## 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
append: Dict[str, Any] = {}
    append["data"] = []
    append["labels"] = []
    append["days"] = []
    labels_format = "%a. {day} %B"
    days_format = "%Y-%m-%d"
    if interval == "hour" or interval == "minute":
        labels_format += ", %H:%M"
        days_format += " %H:%M:%S"
    for item in dates_filled:
        date = item[0]
        value = item[1]
        append["days"].append(date.strftime(days_format))
        append["labels"].append(date.strftime(labels_format.format(day=date.day)))
        append["data"].append(value)
    if math == "sum":
        append["count"] = sum(append["data"])
    return append
def get_ip_address(request: HttpRequest) -> str:
    """ use requestobject to fetch client machine's IP Address """
    x_forwarded_for = request.META.get("HTTP_X_FORWARDED_FOR")
    if x_forwarded_for:
        ip = x_forwarded_for.split(",")[0]
    else:
        ip = request.META.get("REMOTE_ADDR")  
    return ip
def dict_from_cursor_fetchall(cursor):