How ChatGPT Supports Data Exploration, Cleaning, and Financial Analysis

ChatGPT supports data exploration, cleaning, and financial analysis by leveraging its natural language understanding and code execution capabilities to simplify and accelerate these tasks.

• For data exploration, ChatGPT can analyze datasets by generating and running Python code to understand feature distributions, relationships, and trends. It can create visualizations and summaries that help uncover hidden insights in the data, making exploratory data analysis more accessible and faster for both beginners and experts.

• In data cleaning, ChatGPT can automate routine tasks such as removing duplicates, handling missing values (e.g., imputing with mean or median), ensuring consistent formatting, and correcting obvious errors. Users provide the dataset and specify cleaning instructions in natural language, and ChatGPT returns a cleaned dataset along with a summary of the cleaning steps taken. This reduces manual effort compared to traditional tools like PowerQuery, especially for ad hoc or one-time cleaning tasks.

• For financial analysis, ChatGPT assists financial professionals by automating time-consuming manual tasks such as generating financial reports, coding accounts, tracking expenses and budgets, and performing data analytics like cash flow projections and investment analysis. It helps interpret accounting data for financial planning and analysis (FP&A), supports decision-making with data-driven insights, and is increasingly integrated into finance software for tasks like invoice processing and risk management.

Overall, ChatGPT acts as a versatile AI assistant that writes and executes code on behalf of users, enabling complex data operations through simple natural language prompts. This capability streamlines workflows in data science and finance by reducing the technical barrier and saving time on routine data tasks.