A Perspective View on Data Visualization Libraries Used in Data Analytics

Abstract

In today’s data-driven world, one of the cornerstones of data science is data visualization. Data visualization makes information more understandable by presenting complex data sets through graphs, tables, and other visual tools. Thus, trends, relationships, and anomalies in the data can be easily detected. In this way, more intuitive and meaningful results are obtained from the data. In addition, decision makers are able to make the right decisions faster thanks to these visualization tools. Graphics libraries created and used in programming languages are used intensively to perform these operations. This article explores programming language-based data visualization libraries, which are widely utilized in the field of data science, and examines the key features and functionalities of these libraries. In this context, 76 visualization libraries were examined and evaluated in terms of customization level, interactive features, and the data types they support, and presented separately in tables according to programming languages. The study areas of the articles in which these libraries were used in the literature and the results obtained from the studies were also presented. In addition, the directions of future studies in this field were added to the conclusion.