Visualization of Aqueous Geochemical Data Using Python and WQChartPy - Yang, Jing; Liu, Honghua; Tang, Zhonghua; Peeters, Luk; Ye, Ming (Ground water, 2022)
Graphical methods have been widely used for visualization, classification, and interpretation of aqueous geochemical data to obtain a better understanding of surface and subsurface hydrologic systems. This method note presents WQChartPy, an open‐source Python package developed to plot a total of 12 diagrams for analysis of aqueous geochemical data. WQChartPy can handle various data formats including Microsoft Excel, comma‐separated values (CSV), and general delimited text. The 12 diagrams include eight traditional diagrams (trilinear Piper, Durov, Stiff, Chernoff face, Schoeller, Gibbs, Chadha, and Gaillardet) and four recently proposed diagrams (rectangle Piper, color‐coded Piper, contour‐filled Piper, and HFE‐D) that have not been implemented in existing graphing software. The diagrams generated by WQChartPy can be saved as portable network graphics (PNG), scalable vector graphics (SVG), or portable document format (PDF) files for scientific publications. Jupyter and Google Colab notebooks are available online to illustrate how to use WQChartPy with example datasets. The geochemical diagrams can be generated with several lines of Python codes. Source codes of WQChartPy are publicly available at GitHub (https://github.com/jyangfsu/WQChartPy) and PyPI (https://pypi.org/project/wqchartpy/). Article Impact Statement: The open‐source Python package WQChartPy generates 12 publication‐quality diagrams which facilitate analysis of aqueous geochemical data.