> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Pandas Tools - Data Analysis and DataFrame Operations

> Use PandasTools for data manipulation and analysis.

Use PandasTools for data manipulation and analysis. Shows enable\_ flag patterns for selective function access. PandasTools is a small tool (\<6 functions) so it uses enable\_ flags.

```python pandas_tools.py theme={null}
"""
Pandas Tools - Data Analysis and DataFrame Operations

This example demonstrates how to use PandasTools for data manipulation and analysis.
Shows enable_ flag patterns for selective function access.
PandasTools is a small tool (<6 functions) so it uses enable_ flags.

Run: `uv pip install pandas` to install the dependencies
"""

from agno.agent import Agent
from agno.tools.pandas import PandasTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


agent_full = Agent(
    tools=[PandasTools()],  # All functions enabled by default
    description="You are a data analyst with full pandas capabilities for comprehensive data analysis.",
    instructions=[
        "Help users with all aspects of pandas data manipulation",
        "Create, modify, analyze, and visualize DataFrames",
        "Provide detailed explanations of data operations",
        "Suggest best practices for data analysis workflows",
    ],
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    print("=== DataFrame Creation and Analysis Example ===")
    agent_full.print_response("""
    Please perform these tasks:
    1. Create a pandas dataframe named 'sales_data' using DataFrame() with this sample data:
       {'date': ['2023-01-01', '2023-01-02', '2023-01-03', '2023-01-04', '2023-01-05'],
        'product': ['Widget A', 'Widget B', 'Widget A', 'Widget C', 'Widget B'],
        'quantity': [10, 15, 8, 12, 20],
        'price': [9.99, 15.99, 9.99, 12.99, 15.99]}
    2. Show me the first 5 rows of the sales_data dataframe
    3. Calculate the total revenue (quantity * price) for each row
    """)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai pandas
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `pandas_tools.py`, then run:

    ```bash theme={null}
    python pandas_tools.py
    ```
  </Step>
</Steps>

Full source: [cookbook/91\_tools/pandas\_tools.py](https://github.com/agno-agi/agno/blob/main/cookbook/91_tools/pandas_tools.py)