## 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
_create_person(team_id=self.team.pk, distinct_ids=["person_1"], properties={"name": "John"})
        _create_person(team_id=self.team.pk, distinct_ids=["person_2"], properties={"name": "Jane"})
        _create_event(event="event_name", team=self.team, distinct_id="person_1")
        _create_event(event="event_name", team=self.team, distinct_id="person_2")
        _create_event(event="event_name", team=self.team, distinct_id="person_2")
        cohort = _create_cohort(
            team=self.team,
            name="cohort1",
            groups=[{"properties": [{"key": "name", "value": "Jane", "type": "person"}]}],
        )
        cohort.calculate_people_ch(pending_version=0)
        with self.settings(USE_PRECALCULATED_CH_COHORT_PEOPLE=True):
            response = Trends().run(
                Filter(
                    data={
                        "events": [{"id": "event_name"}],
                        "properties": [{"type": "cohort", "key": "id", "value": cohort.pk}],
                    },
                    team=self.team,
                ),
                self.team,
            )
        self.assertEqual(response[0]["count"], 2)
        self.assertEqual(response[0]["data"][-1], 2)
    def test_breakdown_filter_by_precalculated_cohort(self):