Sankey Diagrams in Origin 2020

Sankey diagrams are useful for depicting the distribution and fate of some commodity of interest (energy, money, human migration, etc.) throughout a given system. Flows are represented by bands of varying thickness. Thickness is proportional to the contribution of a given pathway, to the total flow.

Figure 1. Sankey diagram depicting water and energy flows within a production process.

Despite their somewhat cartoonish appearance, Sankey diagrams are underpinned by numerical values and therefore deserve to be taken seriously as a “scientific” graph type. For some types of data, they are uniquely capable of depicting and quickly conveying an understanding of complex systems.

Sankey Diagrams are a new feature in Origin 2020, due for release sometime this in late October or early November. Users of this graph type will find that OriginLab’s implementation is both powerful and easy to manipulate, allowing for full customization of node and link colors, drag-and-drop ordering of nodes, open and loop branches, arrows at link starting points and/or endings, plus flexible labeling of links and nodes.

Additionally, Sankey diagrams are supported by many other great Origin features such as plot highlighting and datapoint tooltips, making them useful as an exploratory or interactive-presentation tool, in addition to their publication value.

Figure 2. Click on a node or link to highlight just a portion of the Sankey diagram. A floating datapoint tooltip will report information about the highlighted data.
Data Requirements, Drawing and Customization:
  • In Origin, a Sankey diagram is always constructed using three columns of data — two columns of categorical data + one column of numeric data.
  • The categorical columns are used to construct the nodes. The numeric column is used to determine the relative thickness of the link between two nodes.
  • If the two categorical columns contain a distinct set of values (i.e. no category appears in both columns), nodes will be constructed only at the outside of the plot. If there are categories which appear in both columns, then intermediary nodes are created and the diagram takes on a more complex structure.
  • The Plot Details dialog box has separate tabs labeled as Node, Link and Label, that are used to customize the Sankey diagram.
  • Link color can be set to Follow Color of Source Node, Follow Color of Target Node, as Gradient Color from Source to Target or as any color list or custom color that you prefer.

Many other customizations are possible. What follows is a sampling of Sankey diagrams that have been created with Origin 2020. Keep in mind as you view these that they are all created and customized using Origin’s point-and-click interface — No programming needed!

Figure 3. Bachelor’s Degrees by Race/Ethnicity and Field of Study.
Figure 4. Breakdown of Contracts Awarded by Government, Queensland, Australia.
Figure 5. US Energy Consumption by Sector, 2018 (Trillion BTUs)
Figure 6. Sources of contributions to major political parties and outside spending groups.

In addition to Sankey diagrams, look for many other new and exciting features when Origin 2020 is released in the Fall of 2019.  In the coming weeks, you will be able to visit and get a look at what is coming. Thanks for reading!

5 Comments on “Sankey Diagrams in Origin 2020”

  1. Hi Mike genthner
    I need to plot sankey plot, my data is five column (chr,start_pos, end_pos, gene_name, feature name) bed files at 6 development points of Drosophila. each development point share some coordinates/features with next development point. is there any way that my files read directly by code and produce sankey plot.


    1. Sankey plot accept two data arrangements:
      – One includes four columns — index value of source link, index value of target link, link values and nodes label — which is connected with a formatted JSON file
      – One includes three columns — label of source link, label of target link and link values.

      In Origin, you can press F11 to launch learning center, find Sankey examples under Categorical Special Charts category. If your data doesn’t have same structure, you need to transform the data first. Let us know if you need help transforming the data:

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