social network in GIS

plot of share of social network users population in CIS countries using ggplot2 and gganimate
barplot
R
ggplot2
gganimate
ggpol
Author

Fazliddin Sultonov

Published

Mar 5, 2025

Datasource: World Population Review | Internet

data

Code 
data_sng <- data.frame(
  SN = c("TikTok", "Instagram", "Telegram", "Facebook", "WhatsApp"),
  ARM = c(NA, 1.4, NA, 2.3, 0.8),
  AZE = c(6.1, 4.3, 5.0, 5.1, 2.5),
  BLR = c(5.6, 3.9, 2.4, 4.3, 2.1),
  KAZ = c(14.1, 12.4, 12.5, 13.2, 8.0),
  KGZ = c( 4.9, 2.9, NA, 3.3, 1.6),
  RUS = c(58.2, 63.0, 35.1, 70.6, 66.7),
  TJK = c(NA, 1.6, NA, 1.8, 1.4),
  TKM = c(NA, 0.2, NA, 0.2, 0.6),
  UZB = c(3.1, 9.4, 18.0, 10.1, 5.1)
)



rmarkdown::paged_table(data_sng) # show sample 10 rows
# oder {r, df_print = "paged"}
# sample_n(data_raw, 10

fill NAs (with column mean)

Code 
data <- 
    data_sng |>
    mutate(
        row_nr = row_number()) |> 
  pivot_longer(-c(SN, row_nr),
    names_to = "col_id",
    values_to = "val") |> 
  group_by(col_id) |> 
  mutate(val = ifelse(is.na(val), round(mean(val,na.rm = TRUE),1), round(val,1))) |> 
  pivot_wider(names_from="col_id", values_from = "val") |> 
  ungroup()

rmarkdown::paged_table(data)

proportion of total population

Code 
pop <- c(
  "ar" = 2.9, "az" = 10.3, "be" = 9.1, "kz" = 20.6, "kg" = 7.2, 
  "ru" = 144.8, "tj" = 10.6, "tm" = 7.5, "uz" = 36.4)

data_pct <-
  data |>
  rowwise() |>
  mutate(
    ARM = round((ARM/pop["ar"]) *100, 1),
    AZE = round((AZE/pop["az"]) *100, 1),
    BLR = round((BLR/pop["be"]) *100, 1),
    KAZ = round((KAZ/pop["kz"]) *100, 1),
    KGZ = round((KGZ/pop["kg"]) *100, 1),
    RUS = round((RUS/pop["ru"]) *100, 1),
    TJK = round((TJK/pop["tj"]) *100, 1),
    TKM = round((TKM/pop["tm"]) *100, 1),
    UZB = round((UZB/pop["uz"]) *100, 1))

data_pct
#> # A tibble: 5 × 11
#> # Rowwise: 
#>   SN        row_nr   ARM   AZE   BLR   KAZ   KGZ   RUS   TJK   TKM   UZB
#>   <chr>      <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 TikTok         1  51.7  59.2  61.5  68.4  68.1  40.2  15.1   4     8.5
#> 2 Instagram      2  48.3  41.7  42.9  60.2  40.3  43.5  15.1   2.7  25.8
#> 3 Telegram       3  51.7  48.5  26.4  60.7  44.4  24.2  15.1   4    49.5
#> 4 Facebook       4  79.3  49.5  47.3  64.1  45.8  48.8  17     2.7  27.7
#> 5 WhatsApp       5  27.6  24.3  23.1  38.8  22.2  46.1  13.2   8    14

prepare data for plotting

Code 
data_pct$frame <- 1:5
#data_pct
for(i in 1:nrow(data_pct)){
  data_pct$frame[i] <- list(data_pct$frame[i][[1]]:5)
}
#data_pct
data_pct <- unnest(data_pct, frame)
#data_pct

