Tabular Data Exploration and Modelling with LLMs

Author(s): Cornellius Yudha Wijaya

Originally published on Towards AI.

Exploring the way to perform tabular data science activity with LLM
Image developed by DALL.E

Large Language Models have been rising recently and will be like that in the upcoming year. The rise could be addressed as a product of the LLM's usefulness in solving many problems. From answering our problems to developing applications, LLM could help us all. However, you might need to learn that LLM could apply to the tabular data.

Tabular data is the data in the typical table — some columns and rows are structured well, like in Excel or SQL data. It's the most common usage of data forms in many data use cases.

With the power of LLM, we would learn how to explore the data and perform data modeling. How do we do? Let's get into it.

Pandas is one of the most prominent Python Packages for data exploration and manipulation. Every data professional learning Python would come across Pandas during their work. That's why we would learn about the Python package that embeds LLM with Pandas — PandasAI.

PandasAI would use the LLM power to help us explore and clean data. It would be conversational tools that we can use to ask Pandas to manipulate data in a way we want.

To use the PandasAI, we need to install… Read the full blog for free on Medium.

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Published via Towards AI