If you do data science in Python it is crucial to be fluent with the Pandas library.
Furthermore, because of the typical workflow for data loading, it is likely that your data will be held in a Pandas DataFrame. In this live coding session Robert Hardy will show how a little bit of time spent getting familiar with the humbler Pandas Series can pay dividends. Yes DataFrames are more generic, but the core concepts like filtering, indexing, reshaping, comparing and merging can be appreciated more clearly with the Series container. A better understanding of and fluency with the Series container will have an immediate and positive impact on your ability to use DataFrames in a Pandastic way.
Robert Hardy is a full stack quant, with over 12 years of experience in the front office teams of major financial institutions. He has built professional portfolio management systems entirely from open source components. He experienced an epiphany when he was introduced to TDD, pair programming and Agile methods. Robert talks and blogs on topics related to software and mathematics, and with his diploma in painting and ceramics in hand he claims to even have some level of expertise in the Fine Arts.