SC_NRJ.R

library(tidyverse)
library(camcorder)
library(showtext)
library(ggtext)

# Set fonts
font_add_google("Raleway","ral")
font_add_google("Bitter","bit")
font_add_google("Fira Sans","fira")
font_add_google("Jost","jost")
showtext_auto()

# Plot size
gg_record(
  dir = file.path(tempdir(),"recording"), 
  device = "png", 
  width = 21, 
  height = 21, 
  units = "cm", 
  dpi = 300 
)

owid_energy <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-06-06/owid-energy.csv')


clean<-owid_energy%>%
  filter(year>2010)%>%
  mutate(iso_code=case_when(
    country=="Kosovo"~'KOS',
    TRUE~iso_code
  ))%>%
  drop_na(iso_code)%>%
  group_by(country)%>%
  summarize(
    iso_code=iso_code[1],
    biofuel=mean(na.omit(biofuel_elec_per_capita)),
    coal=mean(na.omit(coal_elec_per_capita)),
    gas=mean(na.omit(gas_elec_per_capita)),
    hydro=mean(na.omit(hydro_elec_per_capita)),
    nuke=mean(na.omit(nuclear_elec_per_capita)),
    oil=mean(na.omit(oil_elec_per_capita)),
    solar=mean(na.omit(solar_elec_per_capita)),
    wind=mean(na.omit(wind_elec_per_capita))
  )%>%
  ungroup()


fun_country<-function(nm){

fr<-clean%>%
  filter(iso_code==nm)%>%
  pivot_longer(
    !c(country,iso_code),names_to="type",values_to="value" 
  )%>%
  mutate(x=case_when(
    type%in%c("coal","nuke","hydro")~-1/3,
    type%in%c("gas","wind")~0,
    type%in%c("oil","biofuel","solar")~+1/3
  ))%>%
  mutate(y=case_when(
    type%in%c("coal","gas","oil")~-1/3,
    type%in%c("nuke","biofuel")~0,
    type%in%c("hydro","wind","solar")~+1/3
  ))

return(fr)

}

# Country coordinates
coords<-tibble(
  iso_code=c(
    "FRA","ESP","PRT","MLT",
    "GBR","IRL","ISL","BEL",
    "LUX",'NLD','CHE','ITA',
    'SVN','NOR','DNK','DEU',
    'CZE','AUT','HRV',"BIH",
    'SWE','POL','SVK','HUN',
    'MNE','KOS','ALB','FIN',
    'EST','LTU','BLR','UKR',
    'ROU','SRB','MKD','GRC',
    'LVA','RUS','MDA','BGR',
    'GEO','TUR','CYP','AZE',
    'ARM'
  ),
  x_center=c(
    1,1,0,1,
    1,0,0,2,
    2,3,3,3,
    3,4,4,4,
    4,4,4,4,
    5,5,5,5,
    5,5,5,6,
    6,6,6,6,
    6,6,6,6,
    7,7,7,7,
    8,8,8,9,
    9
  ),
  y_center=c(
    -4,-5,-5,-7,
    -2,-2,-0,-3,
    -4,-3,-4,-5,
    -6,-0,-2,-3,
    -4,-5,-6,-7,
    -0,-3,-4,-5,
    -6,-7,-8,-0,
    -1,-2,-3,-4,
    -5,-6,-7,-8,
    -2,-3,-5,-6,
    -5,-6,-8,-5,
    -6
  )
)


