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# Renewable electricity output (% of total electricity output) - EG.ELC.RNEW.ZS |
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library("XML") library("WDI") library("gridExtra") library("scatterplot3d") options(scipen=100) # turning of scientific notation titel<-"Renewable electricity output" subtitel<-"(% of total electricity output)" renewable.electricity.output <- WDI(country="all", indicator="EG.ELC.RNEW.ZS", start=1900, end=2019) str(renewable.electricity.output) # 'data.frame': 15840 obs. of 4 variables: # $ iso2c : chr "1A" "1A" "1A" "1A" ... # $ country : chr "Arab World" "Arab World" "Arab World" "Arab World" ... # $ EG.ELC.RNEW.ZS: num NA NA NA NA 2.92 ... # $ year : num 2019 2018 2017 2016 2015 ... head(renewable.electricity.output) # iso2c country EG.ELC.RNEW.ZS year # 1 1A Arab World NA 2019 # 2 1A Arab World NA 2018 # 3 1A Arab World NA 2017 # 4 1A Arab World NA 2016 # 5 1A Arab World 2.920702 2015 # 6 1A Arab World 3.278073 2014 |
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# selection of the year 2015 year <- 2015 target.year <- which(renewable.electricity.output$year==year) head(renewable.electricity.output[target.year,]) # iso2c country EG.ELC.RNEW.ZS year # 5 1A Arab World 2.920702 2015 # 65 S3 Caribbean small states 8.914780 2015 # 125 B8 Central Europe and the Baltics 20.252851 2015 # 185 V2 Early-demographic dividend 18.104862 2015 # 245 Z4 East Asia & Pacific 20.412466 2015 # 305 4E East Asia & Pacific (excluding high income) 23.394930 2015 |
– Low income
– Lower middle income
– Upper middle income
– High income
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target.income <- which(renewable.electricity.output$country=="Low income") renewable.electricity.output[target.income,] plot(renewable.electricity.output[target.income,4:3],type="l", main=titel,sub=subtitel,ylab="%",xlab="",xlim=c(1980,2020),ylim=c(10,90), axes=TRUE) text(1985, 65, "Low income",cex=0.7) |
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target.income <- which(renewable.electricity.output$country=="Lower middle income") renewable.electricity.output[target.income,] lines(renewable.electricity.output[target.income,4:3],type="l",main=titel,ylab="%",xlab="",col="red") text(1985, 20, "Lower middle income", col="red",cex=0.7) target.income <- which(renewable.electricity.output$country=="Upper middle income") renewable.electricity.output[target.income,] lines(renewable.electricity.output[target.income,4:3],type="l",main=titel,ylab="%",xlab="",col="green") text(1985, 25, "Upper middle income", col="green",cex=0.7) target.income <- which(renewable.electricity.output$country=="High income") renewable.electricity.output[target.income,] lines(renewable.electricity.output[target.income,4:3],type="l",main=titel,ylab="%",xlab="",col="blue") text(1985, 15, "High income", col="blue",cex=0.7) |
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# ------------- # region # World # Euro area # European Union # Europe & Central Asia # Arab World # North America # Latin America & Caribbean # Middle East & North Africa # Sub-Saharan Africa # East Asia & Pacific # South Asia target.area <- which(renewable.electricity.output$country=="World") renewable.electricity.output[target.area,] plot(renewable.electricity.output[target.area,4:3],type="l", main=titel,sub=subtitel,ylab="%",xlab="",xlim=c(1980,2020),ylim=c(1,90), axes=TRUE) text(1985, 20, "World",cex=0.7) target.area <- which(renewable.electricity.output$country=="Euro area") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="red") text(1985, 12, "Euro area", col="red",cex=0.7) target.area <- which(renewable.electricity.output$country=="Arab World") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="green") text(1985, 5, "Arab World", col="green",cex=0.7) target.area <- which(renewable.electricity.output$country=="North America") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="blue",lty=2) text(1985, 17, "North America", col="blue",cex=0.7) target.area <- which(renewable.electricity.output$country=="Latin America & Caribbean") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="yellow") text(1985, 65, "Latin America & Caribbean", col="yellow",cex=0.7) # target.area <- which(renewable.electricity.output$country=="Middle East & North Africa") # renewable.electricity.output[target.area,] # lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="orange") # text(1985, 5, "Middle East & North Africa", col="orange",cex=0.7) target.area <- which(renewable.electricity.output$country=="Sub-Saharan Africa") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="cyan",lty=3) text(1985, 23, "Sub-Saharan Africa", col="cyan",cex=0.7) target.area <- which(renewable.electricity.output$country=="East Asia & Pacific") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="magenta",lty=4) text(1985, 14.5, "East Asia & Pacific", col="magenta",cex=0.7) target.area <- which(renewable.electricity.output$country=="South Asia") renewable.electricity.output[target.area,] lines(renewable.electricity.output[target.area,4:3],type="l",main=titel,ylab="%",xlab="",col="pink",lty=5) text(1985, 28, "South Asia", col="pink",cex=0.7) |
