https://datacarpentry.org/astronomy-python/: Data Carpentry: Foundations of Astronomical Data Science, April 2022

The Foundations of Astronomical Data Science curriculum covers a range of core concepts necessary to efficiently study the ever-growing datasets developed in modern astronomy. In particular, this curriculum teaches learners to perform database operations (SQL queries, joins, filtering) and to create publication-quality data visualisations. Learners will use software packages common to the general and astronomy-specific data science communities (Pandas, Astropy, Astroquery combined with two astronomical datasets: the large, all-sky, multi-dimensional dataset from the Gaia satellite, which measures the positions, motions, and distances of approximately a billion stars in our Milky Way galaxy with unprecedented accuracy and precision; and the Pan-STARRS photometric survey, which precisely measures light output and distribution from many stars. Together, the software and datasets are used to reproduce part of the analysis from the article “Off the beaten path: Gaia reveals GD-1 stars outside of the main stream” by Drs. Adrian M. Price-Whelan and Ana Bonaca. This lesson shows how to identify and visualize the GD-1 stellar stream, which is a globular cluster that has been tidally stretched by the Milky Way.