,0,0,0,0,0,0,1056,0,1056,0,0,0,0
+527,French Polynesia,Households,0,0,0,472,0,36,0,1291,80,1877,115,0,472,588
+528,French Polynesia,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+529,French Polynesia,Non-energy use,0,0,0,117,0,0,0,0,0,117,0,0,117,117
+530,Micronesia,Primary production,0,0,0,0,0,25,0,15,0,40,40,0,0,25
+531,Micronesia,Imports,0,0,0,2574,0,0,0,0,0,2574,0,0,2574,2574
+532,Micronesia,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+533,Micronesia,International marine bunkers,0,0,0,-142,0,0,0,0,0,-142,0,0,-142,-142
+534,Micronesia,International aviation bunkers,0,0,0,-295,0,0,0,0,0,-295,0,0,-295,-295
+535,Micronesia,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+536,Micronesia,Total energy supply,0,0,0,2138,0,25,0,15,0,2177,40,0,2138,2163
+537,Micronesia,Statistical differences,0,0,0,0,0,0,0,0,0,0,15,0,0,0
+538,Micronesia,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+539,Micronesia,Transformation,0,0,0,-826,0,-10,0,233,0,-602,-10,0,-826,-836
+540,Micronesia,Electricity  CHP & Heat Plants,0,0,0,-826,0,0,0,233,0,-592,0,0,-826,-826
+541,Micronesia,Electricity Plants,0,0,0,-826,0,0,0,233,0,-592,0,0,-826,-826
+542,Micronesia,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+543,Micronesia,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+544,Micronesia,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+545,Micronesia,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+546,Micronesia,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+547,Micronesia,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+548,Micronesia,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+549,Micronesia,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+550,Micronesia,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+551,Micronesia,Other transformation,0,0,0,0,0,-10,0,0,0,-10,-10,0,0,-10
+552,Micronesia,Energy industries own use,0,0,0,0,0,0,0,-9,0,-9,0,0,0,0
+553,Micronesia,Losses,0,0,0,0,0,0,0,-74,0,-74,0,0,0,0
+554,Micronesia,Final consumption,0,0,0,1312,0,15,0,166,0,1492,15,0,1312,1327
+555,Micronesia,Final Energy Consumption,0,0,0,1219,0,15,0,166,0,1400,15,0,1219,1234
+556,Micronesia,Manufacturing  const. and mining,0,0,0,0,0,0,0,53,0,53,0,0,0,0
+557,Micronesia,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+558,Micronesia,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+559,Micronesia,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+560,Micronesia,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+561,Micronesia,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+562,Micronesia,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+563,Micronesia,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+564,Micronesia,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+565,Micronesia,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+566,Micronesia,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+567,Micronesia,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+568,Micronesia,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+569,Micronesia,Industry n.e.s,0,0,0,0,0,0,0,53,0,53,0,0,0,0
+570,Micronesia,Transport,0,0,0,1175,0,0,0,0,0,1175,0,0,1175,1175
+571,Micronesia,Road,0,0,0,714,0,0,0,0,0,714,0,0,714,714
+572,Micronesia,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+573,Micronesia,Domestic aviation,0,0,0,46,0,0,0,0,0,46,0,0,46,46
+574,Micronesia,Domestic navigation,0,0,0,415,0,0,0,0,0,415,0,0,415,415
+575,Micronesia,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+576,Micronesia,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+577,Micronesia,Other Consumption,0,0,0,45,0,15,0,113,0,172,15,0,45,60
+578,Micronesia,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+579,Micronesia,Commerce and public services,0,0,0,0,0,0,0,52,0,52,0,0,0,0
+580,Micronesia,Households,0,0,0,0,0,4,0,61,0,64,4,0,0,4
+581,Micronesia,Other consumption n.e.s,0,0,0,45,0,11,0,0,0,56,11,0,45,56
+582,Micronesia,Non-energy use,0,0,0,92,0,0,0,0,0,92,0,0,92,92
+583,Niue,Primary production,0,0,0,0,0,1,0,2,16,18,18,0,0,17
+584,Niue,Imports,0,0,0,110,0,0,0,0,0,110,0,0,110,110
+585,Niue,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+586,Niue,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+587,Niue,International aviation bunkers,0,0,0,-21,0,0,0,0,0,-21,0,0,-21,-21
+588,Niue,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+589,Niue,Total energy supply,0,0,0,89,0,1,0,2,16,107,18,0,89,106
+590,Niue,Statistical differences,0,0,0,-1,0,0,0,0,0,-1,2,0,-1,-1
+591,Niue,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+592,Niue,Transformation,0,0,0,-39,0,0,0,13,0,-26,0,0,-39,-39
+593,Niue,Electricity  CHP & Heat Plants,0,0,0,-39,0,0,0,13,0,-26,0,0,-39,-39
+594,Niue,Electricity Plants,0,0,0,-39,0,0,0,13,0,-26,0,0,-39,-39
+595,Niue,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+596,Niue,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+597,Niue,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+598,Niue,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+599,Niue,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+600,Niue,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+601,Niue,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+602,Niue,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+603,Niue,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+604,Niue,Other transformation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+605,Niue,Energy industries own use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+606,Niue,Losses,0,0,0,0,0,0,0,-1,0,-1,0,0,0,0
+607,Niue,Final consumption,0,0,0,51,0,0,0,12,16,80,16,0,51,67
+608,Niue,Final Energy Consumption,0,0,0,51,0,0,0,12,16,80,16,0,51,67
+609,Niue,Manufacturing  const. and mining,0,0,0,2,0,0,0,3,0,5,0,0,2,2
+610,Niue,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+611,Niue,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+612,Niue,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+613,Niue,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+614,Niue,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+615,Niue,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+616,Niue,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+617,Niue,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+618,Niue,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+619,Niue,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+620,Niue,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+621,Niue,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+622,Niue,Industry n.e.s,0,0,0,2,0,0,0,3,0,5,0,0,2,2
+623,Niue,Transport,0,0,0,44,0,0,0,0,0,44,0,0,44,44
+624,Niue,Road,0,0,0,43,0,0,0,0,0,43,0,0,43,43
+625,Niue,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+626,Niue,Domestic aviation,0,0,0,1,0,0,0,0,0,1,0,0,1,1
+627,Niue,Domestic navigation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+628,Niue,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+629,Niue,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+630,Niue,Other Consumption,0,0,0,5,0,0,0,10,16,31,16,0,5,21
+631,Niue,Agriculture  forestry and fishing,0,0,0,1,0,0,0,0,0,1,0,0,1,1
+632,Niue,Commerce and public services,0,0,0,1,0,0,0,5,0,6,0,0,1,1
+633,Niue,Households,0,0,0,2,0,0,0,5,16,23,16,0,2,18
+634,Niue,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+635,Niue,Non-energy use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+636,Tuvalu,Primary production,0,0,0,0,0,0,0,7,0,7,7,0,0,0
+637,Tuvalu,Imports,0,0,0,132,0,0,0,0,0,132,0,0,132,132
+638,Tuvalu,Exports,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+639,Tuvalu,International marine bunkers,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+640,Tuvalu,International aviation bunkers,0,0,0,-9,0,0,0,0,0,-9,0,0,-9,-9
+641,Tuvalu,Stock changes,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+642,Tuvalu,Total energy supply,0,0,0,122,0,0,0,7,0,130,7,0,122,122
+643,Tuvalu,Statistical differences,0,0,0,0,0,0,0,0,0,0,7,0,0,0
+644,Tuvalu,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+645,Tuvalu,Transformation,0,0,0,-73,0,0,0,24,0,-49,0,0,-73,-73
+646,Tuvalu,Electricity  CHP & Heat Plants,0,0,0,-73,0,0,0,24,0,-49,0,0,-73,-73
+647,Tuvalu,Electricity Plants,0,0,0,-73,0,0,0,24,0,-49,0,0,-73,-73
+648,Tuvalu,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+649,Tuvalu,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+650,Tuvalu,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+651,Tuvalu,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+652,Tuvalu,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+653,Tuvalu,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+654,Tuvalu,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+655,Tuvalu,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+656,Tuvalu,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+657,Tuvalu,Other transformation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+658,Tuvalu,Energy industries own use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+659,Tuvalu,Losses,0,0,0,0,0,0,0,-4,0,-4,0,0,0,0
+660,Tuvalu,Final consumption,0,0,0,49,0,0,0,27,0,76,0,0,49,49
+661,Tuvalu,Final Energy Consumption,0,0,0,49,0,0,0,27,0,76,0,0,49,49
+662,Tuvalu,Manufacturing  const. and mining,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+663,Tuvalu,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+664,Tuvalu,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+665,Tuvalu,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+666,Tuvalu,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+667,Tuvalu,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+668,Tuvalu,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+669,Tuvalu,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+670,Tuvalu,Food and tobacco,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+671,Tuvalu,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+672,Tuvalu,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+673,Tuvalu,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+674,Tuvalu,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+675,Tuvalu,Industry n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+676,Tuvalu,Transport,0,0,0,38,0,0,0,0,0,38,0,0,38,38
+677,Tuvalu,Road,0,0,0,25,0,0,0,0,0,25,0,0,25,25
+678,Tuvalu,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+679,Tuvalu,Domestic aviation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+680,Tuvalu,Domestic navigation,0,0,0,13,0,0,0,0,0,13,0,0,13,13
+681,Tuvalu,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+682,Tuvalu,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+683,Tuvalu,Other Consumption,0,0,0,11,0,0,0,27,0,38,0,0,11,11
+684,Tuvalu,Agriculture  forestry and fishing,0,0,0,4,0,0,0,0,0,4,0,0,4,4
+685,Tuvalu,Commerce and public services,0,0,0,0,0,0,0,15,0,15,0,0,0,0
+686,Tuvalu,Households,0,0,0,8,0,0,0,12,0,19,0,0,8,8
+687,Tuvalu,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+688,Tuvalu,Non-energy use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+689,PNG,Primary production,0,0,43214,0,105639,72141,0,3347,16000,240341,91488,0,43214,236994
+690,PNG,Imports,0,0,58732,59360,0,0,0,0,0,118092,0,0,118092,118092
+691,PNG,Exports,0,0,-43214,-17299,-90762,0,0,0,0,-151275,0,0,-60513,-151275
+692,PNG,International marine bunkers,0,0,0,-308,0,0,0,0,0,-308,0,0,-308,-308
+693,PNG,International aviation bunkers,0,0,0,-2602,0,0,0,0,0,-2602,0,0,-2602,-2602
+694,PNG,Stock changes,0,0,-2198,-528,0,0,0,0,0,-2726,0,0,-2726,-2726
+695,PNG,Total energy supply,0,0,56534,38624,14877,72141,0,3347,16000,201523,91488,0,95158,198176
+696,PNG,Statistical differences,0,0,572,359,0,0,0,0,0,930,4947,0,931,931
+697,PNG,Transfers and recycled products,0,0,0,88,0,0,0,0,0,88,0,0,88,88
+698,PNG,Transformation,0,0,-55963,17628,-6331,-352,0,14140,-16000,-46877,-14752,0,-38335,-61018
+699,PNG,Electricity  CHP & Heat Plants,0,0,0,-35565,-6331,-88,0,14140,-16000,-43843,-14488,0,-35565,-57984
+700,PNG,Electricity Plants,0,0,0,-35565,-6331,-88,0,14140,-16000,-43843,-14488,0,-35565,-57984
+701,PNG,CHP plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+702,PNG,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+703,PNG,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+704,PNG,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+705,PNG,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+706,PNG,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+707,PNG,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+708,PNG,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+709,PNG,Oil refineries,0,0,-55963,53193,0,0,0,0,0,-2770,0,0,-2770,-2770
+710,PNG,Other transformation,0,0,0,0,0,-264,0,0,0,-264,-264,0,0,-264
+711,PNG,Energy industries own use,0,0,0,0,-8546,0,0,-210,0,-8757,0,0,0,-8546
+712,PNG,Losses,0,0,0,0,0,0,0,-1099,0,-1099,0,0,0,0
+713,PNG,Final consumption,0,0,0,55981,0,71789,0,16178,0,143948,71789,0,55981,127770
+714,PNG,Final Energy Consumption,0,0,0,55981,0,71789,0,16178,0,143948,71789,0,55981,127770
+715,PNG,Manufacturing  const. and mining,0,0,0,25058,0,2989,0,11870,0,39917,2989,0,25058,28047
+716,PNG,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+717,PNG,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+718,PNG,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+719,PNG,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+720,PNG,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+721,PNG,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+722,PNG,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+723,PNG,Food and tobacco,0,0,0,0,0,897,0,0,0,897,897,0,0,897
+724,PNG,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+725,PNG,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+726,PNG,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+727,PNG,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+728,PNG,Industry n.e.s,0,0,0,25058,0,2093,0,11870,0,39020,2093,0,25058,27151
+729,PNG,Transport,0,0,0,23911,0,0,0,0,0,23911,0,0,23911,23911
+730,PNG,Road,0,0,0,20618,0,0,0,0,0,20618,0,0,20618,20618
+731,PNG,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+732,PNG,Domestic aviation,0,0,0,3293,0,0,0,0,0,3293,0,0,3293,3293
+733,PNG,Domestic navigation,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+734,PNG,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+735,PNG,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+736,PNG,Other Consumption,0,0,0,7013,0,68800,0,4308,0,80121,68800,0,7013,75813
+737,PNG,Agriculture  forestry and fishing,0,0,0,4484,0,0,0,258,0,4743,0,0,4484,4484
+738,PNG,Commerce and public services,0,0,0,1023,0,10331,0,388,0,11741,10331,0,1023,11354
+739,PNG,Households,0,0,0,1506,0,58469,0,3662,0,63637,58469,0,1506,59975
+740,PNG,Other consumption n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+741,PNG,Non-energy use,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+742,Fiji,Primary production,0,0,0,0,0,4593,0,2071,0,6664,6664,0,0,4593
+743,Fiji,Imports,0,0,0,38412,0,1,0,0,0,38412,1,0,38412,38413
+744,Fiji,Exports,0,0,0,-14587,0,0,0,0,0,-14587,0,0,-14587,-14587
+745,Fiji,International marine bunkers,0,0,0,-2567,0,0,0,0,0,-2567,0,0,-2567,-2567
+746,Fiji,International aviation bunkers,0,0,0,-1345,0,0,0,0,0,-1345,0,0,-1345,-1345
+747,Fiji,Stock changes,0,0,0,-441,0,0,0,0,0,-441,0,0,-441,-441
+748,Fiji,Total energy supply,0,0,0,19471,0,4594,0,2071,0,26136,6665,0,19471,24065
+749,Fiji,Statistical differences,0,0,0,-43,0,-1,0,1,0,-43,2071,0,-43,-44
+750,Fiji,Transfers and recycled products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+751,Fiji,Transformation,0,0,0,-4157,0,-506,0,1794,0,-2869,-506,0,-4157,-4663
+752,Fiji,Electricity  CHP & Heat Plants,0,0,0,-4157,0,-443,0,1794,0,-2806,-443,0,-4157,-4600
+753,Fiji,Electricity Plants,0,0,0,-4157,0,-18,0,1794,0,-2381,-18,0,-4157,-4175
+754,Fiji,CHP plants,0,0,0,0,0,-425,0,0,0,-425,-425,0,0,-425
+755,Fiji,Heat plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+756,Fiji,Coke ovens,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+757,Fiji,Briquetting plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+758,Fiji,Liquefaction plants,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+759,Fiji,Gas works,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+760,Fiji,Blast furnaces,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+761,Fiji,NGL & gas blending,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+762,Fiji,Oil refineries,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+763,Fiji,Other transformation,0,0,0,0,0,-63,0,0,0,-63,-63,0,0,-63
+764,Fiji,Energy industries own use,0,0,0,0,0,0,0,-45,0,-45,0,0,0,0
+765,Fiji,Losses,0,0,0,0,0,0,0,-400,0,-400,0,0,0,0
+766,Fiji,Final consumption,0,0,0,15357,0,4088,0,3420,0,22865,4088,0,15357,19445
+767,Fiji,Final Energy Consumption,0,0,0,15076,0,4088,0,3420,0,22584,4088,0,15076,19164
+768,Fiji,Manufacturing  const. and mining,0,0,0,3368,0,3830,0,817,0,8016,3830,0,3368,7198
+769,Fiji,Iron and steel,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+770,Fiji,Chemical and petrochemical,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+771,Fiji,Non-ferrous metals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+772,Fiji,Non-metallic minerals,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+773,Fiji,Transport equipment,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+774,Fiji,Machinery,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+775,Fiji,Mining and quarrying,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+776,Fiji,Food and tobacco,0,0,0,0,0,3830,0,0,0,3830,3830,0,0,3830
+777,Fiji,Paper  pulp and printing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+778,Fiji,Wood and wood products,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+779,Fiji,Textile and leather,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+780,Fiji,Construction,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+781,Fiji,Industry n.e.s,0,0,0,3368,0,0,0,817,0,4186,0,0,3368,3368
+782,Fiji,Transport,0,0,0,10176,0,0,0,0,0,10176,0,0,10176,10176
+783,Fiji,Road,0,0,0,8063,0,0,0,0,0,8063,0,0,8063,8063
+784,Fiji,Rail,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+785,Fiji,Domestic aviation,0,0,0,551,0,0,0,0,0,551,0,0,551,551
+786,Fiji,Domestic navigation,0,0,0,1562,0,0,0,0,0,1562,0,0,1562,1562
+787,Fiji,Pipeline transport,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+788,Fiji,Transport n.e.s,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+789,Fiji,Other Consumption,0,0,0,1531,0,258,0,2603,0,4392,258,0,1531,1789
+790,Fiji,Agriculture  forestry and fishing,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+791,Fiji,Commerce and public services,0,0,0,95,0,0,0,1537,0,1632,0,0,95,95
+792,Fiji,Households,0,0,0,1295,0,258,0,961,0,2513,258,0,1295,1553
+793,Fiji,Other consumption n.e.s,0,0,0,142,0,0,0,104,0,246,0,0,142,142
+794,Fiji,Non-energy use,0,0,0,281,0,0,0,0,0,281,0,0,281,281
diff --git a/Data/RE potential_Prepared by Shayan Naderi.xlsx b/Data/RE potential_Prepared by Shayan Naderi.xlsx
index 163d544..ee395c2 100644
Binary files a/Data/RE potential_Prepared by Shayan Naderi.xlsx and b/Data/RE potential_Prepared by Shayan Naderi.xlsx differ
diff --git a/Decarbonization.py b/Decarbonization.py
index fe13046..4531743 100644
--- a/Decarbonization.py
+++ b/Decarbonization.py
@@ -312,11 +312,8 @@ def generate_card_deck_2():
                                              ),
                                          ]
                                      ),
-                                     generate_select('ComBattery-MWh', "Battery size (MWh):", 0, 50, 0.5, 3),
-                                     generate_select('ComBattery-cost', "Cost(M$/MWh):", 0, 10, 0.05, 1.3),
-                                     generate_select('ComBattery-installationYear', "Installation year:", 2022, 2050, 1,
-                                                     2024),
-
+                                     generate_select('ComBattery-MWh', "Battery size (MWh):", 0, 10000, 0.5, 3),
+                                     generate_select('ComBattery-cost', "Cost(M$/MWh):", 0, 10, 0.05, 2),
                                      html.Div(
                                 [
                                     dbc.Label("Geothermal parameters"),
@@ -324,7 +321,7 @@ def generate_card_deck_2():
                                         options=[
                                             {"label": "Geothermal", "value": 1},
                                         ],
-                                        value=[1],
+                                        value=[0],
                                         id="switches-geothermal",
                                         switch=True,
                                     ),
diff --git a/EnergyFlows.py b/EnergyFlows.py
index d1cdf7f..b59e657 100644
--- a/EnergyFlows.py
+++ b/EnergyFlows.py
@@ -26,7 +26,7 @@ def generate_select_country_drpdwn():
                 options=[
                     {"label": i, "value": i} for i in Country_List
                 ],
-                value='Solomon Islands',
+                value='New Caledonia',
                 style={'width': "15%", 'margin-left': "15px"}
 
