From the course: Data Quality: Measure, Improve, and Enforce Reliable Systems
Join today to access over 25,300 courses taught by industry experts.
Validation rules in Python - Python Tutorial
From the course: Data Quality: Measure, Improve, and Enforce Reliable Systems
Validation rules in Python
- [Instructor] Have you ever opened a dashboard, only to see a blank chart, or worse, values that make no sense at all? Maybe customer ages were negative or an entire column of emails was missing. These aren't just data quirks, they are quality issues that can break downstream systems, models, or decision making. Now, it's time to go one step further, write simple rules to catch those issues automatically. In this video, we'll see how to create basic data quality checks using Python. We are starting with a very simple case here, just enough to show you the concept. Later, you will learn how to scale these rules using more powerful tools. Rule-based checks are simple conditions that your data must meet. You define them based on what should be true in your dataset. For example, every user should have an email address. Age must be between zero and 120. Country names should come from a known list. These checks help you catch errors early before they cause problems downstream. Let's start…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.