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How to use pandas the wrong way

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Title How to use pandas the wrong way
Title of Series EuroPython 2017
Author Battiston, Pietro
License CC Attribution - NonCommercial - ShareAlike 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this license.
DOI 10.5446/33784
Publisher EuroPython
Release Date 2017
Language English

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Subject Area Information technology
Abstract How to use pandas the wrong way [EuroPython 2017 - Talk - 2017-07-12 - Anfiteatro 1] [Rimini, Italy] UPDATE: slides and materials can be found at http://pietrobattiston.it/python:pycon#europython rimini july 2017 The pandas library represents a very efficient and convenient tool for data manipulation, but sometimes hides unexpected pitfalls which can arise in various and sometimes unintelligible ways. By briefly referring to some aspects of the implementation, I will review specific situations in which a change of approach can make code based on pandas more robust, or more performant. Some examples: inefficient indexing multiple dtypes and efficiency implicit type casting HDF5 storage overhead GroupBy.apply()... when you don't actually need i

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