             ),
@@ -64,19 +64,26 @@ def select_sankey_flows():
                     {"label": i, "value": i} for i in from_
                 ],
                 value=from_[0],
-                style={'width': "25%", 'margin-left': "15px"}
+                style={'width': "20%", 'margin-left': "15px"}
             ),
             dbc.Label("to",style={'margin-left': "15px"}
 ),
             dbc.Select(
                 id="select-to",
-                # options=[
-                #     {"label": i, "value": i}
-                #     for i in to
-                # ],
-                # value=to[1],
-                style={'width': "25%", 'margin-left': "15px"}
+                style={'width': "20%", 'margin-left': "15px"}
             ),
+            html.Div([
+            dbc.RadioItems(
+                    id="radio-normalization-sankey",
+                    options=[
+                        {"label": "Real values", "value": 1},
+                        {"label": "Normalize with destination", "value": ' (to)'},
+                        {"label": "Normalize with origin", "value": ' (from)'},
+                    ],
+                value=1,
+                inline=True,
+                style={"fontSize":14}
+                )]),
             dbc.Button("Add Figure", color="danger", id='update-button-cross-country-figure', n_clicks=0, className="me-1"),
             dbc.Button("Clear Canvas", color="primary", id='update-button-sankey-clear-canvas', n_clicks=0,
                        className="me-1"),
@@ -147,7 +154,6 @@ def generate_navbar(app):
 
                 ),
             ),
-
             MAPNAlogo,
         ],
         color="dark",
@@ -210,7 +216,6 @@ def generate_navbar(app):
                              style={'margin-top': '15px', 'margin-left': '20px','margin-right': '20px'}),
 
                     html.Br(),
-                    # html.Div(dcc.Graph(id="Sankey_elec_figure"),style=figure_border_style)
 
                 ],
                 type="default",
@@ -220,19 +225,9 @@ def generate_navbar(app):
     ),
 ]
 
-
-# buttons = html.Div(
-#     [
-#         dbc.Button("Clear Canvas", color="info", id='clear-canvas-button', n_clicks=0, className="mr-1"),
-#         dbc.Button("Update", id='add-chart', color="danger", n_clicks=0, className="mr-1"),
-#         # dbc.Button("Export Plots",id='export-plot-button', color="success", n_clicks=0, className="mr-1"),
-#     ]
-# )
-
 style = {'border': 'solid', 'padding-top': '10px', 'align': 'center', 'justify': 'center', 'padding-left': '1px',
          'padding-right': '1px', }#'margin': "2px"
 
-
 BODY = dbc.Container(
     [
         dbc.Row([dbc.Col(dbc.Card(Sankey)),], style={"marginTop": 30}),
diff --git a/Summary.py b/Summary.py
index bfff770..cbeb0ed 100644
--- a/Summary.py
+++ b/Summary.py
@@ -83,16 +83,54 @@
                     ]),
                     html.Br(),
                     dbc.Row([
-                        dbc.Col(html.Div(dcc.Graph(id="transit_figure1",figure=figures.UNstats_plots(2019)[0]),style=figure_border_style),md=6),
-                        dbc.Col(html.Div(dcc.Graph(id="transit_figure2",figure=figures.UNstats_plots(2019)[1]), style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="final-demand", figure=figures.UNstats_plots(2019)[4]),
+                                         style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="transit_figure1", figure=figures.UNstats_plots(2019)[7]),
+                                         style=figure_border_style), md=6),
+                    ]),
+                    html.Br(),
+                    dbc.Row([
+                        dbc.Col(html.Div(dcc.Graph(id="Oil-imports", figure=figures.UNstats_plots(2019)[3]),
+                                         style=figure_border_style), md=6),
+
+                        dbc.Col(html.Div(dcc.Graph(id="transit_figure4", figure=figures.imports_to_GDP(2019)[0]),
+                                         style=figure_border_style), md=6),
+                    ]),
+                    html.Br(),
+                    dbc.Row([
+                        dbc.Col(html.Div(dcc.Graph(id="import-per-capita", figure=figures.imports_to_GDP(2019)[1]),
+                                         style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="renewables-per-capita", figure=figures.UNstats_plots(2019)[8]),
+                                         style=figure_border_style), md=6),
+                    ]),
+                    dbc.Row([
+                        dbc.Col(html.Div(dcc.Graph(id="transit_figure3", figure=figures.UNstats_plots(2019)[2]),
+                                         style=figure_border_style), md=6),
 
+                        dbc.Col(html.Div(dcc.Graph(id="transit_figure2", figure=figures.UNstats_plots(2019)[1]),
+                                         style=figure_border_style), md=6),
+                    ]),
+                    html.Br(),
+                    dbc.Row([
+                        dbc.Col(html.Div(dcc.Graph(id="final-demand", figure=figures.UNstats_plots(2019)[0]),
+                                         style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="total renewables", figure=figures.UNstats_plots(2019)[5]),
+                                         style=figure_border_style), md=6),
+                        # dbc.Col(html.Div(dcc.Graph(id="renewable electricity", figure=figures.UNstats_plots(2019)[6]),
+                        #                  style=figure_border_style), md=6),
                     ]),
                     html.Br(),
                     dbc.Row([
-                        dbc.Col(html.Div(dcc.Graph(id="transit_figure3",figure=figures.UNstats_plots(2019)[2]), style=figure_border_style), md=6),
-                        dbc.Col(html.Div(dcc.Graph(id="transit_figure4",figure=figures.imports_to_GDP(2019)), style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="final-vs-non-re-demand", figure=figures.land_use_plot()[4]),
+                                         style=figure_border_style), md=6),
+
+                        dbc.Col(html.Div(dcc.Graph(id="demand-per-capita", figure=figures.land_use_plot()[5]),
+                                         style=figure_border_style), md=6),
                     ]),
 
+                    html.Br(),
+
+
                 ],
                 type="default",
             )
diff --git a/WindSolar.py b/WindSolar.py
index ee695ed..b789d92 100644
--- a/WindSolar.py
+++ b/WindSolar.py
@@ -67,6 +67,31 @@ def generate_single_country_drpdwn():
                         dbc.Col(html.Div(dcc.Graph(id="Wind_physical_resource",figure=figures.Solar_physical_resources()[1]), style=figure_border_style), md=6),
                     ]),
                     html.Br(),
+
+                    dbc.Row([
+                        # dbc.Col(
+                        #     html.Div(dcc.Graph(id="PV_technical_GW", figure=figures.Solar_physical_resources()[6]),
+                        #              style=figure_border_style), md=6),
+
+                        dbc.Col(
+                            html.Div(dcc.Graph(id="PV_theoretical_GW", figure=figures.Solar_physical_resources()[3]),
+                                     style=figure_border_style), md=6),
+                        dbc.Col(html.Div(
+                            dcc.Graph(id="Wind_thechnical_MW", figure=figures.Solar_physical_resources()[5]),
+                            style=figure_border_style), md=6),
+                    ]),
+                    dbc.Row([
+                        dbc.Col(html.Div(
+                            dcc.Graph(id="PV_technical_GWh", figure=figures.Solar_physical_resources()[7]),
+                            style=figure_border_style), md=6),
+                        dbc.Col(html.Div(
+                            dcc.Graph(id="PV_technical_GWh", figure=figures.Solar_physical_resources()[4]),
+                            style=figure_border_style), md=6),
+
+                        dbc.Col(html.Div(
+                            dcc.Graph(id="Wind_thechnical_GWh", figure=figures.Solar_physical_resources()[2]),
+                            style=figure_border_style), md=6),
+                    ]),
                 ],
                 type="default",
             )
@@ -91,7 +116,6 @@ def generate_single_country_drpdwn():
                     dbc.Row([
                         dbc.Col(html.Div(dcc.Graph(id="wind_to_non_RE",figure=figures.land_use_plot()[0]), style=figure_border_style), md=6),
                         dbc.Col(html.Div(dcc.Graph(id="Wind_to_final",figure=figures.land_use_plot()[2]), style=figure_border_style), md=6),
-
                     ]),
                 ],
                 type="default",
@@ -118,7 +142,6 @@ def generate_single_country_drpdwn():
                         dbc.Col(html.Div(dcc.Graph(id="Wind_to_final",figure=figures.land_use_plot()[1]), style=figure_border_style), md=6),
                         dbc.Col(html.Div(dcc.Graph(id="land-use", figure=figures.land_use_plot()[3]),
                                          style=figure_border_style), md=6),
-
                     ]),
                 ],
                 type="default",
@@ -168,12 +191,14 @@ def generate_single_country_drpdwn():
                         style={"display": "none"},
                     ),
                     dbc.Row([
-                        dbc.Col(html.Div(dcc.Graph(id="Pop-and-famil-size",figure=figures.rooftop_PV_plot(0.75,2.5)[0]), style=figure_border_style), md=6),
-                        dbc.Col(html.Div(dcc.Graph(id="number-of-buildings-PV-pot",figure=figures.rooftop_PV_plot(0.75,2.5)[1]), style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="Pop-and-famil-size",figure=figures.rooftop_PV_plot(0.7,2.5)[0]), style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="number-of-buildings-rooftop",figure=figures.rooftop_PV_plot(0.7,2.5)[1]), style=figure_border_style), md=6),
                     ]),
                     html.Br(),
                     dbc.Row([
-                        dbc.Col(html.Div(dcc.Graph(id="Wind_to_final",figure=figures.rooftop_PV_plot(0.75,2.5)[2]), style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="rooftop-capacity", figure=figures.rooftop_PV_plot(0.7, 2.5)[3]),
+                                         style=figure_border_style), md=6),
+                        dbc.Col(html.Div(dcc.Graph(id="roofotp-generation",figure=figures.rooftop_PV_plot(0.7,2.5)[2]), style=figure_border_style), md=6),
                     ]),
                     html.Br(),
                 ],
diff --git a/callbacks.py b/callbacks.py
index f97a227..989b250 100644
--- a/callbacks.py
+++ b/callbacks.py
@@ -1,4 +1,6 @@
 from dash.dependencies import Input, Output, ALL, State, MATCH, ALLSMALLER
+
+import functions
 from app import app
 from dash import html
 import numpy as np
@@ -13,6 +15,7 @@
 import Geothermal
 Country_List = ['Samoa','Nauru','Vanuatu','Palau','Kiribati','Cook Islands','Solomon Islands','Tonga','New Caledonia','French Polynesia','Micronesia','Niue','Tuvalu','PNG','Fiji']
 
+
 @app.callback(
     Output('Visible-content', 'children'),
     Input("tabs", "active_tab")
@@ -43,30 +46,19 @@ def switch_tab(tab):
     [Input("select-year", "value")]
 )
 def update_options(year):
-    # figures.Update_UNstats_database(year)
+    # functions.Update_UNstats_database(year)
     # figures.validation()
     return figures.UNstats_plots(year)[0],figures.UNstats_plots(year)[1],figures.UNstats_plots(year)[2],\
-            figures.imports_to_GDP(year),\
+        figures.imports_to_GDP(year),\
            figures.generation_mix_plot()[0],figures.generation_mix_plot()[1]
 
 @app.callback(
     Output('PV-map', 'figure'),
-    Input("select-justcountry", "value")
+    [Input("select-justcountry", "value"),
+     Input("select-map-style", "value"),]
 )
-def update_options(Country):
-    return figures.mapboxplot(Country)
-
-
-
-
-
-
-
-
-
-
-
-
+def update_options(Country,style):
+    return figures.mapboxplot(Country,style)
 
 @app.callback(
     [Output('generation-cost', 'children'),
@@ -81,26 +73,24 @@ def update_options(Country):
      Output('scenarios-annaul-diesel', 'figure'),
      Output('emission-quantity', 'children'),
      Output('emission-cost', 'children'),
-     # Output('rooftop-MW', 'children'),
-     # Output('rooftop-GWh', 'children')
      ],
     Input('update-button','n_clicks'),
     [State("select-year", "value"),
      State("select-country", "value"),
-    State("diesel_price_slider", "value"),
+     State("diesel_price_slider", "value"),
      State("PV-cost", "value"),
      State("PV-battery-cost", "value"),
-    State("wind-battery-cost", "value"),
+     State("wind-battery-cost", "value"),
      State("wind-large-cost", "value"),
      State("demand-growth", "value"),
-    State('decarb-year', "value"),
+     State('decarb-year', "value"),
      State('rooftop-size', "value"),
-    State('emissions-rate', "value"),
+     State('emissions-rate', "value"),
      State('carbon-price', "value"),
      State('Wind_PV_share', "value"),
      State('small-PV-share', "value"),
      State('small-wind-share', "value"),
-    State('switches-geothermal', "value"),
+     State('switches-geothermal', "value"),
      State('geothermal-completion', "value"),
      State('geothermal-MW', "value"),
      State('geothermal-CF', "value"),
@@ -109,7 +99,6 @@ def update_options(Country):
      State('inflation-rate', "value"),
      State('ComBattery-MWh', "value"),
      State('ComBattery-cost', "value"),
-     State('ComBattery-installationYear', "value"),
      State('switches-communityBattery', "value"),
 
