Explicitly Set Level in Multi-Level Sankey using Plotly: A Step-by-Step Guide
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Explicitly Set Level in Multi-Level Sankey using Plotly: A Step-by-Step Guide

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Are you tired of dealing with messy and unclear Sankey diagrams? Do you want to take your data visualization game to the next level (pun intended)? Look no further! In this article, we’ll dive into the world of multi-level Sankey diagrams using Plotly and explore how to explicitly set levels to create stunning and informative visualizations.

What is a Sankey Diagram?

A Sankey diagram is a type of flow-based visualization that’s used to depict the magnitude of flow between nodes in a process. It’s commonly used in energy, material, and cost flow analysis. Sankey diagrams consist of nodes (representing the process steps) and edges (representing the flows between nodes). The width of the edges is proportional to the magnitude of the flow.

Multi-Level Sankey Diagrams: The Next Level

Multi-level Sankey diagrams take the classic Sankey to the next level (again, pun intended) by allowing for multiple levels of nodes. This enables us to visualize more complex processes and relationships between nodes. However, with great power comes great complexity. Explicitly setting levels in multi-level Sankey diagrams can be a challenge, but fear not, dear reader, for we’re about to tackle this challenge head-on!

Why Explicitly Set Levels?

Explicitly setting levels in multi-level Sankey diagrams is crucial for creating clear and informative visualizations. By doing so, you can:

  • Clearly distinguish between different levels of nodes
  • Highlight the relationships between nodes across different levels
  • Create a more organized and structured visualization
  • Improve the overall aesthetic appeal of your Sankey diagram

Preparing Your Data

Before we dive into the world of Plotly, let’s prepare our data. For this example, we’ll use a simple dataset representing energy flows between different stages of a power plant.

Source Target Value Level
Fuel Boiler 100 0
Boiler Turbine 80 1
Turbine Generator 60 2
Generator Transformer 50 3

In this dataset, we have four columns: Source, Target, Value, and Level. The Level column is where we’ll explicitly set the level for each node.

Creating the Multi-Level Sankey Diagram

import plotly.graph_objects as go

fig = go.Figure(data=[go.Sankey(
    node=dict(
      pad=15,
      thickness=20,
      line=dict(color="black", width=0.5),
      label=["Fuel", "Boiler", "Turbine", "Generator", "Transformer"],
      color=["blue", "orange", "green", "red", "yellow"],
      level=[0, 1, 2, 3, 3]  # Explicitly set levels
    ),
    link=dict(
      source=[0, 1, 2, 3],  # indices correspond to labels
      target=[1, 2, 3, 4],
      value=[100, 80, 60, 50]
    )
)])

fig.update_layout(title_text="Multi-Level Sankey Diagram", font_size=10)

fig.show()

This code creates a basic Sankey diagram with five nodes and four links. We’ve explicitly set the levels for each node using the level parameter in the node dictionary.

Customizing Your Sankey Diagram

Adding Node Colors

We can add node colors to differentiate between different levels. Let’s add a color scale to our nodes based on their level.

node=dict(
  ...
  color=["blue" if level == 0 else "orange" if level == 1 else "green" if level == 2 else "red" if level == 3 else "yellow" for level in [0, 1, 2, 3, 3]]
  ...
)

Adding Edge Colors

We can also add edge colors to highlight the relationships between nodes. Let’s add a color scale to our edges based on their value.

link=dict(
  ...
  color=["gray" if value < 50 else "orange" if value < 80 else "green" if value < 100 else "blue" for value in [100, 80, 60, 50]]
  ...
)

Tips and Tricks

  1. Use a consistent color scheme: Choose a color scheme that's consistent throughout your Sankey diagram to create a cohesive look.
  2. Experiment with node and edge shapes: Use different node and edge shapes to differentiate between different levels or categories.
  3. Add hover text and labels: Use hover text and labels to provide additional information about each node and edge.
  4. Customize the layout: Experiment with different layout options to find the one that best suits your data.

Conclusion

References

Here are 5 Questions and Answers about "Explicitly set Level in Multi level Sankey using Plotly" in English language, written in a creative voice and tone, and formatted in HTML:

Frequently Asked Question

Get ready to dive into the world of Plotly and master the art of creating stunning Sankey diagrams!

Q1: What is a Sankey diagram, and why do I need to set levels explicitly?

A Sankey diagram is a flow-based visualization that represents the magnitude of flow between nodes. Setting levels explicitly in a multi-level Sankey diagram allows you to control the order and organization of your nodes, making it easier to convey meaningful insights from your data. By default, Plotly assigns levels automatically, but explicit control gives you the power to customize your visualization and communicate your findings more effectively.

Q2: How do I specify the levels in a Sankey diagram using Plotly?

To explicitly set levels in a Sankey diagram using Plotly, you need to define a `node` dictionary with a `level` key for each node. The `level` value should be an integer that represents the level at which the node should be placed. For example, `node=dict(label=['A', 'B', 'C'], level=[0, 1, 2])` would place nodes A, B, and C at levels 0, 1, and 2, respectively.

Q3: Can I have multiple nodes at the same level in a Sankey diagram?

Yes, you can have multiple nodes at the same level in a Sankey diagram. In fact, that's what makes Sankey diagrams so powerful for visualizing complex flow relationships. When you assign the same `level` value to multiple nodes, they will be placed at the same level in the diagram. Just be sure to adjust the `x` and `y` coordinates of the nodes to avoid overlap and ensure a clear visualization.

Q4: How do I adjust the spacing between levels in a Sankey diagram?

To adjust the spacing between levels in a Sankey diagram, you can use the `nodepad` property in the `layout` dictionary. `nodepad` sets the padding between nodes in the x-direction, which effectively controls the spacing between levels. For example, `layout=dict(nodepad=20)` would increase the spacing between levels by 20 pixels.

Q5: What are some best practices for designing an effective Sankey diagram?

When designing an effective Sankey diagram, remember to keep your visualization simple and focused on the key insights you want to communicate. Use clear and concise labels, and consider using colors to differentiate between flows or highlight important patterns. Also, be mindful of the ordering of your nodes and the flow directions to ensure that your diagram is easy to follow and understand.

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