python - Efficient loop through two Pandas DataFrames -

i have 2 pandas dataframes:

the first frame contains timestamp (date + time) , 4 sets of lat/long pairs define corners of box on earth.

the second frame contains timestamp , 1 lat/long pair marks event.

i want find out, each event, whether fell inside of 'boxes on earth', , if so, ones , delta_t between timestamps.

the way can think of doing loop through second frame, row row, , compare first frame. i'm hoping more pythonic way, nothing coming mind. ideas?

thanks,

i think work. pseudo codish. need 0.11-dev

both frames have a datetime index, first one, b shorter has events.

on a, set index column, a['date'] = a.index

on b, set index column, b['date'] = b.index

inner join , b, ffill on b

c = a.join(b).ffill()

then want boolean logic if event included, like:

c['is_included'] = (c['a_lat'] > c['b_lat']) & (c['a_long'] > c['b_long'])...etc

so when is_included true, want differential time previous event

set non-selected events nan on original date column of b

c['date_b'][~c['is_included']] = np.nan

forward fill date_b's again

c['date_b'] = c['date_b'].ffill()

if subtract date_b date_a think have timedelta

c['delta'] = c['date_b']-c['date_a']

then

c[c['is_included']] answer, , delta timedelta

Bready