For hierarchical clustering, one perovskite film was dropped from the analysis due to its poor quality and 5 reference samples with Br content (detected in by the clustering algorithm as their own cluster) were dropped from the analysis as the purpose was to focus on iodide-only samples. The color-calibrated film color as a function of aging test duration data were clustered using hierarhical clustering algorithm . Cluster distances were determined using UPGMA algorithm and cosine distance measure was used. In the resulting dendrogram, three distinct clusters were detected. Samples nearest to the compositional cluster centroids and the RGB centroids, i.e., the most typical color degradation curve in the cluster, were determined for the analysis. Hierarchical clustering was chosen among the clustering algorithms due to the graphical analysis of the ideal number of clusters, which is ideal for future use of the degradation data clustering repository in repeated retrospective analysis of the degradation test data.