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[Partner Event] Tips and Tricks for Efficient Data Exploration with Pandas
October 2 @ 6:00 pm - 8:00 pm
NOTE: Please sign-in at the registration area at the entrance. Thank you!
Pandas is a python package dedicated to making data analysis of “relational” data simultaneously fast and easy. Indeed, speed and readability often go hand-in-hand when working in pandas, but it can require a perspective shift away from the standard python for-loop approach to data manipulation. Rather than iterating over a large number of rows, pandas encourages the impatient data explorer to think in terms of “vectorized” operations. While reviewing the practical gains of vectorization, this talk will also offer a conceptual view that highlights how thinking in terms of vectors identifies the fundamental entities of the computation. In vectorizing a range of complex computations, we will also touch upon several additional advanced topics in pandas (e.g. accessors, time-series manipulations, and windowing functions). The speaker will conclude with a quick run-down of some common pitfalls when working with pandas.
About the Speaker – Daniel Little
An academic researcher turned data scientist, Daniel Little is an enthusiastic data explorer. With published research in plant genetics, molecular evolution, and computational neuroscience, he loves discovering the hidden structure underlying complex systems. Now, as a Data Scientist at Shiftgig he’s learning to turn discovery into impact, leveraging data to help connect a talented hourly workforce with the opportunities demanding their skills.
Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs based in Seattle, New York, Chicago, and San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, and more. Students and alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.
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