Numpy to xarray docs

We should make a docs page specifically to ease the transition from pure-numpy to xarray.

A lot of new xarray users come from already using numpy as their primary data structure. We relatively often get questions about "what's the xarray equivalent of X numpy function" but we don't have a dedicated place to collect those answers, or explain key conceptual differences.

I think this deserves its own dedicated docs page, with:

• High-level conceptual differences (e.g. transpose invariance)
• Arguments for the benefits of using xarray over pure numpy
• Table of numpy <-> xarray function equivalents (similar to the existing "How do I..." page)
• Other common recommendations for numpy users (e.g. use netCDF / Zarr instead of .npz or pickle to store data on disk)

For the table I thought of a few already, but I know there will be a lot more:

• np.concatenate/np.vstack/np.hstack/np.stack → xr.concat
• np.block → xr.combine_nested
• np.apply_along_axis → xr.apply_ufunc
• np.polynomial → xr.polyfit
• np.reshape -> xr.coarsen().construct()

Start by locating the existing "How do I..." documentation page and reviewing how it presents function equivalents. Create a dedicated NumPy-to-xarray page covering the listed conceptual differences, benefits, equivalent functions, and storage recommendations, with the requested mappings included.