52:45 Xarray - more than Pandas in multiple dimensions - Ondřej Grover [PyData Prague #8 2020] PyData
34:06 Itamar Turner-Trauring: Small Big Data: using NumPy and Pandas when your data... | PyData NYC 2019 PyData
38:30 Diego Torres Quintanilla: Cleaning, optimizing and windowing pandas with numba | PyData NYC 2019 PyData
1:20:44 Marc Garcia, Jeff Reback, Tom Augspurger: Introduction to pandas | PyData New York City 2019 PyData
36:49 Li Jin, Hyonjee Joo: Spark Backend for Ibis: Seamless Transition Between Pandas... | PyData NYC 2019 PyData
1:24:08 Ian Ozsvald: A gentle introduction to Pandas timeseries and Seaborn | PyData London 2019 PyData
25:07 Diederik Greveling: Building a Multi-Core Apply Function for Pandas | PyData Amsterdam 2019 PyData
28:43 Learning to Scale Data Science, Machine Learning, and Pandas with Ray and Modin - Devin Petersohn PyData
24:16 Li Jin - Improving Pandas and PySpark performance and interoperability with Apache Arrow PyData
48:08 PyData Tel Aviv Meetup: Creating Meaningful Features from Clickstream Data - Shir Meir Lador PyData
32:46 J. Henry Hinnefeld | High Frequency Trading in MMORPG Markets using Luigi, Pandas, and Scikit learn PyData
22:21 Jessica Forde: Visualizing Wireless Router Timeseries Data with the Density API, Seaborn, and Pandas PyData
41:08 Jeffrey Tratner: Pandas Under The Hood: Peeking behind the scenes of a high performance data analys PyData