Finalized directories of QTAIM properties contain either jsons (critic2) or text files (Multiwfn) with QTAIM information including bonding, energetics, and critical point types. Our parse_data.py script intakes these folders, and merges QTAIM information into the original json. This merge process involves parsing a user-specified set of QTAIM features, and optionally, imputation. We compile all of the QTAIM values for the dataset and use these to compute mean and median values for imputation where information is missing or where QTAIM and prior bond definitions are not in alignment. The user can also select to update bond definitions using QTAIM BCPs and whether to parse the dataset as a dataset of molecules or reactions. Atom and bond mappings are computed between final bond definitions and features. This is vital for the construction of reaction-property datasets where atom/bond-mapping across different numbers of reactions/products is non-trivial. The finalized output of these processes is a new json containing pymatgen objects, bonding information, QTAIM features, mappings, and optional features such as spin and charges. The entire pipeline allows for QTAIM calculations at scale, and as such, we include several large datasets for further experimentation and development.