A bipartite network graph visualizes relationships between two distinct sets of entities, where edges only connect nodes from different sets — never within the same set. The two node groups are arranged in separate columns or rows, making the two-mode structure immediately apparent. This layout is fundamental for understanding cross-category relationships, revealing which entities from one set are linked to which entities in the other, and exposing patterns like hubs, clusters, and isolated nodes.
#' anyplot.ai
#' network-bipartite: Bipartite Network Graph
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 92/100 | Created: 2026-09-05
library(ggplot2)
library(dplyr)
library(tidyr)
library(ragg)
set.seed(42)
# --- Theme tokens ------------------------------------------------------------
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
INK_MUTED <- if (THEME == "light") "#6B6A63" else "#A8A79F"
IMPRINT_PALETTE <- c("#009E73", "#C475FD", "#4467A3", "#BD8233",
"#AE3030", "#2ABCCD", "#954477", "#99B314")
# --- Data --------------------------------------------------------------------
# Student-course enrollment: which students registered in which courses,
# with attendance rate as the edge weight.
students <- sprintf("Student %02d", 1:16)
courses <- c("Calculus I", "Linear Algebra", "Data Structures", "Organic Chemistry",
"Cell Biology", "Macroeconomics", "Art History", "Statistics",
"Physics I", "World History")
edges <- bind_rows(lapply(students, function(s) {
chosen <- sample(courses, sample(3:5, 1))
tibble(source = s, target = chosen, weight = round(runif(length(chosen), 0.5, 1.0), 2))
}))
student_degree <- tibble(node = students) %>%
left_join(count(edges, source, name = "degree"), by = c("node" = "source")) %>%
mutate(degree = replace_na(degree, 0))
course_degree <- tibble(node = courses) %>%
left_join(count(edges, target, name = "degree"), by = c("node" = "target")) %>%
mutate(degree = replace_na(degree, 0))
# Two fixed columns, nodes ordered by degree so hubs cluster near the top.
students_pos <- student_degree %>%
arrange(desc(degree), node) %>%
mutate(x = 0, y = seq(1, 0, length.out = n()), set = "Students")
courses_pos <- course_degree %>%
arrange(desc(degree), node) %>%
mutate(x = 1, y = seq(1, 0, length.out = n()), set = "Courses")
nodes <- bind_rows(students_pos, courses_pos)
edge_coords <- edges %>%
left_join(students_pos %>% select(node, x, y), by = c("source" = "node")) %>%
rename(x_start = x, y_start = y) %>%
left_join(courses_pos %>% select(node, x, y), by = c("target" = "node")) %>%
rename(x_end = x, y_end = y)
# --- Plot ----------------------------------------------------------------
p <- ggplot() +
geom_curve(
data = edge_coords,
aes(x = x_start, y = y_start, xend = x_end, yend = y_end, alpha = weight),
color = INK_MUTED, linewidth = 0.35, curvature = 0.25, ncp = 8
) +
geom_point(data = nodes, aes(x = x, y = y, size = degree, color = set)) +
geom_text(
data = students_pos, aes(x = x, y = y, label = node),
hjust = 1, nudge_x = -0.04, size = 3.1, color = INK
) +
geom_text(
data = courses_pos, aes(x = x, y = y, label = node),
hjust = 0, nudge_x = 0.04, size = 3.1, color = INK
) +
scale_color_manual(values = c("Students" = IMPRINT_PALETTE[1], "Courses" = IMPRINT_PALETTE[2]),
name = NULL) +
scale_size_continuous(range = c(3, 9), guide = "none") +
scale_alpha_continuous(range = c(0.12, 0.75), guide = "none") +
coord_cartesian(xlim = c(-0.55, 1.55), ylim = c(-0.05, 1.05), clip = "off") +
labs(
title = "network-bipartite · r · ggplot2 · anyplot.ai",
caption = "Node size encodes number of connections; edge opacity encodes attendance rate"
) +
guides(color = guide_legend(override.aes = list(size = 5))) +
theme_void(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
plot.title = element_text(color = INK, size = 15, face = "bold", hjust = 0.5, margin = margin(b = 8)),
plot.caption = element_text(color = INK_MUTED, size = 8, hjust = 0.5, margin = margin(t = 10)),
legend.position = "top",
legend.text = element_text(color = INK_SOFT, size = 8),
legend.key = element_rect(fill = PAGE_BG, color = NA),
plot.margin = margin(t = 20, r = 50, b = 20, l = 50)
)
# --- Save --------------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/network-bipartite/ggplot2/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "network-bipartite",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/network-bipartite/r/ggplot2",
"hub": "https://anyplot.ai/network-bipartite",
"code_json": "https://api.anyplot.ai/specs/network-bipartite/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/network-bipartite",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/network-bipartite/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/network-bipartite/r/ggplot2/plot-dark.png",
"quality_score": 92.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Bipartite Network Graph on anyplot.ai.