Halle Burns (Libraries) recently published the tutorial, "Crowdsourced-Data Normalization with Python and Pandas," in Programming Historian, an online, international digital humanities and digital history methodology journal. This lesson describes crowdsourcing as a form of data creation as well as how pandas (a Python package for data handling and analysis) can be used to prepare a crowdsourced dataset for analysis. The tutorial covers crowdsourcing best practices, managing duplicate and missing data, and explains the difficulties of dealing with dates.