issue_comments

Both NCO and CDO keep all attributes, and as you mention, maintain a history attribute. Even for operations like "variance" where the units are no longer accurate.

Maybe we're headed to a user specified option to keep the attributes around with the default being option 1. I can see this existing at any (but probably not all) of these levels: - module (xray.maintain_attributes=True) - class (keyword in Dataset or DataArray __init__(self, ..., maintain_attributes=True) - method (ds.mean(dim='time', maintain_attributes=True)

This approach would put the onus on the user to specify they want to keep metadata around. My preference would be to apply this at the module level.

A couple more thoughts.

I agree that staying metatdata unaware is the best course of action. However, I think you can do that but still carry the dataset and variable attributes (in the same manor that NCO and CDO do). You just want to be explicit in the documentation by saying that the attributes are from the original dataset and that xray is not attribute aware or a units system (except for the time variable I guess).

I'm willing to take a crack at it but I'm guessing I'll be requesting some assistance along the way. Let me look into a bit and I'll report back with how I see it going together.

I'm not sure we need to worry about the string representation too much. The pandas.Panel has a limited string representation too - example. Then again, I find the pandas pannels difficult to work with. Maybe adding a thorough Dataset.describe() method would suffice.

To flush out some of the desired functionality a bit more: (I'm going to use numpy.mean as an example but any numpy reduction function could be applied) 1. Dataset.mean() returns a new Dataset, with all the variables and attributes from the original Dataset reduced along all dimensions. 2. Dataset.mean(dim='some_dim_name') returns a new Dataset, with all the variables and attributes from the original Dataset reduced along the sum_dim_name dimension. 3. Dataset.mean(dim=['Y', 'X']) returns a new Dataset, with all the variables from the original Dataset reduced along the Y and X dimensions. 4. What to do with the reduced dimensions/variables? Reduced variables (e.g. when the mean is taken along the time dimension) could be a) reduced in the same manner (e.g. leave the time variable in the Dataset and just take the mean of the time array), b) removed, thereby reducing the Dataset's dimensions. I think the cleanest way would be to remove the reduced dimensions/variables (b). 5. Any implementation should play nice with the Dataset.groupby objects (#122).