Caltech/IPAC–IRSA Python Notebook Tutorials#
These Python Jupyter Notebook tutorials demonstrate access methods and techniques for working with data served by the NASA/IPAC Infrared Science Archive (IRSA). They cover topics like querying IRSA, working with catalogs in Parquet format, visualizing with Firefly, and general other techniques.
Accessing IRSA’s on-premises holdings using VO protocols#
Accessing IRSA’s cloud holdings#
These notebooks demonstrate how to access the IRSA-curated datasets that available in Amazon Web Services (AWS) S3 cloud storage buckets.
- IRSA cloud access introduction
- Analyzing cloud-hosted AllWISE Source Catalog in Parquet format
- Strategies to Efficiently Work with NEOWISE Single-exposure Source Table in Parquet
- Make Light Curves from NEOWISE Single-exposure Source Table
- Analyzing cloud-hosted simulated Roman Time Domain Survey images
- Analyzing cloud-hosted simulated Roman coadded images
Interactive visualization in Python with Firefly#
These notebooks demonstrate how to use the Firefly visualization tools from Python. Firefly is an open-source toolkit based on IVOA standards and designed to enable astronomical data archive access, exploratory data analysis, and visualization.
It is used in archive user interfaces at IRSA, the NASA Exoplanet Science Institute (NExScI), the NASA/IPAC Extragalactic Database (NED), and the Vera C. Rubin Observatory.
Generally useful techniques#
These notebooks cover miscellaneous topics that users might find useful in their analysis of IRSA-curated data.