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Enable Agno agents for data manipulation and analysis. For selective function access, use enable_ flag patterns. 

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

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/91_tools

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python pandas_tools.py
For details, see Pandas cookbook.