issue_comments: 670971584

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https://github.com/pydata/xarray/issues/1050#issuecomment-670971584 https://api.github.com/repos/pydata/xarray/issues/1050 670971584 MDEyOklzc3VlQ29tbWVudDY3MDk3MTU4NA== 8833517 2020-08-08T20:39:11Z 2020-08-08T20:39:11Z CONTRIBUTOR

In core/nanops.py there are some explicit defaults of ddof=0 within xarray, but I'm not sure if those are always used or if there are also cases where var (or std) are directly passed on to numpy/bottleneck/dask.

I'm considering two different options to clarify this:

  1. Add a docstring section on the ddof parameter specifying it uses ddof=0 as default for the reduction methods that use it, i.e. var and std. Possibly just copied from numpy's var page.
  2. Refer to numpy's documentation page in the docstring of all reduction methods for further reference.

Both would require some logic in core/ops.py: either to check for which reduce methods need a ddof paragraph, or to create the proper url (which has to adjust min and max to np.amin and np.amax respectively)

Is there any clear preference from anyone about this?

 
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