      ])
@@ -118,30 +107,22 @@ def sensor_checklist(n_clicks,year,country,diesel_price,PV_cost,PVBatt_cost,Wind
                      wind_share, small_PV_share,small_wind_share,
                      geothermal_switch,geothermal_completion_year,geothermal_MW,geothermal_CF,geothermal_CAPEX,
                      discount_rate,inflation_rate,
-                     CommBattery_size,CommBatery_cost,CommBattery_year,switch_battery):
+                     CommBattery_size,CommBatery_cost,switch_battery):
     if n_clicks:
         diesel_HHV = 3.74/1000000
         df = pd.read_csv("Data/Sankey/csv/{}/{}.csv".format(year,country))
 
-        oil_supplied_TJ = df[(df[' (from)'] == 'Oil: Supplied') & (df[' (to)'] == 'PowerStations')][' (weight)'] # Tj- Modifty the units
-        Natural_gas_supplied = df[(df[' (from)'] == 'Natural Gas: Supplied') & (df[' (to)'] == 'PowerStations')][' (weight)'] # Tj- Modifty the units
-        #Method1
-        # oil_supplied_litre = oil_supplied_TJ/diesel_HHV
-        # oil_supplied_cost = int(oil_supplied_litre * diesel_price/1000000)#$MM
+        # oil_supplied_TJ = df[(df[' (from)'] == 'Oil: Supplied') & (df[' (to)'] == 'PowerStations')][' (weight)'] # Tj- Modifty the units
+        # Natural_gas_supplied = df[(df[' (from)'] == 'Natural Gas: Supplied') & (df[' (to)'] == 'PowerStations')][' (weight)'] # Tj- Modifty the units
 
+        Total_generated_TJ = df[(df[' (from)'] == 'PowerStations') & (df[' (to)'] == 'Electricity & Heat: Supplied')][' (weight)'] #TJ
+        power_stations_input_TJ = df[df[' (to)'] == 'PowerStations'][' (weight)'].sum()
+        Efficiency = round(float(100*(Total_generated_TJ/power_stations_input_TJ)),1)
+        power_generated_GWh,final_demand_GWh = functions.fetch_single_country_demand(Country=country,Year=year,Unit='GWh')
 
-        power_generated_TJ = df[(df[' (from)'] == 'PowerStations') & (df[' (to)'] == 'Electricity & Heat: Supplied')][' (weight)'] #TJ
-        power_generated_GWh = float(power_generated_TJ * 0.2777)
         #Method 2
         oil_supplied_litre = power_generated_GWh * 1000000/2.5 # Litre refined oil for power generation
         oil_supplied_cost = oil_supplied_litre * diesel_price/1000000 #$MM
-
-
-        power_stations_input_TJ = df[df[' (to)'] == 'PowerStations'][' (weight)'].sum()
-        Efficiency = round(float(100*(power_generated_TJ/power_stations_input_TJ)),1)
-
-
-
         oil_import_TJ = df[df[' (from)'] == 'Oil Products: Imports'][' (weight)'].values[0] # Tj-
         oil_import_litre = oil_import_TJ/diesel_HHV
         oil_import_mlitre = oil_import_litre/1000000
@@ -149,14 +130,13 @@ def sensor_checklist(n_clicks,year,country,diesel_price,PV_cost,PVBatt_cost,Wind
         oil_export_TJ = df[(df[' (from)'] == 'Oil: Supplied') & (df[' (to)'] == 'Exports: Secondary')][' (weight)'] # Tj- Modifty the units
         oil_export_litre = oil_export_TJ/diesel_HHV
         oil_export_mlitre= oil_export_litre/1000000
+
         if len(oil_export_mlitre)>0:
             net_oil_product_import_ml = oil_import_mlitre - oil_export_mlitre
             net_oil_product_import_ml = net_oil_product_import_ml.values[0]
         else:
             net_oil_product_import_ml = oil_import_mlitre
 
-
-
         transformation_losses_cost = int(oil_supplied_cost * (1-Efficiency/100))
         #44 MJ/kg
         # 0.85 kg/l
@@ -167,22 +147,20 @@ def sensor_checklist(n_clicks,year,country,diesel_price,PV_cost,PVBatt_cost,Wind
         Wind_pot = df_p.loc[2, country] #GWh/MW/year
         PV_pot = df_p.loc[0, country] #GWh/MW/year
 
-
         #Emissions
         emissions_mtonne = power_generated_GWh * emission_tonneperMWh/1000
-
         emission_cost_mdollar = float(emission_dollarpertonne * emissions_mtonne)
         emissions_mtonne = round(emissions_mtonne, 3)
         emission_cost_mdollar = round(emission_cost_mdollar, 2)
         oil_supplied_cost = round(oil_supplied_cost,1)
         power_generated_GWh = round(power_generated_GWh,1)
-        fig_lists = figures.decarbonization_scenarios(Efficiency/100,net_oil_product_import_ml,power_generated_GWh, demand_growth, PV_cost, PVBatt_cost,
+        fig_lists = figures.decarbonization_scenarios(country,Efficiency/100,net_oil_product_import_ml,power_generated_GWh, demand_growth, PV_cost, PVBatt_cost,
                                                   WindBatt_cost, Wind_cost, decarb_year, wind_share, small_PV_share,
                                                   small_wind_share, PV_pot, Wind_pot, diesel_HHV, diesel_price,
                                                   geothermal_switch,geothermal_completion_year,geothermal_MW,geothermal_CF,geothermal_CAPEX,
                                                   discount_rate,inflation_rate,
                                                       emission_tonneperMWh,
-                                                      CommBattery_size,CommBatery_cost,CommBattery_year,switch_battery,
+                                                      CommBattery_size,CommBatery_cost,switch_battery,
                                                       emission_dollarpertonne)
 
 
@@ -206,3 +184,6 @@ def sensor_checklist(n_clicks,year,country,diesel_price,PV_cost,PVBatt_cost,Wind
 
 
 
+
+
+
diff --git a/callbacks_sankey.py b/callbacks_sankey.py
index a6958c6..24ab442 100644
--- a/callbacks_sankey.py
+++ b/callbacks_sankey.py
@@ -54,30 +54,47 @@ def update_options3(from_):
     Input('update-button-sankey-clear-canvas', 'n_clicks')],
     [State("select-from", "value"),
     State("select-to", "value"),
-     State('Hidden-Div_trend', "children"),
+    State("radio-normalization-sankey", "value"),
+    State('Hidden-Div_trend', "children"),
     State('dynamic_callback_container', 'children')
      ]
 )
-def update_cross_country_comparison(n_clicks,clear_canvas,from_,to_,hidden_div,div_children):
+def update_cross_country_comparison(n_clicks,clear_canvas,from_,to_,normalization,hidden_div,div_children):
     if n_clicks != hidden_div[0]:
         values = []
+        normalized_values = []
         df_cross_country = pd.DataFrame()
-        # to_ = to_['label']
-        # print('Final ',from_,to_)
-
         for country in Country_List:
-            df = pd.read_csv("Data/Sankey/csv/{}/{}.csv".format(2019, country))
-            df = df[(df[' (from)'] == from_)&(df[' (to)']==to_)].reset_index()
+            df1 = pd.read_csv("Data/Sankey/csv/{}/{}.csv".format(2019, country))
+            df = df1[(df1[' (from)'] == from_)&(df1[' (to)']==to_)].reset_index()
             a = df[' (weight)']
+            if normalization == ' (from)':
+                denominator_df = df1[df1[normalization]==from_]
+                denominator = denominator_df[' (weight)'].sum()
+            elif normalization == ' (to)':
+                denominator_df = df1[df1[normalization]==to_]
+                denominator = denominator_df[' (weight)'].sum()
+            elif normalization == 1:
+                denominator = 1
+
             if len(a) == 0:
                 a = 0
             else:
                 a=a[0]
+            if denominator == 0:
+               normalized_value = 0
+            elif denominator > 0:
+                normalized_value = 100*a/denominator
+            normalized_values.append(round(normalized_value,1))
             values.append(a)
 
         df_cross_country['Country'] = Country_List
+
         df_cross_country['Values'] = values
-        fig = figures.cross_country_sankey(df_cross_country,from_,to_)
+        if normalization != 1:
+            df_cross_country['Values'] = normalized_values
+
+        fig = figures.cross_country_sankey(df_cross_country,from_,to_,normalization)
         new_child = html.Div(
             style={'display': 'inline-block', 'outline': 'thin lightgrey solid', 'padding': 10},
             children=[
diff --git a/figures.py b/figures.py
index 0eba71d..4301eb4 100644
--- a/figures.py
+++ b/figures.py
@@ -2,8 +2,10 @@
 from plotly.subplots import make_subplots
 import plotly.graph_objects as go
 import plotly.express as px
+import functions
 from EnergyFlows import Country_List
-
+font_color = 'black'
+line_color = 'black'
 
 def imports_to_GDP(year):
     net_imp_list= []
@@ -16,8 +18,6 @@ def imports_to_GDP(year):
         df_exp['Trade Value'] = df_exp['Trade Value']/1000000 #to million $
 
         df_GDP = pd.read_csv('Data/Economic Indicators.csv')
-
-
         imp = df_imp[df_imp['HS4'].isin(interest_list)]['Trade Value']
         exp = df_exp[df_exp['HS4'].isin(interest_list)]['Trade Value']
 
@@ -28,16 +28,12 @@ def imports_to_GDP(year):
         net_imp_list.append(net_imp)
     df_GDP['Imp'] = net_imp_list
     df_GDP['net_imp_to_GDP'] = 100 * df_GDP['Imp']/df_GDP['GDP(million$)2019']
-    # df_GDP.to_csv('GDPPPPP.csv')
-
+    df_GDP['net_imp_to_GDP'] = df_GDP['net_imp_to_GDP'].round(1)
+    df_GDP['net_imp_per_capita'] = df_GDP['Imp']*1000000/df_GDP['Population'] #$ per capita
+    df_GDP['net_imp_per_capita'] = df_GDP['net_imp_per_capita'].round(0)
+    # df_GDP['net_imp_per_capita'] = df_GDP['net_imp_per_capita']
     fig = go.Figure()
-    fig.add_trace(go.Bar(x=df_GDP['Country'], y=df_GDP['net_imp_to_GDP'],name='dasdsa',marker_color='forestgreen'))
-    # fig.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['aviation_to_import'], name='Int. aviation bunkers',marker_color='lightsalmon'))
-
-    a = df_GDP['Country']
-    b = df_GDP['net_imp_to_GDP']
-
-
+    fig.add_trace(go.Bar(x=df_GDP['Country'], y=df_GDP['net_imp_to_GDP'],text=df_GDP['net_imp_to_GDP'],name='dasdsa',marker_color='forestgreen'))
     fig.update_layout(#width=1500,
         # height=500,
         barmode='relative')
@@ -48,38 +44,60 @@ def imports_to_GDP(year):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig.update_layout({
     'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="% of GDP",showline=True)
-    fig.update_xaxes(showline=True,
+    fig.update_yaxes(title_text="% of GDP",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
                      title_text="<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
 
     fig.update_layout(
-        title="% imported petroleum products in {} to the most recent reported GDP".format(year))
+        title="Ratio of net imported petroleum products to GDP")
     # print(summary_df)
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
-    return fig
-
 
 
+    fig2 = go.Figure()
+    fig2.add_trace(go.Bar(x=df_GDP['Country'], y=df_GDP['net_imp_per_capita'],text=df_GDP['net_imp_per_capita'],name='dasdsa',marker_color='forestgreen'))
+    fig2.update_layout(#width=1500,
+        # height=500,
+        barmode='relative')
+    fig2.update_layout(legend = dict(bgcolor = 'rgba(0,0,0,0)',    yanchor="bottom",orientation="h",
+        y=1.05,
+        xanchor="center",
+        x=0.5),
+                      font=dict(
+                          family="Calibri",
+                          size=16,
+                          color=font_color
+                      )
+                      )
+    fig2.update_layout({
+    'plot_bgcolor': 'rgba(0,0,0,0)',
+    'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig2.update_yaxes(title_text="$ per capita",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showline=True,linecolor=line_color,
+                     title_text="<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
 
+    fig2.update_layout(
+        title="Imported petroleum products per capita")
+    # print(summary_df)
+    fig2.update_traces(marker_line_color=font_color,
+                      marker_line_width=1.5, opacity=1)
 
+    return [fig,fig2]
 
 
 def import_export_figure(df_imp,df_exp,Interest_list,year):
-    # fig = make_subplots(rows=1, cols=1,shared_xaxes=True,shared_yaxes=False,subplot_titles=("2019       Imports {}  Exports {} ($MM)".format(-int(df_imp['Trade Value'].sum()),int(df_exp['Trade Value'].sum()))
-    #                                                                                         ),vertical_spacing =0.05)
     totalImports = int(-df_imp['Trade Value'].sum())
     totalExports = int(df_exp['Trade Value'].sum())
-
-
     fig = go.Figure()
     fig.add_trace(go.Bar(x=df_imp[df_imp['HS4'].isin(Interest_list)]['HS4'], y=df_imp[df_imp['HS4'].isin(Interest_list)]['Trade Value'],name='Imports',marker_color='red'))
     fig.add_trace(go.Bar(x=df_exp[df_exp['HS4'].isin(Interest_list)]['HS4'], y=df_exp[df_exp['HS4'].isin(Interest_list)]['Trade Value'], name='Exports',marker_color='green'))
@@ -94,19 +112,20 @@ def import_export_figure(df_imp,df_exp,Interest_list,year):
                       font=dict(
                           family="Calibri",
                           size=18,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig.update_layout({
     'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="Value ($MM)",showline=True)
-    fig.update_xaxes(showline=True,title_text = "<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
+    fig.update_yaxes(title_text="Value ($MM)",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text = "<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
 
     fig.update_layout(
         title="{}, Total Imports = {}, Total Exports = {} ($million)".format(year,totalImports,totalExports))
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
     return fig
 
@@ -124,8 +143,6 @@ def Generate_Sankey(year,country):
                      |(df[' (to)']=='Other Electricity & Heat')
                      |(df[' (to)']=='Other Electricity & Heat3')|(df[' (to)']=='Electricity & Heat: Supplied')]
 
-
-
     color_dicts = {'Primary Oil: Production': 'grey', 'Primary Oil: Imports': 'grey', 'Oil Products: Imports': 'grey',
                    'Natural Gas: Primary Production': 'blue', 'Electricity: Primary Production': 'red',
                    'Heat: Primary Production': 'red', 'BioFuels: Primary Production': 'green', 'Primary Oil': 'grey',
@@ -178,11 +195,6 @@ def Generate_Sankey(year,country):
         df_elec.loc[df_elec['From'] == i, ' (color)'] = color_dicts[i]
 
 
-
-
-
-
-
     fig = go.Figure(data=[go.Sankey(
         valuesuffix="TJ",
         node=dict(
@@ -220,24 +232,24 @@ def Generate_Sankey(year,country):
 
 
     fig.update_layout(title_text="Sankey Plot for all sectors <br><a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>",
-                      font_size=16)
+                      )
     fig.update_layout(height=900,font=dict(
                           family="Calibri",
-                          size=16,
-                          color="white"
+                          size=22,
+                          color=font_color
                       ))
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'},)
 
-    fig2.update_layout(height=350,font=dict(
+    fig2.update_layout(height=400,font=dict(
                           family="Calibri",
-                          size=16,
-                          color="white"
+                          size=22,
+                          color=font_color
                       ))
     fig2.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'},)
     fig2.update_layout(title_text="Sankey Plot for the electricity sector <br><a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>",
-                       font_size=16)
+                       )
 
     return [fig,fig2]
 
@@ -258,8 +270,8 @@ def oil_to_RE(PV,PV_batt,wind,wind_bat,max_range,year):
     fig = go.Figure(data=data)
     fig.update_layout(
         title="Potential RE installation with the money paid for diesel transformation in {}".format(year))
-    fig.update_yaxes(title_text="MW",showline=True)
-    fig.update_xaxes(showline=True)
+    fig.update_yaxes(title_text="MW",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color)
 
     fig.update_layout(yaxis_range=[0, max_range])
 
