Dataset in vitro: This dataset is not originated by me, but rather comes from the University of Portugal. It was generated within a laboratory setting, so it's important to note that the trends found in the data may not necessarily reflect real-world trends. The data is related to wine preferences and was obtained through data mining of the physicochemical properties of wine. The study was published in the journal "Decision Support Systems" under the title "Modeling wine preferences by data mining from physicochemical properties" and was authored by P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis. The publication appeared in the 47(4) issue of the journal, on pages 547-553, in 2009.
Dataset from Asia (This dataset was scraped by me in 2022 and is one of the datasets used in commercial settings.): The dataset contains the physicochemical properties of Asian wines, scraped over approximately 30 hours. The purpose of this dataset is to identify the representative characteristics of Silver, Gold, and Grand Gold medal-winning wines. This information could be useful for winemakers, wine enthusiasts, and researchers interested in understanding the attributes of high-quality Asian wines. The variables in the dataset include physical and chemical measurements such as pH, alcohol content, sugar levels, and others that contribute to the overall quality and taste of the wine. With this data, it is possible to perform statistical analyses and identify patterns and correlations between the variables and the medal categories. This dataset represents a valuable resource for anyone seeking to gain insight into the properties of high-quality Asian wines.