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Cleaning Data in a Pandas DataFrame

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29 May 2020CPOL4 min read
In this fifth part of the Data Cleaning with Python and Pandas series, we take one last pass to clean up the dataset before reshaping.
It's important to make sure the overall DataFrame is consistent. This includes making sure the data is of the correct type, removing inconsistencies, and normalizing values.


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This article is part of the series 'Data Cleaning with Python and Pandas View All


This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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Hi! I'm a Solution Architect, planning and designing systems based in Denver, Colorado. I also occasionally develop web applications and games, as well as write. My blog has articles, tutorials and general thoughts based on more than twenty years of misadventures in IT.

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