Using ChatGPT for Data Science Analyses

Research output: Contribution to journalArticlepeer-review

Abstract

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 copilot, its limitations demand careful consideration in empirical analyses.This article 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 a copilot for the data science workflow, its broader potential for automation is implicit throughout.
Original languageEnglish
JournalHarvard Data Science Review
Volume8
Issue number1
DOIs
Publication statusPublished - 30 Jan 2026

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