Mastering data visualization with Python: practical tips for researchers.

Soyul Han, Il-Youp Kwak
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Abstract

Big data have revolutionized the way data are processed and used across all fields. In the past, research was primarily conducted with a focus on hypothesis confirmation using sample data. However, in the era of big data, this has shifted to gaining insights from the collected data. Visualizing vast amounts of data to derive insights is crucial. For instance, leveraging big data for visualization can help identify and predict characteristics and patterns related to various infectious diseases. When data are presented in a visual format, patterns within the data become clear, making it easier to comprehend and provide deeper insights. This study aimed to comprehensively discuss data visualization and the various techniques used in the process. It also sought to enable researchers to directly use Python programs for data visualization. By providing practical visualization exercises on GitHub, this study aimed to facilitate their application in research endeavors.

用 Python 掌握数据可视化:研究人员的实用技巧。
大数据彻底改变了所有领域处理和使用数据的方式。过去,研究工作主要是利用样本数据进行假设确认。然而,在大数据时代,这已转变为从收集到的数据中获得洞察力。将海量数据可视化以获得洞察力至关重要。例如,利用大数据进行可视化有助于识别和预测与各种传染病相关的特征和模式。当数据以可视化的形式呈现时,数据中的模式就会变得清晰,从而更容易理解并提供更深入的见解。本研究旨在全面讨论数据可视化和在此过程中使用的各种技术。它还试图让研究人员能够直接使用 Python 程序进行数据可视化。通过在 GitHub 上提供实用的可视化练习,本研究旨在促进其在研究工作中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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