Название: Data Visualization in R and Python Автор: Marco Cremonini Издательство: Wiley Год: 2025 Страниц: 576 Язык: английский Формат: epub Размер: 98.2 MB
Communicate the data that is powering our changing world with this essential text.
The advent of Machine Learning and neural networks in recent years, along with other technologies under the broader umbrella of ‘Artificial Intelligence,’ has produced an explosion in Data Science research and applications. Data Visualization, which combines the technical knowledge of how to work with data and the visual and communication skills required to present it, is an integral part of this subject. The expansion of Data Science is already leading to greater demand for new approaches to Data Visualization, a process that promises only to grow.
Data Visualization in R and Python offers a thorough overview of the key dimensions of this subject. Beginning with the fundamentals of data visualization with Python and R, two key environments for data science, the book proceeds to lay out a range of tools for data visualization and their applications in web dashboards, Data Science environments, graphics, maps, and more. With an eye towards remarkable recent progress in open-source systems and tools, this book offers a cutting-edge introduction to this rapidly growing area of research and technological development.
The text is divided into four parts already mentioned in the previous introduction. The first part presents the fundamentals of data visualization with Python and R, the two reference languages and environments for data science, employed to create static graphs as a direct result of a previous data wrangling (import, transformation) and analysis activity. The reference libraries for this first part are Seaborn for Python and ggplot2 for R. They are both modern open-source graphics libraries and in constant evolution, both produced by the core developers and with the contributions of the respective communities, very large and lively in engaging in continuous innovations. Seaborn is the more recent of the two and partly represents an evolved interface of Python’s traditional matplotlib graphics library, made more functional and enriched with features and graph types popular in modern data visualization. Ggplot2 is the traditional graphic library for R, unanimously recognized as one of the best ever, both in the open-source and proprietary world.
The second part introduces Altair, a Python library capable of producing interactive graphics in HTML and JSON format, as well as static versions in bitmap (PNG and JPG) and vector (SVG) formats. Altair is a young but solid graphic library because in all respects it represents a modern interface of Vega-Lite, a graphic library with an established tradition for web applications thanks to the declarative syntax in JSON format.
The third and fourth parts represent advanced data visualization contents. The difficulty increases and so does the commitment required, on the other hand, we face two real worlds: that of web dashboards and of spatial data and maps.
Data Visualization in R and Python readers will also find:
Coverage suitable for anyone with a foundational knowledge of R and Python Detailed treatment of tools including the Ggplot2, Seaborn, and Altair libraries, Plotly/Dash, Shiny, and others Case studies accompanying each chapter, with full explanations for data operations and logic for each, based on Open Data from many different sources and of different formats
Data Visualization in R and Python is ideal for any student or professional looking to understand the working principles of this key field.
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Data Visualization in R and Python 
