This is a column series focusing on open-source tools for data science: each article focuses on a specific topic and introduces the reader to a set of different tools, showcasing their features with a real-world dataset. This piece focuses on data profiling and reviews ydata-profiling, dataprep, sweetviz, autoviz, and lux. Readers are encouraged to follow along the tutorial: I’ll be referring to all projects on their individual GitHub repositories, but a curated list of tools, as well as the Google Colab notebooks used throughout this article are available in my awesome-data-centric-ai repository.
In a world of Data Imperfection, a carefully-designed tool for data understanding is the philosopher’s stone.