Visualizing Efficiency: The Art and Science of Sankey Charts
Sankey charts are a unique and powerful visualization tool that has found wide application in industries ranging from energy and engineering to finance and marketing. These charts, named after Mark P. Sankey, an engineer at the Stanford University School of Engineering who first used them in the 1960s, are designed to visually represent flows from one process to another, showing changes along those paths. The art and science of creating and interpreting Sankey charts are both fascinating and essential for understanding complex data sets.
Understanding Sankey Charts
At its core, a Sankey chart is a directed acyclic graph (DAG) that converts a table of inputs and outputs into a chart. It visually represents the flow of quantities from one place to another in a process or system. Each bar contains a series of linked blocks, with the widths of the blocks proportional to the relative flows or quantities of materials, energy, data, or any other resource as it moves through a system.
Art and Science of Creating Sankey Charts
The art of creating a Sankey chart involves understanding the data and translating it into a graph that effectively communicates the information. This might include selecting the right scale for the data, ensuring clear labels for flow inputs and outputs, and choosing a layout that is visually intuitive. The science, however, involves accuracy; ensuring that the relative proportions in the chart are precisely aligned with the data.
Steps in Creating a Sankey Chart
Creating a Sankey chart involves several steps, from data collection to customization.
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Data Preparation: The first step is to gather all the relevant data regarding inputs and outputs, and then normalize this data to ensure it can be accurately represented in the chart. This normalization step is crucial because it ensures that the data is correctly scaled.
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Chart Creation: In software tools designed for data visualization (such as Excel, Tableau, or Python libraries like Bokeh and matplotlib), you can input the normalized data into the software program. The software then calculates the widths of the various links based on the provided data, and creates the chart, ready for further customization.
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Customization: After creating the basic Sankey chart, you can further customize it by adding annotations, changing colors, and adjusting the chart settings to better communicate the story your data is telling.
Applications of Sankey Charts
Sankey charts are incredibly versatile in their application. Here are a few examples:
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Energy Systems: They are often used to illustrate the energy flows through a system, showing how energy is transferred from one form to another, and identifying where inefficiency occurs.
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Product Development and Manufacturing: In industries such as automotive or IT, Sankey charts can show where materials are used, and how much value is added at each stage of the manufacturing process.
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Ecological Footprint Analysis: These charts can be used to model the material flows in a community or country, illustrating how much of what type of material is imported/exported, consumed, lost, etc.
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Wealth Distribution: Sankey charts can also show the flow of capital or wealth among companies, countries, or regions, highlighting where most of a wealthy country’s wealth is concentrated.
Conclusion
Sankey charts are an invaluable tool for data visualization, particularly for showing the distribution, transformation, and flow of materials or data in systems and processes. By understanding the art and science of creating and interpreting them, individuals and organizations can make more informed decisions, optimize their processes, and communicate complex data in clear and compelling ways. As data visualization continues to evolve, Sankey charts prove their value in helping us understand the complexities of modern systems and processes.
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