25-6 Geokempy: A Streamlined Integrated Python Plotting Program for Geochemical Data

Session: Integrating metamorphism, mass transfer, and magmatism across the American Cordillera (Posters)

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Mineral and rock geochemical major, minor, and trace element data analysis has long been a powerful tool for understanding and quantifying geochemical processes in magmatic, sedimentary, and metamorphic realms, as geochemistry can provide vital insights and reveal diagnostic signatures for the setting in which a rock formed. Recent advances in in-situ petrochronology and simultaneous acquisition of split-stream or depth-profile U-Pb and trace element data from accessory phases via LA-ICP-MS or SIMS have heightened the ability to elucidate geological and petrological data at unprecedented levels. Python codes that allow for inter-platform operability and easy adaptability by users have been developed and applied by geoscientists across disciplines to manage, analyze, and visualize the increasing mineral and rock geochemical data floods. However, Python’s visualization and statistical capabilities have yet to be deployed and leveraged to their fullest potential, particularly for accessory mineral and whole rock geochemistry and petrochronology. In fact, for simpler plotting such as density contouring, many workers painstakingly create their own plotting routines or draw contours by hand, an immediate but mathematically inaccurate solution. Executable programs often become obsolete and/or are not operable on different computer platforms. Without a universal program, users run into issues when attempting to replot data, reproduce/rescale graphs, calculate regressions, combine datasets, etc. The Geokempy package provides a Python-based program platform with direct access to organized datasets from published sources for compositional comparisons. Thus, the user can select the datasets they would like to employ for analogue comparison, along with the preset scale and particular element combinations that best serve their objective and research question. It processes input data and computes ratios, creating a user-friendly interface with many opportunities for customization. Geokempy enables users to overlay data on reference probability density contours, apply multi-dimensional scaling calculations to compare the evolution of elemental compositions in changing geologic settings, and combine geochemical and age data in an easily modifiable Python environment. 

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