## 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/utils.py
from django.db import connection
    query = (
        f'SELECT pg_size_pretty(pg_total_relation_size(relid)) AS "size" '
        f"FROM pg_catalog.pg_statio_user_tables "
        f"WHERE relname = '{table_name}'"
    )
    cursor = connection.cursor()
    cursor.execute(query)
    return dict_from_cursor_fetchall(cursor)
def get_table_approx_count(table_name):
    from django.db import connection
    query = f"SELECT reltuples::BIGINT as \"approx_count\" FROM pg_class WHERE relname = '{table_name}'"
    cursor = connection.cursor()
    cursor.execute(query)
    return dict_from_cursor_fetchall(cursor)
def is_postgres_alive() -> bool:
    from posthog.models import User
    try:
        User.objects.count()
        return True
    except DatabaseError:
        return False
def is_redis_alive() -> bool:
    try:
        get_redis_info()
        return True
    except BaseException:
        return False
def is_celery_alive() -> bool: