This page lists the Gammapy tutorials that are available as Jupyter notebooks.

You can read them here, or execute them using a temporary cloud server in Binder.

To execute them locally, you have to first install Gammapy locally (see Installation) and download the tutorial notebooks and example datasets (see Getting Started). Once Gammapy installed, remember that you can always use gammapy info to check your setup.

Gammapy is a Python package built on Numpy and Astropy, so to use it effectively, you have to learn the basics. Many good free resources are available, e.g. A Whirlwind tour of Python, the Python data science handbook and the Astropy Hands-On Tutorial.


Getting started

The following tutorials show the same 3D cube analysis of the Crab with the high level interface and with the lower level API:

What data can I analyse?


3-dim sky cube analysis

2-dim sky image analysis

1-dim spectral analysis

Time-dependent analysis

Simulations, Sensitivity, Observability

Gammapy package


Examples how to run Gammapy via Python scripts:

Extra topics

These notebooks contain examples on some more specialised functionality in Gammapy.