https://github.com/Sinaptik-AI/pandas-ai
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
https://github.com/Sinaptik-AI/pandas-ai
ai csv data data-analysis data-science data-visualization database datalake gpt-4 llm pandas sql text-to-sql
Last synced: 20 days ago
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Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
- Host: GitHub
- URL: https://github.com/Sinaptik-AI/pandas-ai
- Owner: sinaptik-ai
- License: other
- Created: 2023-04-22T12:58:01.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-03-18T11:51:59.000Z (27 days ago)
- Last Synced: 2025-03-18T16:05:12.658Z (27 days ago)
- Topics: ai, csv, data, data-analysis, data-science, data-visualization, database, datalake, gpt-4, llm, pandas, sql, text-to-sql
- Language: Python
- Homepage: https://getpanda.ai
- Size: 54.3 MB
- Stars: 18,162
- Watchers: 141
- Forks: 1,692
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
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README
# 
[](https://pypi.org/project/pandasai/)
[](https://github.com/sinaptik-ai/pandas-ai/actions/workflows/ci-core.yml/badge.svg)
[](https://github.com/sinaptik-ai/pandas-ai/actions/workflows/cd.yml/badge.svg)
[](https://codecov.io/gh/sinaptik-ai/pandas-ai)
[](https://discord.gg/KYKj9F2FRH)
[](https://pepy.tech/project/pandasai) [](https://opensource.org/licenses/MIT)
[](https://colab.research.google.com/drive/1ZnO-njhL7TBOYPZaqvMvGtsjckZKrv2E?usp=sharing)
PandaAI is a Python platform that makes it easy to ask questions to your data in natural language. It helps non-technical users to interact with their data in a more natural way, and it helps technical users to save time, and effort when working with data.
# 🔧 Getting started
You can find the full documentation for PandaAI [here](https://pandas-ai.readthedocs.io/en/latest/).
You can either decide to use PandaAI in your Jupyter notebooks, Streamlit apps, or use the client and server architecture from the repo.
## ☁️ Using the platform
The library can be used alongside our powerful data platform, making end-to-end conversational data analytics possible with as little as a few lines of code.
Load your data, save them as a dataframe, and push them to the platform
```python
import pandasai as pai
pai.api_key.set("your-pai-api-key")
file = pai.read_csv("./filepath.csv")
dataset = pai.create(path="your-organization/dataset-name",
df=file,
name="dataset-name",
description="dataset-description")
dataset.push()
```
Your team can now access and query this data using natural language through the platform.
## 📚 Using the library
### Python Requirements
Python version `3.8+ <3.12`
### 📦 Installation
You can install the PandaAI library using pip or poetry.
With pip:
```bash
pip install "pandasai>=3.0.0b2"
```
With poetry:
```bash
poetry add "pandasai>=3.0.0b2"
```
### 💻 Usage
#### Ask questions
```python
import pandasai as pai
# Sample DataFrame
df = pai.DataFrame({
"country": ["United States", "United Kingdom", "France", "Germany", "Italy", "Spain", "Canada", "Australia", "Japan", "China"],
"revenue": [5000, 3200, 2900, 4100, 2300, 2100, 2500, 2600, 4500, 7000]
})
# By default, unless you choose a different LLM, it will use BambooLLM.
# You can get your free API key signing up at https://app.pandabi.ai (you can also configure it in your .env file)
pai.api_key.set("your-pai-api-key")
df.chat('Which are the top 5 countries by sales?')
```
```
China, United States, Japan, Germany, Australia
```
---
Or you can ask more complex questions:
```python
df.chat(
"What is the total sales for the top 3 countries by sales?"
)
```
```
The total sales for the top 3 countries by sales is 16500.
```
#### Visualize charts
You can also ask PandaAI to generate charts for you:
```python
df.chat(
"Plot the histogram of countries showing for each one the gd. Use different colors for each bar",
)
```
#### Multiple DataFrames
You can also pass in multiple dataframes to PandaAI and ask questions relating them.
```python
import pandasai as pai
employees_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Name': ['John', 'Emma', 'Liam', 'Olivia', 'William'],
'Department': ['HR', 'Sales', 'IT', 'Marketing', 'Finance']
}
salaries_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Salary': [5000, 6000, 4500, 7000, 5500]
}
employees_df = pai.DataFrame(employees_data)
salaries_df = pai.DataFrame(salaries_data)
# By default, unless you choose a different LLM, it will use BambooLLM.
# You can get your free API key signing up at https://app.pandabi.ai (you can also configure it in your .env file)
pai.api_key.set("your-pai-api-key")
pai.chat("Who gets paid the most?", employees_df, salaries_df)
```
```
Olivia gets paid the most.
```
#### Docker Sandbox
You can run PandaAI in a Docker sandbox, providing a secure, isolated environment to execute code safely and mitigate the risk of malicious attacks.
##### Python Requirements
```bash
pip install "pandasai-docker"
```
##### Usage
```python
import pandasai as pai
from pandasai_docker import DockerSandbox
# Initialize the sandbox
sandbox = DockerSandbox()
sandbox.start()
employees_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Name': ['John', 'Emma', 'Liam', 'Olivia', 'William'],
'Department': ['HR', 'Sales', 'IT', 'Marketing', 'Finance']
}
salaries_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Salary': [5000, 6000, 4500, 7000, 5500]
}
employees_df = pai.DataFrame(employees_data)
salaries_df = pai.DataFrame(salaries_data)
# By default, unless you choose a different LLM, it will use BambooLLM.
# You can get your free API key signing up at https://app.pandabi.ai (you can also configure it in your .env file)
pai.api_key.set("your-pai-api-key")
pai.chat("Who gets paid the most?", employees_df, salaries_df, sandbox=sandbox)
# Don't forget to stop the sandbox when done
sandbox.stop()
```
```
Olivia gets paid the most.
```
You can find more examples in the [examples](examples) directory.
## 📜 License
PandaAI is available under the MIT expat license, except for the `pandasai/ee` directory of this repository, which has its [license here](https://github.com/sinaptik-ai/pandas-ai/blob/main/ee/LICENSE).
If you are interested in managed PandaAI Cloud or self-hosted Enterprise Offering, [contact us](https://getpanda.ai/pricing).
## Resources
> **Beta Notice**
> Release v3 is currently in beta. The following documentation and examples reflect the features and functionality in progress and may change before the final release.
- [Docs](https://pandas-ai.readthedocs.io/en/latest/) for comprehensive documentation
- [Examples](examples) for example notebooks
- [Discord](https://discord.gg/KYKj9F2FRH) for discussion with the community and PandaAI team
## 🤝 Contributing
Contributions are welcome! Please check the outstanding issues and feel free to open a pull request.
For more information, please check out the [contributing guidelines](CONTRIBUTING.md).
### Thank you!
[](https://github.com/sinaptik-ai/pandas-ai/graphs/contributors)