Sankey charts are a powerful type of data visualization that effectively showcases flows and connections between different categories or nodes. They are particularly useful when presenting complex systems, such as energy consumption, material flow in production processes, or data traffic on the internet, as they allow for a detailed view of the movement and distribution of resources or entities. In this article, we will take a deep dive into the creation and application of Sankey charts, exploring their benefits and the steps involved in building these impactful visualizations.

Benefits of Sankey Charts

Sankey charts offer several advantages over traditional line or bar charts, making them an indispensable tool in the visualization arsenal. Here are some key benefits:

1. Flow Visualization: Sankey charts excel at depicting how quantities move from one category to another. This makes it easier to understand the direction and magnitude of relationships between different entities.

2. Complex Systems Simplification: They help in visualizing complex systems, showing not only which categories are connected but also the proportional sizes of these connections, revealing patterns that might be obscured in simpler charts.

3. Hierarchical Structure Display: Sankey diagrams can show the hierarchical structure of data flows, making it easier to analyze nested data categories and understand the flow at multiple levels.

4. Color Coding: The ability to use color coding allows for quick identification of different flows or categories, enhancing readability and making patterns within the data more apparent.

5. Engagement and Appeal: Sankey charts are visually engaging, making complex data more accessible to a broader audience and enhancing communication and understanding.

How to Create a Sankey Chart

While any data visualization tool can be used to create a Sankey chart, tools like Tableau, Microsoft Power BI, and Python libraries such as Plotly and Matplotlib offer specific functionalities tailored for this type of chart. Here’s a step-by-step guide using Python with Plotly, a library known for its flexibility and interactive capabilities:

Step 1: Data Preparation

First, ensure your data is in the correct format. Sankey charts require two main datasets: source and target for the nodes that are connected, and value for the size of the flow between these nodes. Your data might look something like this:

“`python
import pandas as pd

data = {
‘source’: [‘Customer’, ‘Production’, ‘Storage’],
‘target’: [‘Retail’, ‘End Use’],
‘value’: [100, 200, 300]
}
df = pd.DataFrame(data)
“`

Step 2: Setting Plotly

Next, use Plotly Express to configure the chart:

“`python
import plotly.express as px

fig = px.sunburst(df, path=[‘source’, ‘target’], values=’value’,
title=’Sankey Chart Example’,
colorcontinuousscale=px.colors.sequential.Plasma)
“`

Step 3: Enhancements

Customize the chart to your needs. Adjust colors, node labels, and tooltips to make the chart more informative and appealing:

python
fig.update_traces(textinfo='label+value')
fig.update_layout(
width=800,
height=600,
margin=dict(l=50, r=50, b=100, t=100),
showlegend=False
)


Step 4: Display the Chart

Finally, display or export the chart:

python
fig.show()


Applications of Sankey Charts

Sankey charts find applications across various fields:

• Energy Systems: Analyzing energy consumption within buildings or across different geographical locations.
• Economic Flows: Understanding trade relations, financial transactions, or value chains.
• Website Analytics: Visualizing user navigation patterns on websites or app usage.
• Environmental Science: Tracking flows of pollution, water cycles, or urban waste management.
• Supply Chain Analysis: Mapping the movement of products from suppliers to customers.

Conclusion

Sankey charts are a versatile tool that enhances data comprehension by visualizing complex flows and connections in a clear, engaging manner. Their ability to represent hierarchical data and show proportional relationships makes them invaluable in sectors ranging from business and finance to environment and science. By following the steps outlined above, anyone can create impactful Sankey charts that effectively communicate their data’s story.

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