## 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
self.assertEqual(sum(response[0]["data"]), 1)
        self.assertEqual(response[0]["breakdown_value"], "second url")
        # 
        with freeze_time("2020-01-05T13:01:01Z"):
            response = Trends().run(
                Filter(
                    data={
                        "date_from": "-14d",
                        "breakdown": "$current_url",
                        "events": [
                            {
                                "id": "sign up",
                                "name": "sign up",
                                "type": "events",
                                "order": 0,
                                "properties": [{"key": "$os", "value": "Mac"}],
                            }
                        ],
                        "properties": {
                            "type": "AND",
                            "values": [{"key": "$browser", "value": "Firefox"}, {"key": "$os", "value": "Windows"}],
                        },
                    }
                ),
                self.team,
            )
        response = sorted(response, key=lambda x: x["label"])
        self.assertEqual(response, [])
    @test_with_materialized_columns(["$some_property"])
    def test_dau_with_breakdown_filtering(self):