Show the code
library(ggplot2)
library(ggiraph)
library(patchwork)
# Example data - replace with your data
map_data <- data.frame(
id = 1:3,
lat = c(40, 42, 37),
lon = c(-100, -120, -95),
group = c("A", "B", "C")
)
line_data <- data.frame(
id = rep(1:3, each = 10),
time = rep(seq(as.Date("2021-01-01"), by = "1 month", length.out = 10), 3),
value = rnorm(30),
group = rep(c("A", "B", "C"), each = 10)
)
# Map with interactive points
map_plot <- ggplot() +
borders("world", colour = "gray80", fill = "gray90") + # Add a world map background
geom_point_interactive(data = map_data, aes(x = lon, y = lat, size = 5, color=group, tooltip = group, data_id = group)) +
theme_minimal() +
theme(legend.position = "none") +
coord_sf(xlim = c(-130, -65), ylim = c(10, 75))
# Line chart with interactive lines
line_plot <- ggplot(line_data, aes(x = time, y = value, group = group, color=group)) +
geom_line_interactive(aes(data_id = group, tooltip = group))
combined_plot <- girafe(
ggobj = map_plot + plot_spacer() + line_plot + plot_layout(widths = c(0.35, 0, 0.65)),
options = list(
opts_hover(css = ''),
opts_hover_inv(css = "opacity:0.1;"),
opts_sizing(rescale = FALSE)
),
height_svg = 4,
width_svg = 12
)
Let’s say you have several samples in your dataset. Each coming from a different location.
You can use ggiraph to add a map, and link it with another way to visualize the data.
In the graph below, hover the map to reveal the sample evolution on the line chart!
If you are interested in interactive graphs, check the R graph gallery!!