Class ValueCounts

dask/dataframe/dask_expr/_reductions.py:1405–1474

class ValueCounts(ReductionConstantDim):
    _defaults = {
        "sort": None,
        "ascending": False,
        "dropna": True,
        "normalize": False,
        "split_every": None,
        "split_out": 1,
        "total_length": None,
    }

    _parameters = [
        "frame",
        "sort",
        "ascending",
        "dropna",
        "normalize",
        "split_every",
        "split_out",
        "total_length",
    ]
    reduction_chunk = M.value_counts
    reduction_aggregate = methods.value_counts_aggregate
    reduction_combine = methods.value_counts_combine
    split_by = None

    @functools.cached_property
    def _meta(self):
        return self.frame._meta.value_counts(normalize=self.normalize)

    @classmethod
    def aggregate(cls, inputs, **kwargs):
        func = cls.reduction_aggregate or cls.reduction_chunk
        if is_scalar(inputs[-1]):
            return func(_concat(inputs[:-1]), inputs[-1], observed=True, **kwargs)
        else:
            return func(_concat(inputs), observed=True, **kwargs)

    @property
    def shuffle_by_index(self):
        return True

    @property
    def chunk_kwargs(self):
        return {"sort": self.sort, "ascending": self.ascending, "dropna": self.dropna}

    @property
    def aggregate_args(self):
        if self.normalize and (self.split_out > 1 or self.split_out is True):
            return [self.total_length]
        return []

    @property
    def aggregate_kwargs(self):
        return {**self.chunk_kwargs, "normalize": self.normalize}

    @property
    def combine_kwargs(self):