This Zenodo repository contains a Jupyter Notebook tool designed to evaluate Positive Matrix Factorization (PMF) profiles dissimilarity using Cosine Distance (CD), Pearson Distance (PD), and Standardized Identity Distance (SID), as defined in Brezins et al. (2026, in prep.). The notebook also allows visualization of PD-SID and CD plots, including thresholds for homogeneous chemical profiles. The tool can be applied to factors obtained from either Rolling or classical PMF factors. Factors may be compared pairwise, including all pairwise comparisons with mean values and standard deviations, or evaluated against a selected reference factor profile. Two matrices containing multiple versions of a Xact Biomass Burning factor profile obtained at the MRS-LCP site in 2023, from Brezins et al. (2026, in prep.), through different PMF analyses (static and Rolling), are provided to illustrate how to use the script. The author acknowledges the use of the ChatGPT AI tool for Python script correction.