HDX data Map

Load the required libraries and data

# Install the hdxr package from GitHub
# remotes::install_gitlab("dickoa/rhdx")

Set the HDX site to “prod” and check the configuration settings.

library(tidyverse)
library(rhdx)
set_rhdx_config(hdx_site = "prod")
get_rhdx_config()

Search for Ukraine data on HDX and list the datasets.

dat <- search_datasets("ukraine")
dat[2]

Select the second dataset and display the metadata: ukraine-border-crossings

border_crossing <- dat[2]

Display the resources available in the dataset.

UKR_data <- border_crossing %>%
  nth(1) %>%
  get_resource(1) %>%
  read_resource() 

UKR_data %>% head() %>% glimpse()

Search for Ukraine administrative boundaries data on HDX.

data2 <- search_datasets("Ukraine administrative boundaries")

And select the first dataset and display the metadata: kontur-boundaries-ukraine

boundaries <- search_datasets("kontur-boundaries-ukraine")
boundaries[1]

kontur_boundaries_ukraine <- boundaries[1]

resource <- kontur_boundaries_ukraine %>%
  nth(1) %>%
  get_resource(1)

resource

resource$get_format()

file_path <- resource$download()
file_path

file.info(file_path)$size

Unzip the file

library(R.utils)
gunzip(file_path, 
       destname = decompressed_file, 
       overwrite = TRUE)

Read the shapefile

library(sf)
ukraine_boundaries <- sf::st_read(decompressed_file)

ukraine_boundaries

map <- ggplot(ukraine_boundaries) +
  geom_sf()
map

map +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  ggthemes::theme_map() +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") 

ggplot(ukraine_boundaries) +
  geom_sf(aes(fill = population)) +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  scale_fill_viridis_c() +
  ggthemes::theme_map() +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") 

ggplot(ukraine_boundaries) +
  geom_sf(aes(color = population)) +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  scale_color_gradient(low = "navy", high = "gold",) +
  ggthemes::theme_map() +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") 

ukraine_boundaries%>%
  count(admin_level)

ukraine_boundaries%>%
  count(name_en)

ukraine_pop <- ukraine_boundaries%>%
  group_by(name_en) %>%
  reframe(geom,population = sum(population)) %>%
  arrange(desc(population)) 

ukraine_pop

ukraine_pop %>%
  filter(name_en == "Ukraine") %>%
  ggplot()+
  geom_sf(aes(geometry=geom)) 

ukraine_pop %>%
  filter(!name_en == "Ukraine") %>%
  ggplot()+
  geom_sf(aes(geometry=geom, fill = population)) 

ukraine_pop %>%
  filter(!name_en == "Ukraine") %>%
  ggplot()+
  geom_sf(aes(geometry=geom, 
              fill = population, 
              color = population)) +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  ggthemes::theme_map() +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") +
  scale_fill_viridis_c(
    name = "Population",
    labels = scales::label_comma(),
    guide = "colourbar"  # Show legend for 'fill'
  ) +
  scale_color_viridis_c(
    guide = "none"  # Suppress legend for 'color'
  ) 

ukraine_boundaries %>%
  filter(!name_en == "Ukraine") %>%
  ggplot() +
  geom_sf(aes(fill = population)) +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  scale_fill_viridis_c(name = "Population",
                       labels = scales::label_comma(),
                       guide = "colourbar") +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") +
  ggthemes::theme_map() +
  theme(
    plot.title = element_text(
      size = 24,
      face = "bold", 
      color = "darkred",  
      hjust = 0.5),
    plot.subtitle = element_text(
      size = 14,
      face = "italic",
      color = "gray50",
      hjust = 0.5)) 

ukraine_boundaries %>%
  filter(!name_en == "Ukraine") %>%
  ggplot() +
  geom_sf(aes(fill = population)) +
  geom_sf(data = UKR_data, 
          shape = 4,
          color="red", 
          size=2) +
  scale_fill_viridis_c(name = "Population",
                       labels = scales::label_comma(),
                       guide = "colourbar") +
  labs(title = "Ukraine Border Crossings",
       subtitle = "Data from HDX",
       caption = "Source: HDX | #30DayMapChallenge 2024 Day8 |Created by @fgazzelloni",
       fill = "Population") +
  ggthemes::theme_map() +
  theme(
    plot.title = element_text(
      size = 24,
      face = "bold", 
      color = "darkred",  
      hjust = 0.5),
    plot.subtitle = element_text(
      size = 14,
      face = "italic",
      color = "gray50",
      hjust = 0.5),
    plot.caption = element_text(
      size = 10,
      face = "italic",
      color = "gray50",
      hjust = 0.5))

Save the plot as a PNG file

ggsave("day8_hdx.png", 
       bg = "white",
       width = 8, height = 6, 
       dpi = 300)