Practical data cleaning with Python

Tips and tools for data janitors.

By Katharine Jarmul
March 26, 2017
Practical data cleaning Practical data cleaning (source: O'Reilly)

Join expert Katharine Jarmul for a hands-on, in-depth exploration of practical data cleaning with Python, as she highlights the tools that can help speed up the data wrangling process and automate (or at least allow for general scripting) of some of the repetitive processes. You’ll get an overview of best libraries and tools to use when handling messy data and learn how to apply software development practices to data wrangling problems by writing data unit tests, which allow you to catch problems before they have created innacurate data for your entire company. Along the way, you’ll explore a few case studies to see the application of these techniques on real-world data problems.

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Post topics: Data science