Data Analysis with Natural Language using PandasAI

PandasAI is a Python library that allows you to execute queries on Pandas DataFrames using natural language. It leverages Large Language Models (LLMs) like GPT-4 to perform complex data analysis tasks through simple natural language commands.

Features of PandasAI

• Natural language data analysis queries
• Data visualization capabilities
• Automation of complex data operations

Basic Usage

Here's a basic example of how to use PandasAI:

import pandas as pd
from pandasai import Agent
from pandasai.llm import OpenAI
 
# Create sample data
df = pd.DataFrame({
    'Product': ['A', 'B', 'C', 'D', 'E'],
    'Sales': [100, 200, 150, 300, 250],
    'Cost': [50, 100, 75, 150, 125]
})
 
# Initialize PandasAI agent
agent = Agent(
    df,
    config={
        "llm": OpenAI(model_name="gpt-4o"),
        "custom_whitelisted_dependencies": ["plotly"],
    }
)
 
# Execute natural language query
result = agent.chat("Show me a graph of the relationship between sales and cost")

Summary

Using PandasAI offers several benefits:

1. Lower barrier to entry for data analysis
2. Intuitive natural language operations
3. Automation of complex analysis tasks
4. Automatic visualization generation

However, it's important to consider security aspects and implement proper error handling.

References

• PandasAI Official Documentation
• PandasAI GitHub