R: Plotly Sankey diagram position of nodes cannot be set correctly

3 min read 04-10-2024

R: Plotly Sankey diagram position of nodes cannot be set correctly

Taming the Flow: Mastering Node Positioning in Plotly Sankey Diagrams with R

Sankey diagrams are powerful tools for visualizing flows and relationships between different entities. In R, the plotly package offers a convenient way to create these diagrams, but sometimes, achieving the desired node positioning can feel like a game of tug-of-war. This article explores a common challenge - inability to precisely position nodes in Plotly Sankey diagrams - and provides practical solutions for regaining control over your visualization.

The Struggle: Trying to Tame the Flow

Imagine you're working on a project that involves analyzing data flow through different stages of a process. You've chosen a Sankey diagram to illustrate these connections, but when you use the plotly::plot_ly function to create your diagram, the nodes appear clustered and unorganized. You've tried to adjust their positions using node.x and node.y parameters, but they seem to stubbornly resist your efforts.

library(plotly)

# Sample data for the Sankey diagram
df <- data.frame(
  source = c("A", "A", "B", "B", "C", "C", "D", "D"),
  target = c("B", "C", "C", "D", "D", "E", "E", "F"),
  value = c(10, 15, 20, 25, 30, 35, 40, 45)
)

# Creating the Sankey diagram
plot_ly(
  type = "sankey",
  domain = list(x = c(0, 1), y = c(0, 1)),
  orientation = "h",
  node = list(
    label = c("A", "B", "C", "D", "E", "F"),
    pad = 10,
    thickness = 15,
    line = list(color = "black", width = 0.5)
  ),
  link = list(
    source = c(0, 0, 1, 1, 2, 2, 3, 3),
    target = c(1, 2, 2, 3, 3, 4, 4, 5),
    value = df$value
  )
)

This code generates a basic Sankey diagram, but you'll likely find that the node arrangement isn't what you'd prefer. The node.x and node.y parameters, while seemingly promising, often lead to inconsistent and unpredictable node placement.

Gaining Control: Unveiling the Secrets of Node Positioning

Here's the key insight: Plotly Sankey diagrams prioritize maintaining the visual flow of connections. This means that while you can specify desired node positions, the algorithm might adjust them to ensure the links appear clean and legible. To overcome this, we need a two-pronged approach:

Understanding the Flow: Analyze the connections within your data. Identify key nodes that act as hubs or starting/ending points. Understanding these relationships will help you prioritize the positions of these crucial nodes.
Strategic Placement: Rather than relying solely on node.x and node.y, utilize a combination of ordering and grouping.
- Ordering: By arranging your node labels (node.label) in the order you want them to appear, you can influence their horizontal positioning.
- Grouping: Utilize the node.group parameter to create visual clusters. Nodes belonging to the same group will be arranged closer together, allowing you to influence their vertical positioning.

Example: Crafting a More Controllable Diagram

Let's modify our example code to showcase these strategies:

library(plotly)

# Sample data with node groups
df <- data.frame(
  source = c("A", "A", "B", "B", "C", "C", "D", "D"),
  target = c("B", "C", "C", "D", "D", "E", "E", "F"),
  value = c(10, 15, 20, 25, 30, 35, 40, 45),
  source_group = c("Group 1", "Group 1", "Group 1", "Group 1", "Group 2", "Group 2", "Group 2", "Group 2")
)

# Creating the Sankey diagram with controlled positioning
plot_ly(
  type = "sankey",
  domain = list(x = c(0, 1), y = c(0, 1)),
  orientation = "h",
  node = list(
    label = c("A", "B", "C", "D", "E", "F"), # Order determines horizontal placement
    pad = 10,
    thickness = 15,
    line = list(color = "black", width = 0.5),
    group = c("Group 1", "Group 1", "Group 2", "Group 2", "Group 2", "Group 3") # Group nodes
  ),
  link = list(
    source = c(0, 0, 1, 1, 2, 2, 3, 3),
    target = c(1, 2, 2, 3, 3, 4, 4, 5),
    value = df$value
  )
)

By strategically ordering the labels and grouping nodes, we achieve a more organized and aesthetically pleasing Sankey diagram.

Further Exploration: Unlocking Advanced Customization

Adjusting Link Appearance: Customize the appearance of links using parameters like link.color, link.width, and link.opacity for enhanced visual clarity.
Interactive Sankey Diagrams: Explore plotly::event_register to enable user interactions, such as highlighting nodes and links on hover.

Conclusion: Mastering the Flow, One Node at a Time

While the Sankey diagram's inherent flow prioritization might initially seem challenging, by understanding the underlying principles and using strategic node ordering and grouping, you can effectively manage their positioning and create informative, visually appealing diagrams. The journey to mastering these diagrams is an iterative process, so don't hesitate to experiment and refine your visualizations until they effectively convey your message.