## 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
data={
                            "date_from": "-14d",
                            "breakdown": "$some_numerical_prop",
                            "events": [
                                {"id": "sign up", "name": "sign up", "type": "events", "order": 0,},
                                {"id": "no events"},
                            ],
                        }
                    ),
                    self.team,
                )
            self.assertEqual(response[0]["label"], "sign up - Other")
            self.assertEqual(response[0]["count"], 4.0)
            self.assertEqual(response[1]["label"], "sign up - 80.0")
            self.assertEqual(response[1]["count"], 1.0)
        def test_breakdown_filtering_limit(self):
            self._create_breakdown_events()
            with freeze_time("2020-01-04T13:01:01Z"):
                response = trends().run(
                    Filter(
                        data={
                            "date_from": "-14d",
                            "breakdown": "$some_property",
                            "events": [{"id": "sign up", "name": "sign up", "type": "events", "order": 0,}],
                        }
                    ),
                    self.team,
                )
            self.assertEqual(len(response), 20)
        def test_action_filtering(self):