Creating a Sankey chart involves understanding the fundamental concepts and techniques to design visually appealing data visualization. In this article, we’ll explore the basics of a Sankey chart, its characteristics, and its applications in various fields.

What is a Sankey chart?
A Sankey chart, also known as a directed graph in the field of economics, is a type of network diagram that depicts the flow of data in a specific direction. In this diagram, each object (data flow) is represented by a line segment, and the direction of the line segment represents the flow’s direction.

In a Sankey chart, we often use flow diagrams to visualize the relationship between two or more categories, such as income and expenses, and the data associated with them. A Sankey chart can also be used to visualize the flow of natural resources or resources such as water, air, or electrical power.

Sankey charts are not only useful in the field of economics but also in other fields such as engineering, healthcare, and transportation, where data flows are frequently encountered.

Creating a Sankey chart
To create a Sankey chart, we need to follow these steps:

1. Determine the number of input and output categories.
   For example, if we have two categories (in: water, out: soil), we need two lines, one for inputs and one for outputs.

2. Create the layout using a specific format.
   Sankey charts are usually designed with a specific layout that creates a clear and visually appealing diagram. There are several types of layouts, but one commonly used layout is the flow diagram, where the diagrams are positioned in a flow pattern. For example, the input line is displayed on the input node, and the output line is displayed on the output node. Other layouts may include diagonal lines or multiple lines per node.

3. Fill in the data.
   Once the diagram is created, we need to fill in the data by specifying the flow direction for each category. This can be done manually or through the use of software tools that can automatically fill the data. The direction of the flow can be specified manually or automatically using algorithms.

Applications
Sankey diagrams can be used to visualize the relationships between data categories, show the flow of specific resources, and compare different variables. Here are some practical applications of Sankey diagrams:

• In economics, Sankey diagrams can be used to represent the flow of data related to income, expenses, and investments.
• In transportation, Sankey diagrams can be used to represent the flow of traffic, including passenger flow, truck flow, and container flow.
• In healthcare, Sankey diagrams can be used to track patient flow, including admissions and discharges.
• In engineering, Sankey diagrams can be used to display the flow of materials, such as water, in a building project.

Creative Ways to Create a Sankey Chart
Creating a Sankey chart requires the use of specialized software tools, but you can also create your Sankey chart visually without using software. Here are some creative ways to create a Sankey chart:

• Use symbols, such as arrows or circles, to represent the categories and data flow.
• Use different shades or colors to represent different categories or different flows.
• Use different types of lines to represent different categories or different flows.
• Add labels to each category and data flow to clarify the meaning and purpose of each item.

In conclusion, creating a Sankey chart requires a good understanding of the fundamentals of network diagrams and data flow visualization. With the help of a specific set of tools, a visual representation of the data can be created, making it easier to understand and compare different variables. By understanding the characteristics of the diagrams and the different applications they can be used in, you can use these diagrams to make better sense of the data and communicate your findings more effectively.

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.