missing empty group when iterate over groupby_bins

[miniufo]

When I try to iterate over the object grouped returned by groupby_bins, I found that the empty group is missing silently. Here is a simple case:

array = xr.DataArray(np.arange(4), dims='dim_0')
# one of these bins will be empty
bins = [0,4,5]
grouped = array.groupby_bins('dim_0', bins)

for i, group in enumerate(grouped):
    print(str(i)+'  '+group)

When a bin contains no samples (bin of (4, 5]), the empty group will be dropped. Then how to iterate over the full bins even when some bins contain nothing? I've read this related issue #1019.
But my case here need the correct order in grouped and empty groups need to be iterated over.

[miniufo]

When I use counts = grouped.count(), I can get all the bins and counts in the correct order, and the empty bin just returns nan. But I don't want aggregation operations here. I need the samples in each group to index another array. Maybe this is not the best solution. But my case do need all the groups in the same order as the given bins, including possible empty ones.

[dcherian]

But if there's nothing matching a particular bin, then you have nothing to index the other array?

[dcherian]

Since you know the bins (which are generated with pd.cut), you could use the get_group function in this PR: https://github.com/pydata/xarray/pull/3691/files and catch the KeyError that would be raised.

[miniufo]

Thanks @dcherian. I use the get_group function and solve my problem. But a warning arises at the line if name not in self.groups: as: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.

When the group contains nothing, I may assign nan or 0 to the corresponding bin. If it is dropped silently, then I need to find out which bin is missing its group. I like this PR #1027 by Ryan with a kwarg drop_empty_bins but not sure this option is eventually merged into master or not.