@@ -269,9 +281,9 @@ def oil_to_RE(PV,PV_batt,wind,wind_bat,max_range,year):
     fig.update_layout(height=350,font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       ))
-    fig.update_traces(marker_color='lightsalmon', marker_line_color='white',
+    fig.update_traces(marker_color='lightsalmon', marker_line_color=font_color,
                       marker_line_width=2.5, opacity=1)
 
 
@@ -298,33 +310,28 @@ def annual_demand(demand,growth_rate,decarb_rate):
     fig = go.Figure(data=data)
     fig.update_layout(
         title="Current and future non-RE electricity demand with {}% annual growth".format(growth_rate))
-
-    fig.update_yaxes(title_text="GWh")
-    # fig.update_layout(yaxis_range=[0, max_range])
-
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
                        'paper_bgcolor': 'rgba(0,0,0,0)'})
-
     fig.update_layout(#height=500,
                       font=dict(
         family="Calibri",
         size=16,
-        color="white"
+        color=font_color
     ))
-    fig.update_traces(marker_color='lightsalmon', marker_line_color='white',
+    fig.update_traces(marker_color='lightsalmon', marker_line_color=font_color,
                       marker_line_width=2.5, opacity=1)
-    fig.update_xaxes(showgrid=False,showline=True)
-    fig.update_yaxes(showgrid=True,showline=True)
+    fig.update_xaxes(showgrid=False,showline=True,linecolor=line_color)
+    fig.update_yaxes(title_text="GWh",showgrid=True,showline=True,linecolor=line_color,gridcolor=line_color)
     return fig
 
 
-def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_cost,PVBatt_cost,WindBatt_cost,Wind_cost,decarb_year,
+def decarbonization_scenarios(Country,Efficiency,oil_imports_2019,demand,growth_rate,PV_cost,PVBatt_cost,WindBatt_cost,Wind_cost,decarb_year,
                               total_wind_share,small_PV_share,small_wind_share,
                               PV_pot,Wind_pot,diesel_HHV,diesel_price,
                               geothermal_switch,geothermal_completion_year,geothermal_MW,geothermal_CF,geothermal_CAPEX,
                               discount_rate,inflation_rate,
                               emission_tonneperMWh,
-                              CommBattery_size,CommBatery_cost,CommBattery_year,switch_battery,
+                              CommBattery_size,CommBatery_cost,switch_battery,
                               emission_dollarpertonne):
 
     if geothermal_switch != [1]:
@@ -333,7 +340,6 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
     if switch_battery != [1]:
         CommBatery_cost = 0
         CommBattery_size = 0
-
     geothermal_GWh = geothermal_MW * (geothermal_CF/100) * 8760/1000
 
     total_wind_share = total_wind_share/100
@@ -355,7 +361,6 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
         demand_list.append(demand)
         year += 1
         year_list.append(year)
-
     demand_list=demand_list[3:]
     year_list=year_list[3:]
     demand_df['Year']=year_list
@@ -365,10 +370,12 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
     demand_df['Geothermal_GWh'] = 0
     demand_df['Geothermal_inst_cost'] = 0
     demand_df['Battery_inst_cost'] = 0
+    years= decarb_year - 2022
 
-    demand_df['Battery_inst_cost'][demand_df['Year'] == CommBattery_year] = CommBatery_cost*CommBattery_size #Million Dollar
-
-
+    total_battery_cost =  CommBatery_cost * CommBattery_size
+    installment_comm_battery = total_battery_cost/(years+1)
+    # demand_df['Battery_inst_cost'][demand_df['Year'] == CommBattery_year] = CommBatery_cost*CommBattery_size #Million Dollar
+    demand_df['Battery_inst_cost'][demand_df['Year'] <= decarb_year] = installment_comm_battery #Million Dollar per year
 
     demand_df['RE_cumulative'][demand_df['Year']==decarb_year] = demand_df['Demand'][demand_df['Year']==decarb_year] #GWh
     demand_df['Geothermal_inst'][demand_df['Year'] == geothermal_completion_year] = geothermal_MW #MW
@@ -377,7 +384,6 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
         (geothermal_MW * geothermal_CAPEX*1000000)/(geothermal_completion_year-2022+1)#$Dollar
 
 
-    years= decarb_year - 2022
     if geothermal_completion_year <= decarb_year:
         step = (demand_df['Demand'][demand_df['Year'] == decarb_year]- geothermal_GWh) / (years+1) #GWh
 
@@ -396,48 +402,45 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
 
     demand_df['Annual_RE'] = demand_df['RE_cumulative'].shift(-1) - demand_df['RE_cumulative']
     demand_df['Annual_RE'] = demand_df['Annual_RE'].mask(demand_df['Annual_RE'] < 0, 0)
-    demand_df['PV_inst'] = (demand_df['Annual_RE'] * total_PV_share)/PV_pot #MW
+    demand_df['PV_inst'] = ((demand_df['Annual_RE'] * total_PV_share)/PV_pot) #MW
     demand_df['wind_inst'] = (demand_df['Annual_RE'] * total_wind_share)/Wind_pot #MW
 
-    demand_df['Small PV+B'] = demand_df['PV_inst'] * small_PV_share #MW
+    demand_df['Small PV+B'] = (demand_df['PV_inst'] * small_PV_share)/0.7 #MW #30% less performance for rooftop
     demand_df['Large PV'] = demand_df['PV_inst'] * large_PV_share #MW
     demand_df['Small Wind+B'] = demand_df['wind_inst'] * small_wind_share #MW
     demand_df['Large Wind'] = demand_df['wind_inst'] * large_wind_share #MW
 
-    demand_df['RE_inst_cost'] = (1000000 * demand_df['PV_inst'] * (small_PV_share*PVBatt_cost+large_PV_share*PV_cost) +\
+    demand_df['RE_inst_cost'] = (1000000 * demand_df['PV_inst'] * (small_PV_share*PVBatt_cost*1.5+large_PV_share*PV_cost) +\
                                 1000000 * demand_df['wind_inst'] * (small_wind_share*WindBatt_cost+large_wind_share*Wind_cost)+ \
                                 demand_df['Geothermal_inst_cost']+
                                  demand_df['Battery_inst_cost']*1000000)/1000000 #M$
-
-
-
     demand_df["non_RE_demand_TJ"] = (demand_df['Demand'] - demand_df['RE_cumulative']-demand_df['Geothermal_GWh'])/0.2777
     demand_df['non_RE_demand_TJ'][demand_df['non_RE_demand_TJ'] < 0] = 0
-
     demand_df["diesel_litre_dec"] = demand_df["non_RE_demand_TJ"] / (diesel_HHV*Efficiency) # L
     demand_df["diesel_cost_dec"] = demand_df["diesel_litre_dec"] * diesel_price / 1000000  # $MM
-
     demand_df["diesel_litre_bs"] = (demand_df["Demand"]/0.2777) / (diesel_HHV * Efficiency)
     demand_df["diesel_cost_bs"] = demand_df["diesel_litre_bs"] * diesel_price / 1000000  # $MM
 
-    demand_df['Diesel_cost_saving'] = demand_df["diesel_cost_bs"] - demand_df["diesel_cost_dec"] # $MM
+    if Country =="New Caledonia":
+        #coal price is 400 USD/Tonne
+        demand_df["diesel_cost_dec"] = demand_df["diesel_cost_dec"]/2
+        demand_df['Coal_dec_tonne'] = demand_df["non_RE_demand_TJ"] / 0.02931  # 0.02931TJ = 1 tonne of coal
+        demand_df['Coal_dec_tonne'] = demand_df['Coal_dec_tonne']/2
+        demand_df["coal_dec_mdollar"] = demand_df["Coal_dec_tonne"] * 400 /1000000
+        demand_df["diesel_cost_bs"] = demand_df["diesel_cost_bs"]/2
+        demand_df["coal_bs_tonne"] = (demand_df["Demand"]/0.2777)/0.02931  # 0.02931TJ = 1 tonne of coal
+        demand_df["coal_bs_tonne"]= demand_df["coal_bs_tonne"] / 2 #0.5 total demand is met by coal
+        demand_df["coal_bs_mdollar"] = demand_df["coal_bs_tonne"] * 400 /1000000
 
+        demand_df["diesel_cost_bs"] = demand_df["diesel_cost_bs"] + demand_df["coal_bs_mdollar"]
+        demand_df["diesel_cost_dec"] = demand_df["diesel_cost_dec"] + demand_df["coal_dec_mdollar"]
 
+    demand_df['Diesel_cost_saving'] = demand_df["diesel_cost_bs"] - demand_df["diesel_cost_dec"] # $MM
     demand_df['Net_saving'] = demand_df['Diesel_cost_saving'] - demand_df['RE_inst_cost']  # $MM
-
-
-
-
-
-
-
-
-
     diesel_emission_intensity = emission_tonneperMWh * 1000 # t CO2-e/GWh
     demand_df['Emission_bs_ton'] = demand_df['Demand'] * diesel_emission_intensity
     demand_df['Emission_dec_ton'] = (demand_df['Demand'] - demand_df['RE_cumulative'] -demand_df['Geothermal_GWh']) * diesel_emission_intensity
     demand_df['Emission_dec_ton'][demand_df['Emission_dec_ton'] < 0] = 0
-
     demand_df['Emission_red'] = demand_df['Emission_bs_ton'] - demand_df['Emission_dec_ton']
     demand_df['Emission_red_cum'] = demand_df['Emission_red'].cumsum()
     # add carbon price
@@ -450,35 +453,25 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
     discount_rate = discount_rate/100
 
     for i, row in demand_df.iterrows():
-        # if (i>0) :
         demand_df.at[i,'Net_saving_discounted'] = demand_df.at[i,'Net_saving'] * ((1+inflation_rate)/(1+discount_rate))**i
         demand_df.at[i,'Emission_red_saving_discounted'] = demand_df.at[i,'Emission_red_saving'] * ((1+inflation_rate)/(1+discount_rate))**i
-
-
     demand_df['Net_saving_cumsum'] = demand_df['Net_saving_discounted'].cumsum()
     demand_df['Net_saving_emission_cumsum'] = demand_df['Emission_red_saving_discounted'].cumsum()
 
-
-
-    # fig = make_subplots(specs=[[{"secondary_y": False}]])
     fig=go.Figure()
     fig.add_trace(
         go.Bar(x=demand_df['Year'], y=demand_df['Net_saving_discounted'], name="Annual net saving",marker_color='forestgreen'),
     )
-    fig.add_trace(
-        go.Bar(x=demand_df['Year'], y=demand_df['Emission_red_saving_discounted'], name="Annual savings from emissions",marker_color='lightsalmon'),
-    )
-
-
-
-    fig.update_yaxes(title_text="Annual Saving ($m)",  showline=True, showgrid=False)
-
-    fig.update_xaxes(showgrid=False, showline=True)
+    # fig.add_trace(
+    #     go.Bar(x=demand_df['Year'], y=demand_df['Emission_red_saving_discounted'], name="Annual savings from emissions",marker_color='lightsalmon'),
+    # )
 
+    fig.update_yaxes(title_text="Annual Saving ($m)",  showline=True, showgrid=False,linecolor=line_color,gridcolor=line_color,rangemode='tozero')
+    fig.update_xaxes(showgrid=False, showline=True,linecolor=line_color)
     fig.update_layout(height=350, font=dict(
         family="Calibri",
         size=16,
-        color="white"
+        color=font_color
     ))
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
                        'paper_bgcolor': 'rgba(0,0,0,0)'},
@@ -489,11 +482,8 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                                   ),
                       hovermode="x"
                       )
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
-
-    # fig.update_layout(yaxis_range=[0, max_range])
-
     fig.update_layout(
         title="Annual savings by achieving 100% RE in {}".format(decarb_year))
     fig.update_layout(barmode='relative')
@@ -501,26 +491,23 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
 ############################################################################################
     ########################################################################################
 
-
-
-    # fig2 = make_subplots(specs=[[{"secondary_y": False}]])
     fig2 = go.Figure()
     fig2.add_trace(
         go.Bar(x=year_list, y=demand_df['Net_saving_cumsum'], name="Cumulative net saving"
                ,marker_color='forestgreen'),
     )
-    fig2.add_trace(
-        go.Bar(x=year_list, y=demand_df['Net_saving_emission_cumsum'], name="Cumulative saving from emissions",
-               marker_color='lightsalmon'),
-    )
+    # fig2.add_trace(
+    #     go.Bar(x=year_list, y=demand_df['Net_saving_emission_cumsum'], name="Cumulative saving from emissions",
+    #            marker_color='lightsalmon'),
+    # )
 
-    fig2.update_yaxes(title_text="Cumulative Saving ($m)", showline=True, showgrid=False)
-    fig2.update_xaxes(showgrid=False, showline=True)
+    fig2.update_yaxes(title_text="Cumulative Saving ($m)", showline=True, showgrid=False,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showgrid=False, showline=True,linecolor=line_color)
 
     fig2.update_layout(height=350, font=dict(
         family="Calibri",
         size=16,
-        color="white"
+        color=font_color
     ))
     fig2.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
                        'paper_bgcolor': 'rgba(0,0,0,0)'},
@@ -531,7 +518,7 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                                   ),
                        hovermode="x"
                        )
-    fig2.update_traces(marker_line_color='white',
+    fig2.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
     # fig.update_layout(yaxis_range=[0, max_range])
@@ -549,10 +536,7 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                           marker_color='greenyellow'))
     fig3.add_trace(go.Bar(x=demand_df['Year'], y=demand_df['Large Wind'], name='Large Wind',
                           marker_color='orangered'))
-    # fig3.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['Pipeline transport'], name='Pipeline transport',
-    #                       marker_color='mediumvioletred'))
-    # fig3.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['transport n.e.s'], name='Transport n.e.s',
-    #                       marker_color='darkturquoise'))
+
 
     fig3.update_layout(  # width=1500,
         # height=500,
@@ -564,19 +548,19 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        )
                        )
     fig3.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig3.update_yaxes(title_text="Installed Capacity (MW)", showline=True)
-    fig3.update_xaxes(showline=True)
+    fig3.update_yaxes(title_text="Installed Capacity (MW)", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig3.update_xaxes(showline=True,linecolor=line_color)
 
     fig3.update_layout(
         title="Breakdown of annual RE installation for 100% RE in {}".format(decarb_year))
-    fig3.update_traces(marker_line_color='white',
+    fig3.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
 
 
@@ -597,22 +581,22 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        )
                        )
     fig4.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig4.update_yaxes(title_text="Annual (t CO2-e)", showline=True)
-    fig4.update_yaxes(title_text="Cumulative (t CO2-e)", secondary_y=True, showline=True, showgrid=False)
+    fig4.update_yaxes(title_text="Annual (t CO2-e)", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig4.update_yaxes(title_text="Cumulative (t CO2-e)", secondary_y=True, showline=True, showgrid=False,linecolor=line_color,gridcolor=line_color)
 
-    fig4.update_xaxes(showline=True)
+    fig4.update_xaxes(showline=True,linecolor=line_color)
 
     fig4.update_layout(
         title="Annaul CO2-e emission reduction by achieving 100% RE in {}".format(decarb_year))
     # print(summary_df)
-    fig4.update_traces(marker_line_color='white',
+    fig4.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
 
 
@@ -625,10 +609,6 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                           marker_color='lightsalmon',),secondary_y=True)
     fig5.add_trace(go.Scatter(x=demand_df['Year'], y=[oil_imports_2019]*len(demand_df['Year']), name='Net oil products import in 2019',
                           marker_color='red'),secondary_y=False)
-    # fig5.add_hline(y=oil_imports_2019, line_dash="dot",line=dict(color='Red',),
-    #               annotation_text="2019 oil product imports",
-    #               annotation_position="bottom left")
-    # [z0] * len(seconds)
 
     fig5.update_layout(  # width=1500,
         # height=500,
@@ -640,23 +620,21 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        )
                        )
     fig5.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig5.update_yaxes(title_text="Annual (million Litre)", showline=True)
-    fig5.update_yaxes(title_text="Cumulative (million Litre)", secondary_y=True, showline=True, showgrid=False)
-    fig5.update_yaxes(title_text="Cumulative (million Litre)", secondary_y=True, showline=True, showgrid=False)
-
-    fig5.update_xaxes(showline=True)
+    fig5.update_yaxes(title_text="Annual (million Litre)", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig5.update_yaxes(title_text="Cumulative (million Litre)", secondary_y=True, showline=True, showgrid=False,linecolor=line_color,gridcolor=line_color)
+    fig5.update_xaxes(showline=True,linecolor=line_color)
 
     fig5.update_layout(
         title="Diesel import reduction by achieving 100% RE in {}".format(decarb_year))
     # print(summary_df)
-    fig5.update_traces(marker_line_color='white',
+    fig5.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
 
     return [fig,fig2,fig3,fig4,fig5]
@@ -664,37 +642,38 @@ def decarbonization_scenarios(Efficiency,oil_imports_2019,demand,growth_rate,PV_
 
 def rooftop_PV_plot(available_buildings,PV_size):
     import pandas as pd
+    rooftop_df = pd.DataFrame()
     df = pd.read_csv('Data/Rooftop Potential.csv')
     Countries = df['Country']
     Population = df['Population']
     Household_size = df['Household size']
     solar_radiation = df['Potential of Av.PV gen (GWh/MW/year)']
-
     number_of_homes = available_buildings*Population/Household_size # only those homes with rooftop PV potential
-
+    number_of_homes = number_of_homes.round(0)
     rooftop_capacity_MW = number_of_homes * PV_size/1000
-
+    rooftop_capacity_MW = rooftop_capacity_MW.round(1)
     rooftop_PV_generation_GWh = rooftop_capacity_MW * solar_radiation
+    rooftop_PV_generation_GWh = rooftop_PV_generation_GWh.astype(float)
+    rooftop_PV_generation_GWh = rooftop_PV_generation_GWh.round(decimals=1)
 
+    rooftop_df['Generation_GWh'] = rooftop_PV_generation_GWh
+    rooftop_df.to_csv('rooftop_Pv_potential.csv')
     fig = make_subplots(specs=[[{"secondary_y": True}]])
-
     fig.add_trace(
         go.Bar(x=Countries, y=Population, name="Population",marker_color='forestgreen'),
         secondary_y=False,
     )
-
     fig.add_trace(
-        go.Scatter(x=Countries, y=Household_size, name="Average household size",marker_color='red'),
-        secondary_y=True,
-    )
-    fig.update_yaxes(title_text="Population", secondary_y=False,showline=True,showgrid=True)
-    fig.update_yaxes(title_text="Average household size", secondary_y=True,showline=True, showgrid=True)
-    fig.update_xaxes(showgrid=False,showline=True)
-    fig.update_layout(#height=350,
+        go.Scatter(x=Countries, y=Household_size, name="Average household size",marker_color='red',mode='markers'),
+        secondary_y=True,)
+    fig.update_yaxes(title_text="Population", secondary_y=False,showline=True,showgrid=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_yaxes(title_text="Average household size", secondary_y=True,showline=True, showgrid=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showgrid=False,showline=True,linecolor=line_color)
+    fig.update_layout(
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       ),
         hovermode="x"
     )
@@ -705,33 +684,28 @@ def rooftop_PV_plot(available_buildings,PV_size):
                                   xanchor="center",
                                   x=0.5,
                       ))
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
-
     fig.update_layout(
         title="Population and average households size")
-    fig.update_xaxes(showline=True,title_text="<a href=\"http://purl.org/spc/digilib/doc/z8n4m\"><sub>Source: 2020 Pacific Populations, SPC<sub></a>")
-
-
-
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text="<a href=\"http://purl.org/spc/digilib/doc/z8n4m\"><sub>Source: 2020 Pacific Populations, SPC<sub></a>")
+    fig.update_layout(#width=1500,
+        # height=500,
+        barmode='group')
     fig2 = make_subplots(specs=[[{"secondary_y": True}]])
     fig2.add_trace(
-        go.Bar(x=Countries, y=number_of_homes, name="Number of homes available for rooftop PV",marker_color='forestgreen'),
+        go.Bar(x=Countries, y=number_of_homes,text=number_of_homes, name="Number of homes available for rooftop PV",marker_color='forestgreen'),
         secondary_y=False,
     )
-    fig2.add_trace(
-        go.Scatter(x=Countries, y=rooftop_capacity_MW, name="Potential rooftop PV generation",marker_color='red'),
-        secondary_y=True,
-    )
-    fig2.update_yaxes(title_text="Number of homes available for rooftop PV", secondary_y=False,showline=True,showgrid=True)
-    fig2.update_yaxes(title_text="Potential rooftop PV capacity (MW)", secondary_y=True,showline=True, showgrid=False,rangemode='tozero')
-    fig2.update_xaxes(showgrid=False,showline=True)
+    fig2.update_yaxes(title_text="Number of homes available for rooftop PV", secondary_y=False,showline=True,showgrid=True,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showgrid=False,showline=True,linecolor=line_color)
 
     fig2.update_layout(#height=350,
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       ),
         hovermode="x"
     )
@@ -742,25 +716,25 @@ def rooftop_PV_plot(available_buildings,PV_size):
                                   xanchor="center",
                                   x=0.5,
                       ))
-    fig2.update_traces(marker_line_color='white',
+    fig2.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
     fig2.update_layout(
-        title="Number of homes available for rooftop PV and potential rooftop PV capacity")
+        title="Number of homes available for rooftop PV ")
 
 
 
     fig3 = make_subplots(specs=[[{"secondary_y": False}]])
     fig3.add_trace(
-        go.Bar(x=Countries, y=rooftop_PV_generation_GWh, name="Potential rooftop PV generation (GWh)",marker_color='forestgreen'),
+        go.Bar(x=Countries, y=rooftop_PV_generation_GWh,text=rooftop_PV_generation_GWh, name="Potential rooftop PV generation (GWh)",marker_color='forestgreen'),
     )
-    fig3.update_yaxes(title_text="Rooftop PV generation (GWh/year)", showline=True, showgrid=True)
-    fig3.update_xaxes(showgrid=False,showline=True)
+    fig3.update_yaxes(title_text="Rooftop PV generation (GWh/year)", showline=True, showgrid=True,linecolor=line_color,gridcolor=line_color)
+    fig3.update_xaxes(showgrid=False,showline=True,linecolor=line_color)
 
     fig3.update_layout(#height=350,
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       ),
         hovermode="x"
     )
@@ -771,87 +745,50 @@ def rooftop_PV_plot(available_buildings,PV_size):
                                   xanchor="center",
                                   x=0.5,
                       ))
-    fig3.update_traces(marker_line_color='white',
+    fig3.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
     fig3.update_layout(
         title="Potential rooftop PV generation")
-    return [fig,fig2,fig3]
-
-
-def Update_UNstats_database(year):
-    Country_List = ['Samoa', 'Nauru', 'Vanuatu', 'Palau', 'Kiribati', 'Cook Islands', 'Solomon Islands', 'Tonga',
-                    'New Caledonia', 'French Polynesia', 'Micronesia', 'Niue', 'Tuvalu', 'PNG', 'Fiji']
-    all_countries_df = pd.DataFrame()
 
-    for country in Country_List:
-        df = pd.read_csv("Data/EnergyBalance/{}/{}.csv".format(year,country))
-        if country == Country_List[0]:
-            all_countries_df = df
-        elif country != Country_List[0]:
-            # pd.concat([all_countries_df,df],inplace=True)
-            # pass
-            all_countries_df = all_countries_df.append(df,ignore_index=True)
 
-    all_countries_df.replace({"---": 0}, inplace=True)
-    all_countries_df = all_countries_df.replace({'\*': ''},regex=True)
+    fig4 = make_subplots(specs=[[{"secondary_y": False}]])
+    fig4.add_trace(
+        go.Bar(x=Countries, y=rooftop_capacity_MW, text=rooftop_capacity_MW,name="Rooftop PV capacity",marker_color='forestgreen'),
+    )
 
-    c_list = all_countries_df.columns
-    for i in c_list[2:]:
-        all_countries_df[i] = all_countries_df[i].astype(float)
+    fig4.update_yaxes(title_text="Potential rooftop PV capacity (MW)", secondary_y=False,showline=True,showgrid=True,linecolor=line_color,gridcolor=line_color)
+    fig4.update_xaxes(showgrid=False,showline=True,linecolor=line_color)
 
-    all_countries_df['All Coal'] = all_countries_df['Primary Coal and Peat'] + all_countries_df['Coal and Peat Products']
+    fig4.update_layout(#height=350,
+                      font=dict(
+                          family="Calibri",
+                          size=16,
+                          color=font_color
+                      ),
+        hovermode="x"
+    )
+    fig4.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+                       'paper_bgcolor': 'rgba(0,0,0,0)'},
+                      legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                  y=1.05,
+                                  xanchor="center",
+                                  x=0.5,
+                      ))
+    fig4.update_traces(marker_line_color=font_color,
+                      marker_line_width=1.5, opacity=1)
+    fig4.update_layout(
+        title="Potential rooftop PV capacity")
 
-    all_countries_df['All Oil'] = all_countries_df['Primary Oil'] + all_countries_df['Oil Products']
+    return [fig,fig2,fig3,fig4]
 
 
-    all_countries_df['All Inputs'] = all_countries_df['All Coal'] + all_countries_df['All Oil'] + all_countries_df['Natural Gas'] +\
-                                     all_countries_df['Biofuels and Waste'] + all_countries_df['Nuclear'] +all_countries_df['Heat']
-    # all_countries_df.applymap(lambda x: 'Micronesia' if "Micronesia" in str(x) else x)
-    all_countries_df.replace('Micronesia (Federated States of)', 'Micronesia',inplace=True)
-    all_countries_df.replace('Papua New Guinea', 'PNG',inplace=True)
 
-    all_countries_df.to_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(year))
 
 def UNstats_plots(year):
-    summary_df = pd.DataFrame()
-    df = pd.read_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(year))
-    imports = df[df['Transactions(down)/Commodity(right)']=='Imports']['All Oil'].values
-    Int_marine = df[df['Transactions(down)/Commodity(right)']=='International marine bunkers']['All Oil'].values
-    Int_avi = df[df['Transactions(down)/Commodity(right)']=='International aviation bunkers']['All Oil'].values
-    transformation = -df[df['Transactions(down)/Commodity(right)']=='Transformation']['All Oil'].values
-    transformation_losses = - df[df['Transactions(down)/Commodity(right)']=='Transformation']['Total Energy'].values
-
-    summary_df['Country'] = df. iloc[:, 1].unique()
-    summary_df['Oil imports'] = imports
-    summary_df['Transformation'] = transformation
-    summary_df['transformation_losses'] = transformation_losses
-
-
-    summary_df['int marine'] = -Int_marine
-    summary_df['int aviation'] = -Int_avi
-    summary_df['marine_to_import'] = 100 * summary_df['int marine']/summary_df['Oil imports']
-    summary_df['aviation_to_import'] = 100 * summary_df['int aviation']/summary_df['Oil imports']
-    summary_df['transformation_to_import'] = 100 * summary_df['Transformation']/summary_df['Oil imports']
-    summary_df['transformation_losses_to_import'] = 100 * summary_df['transformation_losses']/summary_df['Oil imports']
-    summary_df['road'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Road']['All Oil'].values/summary_df['Oil imports']
-    summary_df['rail'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Rail']['All Oil'].values/summary_df['Oil imports']
-    summary_df['Domestic aviation'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Domestic aviation']['All Oil'].values/summary_df['Oil imports']
-    summary_df['Domestic navigation'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Domestic navigation']['All Oil'].values/summary_df['Oil imports']
-    summary_df['Pipeline transport'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Pipeline transport']['All Oil'].values/summary_df['Oil imports']
-    summary_df['transport n.e.s'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Transport n.e.s']['All Oil'].values/summary_df['Oil imports']
-
-
-
-
-
-
-
+    summary_df = functions.all_countries_cross_comparison_unstats(2019,Unit='TJ',Use="SummaryPlot")
     fig = go.Figure()
     fig.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['marine_to_import'],name='Int. marine bunkers',marker_color='forestgreen'))
     fig.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['aviation_to_import'], name='Int. aviation bunkers',marker_color='lightsalmon'))
-
-
-
     fig.update_layout(#width=1500,
         # height=500,
         barmode='relative')
@@ -862,7 +799,7 @@ def UNstats_plots(year):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       ),
                         hovermode = "x"
                       )
@@ -870,13 +807,14 @@ def UNstats_plots(year):
     'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="% of imported oil",showline=True)
-    fig.update_xaxes(showline=True,title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig.update_yaxes(title_text="% of imported oil",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
 
     fig.update_layout(
         title="% of imported oil consumed for international transit in {}".format(year))
     # print(summary_df)
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
     fig2 = go.Figure()
@@ -884,10 +822,6 @@ def UNstats_plots(year):
                          marker_color='forestgreen'))
     fig2.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['transformation_losses_to_import'], name='Transformation losses',
                          marker_color='lightsalmon'))
-
-    # fig2.update_layout(  # width=1500,
-    #     # height=500,
-    # )barmode='relative')
     fig2.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
                                   y=1.05,
                                   xanchor="center",
@@ -895,21 +829,22 @@ def UNstats_plots(year):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
-                      )
-                      )
+                          color=font_color
+                      ),
+                       hovermode="x"
+
+                       )
     fig2.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig2.update_yaxes(title_text="% of imported oil", showline=True)
-    fig2.update_xaxes(showline=True,title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig2.update_yaxes(title_text="% of imported oil", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
 
     fig2.update_layout(
         title="% of imported oil transformed into electricity and transformation losses in {}".format(year))
-    # title="Plot Title <br><sub>Plot Subtitle</sub>",)
-    # print(summary_df)
-    fig2.update_traces(marker_line_color='white',
+    fig2.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
 
@@ -928,7 +863,6 @@ def UNstats_plots(year):
                          marker_color='darkturquoise'))
 
     fig3.update_layout(  # width=1500,
-        # height=500,
         barmode='relative')
     fig3.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
                                   y=0.98,
@@ -937,28 +871,213 @@ def UNstats_plots(year):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
-                      )
-                      )
+                          color=font_color
+                      ),
+                       hovermode="x"
+
+                       )
     fig3.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig3.update_yaxes(title_text="% of imported oil", showline=True)
-    fig3.update_xaxes(showline=True,title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig3.update_yaxes(title_text="% of imported oil", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig3.update_xaxes(showline=True,linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
 
     fig3.update_layout(
         title="Breakdown of imported oil consumed for domestic transport in {}".format(year))
-    # print(summary_df)
-    fig3.update_traces(marker_line_color='white',
+    fig3.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
+    fig4 = go.Figure()
+    fig4.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['Oil imports'], name='Oil imports',text=summary_df['Oil imports'],
+                          marker_color='forestgreen'))
 
-    return [fig,fig2,fig3]
+    fig4.update_layout(  # width=1500,
+        # height=500,
+        barmode='relative')
+    fig4.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig4.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig4.update_yaxes(title_text="TJ", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig4.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig4.update_layout(
+        title="Imported oil in {}".format(year))
+    fig4.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    # fig4.update_traces(texttemplate='%{text:.1s}')
+
+    fig5 = go.Figure()
+    fig5.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['Total_demand'], name='Total demand',text=summary_df['Total_demand'],
+                          marker_color='forestgreen'))
+
+    fig5.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig5.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig5.update_yaxes(title_text="TJ", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig5.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+
+    fig5.update_layout(
+        title="Total demand (excluding int transit) in {}".format(year))
+    # print(summary_df)
+    fig5.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    fig5.update_traces(hovertemplate=None)
+
+
+
+    fig6 = go.Figure()
+    fig6.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['renewables_in_total'], name='Total energy from renewables',text=summary_df['renewables_in_total'],
+                          marker_color='forestgreen'))
+
+    fig6.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig6.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig6.update_yaxes(title_text="TJ", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig6.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig6.update_layout(
+        title="Total renewable energy (electricity and final consumption) used in {}".format(year))
+    # print(summary_df)
+    fig6.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    fig6.update_traces(hovertemplate=None)
+
+    fig7 = go.Figure()
+    fig7.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['renewable_electricity'], name='Total energy from renewables',text=summary_df['renewable_electricity'],
+                          marker_color='forestgreen'))
+
+    fig7.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig7.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig7.update_yaxes(title_text="TJ", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig7.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig7.update_layout(
+        title="Primary electricity production (wind, PV, hydro, geothermal) in {}".format(year))
+    # print(summary_df)
+    fig7.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    fig7.update_traces(hovertemplate=None)
+
+    fig8 = go.Figure()
+    fig8.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['Renewables/Total_demand'], name='Total energy from renewables',text=summary_df['Renewables/Total_demand'],
+                          marker_color='forestgreen'))
+
+    fig8.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig8.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig8.update_yaxes(title_text="% of total demand", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig8.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig8.update_layout(
+        title="Contribution of renewables in total demand (excluding int transit) in {}".format(year))
+    fig8.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    fig8.update_traces(hovertemplate=None)
+
+    fig9 = go.Figure()
+    fig9.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['Renewables/capita'], name='Total energy from renewables',text=summary_df['Renewables/capita'],
+                          marker_color='forestgreen'))
+
+    fig9.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
+                       )
+    fig9.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig9.update_yaxes(title_text="MJ per capita", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig9.update_xaxes(showline=True, linecolor=line_color,
+                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>")
+    fig9.update_layout(
+        title="Renewable energy consumption per capita in {}".format(year))
+    fig9.update_traces(marker_line_color=font_color,
+                       marker_line_width=1.5, opacity=1)
+    fig9.update_traces(hovertemplate=None)
+
+    return [fig,fig2,fig3,fig4,fig5,fig6,fig7,fig8,fig9]
 
 def land_use_plot():
+    final_demand = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[1]
+    non_RE_demand = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[9]
+    countries = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[0]
+    non_RE_demand = non_RE_demand.round(0)
+    final_demand=final_demand.round(0)
+
+    df_pop = pd.read_csv('Data/Economic Indicators.csv')
+
     df = pd.read_excel('Data/Potentials.xlsx')
-    countries = df.columns[2:]
     PV_pot = df.iloc[0, 2:] #GWh/MW/year
     Wind_CF =df.iloc[1, 2:]
     Wind_pot =df.iloc[2, 2:] #GWh/MW/year
@@ -968,13 +1087,9 @@ def land_use_plot():
     pasture = df.iloc[6, 2:]
     forested = df.iloc[7, 2:]
     other =df.iloc[8, 2:]
-    non_RE_demand = df.iloc[10,2:]
-    final_demand = df.iloc[12,2:]
     coastline = df.iloc[13,2:]
     area = df.iloc[14,2:]
 
-
-
     Wind_MW_non_RE = 1.2 * non_RE_demand/Wind_pot
     Wind_MW_final = 1.2 * final_demand/Wind_pot
 
@@ -988,12 +1103,19 @@ def land_use_plot():
     PV_area_non_RE_per = 100 * PV_area_non_RE/area
     PV_area_final_demand = PV_final_demand/(100) #0.1kw/m2
     PV_area_final_demand_per = 100 * PV_area_final_demand/area
+
+
+
+    final_demand_per_capita = 1000*final_demand/df_pop['Population']#MWh/year.person
+    non_RE_demand_per_capita = 1000*non_RE_demand/df_pop['Population']#MWh/year.person
+    final_demand_per_capita = final_demand_per_capita.round(1)
+    non_RE_demand_per_capita = non_RE_demand_per_capita.round(1)
     fig = make_subplots(specs=[[{"secondary_y": False}]])
 
     fig.add_trace(go.Scatter(x=countries, y=Wind_MW_non_RE, name='Decarbonizing the electricity sector',
-                          marker_color='red', text = Wind_MW_non_RE,
+                          marker_color='red', text = Wind_MW_non_RE,mode='markers',
                       ))
-    fig.add_trace(go.Scatter(x=countries, y=Wind_MW_final, name='Meeting the final demand',
+    fig.add_trace(go.Bar(x=countries, y=Wind_MW_final, name='Meeting the final demand',
                           marker_color='black', text = Wind_MW_final,
                       ))
     fig.update_layout(  # width=1500,
@@ -1006,7 +1128,7 @@ def land_use_plot():
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        ),
                       hovermode="x"
                       )
@@ -1014,25 +1136,21 @@ def land_use_plot():
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="Wind capacity (MW)", showline=True,rangemode='tozero')
-    fig.update_xaxes(showline=True,showgrid=False)
+    fig.update_yaxes(title_text="Wind capacity (MW)", showline=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,showgrid=False,linecolor=line_color)
     fig.update_layout(
         title="Required wind capacity")
     # print(summary_df)
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
     fig.update_traces(texttemplate='%{text:.1s}',)
 
-
-
     fig1 = make_subplots(specs=[[{"secondary_y": False}]])
-
-
-    fig1.add_trace(go.Scatter(x=countries, y=percentage_of_coastline_final, name='% coastline for final demand',
+    fig1.add_trace(go.Bar(x=countries, y=percentage_of_coastline_final, name='% coastline for final demand',
                           marker_color='black'))
     fig1.add_trace(
         go.Scatter(x=countries, y=percentage_of_coastline_non_RE, name='% coastline for decarbonizing the electricity sector',
-                   marker_color='red'))
+                   marker_color='red',mode='markers'))
     fig1.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
                                    y=0.98,
                                    xanchor="center",
@@ -1040,37 +1158,28 @@ def land_use_plot():
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        ),
                        hovermode="x",
-
-
                        )
     fig1.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig1.update_yaxes(title_text="% of coastline", showline=True, showgrid=True)
-
-    fig1.update_xaxes(showline=True,showgrid=False)
-
+    fig1.update_xaxes(showline=True,showgrid=False,linecolor=line_color)
     fig1.update_layout(
         title="Coastline required for wind turbine installation")
-    fig1.update_traces(marker_line_color='white',
+    fig1.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
-    fig1.update_yaxes(rangemode='tozero')
-
-
+    fig1.update_yaxes(title_text="% of coastline", showline=True, showgrid=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
     fig2 = make_subplots(specs=[[{"secondary_y": False}]])
-
     fig2.add_trace(go.Scatter(x=countries, y=PV_non_RE, name='Decarbonizing the electricity sector',
-                          marker_color='red',text = PV_non_RE,
+                          marker_color='red',text = PV_non_RE,mode='markers',
                       ))
-    fig2.add_trace(go.Scatter(x=countries, y=PV_final_demand, name='Meeting the final demand',
+    fig2.add_trace(go.Bar(x=countries, y=PV_final_demand, name='Meeting the final demand',
                           marker_color='black',text = PV_final_demand,
                       ))
-
-    fig2.update_layout(  # width=1500,
+    fig2.update_layout(
         # height=500,
         barmode='relative')
     fig2.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
@@ -1080,7 +1189,7 @@ def land_use_plot():
                        font=dict(
                            family="Calibri",
                            size=16,
-                           color="white"
+                           color=font_color
                        ),
                        hovermode="x"
 
@@ -1089,21 +1198,15 @@ def land_use_plot():
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig2.update_yaxes(title_text="PV capacity (MW)", showline=True,rangemode='tozero')
-    # fig2.update_yaxes(title_text="Capacity Factor (%)", secondary_y=True, showline=True, showgrid=False)
-
-    fig2.update_xaxes(showline=True,showgrid=False)
-
+    fig2.update_yaxes(title_text="PV capacity (MW)", showline=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showline=True,showgrid=False,linecolor=line_color,)
     fig2.update_layout(
         title="Required PV capacity")
-    # print(summary_df)
-    fig2.update_traces(marker_line_color='white',
+    fig2.update_traces(marker_line_color=font_color,
                        marker_line_width=1.5, opacity=1)
-    fig2.update_yaxes(rangemode='tozero')
+    fig2.update_yaxes(rangemode='tozero',linecolor=line_color,gridcolor=line_color)
     fig2.update_traces(texttemplate='%{text:.1s}')
 
-
-
     fig3 = go.Figure()
     fig3.add_trace(go.Bar(x=countries, y=arable, name='Arable',
                          marker_color='orangered'))
@@ -1121,10 +1224,7 @@ def land_use_plot():
                          marker_color='black'))
 
     fig3.update_layout(  # width=1500,
-        # height=600,
-        # autosize = True,
         barmode='relative')
-
     fig3.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
                                   y=0.94,
                                   xanchor="left",
@@ -1132,17 +1232,18 @@ def land_use_plot():
                       font=dict(
                           family="Calibri",
                           size=14,
-                          color="white"
+                          color=font_color
                       ),
-                      )
+                       hovermode="x"
+                       )
     fig3.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig3.update_yaxes(title_text="% land", showline=True,rangemode='tozero')
-    fig3.update_xaxes(showline=True,title_text="<a href=\"https://www.cia.gov/the-world-factbook/countries\"><sub>Source: The World Factbook, CIA<sub></a>")
-
-    fig3.update_traces(marker_line_color='white',
+    fig3.update_yaxes(title_text="% land", showline=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    fig3.update_xaxes(showline=True,linecolor=line_color,
+                      title_text="<a href=\"https://www.cia.gov/the-world-factbook/countries\"><sub>Source: The World Factbook, CIA<sub></a>")
+    fig3.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
     fig3.update_layout(margin=dict(t=130))
     fig3.update_layout(
@@ -1152,57 +1253,83 @@ def land_use_plot():
             # 'x': 0,
             'xanchor': 'left',
             'yanchor': 'top'})
+    fig4 = make_subplots(specs=[[{"secondary_y": False}]])
+    fig4.add_trace(go.Bar(x=countries, y=non_RE_demand,text=non_RE_demand, name='Decarbonizing the electricity sector',
+                          marker_color='red',
+                      ))
+    fig4.add_trace(go.Bar(x=countries, y=final_demand,text=final_demand, name='Meeting the final demand',
+                          marker_color='darkgrey',
+                      ))
+    fig4.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
 
+                       )
+    fig4.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig4.update_yaxes(title_text="Demand (GWh/year)", showline=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    fig4.update_xaxes(showline=True,showgrid=False,linecolor=line_color,)
+    fig4.update_layout(
+        title="Demand for decarbonization")
+    fig4.update_traces(marker_line_color=font_color,
+                       marker_line_width=0, opacity=1)
+    fig4.update_yaxes(rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    # fig4.update_traces(texttemplate='%{text:.1s}')
 
 
+    fig5 = make_subplots(specs=[[{"secondary_y": False}]])
+    fig5.add_trace(go.Bar(x=countries, y=non_RE_demand_per_capita,text=non_RE_demand_per_capita, name='Decarbonizing the electricity sector',
+                          marker_color='red',
+                      ))
+    fig5.add_trace(go.Bar(x=countries, y=final_demand_per_capita,text=final_demand_per_capita, name='Meeting the final demand',
+                          marker_color='darkgrey',
+                      ))
+    fig5.update_layout(legend=dict(bgcolor='rgba(0,0,0,0)', yanchor="bottom", orientation="h",
+                                   y=0.98,
+                                   xanchor="center",
+                                   x=0.5),
+                       font=dict(
+                           family="Calibri",
+                           size=16,
+                           color=font_color
+                       ),
+                       hovermode="x"
 
+                       )
+    fig5.update_layout({
+        'plot_bgcolor': 'rgba(0,0,0,0)',
+        'paper_bgcolor': 'rgba(0,0,0,0)',
+    })
+    fig5.update_yaxes(title_text="Demand (MWh/year.person)", showline=True,rangemode='tozero',linecolor=line_color,gridcolor=line_color)
+    fig5.update_xaxes(showline=True,showgrid=False,linecolor=line_color,)
+    fig5.update_layout(
+        title="Demand per capita")
+    fig5.update_traces(marker_line_color=font_color,
+                       marker_line_width=0, opacity=1)
+    fig5.update_yaxes(rangemode='tozero',linecolor=line_color,gridcolor=line_color)
 
+    return fig, fig1,fig2,fig3,fig4,fig5
 
 
-
-    return fig, fig1,fig2,fig3
-
-
-def mapboxplot(Country):
+def mapboxplot(Country,style):
     import math
-    df = pd.read_excel('Data/Potentials.xlsx')
-    countries = df.columns[2:]
-    # PV_pot = df.iloc[0, 2:] #GWh/MW/year
-    PV_pot = df.iloc[0][Country] #GWh/MW/year
-
-    Wind_CF = df.iloc[1][Country]
-    Wind_pot = df.iloc[2][Country]#GWh/MW/year
-
-    non_RE_demand = df.iloc[10][Country]
-    final_demand = df.iloc[12][Country]
-    coastline = df.iloc[13][Country]
-    area = df.iloc[14][Country] #km2
-
-
-
-    Wind_MW_non_RE = 1.2 * non_RE_demand/Wind_pot
-    Wind_MW_final = 1.2 * final_demand/Wind_pot
-
-    percentage_of_coastline_final = ((Wind_MW_final * 100/1.5)*0.25)/coastline
-    percentage_of_coastline_non_RE = ((Wind_MW_non_RE * 100/1.5)*0.25)/coastline
-
-    PV_non_RE = 1.2 * non_RE_demand/PV_pot #MW
-    PV_final_demand = 1.2 * final_demand/PV_pot #MW
-
-    PV_area_non_RE = PV_non_RE/(100) #0.1kw/m2 # Converted to km2
-    PV_area_non_RE_per = 100 * PV_area_non_RE/area
-    PV_area_final_demand = PV_final_demand/(100) #0.1kw/m2
-    PV_area_final_demand_per = 100 * PV_area_final_demand/area
-
-    width_decarb = math.sqrt(PV_area_non_RE) * 1000/2
-    width_final_demand = math.sqrt(PV_area_final_demand) * 1000/2
-
     import plotly.graph_objects as go
     from math import sqrt, atan, pi
     import pyproj
-    geod = pyproj.Geod(ellps='WGS84')
-    # Country = "Samoa"
 
+    PV_area_non_RE, PV_area_final_demand, PV_area_non_RE_per, PV_area_final_demand_per = functions.PV_area_single_country(Country,2019)
+    width_decarb = math.sqrt(PV_area_non_RE) * 1000/2
+    width_final_demand = math.sqrt(PV_area_final_demand) * 1000/2
+    geod = pyproj.Geod(ellps='WGS84')
     Coordinates = {"Samoa": [-13.597336, -172.457458], "Nauru": [-0.5228, 166.9315], "Vanuatu": [-15.3767, 166.9592],
                    "Palau": [7.5150, 134.5825], "Kiribati": [1.780915, -157.304505],
                    "Cook Islands": [-21.2367, -159.7777],
@@ -1214,9 +1341,7 @@ def mapboxplot(Country):
 
     width = width_decarb  # m
     height = width_decarb  # m
-
     rect_diag = sqrt(width ** 2 + height ** 2)
-
     center_lon = Coordinates[Country][1]
     center_lat = Coordinates[Country][0]
     azimuth1 = atan(width / height)
@@ -1228,9 +1353,6 @@ def mapboxplot(Country):
     pt3_lon, pt3_lat, _ = geod.fwd(center_lon, center_lat, azimuth3 * 180 / pi, rect_diag)
     pt4_lon, pt4_lat, _ = geod.fwd(center_lon, center_lat, azimuth4 * 180 / pi, rect_diag)
 
-
-
-
     fig = go.Figure(go.Scattermapbox(
         mode="lines+text", fill="toself",
         marker=dict(size=16, color='red'),
@@ -1238,8 +1360,8 @@ def mapboxplot(Country):
         # name = "asdsadad"
         textfont=dict(size=16, color='red'),
         hovertemplate="<b>{}</b><br><br>".format(Country) +
-                      "PV area for decarbonizing the electricity sector: {} km2</b><br>".format(round(PV_area_non_RE,2)) +
-                      "% of land: {}<extra></extra>".format(round(PV_area_non_RE_per,2)),
+                      "PV area for decarbonizing the electricity sector: {} km2</b><br>".format(round(PV_area_non_RE,3)) +
+                      "% of land: {}<extra></extra>".format(round(PV_area_non_RE_per,3)),
         lon=[pt1_lon, pt2_lon, pt3_lon, pt4_lon, pt1_lon, ],
         lat=[pt1_lat, pt2_lat, pt3_lat, pt4_lat, pt1_lat],
     ))
@@ -1264,24 +1386,21 @@ def mapboxplot(Country):
         # name = "asdsadad"
         textfont=dict(size=16, color='black'),
         hovertemplate="<b>{}</b><br><br>".format(Country) +
-                      "PV area for final demand: {} km2</b><br>".format(round(PV_area_final_demand,2)) +
-                      "% of land: {}<extra></extra>".format(round(PV_area_final_demand_per,2)),
+                      "PV area for final demand: {} km2</b><br>".format(round(PV_area_final_demand,3)) +
+                      "% of land: {}<extra></extra>".format(round(PV_area_final_demand_per,3)),
         lon=[pt1_lon, pt2_lon, pt3_lon, pt4_lon, pt1_lon, ],
         lat=[pt1_lat, pt2_lat, pt3_lat, pt4_lat, pt1_lat],
     ))
 
