## 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
filter = Filter(
            {
                "date_from": "2020-01-01T00:00:00Z",
                "date_to": "2020-01-12T00:00:00Z",
                "events": [{"id": "$pageview", "type": "events", "order": 0}],
                "properties": [
                    {"key": "industry", "value": "finance", "type": "group", "group_type_index": 0},
                    {"key": "key", "value": "value", "type": "person"},
                ],
            },
            team=self.team,
        )
        response = Trends().run(filter, self.team)
        self.assertEqual(response[0]["count"], 1)
    @test_with_materialized_columns(
        person_properties=["key"], group_properties=[(0, "industry")], materialize_only_with_person_on_events=True
    )
    @snapshot_clickhouse_queries
    def test_breakdown_by_group_props_with_person_filter_person_on_events(self):
        self._create_groups()
        Person.objects.create(team_id=self.team.pk, distinct_ids=["person1"], properties={"key": "value"})
        _create_event(
            event="sign up",
            distinct_id="person1",
            team=self.team,
            properties={"$group_0": "org:5"},
            timestamp="2020-01-02T12:00:00Z",
            person_properties={"key": "value"},
            group0_properties={"industry": "finance"},
        )