dt<-fun_country("FRA")%>%
  bind_rows(fun_country("ESP"))%>%
  bind_rows(fun_country("PRT"))%>%
  bind_rows(fun_country("MLT"))%>%
  bind_rows(fun_country("GBR"))%>%
  bind_rows(fun_country("IRL"))%>%
  bind_rows(fun_country("ISL"))%>%
  bind_rows(fun_country("BEL"))%>%
  bind_rows(fun_country("LUX"))%>%
  bind_rows(fun_country("NLD"))%>%
  bind_rows(fun_country("CHE"))%>%
  bind_rows(fun_country("ITA"))%>%
  bind_rows(fun_country("SVN"))%>%
  bind_rows(fun_country("NOR"))%>%
  bind_rows(fun_country("DNK"))%>%
  bind_rows(fun_country("DEU"))%>%
  bind_rows(fun_country("CZE"))%>%
  bind_rows(fun_country("AUT"))%>%
  bind_rows(fun_country("HRV"))%>%
  bind_rows(fun_country("BIH"))%>%
  bind_rows(fun_country("SWE"))%>%
  bind_rows(fun_country("POL"))%>%
  bind_rows(fun_country("SVK"))%>%
  bind_rows(fun_country("HUN"))%>%
  bind_rows(fun_country("MNE"))%>%
  bind_rows(fun_country("KOS"))%>%
  bind_rows(fun_country("ALB"))%>%
  bind_rows(fun_country("FIN"))%>%
  bind_rows(fun_country("EST"))%>%
  bind_rows(fun_country("LTU"))%>%
  bind_rows(fun_country("BLR"))%>%
  bind_rows(fun_country("UKR"))%>%
  bind_rows(fun_country("ROU"))%>%
  bind_rows(fun_country("SRB"))%>%
  bind_rows(fun_country("MKD"))%>%
  bind_rows(fun_country("GRC"))%>%
  bind_rows(fun_country("LVA"))%>%
  bind_rows(fun_country("RUS"))%>%
  bind_rows(fun_country("MDA"))%>%
  bind_rows(fun_country("BGR"))%>%
  bind_rows(fun_country("GEO"))%>%
  bind_rows(fun_country("TUR"))%>%
  bind_rows(fun_country("CYP"))%>%
  bind_rows(fun_country("AZE"))%>%
  bind_rows(fun_country("ARM"))%>%
  left_join(coords)%>%
  mutate(
    x=x+x_center,
    y=y+y_center
  )%>%
  mutate(cl=case_when(
    type%in%c('oil','gas','coal')~'fossil',
    type%in%c('nuke','biofuel')~'low_carb',
    type%in%c('hydro','wind','solar')~'renew'
  ))

bordR<-coords%>%
  # horizontal lines
  mutate(
    y_low=y_center-0.5*1/3,
    y_high=y_center+0.5*1/3,
    x_min=x_center-0.5,
    x_max=x_center+0.5
  )%>%
  # vertical lines
  mutate(
    x_low=x_center-0.5*1/3,
    x_high=x_center+0.5*1/3,
    y_min=y_center-0.5,
    y_max=y_center+0.5
  )

col_line<-"grey50"
col_bord<-"black"

lwd_line<-0.1
lwd_bord<-0.5

pal<-c(
  'fossil'="#F21C8D",
  'low_carb'='#FEFF00',
  'renew'='#01A0C6'
)



col_back<-"grey25"

ggplot()+
  # Back
  geom_rect(
    bordR,
    mapping=aes(xmin=x_min,xmax=x_max,ymin=y_min,ymax=y_max),
    fill=col_back, col=NA
  )+
  # Horizontal lines
  geom_segment(
    bordR,
    mapping=aes(y=y_low,yend=y_low,x=x_min,xend=x_max),
    col=col_line,lwd=lwd_line
  )+
  geom_segment(
    bordR,
    mapping=aes(y=y_high,yend=y_high,x=x_min,xend=x_max),
    col=col_line,lwd=lwd_line
  )+
  # Vertical lines
  geom_segment(
    bordR,
    mapping=aes(x=x_low,xend=x_low,y=y_min,yend=y_max),
    col=col_line,lwd=lwd_line
  )+
  geom_segment(
    bordR,
    mapping=aes(x=x_high,xend=x_high,y=y_min,yend=y_max),
    col=col_line,lwd=lwd_line
  )+
  # Borders
  geom_rect(
    bordR,
    mapping=aes(xmin=x_min,xmax=x_max,ymin=y_min,ymax=y_max),
    fill=NA, col=col_bord,lwd=lwd_bord
  )+

  # Electricity per capita
  geom_point(
    dt%>%filter(value>0),
    mapping=aes(x=x,y=y,size=value,color=cl),
    pch=15
  )+
  
  # Country name
  geom_text(
    dt,
    mapping=aes(x=x_center,y=y_center,label=iso_code),
    family="bit",size=9,col="white"
  )+
  scale_color_manual(values=pal)+
  #scale_x_continuous(limits=c(-1,1))+
  #scale_y_continuous(limits=c(-1,1))+
  guides(color='none',size='none')+
  coord_fixed()+
  theme_void()