## Bug description

When calculating Trends results with an aggregated (e.g. single output, like big number) display type, WAU/MAU don't work. This is because we have an `ACTIVE_USERS_SQL` query for time series display types, but we don't have a version of this for aggregated display types. (See ZEN-1043.)

## How to reproduce

1. Create an insight with a single WAU or MAU series.
2. Switch display type to "Number".
3. Open the "Debug ClickHouse queries" modal from the command palette.
4. See `COUNT(*)` instead of `COUNT(DISTINCT person_id)`.

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posthog/queries/breakdown_props.py
elif breakdown_type == "group":
        value_expression, _ = get_property_string_expr(
            table="events" if direct_on_events else "groups",
            property_name=cast(str, breakdown),
            var="%(key)s",
            column=f"group{breakdown_group_type_index}_properties"
            if direct_on_events
            else f"group_properties_{breakdown_group_type_index}",
            materialised_table_column=f"group{breakdown_group_type_index}_properties"
            if direct_on_events
            else "group_properties",
        )
    else:
        value_expression = get_single_or_multi_property_string_expr(
            breakdown, table="events", query_alias=None, column="properties", normalize_url=breakdown_normalize_url
        )
    if cast_as_float:
        value_expression = f"toFloat64OrNull(toString({value_expression}))"
    return f"{value_expression} AS value"
def _to_bucketing_expression(bin_count: int) -> str:
    if bin_count <= 1:
        qunatile_expression = "quantiles(0,1)(value)"
    else:
        quantiles = []
        bin_size = 1.0 / bin_count
        for i in range(bin_count + 1):
            quantiles.append(i * bin_size)
        qunatile_expression = f"quantiles({','.join([f'{quantile:.2f}' for quantile in quantiles])})(value)"
    return f"arrayCompact(arrayMap(x -> floor(x, 2), {qunatile_expression}))"
def _format_all_query(team: Team, filter: Filter, **kwargs) -> Tuple[str, Dict]: