The Piper diagram has increased in popularity since its 1944 introduction and is now one of the most familiar and effective tools in the hydrogeologist's toolbox. Within the Piper diagram, three points on three related plots fully display the major ionic species of a water sample. Recently the size and availability of datasets have increased as additional field measurements and modeling results are shared more effectively in online databases. This growth presents opportunities and challenges for data analysis and conveyance—larger and longer datasets increase the potential to identify trends and patterns, but traditional Piper diagrams are quickly overwhelmed by large datasets as dense points overlap and become obscured. We present guidelines for effectively displaying large geochemical datasets on traditional Piper diagrams and new code that adds novel functionality for following these generic guidelines. This code, plotting interesting environmental data with Piper diagrams (PIED Piper), can be run within the Matlab environment or through a stand‐alone graphical user interface, and is the first Matlab code to generate Piper diagrams. The illustrative examples herein demonstrate (1) how limitations in displays of large datasets may be overcome with translucent symbology, contours, and heatmaps to identify trends and patterns, (2) how clusters of similar points can be identified and differentiated with convex hulls, and (3) how temporal‐and‐spatial patterns may be visually diagnosed with image groups and movies. The guidelines discussed in these examples will aid PIED Piper users to achieve the two goals of effective big data visualization: analysis and communication.

中文翻译：

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付费使用PIED Piper：在Piper图上可视化大型地球化学数据集的准则

自1944年问世以来，Piper图已越来越受欢迎，现在已成为水文地质学家工具箱中最熟悉，最有效的工具之一。在Piper图中，三个相关图上的三个点完全显示了水样品中的主要离子种类。最近，随着在线数据库中更有效地共享其他现场测量结果和建模结果，数据集的大小和可用性也有所增加。这种增长为数据分析和传输带来了机遇和挑战—越来越大的数据集增加了识别趋势和模式的潜力，但是随着密集点的重叠并​​变得模糊，传统的Piper图很快就被大型数据集淹没。我们提供了在传统Piper图上有效显示大型地球化学数据集的准则，以及为遵循这些通用准则而增加了新颖功能的新代码。该代码可以用Piper图（PIED Piper）绘制有趣的环境数据，可以在Matlab环境中运行，也可以通过独立的图形用户界面运行，并且是第一个生成Piper图的Matlab代码。本文的说明性示例演示（1）如何通过半透明的符号系统，轮廓和热图克服大型数据集显示中的局限性，以识别趋势和模式；（2）如何用凸包识别和区分相似点的群集，以及（3）如何通过图像组和电影视觉诊断时空模式。