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feat(ggplot2): implement flowmap-origin-destination (#7504)
## Implementation: `flowmap-origin-destination` - r/ggplot2 Implements the **r/ggplot2** version of `flowmap-origin-destination`. **File:** `plots/flowmap-origin-destination/implementations/r/ggplot2.R` **Parent Issue:** #3765 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/26154296171)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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‎plots/flowmap-origin-destination/implementations/r/ggplot2.R‎

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#' anyplot.ai
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#' flowmap-origin-destination: Origin-Destination Flow Map
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#' Library: ggplot2 3.5.1 | R 4.4.1
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#' Quality: 81/100 | Created: 2026-05-20
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library(ggplot2)
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library(dplyr)
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library(maps)
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library(ragg)
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set.seed(42)
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# Theme tokens
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THEME <- Sys.getenv("ANYPLOT_THEME", "light")
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PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
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ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
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INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
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INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
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OKABE_ITO <- c("#009E73", "#D55E00", "#0072B2", "#CC79A7",
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"#E69F00", "#56B4E9", "#F0E442")
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# World basemap polygons for geographic context
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world <- map_data("world")
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# Major global air hub coordinates and IATA codes
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airports <- data.frame(
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name = c("New York", "London", "Paris", "Dubai", "Tokyo",
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"Singapore", "Sydney", "Hong Kong", "Amsterdam", "Frankfurt"),
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code = c("NYC", "LHR", "CDG", "DXB", "TYO",
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"SIN", "SYD", "HKG", "AMS", "FRA"),
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lat = c(40.64, 51.47, 49.00, 25.25, 35.55,
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1.35, -33.95, 22.31, 52.31, 50.03),
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lon = c(-73.78, -0.45, 2.55, 55.36, 139.78,
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103.99, 151.18, 113.92, 4.76, 8.57),
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region = c("Americas", "Europe", "Europe", "Middle East", "Asia Pacific",
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"Asia Pacific", "Asia Pacific", "Asia Pacific", "Europe", "Europe"),
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stringsAsFactors = FALSE
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)
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# Synthetic international air passenger flows (millions per year)
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flows_raw <- data.frame(
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origin = c("New York", "New York", "New York", "London", "London",
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"London", "Dubai", "Dubai", "Dubai", "Singapore",
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"Singapore", "Singapore", "Tokyo", "Frankfurt", "Amsterdam"),
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dest = c("London", "Paris", "Dubai", "Dubai", "Tokyo",
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"Amsterdam", "Singapore", "Frankfurt", "Tokyo", "Hong Kong",
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"Sydney", "Tokyo", "Hong Kong", "Amsterdam", "Paris"),
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flow = c(4.2, 2.8, 3.6, 6.5, 3.1, 2.5, 5.8, 3.4, 2.6, 4.7,
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2.3, 3.2, 5.1, 3.8, 2.9),
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stringsAsFactors = FALSE
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)
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# Join origin and destination coordinates
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flows <- flows_raw |>
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left_join(airports[, c("name", "lat", "lon", "region")],
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by = c("origin" = "name")) |>
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rename(origin_lat = lat, origin_lon = lon, origin_region = region) |>
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left_join(airports[, c("name", "lat", "lon")],
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by = c("dest" = "name")) |>
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rename(dest_lat = lat, dest_lon = lon)
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region_colors <- c(
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"Americas" = OKABE_ITO[1],
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"Europe" = OKABE_ITO[2],
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"Middle East" = OKABE_ITO[3],
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"Asia Pacific" = OKABE_ITO[4]
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)
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# Manual label nudges to spread the dense European cluster
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airports$nudge_x <- c(-8, -11, -11, 4, 4, 4, 4, 4, -11, 3)
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airports$nudge_y <- c( 2, 4, -3, 2, 2, 2, -3, 2, 1, -4)
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p <- ggplot() +
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geom_polygon(
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data = world,
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aes(x = long, y = lat, group = group),
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fill = NA,
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color = INK_SOFT,
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linewidth = 0.15
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) +
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geom_curve(
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data = flows,
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aes(
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x = origin_lon, y = origin_lat,
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xend = dest_lon, yend = dest_lat,
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color = origin_region,
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linewidth = flow
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),
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curvature = -0.3,
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alpha = 0.65,
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arrow = arrow(length = unit(0.006, "npc"), type = "open")
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) +
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geom_point(
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data = airports,
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aes(x = lon, y = lat, fill = region),
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shape = 21,
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color = PAGE_BG,
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size = 3.5,
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stroke = 0.8
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) +
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geom_text(
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data = airports,
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aes(x = lon + nudge_x, y = lat + nudge_y, label = code),
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color = INK,
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size = 2.5,
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fontface = "bold"
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) +
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scale_color_manual(values = region_colors, name = "Origin Region") +
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scale_fill_manual(values = region_colors, name = "Origin Region") +
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scale_linewidth_continuous(range = c(0.4, 2.8), name = "Flow (M pax/yr)") +
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coord_cartesian(xlim = c(-100, 165), ylim = c(-40, 65)) +
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labs(
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title = "Global Air Passenger Flows · flowmap-origin-destination · r · ggplot2 · anyplot.ai",
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subtitle = "LHR–DXB is the busiest corridor at 6.5M pax/yr",
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x = "Longitude", y = "Latitude"
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) +
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theme_minimal(base_size = 8) +
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theme(
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plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
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panel.background = element_rect(fill = PAGE_BG, color = NA),
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panel.grid.major = element_line(color = INK_SOFT, linewidth = 0.1),
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panel.grid.minor = element_blank(),
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axis.text = element_text(color = INK_SOFT, size = 7),
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axis.title = element_text(color = INK_SOFT, size = 8),
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axis.ticks = element_blank(),
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plot.title = element_text(color = INK, size = 12, face = "bold",
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margin = margin(b = 4)),
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plot.subtitle = element_text(color = INK_SOFT, size = 8,
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margin = margin(b = 6)),
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legend.background = element_rect(fill = ELEVATED_BG, color = INK_SOFT,
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linewidth = 0.3),
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legend.text = element_text(color = INK_SOFT, size = 7),
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legend.title = element_text(color = INK, size = 8),
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legend.key = element_rect(fill = NA, color = NA),
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legend.position = "right",
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plot.margin = margin(t = 8, r = 8, b = 8, l = 8)
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) +
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guides(
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fill = guide_legend(order = 1),
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color = guide_legend(order = 1),
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linewidth = guide_legend(order = 2)
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)
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ggsave(
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filename = sprintf("plot-%s.png", THEME),
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plot = p,
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device = ragg::agg_png,
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width = 8,
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height = 4.5,
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units = "in",
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dpi = 400
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)

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