## Is your feature request related to a problem?

There's only 2 files where we use pandas, but pandas is 49MB and numpy is another 86MB, slowing down builds massively.

## Describe the solution you'd like

Replace pandas with a pure SQL/Python solution in
- posthog/queries/trends.py
- posthog/queries/sessions.py

Both of those have equivalent examples in Clickhouse (ee/clickhouse) that don't use Pandas.

## Describe alternatives you've considered

Continue using Pandas and clogging builds

## Additional context



#### *Thank you* for your feature request – we love each and every one!

posthog/queries/test/test_trends.py
team=self.team, event="sign up", distinct_id="blabla", properties={"$math_prop": 4},
                )
                event_factory(
                    team=self.team, event="sign up", distinct_id="blabla", properties={"$math_prop": 4},
                )
            with freeze_time("2020-01-04T13:00:01Z"):
                daily_response = trends().run(
                    Filter(
                        data={
                            "display": TRENDS_TABLE,
                            "interval": "week",
                            "events": [{"id": "sign up", "math": "median", "math_property": "$math_prop"}],
                        }
                    ),
                    self.team,
                )
            with freeze_time("2020-01-04T13:00:01Z"):
                weekly_response = trends().run(
                    Filter(
                        data={
                            "display": TRENDS_TABLE,
                            "interval": "day",
                            "events": [{"id": "sign up", "math": "median", "math_property": "$math_prop"}],
                        }
                    ),
                    self.team,
                )
            self.assertEqual(daily_response[0]["aggregated_value"], 2.0)
            self.assertEqual(daily_response[0]["aggregated_value"], weekly_response[0]["aggregated_value"])
        def test_trends_breakdown_single_aggregate_cohorts(self):