Your gateway to the universe's data treasures - curated Jupyter notebooks from MAST that transform raw space telescope observations into discoverable insights across JWST, TESS, and beyond.

Every photon captured by humanity’s greatest space observatories tells a story, but extracting those cosmic narratives from raw astronomical data requires the right tools and techniques. The Mikulski Archive for Space Telescopes (MAST) houses petabytes of observations from missions like the James Webb Space Telescope, TESS, and Hubble, yet navigating this treasure trove can be daunting for both seasoned astronomers and emerging researchers.

This curated collection of Jupyter notebooks serves as your personal guide through MAST’s vast archives, offering mission-specific workflows that demonstrate best practices for data access, analysis, and visualization. Each notebook is meticulously organized by mission or service, complete with supplemental files and clean folder structures that keep your research workflow tidy. From querying PanSTARRS catalogs to processing JWST spectroscopic data, these notebooks bridge the gap between raw observations and scientific discovery, with automated testing ensuring reliability across the ecosystem.

Whether you’re hunting exoplanets in TESS light curves, analyzing galaxy evolution with HST mosaics, or exploring the infrared universe through JWST’s revolutionary instruments, these notebooks provide production-ready code that accelerates your path from data to publication. The open-source nature and contribution guidelines ensure this knowledge base evolves with the astronomical community’s needs.

⭐ Stars: 25
💻 Language: Jupyter Notebook
🔗 Repository: spacetelescope/mast_notebooks