This talk will introduce the Scipp library, originally developed for neutron science experiments, and how it can be useful for record-based "tabular"/"event" data in general.

One of Scipp's key features is the possibility of binning to sort record-based data into arrays of bins. This provides fast and flexible binning, rebinning, and filtering operations, all while preserving the original individual records.

If your use case requires one or several of the items on the following list, using Scipp may be worth considering:

• Physical units are stored with each data or coord array and are handled in arithmetic operations.
• Histograms, i.e., bin-edge axes, which are by 1 longer than the data extent.
• Support for non-regular or scattered data and non-destructive binning.
• Support for masks stored with data.
• Propagation of uncertainties.
• Internals written in C++ for better performance (for certain applications), in combination with Python bindings.

In the talk we will cover:

• Why units are important? What's the current landscape? (5 mins)
• Labeled dimensions, Units (in Scipp) and data structures in scipp (5 mins)
• Bins, Histograms and Uncertainties in Scipp (10 mins)
• Tips and tricks of multi dimensional data handling (5 mins)
• Buffer and Q/A (5 mins)