Daily Archives: 12/07/2019

# -------------

# 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)

# -------------

# 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)

Renewable electricity output – World Map

12/07/2019Allgemein, Data Analysis, Programming, RMartin Stoppacher

https://host6.ssl-net.net/martinstoppacher_com/blog/?p=1194

# ----------------

library(rworldmap)

options("scipen"=100, "digits"=4)

year <- 2015
target.year <- which(renewable.electricity.output$year==year)
head(renewable.electricity.output[target.year,])

renewable.electricity.output.year <- na.omit(renewable.electricity.output[target.year,])
renewable.electricity.output.year <- renewable.electricity.output.year[which(renewable.electricity.output.year$EG.ELC.RNEW.ZS>0),]

mapped_data <- joinCountryData2Map(renewable.electricity.output.year, joinCode = "ISO2", nameJoinColumn = "iso2c")
par(mai=c(0,0,0.2,0),xaxs="i",yaxs="i")
mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapTitle=paste(titel,subtitel))

mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapRegion="world",mapTitle=paste(titel,subtitel),
               numCats=2,catMethod=c(0:100),addLegend=FALSE,colourPalette=c("red","green"))

# ----------------

library(rworldmap)

options("scipen"=100, "digits"=4)

year <- 2015

target.year <- which(renewable.electricity.output$year==year)

head(renewable.electricity.output[target.year,])

renewable.electricity.output.year <- na.omit(renewable.electricity.output[target.year,])

renewable.electricity.output.year <- renewable.electricity.output.year[which(renewable.electricity.output.year$EG.ELC.RNEW.ZS>0),]

mapped_data <- joinCountryData2Map(renewable.electricity.output.year, joinCode = "ISO2", nameJoinColumn = "iso2c")

par(mai=c(0,0,0.2,0),xaxs="i",yaxs="i")

mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapTitle=paste(titel,subtitel))

mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapRegion="world",mapTitle=paste(titel,subtitel),

numCats=2,catMethod=c(0:100),addLegend=FALSE,colourPalette=c("red","green"))

mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapRegion="world",mapTitle=paste(titel,subtitel),
               numCats=3,catMethod=c(0:100),addLegend=FALSE,colourPalette=c("red","yellow","green"))
legend(-179, -10, legend=c("low", "medium","high"), col=c("red", "yellow","green"), lty=1:3, cex=0.6)

mapCountryData(mapped_data, nameColumnToPlot = "EG.ELC.RNEW.ZS",mapRegion="world",mapTitle=paste(titel,subtitel),

numCats=3,catMethod=c(0:100),addLegend=FALSE,colourPalette=c("red","yellow","green"))

legend(-179, -10, legend=c("low", "medium","high"), col=c("red", "yellow","green"), lty=1:3, cex=0.6)

Renewable electricity output – Statistics

12/07/2019Data Analysis, Programming, RMartin Stoppacher

# Renewable electricity output (% of total electricity output) - EG.ELC.RNEW.ZS

1	# 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

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

# 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=="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)

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)

# -------------

# 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)

MST

Daily Archives: 12/07/2019

Renewable electricity output – Regions

Renewable electricity output – World Map

Renewable electricity output – Statistics