Is it possible to use custom Aggregation over entire ddf/column?

Hi, is it possible to use custom Aggregations across an entire dataframe or column? They work with ddf.groupby(...).agg(...), but pandas also supports df.agg(...) and dask even supports full aggregations with things like ddf.max().

Looking into the code for ddf.max(), it appears to use the undocumented ddf.reduction function (via _reduction_agg), which appears very close (chunk->chunk, agg->aggregate, finalize->combine?), but the parameters aren’t exactly compatible (eg: Aggregation gets SeriesGroupBy objects while .reduction funcs get Series objects; aggregate and combine are supposed to return the same output, etc). I may be able to work around these, but just wondering if this is the right approach. Thanks!

@JacobHayes Welcome to Discourse!

I don’t think this is implemented yet, but it’s a reasonable feature to support.

There is an open feature request for Series here: Suggestion: Series.agg · Issue #3527 · dask/dask · GitHub, but I couldn’t find one for DataFrame. Please feel free to open one or chime in on the Series issue, and let us know if you’d like to work on this!