Research & Knowledge Management · Public

pandas-ai

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

Best fitUsers who want source-backed project understanding before installing it.

Check whether this project matches your task before installing it.

What it can doPortable AI capability asset

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot24k stars

2.3k forks · 112 contributors

Doramagic.ai Last verification date: 2026-06-22 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-22

What is pandas-ai?

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Best fit: Users who want source-backed project understanding before installing it.
Not for: Not for users who want to skip sandbox verification or cannot accept configuration, permission, or maintenance overhead.
Capability added to an AI workflow: Portable AI capability asset
First safe verification step: Verify the smallest path in an isolated environment and keep a rollback path.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/sinaptik-ai/pandas-ai, https://github.com/sinaptik-ai/pandas-ai#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forUsers who want source-backed project understanding before installing it.

Match the project to your task before installing it.

CapabilityPortable AI capability asset

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

Repositorysinaptik-ai/pandas-ai

24k stars · 2.3k forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview, Installation, and Quickstart

Related topics: Code Execution, Sandbox, and Security Model, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Code Execution, Sandbox, and Security Model

Related topics: Overview, Installation, and Quickstart, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

LLM Backends, Local Models, and Extension Ecosystem

Related topics: Overview, Installation, and Quickstart, Code Execution, Sandbox, and Security Model, Agent Lifecycle, Prompts, and Semantic Layer

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Agent Lifecycle, Prompts, and Semantic Layer

Related topics: Overview, Installation, and Quickstart, Code Execution, Sandbox, and Security Model, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/sinaptik-ai/pandas-ai, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars24k stars

Forks2.3k forks

Contributors112 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using pandas-ai with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Free trial is mentioned as no cc required but it expects a cc
github / github_issue
02
Default code executor runs LLM-generated code with full builtins (no san
github / github_issue
03
Agent ignores Conversation History: Missing placeholders in generate_pyt
github / github_issue
04
agent.chat() Fails to Reset Code Context (State Residue)
github / github_issue
05
agent.description (System Prompt) is dead-code
github / github_issue
06
SemanticLayerSchema limit seems to do nothing
github / github_issue
07
Code Injection in CodeExecutor.execute Allows Arbitrary Code Execution v
github / github_issue
08
Upgrade supported Python version >=3.12 for pandasai
github / github_issue
09
pillow of version ^10.1.0 has OOB CVE
github / github_issue
10
Feature request: optional WFGY 16-problem RAG debugger for pandas-ai
github / github_issue
11
Support for GPT-5 or above Reasoning Model
github / github_issue
12
Issue on Ollama Models
github / github_issue

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install pandasai

Official start command · https://github.com/sinaptik-ai/pandas-ai#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

pandas-ai Manual

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

Open the full manual

https://github.com/sinaptik-ai/pandas-ai Project Manual
Table of Contents
Overview, Installation, and Quickstart
Related Pages
What is PandasAI
Installation
pip
poetry

Overview, Installation, and Quickstart

Related topics: Code Execution, Sandbox, and Security Model, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Code Execution, Sandbox, and Security Model

Related topics: Overview, Installation, and Quickstart, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

LLM Backends, Local Models, and Extension Ecosystem

Related topics: Overview, Installation, and Quickstart, Code Execution, Sandbox, and Security Model, Agent Lifecycle, Prompts, and Semantic Layer

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Agent Lifecycle, Prompts, and Semantic Layer

Related topics: Overview, Installation, and Quickstart, Code Execution, Sandbox, and Security Model, LLM Backends, Local Models, and Extension Ecosystem

Source: https://github.com/sinaptik-ai/pandas-ai / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.