ydata-profiling: Accelerating data-centric AI with high-quality data

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Clemente, F (Author) Other; Ribeiro, GM (Author) Other; Quemy, A (Author) Other; Santos, MS (Author) Other; Pereira, RC (Author) Other; Barros, A (Author) Other

Journal

Title: Neurocomputing

Vol. 554

ISSN: 0925-2312

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 12 Citations

Other information

Authenticus ID: P-010-7KQ

DOI: 10.1016/j.neucom.2023.126585

Abstract (EN): ydata-profiling is an open-source Python package for advanced exploratory data analysis that enables users to generate data profiling reports in a simple, fast, and efficient manner, fostering a standardized and visual understanding of the data. Beyond traditional descriptive properties and statistics, ydata-profiling follows a Data-Centric AI approach to exploratory analysis, as it focuses on the automatic detection and highlighting of complex data characteristics often associated with potential data quality issues, such as high ratios of missing or imbalanced data, infinite, unique, or constant values, skewness, high correlation, high cardinality, non-stationarity, seasonality, duplicate records, and other inconsistencies. The source code, documentation, and examples are available in the GitHub repository: https://github.com/ydataai/ydata-profiling.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10