Electric power consumption (kWh per capita)

China, Mexico, Turkey and USA.

From year 1995 to 2005

Attach WDI

library(WDI)
## Warning: package 'WDI' was built under R version 4.1.3
df = WDI(indicator = 'EG.USE.ELEC.KH.PC',country=c('CN','MX','TR','USA'),start=1995,end=2005)
head(df)
##   country iso2c iso3c year EG.USE.ELEC.KH.PC
## 1   China    CN   CHN 2005         1782.3122
## 2   China    CN   CHN 2004         1585.8388
## 3   China    CN   CHN 2003         1379.4846
## 4   China    CN   CHN 2002         1194.8563
## 5   China    CN   CHN 2001         1076.5491
## 6   China    CN   CHN 2000          992.9434
tail(df)
##          country iso2c iso3c year EG.USE.ELEC.KH.PC
## 39 United States    US   USA 2000          13671.05
## 40 United States    US   USA 1999          13281.87
## 41 United States    US   USA 1998          13154.76
## 42 United States    US   USA 1997          12889.83
## 43 United States    US   USA 1996          12854.30
## 44 United States    US   USA 1995          12659.61

Attach dplyr

library(dplyr)
## Warning: package 'dplyr' was built under R version 4.1.3
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
df<-df %>%
  rename(country = 1,
         countrycodeiso2 = 2,
         countryiso3 = 3,
         year = 4,
         EG.USE.ELEC.KH.PC = 5)

Attach reshape2 to monitor data more broadly

library(reshape2)
## Warning: package 'reshape2' was built under R version 4.1.3
data_genis <- dcast(df, year ~ country, value.var = "EG.USE.ELEC.KH.PC")
head(data_genis)
##   year    China   Mexico  Turkiye United States
## 1 1995 770.2802 1419.903 1227.327      12659.61
## 2 1996 821.0809 1444.361 1328.351      12854.30
## 3 1997 852.7407 1528.184 1439.975      12889.83
## 4 1998 870.6172 1643.047 1520.096      13154.76
## 5 1999 913.9634 1689.186 1556.334      13281.87
## 6 2000 992.9434 1800.468 1652.746      13671.05
tail(data_genis)
##    year     China   Mexico  Turkiye United States
## 6  2000  992.9434 1800.468 1652.746      13671.05
## 7  2001 1076.5491 1834.151 1612.999      13046.61
## 8  2002 1194.8563 1843.964 1667.364      13296.18
## 9  2003 1379.4846 2001.018 1771.827      13307.49
## 10 2004 1585.8388 1927.074 1891.841      13388.59
## 11 2005 1782.3122 1996.393 2013.889      13704.58

Net Electricity power consumption of all countries in the data set

df2 <- WDI(
  country = "all",
  indicator = "EG.USE.ELEC.KH.PC",
  start = 2000,
  end = 2022,
  extra = TRUE,
  cache = NULL,
  latest = NULL,)

Attach ggplot2

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.1.3
library(ggfortify)
## Warning: package 'ggfortify' was built under R version 4.1.3

Convert data-set to Time series Use tsveris

tsveri <- ts(data_genis, start=1995, frequency=1)
head(tsveri)
##      year    China   Mexico  Turkiye United States
## [1,] 1995 770.2802 1419.903 1227.327      12659.61
## [2,] 1996 821.0809 1444.361 1328.351      12854.30
## [3,] 1997 852.7407 1528.184 1439.975      12889.83
## [4,] 1998 870.6172 1643.047 1520.096      13154.76
## [5,] 1999 913.9634 1689.186 1556.334      13281.87
## [6,] 2000 992.9434 1800.468 1652.746      13671.05
tail(tsveri)
##       year     China   Mexico  Turkiye United States
##  [6,] 2000  992.9434 1800.468 1652.746      13671.05
##  [7,] 2001 1076.5491 1834.151 1612.999      13046.61
##  [8,] 2002 1194.8563 1843.964 1667.364      13296.18
##  [9,] 2003 1379.4846 2001.018 1771.827      13307.49
## [10,] 2004 1585.8388 1927.074 1891.841      13388.59
## [11,] 2005 1782.3122 1996.393 2013.889      13704.58

Plot time series

plot(tsveri[,2:5])

Plot On a Single graph

plot(tsveri[,2:5], plot.type = "single")

Graph the time series

plot(tsveri[,2],
     type = "l",
     col = 2,
     ylim = c(0, 25),
     xlab = "year",
     ylab = "EG.USE.ELEC.KH.PC")
lines(tsveri[,3],
      type = "l",
      col = 3)
lines(tsveri[,4],
      type = "l",
      col = 4)
lines(tsveri[,5],
      type = "l",
      col = 5)
legend("topright",                           
       c("China","Mexico", "Türkey", "US"),
       lty = 1,
       col = 2:5)

data_long <-melt(data_genis, id.vars = "year")
ggplot(data_long,                           
       aes(x = year,
           y = value,
           col = variable)) +
  geom_line()