Creates a Sankey diagram showing the flows between different values of variables. It is generally advisable to view only a small number of variables. Please see the Sankey articles on our blog examples of different how to set up data for Sankey diagrams.

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Example

Object Inspector Options

The following is an explanation of the options available in the Object Inspector for this specific visualization. Refer to Visualization Options for general chart formatting options.

• 5: Comparing Sankey diagram tools. Other cool examples of Sankey diagrams. Our Energy System, The National Academy of Sciences This interactive Sankey diagram estimates the amount of energy used within the United States organized by the sources from the energy is provided, to which sectors they serve, and the amount used vs.
• This opens new possibilities to integrate Sankey diagrams in other software solutions, such as e.g. Energy management software. Export Sankey diagrams as image file After creating your diagram, you can export it as an image file, to show it in a report or to include it in a PowerPoint presentation.

Sankey diagram software The Energy Management Register Sankey Diagram – Everything you need to know - My Chart Guide 8 Excel Flow Chart Template - Excel Templates - Excel Templates. A Sankey diagram depicts flows of any kind, where the width of each flow pictured is based on its quantity. Sankey diagrams are very good at showing particular kinds of complex information -Where money came from & went to (budgets, contributions) Flows of energy from source to destination; Flows of goods from place to place.

Inputs

DATA SOURCE

There are three options for inserting table into a Sankey diagram:

Input table A table with each row describing a set of linked categories.

Variables Categorical variables from a Data set.

Paste or type data Enter a table with each row describing a set of linked categories.

Max. categories The maximum number of categories to display for each variable.

FILTERS & WEIGHT

Weight A dropdown that takes a numeric variable to control the size of each link. This option is only available if the Variables data source is used. Otherwise, use the checkbox last column contains weights.

Chart

APPEARANCE

Links colored by

None: all links are shown in grey.

Source: links are shown in the same color as the source node (left)

Target: links are shown in the same color as the target node (right)

First variable: similar to Source but nodes will also be the same color as nodes they are linked to on the left. If there are multiple such nodes, then the color will be taken from the node which is linked with the largest weight.

Last variable: similar to First variable, but using the color of the Target node, and looking at downstream links.

Variables share common values If the same colors should be used for each variable in the Sankey diagram.

Node colors / Node and link colors Customize colors of the nodes.

Node width Controls width of the nodes.

Vertical spacing between nodes Controls padding between nodes of the same variable.

Order nodes to reduce overlap The vertical positions of the nodes are automatically adjusted to reduce the overlap between links. When this is turned off, nodes are positioned in the order they occur in the data.

Place right-most nodes at the edge Force the nodes to fill up the right-edge of the widget. The node labels in the last column will then be placed to the left of the node.

LABELS

Font family Font family of node labels.

Font size Font size of node labels.

Include variable in node label Prefix node label with the variable name or label.

Include counts in node label Append node label with the number of observations in each category.

Include percentages in node label Append node label with the percentages of each category.

Variable names Displays Variable Names in the node labels if the Variables data source is used.

Tidy labels Extract common prefixes from the node labels.

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Label maximum length Number of characters in the node label before it is truncated. Truncated labels will be indicated with an ellipsis. No truncation is applied to numeric variables.

HOVERTEXT

Show percentages instead of counts Show percentages instead of counts in the hovertext (tooltips) for nodes and links.

Acknowledgements

Uses on a variant of the networkD3 htmlwidget, created by Kent Russell.

Technical details

• An error will occur if more than 20 variables are selected. It is generally advisable to show a relatively small number (e.g., 4 or 5).
• Although the sankey diagram in this example shows flows between different values of variables, sankey diagrams can be used to show many other types of flows (e.g., migration patterns, regression trees, and energy flows (see https://christophergandrud.github.io/networkD3/).

Code

This post is part of a series of articles written by 2017 Summer of Maps Fellows. Azavea’s Summer of Maps Fellowship Program provides impactful pro bono spatial analysis for nonprofits, while fellows benefit from Azavea mentors’ expertise. To see more blog posts about Summer of Maps, click here.

One of the non-profits I am working with this summer is The Common Market, a distributor of regional food from sustainable farms that targets underserved communities. The main datasets I am utilizing for this spatial analysis project offer detailed accounts of each Common Market transaction (from 2014 to 2017) for both of the regions the organization serves – the Mid-Atlantic and Georgia. These data offer a great deal of information about the “flow of food” from farmers to Common Market customers. While searching for ways to visualize the vendor to customer network, I came across Sankey diagrams – which prove to be ideal for these type of datasets.

What is a Sankey diagram?

A Sankey diagram visualizes the proportional flow between variables (or nodes) within a network. The term “alluvial diagram” is generally used interchangeably. However, some argue that an alluvial diagram visualizes the changes in the network over time as opposed to across different variables.

Irish-born engineer Matthew H.P.R. Sankey gave the diagrams their name. A member of the Royal Engineers and perhaps bearer of too many initials, Sankey first presented his diagram depicting the energy flow of steam engines in the Minutes of Proceedings of the Institution of Civil Engineers. In Sankey’s diagram, he visualizes the differences between an actual steam plant and an ideal steam plant. (Note the links between the nodes indicate heat loss. The actual steam plant shows that there is proportionally more heat loss compared to the idealized steam plant.) His flow diagram caught the attention of some renowned engineers, who later deemed such visual as a “Sankey diagram.”

_{Fig. 1: Sankey’s original diagram found in his article The Thermal Efficiency of Steam-Engines (1898).}

Though this particular type of flow diagram bears Sankey’s name, he was not the first one to conceptualize it. French civil engineer Charles Joseph Minard created a flow diagram of the French invasion of Russia, a failed effort by Napoleon and his troops to defeat the Russian army. In this diagram, the audience can see the number of Napoleon’s troops decreasing as they advance towards Russia into the winter (indicated by the light brown line). This diagram is particularly interesting because it is spatially referenced. Theoretically, one could track the route of Napoleon’s army by lining this up above a basemap according to the coordinates listed at each node.

_{Fig. 2: Minard’s flow diagram of Napoleon’s Russian Campaign of 1812. What is notable about Minard’s diagram is its integration of six different variables as mentioned in Edward Tufte’s work The Visual Display of Quantitative Information (1983).}

Preparing your data for a Sankey diagram

Sankey diagrams require multicategorical data. The different variables within the dataset serve as the different nodes within the diagram. There are a number of different ways one could create a Sankey diagram – through R packages, online applications, Tableau, JavaScript libraries, amongst others – so preparing data for a Sankey diagram depends on the tool one wishes to use. At the very least, one would need a dataset that contains a source field, a target field, and a metric that is measured between those two fields. The Common Market operations data are multicategorical in nature. In this case, the source is the vendor and the target is the customer. The other categories in between (such as product and industry type) serve as connecting nodes. The magnitude of the links connecting each node is measured by the price for each transaction.

Tools to create Sankey diagrams

There are a number of different tools available to create Sankey diagrams. In the list below, I showcase six different options that I came across while creating visualizations for the Common Market.

R packages

1. riverplot

As an R user, I explored several R packages to build Sankey diagrams. The first of these packages was riverplot. The package documentation provides a few examples, including a re-creation of Minard’s diagram of the Russian Campaign of 1812. The best way to create a Sankey diagram using the riverplot package is to organize the data as a list of nodes, its partner nodes, and the position each node resides using the makeRiver function.

_{Fig. 3: Basic example code and visual output provided by riverplot package}

2. alluvial

An alternative to riverplot is the R package alluvial. For someone who had no prior experience using R, the alluvial package seemed simpler than the riverplot package. For instance, instead of having to assign a position for each node, the alluvial function reads the position of each node based on where they are positioned in the data frame.

3. networkD3

The networkD3 package, based off of the D3.js JavaScript library, allows users to create Sankey diagrams (amongst other network diagrams) that can be saved as standalone graphics or easily integrated into RMarkdown documents or Shiny web applications. Unlike the two other R packages mentioned, the networkD3 package allows for the creation of other network diagrams, including dendrograms and tree networks.

Online Applications

4. RawGraphs

I first read about an earlier version of this online application from Isabel Meirelles’s book Design for Information. After searching for the application and exploring the sample data provided, I was impressed both by its simplicity and functionality. RawGraphs provides a drag and drop interface for users who may be unfamiliar with R or other coding software. There are a number of other graphics that RawGraphs users can choose from, in addition to Sankey Diagrams.

_{Fig. 4: The Common Market’s Mid-Atlantic (top) and Georgia (bottom) operations in 2016. The variables represented from left to right are as followed: vendor county→vendor state→product type→customer industry→customer state→customer county}

5. SankeyMatic

If a user wishes to create a simple Sankey diagram with not too many variables, SankeyMatic seems to be the best option. The difference between this application and RawGraphs is that SankeyMatic requires the user either concatenate the variables into one line or enter the data manually. Whereas RawGraphs is able to aggregate the data according to the chosen diagram.

6. Google Charts

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As with RawGraphs, Google Charts allows the user to create a multitude of different graphics, one of which is a Sankey diagram. As with the networkD3 package, the layout for Google Charts is derived from the D3.js Sankey layout. While it is possible to take a screenshot of the final output, Google Charts is mainly used to embed data visualizations on a website.

Overview

This list just scratches the surface of the many different ways one could create a Sankey diagram. Assuming there would be limitations in customizing the diagrams with some of these tools, I was surprised at the different ways one could modify the Sankey diagrams using the online applications. It was also nice to see that a few of these tools had the capability to create other diagrams and charts in addition to Sankey diagrams.

How do they compare?

_{Fig. 5: Comparing Sankey diagram tools}

Other cool examples of Sankey diagrams

Our Energy System, The National Academy of Sciences
This interactive Sankey diagram estimates the amount of energy used within the United States organized by the sources from the energy is provided, to which sectors they serve, and the amount used vs. unused energy.

Energy balance flow for European Union, Eurostat
Similar to Our Energy System, this interactive web application allows the user to visualize the annual energy balance within different geographic areas within the EU. Upon the user selecting the desired year and country (or supranational entity), the application creates a Sankey diagram on the fly based on those set parameters.

What are you going to do with that degree?, Ben Schmidt
A question I am often asked upon telling people I am getting my Master’s in Geography, this Sankey diagram shows the network between college degrees and professions based on American Community Survey data. Another version of this diagram with broader degree categories can be found here.

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