Tables are frequently used to communicate information–from sports analytics, to research papers, and company dashboards. However, to make professional looking tables, Python users often have to copy their data manually into tools like excel.
Great Tables enables you to create beautiful, publication ready tables directly in Python.
It works with DataFrame libraries like Polars and Pandas.
In this talk, we’ll cover the basics of making publication-ready tables:
- Using Great Tables with Polars DataFrames.
- The basics of structuring, formatting, and styling tables.
- Advanced features like nanoplots, heatmaps, and interactivity.
Basic knowledge of Python and data analysis are assumed. No experience with Polars needed!
Featured Presenter: Michael Chow – Software Engineer, Open Source at Posit
Michael is data science tool builder at Posit, where he work on open source tools for data analysis. Previously, he worked as a consultant building out a data team for Caltrans (and love all things GTFS).
He received a Ph.D. in Cognitive Psychology from Princeton University, and is interested in what drives expert data science performance.
