This repository contains a standalone Python implementation for calculating coordinates and generating "Partial Parallelism Plots" (https://doi.org/10.3390/app14020602).Partial Parallelism Plots are used in bioassays, immunoassay validations, and biomarker quantification to visually assess and verify parallel relationships between sample dilution series and reference standard curves. By standardising the dilution factors logarithmically on the X-axis and normalising the baseline-corrected concentrations to 1.0 on the Y-axis, this visualisation allows for direct, overlaid geometric comparison across distinct samples regardless of variations in their initial starting concentrations. This is much easier than trying to prove parallelism by statistical means.Features:- Accepts automated data ingestion from standard CSV file formats.- Dynamically processes multi-sample arrays in a single execution.- Automatically handles non-interactive backend environments (e.g., headless servers, CI/CD pipelines) by saving high resolution figures (300 DPI PNG) directly to the workspace.- Includes automated log-scaling, concentration correction, and baseline normalization mathematics.Prerequisites:Python 3.x with numpy, pandas, and matplotlib libraries.