Inaccurate or inconsistent data can lead to poor business decisions. However, manually validating data can be time-consuming and error-prone. Tools and technologies available today can help automate the process of validating and cleaning data. In this course, Validate Data Cleanliness Using Asserts in Python, you will learn how to use asserts in Python to validate the cleanliness of data. First, you will be introduced to the numpy.testing module and how it can be used to verify data tidiness. Next, you will discover how to verify the equality of two indexes, two Series, and two DataFrames using the various testing functions available in the numpy.testing module. Finally, you will explore how to compose quantitative and logical tests for clean data using asserts and apply them for data cleaning. When you are finished with this course, you will have the skills needed to use asserts to validate data cleanliness in Python.
Author Name: Pinal Dave
Author Description:
Pinal Dave is an SQL Server Performance Tuning Expert and independent consultant with over 22 years of hands-on experience. He holds a Master of Science degree and numerous database certifications. Pinal has authored 14 SQL Server database books and 81 Pluralsight courses. To freely share his knowledge and help others build their expertise, Pinal has also written more than 5,800 database tech articles on his blog at https://blog.sqlauthority.com.

Table of Contents

• Course Overview
  1min
• Validating and Verifying Data Using Asserts
  28mins
• Using Assert-based Tests for Data Cleaning
  12mins