issue_comments

What may be possible: extend @_plot2d with a projection=None and a transform=None keyword (and the handling thereof)*. In geoplot we import @_plot2d set the defaults to projection=ccrs.PlateCaree() and transform=ccrs.PlateCaree(), possibly intercept coastlines from kwargs. I don't know if it is possible to update the defaults without explicitly re-writing the call signature of the function (which may change (but this could possibly be tested)).

* This may conflict with the current ax = plt.gca().

We would need to think hard about how to extend the current implementation without needing to duplicate it.

Do you think it would be enough to expose the @_plot2d decorator?

Yes is is possible to say subplot_kws=dict(projection=ccrs.PlateCaree(). For a single plot it is not possible to specify the projection (as ax=plt.gca()) in the current implementation. Thus one has to create and pass a geoaxes explicitly.

I like the idea of doing data.geoplot.pcolormesh() - We could keep the standard name of the plotting function without the need to make up our own. - It is possibly easier to extend it to contour and contourf. - We can possibly offer more control over specific cartopy features (although adding coasts is possibly the one thing that we will be able to agree on).

Some questions: - Would it also offer data.geoplot.line ect.? There is no point but this would be consistent might be asked for. - We would need to think hard about how to extend the current implementation without needing to duplicate it.

I'm pretty sure it's possible to add cartopy axes to a FacetGrid using the subplot_kwds argument already. Unfortunately, I don't have any examples handy since I wrote that code at my last job.

What this code does is add the projection=ccrs.PlateCarree() automatically, along with a few other geo specific niceties. I made that suggestion for cartopy itself (https://github.com/SciTools/cartopy/issues/645) but it hasn't been acted on yet.

I agree that this is a good fit for xarray because the plotting API is difficult to extend externally. One nice way to present this to users could be to make a geoplot accessor that works like the current plot accessor but adds these geo specific options. Then you could write, e.g., data.geoplot.pcolormesh().

I also agree that this is a not to intrusive and useful "geo-specific" addition. Without looking at the implementation, I also wonder if it would be possible to add the same functionality to the existing framework without adding a specific function? The background is that there are other ways than pcolormesh to plot on a map (see also https://github.com/pydata/xarray/issues/657)

I was trying to avoid getting too much geo-specific functionality in xarray, but this does nicely extend the existing plotting methods, so I think this is a reasonable addition. Anyone else have opinions on this one?

These are the plots from above.