Data and code for: Unsupervised Learning for Profiling University Students with Parental Responsibilities

Anonymized dataset and analysis code supporting the study "Unsupervised Learning for Profiling University Students with Parental Responsibilities", conducted at the Universidad Nacional del Altiplano, Puno, Peru. The data come from the institutional registration program carried out in 2024 to identify students who are mothers or fathers. The questionnaire collected demographic, academic, parental, time-management, and support-related variables, mostly through closed questions and four-level Likert scales. The raw anonymized file contains 236 records and the cleaned file used in the analysis contains 206 records. The deposit includes two datasets and two equivalent implementations of the analysis pipeline: cleaning, ordinal encoding of the Likert items, conceptual feature selection, Principal Component Analysis, and a comparison of K-Means, DBSCAN, and Agglomerative Clustering with internal validation metrics. The pipeline uses a fixed random seed and reproduces the results reported in the paper. Privacy: direct identifiers (national identity number, student code, and internal ID) were removed before publication, and the date of birth was replaced by age in completed years at the time of registration, so exact dates cannot be reconstructed. The files contain no names, e-mail addresses, or contact numbers. Full Changelog: https://github.com/michaelmcs/estudiantes_parentales/commits/v1.1