# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
install.packages("jsonlite")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
install.packages("ggplot2")
}
if (!requireNamespace("RColorBrewer", quietly = TRUE)) {
install.packages("RColorBrewer")
}
# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
library(RColorBrewer)Europe Map
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Europe Map plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;ggplot2;RColorBrewer
sessioninfo::session_info("attached")β Session info βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
setting value
version R version 4.5.2 (2025-10-31)
os Ubuntu 24.04.3 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate C.UTF-8
ctype C.UTF-8
tz UTC
date 2026-01-17
pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)
quarto 1.8.27 @ /usr/local/bin/quarto
β Packages βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
package * version date (UTC) lib source
data.table * 1.18.0 2025-12-24 [1] RSPM
ggplot2 * 4.0.1 2025-11-14 [1] RSPM
jsonlite * 2.0.0 2025-03-27 [1] RSPM
RColorBrewer * 1.1-3 2022-04-03 [1] RSPM
[1] /home/runner/work/_temp/Library
[2] /opt/R/4.5.2/lib/R/site-library
[3] /opt/R/4.5.2/lib/R/library
* ββ Packages attached to the search path.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Data Preparation
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/map-europe/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
dt_map <- readRDS(url("https://download.hiplot.cn/ui/basic/map-europe/eu.rds"))
# Convert data structure
dt_map$Value <- data$value[match(dt_map$ENG_NAME, data$region)]
# View data
head(data) region value
1 Albania 758
2 Andorra 139
3 Austria 256
4 Belgium 959
5 Bosnia Herzegovina 422
6 Croatia 791
Visualization
# Europe Map
p <- ggplot(dt_map) +
geom_polygon(aes(x = long, y = lat, group = group, fill = Value),
alpha = 0.9, size = 0.5) +
geom_path(aes(x = long, y = lat, group = group), color = "black", size = 0.2) +
coord_fixed() +
scale_fill_gradientn(
colours = colorRampPalette(rev(brewer.pal(11,"RdYlBu")))(500),
breaks = seq(min(data$value), max(data$value),
round((max(data$value)-min(data$value))/7)),
name = "Color Key",
guide = guide_legend(
direction = "vertical", keyheight = unit(1, units = "mm"),
keywidth = unit(8, units = "mm"),
title.position = "top", title.hjust = 0.5, label.hjust = 0.5,
nrow = 1, byrow = T, reverse = F, label.position = "bottom")) +
theme(text = element_text(color = "#3A3F4A"),
axis.text = element_blank(),
axis.ticks = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
legend.position = "top",
legend.text = element_text(size = 4 * 1.5, color = "black"),
legend.title = element_text(size = 5 * 1.5, color = "black"),
plot.title = element_text(
face = "bold", size = 5 * 1.5, hjust = 0.5,
margin = margin(t = 4, b = 5), color = "black"),
plot.background = element_rect(fill = "#FFFFFF", color = "#FFFFFF"),
panel.background = element_rect(fill = "#FFFFFF", color = NA),
legend.background = element_rect(fill = "#FFFFFF", color = NA),
plot.margin = unit(c(1.5, 1.5, 1.5, 1.5), "cm")) +
labs(x = NULL, y = NULL, title = "Europe Map")
p
