pandasai 3.0.0
Chat with your database (SQL, CSV, pandas, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
License: MIT
Requires Python: <3.12,>=3.8

# ![PandasAI](assets/logo.png)

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PandasAI is a Python library 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 PandasAI [here](https://docs.pandas-ai.com/).


## 📚 Using the library

### Python Requirements

Python version `3.8+ <=3.11`

### 📦 Installation

You can install the PandasAI library using pip or poetry.

With pip:

```bash
pip install pandasai
pip install pandasai-litellm
```

With poetry:

```bash
poetry add pandasai
poetry add pandasai-litellm
```

### 💻 Usage

#### Ask questions

```python
import pandasai as pai
from pandasai_litellm.litellm import LiteLLM

# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENAI_API_KEY")

# Configure PandasAI to use this LLM
pai.config.set({
    "llm": llm
})

# Load your data
df = pai.read_csv("data/companies.csv")

response = df.chat("What is the average revenue by region?")
print(response)
```

---

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 PandasAI 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",
)
```

![Chart](assets/histogram-chart.png?raw=true)

#### Multiple DataFrames

You can also pass in multiple dataframes to PandasAI and ask questions relating them.

```python
import pandasai as pai
from pandasai_litellm.litellm import LiteLLM

# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENAI_API_KEY")

# Configure PandasAI to use this LLM
pai.config.set({
    "llm": llm
})

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)


pai.chat("Who gets paid the most?", employees_df, salaries_df)
```

```
Olivia gets paid the most.
```

#### Docker Sandbox

You can run PandasAI 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
from pandasai_litellm.litellm import LiteLLM

# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENAI_API_KEY")

# Configure PandasAI to use this LLM
pai.config.set({
    "llm": llm
})

# 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)

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

PandasAI 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 PandasAI Cloud or self-hosted Enterprise Offering, [contact us](https://pandas-ai.com).

## Resources

- [Docs](https://docs.pandas-ai.com/) for comprehensive documentation
- [Examples](examples) for example notebooks
- [Discord](https://discord.gg/KYKj9F2FRH) for discussion with the community and PandasAI 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!

[![Contributors](https://contrib.rocks/image?repo=sinaptik-ai/pandas-ai)](https://github.com/sinaptik-ai/pandas-ai/graphs/contributors)