# Data Frame for Plot
df_pct <-  gather(data_pct, variable, value, -c(frame, SN, row_nr))
head(df_pct)
#> # A tibble: 6 × 5
#>   SN        row_nr frame variable value
#>   <chr>      <int> <int> <chr>    <dbl>
#> 1 TikTok         1     1 ARM       51.7
#> 2 TikTok         1     2 ARM       51.7
#> 3 TikTok         1     3 ARM       51.7
#> 4 TikTok         1     4 ARM       51.7
#> 5 TikTok         1     5 ARM       51.7
#> 6 Instagram      2     2 ARM       48.3

plotting

Code 
# Title/subtitle/datasource
data_source <- "World Population Review | Internet"
p_title <- "<br>Часть соцсеть пользователей в общей населения в странах СНГ"
p_subtitle <- ""

# caption
social_caption <- glue::glue(
  "<span style = 'color:skyblue3;'><i><strong><br>DataSource: {data_source} <br/></strong></i></span>  Plot by:
  <span style='color: #C4302B; font-family:\"Font Awesome 6 Brands\";'>{yt_icon};</span>
  <span style='color: #C4302B'>{yt_username}</span> |
  <span style='color: #e1306c; font-family:\"Font Awesome 6 Brands\";'>{ins_icon};</span>
  <span style='color: #e1306c'>{ins_username}</span> |
  <span style='color: #24A1DE; font-family:\"Font Awesome 6 Brands\";'>{tg_icon};</span>
  <span style='color: #24A1DE'>{tg_username}<br></span>"
)

# caption
social_caption_anim <- glue::glue(
  "<span style='color: #C4302B; font-family:\"Font Awesome 6 Brands\";'>{yt_icon};</span>
  <span style='color: #C4302B'>{yt_username}</span> |
  <span style='color: #e1306c; font-family:\"Font Awesome 6 Brands\";'>{ins_icon};</span>
  <span style='color: #e1306c'>{ins_username}</span> |
  <span style='color: #24A1DE; font-family:\"Font Awesome 6 Brands\";'>{tg_icon};</span>
  <span style='color: #24A1DE'>{tg_username}<br></span>"
)
Code 
# flag image path
imgpat <- "gallery_img/flags/"
cntry <- 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(cntry)){
  imgname <- names(cntry[i])
  xlabels <- c(xlabels, paste0("<img src='", imgpat, cntry[[i]], ".png' width='50' hight ='25'  /><br>**", imgname, "**"))
}

# custom color
my_color <- c("TikTok" = "#2AF0EA", "Instagram" = "#E1306C", "Telegram" = "#24A1DE", "Facebook" = "#1877F2", "WhatsApp" = "#25D366")

# plot
gg_pct <- 
  ggplot(data = df_pct, aes(x = variable, y = value, fill = SN)) + 
  geom_bar(stat = "identity", position = "dodge") +
  scale_y_continuous(
    limits = c(0,80 ),
    breaks = seq(0, 80, 5),
    labels = function(x) paste0(x,"%")) +
  scale_x_discrete(name = NULL, labels = xlabels) +
  geom_text(aes(label = as.character(" ")), vjust = 1, size = 4)+
  #titles
  labs(
    title = p_title, 
    #subtitle = data_source,
    caption = social_caption,
    x = NULL, y = NULL) +
  scale_fill_manual(name = "Cоцсеть:", values =  my_color) +
  # format
  theme_minimal() +
  theme(
    plot.title = element_markdown(size = 16, color = "steelblue4", face = "bold", hjust = 0.5),
    plot.caption = ggtext::element_markdown(size=14, hjust = 0.5),
    axis.text.x = element_markdown(), # x-axis flags
    axis.line = element_blank(),
    legend.position = "top", legend.direction="horizontal",legend.box = "horizontal",
    panel.border = element_blank(),
    plot.background = element_rect(fill = "seashell2"), #paleturquoise "seashell1"
    panel.background = element_rect(fill = "ghostwhite"), #floralwhite
    panel.grid.minor = element_blank()
  )

# Show plot
gg_pct

animated plot

Code 
gganim_pct <-
  gg_pct +
  transition_states(frame, wrap = FALSE, transition_length = 6) +
  enter_fade()

# animate gif
anim_pct <- animate(
  gganim_pct,
  duration = 10,
  start_pause =5,
  end_pause = 10,
  renderer = gifski_renderer()
)

# show plot
anim_pct

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