Improve keyboard accessibility for scatter-trendline plots in plotly/ggplotly

Usage

ro_ply_keyboard_nav_trendline(fig)

Arguments

fig

A plotly object (from plotly::plot_ly() or plotly::ggplotly()).

Value

A plotly object with improved keyboard accessibility.

Details

Enhances the accessibility of interactive scatter-trendline plots created with plotly or ggplotly. This function injects custom JavaScript to make bar elements focusable and navigable via keyboard, displays accessible tooltips, and ensures screen readers can interpret the chart. The function is intended for use on plotly scatter-trendline plots (including those created with ggplotly). The focusable element are the points.

Keyboard navigation: users can use Tab to focus the first point, and arrow keys (Left/Right/Up/Down) to move between points. Pressing Esc removes focus from the chart and returns focus to the next logical element.

See also

Other ggplotly: ro_ply_cursor(), ro_ply_disable_toolbar(), ro_ply_keyboard_nav_barchart(), ro_ply_keyboard_nav_bargraph(), ro_ply_keyboard_nav_legend(), ro_ply_keyboard_nav_linechart()

Other plotly: ro_ply_add_theme(), ro_ply_cursor(), ro_ply_dim(), ro_ply_disable_toolbar(), ro_ply_focus_linechart(), ro_ply_keyboard_nav_barchart(), ro_ply_keyboard_nav_bargraph(), ro_ply_keyboard_nav_legend(), ro_ply_keyboard_nav_linechart(), ro_ply_legend_theme(), ro_ply_theme(), ro_ply_title()

Examples

if (FALSE) { # \dontrun{
dates <- seq(as.Date("2021-10-04"), by = "day", length.out = 100)
n <- round(2500 + 700 * sin(seq_along(dates) / 25) + seq_along(dates) *
3 + rnorm(length(dates), 0, 150))

moving_average <- stats::filter(n, rep(1 / 7, 7), sides = 2)
text <- paste0(
  "Dag: <b>", format(dates, "%d-%m-%Y"), "</b><br>",
  "Aantal cases: <b>", format(n,
  big.mark = ".", decimal.mark = ",", scientific = FALSE), "</b><br>",
  "7-daags gemiddelde: <b>",
  format(round(moving_average, 0),
   big.mark = ".",
   decimal.mark = ",", scientific = FALSE), "</b>"
)
data <- tibble::tibble(
  Date_statistics = dates,
  n = n,
  moving_average = as.numeric(moving_average),
  text = text
)
library(ggplot2)
library(plotly)
p <- ggplot(data, aes(x = Date_statistics, y = n, text = text, group = 1)) +
  geom_line() +
  geom_point()
fig <- ggplotly(p, tooltip = "text")
fig <- ro_ply_keyboard_nav_trendline(fig)
fig
} # }