Currently, it is slightly tedious to create new datasets based on existing ones. This requires you to use the copy method.
For example, if you wanted to create a new dataset so that you could plot the spatial average of a dataset, you would have to do this:
`ds1 = ds.copy()`
`ds.spatial_mean()`
`ds1.plot()`
This is one step too many. Methods currently modify datasets in place. What's needed is a way to return a new dataset with an inplace arg similar to what happens in pandas. So the above would become:
`ds1 = ds.spatial_mean(inplace = False)`
`ds1.plot()`
Currently, it is slightly tedious to create new datasets based on existing ones. This requires you to use the
copymethod.For example, if you wanted to create a new dataset so that you could plot the spatial average of a dataset, you would have to do this:
This is one step too many. Methods currently modify datasets in place. What's needed is a way to return a new dataset with an inplace arg similar to what happens in pandas. So the above would become: