Next steps: random small tasks

• .labels.get() return an array and labels.get(as_dict=True) return dict
• Add test to compare compute_hs() against SMET file variable snow_height(mod). The results should match
• Add profile_status variable and use it in __repr__()
• Implement Swiss graincode translator to IACS grain type labels & store translation in attributes so that ds['grain_type'].labels.get() results in human-readable grain_types
• Create a callable function to load a sample dataset (during interactive explorations and for docstrings), e.g., ds = xsnow.sample_ds()`