Room 215
Extending pandas with Dask: Do you have too much data to process locally? Do you want tools to probe datasets bigger than your laptop can handle? This workshop, the second in a two-part series on pandas, will introduce participants to Dask Dataframe, a Python library that parallelizes pandas efficient computation and lazy processing. We will explore how Dask Dataframes operates, and use it to reduce large datasets to manageable size. No prior programming experience is required.
Topics covered: pandas, dask
Data Club meetups typically occur twice-monthly, on Thursdays, throughout the semester. Open to everyone in the Columbia community, these informal events will start with a presentation on a specific use case for Python, R, Julia, or JavaScript, then open up to questions, collaborative work, and discussion. Computation typically occurs within a Jupyter/Colab workflow, and participants of all skill levels are welcome.
