# 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)Germany Map (Town)
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Germany Map (Town) 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-germany-town/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
dt_map <- readRDS(url("https://download.hiplot.cn/ui/basic/map-germany-town/germany_town.rds"))
# Convert data structure
dt_map$Value <- data$value[match(dt_map$ENG_NAME, data$name)]
# View data
head(data) name value
1 Allmendingen 711
2 Altheim 540
3 BerghΓΌlen 582
4 Blaubeuren 454
5 Blaustein 766
6 Balzheim 480
Visualization
# Germany Map (Town)
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 = "Germany Map")
p
