How to build a travel map in R (Updated 2025)
One of my first posts on this site was how to create a travel map in R. I always wanted to re-visit that map to add new destinations, to make the code more efficient, to use better packages.
In the old map, I found that the grouping by continent was a lot of coding effort for not much pay-off, alphabetical sorting would be easier and intuitive to readers. I also wanted to write the greying out unvisited countries into the code itself instead of photoshopping the flags manually. There were a lot of changes to make.
After much delay, I finally got around to doing just that! Here's the updated map, and if you want to create your own map like this in R you can take the code below and adapt it to your travels.
Code
Setup
pacman::p_load(
char = c(
"googlesheets4",
"rnaturalearth",
"countrycode",
"tidyverse", # For everything
"patchwork", # For better plot layout
"rappdirs",
"ggimage", # For images on plots
"giscoR",
"magick",
"rvest",
"here",
"sf",
"fs"
)
)
graph_colours <- c(
"Visited" = "#F07C51",
"Planned" = "#FFCF66",
"Travel_outline" = "#000000",
"Country_fill" = "#D4CEC4",
"Border_line" = "#FFFFFF"
)
Read
Trips
df_trips <- googlesheets4::read_sheet(URL) %>%
janitor::clean_names() %>%
mutate(
visited = if_else(status == "Visited", TRUE, FALSE),
place_country = ifelse(
is.na(place_country),
paste(place, country, sep = ", "),
place_country),
iso2 = countrycode::countrycode(
sourcevar = country,
origin = "country.name",
destination = "iso2c",
custom_match = c(
"Kosovo" = "XK",
"United Kingdom" = "GB"
)
)
)
Flags
df_flags <- list.files(path = here::here("Input", "Flags")) %>%
as_tibble() %>%
rename(file_name = value) %>%
mutate(
file_path = paste0(here::here("Input", "Flags"), "/", file_name),
country = str_extract(file_name, '(?<=-).*(?=\\.)') %>%
str_replace_all("-", " ") %>%
str_to_title(),
iso2 = countrycode::countrycode(
sourcevar = country,
origin = "country.name",
destination = "iso2c",
custom_match = c(
"Kosovo" = "XK",
"Malasya" = "MY",
"Micronesia" = "FM",
"United Kingdom" = "GB")
)
) %>%
filter(country != "Tuvalu 1")
df_flags <- df_flags %>%
filter(
!is.na(iso2)
| country %in% c( # Add 10 so we reach 240 flags total
#"Basque Country",
"Somaliland",
#"Rapa Nui",
"Scotland",
#"Sardinia",
#"Corsica",
#"Hawaii",
#"Sicily",
"Wales",
"Tibet"
),
!country %in% c(
# British Overseas Territories & Crown Dependencies
"Anguilla",
"Bermuda",
"British Indian Ocean Territory",
"British Virgin Islands",
"Cayman Islands",
"Falkland Islands",
"Gibraltar",
"Guernsey",
"Jersey",
"Montserrat",
"Pitcairn Islands",
"Turks And Caicos",
# American Overseas Territories
"American Samoa",
"Northern Marianas Islands",
"Guam",
# Australian Overseas Territories
"Cocos Island",
"Christmas Island",
"Norfolk Island",
# Other
"Aland Islands",
"Aruba",
"French Polynesia",
"New Caledonia",
"Northern Cyprus",
"Sint Maarten"
)
) %>%
arrange(country) %>%
mutate(
x = 1 + (row_number() - 1) %% 30, # 22 is the n flags per row
y = 1 + (row_number() - 1) %/% 30,
y = rev(y), # To put A at the top, Z at the bottom
y = if_else(y > max(y + 1) / 2, y + 15, y)
)
Grey-out unvisited flags
df_flags <- df_flags %>%
mutate(
visited = case_when(
!is.na(iso2) ~ iso2 %in% df_trips$iso2,
TRUE ~ country %in% df_trips$country,
.default = NA
)
)
df_flags <- df_flags %>%
mutate(
file_grey = paste0(here::here("Input", "Flags", "Grey PNG"), "/grey-", file_name),
file_plot = if_else(visited, file_path, file_grey)
)
df_flags %>%
filter(!fs::file_exists(file_grey)) %>%
select(file_path, file_grey) %>%
purrr::pwalk(~{
img <- magick::image_read(..1)
img <- magick::image_modulate(img, saturation = 0) # preserve brightness; set sat=0
magick::image_write(img, path = ..2, format = "png")
})
Map data
World map
df_world <- gisco_get_countries(resolution = "60") %>%
janitor::clean_names() %>%
st_make_valid() %>%
st_transform("+proj=latlon +lon_0=10") %>%
st_wrap_dateline()
# Remove Antarctica
df_world <- df_world %>%
filter(name_engl != "Antarctica")
States
df_states <- ne_states(
country = c(
"United States of America",
"Australia",
"Argentina",
"Algeria",
"Brazil",
"Canada",
"China",
"India"
),
returnclass = "sf") %>%
janitor::clean_names() %>%
st_make_valid() %>%
st_transform("+proj=latlon +lon_0=10") %>%
st_wrap_dateline()
Lakes
df_lakes <- rnaturalearth::ne_download(
scale = "large",
type = "lakes",
category = "physical"
) %>%
filter(scalerank == 0)
Graph
Flags
graph_flags <- df_flags %>%
ggplot() +
ggimage::geom_image(
aes(
x = x,
y = y,
image = file_plot
),
size = 0.045
) +
theme_void()
World
# Create map
graph_world <-
ggplot() +
ggplot2::geom_sf( # Countries
data = df_world,
fill = graph_colours["Country_fill"],
colour = graph_colours["Border_line"],
linewidth = 0.25
) +
ggplot2::geom_sf( # State borders
data = df_states,
colour = graph_colours["Border_line"], # State border
fill = NA,
linewidth = 0.05
) +
ggplot2::geom_sf( # Lakes
data = df_lakes,
fill = "#FFFFFF",
colour = graph_colours["Border_line"],
linewidth = 0.05
)
# Add travel dots
graph_world <-
graph_world +
geom_point( # Back dots
data = df_trips,
aes(x = long, y = lat),
colour = graph_colours["Travel_outline"],
size = 1.25
) +
geom_point( # Front dots
data = df_trips,
aes(x = long, y = lat, colour = status),
size = 1
) +
scale_color_manual(
name = "",
values = c(
"Visited" = graph_colours[["Visited"]],
"Planned" = graph_colours[["Planned"]]
)
)
# Crop the map
graph_world <-
graph_world +
ggplot2::coord_sf(
expand = FALSE,
default_crs = sf::st_crs(4326),
xlim = c(-172, -169),
ylim = c(90, -60)
) +
theme(
axis.text = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
panel.grid = element_blank(),
panel.background = element_blank(),
plot.background = element_blank(),
legend.position = "none"
)
Combine Graphs
graph_world_travel_flags <- graph_flags +
patchwork::inset_element(
p = graph_world,
left = 0,
right = 1,
top = 0.875,
bottom = 0.175
)
Export
ggsave(
plot = graph_world_travel_flags,
path = here::here("Output"),
filename = "graph_travel_and_flags_A4.png",
device = "png",
dpi = 600,
units = "cm",
width = 36.6,
height = 16.0
)
