population in GIS countries

Datasource: World Bank

raw data

Code

dataraw <- read.csv2("data/pop_cis.csv") # , sep = ";",encoding = "utf-8"
years <- paste(1960:2024) #, sep=",", collapse= ","
years <- unlist(strsplit(years, ","))
new_cnames <- c("country", "ccode",  years)
colnames(dataraw) <- new_cnames


data <- dataraw
rmarkdown::paged_table(head(data)) # show sample 10 rows
# oder {r, df_print = "paged"}
# sample_n(data_raw, 10

data frame

Code

fmil <- function(x) round(x/1000000, digits = 2) # funk to x/Mill um zu verkürzen

# dataframe
df <- 
  data |> 
  mutate(across(!c(country, ccode), fmil)) |> 
  pivot_longer(
    cols = !c(country, ccode),
    names_to = "year",
    values_to = "pop"
  ) |> 
  mutate(year = as.integer(year)) |> 
  group_by(year) |> 
  arrange(year, pop) |> #desc(pop)
  mutate(rank = 1:n()) |> 
  ungroup()

head(df)

#> # A tibble: 6 × 5
#>   country      ccode  year   pop  rank
#>   <chr>        <chr> <int> <dbl> <int>
#> 1 Turkmenistan TKM    1960  1.64     1
#> 2 Armenia      ARM    1960  1.86     2
#> 3 Tajikistan   TJK    1960  2.11     3
#> 4 Kyrgyzstan   KGZ    1960  2.17     4
#> 5 Azerbaijan   AZE    1960  3.89     5
#> 6 Belarus      BLR    1960  8.2      6

plot for the year 2024

Code

pl24 <- 
  # data -----------------------------------------------
  df |> 
  filter(
    year==2024
  ) |>
  mutate(
    images = case_when(
      ccode == "ARM" ~ paste0(imgpat, "AM.png"),
      ccode == "AZE" ~ paste0(imgpat, "AZ.png"),
      ccode == "BLR" ~ paste0(imgpat, "BY.png"),
      ccode == "KAZ" ~ paste0(imgpat, "KZ.png"),
      ccode == "KGZ" ~ paste0(imgpat, "KG.png"),
      ccode == "RUS" ~ paste0(imgpat, "RU.png"),
      ccode == "TJK" ~ paste0(imgpat, "TJ.png"),
      ccode == "TKM" ~ paste0(imgpat, "TM.png"),
      ccode == "UZB" ~ paste0(imgpat, "UZ.png"),
      TRUE ~ ccode)
  ) |>
  # plot aes ----------------------------------------------------
  ggplot(aes(
  xmin = 0,
  xmax = pop,
  y = rank,
  ymin = rank - 0.45,
  ymax = rank + 0.45,
  fill = ccode)) +
  geom_rect(alpha = 0.5) +
  # axises, labels
  scale_x_continuous(
    limits = c(0,150),
    breaks = seq(0, 150, 25),
    labels = function(x) paste0(x, "M"),
    expand = expansion(c(0.09, 0.0))) +
  geom_image(aes(y= rank, image = images), 
             x = -10, size = 0.07, by="height") + 
  geom_label(aes(x = pop, label = as.character(pop)), 
             colour = "white", hjust=0.0) +
  geom_label(aes(label = paste("Year:",year)),
             x = 125, y = 2, size = 8, fill = "white", col = "gray") +
  # title, caption ---------------------------------------------
  labs(
    x = "Population (in millions)",
    y = NULL,
    title = "Population in CIS countries in 2024",
    caption = social_caption) +
  # format, theme ----------------------------------------------
  theme_minimal() +
  theme(legend.position = "none",
        plot.title = element_text(size=14, face = "bold", color="steelblue4", hjust = 0.5 ),
        plot.caption = ggtext::element_markdown(size=12, hjust = 0.5),
        panel.grid.major.y = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.line.x =  element_line(colour = "gray"),
        axis.text.y = element_blank())

# show plot
pl24

Slopegraph in ggplot2

Code

library(CGPfunctions)

gg <-
  df |> 
  filter(
  year==1990 | year==2024
  ) |> 
  mutate(year=as.character(year))

# graph
newggslopegraph(
  dataframe = gg,
  Times = year,Measurement = pop, Grouping = country,
  Title = "Population evolution in CIS countries",
  SubTitle = "a comparison for the years: 1990-2024",
  Caption = "Data Source: Worldbank | Plot by: \u00A9ф",
  XTextSize = 18,    # Size of the times
  YTextSize = 3,     # Size of the groups
  TitleTextSize = 14,
  SubTitleTextSize = 12,
  CaptionTextSize = 12,
  TitleJustify = "right",
  SubTitleJustify = "right",
  CaptionJustify = "left",
  DataTextSize = 3.0
) -> slop

slop

range plot

Code

cflags <- c(
  "ARM" = "AM", "AZE" = "AZ", "BLR" ="BY", "KAZ" = "KZ", "KGZ" ="KG", 
  "RUS" = "RU", "TJK" ="TJ", "TKM" = "TM", "UZB" = "UZ")
# read images
xlabels <- c()
for(i in 1:length(cflags)){
  imgname <- names(cflags[i])
  xlabels <- c(xlabels, paste0("<img src='", imgpat, cflags[[i]], ".png' width='50' hight ='50'/>"))
}

