Unable to Zoom or Hover on Nested Plotly Map in R Using nested subplot()

Plotly R, MATLAB, Julia, Net
1

I’m working on an interactive dashboard where multiple plotly objects including maps are displayed using nested subplot() in R. The code works structurally, but I’ve hit a wall:

library(digest)
library(sf)
library(jsonlite)
library(plotly)
library(ggplot2)
library(tidyr)
library(dplyr)
library(tibble)

sa_final_dataset <- read.csv("state_data.csv")
final_dataset <- read.csv("nation_data.csv")
australia_data <- read_sf("australia_map.shp")
pivot_data <- read.csv("pivot_data.csv")

sa_map_data <- subset(australia_data, STE_NAME21 == "South Australia")

# Interpolate and split into line segments
  interpolate_segments_as_lines <- function(df, steps = 50) {
    df %>%
      rowwise() %>%
      do({
        x_vals <- seq(.$fromX, .$X, length.out = steps)
        y_vals <- seq(.$fromY, .$Y, length.out = steps)
        position <- seq(0, 1, length.out = steps)
        
        # Construct segments
        data.frame(
          x = head(x_vals, -1),
          y = head(y_vals, -1),
          xend = tail(x_vals, -1),
          yend = tail(y_vals, -1),
          position = head(position, -1),
          FROM_NAME = .$FROM_NAME,
          TO_NAME = .$TO_NAME,
          TOTAL = .$TOTAL,
          AGE_15_34 = .$AGE_15_34,
          AGE_35_49 = .$AGE_35_49,
          AGE_50_65 = .$AGE_50_65,
          AGE_65_PLUS = .$AGE_65_PLUS
        )
      }) %>%
      ungroup()
  }
  
  # Apply interpolation
  sa_lines_segments <- interpolate_segments_as_lines(sa_final_dataset)
  
  sa_lines_segments <- sa_lines_segments %>%
    mutate(
      thickness = round(rescale(abs(TOTAL), to = c(3, 10))),
      color = rgb(
        colorRamp(c("#cc0b15ff", "#1cc00dff"))(position),
        maxColorValue = 255
      )
    )

  # Use add_segments with thickness mapped to line width
  sa_plotly <- plot_ly(height = 900, source = "South_Australia_Map") %>%
    add_sf(
    data = sa_map_data,
    fill = "#007499",
    line = list(color = "black"),
    showlegend = FALSE,
    hoverinfo = "skip"
    )

  # Optionally, you can color by direction or other variable if needed
  for (t in sort(unique(sa_lines_segments$thickness))) {
    seg_data <- sa_lines_segments %>% filter(thickness == t )
    for (g in unique(seg_data$color)) {
      seg_data_color <- seg_data %>% filter(color == g)
      if (nrow(seg_data_color) > 0) {
        sa_plotly <- sa_plotly %>%
          add_segments(
            data = seg_data_color,
            x = ~x, y = ~y, xend = ~xend, yend = ~yend,
            line = list(
              color = ~color,
              width = t
            ),
            opacity = 0.8,
            hovertext = paste0(
              "From: ", seg_data_color$FROM_NAME, "<br>",
              "To: ", seg_data_color$TO_NAME, "<br>",
              "Age 15 - 34 Migrations: <b>", seg_data_color$AGE_15_34, "</b><br>",
              "Age 35 - 49 Migrations: <b>", seg_data_color$AGE_35_49, "</b><br>",
              "Age 50 - 65 Migrations: <b>", seg_data_color$AGE_50_65, "</b><br>",
              "Age 66+ Migrations: <b>", seg_data_color$AGE_65_PLUS, "</b><br>",
              "Net Migrations: <b>", seg_data_color$TOTAL, "</b>"
            ),
            hoverinfo = "text",
            showlegend = FALSE,
            inherit = FALSE,
            yaxis="y"
          )
      }
    }
  }

