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Published on Jul 26, 2017
Description Test-driven data analysis fuses and builds upon the ideas of test-driven development and reproducible research to support higher quality data analysis. This talk will extend the foundation parts of TDDA with extensions including tight constraints on string fields with automatically discovered regular expressions and automatically discovered relationships between datasets.
Abstract Test-driven data analysis fuses and builds upon the ideas of test-driven development and reproducible research to support higher quality data analysis.
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.