Sankey charts are a type of data visualization that use arrows to represent the flow of a data set. They are particularly useful for showing relationships and patterns in networks, such as energy usage or data flows within a system. In this guide, we will explore the power of Sankey charts and provide a step-by-step tutorial on how to create and interpret them.

What are Sankey Charts?

Sankey charts were first introduced by John Snow, a British doctor, in the 1850s to map the spread of cholera outbreaks in London. Snow used the chart to show how different areas of the city were impacted by the disease, and it quickly became a popular tool for visualizing complex networks and flows.
Today, Sankey charts are used in a variety of contexts, from energy use to data flows in complex computer systems. They are particularly useful for visualizing data with multiple sources and destinations, as well as data that has a strong directional flow.

How to Create a Sankey Chart

To create a Sankey chart, you will need to have data that includes the flow values from each source to each destination, as well as information about the width of the arrows that represent the flow. Here is a step-by-step guide on how to create a simple Sankey chart:

Step 1: Gather Your Data

Start by collecting the data you want to visualize. For a basic Sankey chart, you will need:

Source nodes (the starting points or suppliers of the flow)
Destination nodes (the receiving points or consumers of the flow)
Flow values (the amount of data or resources that flow from one node to another)

Step 2: Choose Your Data Visualization Tool

There are many tools available for creating Sankey charts, ranging from simple online tools to more advanced software like Tableau or R. For this tutorial, we will use the popular open-source data visualization library, Plotly.
You can create a Sankey chart using Plotly by following these steps:

Install Plotly by running pip install plotly in Python or brew install plotly in macOS.
Import the necessary libraries:
```
python
```
import plotly.express as px
Load your data. For this example, we will use the built-in Iris dataset that comes with Plotly:
```
python
```
df = px.data.iris()
Use the make_sankey() function to create a Sankey chart:
```
python
```
fig = px.make_sankey(
df,
node_names=[“setosa”, “versicolor”, “virginica”],
value_labels=df[“sepal_width”],
direction=1,
)
Add any necessary customizations, such as colors or labels:
```
python
```
fig.update_layout(title=”Sankey Chart Example”)
Display the chart using the show() function:
```
python
```
fig.show()

Step 3: Customize Your Chart

To make your Sankey chart more impactful and easier to understand, customize it with features such as:

Title and labels: Add a clear and concise title and labels to identify nodes and flows.
Arrow thickness: Adjust the width of the arrows to represent the flow values.
Legend: Include a legend to explain the symbols or colors used in the chart.
Annotations: Add annotations or tooltips to provide additional context or information about specific nodes or flows.

Mastering Sankey Charts: Applications and Examples

Sankey charts are useful in a variety of fields, and here are some examples of their applications and how they can be used to convey specific insights:

1. Energy Use and Efficiency

Sankey charts can help visualize the various sources and destinations of energy consumption within an organization, showing how much energy is used in different departments or services. By highlighting high-energy consuming areas, organizations can identify opportunities for energy reduction and efficiency improvements.

2. Data Flow in IT Systems

In the context of information technology, Sankey charts can represent data flows within computer systems or networks, such as website traffic, content delivery, or data processing pipelines. This visualization allows stakeholders to understand the distribution and consumption of resources, as well as identify bottlenecks or redundant flows.

3. Supply Chain Management

Sankey charts can illustrate the flow of goods, materials, or resources in supply chains, highlighting upstream suppliers and downstream customers. By analyzing the chart, businesses can optimize their supply chain logistics, streamline processes, and address potential bottlenecks.

4. Demographic Flows

Sankey charts can be used to visualize demographic flows, such as migration patterns, population movements, or changes in the age structure of a population. This can help policymakers make informed decisions regarding urban planning, healthcare, and resource allocation.

5. Network Analysis

Sankey charts aid in visualizing complex networks, such as relationships between organizations, individuals, or data sources. By analyzing the chart, network researchers can identify key nodes, patterns of interaction, and potential areas for collaboration or intervention.

Conclusion

Sankey charts are a powerful tool for visualizing complex flows and networks. Their ability to represent data in the form of arrows helps users grasp the relationships and patterns between sources, destinations, and flows more easily than with traditional charts. By mastering the creation and customization of Sankey charts, you can effectively communicate insights in a wide range of applications, from supply chain optimization to network analysis and beyond.

SankeyMaster

SankeyMaster is your go-to tool for creating complex Sankey charts . Easily enter data and create Sankey charts that accurately reveal intricate data relationships.

Unleashing the Power of Flow: A Guide to Mastering Sankey Charts