index.qmd

---
title: "Interactive map"
format:
  html:
    code-fold: true
    code-summary: "Show the code"
editor: visual
---

```{r}
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!

<br/>


```{r}
combined_plot
```

<br/>

If you are interested in interactive graphs, check the [R graph gallery!](https://www.r-graph-gallery.com)!



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