# Renewable electricity output (% of total electricity output) - EG.ELC.RNEW.ZS
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
# selection of the year 2015 year <- 2015 target.year <- which(renewable.electricity.output$year==year) head(renewable.electricity.output[target.year,]) # iso2c country EG.ELC.RNEW.ZS year # 5 1A Arab World 2.920702 2015 # 65 S3 Caribbean small states 8.914780 2015 # 125 B8 Central Europe and the Baltics 20.252851 2015 # 185 V2 Early-demographic dividend 18.104862 2015 # 245 Z4 East Asia & Pacific 20.412466 2015 # 305 4E East Asia & Pacific (excluding high income) 23.394930 2015
# income categories
– Low income
– Lower middle income
– Upper middle income
– High income
target.income <- which(renewable.electricity.output$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)
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$country=="High income") renewable.electricity.output[target.income,] lines(renewable.electricity.output[target.income,4:3],type="l",main=titel,ylab="%",xlab="",col="blue") text(1985, 15, "High income", col="blue",cex=0.7)
# -------------
# region
# World
# Euro area
# European Union
# Europe & Central Asia
# Arab World
# North America
# Latin America & Caribbean
# Middle East & North Africa
# Sub-Saharan Africa
# East Asia & Pacific
# South Asia
target.area <- which(renewable.electricity.output$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)