Notebook Tutorials

These Jupyter Notebook tutorials demonstrate access methods and techniques for working with data served by IRSA. They cover topics like querying IRSA, working with catalogs in Parquet format, and general parallelization techniques. Some of the notebooks are downloadable, others have been rendered and are viewable in a web browser.

Images

• Searching 2MASS Allsky Atlas Images (rendered)
• Searching AllWISE Atlas Images (rendered)
• Searching COSMOS Images (rendered)
• Searching Spitzer Enhanced Imaging Products (rendered)

These notebooks show how to query IRSA's image services, inspect the results, and download and visualize images. They use the tools: PyVO, Astropy.

Catalogs

• AllWISE Source Catalog (downloadable)
• tools: Pandas, PyArrow, Astropy
• shows how to query and load data from a catalog in Apache Parquet format, located in an AWS S3 cloud bucket. This catalog is partitioned by HEALPix order 5 and is available through the AWS Open Data program as part of the NASA Open-Source Science Initiative.
• CosmoDC2 Mock V1 catalogs (rendered)
• tools: PyVO
• shows how to query IRSA's Table Access Protocol (TAP) service

General

• General parallelization techniques (downloadable)
• tools: python multiprocessing, Dask, Ray
• image convolution is used as an example computationally-intensive task