PandasAI is a Python library designed to make data analysis conversational, enabling users to query databases, CSVs, and datalakes using natural language. It targets both technical and non-technical users, aiming to simplify data interaction and accelerate analysis workflows through Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).

How It Works

PandasAI integrates with LLMs to interpret natural language queries and translate them into executable code (e.g., Python/Pandas or SQL). It supports RAG for enhanced context and accuracy, allowing it to query various data sources. The library can also generate visualizations based on user prompts, and it supports querying across multiple DataFrames. A key feature is its Docker sandbox for secure code execution.

Quick Start & Requirements

• Installation: pip install "pandasai>=3.0.0b2" or poetry add "pandasai>=3.0.0b2"
• Requirements: Python 3.8 to <3.12. Requires an API key for the default BambooLLM, obtainable at https://app.pandabi.ai.
• Documentation: https://docs.pandasai.ai/
• Examples: https://github.com/sinaptik-ai/pandas-ai/tree/main/examples

Highlighted Details

• Supports querying SQL databases, CSVs, and Parquet files.
• Enables natural language querying across multiple DataFrames.
• Offers a Docker sandbox for secure code execution.
• Can generate data visualizations based on natural language prompts.

Maintenance & Community

• Beta Notice: Release v3 is currently in beta.
• Community: Discord server available for discussions.
• Contributing: Guidelines are provided for contributions.

Licensing & Compatibility

• License: MIT Expat license for the core library. The pandasai/ee directory has a separate license.
• Commercial Use: Compatibility for commercial use is implied by the MIT license for the core library, but specific terms for enterprise offerings should be confirmed.

Limitations & Caveats

The project is currently in beta (v3), meaning features and functionality are in progress and subject to change. The default LLM (BambooLLM) requires an API key, and while other LLMs can be configured, this is not explicitly detailed in the README.