Ask Your CSV Anything: Build a Data Analysis Agent in Python

Every data scientist has the same ritual. Load a CSV. Write df.describe() . Squint at column names. Write 14 lines of pandas to answer one question. Repeat. What if an LLM could write those 14 lines for you — and run them? That is exactly what data analysis agents do. You ask a question in English. The agent writes pandas code, executes it in a sandboxed Python environment, reads the output, and returns a plain-language answer. No manual wrangling. No copy-pasting between notebook cells. Here are 4 patterns that make this work in production — from a 5-line quick start to a fully custom analysis pipeline. Pattern 1: The Pandas DataFrame Agent LangChain's create_pandas_dataframe_agent is the fastest path from CSV to answers. It wraps your DataFrame in a tool-calling agent that writes and executes pandas code through a sandboxed Python REPL. Install the dependencies: pip install langchain-experimental langchain-openai pandas Load your data and create the agent: import pandas as pd from la