[PyData] Cleaning and Tidying Data in Pandas - Daniel Chen

PyData DC 2018 Most of your time is going to involve processing/cleaning/munging data. How do you know your data is clean? Sometimes you know what you need beforehand, but other times you don't. We'll cover the basics of looking at your data and getting started with the Pandas Python library, and then focus on how to "tidy" and reshape data. We'll finish with applying customized processing functions on our data. === www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.