As a result of recent advancements in generative AI, the field of data science is prone to various changes. The way practitioners construct their data science workflows is now irreversibly shaped by recent advancements, particularly by tools like OpenAI's Data Analysis plugin. While it offers powerful support as a quantitative co-pilot, its limitations demand careful consideration in empirical analysis. This paper assesses the potential of ChatGPT for data science analyses, illustrating its capabilities for data exploration and visualization, as well as for commonly used supervised and unsupervised modeling tasks. While we focus here on how the Data Analysis plugin can serve as co-pilot for Data Science workflows, its broader potential for automation is implicit throughout.

翻译：随着生成式人工智能的最新进展，数据科学领域正面临多方面的变革。从业者构建数据科学工作流的方式已不可逆转地受到近期技术发展的影响，特别是像OpenAI的数据分析插件这类工具。虽然它作为量化协同助手提供了强大支持，但其局限性要求我们在实证分析中予以审慎考量。本文评估了ChatGPT在数据科学分析中的潜力，展示了其在数据探索与可视化、以及常用监督式与非监督式建模任务方面的能力。尽管本文主要关注数据分析插件如何作为数据科学工作流的协同助手，但其在自动化方面更广泛的潜力始终贯穿其中。