This will be a somewhat advanced, technical talk connecting computer science concepts like data structure design and algorithms with the details of building intuitive, high performance, and flexible tools for data analysis. It is an accumulation of lessons learned and experience gained building pandas, a widely used, battle-tested data analysis toolkit for Python. I will give a number of short code demonstrations as a means of illustrating the various points.
Building analytics libraries and research tools for quantitative finance and other fields. Actively involved in data analysis and statistics applications in the scientific Python community. Author of pandas library, contributor to statsmodels. Upcoming author of “Python for Data Analysis” from O’Reilly Media. CEO of Lambda Foundry, Inc.
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