Each of the specialized graphs we’ll feature in our blog series is uniquely suited to visualizing complex scientific data. These plots aren’t your everyday bar charts and line graphs. They’re unique, purposeful tools, and once you’ve created one successfully, you’ll want to recreate it when similar projects arise—only with new data and zero hassle. But to make sure we’re on the same page about what this blog series will cover, here’s a look at the specialized graphs we’ll be diving into.

Piper plots are essential for water quality and hydrochemical classification. They help visualize the chemical composition of water samples using a trilinear diagram. By plotting major cations and anions, piper plots make it easy to compare samples and quickly identify water types and potential trends across geographic or temporal datasets.

Box plots (also called box-and-whisker plots) are ideal for summarizing distributions and spotting outliers in your data. They provide a quick, intuitive sense of a dataset’s median, range, and variability—great for comparing groups, summarizing field data, or visualizing summary stats across locations or time periods.

Stiff plots are another key tool for water chemistry analysis, especially for comparing ion concentrations between samples. The mirrored polygon shape makes it easy to spot differences or similarities across a dataset.

Ternary plots help visualize the relative proportions of three variables in a triangle-shaped plot. Whether analyzing sediment compositions, chemical proportions, or mineral contents, ternary plots are a go-to visual for compositional data.

Also known as wind roses, these plots show the frequency and direction of wind speeds (or any directional data). They’re especially useful in environmental studies, site assessments, and regulatory reports where it’s important to show patterns over time.

Durov plots are similar to piper plots but offer an expanded way to interpret water chemistry. They combine two ternary diagrams and a central square plot to give a more complete picture of hydrochemical facies and potential processes affecting water quality.

Now, let’s briefly discuss the solution we’re going to suggest for creating and recreating these six specialized graphs with ease. As we already know, when creating a specialized graph in a particular software for the first time, there’s always some trial and error involved as you figure out where to find the plot type, how to format your data, and how to make customizations. Once you’ve figured all this out, the second challenge comes whenever it’s time to make a similar plot. Now, you have to remember the answers to these questions: Which data columns did you assign where? What did you change in the properties? How did you customize the labels, legends, and scale?

To bypass all these challenges and questions, templates can really save the day. 

There are high-quality, ready-to-use templates of specialized graphs that you can use to create and recreate scientific plots with ease. These templates are designed to move you from data to publication-ready visuals without the hassle. Instead of navigating a learning curve or reconfiguring plots, styles, labels, and legends, you can just open a template for a specialized graph, import your dataset, customize it further if necessary, send it to your stakeholder, and reuse the template when necessary. In a nutshell, with templates, creating and recreating specialized graphs is easier and more enjoyable—and throughout this blog series, we’ll point to where you can find a template for each of the six plots we discuss.