The Data Analysis Pipeline (DAP) provides multiple derived quantities from MaNGA data cubes (e.g., line fluxes, velocities, spectral indices, etc.). A detailed description of the DAP can be found at the MaNGA Data Analysis Pipeline (DAP) documentation page. Here we provide three different tutorials illustrating how to access the DAP output. We highly recommend people use Marvin, a custom Python package designed to easily work with MaNGA data. However, we also provide tutorials for how to access DAP output using standard Python packages and IDL.
Click one of the links below to see a tutorial about how to use the MaNGA Data Analysis Pipeline (DAP) with one of these software environments.