-
-    styles = ["open-street-map", "carto-positron", "carto-darkmatter", "stamen-terrain", "stamen-toner",
-              "stamen-watercolor"]
     fig.update_layout(
-        mapbox={'style': styles[3], 'center': {'lon': center_lon, 'lat': center_lat}, 'zoom': 6},
+        mapbox={'style': style, 'center': {'lon': center_lon, 'lat': center_lat}, 'zoom': 9},
         # add zoom as a slider
         showlegend=False,
         margin={'l': 0, 'r': 0, 'b': 0, 't': 0},
     )
-    print(width_decarb , width_final_demand)
     return fig
 
+
 def generation_mix_plot():
     df = pd.read_csv('Data/Energy Pofiles.csv')
     Generation_df = df[['Country','Total_GWh_2019','Rebewable_GWh_2019','Non-Renewable_GWh_2019','Hydro_GWh_2019','Solar_GWh_2019','Wind_GWh_2019','Bio_GWh_2019','Geothermal_GWh_2020']]
@@ -1310,20 +1429,21 @@ def generation_mix_plot():
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="% of total GWh generation", showline=True)
-    fig.update_xaxes(showline=True,title_text="<a href=\"https://www.irena.org/Statistics/Statistical-Profiles\"><sub>Source: Country Profiles, IRENA<sub></a>")
+    fig.update_yaxes(title_text="% of total GWh generation", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text="<a href=\"https://www.irena.org/Statistics/Statistical-Profiles\"><sub>Source: Country Profiles, IRENA<sub></a>")
 
     fig.update_layout(
         title="Generation mix in 2019")
     # print(summary_df)
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
     fig2 = go.Figure()
@@ -1350,20 +1470,21 @@ def generation_mix_plot():
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig2.update_layout({
         'plot_bgcolor': 'rgba(0,0,0,0)',
         'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig2.update_yaxes(title_text="% of total MW capacity", showline=True)
-    fig2.update_xaxes(showline=True,title_text="<a href=\"https://www.irena.org/Statistics/Statistical-Profiles\"><sub>Source: Country Profiles, IRENA<sub></a>")
+    fig2.update_yaxes(title_text="% of total MW capacity", showline=True,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showline=True,linecolor=line_color,
+                      title_text="<a href=\"https://www.irena.org/Statistics/Statistical-Profiles\"><sub>Source: Country Profiles, IRENA<sub></a>")
 
     fig2.update_layout(
         title="Installed capacity mix in 2020")
     # print(summary_df)
-    fig2.update_traces(marker_line_color='white',
+    fig2.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
 
 
@@ -1393,14 +1514,19 @@ def validation():
 
 
 
-def cross_country_sankey(df,from_,to_):
+def cross_country_sankey(df,from_,to_,normalization):
+    if normalization ==1:
+        Unit = "TJ"
+        tail = "real values"
+
+    elif normalization == ' (from)':
+        Unit = "%"
+        tail = 'normalized with origin'
+    elif normalization == ' (to)':
+        Unit = "%"
+        tail = 'normalized with destination'
     fig = go.Figure()
     fig.add_trace(go.Bar(x=df['Country'], y=df['Values'],name='dasdsa',marker_color='forestgreen',text = df['Values']))
-    # fig.add_trace(go.Bar(x=summary_df['Country'], y=summary_df['aviation_to_import'], name='Int. aviation bunkers',marker_color='lightsalmon'))
-
-
-
-
     fig.update_layout(width=800,
         # height=500,
         barmode='relative')
@@ -1411,7 +1537,7 @@ def cross_country_sankey(df,from_,to_):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig.update_layout({
@@ -1419,16 +1545,16 @@ def cross_country_sankey(df,from_,to_):
     'paper_bgcolor': 'rgba(0,0,0,0)',
 
     })
-    fig.update_yaxes(title_text="TJ",showline=True)
-    fig.update_xaxes(showline=True,
+    fig.update_yaxes(title_text=Unit,showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
                      title_text="<a href=\"http://unstats.un.org/unsd/energystats/pubs/balance\"><sub>Source: Energy Balances, United Nations<sub></a>"),
 
     fig.update_layout(
-        title="From {} to {}".format(from_,to_))
+        title="From {} to {} ({})".format(from_,to_,tail))
     # print(summary_df)
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
-    fig.update_traces(texttemplate='%{text:.1s}')
+    # fig.update_traces(texttemplate='%{text:.1s}')
 
 
     return fig
@@ -1442,8 +1568,6 @@ def import_export_figure_dynamic(df,product):
     min = min + 0.2 * min
     max = df['export_values'].max()
     max = max + 0.2 * max
-
-    print(df)
     fig.add_trace(go.Bar(x=df['Country'], y=df['import_values'], name='Imports', marker_color='red',text = df['import_values'].round(decimals=2)))
     fig.add_trace(go.Bar(x=df['Country'], y=df['export_values'], name='Exports', marker_color='green',text = df['export_values'].round(decimals=2)))
     fig.update_layout(width=800,
@@ -1456,36 +1580,89 @@ def import_export_figure_dynamic(df,product):
                       font=dict(
                           family="Calibri",
                           size=16,
-                          color="white"
+                          color=font_color
                       )
                       )
     fig.update_layout({
     'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)',
     })
-    fig.update_yaxes(title_text="Value ($MM)",showline=True)
-    fig.update_xaxes(showline=True,title_text = "<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
+    fig.update_yaxes(title_text="Value ($MM)",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text = "<a href=\"https://oec.world/en/home-b\"><sub>Source: The Observatory of Economic Complexity (OEC)<sub></a>")
 
     fig.update_layout(
         title="{}".format(product))
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=1.5, opacity=1)
     # fig.update_traces(texttemplate='%{text:.1s}')
     fig.update_layout(
-        yaxis_range=[min-5, max+5]
+        yaxis_range=[min-10, max+5]
     )
 
     return fig
 
 
 def Solar_physical_resources():
+    df_technical_potential = pd.DataFrame()
     import plotly.graph_objs as go
     names = ['Wind', 'PV']
     df = pd.read_excel('Data/Potentials.xlsx')
-
     countries = Country_List
     Wind_pot = df.iloc[2, 2:]  # GWh/MW/year
     PV_pot = df.iloc[0, 2:]  # GWh/MW/year
+    coastline = df.iloc[13,2:]
+    area = df.iloc[14,2:]
+
+    arable = df.iloc[4, 2:]
+    crops = df.iloc[5, 2:]
+    pasture = df.iloc[6, 2:]
+    forested = df.iloc[7, 2:]
+    other = df.iloc[8, 2:]
+
+    Technical_PV_area = (0.1 * pasture/100 + 0.1 * arable/100) * area
+
+
+    Theoretical_PV = PV_pot * area * 0.1 * 1000 * 0.8 #GWh
+    Theoretical_wind = Wind_pot * coastline * (1.5/0.25) * 0.8 # GWh
+
+    Technical_PV_GWh = PV_pot * Technical_PV_area * 0.1 * 1000 * 0.8 #GWh
+    Technical_wind_GWh = Theoretical_wind * 0.1
+
+    Theoretical_PV_GW = area * 1000 * 0.1/1000
+    Technical_PV_GW = Technical_PV_area * 1000 * 0.1 / 1000
+
+    Theoretical_wind_GW = (1.5/0.25) * coastline/1000
+    Technical_wind_GW = Theoretical_wind_GW * 0.1
+    Theoretical_wind = Theoretical_wind * 0.1
+    Theoretical_wind_GW = Theoretical_wind_GW * 0.1
+
+    Theoretical_PV = Theoretical_PV.astype(int)
+    Theoretical_wind = Theoretical_wind.astype(float)
+    Theoretical_wind = Theoretical_wind.round(decimals= 1)
+
+    Theoretical_PV_GW = Theoretical_PV_GW.astype(int)
+    Theoretical_wind_GW = Theoretical_wind_GW.astype(float)
+    Theoretical_wind_GW = Theoretical_wind_GW.round(decimals= 2)
+    Technical_PV_GW = Technical_PV_GW.astype(float)
+    Technical_PV_GW = Technical_PV_GW.round(decimals=1)
+
+    Technical_PV_GWh = Technical_PV_GWh.astype(int)
+    Technical_wind_GWh = Technical_wind_GWh.astype(int)
+
+    df_technical_potential['Country'] = countries
+    df_technical_potential['PV_technical_potential_GWh'] = Technical_PV_GWh.values
+    df_technical_potential['Wind_technical_potential_GWh'] = Technical_wind_GWh.values
+    df_technical_potential['sum_of_wind_and_solar_GWh'] =df_technical_potential['PV_technical_potential_GWh']+df_technical_potential['Wind_technical_potential_GWh']
+    df_technical_potential['Pv_MW'] = Technical_PV_GW.values
+    df_technical_potential['Wind_MW'] = Theoretical_wind_GW.values
+    df_technical_potential.to_csv('Wind_and_solar_technical_potential.csv')
+
+
+
+
+
+
     fig = go.Figure(data=[go.Bar(
         x=countries,
         y=PV_pot,
@@ -1493,8 +1670,8 @@ def Solar_physical_resources():
     )])
     fig.update_layout(
         title="Available solar resources")
-    fig.update_yaxes(title_text="GWh/MW/year",showline=True)
-    fig.update_xaxes(showline=True)
+    fig.update_yaxes(title_text="GWh/MW/year",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig.update_xaxes(showline=True,linecolor=line_color,)
 
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'})
@@ -1504,9 +1681,9 @@ def Solar_physical_resources():
                       font=dict(
                           family="Calibri",
                           size=15,
-                          color="white"
+                          color=font_color
                       ))
-    fig.update_traces(marker_color='Yellow', marker_line_color='white',
+    fig.update_traces(marker_color='Yellow', marker_line_color=font_color,
                       marker_line_width=2, opacity=1)
 
 
@@ -1517,32 +1694,150 @@ def Solar_physical_resources():
     )])
     fig2.update_layout(
         title="Available wind resources")
-    fig2.update_yaxes(title_text="GWh/MW/year",showline=True)
-    fig2.update_xaxes(showline=True)
+    fig2.update_yaxes(title_text="GWh/MW/year",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig2.update_xaxes(showline=True,linecolor=line_color)
 
     fig2.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'})
-    # fig.update_layout(yaxis_range=[0, max_range])
-
     fig2.update_layout(#height=350,
                        font=dict(
                           family="Calibri",
                           size=15,
-                          color="white"
+                          color=font_color
                       ))
-    fig2.update_traces(marker_color='lightblue', marker_line_color='white',
+    fig2.update_traces(marker_color='lightblue', marker_line_color=font_color,
                       marker_line_width=2, opacity=1)
 
-    return fig,fig2
+    fig3 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Theoretical_wind,
+        text=Theoretical_wind
+    )])
+    fig3.update_layout(
+        title="Technical wind generation")
+    fig3.update_yaxes(title_text="GWh/year",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig3.update_xaxes(showline=True,linecolor=line_color)
 
+    fig3.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+    'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig3.update_layout(#height=350,
+                       font=dict(
+                          family="Calibri",
+                          size=15,
+                          color=font_color
+                      ))
+    fig3.update_traces(marker_color='lightblue', marker_line_color=font_color,
+                      marker_line_width=2, opacity=1)
+    # fig3.update_traces(texttemplate='%{text:.1s}')
 
+    fig4 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Theoretical_PV,
+        text=Theoretical_PV
+    )])
+    fig4.update_layout(
+        title="Theoretical PV generation")
+    fig4.update_yaxes(title_text="GWh/year",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig4.update_xaxes(showline=True,linecolor=line_color)
+    fig4.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+    'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig4.update_layout(#height=350,
+                       font=dict(
+                          family="Calibri",
+                          size=15,
+                          color=font_color
+                      ))
+    fig4.update_traces(marker_color='yellow', marker_line_color=font_color,
+                      marker_line_width=2, opacity=1)
+    fig4.update_traces(texttemplate='%{text:.1s}')
 
-def diesel_petrol_price(Fuel):
-    import plotly.graph_objs as go
-    df = pd.read_csv("Data/{}.csv".format(Fuel)) #USD c/Litre
+    fig5 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Theoretical_PV_GW,
+        text=Theoretical_PV_GW
+    )])
+    fig5.update_layout(
+        title="Theoretical PV capacity")
+    fig5.update_yaxes(title_text="GW",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig5.update_xaxes(showline=True,linecolor=line_color)
+    fig5.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+    'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig5.update_layout(#height=350,
+                       font=dict(
+                          family="Calibri",
+                          size=15,
+                          color=font_color
+                      ))
+    fig5.update_traces(marker_color='yellow', marker_line_color=font_color,
+                      marker_line_width=2, opacity=1)
 
+    fig6 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Theoretical_wind_GW,
+        text=Theoretical_wind_GW
+    )])
+    fig6.update_layout(
+        title="Technical wind capacity")
+    fig6.update_yaxes(title_text="GW",showline=True,linecolor=line_color,gridcolor=line_color)
+    fig6.update_xaxes(showline=True,linecolor=line_color)
+    fig6.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+    'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig6.update_layout(#height=350,
+                       font=dict(
+                          family="Calibri",
+                          size=15,
+                          color=font_color
+                      ))
+    fig6.update_traces(marker_color='lightblue', marker_line_color=font_color,
+                      marker_line_width=2, opacity=1)
 
+    fig7 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Technical_PV_GW,
+        text=Technical_PV_GW
+    )])
+    fig7.update_layout(
+        title="Technical PV capacity")
+    fig7.update_yaxes(title_text="GW", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig7.update_xaxes(showline=True, linecolor=line_color)
+    fig7.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+                        'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig7.update_layout(  # height=350,
+        font=dict(
+            family="Calibri",
+            size=15,
+            color=font_color
+        ))
+    fig7.update_traces(marker_color='yellow', marker_line_color=font_color,
+                       marker_line_width=2, opacity=1)
+    # fig7.update_traces(texttemplate='%{text:.1s}')
+
+    fig8 = go.Figure(data=[go.Bar(
+        x=countries,
+        y=Technical_PV_GWh,
+        text=Technical_PV_GWh
+    )])
+    fig8.update_layout(
+        title="Technical PV generation")
+    fig8.update_yaxes(title_text="GWh/year", showline=True, linecolor=line_color, gridcolor=line_color)
+    fig8.update_xaxes(showline=True, linecolor=line_color)
+    fig8.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
+                        'paper_bgcolor': 'rgba(0,0,0,0)'})
+    fig8.update_layout(  # height=350,
+        font=dict(
+            family="Calibri",
+            size=15,
+            color=font_color
+        ))
+    fig8.update_traces(marker_color='yellow', marker_line_color=font_color,
+                       marker_line_width=2, opacity=1)
+    # fig8.update_traces(texttemplate='%{text:.1s}')
+
+    return fig,fig2,fig3,fig4,fig5,fig6,fig7,fig8
 
+def diesel_petrol_price(Fuel):
+    import plotly.graph_objs as go
+    df = pd.read_csv("Data/{}.csv".format(Fuel)) #USD c/Litre
     fig = go.Figure()
     fig.add_trace(go.Bar(x=df['Country'], y=df['Tax excluded'],name='Tax excluded',marker_color='forestgreen'))
     fig.add_trace(go.Bar(x=df['Country'], y=df['Tax'],name='Tax',marker_color='red'))
@@ -1550,27 +1845,23 @@ def diesel_petrol_price(Fuel):
 
     fig.update_layout(
         title="Regional {} retail price for quarter 1, 2022 ".format(Fuel))
-    fig.update_yaxes(title_text="US cents/Litre",showline=True)
-    # fig.update_xaxes(showline=True)
-
+    fig.update_yaxes(title_text="US cents/Litre",showline=True,linecolor=line_color,gridcolor=line_color)
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'})
-    # fig.update_layout(yaxis_range=[0, max_range])
-
     fig.update_layout(#height=350,
                       font=dict(
                           family="Calibri",
                           size=15,
-                          color="white"
+                          color=font_color
                       ),
                         barmode='relative')
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=2, opacity=1)
     fig.update_layout(legend = dict(bgcolor = 'rgba(0,0,0,0)',    yanchor="bottom",orientation="h",
         y=1.05,
         xanchor="center",
         x=0.5))
-    fig.update_xaxes(showline=True,title_text = "<a href=\"https://www.haletwomey.co.nz/\"><sub>Source: Pacific Islands fuel supply, demand and comparison of regional prices 2022, Hale&Twomey <sub></a>")
+    fig.update_xaxes(linecolor=line_color,showline=True,title_text = "<a href=\"https://www.haletwomey.co.nz/\"><sub>Source: Pacific Islands fuel supply, demand and comparison of regional prices 2022, Hale&Twomey <sub></a>")
 
     return fig
 
@@ -1579,8 +1870,6 @@ def elec_price_plot():
     import plotly.graph_objs as go
     df = pd.read_csv("Data/elec Price and subsidies.csv") #USD c/Litre
 
