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Published on Jul 26, 2017
Description Most of us regularly work with Jupyter notebooks, but fail to see obvious productivity gains involving its usage. Did you know that the web interface works like a modal editor such as VIM? Do you know that you can actually profile AND debug code in notebooks? How about setting formulas or use pre-made style settings for visualizations? Let us go through the tricks of the trade together!
Abstract Overview of the Jupyter project + setup to get everyone on board. Handling the UI, know the shortcuts Different type of cells Exporting notebooks for presentations Handling different kernels Set styles for visualizations for professional quality Mod the style of the web interface yourself via CSS Profiling code in notebooks, use Cython Debugging in notebooks
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.