Data cleaning

• Jun 18, 2026
• data-engineering

Cleaning, Transforming, and Enriching Data With Pandas

Book: Data Engineering with Python
Author: Paul Crickard
ISBN: 978-1-83921-418-9

Chapters 3 and 4 taught you how to move data in and out of files and databases. Chapter 5 asks the next obvious question: what do you do with the data in the middle? Often the answer is clean it, reshape it, and sometimes bolt on extra context from another source. Crickard uses real Albuquerque e-scooter trip data for all of this, which makes the examples feel grounded instead of toy-like.

• Feb 18, 2026
• software-engineering

Data Science Foundations Chapter 8: Cleaning and Preparing Your Data

You know that feeling when you buy fresh ingredients for dinner, and then spend 80% of your time washing, cutting, and peeling? The actual cooking takes 20 minutes. Data science is exactly like that. The cooking is the model. The prep work is this chapter.

• Feb 17, 2026
• software-engineering

Cleaning and Transforming Data - Study Notes From Data Engineering With Python Ch 5

You can build the best pipeline in the world. You can read files, write to databases, schedule everything with Airflow. But if the data going through that pipeline is messy, none of it matters.