## 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/breakdown.py
)
            else:
                breakdown_value, _ = get_property_string_expr("events", breakdown, "%(key)s", "properties")
        if self.filter.using_histogram:
            breakdown_value = f"toFloat64OrNull(toString({breakdown_value}))"
        breakdown_value = normalize_url_breakdown(breakdown_value, self.filter.breakdown_normalize_url)
        return breakdown_value
    def _get_histogram_breakdown_values(self, raw_breakdown_value: str, buckets: List[int]):
        multi_if_conditionals = []
        values_arr = []
        if len(buckets) == 1:
            
            
            buckets = [buckets[0], buckets[0]]
        for i in range(len(buckets) - 1):
            last_bucket = i == len(buckets) - 2
            
            
            lower_bound = buckets[i]
            upper_bound = buckets[i + 1] + 0.01 if last_bucket else buckets[i + 1]
            multi_if_conditionals.append(
                f"{raw_breakdown_value} >= {lower_bound} AND {raw_breakdown_value} < {upper_bound}"
            )
            bucket_value = f"[{lower_bound},{upper_bound}]"
            multi_if_conditionals.append(f"'{bucket_value}'")
            values_arr.append(bucket_value)
        
        multi_if_conditionals.append(f"""'["",""]'""")
        return f"multiIf({','.join(multi_if_conditionals)})", values_arr
    def breakdown_sort_function(self, value):