How to Import CSV and Tab-Delimited Files Into Python With Pandas
Most engineering and scientific data lives in CSV files, tab-delimited files, or Excel exports.
Before you can analyze anything in Python you need to get that data in. In this video I walk you through exactly how to do that using Pandas — the most widely used data analysis library in Python.
What you will learn:
📂 Why delimited files are the standard format for engineering and scientific data — and why tab-delimited files in particular work well for data that non-programmers need to edit
📊 Importing Pandas — the one line that sets up everything
📥 Reading a CSV file with pd.read_csv() — the most important function in Pandas for engineering data workflows
🔤 Handling files without header rows — two approaches:
→ Letting Pandas assign default column names automatically
→ Specifying your own column names at import
📋 Specifying column names on import with the names parameter — so your DataFrame is immediately organized the way you need it
🔀 Reading tab-delimited and other delimiter formats — how to tell Pandas what separator your file uses
All examples use realistic data scenarios that engineers and scientists encounter regularly — including instrument exports, data logger output, and structured lab data files.
If your data starts in a spreadsheet or a delimited file — and most engineering data does — this video gives you the foundation to get it into Python and start working with it.
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🐍 Python for Scientists and Engineers — practical Python for real engineering and scientific data problems.
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