Description
The open-source project, Xarray, combines labeled data structures inspired by Pandas with NumPy-like multi-dimensional arrays to provide an intuitive and scalable interface for scientific analysis. Xarray has strong user bases in the physical sciences and geospatial community. However, new users commonly struggle to fit their dataset into the Xarray model and with conceptualizing and constructing an Xarray object that makes subsequent analysis steps easy (“dataset wrangling”). We take inspiration from the “tidy data” concept for dataframes — “datasets structured to facilitate analysis” (Wickham, 2014) — and attempt a definition of tidy data for labeled array objects provided by Xarray.