Using ChatGPT for Data Science Analyses

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Authors: Ozan Evkaya, Miguel de Carvalho
Cited by: 1

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 co-pilot, its limitations demand careful consideration in empirical analyses.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 a co-pilot for the Data Science workflow, its broader potential for automation is implicit throughout.

Fields of Study & Subjects

Machine Learning in Healthcare Explainable Artificial Intelligence (XAI)

Publication details

Journal / source
Harvard Data Science Review
Publisher
MIT Press
Volume
8
Issue
1
Publication date
13 January 2026
Language
EN