  sa_plotly <- sa_plotly %>%
    layout(
    xaxis = list(title = ""),
    yaxis = list(title = "")
    )

  interpolate_segments_as_lines_inter <- function(df, steps = 50) {
    df %>%
    rowwise() %>%
    do({
      x_vals <- seq(.$fromX, .$X, length.out = steps)
      y_vals <- seq(.$fromY, .$Y, length.out = steps)
      position <- seq(0, 1, length.out = steps)
      data.frame(
      x = head(x_vals, -1),
      y = head(y_vals, -1),
      xend = tail(x_vals, -1),
      yend = tail(y_vals, -1),
      position = head(position, -1),
      group = .$group,
      thickness = .$thickness,
      SA3_NAME21 = .$SA3_NAME21,
      State = .$State,
      FinalValue = .$FinalValue,
      AGE_15_34 = .$AGE_15_34,
      AGE_35_49 = .$AGE_35_49,
      AGE_50_65 = .$AGE_50_65,
      AGE_65_PLUS = .$AGE_65_PLUS
      )
    }) %>%
    ungroup()
  }

  inter_lines_segments <- interpolate_segments_as_lines_inter(final_dataset)

  inter_hovertexts <- paste0(
    "SA3 Name: ", inter_lines_segments$SA3_NAME21, "<br>",
    "Age 15 - 34 Migrations: <b>", inter_lines_segments$AGE_15_34, "</b><br>",
    "Age 35 - 49 Migrations: <b>", inter_lines_segments$AGE_35_49, "</b><br>",
    "Age 50 - 65 Migrations: <b>", inter_lines_segments$AGE_50_65, "</b><br>",
    "Age 66+ Migrations: <b>", inter_lines_segments$AGE_65_PLUS, "</b><br>",
    "State: <b>", inter_lines_segments$State, "</b><br>",
    "Net Value: <b>", inter_lines_segments$FinalValue, "</b>"
  )

  # Build plotly map for inter-state migration
  plotly_gg_map <- plot_ly(height = 900, source = "Australia_Map") %>%
    add_sf(
      data = subset(australia_data, STE_NAME21 != "South Australia"),
      fill = "#007499",
      line = list(color = "black"),
      showlegend = FALSE,
      hoverinfo = "skip"
    ) %>%
    add_sf(
      data = subset(australia_data, STE_NAME21 == "South Australia"),
      fill = "#007499",
      line = list(color = "black"),
      showlegend = FALSE,
      hoverinfo = "skip"
    )

  groups <- c("Outgoing Migration", "Incoming Migration")
  colors <- c("Outgoing Migration" = "#cc0b15ff", "Incoming Migration" = "#1cc00dff")

  # Track if legend has been added for each group
  legend_added <- setNames(rep(FALSE, length(groups)), groups)

  for (g in groups) {
    for (t in sort(unique(inter_lines_segments$thickness))) {
    seg_data <- inter_lines_segments %>%
      filter(group == g, thickness == t)

    if (nrow(seg_data) > 0) {
      seg_hovertexts <- inter_hovertexts[which(inter_lines_segments$group == g & inter_lines_segments$thickness == t)]
      plotly_gg_map <- plotly_gg_map %>%
      add_segments(
        data = seg_data,
        x = ~x, y = ~y, xend = ~xend, yend = ~yend,
        line = list(color = colors[[g]], width = t),
        opacity = 0.7,
        hovertext = seg_hovertexts,
        hoverinfo = "text",
        name = g,
        legendgroup = g,
        showlegend = !legend_added[[g]]
      )
      legend_added[[g]] <- TRUE
    }
    }
  }

  plotly_gg_map <- plotly_gg_map %>%
    layout(
      showlegend = TRUE,
      xaxis = list(title = ""),
      yaxis = list(overlaying="y2"),
      legend = list(title = list(text = ""))
    )

