## 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
sign_up_action = self._create_maths_events(values)
        action_response = Trends().run(
            Filter(
                data={"actions": [{"id": sign_up_action.id, "math": math_property, "math_property": "some_number"}]}
            ),
            self.team,
        )
        event_response = Trends().run(
            Filter(data={"events": [{"id": "sign up", "math": math_property, "math_property": "some_number"}]}),
            self.team,
        )
        # 
        self.assertAlmostEqual(action_response[0]["data"][-1], expected_value, delta=0.5)
        self.assertEntityResponseEqual(action_response, event_response)
    @test_with_materialized_columns(["some_number"])
    def test_sum_filtering(self):
        self._test_math_property_aggregation("sum", values=[2, 3, 5.5, 7.5], expected_value=18)
    @test_with_materialized_columns(["some_number"])
    def test_avg_filtering(self):
        self._test_math_property_aggregation("avg", values=[2, 3, 5.5, 7.5], expected_value=4.5)
    @test_with_materialized_columns(["some_number"])
    def test_min_filtering(self):
        self._test_math_property_aggregation("min", values=[2, 3, 5.5, 7.5], expected_value=2)
    @test_with_materialized_columns(["some_number"])
    def test_max_filtering(self):
        self._test_math_property_aggregation("max", values=[2, 3, 5.5, 7.5], expected_value=7.5)
    @test_with_materialized_columns(["some_number"])
    def test_median_filtering(self):