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Demo

Irene-Sankey Demo

The output of the plot_irene_sankey_diagram and traverse_sankey_flow function provides three structured components that represent the flow of data for generating a Sankey diagram. Here’s what each component looks like:

Demo plot

The input dataframe input_df for this demo:

country industry field
NL Technology Software
NL Finance Banking
NL Healthcare Pharmaceuticals
DE Automotive Car Manufacturing
DE Engineering Mechanical Engineering
FR Technology Software
FR Agriculture Crop Science
FR Healthcare Medical Devices
US Manufacturing Electronics
US Technology AI & Robotics
US Finance Investment Banking

This dataframe that captures the flow relationships in the input dataframe df. It consists of five columns

  • source represents the label of the starting node for each flow.
  • target represents the label of the destination node for each flow.
  • value contains the count the records in each flow, indicating the weight of the connection from source to target.
  • source_idx represents the index of the starting node for each flow.
  • target_idx represents the index of the destination node for each flow.

flow_df is the first output component in this demo:

source target value source_idx target_idx
Root DE 2 0 8
Root FR 3 0 13
Root NL 3 0 1
Root US 3 0 17
DE Automotive 1 8 9
DE Engineering 1 8 11
FR Agriculture 1 13 14
FR Healthcare 1 13 6
FR Technology 1 13 2
NL Finance 1 1 4
NL Healthcare 1 1 6
NL Technology 1 1 2
US Finance 1 17 4
US Manufacturing 1 17 18
US Technology 1 17 2
Automotive Car Manufacturing 1 9 10
Engineering Mechanical Engineering 1 11 12
Agriculture Crop Science 1 14 15
Healthcare Medical Devices 1 6 16
Technology Software 1 2 3
Finance Banking 1 4 5
Healthcare Pharmaceuticals 1 6 7
Technology Software 1 2 3
Finance Investment Banking 1 4 21
Manufacturing Electronics 1 18 19
Technology AI & Robotics 1 2 20

Note

This component is required to work directly with Plotly’s Sankey diagram functions.

This dictionary maps each unique node (e.g., country, industry, or field) to an index:

{
    'Root': 0, 
    'NL': 1, 
    'Technology': 2, 
    'Software': 3, 
    'Finance': 4, 
    'Banking': 5, 
    'Healthcare': 6, 
    'Pharmaceuticals': 7, 
    'DE': 8, 
    'Automotive': 9, 
    'Car Manufacturing': 10, 
    'Engineering': 11, 
    'Mechanical Engineering': 12, 
    'FR': 13, 
    'Agriculture': 14, 
    'Crop Science': 15, 
    'Medical Devices': 16, 
    'US': 17, 
    'Manufacturing': 18, 
    'Electronics': 19, 
    'AI & Robotics': 20, 
    'Investment Banking': 21
}

Note

This component is required to work directly with Plotly’s Sankey diagram functions.

This dictionary containing lists of indices that define the connections between nodes, formatted to work directly with Plotly’s Sankey diagram functions. It has three keys:

  • source A list of indices from node_map that represent the starting point of each flow.
  • target A list of indices from node_map representing the end point of each flow.
  • value A list of values matching each connection, indicating the flow strength.
{
    'source': [0, 0, 0, 0, 8, 8, 13, 13, 13, 1, 1, 1, 17, 17, 17, 9, 11, 14, 6, 2, 4, 6, 2, 4, 18, 2], 
    'target': [8, 13, 1, 17, 9, 11, 14, 6, 2, 4, 6, 2, 4, 18, 2, 10, 12, 15, 16, 3, 5, 7, 3, 21, 19, 20], 
    'value': [2, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
}

How to Use

Once the Irene-Sankey package is installed, you can use it in your projects. Here’s the code of the demo:

irene_sankey_demo.py
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import pandas as pd
from irene_sankey.core.traverse import traverse_sankey_flow
from irene_sankey.plots.sankey import plot_irene_sankey_diagram

# Sample data to test the functionality
input_df = pd.DataFrame(
    {
        "country": ["NL","NL","NL","DE","DE","FR","FR","FR","US","US","US"],
        "industry": [
            "Technology","Finance","Healthcare",
            "Automotive","Engineering",
            "Technology","Agriculture","Healthcare",
            "Manufacturing","Technology","Finance"],
        "field": [
            "Software","Banking","Pharmaceuticals",
            "Car Manufacturing","Mechanical Engineering",
            "Software","Crop Science","Medical Devices",
            "Electronics","AI & Robotics","Investment Banking"],
    }
)

# Generate source-target pair, node map and link for Sankey diagrams
flow_df, node_map, link = traverse_sankey_flow(input_df, ["", "country", "industry", "field"])

# Plot Sankey diagram 
fig = plot_irene_sankey_diagram(node_map, link, title = "Irene-Sankey Demo", node_config={
        "pad": 10,
        "line": dict(color="black", width=1),
    }
)
fig.show()

Tip

You can use node_map and link with your own Plotly’s Sankey diagram functions.

Thank you for exploring our demo! We hope this example has given you a clear understanding of how to utilize our package and integrate its features into your projects. Whether you're just getting started or diving deeper, our goal is to make your experience as seamless and productive as possible.

Happy coding!