## 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/trends/sql.py
GROUP BY {aggregator}, date
) GROUP BY date
"""
VOLUME_PER_ACTOR_AGGREGATE_SQL = """
SELECT {aggregate_operation} as data FROM (
    SELECT COUNT(*) AS intermediate_count, {aggregator}
    FROM ({event_query})
    GROUP BY {aggregator}
) events
"""
SESSION_DURATION_SQL = """
SELECT {aggregate_operation} as data, date FROM (
    SELECT {interval}(toTimeZone(toDateTime(timestamp, 'UTC'), %(timezone)s) {start_of_week_fix}) as date, any(session_duration) as session_duration
    FROM ({event_query})
    GROUP BY $session_id, date
) GROUP BY date
"""
SESSION_DURATION_AGGREGATE_SQL = """
SELECT {aggregate_operation} as data FROM (
    SELECT any(session_duration) as session_duration FROM ({event_query}) events GROUP BY $session_id
)
"""
ACTIVE_USERS_SQL = """
SELECT counts AS total, timestamp AS day_start FROM (
    SELECT d.timestamp, COUNT(DISTINCT {aggregator}) AS counts FROM (
        /* We generate a table of periods to match events against. This has to be synthesized from `numbers`
           and not `events`, because we cannot rely on there being an event for each period (this assumption previously
           caused active user counts to be off for sparse events). */
        SELECT {interval}(toDateTime(%(date_to)s, %(timezone)s) - {interval_func}(number) {start_of_week_fix}) AS timestamp
        FROM numbers(dateDiff(%(interval)s, {interval}(toDateTime(%(date_from_active_users_adjusted)s, %(timezone)s) {start_of_week_fix}), toDateTime(%(date_to)s, %(timezone)s)))