Tutorials - Matt Harrison: Getting Started with Polars Published 2023-06-02 Download video MP4 360p Recommendations 29:49 Thomas Bierhance: Polars - make the switch to lightning-fast dataframes 2:17:33 Tutorials - Reuven M. Lerner: Comprehending comprehensions 47:07 From Pandas to Production: Best Practices for using "Effective Pandas" with Matt Harrison 57:18 EuroSciPy 2023 - Keynote: Polars 1:29:00 Effective Pandas I Matt Harrison I PyData Salt Lake City Meetup 14:12 Polars: The Next Big Python Data Science Library... written in RUST? 48:57 OPENING KEYNOTE Code Europe 2023 Tech Festival - "Idiomatic Pandas" by Matt Harrison (MetaSnake) 27:45 What polars does for you — Ritchie Vink 45:42 Talks - Hynek Schlawack: Subclassing, Composition, Python, and You 1:00:27 Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby) 11:30 25 Nooby Pandas Coding Mistakes You Should NEVER make. 31:32 Polars - An Introduction to Polars v1 for Python Data Analytics! 20:31 Polars: A highly optimized dataframe library | Matt Harrison | Conf42 Machine Learning 2023 38:15 Juan Luis- Expressive and fast dataframes in Python with polars | PyData NYC 2022 2:24:16 Tutorial: Idiomatic Pandas by Matt Harrison 2:55:29 Tutorials - Ted Patrick: Writing Serverless Python Web Apps with PyScript Similar videos 02:50 How to Master Pandas with Matt Harrison 22:47 Learning Polars for Data Analysis? Start Here! 15:05 1) Polars Tutorial - Basic operations, select and filter 29:37 Introduction to Polars: A Python Library for Data Analysis and Visualization 05:42 Introducing lazy mode and query optimisation in Polars 27:52 Polars Tutorial: Aggregate and Analytic Functions (Group By, Dynamic Group By, Rolling Averages) 00:20 Effortless Data Filtering in Python with Polars: Mastering DataFrame Operations 04:28 Learn Pandas the right way: great pandas book 21:46 Polars is the Pandas killer / Igor Mintz (Viz.ai) 02:04 Working with larger-than-memory datasets with Polars 18:39 Polars: The Super Fast Dataframe Library for Python ... bye bye Pandas? More results