# named vector
xnames <- names(cflags)
names(xlabels) <- xnames  # zum matchen nachher für plot labels

Code

ggtext_st <- "in <span style='color:#CB5416'>1990</span> and 
<span style='color:#267266'>2024</span> \u00A9ф"

rr <-
  # data ----------------------------------------------------
  df |> 
  filter(
    year==1990 | year==2024
  ) |> 
  select(-c(country, rank)) |> 
  pivot_wider(
    names_from = year,
    values_from = pop
  ) |> 
  # plot -----------------------------------------------------
  ggplot(aes(x = ccode))+
  geom_linerange(aes(ymin = `1990`, ymax = `2024`, x= ccode),
                 size = 0.9, alpha = 0.5) +
  geom_point(aes(y = `1990`), colour = "#CB5416", size=3) +
  geom_point(aes(y = `2024`), colour = "#267266", size= 3) +
  scale_x_discrete(name = NULL, labels =  xlabels)+
  coord_flip()+
  labs(
    title =  "Population in CIS countries", 
    subtitle = ggtext_st,
    caption = social_caption,
    x = NULL,
    y = NULL
  ) +
  # format -----------------------------------------------------
  theme(
    legend.position = "none",
    plot.title = element_text(hjust = 0.5),
    plot.subtitle = element_textbox(hjust = 0.5),
    plot.caption = element_textbox(hjust = 0.5, size = 11),
    axis.text.y = element_markdown()
  )

rr

plot animate

barplot

Code

# Title/subtitle/datasource

pl <- 
  # data -----------------------------------------------
  df |>
  # filter(
  #   year==2024
  # ) |>
  mutate(
    images = case_when(
      ccode == "ARM" ~ paste0(imgpat, "AM.png"),
      ccode == "AZE" ~ paste0(imgpat, "AZ.png"),
      ccode == "BLR" ~ paste0(imgpat, "BY.png"),
      ccode == "KAZ" ~ paste0(imgpat, "KZ.png"),
      ccode == "KGZ" ~ paste0(imgpat, "KG.png"),
      ccode == "RUS" ~ paste0(imgpat, "RU.png"),
      ccode == "TJK" ~ paste0(imgpat, "TJ.png"),
      ccode == "TKM" ~ paste0(imgpat, "TM.png"),
      ccode == "UZB" ~ paste0(imgpat, "UZ.png"),
      TRUE ~ ccode)
  ) |>
  # plot aes ----------------------------------------------------
  ggplot(aes(
  xmin = 0,
  xmax = pop,
  y = rank,
  ymin = rank - 0.45,
  ymax = rank + 0.45,
  fill = ccode)) +
  geom_rect(alpha = 0.5) +
  # axises, labels
  scale_x_continuous(
    limits = c(0,150),
    breaks = seq(0, 150, 25),
    labels = function(x) paste0(x, "M"),
    expand = expansion(c(0.09, 0.0))) +
  geom_image(aes(y= rank, image = images), 
             x = -10, size = 0.07, by="height") + 
  geom_label(aes(x = pop, label = as.character(pop)), 
             colour = "white", hjust=0.0) +
  geom_label(aes(label = paste("Year:",year)),
             x = 125, y = 2, size = 8, fill = "white", col = "gray") +
  # title, caption ---------------------------------------------
  labs(
    x = "Population (in millions)",
    y = NULL,
    title = "Population evolution in CIS countries in 1960-2024",
    caption = social_caption) +
  # format, theme ----------------------------------------------
  theme_minimal() +
  theme(legend.position = "none",
        plot.title = element_text(size=14, face = "bold", color="steelblue4", hjust = 0.5 ),
        plot.caption = ggtext::element_markdown(size=12, hjust = 0.5),
        panel.grid.major.y = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.line.x =  element_line(colour = "gray"),
        axis.text.y = element_blank())

Code

# animate
pl_anim <-
  pl +
  transition_states(year,wrap = FALSE, transition_length = 64) + #, transition_length = 
  ease_aes("cubic-in-out") +
  enter_fade()+
  exit_fade()#+
  #shadow_mark()

#pl_anim

anim <- animate(
  pl_anim,
  duration = 32,
  start_pause =5,
  end_pause = 5,
  renderer = gifski_renderer()
)
anim

treemap

Code

# library(treemapify)
pl_tm <-
  df |> 
  filter(year >= 1990) |> 
  ggplot(aes(
    area = pop, fill = country,
    label = paste(country, paste0(pop, " Mln"), sep = "\n"))) +
  geom_treemap()+
  geom_treemap_text(
    colour = "white",
    place = "centre",
    #face = "bold", # ohne grow = TRUE zu benutzen
    #size = 10,     # ohne grow = TRUE zu benutzen
    grow = TRUE) +
  labs(
    title = "Population in CIS countries for the year: {(frame_time)}",
    caption = social_caption) +
  theme(
    legend.position = "none",
    plot.title = element_text(colour =  "steelblue", size = 15, face = "bold", hjust = 0.5),
    plot.caption = element_textbox(hjust = 0.5, size = 12)) +
  transition_time(time = year)

anim_tm <- animate(
  pl_tm,
  duration = 30,
  start_pause =5,
  end_pause = 5,
  renderer = gifski_renderer()
)
anim_tm