Aggregations

flox implements all common reductions provided by numpy_groupies in aggregations.py. Control this by passing the func kwarg:

• "sum", "nansum"

• "prod", "nanprod"

• "count" - number of non-NaN elements by group

• "mean", "nanmean"

• "var", "nanvar"

• "std", "nanstd"

• "argmin"

• "argmax"

• "first", "nanfirst"

• "last", "nanlast"

• "median", "nanmedian"

• "mode", "nanmode"

• "quantile", "nanquantile"

Tip

We would like to add support for cumsum, cumprod (issue). Contributions are welcome!

Custom Aggregations

flox also allows you to specify a custom Aggregation (again inspired by dask.dataframe), though this might not be fully functional at the moment. See aggregations.py for examples.

See the “Custom Aggregations” user story for a more user-friendly example.

mean = Aggregation(
    # name used for dask tasks
    name="mean",
    # operation to use for pure-numpy inputs
    numpy="mean",
    # blockwise reduction
    chunk=("sum", "count"),
    # combine intermediate results: sum the sums, sum the counts
    combine=("sum", "sum"),
    # generate final result as sum / count
    finalize=lambda sum_, count: sum_ / count,
    # Used when "reindexing" at combine-time
    fill_value=0,
    # Used when any member of `expected_groups` is not found
    final_fill_value=np.nan,
)