## 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
team = kwargs.pop("team")
    name = kwargs.pop("name")
    properties = kwargs.pop("properties", {})
    action = Action.objects.create(team=team, name=name)
    ActionStep.objects.create(action=action, event=name, properties=properties)
    return action
def _create_cohort(**kwargs):
    team = kwargs.pop("team")
    name = kwargs.pop("name")
    groups = kwargs.pop("groups")
    cohort = Cohort.objects.create(team=team, name=name, groups=groups, last_calculation=timezone.now())
    return cohort
class TestTrends(ClickhouseTestMixin, APIBaseTest):
    maxDiff = None
    def _get_trend_people(self, filter: Filter, entity: Entity):
        data = filter.to_dict()
        
        if data.get("events", None):
            data["events"] = json.dumps(data["events"])
        if data.get("properties", None):
            data["properties"] = json.dumps(data["properties"])
        with self.settings(DEBUG=True):
            response = self.client.get(
                f"/api/projects/{self.team.id}/persons/trends/",
                data={**data, ENTITY_TYPE: entity.type, ENTITY_ID: entity.id},
                content_type="application/json",
            ).json()
        return response["results"][0]["people"]
    def _create_events(self, use_time=False) -> Tuple[Action, Person]: