Matthew Long
Matthew Long
cc @andersy005 and @erogluorhan from NCAR.
I think this approach has a lot in common with what we do in intake-esm—which is essentially based on a pandas dataframe. We used to store this in a csv...
It should be relatively easy to return the nested dictionary. A couple other ideas include enabling an `aggregate=False` option, which would return each of the individual datasets and a `get_keys()`...
It would return a dataset for each row in the database. We could form keys from the groupby applied to all columns, but maybe it would be more accessible if...
Agreed, that's a bug, but easy to fix. Without `aggregation_control` the code forms groups over all columns: ```python groups = self.df.groupby(self.df.columns.tolist()) ``` and the returned keys will be of the...
I think it may be relatively easy to implement a `preprocess` argument to `to_dataset_dict` that would accept a function that operates on the individual datasets as they are opened (could...
@jbusecke, @rabernat, Does #155 provide enough functionality to address this issue?
TEMP is the POP variable name for potential temperature (not THETA). Many of the data not available on glade are available on HPSS [HSI]: /CCSM/csm/CESM-CAM5-BGC-LE/ocn/proc/tseries/monthly And (possibly) on NCAR Campaign...
I am fine with dependencies as long as they are good ones.
@alperaltuntas, what if we "unfix time" and use the resample on the float time-axis, then "refix time" to compute the monthly climatology?