## Bug description

Monthly Active Users metric seems wrong when choosing "# Number" as chart type.

Number: 
![image](https://user-images.githubusercontent.com/513669/201980874-be7d9c0d-5c9c-4c1e-955c-ea4143c84061.png)

Line chart: 
![image](https://user-images.githubusercontent.com/513669/201980986-b17af929-84e5-4f6a-b7f8-23b7ac8bedbc.png)

**490 != 70**

## How to reproduce

1. Create a new insight using any event and the "Monthly active users" metric
2. Date range = This month + Grouped by = Day
3. Choose chart type as Number => remember value
4. Change chart type as Linear => check last data point

=> the 2 values do not match
=> in other words there's a diff between a total aggregation and an aggregation per bucket of time ?

## Environment

- [x] PostHog Cloud
posthog/queries/test/test_trends.py
from posthog.models.instance_setting import get_instance_setting, override_instance_config, set_instance_setting
from posthog.models.person.util import create_person_distinct_id
from posthog.queries.trends.trends import Trends
from posthog.test.base import (
    APIBaseTest,
    ClickhouseTestMixin,
    _create_event,
    _create_person,
    flush_persons_and_events,
    snapshot_clickhouse_queries,
    test_with_materialized_columns,
)
from posthog.test.test_journeys import journeys_for
from posthog.utils import generate_cache_key
def breakdown_label(entity: Entity, value: Union[str, int]) -> Dict[str, Optional[Union[str, int]]]:
    ret_dict: Dict[str, Optional[Union[str, int]]] = {}
    if not value or not isinstance(value, str) or "cohort_" not in value:
        label = value if (value or type(value) == bool) and value != "None" and value != "nan" else "Other"
        ret_dict["label"] = f"{entity.name} - {label}"
        ret_dict["breakdown_value"] = label
    else:
        if value == "cohort_all":
            ret_dict["label"] = f"{entity.name} - all users"
            ret_dict["breakdown_value"] = "all"
        else:
            cohort = Cohort.objects.get(pk=value.replace("cohort_", ""))
            ret_dict["label"] = f"{entity.name} - {cohort.name}"
            ret_dict["breakdown_value"] = cohort.pk
    return ret_dict
def _create_action(**kwargs):