Railway Lines in Great Britain - UK and Ireland

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Figure 1: ……………..

Loading required libraries, data import & creating custom functions.

# Data Wrangling & Plotting Tools
library(tidyverse)            # All things tidy
library(sf)                   # Simple Features in R

# Plot touch-up tools
library(scales)               # Nice Scales for ggplot2
library(fontawesome)          # Icons display in ggplot2
library(ggtext)               # Markdown text support for ggplot2
library(showtext)             # Display fonts in ggplot2
library(colorspace)           # Lighten and Darken colours


# Getting geographic data 
library(ggmap)                # Getting raster maps
library(terra)                # Cropping / Masking rasters
library(tidyterra)            # Rasters with ggplot2
library(osmdata)              # Open Street Maps data

Visualization Parameters

# Font for titles
font_add_google("Saira",
  family = "title_font"
) 

# Font for the caption
font_add_google("Saira Extra Condensed",
  family = "caption_font"
) 

# Font for plot text
font_add_google("Saira Condensed",
  family = "body_font"
) 

showtext_auto()

mypal <- c("#dcdde1", "#487eb0", "#192a56", "#fbc531", "#DC143C")

# A base Colour
bg_col <- mypal[2]
seecolor::print_color(bg_col)

# Colour for highlighted text
text_hil <- mypal[3]
seecolor::print_color(text_hil)

# Colour for the text
text_col <- mypal[3]
seecolor::print_color(text_col)

point_col <- mypal[5]
seecolor::print_color(point_col)

# Define Base Text Size
bts <- 90 

# Caption stuff for the plot
sysfonts::font_add(
  family = "Font Awesome 6 Brands",
  regular = here::here("docs", "Font Awesome 6 Brands-Regular-400.otf")
)
github <- "&#xf09b"
github_username <- "aditya-dahiya"
xtwitter <- "&#xe61b"
xtwitter_username <- "@adityadahiyaias"
social_caption_1 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{github};</span> <span style='color: {text_hil}'>{github_username}  </span>")
social_caption_2 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{xtwitter};</span> <span style='color: {text_hil}'>{xtwitter_username}</span>")
plot_caption <- paste0(
  "**Data:** Open Street Maps & Stadia Maps", 
  " |  **Code:** ", 
  social_caption_1, 
  " |  **Graphics:** ", 
  social_caption_2
  )
rm(github, github_username, xtwitter, 
   xtwitter_username, social_caption_1, 
   social_caption_2)

# Add text to plot-------------------------------------------------
plot_title <- "British Tourist Locations"

plot_subtitle <- "This map shows the major tourist locations in the British Isles - UK and Ireland, i.e. England, Scotland, Wales, Northern Ireland and Ireland."

Get custom data

british_units <- geodata::gadm(
  country = c("IRL", "GBR"),
  level = 2,
  path = tempdir()
) |> 
  janitor::clean_names() |> 
  st_as_sf() |> 
  select(country, name_1, name_2, geometry)

# Get boundary of British Isles - UK + Ireland
british_boundary <- rnaturalearth::ne_countries(
  scale = "large",
  country = c("United Kingdom", "Ireland")
) |> 
  select(name, iso_a3)


british_units |> 
  st_drop_geometry() |> 
  visdat::vis_miss()

british_units |> 
  st_drop_geometry() |> 
  as_tibble() |> 
  dplyr::distinct(name_2)


# g <- ggplot() +
#   geom_sf(
#     data = british_boundary
#   ) +
#   geom_sf(
#     data = df_tourism,
#     alpha = 0.5,
#     size = 0.5
#   ) +
#   theme(
#     legend.position = "none"
#   )

# ggplot(british_boundary) +
#   geom_sf()

british_tourism <- opq(
  bbox = st_bbox(british_boundary),
  timeout = 150
) |> 
  add_osm_feature(
    key = "tourism",
    value = "attraction"
  ) |> 
  osmdata_sf()

# study British Tourism data to explore interesting trends
# tour_missing <- british_tourism$osm_points |> 
#   # filter(!is.na(name)) |> 
#   st_drop_geometry() |> 
#   summarise(
#     across(
#       everything(), 
#       ~ mean(is.na(.)) * 100
#       ), 
#     .groups = "drop"
#   ) |> 
#   pivot_longer(
#     everything(), 
#     names_to = "column_name", 
#     values_to = "perc_missing"
#   )

df_tourism <- british_tourism$osm_points |> 
    select(name, accessibility, accessible) |> 
  filter(!is.na(name)) |> 
  

british_bbox <- st_bbox(british_boundary)

# A bounding box in the format c(lowerleftlon, lowerleftlat, upperrightlon, upperrightlat)
british_bbox <- c(
  left = british_bbox$xmin,
  right = british_bbox$xmax,
  bottom = british_bbox$ymin,
  top = british_bbox$ymax
)
names(british_bbox) <- c("left", "right", "bottom", "top")


# Register the Stadia Maps Key here
# register_stadiamaps("KEY")
raw_rast <- get_stadiamap(
  bbox = british_bbox,
  zoom = 7,
  maptype = "alidade_smooth"
)

rast1 <- rast(raw_rast) |> 
  crop(london_city_sf) |> 
  mask(london_city_sf)

The Base Plot

g <- ggplot() +
  # geom_spatraster_rgb(
  #   data = rast1,
  #   alpha = 0.8,
  #   maxcell = Inf
  # ) +
  geom_sf(
    data = british_units,
    fill = mypal[1],
    colour = mypal[3],
    linewidth = 0.25
  ) + 
  geom_sf(
    data = british_boundary,
    fill = NA,
    colour = mypal[3],
    linewidth = 0.5
  ) + 
  geom_sf(
    data = df_tourism,
    colour = mypal[5],
    size = 2,
    alpha = 0.5
  ) +
  # ggrepel::geom_text_repel(
  #   data = df_tourism,
  #   mapping = aes(
  #     label = name,
  #     geometry = geometry
  #   ),
  #   family = "caption_font",
  #   colour = text_col,
  #   lineheight = 0.25,
  #   size = 24,
  #   stat = "sf_coordinates",
  #   force = 1,
  #   force_pull = 0.001,
  #   max.iter = 100
  # ) +
  labs(
    title = plot_title,
    subtitle = str_wrap(plot_subtitle, 110),
    caption = plot_caption
  ) +
  coord_sf(
    expand = FALSE,
    clip = "off"
  ) +
  ggthemes::theme_map(
    base_family = "body_font",
    base_size = bts
  ) +
  theme(
    
    # Full plot features
    plot.margin = margin(10,10,5,10, "mm"),
    plot.title.position = "plot",
    text = element_text(
      colour = text_col,
      margin = margin(0,0,0,0, "mm")
    ),
    
    # Labels and titles
    plot.title = element_text(
      hjust = 0.5,
      size = 3 * bts,
      lineheight = 0.3,
      margin = margin(0,0,5,0, "mm"),
      colour = text_hil,
      face = "bold"
    ),
    plot.subtitle = element_text(
      hjust = 0.5,
      size = bts,
      lineheight = 0.3,
      margin = margin(0,0,0,0, "mm"),
      colour = text_hil
    ),
    plot.caption = element_textbox(
      hjust = 0.5,
      family = "body_font",
      lineheight = 0.3,
      margin = margin(0,0,0,0, "mm"),
      size = 0.7 * bts,
      colour = text_hil
    )
  )

ggsave(
  plot = g,
  filename = here::here(
    "data_vizs", "viz_britain_railways.png"
  ),
  height = 50,
  width = 40,
  units = "cm",
  bg = colorspace::lighten(bg_col, 0.5)
)

Savings the thumbnail for the webpage

# Saving a thumbnail

library(magick)
# Saving a thumbnail for the webpage
image_read(here::here("data_vizs", 
                      "viz_britain_railways.png")) |> 
  image_resize(geometry = "x400") |> 
  image_write(
    here::here(
      "data_vizs", 
      "thumbnails", 
      "viz_britain_railways.png"
    )
  )

Session Info

# Data Wrangling & Plotting Tools
library(tidyverse)            # All things tidy
library(sf)                   # Simple Features in R

# Plot touch-up tools
library(scales)               # Nice Scales for ggplot2
library(fontawesome)          # Icons display in ggplot2
library(ggtext)               # Markdown text support for ggplot2
library(showtext)             # Display fonts in ggplot2
library(colorspace)           # Lighten and Darken colours


# Getting geographic data 
library(ggmap)                # Getting raster maps
library(terra)                # Cropping / Masking rasters
library(tidyterra)            # Rasters with ggplot2
library(osmdata)              # Open Street Maps data

sessioninfo::session_info()$packages |> 
  as_tibble() |> 
  select(package, 
         version = loadedversion, 
         date, source) |> 
  arrange(package) |> 
  janitor::clean_names(
    case = "title"
  ) |> 
  gt::gt() |> 
  gt::opt_interactive(
    use_search = TRUE
  ) |> 
  gtExtras::gt_theme_espn()

Table 1: R Packages and their versions used in the creation of this page and graphics