  plotly_combined <- subplot(
    plotly_gg_map,
    sa_plotly,
    nrows = 1
  ) %>%
    layout(
      showlegend = TRUE,
      legend = list(
        orientation = "h",     
        x = 0.5,
        y = 0.1,
        xanchor = "center",
        yanchor = "top",
        font = list(size = 12)
      ),
      annotations = list(
        list(
          text = "<b>Inter State Migration Map</b>",
          x = 0.185,
          y = 1.035,
          xref = "paper",
          yref = "paper",
          showarrow = FALSE
        ),
        list(
          text = "<b>Intra State Migration Map</b>",
          x = 0.825,
          y = 1.035,
          xref = "paper",
          yref = "paper",
          showarrow = FALSE
        )
      )
    )

  # Plotly table
  table_plot <- plot_ly(
    source = "Table 1",
    type = "table",
    columnwidth = c(15, 10, 10, 10, 10, 10, 10, 10, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20),
    header = list(
      values = colnames(pivot_data),
      align = "center",
      line = list(color = "#000000ff"),
      font = list(color = list(
        "black",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white",
        "white"
      ), size = 12),
      fill = list(
        color = list(
          c("#ffffffff"),
          c("#6A625E"), 
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#6A625E"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333"),
          c("#333333")
        )
      ),
      height = 40
    ),
    cells = list(
      values = rbind(t(as.matrix(unname(pivot_data)))
      ),
      align = "center",
      line = list(color = "#000000ff"),
      fill = list(color = "#ffffffff"),
      font = list(color = "#000000ff", size = 12)
    )
  )

  table_plot2 <- plot_ly(
    type = "table",
    source = "Table 2",
    header = list(
        values = list(
            c("<b>Sources:</b> Demo")
        ),
        align = "left",
        font = list(family = "Arial", size = 12),
        height = 40,
        line = list(color = "rgba(0,0,0,0)") # Remove borders
    ),
    cells = list(
        line = list(color = "rgba(0,0,0,0)") # Remove borders
    ),
    domain = list(
        x = c(0, 1),
        y = c(0, 0.03)
    )
  )

  # Ensure hoverinfo is retained for all subplots by explicitly setting hoverinfo for each axis
  final_combined <- subplot(
    table_plot, plotly_combined, table_plot2,
    nrows = 3,
    heights = c(0.25, 0.7, 0.05),
    shareX = FALSE,
    shareY = FALSE,
    titleX = FALSE,
    titleY = FALSE
  ) %>%
  layout(
    annotations = list(
      list(
        text = "<b>Average Monthly Net Migration</b>",
        x = 0.5,
        y = 1.035,
        xref = "paper",
        yref = "paper",
        showarrow = FALSE,
        font = list(size = 16, color = "#000000")
      )
    )
  )
  
print(final_combined)

When using subplot() with multiple maps (from sf objects), I cannot zoom or pan into the maps, and hover text does not appear — even though it works perfectly when the map is plotted individually.

Context

  • I’ve attached all required files to reproduce the issue here.

  • The data has been modified to remove any confidential information. Values have been changed to be shareable, so please ignore any inconsistency or logical mismatches in the numbers they won’t add up and aren’t meant to.

Setup

The backend for this dashboard is in R, but it’s part of a larger architecture where R acts only as the backend, hence I am limited to using plotly (and not other libraries like leaflet or mapview).

What I Need Help With

  • Is this an existing limitation or bug in nested subplot() when used with sf objects or map traces?

  • Has anyone found a reliable workaround to retain map interactivity (zoom, pan, hover) when embedded as part of a nested subplot() layout?

What I’ve Tried

  • Using subplot() directly with add_sf() and add_trace().

  • Modifying layout options (dragmode, uirevision, geo anchoring, etc.)

  • Reviewing known issues on Plotly’s GitHub repo.

Still no success.

Summary

I’d greatly appreciate if anyone could confirm:

  • Whether this is a known issue with Plotly in R

  • If a workaround exists to restore zooming and hover functionality in nested subplots containing maps

Thanks in advance for your time and help!