-
-
     fig = go.Figure()
     fig.add_trace(go.Bar(x=df['Country'], y=df['small res'],name='Residential consumer, 1.1 kVA, 60 kWh/month',marker_color='forestgreen'))
     fig.add_trace(go.Bar(x=df['Country'], y=df['res'],name='Residential consumer, 3.3 kVA, 300 kWh/month',marker_color='yellow'))
@@ -1590,24 +1879,29 @@ def elec_price_plot():
 
     fig.update_layout(
         title="Regional electricity retail price in 2019")
-    fig.update_yaxes(title_text="USD/kWh",showline=True)
-    fig.update_xaxes(showline=True)
+    fig.update_yaxes(title_text="USD/kWh",showline=True,linecolor=line_color,gridcolor=line_color)
 
     fig.update_layout({'plot_bgcolor': 'rgba(0,0,0,0)',
     'paper_bgcolor': 'rgba(0,0,0,0)'})
     fig.update_layout(#height=350,
                       font=dict(
                           family="Calibri",
-                          size=15,
-                          color="white"
+                          size=18,
+                          color=font_color
                       ),
                         )
-    fig.update_traces(marker_line_color='white',
+    fig.update_traces(marker_line_color=font_color,
                       marker_line_width=2, opacity=1)
-    fig.update_layout(legend = dict(bgcolor = 'rgba(0,0,0,0)',    yanchor="bottom",orientation="h",
+    fig.update_layout(legend = dict(bgcolor = 'rgba(0,0,0,0)', yanchor="bottom",orientation="h",
         y=1.05,
         xanchor="center",
         x=0.5))
-    fig.update_xaxes(showline=True,title_text = "<a href=\"chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/http://ura.gov.vu/attachments/article/67/Comparative%20Report%20-%20Pacific%20Region%20Electricity%20Bills%20June%202016.pdf\"><sub>Source: Pacific Region Electricity Bills 2019, Utilities Regulatory Authority (URA) <sub></a>")
+    fig.update_xaxes(showline=True,linecolor=line_color,
+                     title_text = "<a href=\"chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/http://ura.gov.vu/attachments/article/67/Comparative%20Report%20-%20Pacific%20Region%20Electricity%20Bills%20June%202016.pdf\"><sub>Source: Pacific Region Electricity Bills 2019, Utilities Regulatory Authority (URA) <sub></a>")
 
     return fig
+
+def Total_imports_plot():
+    pass
+    #total imports in GWh
+    # final demand comparative in GWh
\ No newline at end of file
diff --git a/functions.py b/functions.py
new file mode 100644
index 0000000..779f646
--- /dev/null
+++ b/functions.py
@@ -0,0 +1,178 @@
+import pandas as pd
+import numpy as np
+
+
+def fetch_wind_PV_potential(Country):
+    df_p = pd.read_excel('Data/Potentials.xlsx')
+    # print(df_p.loc[2, country],power_generated_GWh)
+    Wind_pot = df_p.loc[2, Country]  # GWh/MW/year
+    PV_pot = df_p.loc[0, Country]  # GWh/MW/year
+    area = df_p.iloc[14][Country]  # km2
+    coastline = df_p.iloc[13][Country]
+
+
+    return PV_pot,Wind_pot,area,coastline
+def fetch_single_country_demand(Country,Year,Unit='GWh'):
+    """This function calculates the final demand and non-RE transformation"""
+    df = pd.read_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(Year))
+    df = df[df["Country ({})".format(Year)] == Country]
+    ElectricitySupply = df[df['Transactions(down)/Commodity(right)']=='Transformation']['Electricity'].values[0] #TJ
+    ofWhichRenewable_transformation = -df[df['Transactions(down)/Commodity(right)']=='Transformation']['memo: Of which Renewables'].values[0] #TJ # This is the input to power plants
+    renewable_transformation_efficiency = 0.35
+    non_RE_demand =  ElectricitySupply - ofWhichRenewable_transformation * renewable_transformation_efficiency #TJ
+
+    electrification_efficiency_improvement = 0.4
+    final_consumption = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['Total Energy'].values[0] #TJ#Does not include fuel for transformation. Only output of power plants and energy delivered to users
+    ofWhichRenewable_final_consumption = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['memo: Of which Renewables'].values[0] #TJ # This is the input to power plants
+    final_consumption_electricity = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['Electricity'].values[0]
+    """
+    final demand is the non renewable part of the demand, assuming that all sectors are electrified
+    """
+    final_demand = non_RE_demand + (final_consumption-final_consumption_electricity-ofWhichRenewable_final_consumption) * (1-electrification_efficiency_improvement)
+    #previously
+    # final_demand = df[df['Transactions(down)/Commodity(right)']=='Total energy supply']['Total Energy'].values[0] #TJ
+
+    if Unit =='GWh':
+        final_demand = final_demand * 0.277778
+        non_RE_demand = non_RE_demand * 0.277778
+    return non_RE_demand,final_demand
+
+
+def PV_area_single_country(Country,Year):
+    PV_pot, Wind_pot, area, coastline = fetch_wind_PV_potential(Country)
+    non_RE_demand,final_demand = fetch_single_country_demand(Country,Year)
+    PV_non_RE = 1.2 * non_RE_demand / PV_pot  # MW
+    PV_final_demand = 1.2 * final_demand / PV_pot  # MW
+    PV_area_non_RE = PV_non_RE / (100)  # 0.1kw/m2 # Converted to km2
+    PV_area_non_RE_per = 100 * PV_area_non_RE / area
+    PV_area_final_demand = PV_final_demand / (100)  # 0.1kw/m2
+    PV_area_final_demand_per = 100 * PV_area_final_demand / area
+
+    return PV_area_non_RE,PV_area_final_demand,PV_area_non_RE_per,PV_area_final_demand_per
+
+
+def Wind_area_single_country(Country,Year):
+    PV_pot, Wind_pot, area, coastline = fetch_wind_PV_potential(Country)
+
+    non_RE_demand,final_demand = fetch_single_country_demand(Country,Year)
+    Wind_MW_non_RE = 1.2 * non_RE_demand / Wind_pot
+    Wind_MW_final = 1.2 * final_demand / Wind_pot
+    percentage_of_coastline_final = ((Wind_MW_final * 100/1.5)*0.25)/coastline
+    percentage_of_coastline_non_RE = ((Wind_MW_non_RE * 100/1.5)*0.25)/coastline
+
+    return percentage_of_coastline_final,percentage_of_coastline_non_RE
+
+
+def fetch_all_countries_demand(Year,Unit='GWh',Use="Analysis"):
+    df = pd.read_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(Year))
+    # final_demand = df[df['Transactions(down)/Commodity(right)']=='Total energy supply']['Total Energy'].values
+    Countries = df. iloc[:, 1].unique()
+
+    ElectricitySupply = df[df['Transactions(down)/Commodity(right)']=='Transformation']['Electricity'].values #TJ
+    ofWhichRenewable_transformation = -df[df['Transactions(down)/Commodity(right)']=='Transformation']['memo: Of which Renewables'].values #TJ # This is the input to power plants
+    renewable_transformation_efficiency = 0.35
+    non_RE_demand =  ElectricitySupply - ofWhichRenewable_transformation * renewable_transformation_efficiency #TJ
+
+    if Use == 'Analysis':
+        electrification_efficiency_improvement = 0.4
+        final_consumption = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['Total Energy'].values #TJ#Does not include fuel for transformation. Only output of power plants and energy delivered to users
+        ofWhichRenewable_final_consumption = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['memo: Of which Renewables'].values #TJ # This is the input to power plants
+        final_consumption_electricity = df[df['Transactions(down)/Commodity(right)']=='Final consumption']['Electricity'].values
+        total_demand = non_RE_demand + (final_consumption-final_consumption_electricity-ofWhichRenewable_final_consumption) * (1-electrification_efficiency_improvement)
+
+
+
+    #previously
+    if Use == 'SummaryPlot':
+        total_demand = df[df['Transactions(down)/Commodity(right)']=='Total energy supply']['Total Energy'].values #TJ#Total energy entering the country(oil and renewables)
+
+    renewables_in_total = df[df['Transactions(down)/Commodity(right)']=='Total energy supply']['memo: Of which Renewables'].values #TJ
+    renewable_electricity = df[df['Transactions(down)/Commodity(right)']=='Primary production']['Electricity'].values #TJ
+    imports = df[df['Transactions(down)/Commodity(right)']=='Imports']['All Oil'].values
+    Int_marine = df[df['Transactions(down)/Commodity(right)']=='International marine bunkers']['All Oil'].values
+    Int_avi = df[df['Transactions(down)/Commodity(right)']=='International aviation bunkers']['All Oil'].values
+    transformation = -df[df['Transactions(down)/Commodity(right)']=='Electricity  CHP & Heat Plants']['All Oil'].values
+    transformation_losses = - df[df['Transactions(down)/Commodity(right)']=='Electricity  CHP & Heat Plants']['Total Energy'].values
+    if Unit == "GWh":
+        non_RE_demand = non_RE_demand * 0.277778
+        total_demand = total_demand * 0.277778
+        imports = imports * 0.277778
+        Int_marine = Int_marine * 0.277778
+        Int_avi = Int_avi * 0.277778
+        transformation = transformation * 0.277778
+        transformation_losses = transformation_losses * 0.277778
+        renewables_in_total = renewables_in_total * 0.277778
+        renewable_electricity = renewable_electricity * 0.277778
+
+        df_demand = pd.DataFrame()
+        df_demand['Country'] = Countries
+        df_demand['Non-RE'] = non_RE_demand
+        df_demand['Total'] = total_demand
+        df_demand.to_csv('demand_df.csv')
+
+    return [Countries,total_demand,imports,Int_marine,Int_avi,transformation,transformation_losses,renewables_in_total,renewable_electricity,non_RE_demand]
+
+def all_countries_cross_comparison_unstats(Year,Unit,Use):
+    summary_df = pd.DataFrame()
+    population= pd.read_csv('Data/Economic Indicators.csv')
+
+
+
+
+    df = pd.read_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(Year))
+    summary_list = fetch_all_countries_demand(2019,Unit=Unit,Use=Use)
+    summary_df['Country'] = summary_list[0]
+    summary_df['Total_demand'] = summary_list[1]
+    summary_df['Oil imports'] = summary_list[2]
+    summary_df['int marine'] = -summary_list[3]
+    summary_df['int aviation'] = -summary_list[4]
+    summary_df['Transformation'] = summary_list[5]
+    summary_df['transformation_losses'] = summary_list[6]
+    summary_df['renewables_in_total'] = summary_list[7]
+    summary_df['renewable_electricity'] = summary_list[8]
+
+    summary_df['Renewables/Total_demand'] = 100 * summary_df['renewables_in_total']/summary_df['Total_demand']
+    summary_df['Renewables/Total_demand']=summary_df['Renewables/Total_demand'].round(1)
+
+    summary_df['Renewables/capita'] = (summary_df['renewables_in_total']/population['Population']) * 1000000 #MJ
+    summary_df['Renewables/capita'] = summary_df['Renewables/capita'].round(0)
+
+    summary_df['marine_to_import'] = 100 * summary_df['int marine']/summary_df['Oil imports']
+    summary_df['aviation_to_import'] = 100 * summary_df['int aviation']/summary_df['Oil imports']
+    summary_df['transformation_to_import'] = 100 * summary_df['Transformation']/summary_df['Oil imports']
+    summary_df['transformation_losses_to_import'] = 100 * summary_df['transformation_losses']/summary_df['Oil imports']
+    summary_df['road'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Road']['All Oil'].values/summary_df['Oil imports']
+    summary_df['rail'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Rail']['All Oil'].values/summary_df['Oil imports']
+    summary_df['Domestic aviation'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Domestic aviation']['All Oil'].values/summary_df['Oil imports']
+    summary_df['Domestic navigation'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Domestic navigation']['All Oil'].values/summary_df['Oil imports']
+    summary_df['Pipeline transport'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Pipeline transport']['All Oil'].values/summary_df['Oil imports']
+    summary_df['transport n.e.s'] = 100 * df[df['Transactions(down)/Commodity(right)']=='Transport n.e.s']['All Oil'].values/summary_df['Oil imports']
+    summary_df.to_csv("Summary_df.csv")
+    return summary_df
+
+
+
+
+def Update_UNstats_database(year):
+    Country_List = ['Samoa', 'Nauru', 'Vanuatu', 'Palau', 'Kiribati', 'Cook Islands', 'Solomon Islands', 'Tonga',
+                    'New Caledonia', 'French Polynesia', 'Micronesia', 'Niue', 'Tuvalu', 'PNG', 'Fiji']
+    all_countries_df = pd.DataFrame()
+    for country in Country_List:
+        df = pd.read_csv("Data/EnergyBalance/{}/{}.csv".format(year,country))
+        if country == Country_List[0]:
+            all_countries_df = df
+        elif country != Country_List[0]:
+            all_countries_df = all_countries_df.append(df,ignore_index=True)
+    all_countries_df.replace({"---": 0}, inplace=True)
+    all_countries_df = all_countries_df.replace({'\*': ''},regex=True)
+    c_list = all_countries_df.columns
+    for i in c_list[2:]:
+        all_countries_df[i] = all_countries_df[i].astype(float)
+    all_countries_df['All Coal'] = all_countries_df['Primary Coal and Peat'] + all_countries_df['Coal and Peat Products']
+    all_countries_df['All Oil'] = all_countries_df['Primary Oil'] + all_countries_df['Oil Products']
+    all_countries_df['All Inputs'] = all_countries_df['All Coal'] + all_countries_df['All Oil'] + all_countries_df['Natural Gas'] +\
+                                     all_countries_df['Biofuels and Waste'] + all_countries_df['Nuclear'] +all_countries_df['Heat']
+    all_countries_df.replace('Micronesia (Federated States of)', 'Micronesia',inplace=True)
+    all_countries_df.replace('Papua New Guinea', 'PNG',inplace=True)
+
+    all_countries_df.to_csv("Data/EnergyBalance/{}/all_countries_df.csv".format(year))
diff --git a/index.py b/index.py
index 591cb02..7e51ffa 100644
--- a/index.py
+++ b/index.py
@@ -5,9 +5,7 @@
 from EnergyFlows import CONTENT_STYLE
 import callbacks
 import callbacks_sankey
-
 import callbacks_FinancialFlows
-
 import dash_auth
 
 # VALID_USERNAME_PASSWORD_PAIRS = {
@@ -37,10 +35,10 @@
             dbc.Tab(label="Bioenergy potential", active_tab_style={"textTransform": "uppercase"},
                     active_label_style={"color": '#FF0000'}, tab_id='bioenergy-tab'),
             dbc.Tab(label="Decarbonization of electricity sector", active_tab_style={"textTransform": "uppercase"},active_label_style={"color": '#FF0000'},tab_id='decrb-tab'),
-            dbc.Tab(label="Plicies", active_tab_style={"textTransform": "uppercase"},
-                    active_label_style={"color": '#FF0000'}, tab_id='Plicies'),
-            dbc.Tab(label="Decarbonization of transport", active_tab_style={"textTransform": "uppercase"},
-                    active_label_style={"color": '#FF0000'}, tab_id='decrb-fleet'),
+            # dbc.Tab(label="Policies", active_tab_style={"textTransform": "uppercase"},
+            #         active_label_style={"color": '#FF0000'}, tab_id='Plicies'),
+            # dbc.Tab(label="Decarbonization of transport", active_tab_style={"textTransform": "uppercase"},
+            #         active_label_style={"color": '#FF0000'}, tab_id='decrb-fleet'),
 
         ],
         id="tabs",