interactve_line_chart.R

interactve_line_chart.R

library(dplyr)
library(ggplot2)
library(ggiraph)

# STEP 0: Compute Data and generate color palette
mean_life_exps <- gapminder::gapminder |> 
  janitor::clean_names() |> 
  group_by(continent, year) |> 
  summarise(mean_life_exp = mean(life_exp)) 
color_palette <- thematic::okabe_ito(5)
names(color_palette) <- unique(dat$continent)

# STEP 1: Use interactive geoms
line_chart <- mean_life_exps |> 
  ggplot(
    aes(
      x = year, 
      y = mean_life_exp, 
      col = continent, 
      # STEP 2: Use data_id aesthetic to share
      # interactivity across continent line
      data_id = continent
    )
  ) +
  geom_line_interactive(linewidth = 2.5) +
  geom_point_interactive(size = 4) +
  theme_minimal(base_size = 20) +
  labs(
    x = element_blank(),
    y = 'Life expectancy (in years)',
    title = 'Life expectancy over time'
  ) +
  theme(
    text = element_text(color = 'grey20'),
    legend.position = 'none',
    panel.grid.minor = element_blank(),
    plot.title.position = 'plot'
  ) +
  scale_color_manual(values = color_palette)


# STEP 3: Render plot
girafe(
  ggobj = line_chart,
  # Optional: add hover transparency
  options = list(
  	opts_hover(css = ''),
    opts_hover_inv(css = "opacity:0.1;")
  ),
  height_svg = 6, # Optional: Set plot height
  width_svg = 9 # Optional: Set plot width
)