PandasAI - AI Data Tools Tool

Overview

PandasAI is an open-source Python library that makes data analysis conversational by letting users query DataFrames, databases, and data files using natural language. It leverages large language models (LLMs) and Retrieval-Augmented Generation (RAG) so users can ask questions like “Show top 10 customers by revenue” against CSVs, Parquet files, SQL sources, or an in-memory pandas DataFrame and receive executable answers. The library is designed to bridge non-technical stakeholders and data practitioners, letting analysts prototype in Jupyter notebooks and developers embed conversational data features in Streamlit apps or client-server architectures. According to the GitHub repository, PandasAI focuses on generating and executing pandas-aware code to answer user prompts, integrating with popular LLM providers and enabling retrieval from external datasets for improved context. The project has attracted a sizable developer community and is used as a tool for rapid exploratory analysis, automated reporting, and as an assistive layer for data teams who want natural-language access to tabular and relational data without hand-writing transformations.

GitHub Statistics

• Stars: 22,974
• Forks: 2,254
• Contributors: 110
• License: NOASSERTION
• Primary Language: Python
• Last Updated: 2025-10-28T10:02:13Z
• Latest Release: v3.0.0

According to the GitHub repository, PandasAI has 22,974 stars, 2,254 forks, and 110 contributors, indicating significant interest and community contribution. The repository shows active maintenance with the last recorded commit on 2025-10-28. The project license field is listed as NOASSERTION in the provided metadata, so users should verify licensing details before commercial use. Overall activity and contributor count suggest a healthy open-source community and ongoing development.

Installation

Install via pip:

pip install pandasai

pip install --upgrade pandasai

pip install openai  # optional, for OpenAI provider integration

Key Features

• Natural-language queries over DataFrames, SQL, CSV and Parquet sources.
• Generates and executes pandas code to implement query results automatically.
• Retrieval-Augmented Generation (RAG) support to provide external context during queries.
• Integrates into Jupyter notebooks, Streamlit apps, or client-server deployments.
• Works with popular LLM providers (e.g., OpenAI, Hugging Face) for flexible model choice.

Community

PandasAI has an active community with ~23k GitHub stars, 2.2k forks, and 110 contributors. Frequent commits through 2025-10-28 indicate ongoing maintenance; users should check the repository for issue trackers, contribution guidelines, and up-to-date docs.

Key Information

• Category: Data Tools
• Type: AI Data Tools Tool